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Text follows. ____ tS ____ University Microfilms International THE ROLE OF RURAL DEV EL OP ME NT AND FARMERS' PREFERENCES IN CH ANGING THE VI AB IL IT Y AND SPATIAL DISTRIBUTIONS OF CENTR AL VILLAGES By Fatemeh Behforooz A DIS SERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Ge ography 1985 © Co pyright by Fatemeh Behforooz 1985 ABSTRACT THE ROLE OF RURAL DEV EL OPM ENT AND FARMERS' PREFERENCES IN CHANGING THE V I A BI LI TY AND SPATIAL DISTRIBUTIONS OF CE NTR AL VILLAGES By Fatemeh Behforooz This study identifies the pr ocesses of change in the functional viability and spatial d i s t r ib ut io n of different sizes of population and functions of central villages in southcentral Michigan in the periods 1980, according to rural development, shopping preferences. 1950-1970 and 1970and rural families' The app lic ati on of revised central place theory aids causal explanations of change functions and patterns of central vi llages temporal and probabilistic framework. in the in a spatial, The majority of previous central place studies have focused on the whole urban/rural system of central places wi th ou t concentrated study of the central villages of a region. Therefore, the major findings of this research com pl em en t previous central place studies, particularly in light of the scarcity of studies on the central villages, future central place studies. and will be useful for The recommenda tio ns of this Fatemeh Behforooz study for reallocations of central for future regional planning functions may be helpful in southcentral Michigan. The findings of this research support the existence of the rank/size rule and hierarchical structure of central places among the central villages studied of three points of the study time. The spatial di st ribution of central v i l ­ lages was random in the first period of the study and tended toward dispersion in the second period. This implies that change in the functional viability of different classes of central villages causes changes distribution. spatial The influences of rural development and farm and nonfarm families' central in the villages' preference for shopping in larger places were found to encourage the growth of larger central villages and the considerable decline of smaller ones. The rea llocation (polarization) tions with their greater ranges villages seems inevitable, of high order func ­ in high order central while the retention of low order functions with smaller ranges will characterize the small or lower order villages. The continuous decline of farm families and increase of nonfarm families in southcentral Mic hig an will continue to promote noticeable decline of smaller central villages and more po la rizaton of central functions places. in higher order central villages or urban central To My Teachers And To * \ My Family Acknowledgements I wish to express my greatest thanks to the guidance co mmittee of my doctoral program who kindly and co ns t r u c ­ tively c ri ti ci zed my research problems and advised me in' w r i t i n g this dissertation. Professor Ian M. Matley I am deeply indebted to (the Chairman of the Committee) fam il iarized me with the concepts of rural graphy and the general methodological analytical empirical study. settlement g e o ­ procedures in an His consistent concern and his keen ap proach to my disse rt at io n was essential and co mp l e t i n g this work. who in writing I am truly proud to have been his student and I extend my sincere gratitude and my best wishes to him and his family. It is my privilege also to express my sincere a p p re ci at io n to Professor Gary Manson person of the Ge ography Department) (the C h a i r ­ who has been c o n s i s ­ tently c o n ce rn ed for the progress of this dissertation. advice on general methodology, the rural nonfa rm families, has been vital grateful His field surveying and including as well as the farm population, in the structure of this research. I am also to him for subsidizing the computer time necessary for this research. I am very grateful Jac ob so n for his advice on the temporal iv to Professor Daniel framework of this study and on agricultural and rural development concepts and policies in the United States. Bruce Wm. I am indebted to Professor Pigozzi for his sincere concern and vital guidance on the basic structure of this research. His constructive advice on applying central place theory and its revision in this dissertation and his guidance on all of the qu an t i t a ­ tive procedures were essential I am truly grateful and sincerely appreciated. for his admirable patience, re sponsibility and advice on my dissertation. concern, My gratitude also goes to Professor Richard Groop for his guidance and patient assistance on the data cla ss ifi ca tio n methods in geography. In conducting the field survey, the farm and nonfarm families of southcentral Michigan who were interviewed were very helpful and generous in giving their time and in­ formation to the research. Therefore, I am delighted to thank them very kindly for their time and concern in answering the questions. I am also grateful to the local persons and officials who filled out the public q u e s t i o n ­ naires related to central villages. Ms. Anne Kellogg d e ­ serves sincere thanks for her help during the field survey and thanks is also extended to Mrs. Mr. Stephanie Sambrook and Richard Sambrook for their great effort and assistance on the cartographic works of this dissertation. my honor to thank my very dear friend, Ms. It is also Kay J. Kay, for her consistent en cou ra ge me nt and her sincere concern in editing my dissertation. Fellowships awarded by the University of Tehran and the Ministry of Science and Higher Educa tio n in Iran for the two years of 1978-1980 we r e very helpful and I am very thankful to them. The warm en co ur age men t of the professors in the geography department of the University of Tehran were of great moral support in my doctoral program at Michigan State University. The endless support and love of my father, Behforooz, my dear son, Kasra, Behforooz and his wife Mrs. Mr. Abass my brother Mr. Bijan Mary Behforooz and my aunt, Dr. Azar Behforooz have given me great support and encouragement during my student life in the United States. grateful to all of them. I am truly I would also like to extend my gratitude for the concer n and encouragement of my dear mother, Mrs. Zahrah Razavi, and my brother, my stepfather, Mr. Ners i Razavi. I should also like to honor the memory of my beloved uncle, Former Professor Emeritus of Tehran, Mrs. Dr. Ahmad Behforooz, in Mathematics at the University and share my concern and caring for his widow, Gitie Behforooz, Behforooz, Dr. Ahmad Razavi, Dr. Dr. Mohamma- Sohilah jamilah Behforooz. Our family sincerely honors his memc vi r. TABLE OF CONTENTS Page List of T a b l e s .............................................. List of F i g u r e s ............................................. CHAPTER I: CO NC E P T U AL FRAMEWORK AND LITERATURE R E V I E W ......... Purpose of the S t u d y ................................. The Conte nt of the C h a p t e r s ......................... An Introduction to the Settlement G e o g r a p h y ...... Li terature R e v i e w .................................... Components of Central Place T h e o r y ................ U n i f o r m i t y ....................................... Ge ometric Arrangements and the Concept of R a n g e ......................................... Hie rarchy or Rank Size R u l e ................... Dynamic O r i e n t a t i o n .................................. Consumers' Shopping B e h a v i o r ....................... CHAPTER II: PROBLEM AND RESEARCH D E S I G N ............... Problem S t a t e m e n t .................................... H y p o t h e s e s ............................................. P r o c e d u r e s ............................................. Study Area and Study T i m e ..................... Data S o u r c e s .................................... General D a t a ............................... Sample Villages for Field S u r v e y ....... Sampled Rural Functions (Goods and Services) Maps, Diagrams, Tables and G r a p h s ............ Data C ol le cti on and A n a l y s i s .................. L i m i t a t i o n s ............................................ Significance of the S t u d y ........................... CHAPTER III: RURAL DEVELOPMENT IN SOUTHCENTRAL M I C H I G A N ......................................... 1 1 3 7 9 18 18 19 22 27 36 48 48 50 58 58 69 69 72 76 84 85 87 88 91 Establ is hm en t of Early Rural S e t t l e m e n t s ......... 91 Agricultural M e c h a n i z a t i o n .......................... 94 S p e c i a l i z a t i o n ........................................ 99 Farm C o n s o l i d a t i o n .................................... 103 Gross Farm I n c o m e ..................................... 108 vii C H A P T E R III: Cont The Evolution of Transportation and Highway Development in Southcentral M i c h i g a n ............... Ill The Effects of Rural Development in Changing the Pattern and Cha racteristics of the Rural P o p u l a t i o n ............................................. 121 CH APT E R IV: SOCIOECONOMIC MODELING OF CENTRAL VILLAGES: FUNCTIONAL AND S T R U C T U R A L ............................133 Functional M o d e l i n g ...................................133 Structural M o d e l i n g ...................................146 Continuous Models of Population and Function R e l a t i o n s h i p .......................... 146 Discontinuous Models of Population and Function Relat ionship (Hierarchical)......... 161 C H AP TE R V: THE ROLE OF RURAL DEVELOPMENT IN CHANGING THE VIAB IL IT Y AND S PATIAL DISTRIBUTION OF CENTRAL V I L L A G E S ................................................172. Change in the Number and Distribution of Central V i l l a g e s ...................................... 172 Functional V ia bi lit y of Different Classes of Central Villages in the Process of C h a n g e ........ .176 General P e r s p e c t i v e ............................. 176 General Change in the Central Functions and Rural Services of Central V i l l a g e s ...... 182 Functional Changes of First Order V i l l a g e s ..194 Functional Changes of Second Order V i l l a g e s . 205 Functional Changes of Third Order V i l l a g e s ..211 Functional Changes of Fourth Order Vi l l a g e s . 216 Functional Changes of Fifth Order V i l l a g e s ..222 Functional Changes of Sixth Order V i l l a g e s ..227 Spatial Dis tribution of Different Classes of Central Villages in a Process of C h a n g e ........... 233 Spatial M o d e l i n g ............................ ,...233 Regional Development and Spatial C o m p o n e n t s .241 CH AP T E R VI: A SOCIOECONOMIC ANALYSIS ON FARMERS' PREFERENCES IN ESTABLISHING THE BEHAVIORAL RANGE FOR CENTRA L VILLAGES' GOODS AND S E R V I C E S .......... 244 Range of Goods and S e r v i c e s ......................... P r o c e d u r e .............................................. Sampled Goods and S e r v i c e s .......................... Sixth Order Village F u n c t i o n s ......... viii 244 245 252 254 CHAPTER VI: Cont. Third Order V U lage F u n c t i o n s ....................... 266 Second Order <^il lage F u n c t i o n s ...................... 277 First Order Vil lage F u n c t i o n s ....................... 287 Town and Cjfty Level F u n c t i o n s ....................... 297 General Findings of Factors Influencing the Shoppi ng Models of Rural F a m i l i e s .................. 313 C HA PTE R VII: TIONS SUMMARY, CONCLUSIONS AND FUTURE S P EC UL A­ 321 AP PENDICES App en d ix A: Tables A.l to A . 8 ...................... 341 App en d ix B: Sur vey Q u e s t i o n n a i r e s ................. 403 Ap pe nd ix C: Tables C.l to C . 2 0 ..................... 410 B I B L I O G R A P H Y ................................................. 430 ix LIST OF TABLES Table 2.1 2.2 2.3 2.4 3.1 3.2 3.3 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 Page Population of Central Villages in 1980 and Their Z V a l u e s ............................... Central Villages Ordered by Their Functional Indices, 1 9 8 0 ....................................... 73 Ranks and Classes of Rural Functions (goods and services) in the Order of Their Locati on C o e f f i c i e n t s ........................................ 78 Ranges of Rural Functions' Locatio n Coefficients and the Sample Functions Drawn From Each Range. 83 Number and Percentages of Work Animals and Tractors on Farms in 16 Counties of Southcentral Michigan, 1 9 5 0 ............................ 95 Average Number of Live st ock per Farm and P e r ­ centages of Farms Raising Li vestock in 16 Counties of Southcentral Michigan for 1950, 1969, 1 9 7 8 ........................... Patterns of Population in the Counties of Southcentral Mi chi gan in 1950, 1970, and 1980 Showing Percent Change for 1950-1970 and 19701 9 8 0 .................................................. 117 A Hypothetical Model of Functional Index C l a s s i f i c a t i o n ...................................... 135 Hierarchical Order of Central Villages in 1 9 5 0 .................................................. 139 Hierarchical Order of Central Villages in 1 9 7 0 .................................................. 140 Hierarchical Order of Central Villages in 1 9 8 0 ............................... Central Villages' Order According to Their Functional Viabi lit y in 1950, 1970 and 1980....145 Threshold Population for Sampled Functions (village level) for 1950, 1970 and 1 9 8 0 ........... 155 Threshold Population for Sampled Functions (township level) for 1950, 1970 and 1980 ......... 156 Some Services Offered in the Central Villages of Southcentral Michigan, 1950, 1970, 1 9 8 0 ....... 158 Relationship Between the Population Size of Central Villages and Their Numbers of Functions in Regard to Different Hierarchical Classes: 1950, 1970, 198 0 / .................................. 168 x 64 100 141 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5 ..9 5.10 5.11 5.12 5.13 5.14 5.15 5.16 5.17 5.18 5.19 5.20 Numbers, Proportions and Percent Change in Proportions of Central Villages over the Study T i m e .................................................. 173 Change in Number and Functional Hierarchical Order of Central Villages: 1 9 5 0 - 1 9 7 0 ............ 175 Change in Number and Functional Hierarchical Order of Central Villages: 1 9 7 0 - 1 9 8 0 ............ 175 Major Ch aracteristics of Di fferent Classes of Central Villages Studied, for 1950, 1970 and 1 9 8 0 .................................................. 178 Average Number of Est ablishments (Total Functional Units) or Per Class of Central Villages and Their Rates of Change Over the Study P e r i o d s ........................................ 180 Central Functions Offered in Central Villages in 1950 that Had Disappeared by 1 9 7 0 ............ 185 Selected Central Functions That Increased or Emerged in the Central Villages Over the Study T i m e .................................................. 186 Selected Central Functions Found to Have Declined in the Central Villages Over the Study T i m e ........................................... 189 Functional Units of Rural Services, Including Professions, in Central Villages: 1970-1980.... 192 Selected Central Functions that Declined in the Central Villages by Average Value per Class for 1950,1970 and 1 9 8 0 ............................. 196 Selected Central Functions that Essentially Disappeared from the Central Vi llages after 1950, by Average Number of Total Establishments Per Class of Central Villages for 1 9 5 0 ........... 197 Selected Central Functions that Either Emerged or Increased in the Central Villages, by Av e r ­ age Value per Class of Central Villages for 1950, 1970 and 1 9 8 0 ................................ 200 Typical Central Functions Offere d in First Order Villages: 1950, 1970 and 1 9 8 0 ..............201 Typical Central Functions Ava il ab le in Second Order Villages: 1950, 1970 and 1 9 8 0 ............. 207 Typical Central Functions Ava ilable in Third Order Villages: 1950, 197.0 and 1 9 8 0 ............. 212 Typical Central Functions Ava ilable in Fourth Order Villages: 1950, 1970 and 1 9 8 0 ............. 218 Typical Central Functions Ava ilable in Fifth Order Villages: 1950, 1970 and 1 9 8 0 ............. 224 Typical Central Functions Ava ilable in Sixth Order Villages: 1950, 1970 and 1 9 8 0 . . . . ......... 230 Typical Rural Services Av ailable in Central Villages in 1970 and 1 9 8 0 ......................... 231 Spatial Di st ribution of Central Villages: 1950, 1970 and 1 9 8 0 ................................ 237 xi 6 . 1.1 6 . 1.2 6.2 6.3 6.3.1 6.4.1 6.4.2 A. 1 A.2 A.3 A. 4 A.5 A. 6 A.7 A. 8 C.l C .2 C .3 C .4 A Pilot Pattern for a Chi-square Test: Examining the Association Between The Age of Farmers and their Selection of a Grocery Store in a Certain Central P l a c e ................ 249 A Pilot Pattern of Factors Related to Farmers' Selection of Grocery Stores in Central P l a c e s ..................................... 250 Distribution of Functional Units (N) and Average Number of Sampled Functions in Central Villages: 1 9 8 0 ............................255 Farmers and N o n f a r m e r s 1 Travel Mileage for Sampled Functions, by Descriptive Statistical V a l u e s ...............................................258 Percent of Outsho pping and Inshopping by Rural Families for the Sampled F u n c t i o n s ..............259 Factors Related to Farm Families' Shopping Travel Models of Sampled Functions: Cramer's V and P h i - C o e f f i c i e n t ............................. 261 Factors Related to Nonfarm Families' Shopping Travel Models of Sampled Functions: Cramer's V and P h i - C o e f f i c i e n t ............................. 262 Central Functions, Location Coefficients and Functional Indices of Central Villages, 1950..341 Central Functions, Location Coefficients and Functional Indices of Central Villages, 1970..356 Central Functions, Location Coefficients and Functional Indices of Central Villages, 1980..372 Services Offered in the Central Villages of Southcentral Michigan, 1 9 5 0 ..................... 390 Services Offered in the Central Villages of Southcentral Michigan, 1 9 7 0 ......... '........... 393 Services Offered in the Central Villages of Southcentral Michigan, 1 9 8 0 ..................... 397 Other Services Offered in Central Villages, Southcentral Michigan, 1 9 7 0 ..................... 401 Other Services Offered in Central Villages, Southcentral Michigan, 1 9 8 0 ..................... 402 Factors Related to Farmer Families' Selection of Groce ry Stores in a Particular Central Place (A Chi-Square T e s t ) ............................... 410 Factors Related to Farmer Families' Selection of Opt ome tri st in a Particular Central Place (A Chi-Square T e s t ) ............................... 411 Factors Related to Farmer Families' Selection of Clinics in a Particular Central Place (A Chi-Square T e s t ) ............................... 412 Factors Related to Farmer Families' Selection of Floor Coverin g Store in a Particular C e n ­ tral Place (A Chi-Square T e s t ) ................... 413 xii C.5 C.6 C.7 C.8 C.9 C.10 C.ll C.12 C.13 C.14 C.15 C.16 C.17 C.18 C.19 C.20 Factors Related to Farmer Families' Selection of Jewelry Stores in a Particular Central Place (A Ch i-Square T e s t ) ......................... 414 Factors Related to Farmer Families' Selection of Paint and Wallpaper Store in a Particular Central Place (A Chi-Square T e s t ) ................ 415 Factors Related to Farmer Families' Selection of De partment Store in a Particular Central Place (A Chi-Squ are T e s t ) ......................... 416 Factors Related to Farmer Families' Selection of Family Cl othing Store in a Particular C e n ­ tral Place (A Chi-Square T e s t ) ................... 417 Factors Related to Farmer Families' Selection of Au tomotive Dealer in a Particular Central Place (A Chi-Squ are T e s t ) ......................... 418 Factors Related to Farmer Families' Selection of Shoe Store in a Particular Central Place (A Ch i-Square T e s t ) ................................ 419 Factors Related to Nonfarmer Families' Selection of Grocery Store in a Particular Central Place (A Ch i-Square T e s t ) ................................ 420 Factors Related to Nonfarm Families' Selection of Op tom et ris t in a Certain Central Place (A C hi-Square T e s t ) .................................... 421 Factors Related to Nonfarm Families' Selection of Clinics in a Certain Central Place (A ChiSquare T e s t ) .........................................422 Factors Related to Nonfarm Families' Selection of Floor Covering Store in a Certain Central Place (A Chi-Square T e s t ) ......................... 423 Factors Related to Nonfarm Families' Selection of Jewelry Store in a Particular Central Place (A Ch i-Square T e s t ) ................................ 424 Factors Related to Nonfarm Families' Selection of Paint and Wallpaper Store in a Certain C e n ­ tral place (A Chi-Square T e s t ) ................... 425 Factors Related to Nonfarm Families' Selection of De partment Store in a Certain Central Place (A Ch i-Square T e s t ) ................................ 426 Factors Relate d to Nonfarm Families' Selection of Family Clo thing Store in a Certain Central Place (A Chi-Squ are T e s t ) ......................... 427 Factors Related to Nonfar m Families' Selection of Autom ot iv e Dealers in a Certain Central Place (A Chi-Square T e s t ) ..................... ,...428 Factors Related to Nonfarm Families' Selection of Shoe Store in a Certain Central Place (A Chi-Square T e s t ) .................................... 429 xiii LIST OF FIGURES Figure 2.1 2.2 2.3 2.4 2.5 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 Page Types of Farming Areas: M i c h i g a n ................. 59 Coun ty Divisions in the Study A r e a ............... 61 Relative Lo cation of Central Villages of Southcentral Michigan on the County Division Patterns, 1 9 8 0 ................................................... 62 Townships That Surround the Central Villages of the Study A r e a ....................................... 63 The Relative Location of Central Villages of Southcentral Michigan on the Highway Patterns of the Study Area, 19 8 0 ............................ 68 Po pulation of Horses and Colts by Counties; and Their Distribution by Average and P e r c e n ­ tage Values in 16 Counties of Southcentral Michigan: 1950, 1969, 1 9 7 8 ......................... 96 Popula ti on of Wheel Tractors by Counties; and Their Dis tribution by Average and Percentage Values in 16 Counties of Southcentral Michigan 1950, 1969, 1 9 7 8 . . ....... 96 Popula ti on of Cornpickers by Counties: and Their Distri bu tio n by Average and Percentage Value in 16 Counties of Southcentral Michigan, 1950, 1969, 1 9 7 8 ..................................... 98 Po pulation of Motor Trucks by Counties; and Their Dis tribution by Average and Percentage Values in 16 Counties of Southcentral Michigan, 1950, 1969, 1 9 7 8 . . , .................................. 98 Total Number of Farms by County; and Their Average Values in 16 Counties of Southcentral Michigan: 1950, 1969, 1 9 7 8 ......................... 104 Average Size of Farms (Acres) by Counties; and Their Mean Values in 16 Counties of Southcentral Michigan: 1950, 1969, 1 9 7 8 ............... 104 Percent Values of Farm Ownership Types in Co mpa ris on with the Average Size of Farms in Sixteen Counties of Southcentral Michigan in 1950, 1969 and 1 9 7 8 ................................. 107 Farm Products' Sales per Farm (Dollars); and Their General Average Values in 16 Counties of Southcentral Michigan: 1950, 1969, 1 9 7 8 ...... 109 Po pulation of Automobiles by Counties; and Their Distribution by Average and Percentage in 16 Counties of Southcentral Michigan: 1950, 1969 and 1978 . ...................................... 115 xiv 3.10 The E st ab l ish me nt and Development of the Inter­ state Highwa y System in the State of Michigan and the Study R e g i o n .................................119 3.11 Total Population, Urban Population and Rural Population of Sixte en Counties of Southcentral M ichi gan in 1950, 1970 and 1 9 8 0 ................... 123 3.12 The Po pulation of Central Villages and Their Surrounding Townships At Three Points in T i m e ... 125-127 3.13 Total Acres of Land in Farms by Counties; and Their Average Values in 16 Counties of Southcentral Michigan: 1950, 1969, 1 9 7 8 ............... 128 4.1 Spatial Di str i bu ti o n of Different Classes of Central Vil lages Studied in 1 9 5 0 ......... 142 4.2 Spatial Di str i bu ti o n of Different Classes of Central Villages Studied in 1 9 7 0 .......... 143 4.3 Spatial Di str i bu ti o n of Different Classes of Central Vil lages Studied in 1 9 8 0 ......... 144 4.4 The Continuous Linear Relationship Between The Central Villages' Functional Range (Number of Functions) and Their Population Size at Three Points of T i m e ........................................ 149 4.5 The Continuous Linear Relationship Between Functional Range (Number of Functions Offered in Central Villages) and Population Served (Population of Townships) at Three Points of T i m e ....................................................151 4.6 A Discontinuous Model of Linear Relationship Between Number of F unctions and Population Size of Each Class of Central Villages in 1950..163 4.7 A Discontinuous Model of Linear Relationship Between Number of Functions and Population Size of Each Class of Central Villages in 1970..164 4.8 A Discontinuous Model of Linear Re la tionship Betw ee n Number of Functions and Po pulation Size of Each Class of Central Villages in 1 9 8 0 ....... 165 5.0 The General Patte rn of Central Villages in the Study Area and Their Relative Lo cation Against The Super H i g hw a y Network: 1950, 1970, 1 9 8 0 ....... 238 6.1.1 The Key Settlements of Urban and Rural Centers for Shopping or Vis iti ng Travel Models of Farm Families Sampled: 1983 ............................. 246 6.1.2 The Key Settlements of Urban and Rural Centers for Shopping or Vis it in g Travel Models of N o n ­ farm Families Sampled: 1983 ....................... 247 6.1.3 A Pilot Patter n of Chi-Square Probabi li ty Scale for Grocery F u n c t i o n ............................... 251 6.2.1 Shopping Travel Model of Farm Families Sampled for Groce ry S t o r e s ..................................256 6.2.2 Shopping Travel Model of Nonfarm Families Sampled for Grocer y S t o r e s ..................................256 6.2.3 Factors Relat ed to Farmers' Selection of Grocery Stores in Ce rta in Central P l a c e s .............. ...260 xv 6.2.4 Factors Related to Nonfarmers' Selection of Grocery Stores in Certai n Central P l a c e s ........260 6.3.1 Vi siting Travel Model of Farm Families Sampled for O p t o m e t r i s t ..................................... 269 6.3.2 Visiting Travel Model of No nfa rm Families Sam ­ pled for O p t o m e t r i s t ............................... 269 6.3.3 Factors Related to Farmers' Selection of Op to m­ etrists in Ce rta in Central P l a c e s ................ 270 6.3.4 Factors Related to N o n f a r m e r s ' Selection of Optometrists in Certa in Central P l a c e s .......... 270 6.4.1 Visiti ng Travel Model of Farm Families Sampled for C l i n i c ........................................... 274 6.4.2 Visiting Travel Model of Nonfa rm Families Sampled for C l i n i c ........ 274 6.4.3 Factors Relatd to Farmers' Selection of Clinics in Certain Central P l a c e s ......................... 275 6.4.4 Factors Relatd to N o nf ar m Families Selection of Clinics in C er ta in Central... P l a c e s .............. 275 6.5.1 Shopping Travel Model of Farm Families Sampled for Floor Cov ering S t o r e .......................... 279 6.5.2 Shopping Travel Model of No nfa rm Families Sampled for Floor Cov eri ng S t o r e .......................... 279 6.5.3 Factors Related to Farmers' Selection of Floor Covering Stores in Certai n Central P l a c e s ...... 280 6.5.4 Factors Related to Nonfarmers' Selection of Floor Covering Stores in Certai n Central P l a c e s ...... 280 6.6.1 Shopping Travel Model of Farm Families Sampled for Jewelry S t o r e ................................... 283 6.6.2 Shopping Travel Model of Nonfa rm Families Sampled for Jewelry S t o r e ................................... 283 6.6.3 Factors Related to Farmers' Selection of Jewelry Stores in Certai n Central P l a c e s ................ 285 6.6.4 Factors Related to Nonfarmers' Selection of Jewelry Stores in Certa in Central P l a c e s ....... 285 6.7.1 Shopping Travel Model of Farm Families' Sampled for Paint and Wall pa pe r S t o r e .....................288 6.7.2 Shopping Travel Model of Nonfar m Families Sampled for Paint and Wallp ape r S t o r e .....................288 6.7.3 Factors Related to Farmers' Selection of Paint and Wall pap er Stores in Certai n Central P l a c e s . 290 6.7.4 Factors Related to Nonfarmers' Selection of Paint and W al lpa pe r Stores in Certain Central P l a c e s ................................................ 290 6.8.1 Shopping Travel Model of Farm Families for De ­ partment S t o r e ...................................... 294 6.8.2 Shopping Travel Model of Nonfar m Families Sampled for Department S t o r e ............................. ..294 6.8.3 Factors Related to Farmers' Selection of D e pa rt ­ ment Stores in Certain Central P l a c e s ............ 295 6.8.4 Factors Related to Nonfarmers' Selection of D e ­ partment Stores in Certain Central P l a c e s ........ 295 xv i 6.9.1 Shopping Travel Model of Farm Families Sampled for Family Clothing S t o r e ...........................299 6.9.2 Shopping Travel Model of No nfa rm Families Sampled for Family Clothing S t o r e ...........................299 6.9.3 Factors Related to Farmers' Selec tio n of Family Clothing Stores in Certain Central P l a c e s ........300 6.9.4 Factors Related to N o n f a r m e r s ' Selec tio n of Family Clothing Stores in Certa in Central P l a c e s .............................. 300 6.10.1 Shopping Travel Model of Farm Families Sampled for Automotive D e a l e r .............................. 305 6.10.2 Shopping Travel Model of Nonfa rm Families Sampled for Automotive D e a l e r ..................... 305 6.10.3 Factors Related to Farmers' Sele ct io n of A u t o ­ motive Dealers in Certain Central P l a c e s ........306 6.10.4 Factors Related to Nonfarmers' Se lection of Automotive Dealers in Certain Central P l a c e s . . . 306 6.11.1 Shopping Travel Model of Farm Families Sampled for Shoe S t o r e ...................................... 310 6.11.2 Shopping Travel Model of No nfa rm Families Sampled for Shoe S t o r e ............................. 310 6.11.3 Factors Related to Farmers' Se lection of Shoe Stores in Certain Central P l a c e s . . . . ............ 311 6.11.4 Factors Related to Nonfarmers' Selec tio n of Shoe Stores in Certain Central P l a c e s ........... 311 xvii CHAPTER ONE C ONC EP TUA L FRAMEWORK AND LITER AT URE REVIEW Purpose Of The Study This study was done to analyze changes tional viabi lit y in the fu n c ­ (retail and wh olesale trade and services) and spatial d is tr ibu ti on of different sized central villages in southcentral Mi ch ig an and to explain the causes of such changes over the 1950-1980 period, of revised central place theory. theory, with its temporal objectives, was useful through the application Revised central place and probabilistic (humanistic) for resolving the problem of this res earch in an explana to ry framework. Classical central place theory Losch, 1939) (Christaller, with its static and deterministic assumptions have been mo dified in vi e w of homogen ei ty regions 1933 and (Brush, 1953; Janelle, 1968) in socioeconomic and a deterministic hexagonal patte rn of marketing or distance minimization (Berry and Garrison, 1958; Davies, 1967; and Rowley, 1971). The result is a revised central place theory that takes account the causal into factors that change the viability of c e n ­ tral places of a reg io n over any given period of study (Bracey, 1956; Brush, 1953; allows for probabil ist ic Golledge, 1971; 1973; 1966; Pacione, 1981 and Hall, 1965; implications Rushton and Clark, Burnett, Gross, Hodge, 1983). Smith, (Murdie, Davies, and 1965; 1969; 1975; Williams, 1970) Rushton, 1979; Brooker- This theory has been developed to explain the impact of regional development and economic growth over time and the impact of individual peculiarities and choices of shopping behavior in changing the viability and spatial di st ri b u t i o n of central functions or central places of a study area. The hierarchical Garrison, 1967; 1958; Bracey, O'Farrell, 1969; size relationships 1962; Hodge, and Marshall, 1970; 1969) 1965; (Berry and Davies, or their rank 1963; O'Farrell, 1969; Carter, and Johansen and Fuguitt, 1979, are a signifi ca nt component of classical and revised central place theory. ture 1956, (Stafford, Stafford and Gilbert, 1984) structure of central places (Pahl, 1980) 1964; The changes of hierarchical noted in Lewis, 1979 and McGranahan, and/or rank size relationships 1979 and 1984) were hypo t h es iz ed struc­ (Johansen and Fuguitt, in the study area,did not negate the presence of hierarchical structure and rank size relationship study time. O'Farrell, useful of central Functional 1969; villages at three points index data classing Marshall, (Davies, 1969 and Bennison, 1978) in the 1967; was in determi ni ng and comparing the functional changes of the different classes and sizes of selected villages a temporal framework. The threshold population for in 3 selected central functions and Johansen and Fuguitt, (Berry and Garrison, 1984) 1958; at different points in time was determined to dis ti ng ui sh w h eth er certain f u n c ­ tions belonged to high or low order central villages, lages. The distribution of central villages in the study re ­ gion and their interrelationships provides the spatial c o m ­ ponent of this study. E x a m ina ti on of their developmental patterns over certain periods of time 1980) (1950-1970 and 1970- provides the temporal or dynamic aspects, and inves­ tigation of the shopping patterns and preferences of farm and nonfarm families, who live in areas surrounding the v i l ­ lages, provides the behavioral co mponent of the study. The Content Of The Chapters Chapter One is devoted to re viewing classical central place theory and its revisions. This chapter is important in shaping the deductive hypotheses that appear in the second chapter. In Chapter Two, presented. theses the research desig n and procedure are A statement of the problem, in their theoretical overview of the study area central Michigan) 1980: 1950-1970, chapter. delineation of hy p o ­ and empirical dimensions, (46 central villages and study time and period 1970-1980) Data sources, and an in south- (1950, 1970, provide an introduction to this methods of analysis, and the field 4 survey que stionnaires are presented, ale for selecting eighteen villages as well as the ra ti o n ­ for field surveying and the rationale for selecting ten central functions that are inserted in the farm and nonfarm family questionnaires providing behavioral (thus interpretation to determine a h u m a n i s ­ tic range for a certain function). and graphs are described. Maps, diagrams, tables, A brief general outline provides the meth od olo gy used to classify the functional vi ability of central villages, tern of spatial the method used to measure the point p a t ­ distribution of di fferent classes of central villages classes (nearest neighbor analysis) and ju s t i fi ca ­ tion for using the chi-square test to cluster the factors influencing the selection of a certain good at a particular central place. The limitations and significance of the study are p r e se nt ed in concluding this chapter. Chapter Three focuses on agricultural develop me nt mechanization, sp ecialization and consolidation) port development portation) (rail, highway, (farm and t r a n s ­ and truck-oriented tr ans ­ in 16 counties of southcentral Michigan. It also demonstrates how the consequences of rural development created specialized demand for modern agricultural logy, consistent wi t h higher farm income, changes (due to rural development) te ch n o ­ and demographic in the spatial d i s t r i ­ bution of p op ul at io n in the study region over the study period. The increase of nonfarm po pulation in no n­ me tr opolitan aras and farm depop ul at io n in relation to rural 5 dev elopment in the region is explained. This chapter is a prese nt at io n of overall rural development in the study area over the study time. It provides essential data for Chapter Five w h i ch deals wi t h changes in the viability and spatial distr ib ut io n of central villages as a consequence of rural development. Chapter Four deals with socioeconomic modeling of c e n ­ tral villages tions. in functional and structural pr es e n t a ­ To facilitate a comparative theoretical v i s u a l ­ ization of the functional vi ability of central villages, they have been classified in their hierarchical groupings for 1950, 1970, and 1980. This classification is useful in de mo ns tr at in g the growth or decline of the classes of c e n ­ tral villages. In explaining the structural models for these villages, continuous and discontinuous models size rule and hierarchical models are helpful grouping) (rank have been used. These in predicting the population required for a certa in function or for a certain class of villages. Functional and structural modeling of central villages have been essential for explanations in Chapters Five and Six. Chapter Five focuses on the viability and spatial d i s ­ tribution of central village classifications and 1980. in 1950, 1970, Ex pl anations of the role of rural development in ch anging the functions of central villages and their frequency of di st ribution over the periods of 1950-1970 and 1970-1980 are provided. The disappearance of old functions 6 and the emergence of new rural lages are discussed. in the central v i l ­ The spatial di st ribution of different classes of central villages pattern functions in regard to their standardized (using neares t neighbor analysis) time has been modele d and explained. over the study Indeed, their relative location is disc us se d in re lation to the network of super highways in the region. Chapter Six explains the as so ciation between the hy p o ­ thesized factors (s u b j e c t i v e s , objectives, characteristics) relative to farmers' tions of certain functions come, age, mobility, and individual and nonfarmers' in a certa in central farm size, se le c­ place. In­ and types of f a r m i n g ... e t c ., are tabulated on the ch i-square probability scale figures that resulted from this discussion. havior of farmers and nonfarmers The shopping choice b e ­ in the villages surveyed is representative of the range of each function in this region that is created by spatial choice behavior. This chapter shows the influence of individual preferences in changing the viability and spatial d i str ib uti on of central villages and is helpful in identifying the patronization of central villages and their functions. In Chapter Seven, the results of this research are re ­ viewed to identify non-viable villages and the problems volved in their survival in com petitive space. tral villages are also determined, tial for po la rization in­ Viable c en ­ along with their p o t e n ­ (economies of scale) of higher order 7 functions. In light of the research results, some specu la ­ tions are made about the future development of the central villages studied. An Introduction To Settlement Geography Settlement studies are considered a part of human geo ­ graphy line, (Garner, 1968:303). involves several tural, social, subfields political, (Broek and Webb, Human geography, including economic, historical 1978:2). (man as the subject) perience The study of human geography may that relates to subjective ex ­ approach that is objective a determi ned factor), straints a humanistic ap ­ (with man as the active and determining factor) a structural ject, cu l ­ and urban geography be approached from two basic frameworks: proach as a d i s c i p ­ (with man as an ob­ and relates to social c o n ­ (P. Jackson and S. Smith, 1984:8-12). Thus, be argued that among the subfields of human geography, tural and social geography are structural or holistic passive approach, studies) and such as Sauer's cultural it can cul­ (a landscape and economic geography with its behavioral aspects is interested in process and application approach). (an active Both have made important contributions to set­ tlement geography. As Jordan notes "settlement geography stands as a sep­ arate field withi n the discipline, on a plane with 8 population or economic geography." settlement geography, from a structural (subjective) (1966:26). like human geography, (objective) standpoint. Therefore, can be studied or an individualistic In rural settlement literature the two major trends are clearly distinguishable. One is made up of followers of von Thunen and Weber or contributors to location theory (po sitivism), wi th later revision in the 1 light of behavioral geography. The other approach is structural and is characte ri st ic of the work of Meitzen (1895), Vidal (1926), Brunhes (1952) and Demangeon (1920, 1927), whose works have inspired and stimulated later settlement geography studies. Their major contributions to settlement geography discuss the historical, social, and other words, economic components of rural they examine the origin (morphological features of rural including architectural settlements. (historical of human occupation and ex pansion of rural form cultural, In sequences settlements); settlements, styles and distributional patterns of rural dwellings and farmsteads and land use patterns of fields and rural r o a d s ) ; and function (types of land use 1 Spatial human behavior with its positivist fou nd a­ tions, and humanistic components is ranged against the structural approaches in social and cultural studies (Ley, 1981:249-257; Couclelis and Golledge, 1983:331-339). and kinds of farming that represent rural activities) of rural settlements. agroeconomic These notions have stimu­ lated later contributors such as Lefevre (1945), (1925, and Clout 1945), Kohn (1954), Stone (1965), Sauer (1972), whose studies are va luable sources of tradition in the ideas and methodology of modern and contemporary settlement geography. Their idiographic methodologies and concepts, however, are mos tl y descriptive and difficult to apply in empirical studies. They are not formulated as theories that can aid analyses and explanations of places and processes and facts of settlements. In fact, the main core of the literature deals with the site of a settlement rather than its situa­ tion, i.e., its relative placement on a spatial plane with other settlements in a region. In adopting an analytical ground for this study, it was thus ne cessary to co nsider the ideas of the contributors to location theory who were inspired by von Thunen and Weber. The theory was deve lo pe d and reoriented by later c o n t r i b u ­ tors to the spatial vi e w of human geography, use of the behavioral as revised by concepts. Literature Review Von T h u n e n 1s work (1826) such as Christaller and Losch, stimulated contributors, to study the functional 10 relationships between central places in regard to their re ­ lative location in competitive space. Von Thunen's a s s u m p ­ tions deal with an "isolated state", with a competi ti ve p r o ­ cess between agricultural land-uses and their distan ce to a single market city avai lable to farmers. Distance from the market is the most important factor influencing the rents of agricultural (Thunen, 1826). land lands and agricultural products "One essential characteristic of von Thunen's writing is the postulate of rational economic man, possessed of full and certain knowledge, his income." (Chisholm, 1969:401) seeking to maximize It should be explained that the factor of distance is not always equally im po r­ tant, because the development of transportation, agricultural farmers' products for other competitive markets, and choices in various communities of the w o r l d may overs ha do w distance in importance. "economic man" farmers' v a ri et y in Thunen's concept of is idealistic and de te rministic because behavior cannot be optimized because of individual preferences (active vie w of human beings). However, his work is valuable for establishing the fr amework for the concept of relative location. Ch isholm argues that, "the ideas developed and expounded by von Thunen do not c o n s t i ­ tute a theory of location," stimulate the work of Weber, (Ibid, 1962:21) but they did Christaller and Losch. Foust and deSouza mention that, "classical location theory is founded on the work of Alfred Weber," that was 11 pu b li sh ed in 1909 (Foust and deSouza, 1978:129). Weber's location theory is a modification of von Thunen's theory of rent (Barlowe, concerns 1978:286). industrial Weber's (1929) location theory planning and includes a model for d e ­ termi nin g optimum location for establishing new industrial plants. In it he indicates that geographical a va ila bil ity of resources, elements deed, location, labor force and supply are vital in the location of industries and factories. transportation development ment of regional industries. is vital In­ for the de ve lo p­ The industrial location theory of Web er is important because of its stimulating effects on 2 Chr ist all er (1933), Losch (1939), Hoover (1943), and Isard 3 (1950) . In order to "make new paths for demonstrating the spatial effects of economic laws and rules on the geography of settlements," Christal le r deductively derived central 2 Hoover's 1943 work concerns the economics of in­ dust ry location, land utilization, land use competition, u r ­ ban structure and regional development. His emphasis is bas ed on the optimum ut ili zation of land, land rent, site value, processes of locational change, market location for regional dev elopment and locational stabilization. Hoover was influenced by Weber and Losch. His contribution to lo­ cati on theory is industrial rather than agricultural, so it is not appropriate for rural and agricultural studies. 3 Isard (1950) has developed the location theory of W eb er an al ytically in his system of input-output analysis (economies of scale). Isard's work deals with industrial and agro-industrial planning in a theoretical analysis to­ ward overall dev elo pme nt of a region. Isard was influenced by Weber and Losch. His co nt ribution to location theory is most useful for ur banized areas. 12 place theory (1933) Thunen and Weber according to his (Berry and Harris, inspiration from von 1970:117). Chris­ taller's work in southern Germany is most significant for its patterns of central places in a relative or competitive location, and their functional surrounding areas. and economic relationships to James notes that The foci or nodes around which settlements tend to cluster are what Christaller called central places, each surrounded by a com ­ plementary area with which the central place is functionally related (1977:518). Christaller (1933) arran ged the central places of southern Germany in a hexagonal m a rketing pattern and classified the central places in hierarchical order from larger to smaller. This hierarchical order was arranged according to population size and centrality, with relatively few larger centers in a study area with greater ranges of goods and services and numerous smaller settlements in the region with lesser ranges of goods and services (Christaller, 1933). Losch supported Chr istaller's triangular pattern of settlement distr ibu ti on and hierarchical ordering of c e n ­ tral places and deSouza, Frey, in their hexagonal patterns of marketing 1978:83; 1977:98). James, 1977:519; Haggett, (Foust Cliff, and He was doubtful of the existence of h i e r ­ archies, however, in his research on Iowa Tennant, 1962:102). (Berry, Barnum and Judging whether a hierarchy or a con ­ tinuous relationship exists in the spatial distribution of 13 central places point out that, archices, is difficult. Berry, Barnum and Tennant "Both continuous relationships and hier- and blends thereof, may be produced from the same data and it therefore seems foolhardy to continue the argu­ ment as to which is valid. L o s c h 1s (1939) Both exist." approach also differs from Christaller's in that he starts from the system place (farmstead) lower part of a central place and m oves to the higher order central (me tropolitan). In practical terms this would be ex­ tremely detailed, but could be applicable studies of relative location uses and land rents. land In fact, Losch's agglomerated system Christaller's agglomerated model Thus, in empirical in a region of farmstead would be difficult to veri fy by empirical cable to empirical (Ibid:103) studies. Christaller's model facts, while is simpler and more a pp li ­ (Foust and deSouza, 1978:83) is pr eferred for its simple spat­ ial arrangement of central places in empirical studies. Losch was primarily con cerned with the future planning of optimal patterns of towns, firms and factories, than explaining their present situation. This rather is not use­ ful from the point of vie w of some geographers, because they are concerned with human beh avior and attitudes in existing regional developments, cational planning. M.J. Webber (1971) rather than purely deterministic lo­ In a compar iso n of Losch and Christaller points out that the idealistic and sug­ gestive regional planning of Losch implies what town 14 patterns trast, "ought" to be if reality were rational. In c o n ­ Christaller has explicitly applied his theory to e x ­ plaining and predi ct in g the actual patterns of towns (Webber, 1971:15). Another peculiar ity of L o s c h ’s theory is that systems, ban, (1939) central place it is con cerned mostly with large regional including urban and metropolitan areas, with u r ­ industrial, and man ufacturing activities while Christaller's (1933) theory deals with (macro-scale), local systems of central places that are relatively micro-scale and c on ­ cerned with retailing and service activities for the sparse agricultural places. people of the hinterlands around the central To be sure, both these concepts are valid and ap­ plicable for empirical study, however, study. For the purposes of this Christaller's theory of micro-scale regions with rural retail and service-oriented activities is pre­ ferred. The ideas of Christal ler and Losch are criticized for being static, not dynamic, and for being deterministic. Allen and Sanglier note that, place theory, general, "The developments of central although quite sophisticated, static." (Allen and Sanglier, have been, 1979:256). in Abler, Adams and Gould also believe that central place theory is not dynamic and does not show the processes of change in central places (Abler, called deterministic, Adams and Gould, 1971:377). It is because the probabilistic aspects of 15 consumers' behavior toward central places are not developed in the models of central place theory. mention that, Foust and deSouza "Formulations of Christaller and L o s c h . . .de­ velope d on the basis of classical economic theory, ignore nonoptimal consumer behavior." 1978:83) (Foust and deSouza, But Losch's concern for the subjectivity of farmers' choices of different goods and services is a helpful probabilistic perspective developed in later studies that has mo dified the rigid models of central place theory. graphers, particularly, have overcome the deterministic problems of this theory. historical dimension Behavioral g e o ­ Approaching central places from a (change over time) probabilistic aspects of farmers' and including the preferences and shopping behavior in adaptation of rural develop me nt are essential modifications in central place theory. The theoretical central place work of Chri sta lle r and Losch inspired a whole school of human geographers United States during the 1950s post-1960s period, In fact, 1969:3). location hypothesized by Thunen, and Losch." (Berry, Conkling and Ray, 1976:7). although early re­ largely involving rural communities and small in North America, theory Weber, only during the last two decades has there been any rigorous testing of central place theory, search, In the "geographers rediscovered the classical economic theories of Christaller, (Gould, in the (Lewis, towns tended to confirm the val idi ty of this 1979:119). Central place theory with its 16 novel perspectives signaled the end of a period of stagna­ tion and set the stage for an era of continued progress and intermittent co nflict in geographic knowledge as well as theory (Muller-Willie, 1978:64). Among later contributors to settlement ge og rap hy were those essentially influenced by central place theory and others influenced mainly by von T h u n e n 's notion of competition between rural (farm ste ads ). (1962) It should be noted that the work of Chisholm and Huds on Thunen's settlements (1969), which was influenced by von land rent theory, Weber's location theory, Christal ler and Losch's central place theory, and is modified pr imarily from perspectives that were concentrated on the relative location of farmsteads and farmers toward a c en ­ tral market (Chisholm, 1962) and the stages of change in the spatial distri but ion of farmsteads ally, (Hudson, 1969). their approach concerned the locational social and economic life of farmsteads, Gener­ factors of the rather than central places. Chisholm's work ( 1962) is a systematic and conceptual approach that deals wit h the rural subjects. His ideas settlement's contents and of rural development essentially con­ sider optimal pla nning for settlement patterns of farmsteads in the countryside, Chisholm, rather than focusing on central places. like von Thunen, emphasizes the locational factor of distance of farmers from a market in the central city for their agricultural products, but other markets in other 17 central places are not considered. Chisholm that with price competition in marketing, (farmers) (1971) the consumers' mark et in g behavior will be rational. noted that price believes It should be is only one attraction of central places for farmers and is not all-inclusive, dividual behavior is not the same. because farmers' On the whole, work does not provide a theoretical model to apply in empirical studies of rural for the purposes of this research, in­ Chisholm's that would be easy settlements. Indeed, which deals with the b e ­ havior and preferences of farmers toward central places, Chisholm's work was not as useful as revised central place theory studies and recent works of behavioral geographers. Another con tributio n to the location theory of rural settlements was provided by Hudson (1969), whose work deals wi th rural settlement location theory and its application to the farm landscape of parts of eastern Iowa. lieves that patterns of rural over time. helpful; Hudson b e ­ settlements will be changed The notion that change is a dynamic process, is but a problem arises with Hudson's assumption of a biological model over time. for the colonization of each settlement Huds on believes theoretically in a niche space or biotop space of each settlement which will be expanded by human occupation population densit y (colonization) (spread). and also by increasing These models of biological processes of settlements create deterministic conditions for the settlements' processes of change over time, without considering non-optimal human preferences. Hudson's 18 biological (1971) assumption and Lewis developmental is severely criticized by Grossman (1979). Gr ossman criticized the stages of Hudson's theory and decided it would hardly coincide with real changes. (1983) Generally, settlement patterns and their Hudson's location theory does not deal wit h the spatial dist rib ut ion of central places in the rural landscape, but only with the changes in cluster patterns of farmsteads toward a regular pattern. the biological Therefore, aspects of his location theory, apart from it is not useful for research that deals with patterns of spatial di st ribution of rural central places. Components Of Central Place Theory In the following discussion the essential components and at tributes of central place theory are explained. Uniformity A c cording to central place theory, ity in the physical and human uniformity comes of consumers) 248). unity and ho mo ge ne ­ environment and some aspects of economic in the study area are required (such as equal (Kariel and Kariel, in­ 1972: This as sumption of economic and human uniformity in any given region of the developed world has been discarded by Berry and Ga rrison due to a demonstrated geneity among consumers (Bunge, 1966:143), lack of h o m o ­ by Janelle in the 19 case of di suniformity in transportational 1968:5-10), factors (Janelle, and by Brush in the case of disuni fo rm it y of methods of tr ansportation (Brush, 1953:400). Indeed, the assumption of uniform income of farmers or consumers as postulated by Christal le r coincide with reality. ferential (1933) and Losch does not Rural dev el opm en t and farmers' success in upgrading outputs, their income, (1939) dif­ and con sequently has increased the diversity in their incomes. Geometric Arrangements And The Concept Of Range As mentioned before, (1939) both Chri sta lle r (1933) and Losch bel ieved in triangular patterns of settlement d i s ­ tribution that central places with triangular lattice d i s ­ tribution are characterized by dispe rse d patterns and c om ­ petitive processes in market space (Taylor, 1977:141). Their differences are apparent in the pr es entation of their models. Losch's (1939) marketing system is excessively complicated for empirical work, and more deterministic, which made it inappropriate for this research. taller's Chris­ less complicated marketing system and its m o d i f i ­ cations were found to be more appropriate. Christaller's Accor din g to theory there is a pro gressive order of d i s ­ tance between central places; the next order range limit of central places will be computed by mult ipl ica tio n of its lower range limit by 1.732 when K=3 in the network of the 20 classical central place theory's marketing model taller, 1933:63). (Chris­ Brush's case study in southwestern W i s ­ consin reveals a progressive order of hamlets, villages and towns that closely adheres to this rule of central place (Abler, Adams, and Gould, 1971:371). The rigid and d e t e r ­ ministic hexagonal pattern of market system in original central place theory paved the wa y for modifications later central (1958), Rowley place Stafford (1971). studies, (1963), in such as Berry and Ga rrison Davies (1967), Alternative methods Kenyon (1967) and include nearest ne ig h­ bor analysis, which enables dot patterns to be measured by an index (Garner, 1968:310). This method is in keeping with the predictions ge nerally made on the basis of central place theory (Kariel and Kariel, 1972:262). The concept of range is implied in the geometric p a t ­ terns of central place theory. Acco rd ing to Christaller, "the range is the distance to which the dispersed population will still be willing to go to purchase a good offered at a central place." (Christaller, concept of range, 1933:49,50) In Christaller's the premise is "That consumers always patronize the nearest place which offers the required good." (Clark and Rushton, wi th reality. Clark 1970:486) (1968) This, too, is not consistent found in his empirical study that fewer than half of a sample of consumers were a c c u s ­ tomed to traveling to the nearest center to shop, while others travelled much greater distances to larger centers 21 (Clark, 1968:386). Consumers' shopping habits do not coni­ form strictly to a rule of distance minimization; factors, other such as the socioeconomic attributes of consumers and individual behavior, will also affect the range of a good or service in a central place system. study, Murdie (1965) has shown that cultural differences b e ­ tween two social groups in Canada affect their travel b e ­ havior toward such goods as auto repairs, ing. In an empirical shoes and cl ot h­ The figures provided clearly show differences in the preferences of these two groups of consumers toward central goods and services. goods and services In other words, the maximum range of is determined by different consumer pr e­ ferences toward various goods and services. (1967) in his empirical community Similarly, Ray study of the farmers of a bicultural (French and English Canadians) in eastern Ontario, found that cultural differences were significant only in shopping for intermediate services, of shopping travel while different ranges for different functions were important in both cultural communities. Food stores had the smallest range of travel and optical services had the largest range of travel among both ethnic groups. The patterns of shop­ ping were assumed to be the functional places. levels of central This method of visual iz at ion is probabilistic and preferable to the rigid marketing pattern vi su alizations of central place theory. like Losch in 1939, Golledge, Rushton and Clark (1966), found that consumers are biased in their . 22 shopping travel (range of a good) spatially flexible goods, for different goods. such as girls' clothing, sumers will often go to alternative centers, For con­ rather than the nearest occurrence of the good, before making a purchase (Golledge, Rushto n and Clark, inflexible goods and services pair) are not competitive, distances, 1966:263). (such as church and T.V. Therefore, re­ because people do not travel or a great range of distances, (Ibid:264). Certain spatially long for these services the subjectivity of consumer pr e f e r ­ ences affects various ranges of marketing space and invali­ dates the di stance mi nim iz at io n concept of classical central place theory. In conclusion, shopping or visiti ng travel maps for diffe ren t functions, are probabilistic and pr a c t i ­ cal for use research. in this empirical Hi erarchy Or Rank Size Rule The pro pos it ion of a hierarchical vice centers (Davies, lies at the heart of central place theory 1967:61). H i e ra rc hy is a fundamental concept of system orga ni za tio n and interaction Ray, arrangement of ser ­ (Berry, Conkling and 1976:8). Chri sta lle r stressed that the basic func4 tions of a city are ordered by centrality; such central 4 C en tr ali ty means "the relative importance of a place with regard to the region surrounding it, to the degree to which the town exercises central functions." (Foust and de ­ Souza, 1978 :69) . 23 places are ordered into an. hi erarchy comprised of discrete groups of c e n t e r s — the greater the centrality of a place, the higher its order (Young, 1978:75). Indeed, higher order central places have greater population size. were classi fie d by Chr is ta ll er discrete levels of population. (1933) Central places according to their Christaller's hierarchical order of central places deals with aggregation of functions and tertiary activities attention (retail and services), while Losch's is focused on continuous attributes of functions in central places and their secondary activities, industry and ma nuf act ur ing 1974:214). (Bell, Lieber, such as and Rushton, For the purposes of this research, which deals with the relationships be twe en the preferences of farmers (people of the hinterland) central villages' and the functional goods and services, the hierarchical cept of Christaller would be appropriate. the small importance of However, con­ because sample size for each class of central villages can cause difficulties regression tests, sample size in deriving results from correlation and a continuous model (N=46 central villages) that has a greater and stronger results will be applied in identifying population and function re ­ lationships in the study area. Several contributors to central place theory have demonstrated the va li di ty of the functional hierarchical class-system. Bracey (1956, For instance, 1962), Hodge Berry and Garrison (1965), Rowley (1958), (1971), Davies 24 (1967), O'Farrell (1969), and Marshall supported this assumption of central and Rushton (1979), Indian villages, order of rural place theory. services, wh ic h they call (Fisher and Rushton, studies hierarchically, 1979:84). in terpretation of hierarchical bert of functions in each village) in empirical range (maximum num- is taken into account. in his study of southern Illinois, this relationship to be positive (r=.892). of Tipperary County sys­ the notion of a continuous re la t i on ­ ship between population and functional gression analysis inte­ (population size of settlement and func ­ is another (1963) planning in "functional In order to cl assify central places Stafford Fisher have applied the not io n of a hierarchical Rank size rule tem. have strongly in their study of regional gration of services." tional range) (1969) in a correla ti on and re­ O'Farrell (Ireland) found (1969) found r=.997 in his study in a continuous relationship of population and functions of settlement. analysis of another area, Johansen and Fuguitt United States' Rowley (1979, villages, 1984) (1971) Carter, found r=.948. in their study of the worke d on this continuous re ­ lationship and found r=.80 in 1950, in 1970. r=.82 in 1960 and r=.75 Stafford and Gilber t pirical study of Welsh towns, (1970) in their em ­ found a continuous r e l a t i o n ­ ship between population size and functional range, with r=.87. r=.81 In a discontinuous model of the same data, for places with In less than 50 functions, it was r=.59 for 25 places with less than 20 functions, with less than 10 functions. and r=.47 for places These writers thus concluded that smaller central places are very sensitive to regional development and socioeconomic change Gilbert, 1970:34). (Carter, Stafford, and The great amount of correlation c o e f ­ ficients betwe en the population size of settlements and their functional range in these continuous models, strong association between these two variables vious empirical studies. shows a in the p r e ­ It means that any changes in the population of a village is effective in the change of its functional range.in the case of discontinous models, smaller correlation coefficients between population size and func­ tional range of smaller central places, larger ones, compared with show that the population change of smaller central places is not strongly associated with change in their functional ranges. A ccor din g to King and Golledge, fined as the minimum bers of population, "threshold level level of support, as measured by n u m ­ required to support a function particular community." is de ­ (King and Golledge, in a 1978:122) The required population for supporting a function in a central place varies with the type of function. threshold population for (lowest order f u n c ­ and 1,424 persons for "health practitioners" order function) the (using a linear regression analysis) "filling stations" was 196 persons tion); For example, in Berry and Garrison's study of Snohomish County. (1958) (highest empirical Johansen and Fuguitt (1984) 26 found the threshold population for "service stations" est order function) equal to 305 in 1950 and 457 in 1970; for "photography studio" 1,453 persons (low­ (highest order function) in 1950 and 2,049 persons in 1979. they found It evolves that the threshold population increases over time and the continuous relationship between function and popul at io n is additional theory. support for the rank size rule of central place A continuous correlation between po pulation size and functions of central places needs arbitrary divisions of functions methods, that are usually done by the "natural breaks" as in Bracey's (1962) and Kenyon's Such arbitrary div ision of functions not determine the hierarchical tions of central places. agglome rat iv e linkage, (1967) work. is subjective and does linkages between the f u n c ­ The classification of functional called "functional index," is more val uable because it is objective and focuses on the fu n c ­ tional interrelationships between the central places of a region. The "functional index" was created by Davies (1967), who stimulated the work of Marshall O'Farrell helpful (1969), and Bennison (1978). (1969), This model is also for determining the rank order of each individual function, consistent with its coefficient value. There is also an alternative continuous approach that considers discontinuities in relationships betwe en p o p u l a ­ tion size and settlement functions. nant (1962) and Ray (1967) Berry, Barnum and Te n­ have applied factor analysis in 27 their c l as si fi ca tio ns of central places lages, towns and cities. tion size and functional with other classes. into hamlets, vil­ The relationship between po p u l a ­ range Therefore, in each class is unconnected there is a discontinuous re ­ lationship b et we en the popula ti on and function of the four discrete classes. This method also reveals the maximum range and threshold (minimum range) of each class. Visual­ izing the range and threshold of each class of central places is pos sible by using other classifications, functional indexing. Because classes are determined by their functional viability, the related data of population could be used agains t the related functional tral places. including Indeed, ranges of cen ­ comp ut in g the location coefficient is a complem en tar y and preferable advantage of this method, compared wi th factor analysis. Dynamic Orienta ti on In adopti ng a p ro ce ss -o rie nt ed and dynamic approach, the use of a historical ap proach is complementary. analyzing changes in central places' functions, In contribu­ tors to central place theory have identified several fac­ tors that have influenced the functional bases and v i a ­ bility of central places in their study areas. Christaller himself be li ev ed that effective demand for a good or a ser­ vice depends on consumers' to conclude that, incomes and tastes. This "c on sumption of central place goods led him is decisive in the develop me nt of central places." deSouza, 1978:70). Bracey indicates that because of im­ provements in agricultural trial skills, surpluses, the growth of indus­ and developm en t of improved means of c o mm un ­ ication, rural (Bracey, 1956:50). Wisconsin, (Foust and services have been a part of regional growth Brush (1953), in his study of southern found that economic and technological changes have been influential central places. factors in the functional changes of Smith (1970) de scribed how technological innovation and adapta tio n in tr ansportation and agriculture have shaped economic changes in the River Bend area. (Minnesota). To conclude, growth it is apparent that social and economic (in agricultural and industrial ical development, and improvements geographers, in changing the func­ In opinions expressed by other partic ula r factors are believed to influence the growth or decline of central places. and Gauthier, tec hn olo g­ in transportation and communication have been major factors tions of central places. sectors), Jr., (1968) found that, For instance, Brush in the United States increasing income, dec ent ral iza tio n of population and the use of automobiles seemed to be changing the patterns of settlements. In Lewis' opinion, the improved mobility of consumers and their increased wealth, with a concommitant demand for specialized goods and services growth and decline of central places influenced the (Lewis, 1979:137, 138). 29 Clawson (1966) notes when farmers' incomes demands for goods and services change. increase, their They may become un ­ willin g to,accept wh a t they per ceive as inferior goods and services offered to smaller central places will travel to larger centers (towns) and more varied goods and services. (hamlets), and so that may offer better These ideas seem ap ­ propriate and complement pr eviously me ntioned factors. Hodge's empirical Saskatchewan, changes study (1965) of the trading centers of supports the impact of these factors on in settlement patterns and functional trade centers. Hodge found that demographic, economic and social factors caused essential changes in locational, changes in the viability of these trade centers over a short period of time (1941 — 19'61) . He determined that smaller trading centers had declined or disappe ar ed while intermediate trading centers had grown up and entered the ranks of the larger trading centers. He predicted that future patterns in his study area would show more disappearing small trade centers increasingly di spersed pattern of small trade centers); an increase of larger trade centers spatial distribution). (an and (a more clustered Hodge's wo r k is a dynamic and p r e d i c ­ tive analysis of interactions among seven different h i e r a r ­ chical classes of trade centers in a framework of time and space and his suggestions about the future real lo cat ion of trade services in the study area are useful. Central place studies of this type need to be augm ent ed by further study of the behavioral preferences of consumers. Like Hodge, 30 Joh ansen and Fuguitt (1973) found in their empirical of Wisc ons in villages that locational study (interacting re ­ lationships between central p l a c e s ) , technological and transportational factors were significant in changing the trade c e n t e r s ’ vi ability over thirty-one years. As discussed before, transportation factors are signi­ ficant in the development of central places and are an im5 portant co mponent of rural development. Christaller stressed the importance of means of transportation as m e d ­ iators in the development of central places (1933:47). Losch distance from (1939) determ ine d that the consumers' the market was significant in the marketing process. regard to general transportational development, In the ideas of Ch ri staller are more realistic than those of Losch, who em ­ phasized the factor of distance witho ut taking into co ns i d ­ eration advanced means of transportation. Brush (1953), in his study of southwestern Wisconsin, indicates that the spatial patterns of agglomerated settle­ ments there were due to the influence of transportation 5 Rural development is considered here in agricultural and non-agricultural sectors. The latter includes the d e ­ velop me nt of roads, educational services, rural electricity and rural health services, etc. (Yudelman, 1976:313). Among the non-agricultural components of rural development, road and highway development is considered crucial. James S. Burch, in a study of secondary road problems in North Carolina, found that many changes of rural areas were in­ fluenced by highway improvement (also noted by Garrison, Berry, Marble, Nystuen, and Morrill, 1959:12). 31 types and sites in the nineteenth century. The railroad function that was prevalent then has since been reduced; trains have been replaced by trucks and passenger cars and the original patterns of agglomerated settlements (central p l a c e s ) , which had be e n influenced by the role of railroads are presently changing under the impact of modern t r a n s p o r ­ tation. tional Clawson found that the development of tr an sp or ta ­ factors and the drawing power of larger towns had decreased the former importance of smaller centers in rural areas of the United States. When a farmer hauled any product to market by ho rs e-d raw n wagon, he was anxious to have that market point nearby. Hence, small hamlets often existed at r a i l - s i d i n g s . Today, the truck may take the same product 25, 50, 100, 200 or more miles to a more nearby central market, either eliminating rail haul completely or continuing it only from a larger town. There is less need, or no. need at all, for formerly intermediate market points. ...the sad state of most small rural towns is dramatic evidence that most farmers find the drawin g power of the larger towns relatively very powerful, many farmers drive past the small towns in order to stop in the larger ones. (Clawson, 1966:286 ,289) . Foust and deSouza also noted that, the improvement of transportation mobiles and paved roads) bypass (widespread use of au t o ­ after 1914, enabled consumers to smaller centers and patronize the larger ones and deSouza, study in the Middle West, (1963), 1978:98). Stafford, in a related, (Foust empirical considered the influence of the increasing 32 popularity of the au to m o bi le on the increase in numbers of gasoline filling stations and auto repair garages in small towns. In fact, changes extensive changes in transport ati on have fostered in the form, functions and vi ability of central places over time. Janelle (1968) and Smith (1970) have indicated the role of speed in re ducing trip time between central places. When central places can be reached more quickly than was formerly possible due to technological development, distance is subor di na te d by increase of travel time. travel the factor of in speed and reduction Smith be lieves that such reductions of time and increases in income encourage consumers to ­ ward larger and further central places, causing the growth of larger centers and the decline of smaller ones. Adams and Gould (1971) Abler, also di scussed the impact of time- space convergence and the increased income of farmerconsumers on their r el at io ns hip s with central places. Today, because of the time-space convergence due to automobiles and good rural roads, a farmer can visit the sixth-order village center more easily than his gr and fat he r could get to the nearest hamlet. He also has more money to spend and larger shopping lists. Many of yesterday's sixth-order goods and services have become today's ev ery da y needs. The result has been the steady decline of the hamlets as a central place (Abler, Adams and Gould, 1971:369). Johansen and Fugui tt lages of the United States (1979) in their research on v i l ­ found that rural people's greater mobility has been influential in the decline of the economic 33 viability of villages in the urban/rural period of 1950 to 1970 system over the (Johansen and Fuguitt, 1979:25). They also found that the viability of central villages is dependent on their retail sections; thus, the viability of those villages is altered by changes in farmers' patterns over time (Johansen and Fuguitt: 1973, shopping 1979). The development of transport technology has enhanced the rural areas for commuters, tional seekers. Hart, retired people, Salisbury and Smith lieve that cheaper housing costs and re c re a­ (1968:345) be­ in the villages of the U.S. make them at tractive for low-income families who have their jobs in the cities. Wheeler (1971:110-119) rural nonfarm p opu la tio n in the U.S. states that partly includes the urban to rural migrants who prefer rural living and city employment. He explains the situation by the increase of geographical mo bility of labor in the U.S. decades. Jo hansen and Fuguitt (1973) over the past found that the impact of automobile technology and road development in Wi sconsin has attracted new residents for the recreational in villages and their surrounding areas. some functional changes lages. In the 1970s, in the retail advantages This has caused sections of the v i l ­ retirement and recreation emerged as important g r ow th- in duc in g activities in the non metropolitan areas of the United States 140). Thus, (McCarthy and Morrison, 1977: there has been a great increase in the d e m o ­ graphic growth of some rural areas (Long and DeAre, 1983: 34 41). McCarthy and Morrison (1977) mention that the m i g r a ­ tion to the United State's rural areas is due to the a d ­ vances of transportation technology and the increased im­ portance of natural emenities. Hodge and Wh it b y (1981) similarly believe the increased demand for leisure a c t i ­ vities and improvement of transport facilities among the de veloped nations, have increased their rural populations. It may be expected that these demographic changes have had an impact on the central functions of villages. in his empirical study of a Swedish city Falk (1980) (Norrkoping) found a large reduction in the number of stores in the downtown area over 25 years. This was due to residential develop­ ment in areas surrounding the city that required new stores and shows that demographic changes will influence the d i f ­ fusion of stores and consequently the vi ability of cities and villages. Johansen and Fuguitt (1979) have found the changi ng patterns of po pulation distribution to be one of the important factors activities in changing the viability of retail in U.S. villages. As a result, improvements in transpor ta ti on and the increased mobility of people are en ­ co uraging change in the demographic patterns of rural areas of the developed world, including the U.S. change of demographic patterns Indeed, the itself has been responsible for changing the viability of rural American villages. In conclusion, therefore, technological improvements have influenced the development of means and networks of 35 tran spo rt ati on and made central places more accessible to farmers than in the past. nological Indeed, the adaptation of tech ­ im pro vements has up graded the wealth of farmers and wealthier, more mobile farmers have shifted their shop­ ping patterns from smaller centers toward more remote c en ­ tral places wit h more complex and specialized functions. Ch ris taller be l i e v e d there is a definite connection between the cons ump ti on of central goods and the development of central places (Christaller, notes the consumers' tributional places. Losch (1939) also role in affecting functional and d i s ­ pa tterns of goods and services in central Co n s i d e r i n g these ideas and the aforementioned empirical studies, comes and demands ment) 1933:27). the influence of farmers' (due to rural increased in­ and agricultural d e v e l o p ­ on the v i a b i l i t y and spatial di st ribution of central places has been fairly well established. The increase of consumers' income and mobility takes place over a period of time and their impact on central place d e v e l op me nt or decline implies a time dimension. Therefore, c on tr ibu to rs to revised central place theory have specified time frames change in central the changes Smith's for their approaches to functional places. Hodge's (1965) in a trade center system from 1941 to 1961; (1970) study concerns an approach to agricultural and economic de v e lo p me nt in a region, places, study focuses on from 1900 to 1960; Kenyon's including its central (1967) work on the 36 central places of Georgia provides a cross-sectional study of changes in the social and economic activities of central places from 1950 to 1960; Fuguitt's ties (1973) (functions) and finally, Johansen and research on the changes in retail occurring in Wisco nsi n villages acti vi­ includes the period from 1939 to 1970, with an emphasis on 1954 when these retail functions began to decline. Taken together, these investigations of functional changes in central places over time have focused on varying time periods of 10, and 60 years. 20, 30 After examining each scholar's rationale for the time period selected, ingly advantageous; neither extreme seemed ove rw he lm ­ the average and median of these cross- sectional studies suggested that 25 to 30 years would be an 6 appropriate time period for the study at hand. Consumers' Shopping Behavior Applying central place theory in an empirical that examines the changes study in rural retail centers and rural services, in relationship to the preferences of farmers or consumers (people who live in the complementary region or hinterland of each central p l a c e ) , necessarily involves consideration of the behavior of consumers. Spatialism is 6 Norling, in research on the abandonment of rural settlements in nor thern Sweden, has used 30 years as his study period (1960:23 2-243). 37 criticized when it ignores the social questions 1974). (Taaffe, A behavioral approach as a comple me nt ar y vi e w in spatial analyses modifies the de te rmi nis m of positivistic studies (Ley, 1981:250). En tr i k i n (1976) verifies the need in scientific geography for a body of empirical their verified conclusions based on historical studies and and regional geography and positivistic or ie ntations of spatial and b e ­ havioral analysis. According to central place theory, there are p r e d i c t ­ able minimum and maximum distances that consumers will travel to and from central places for shopping and services. This assumption is de te rministic and cannot be generalized. Central place theory is a model which helps us to better understand and predict spatial patterns of consumer behavior. We must keep in mind that human beings are not economic optimizers, but do, to a limited extent, adhere to the principle of distance minimization. (Foust and deSouza, 1978: 61) Blommestein, Nijkamp and Ve enendaal menti on that c e n ­ tral place theory assumptions of shopping models do not al ­ low for the socio-psychological havior, elements of consumer b e ­ such as their perceptions and preferences stein, Nijkamp and Veenendaal, 1980:160). (Blomme­ Therefore, the preferences of farmers need to be examined from the point of view of behavioral modifications to central place theory. 38 In the early 1960s, focus on environmental behavioral ap pr oaches-tended to perceptions and de cision-making p r o ­ cesses and the conce pt of "economic man". d e f i n i t io n of "economic man" Wolpert's (1964) is concerned with individual d ec i s i on -m ak ing in ec onomic activities and occupations. As a rational being, "economic man" is free from the m u lt ip li ci ty of goals and imperfect knowledge w h i c h introduce complexity into our own decision behavior. Economic man has a single profit goal, omniscient powers of perception, reasoning, and computation, and is bless ed with perfect p r e ­ dictive ab.il ities ... economic man organizes h i m ­ self and his ac tivities in space so as to o p ­ timize utility. (1964:537) Ad j us ti ng and comp ar in g the spatial and economic b e ­ havior of farmer-consumers with the model of economic man is not a reasonable and practical approach, because the various ch ara cte ris ti cs and preferences of individuals are d i f f e r ­ ent. Indeed, preferences in economic activities cannot be op t im iz ed to fit an ideal model that assumes all people p e r ­ form their economic activities optimally. In the which late 1960s, behavioral looked at spatial behavior, studies began to appear shopping behavior, co nsumer behavior toward markets or central places. omic and psychological formed the analytical to Golledge, and Econ­ models and shopping behavior models framework of this period. Brown and Williamson, behavioral According studies in this period were preoccupied' with consumer travel behavior and re-examinations of central place theory (Golledge, Brown 39 and Williamson, sectional 1972:61). Murdie (1965), study of "cultural differences in his crossin consumer travel," compares the shopping travel behavior of two c u l ­ tural and social groups, a group of "modern" (Canada). an old order Mennonite group and Canadians in southwestern Ontario He found that these two groups have some d i f ­ ferences and some similarities in their shopping behavior 7 tov/ard selected goods and services. Their range of shopping travel for goods and services was different and related to their subjective view of shopping in relation to spatial distri bu tio n of goods and services tral places. in certain c e n ­ Another point was that the modern Canadians, who have adopted new technology, were more mobile and richer than the M e n n o n i t e s , so the modern group made a greater range of shopping trips than the Mennonites. This study was concerned with choice behavior in an analytical processoriented framework. The concept of choice or selection in shopping for a particular good or particular service is ex ­ amined by Golledge, Rushton and Clark farm population of Iowa. willing to travel rence, clothing and movies, who studied the They found that farmers were longer distances, for particu lar (1966) (flexible) from the nearest o c c u r ­ goods and services such as while they were not willing to travel In Murdie (1965:215), food, clothing, shoes, a p ­ pliances, banking, auto repair or harness repair, doctor and dentist are shopping and convenience goods and services. 40 far and would stop at the nearest purvey or for inflexible goods and services, repairs. Thus, such as church services and applicance inflexible rural goods and services did not exert com petitive power, selections. in terms of farmers' choices and It can be con cluded that the behavioral p r e ­ ferences of farmers, in seeking goods or services, affect the pattern and frequ enc y di st ribution of goods and s e r ­ vices in central places. and Clark (1966) The approach of Golledge, Rushton c on ce rn in g the biased travel behavior of shopping for di f f er e nt goods is process-oriented and a na ly­ tical. Golledge and B row n search and learning (1967) have studied the processes of in consumers' They found that an individual behavior toward marketing. consumer first exerts search or explorat ory beh avi or toward markets, which is continued until minimum dis tance and maximum aesthetic value are a t ­ tained. He will the refore respond habitua lly toward the market experience. cess, habitual "In terms of the market decision p r o ­ responses may include the patronage of one or many market centers." (1967:117). Thus, learning and trial behavior are important in establishing habitual and stable shopping behavior. plicable This type of study was found to be ap ­ in ex am ini ng the habitual shopping behavior that study subjects dir ec te d toward central places. In fact, length of re si den cy was found to be a factor which affected 41 the perceptions and choices of consumers and had an impact on marketing patterns. Other peculiarities of consumer shopping behavior are age, income-level, socio economic condition and ac ce ss i­ bility to central places. (1969) For example, has compared and analyzed the shopping movements of two income groups from Middleton Lane Ross L. Davies (high income) (low income) in the south of Leeds selected goods and services such as shoe repairs, bank services. and Street (England), toward groceries, hardware, He selected his subjects from groups of similar age and ethnic-racial composition, di ffering income levels and his results cant shopping preference differences, level. but indicated s i gn if i­ according to income The majority of low income people patronized chain stores and general stores while the high income people pre ­ ferred to shop in smaller and more specialized stores (Davies, 1969:120). The individual choice behavioral approach of the late 1960s continued to be employed in related studies u n d e r ­ taken in the early 1970s (Hudson, 1980:347). however, psychological havioral studies of shopping patterns, In the 1970s, approaches began to appear in b e ­ especially the ap­ pl icat ion of personality and cognitive maps as correlates of spatial choice 1975, (Br ooker-Gross, 1981:28). Cadwallader, in mentions that there had been recent efforts made to explain individual behavior in space, especially individual 42 decision-making. Meanwhile, the u n s a ti sf ac to ry concept of "economic man" was gradually replaced by the idea of sat­ isfactory be havior and bounded ra ti onality 1975:339). Finally, (Cadw al lad er, di sa ggregate behavioral research, based on the motives and attitudes of individual choice, became typical of geographical (Blommestein, Nijkamp and Veenendaal, spatial studies in the 1970s 1980:155). At the beginning of the 1970s, when behavioral proaches were popular in central place studies, (1971:140) theory, tions, expressed the view that, Rushton "a revised central place constructed on more realistic behavioral yields some spatial properties different from those of classical a p­ fo u n d a ­ that are markedly theory." He believed that distance and site attraction are variables which influence shopping behavior in the spatial choice process Burnett (1973) town size, (Ibid:141). disagreed that the objectives of distance, convenience of parking, quality of goods, and prices of goods were necessarily the actual components of consumer choice and believed time and money to be the sub­ jective alloys. She found that such factors as age and length of residency in a place influenced purchasers' choices from women's wear shops. result of their experiences, shopping center. people, as a are biased in choosing a While it is reasonable that the sub je c­ tive experiences of consumers cational aspects, Therefore, influence their choices, such as town size, lo­ its attractiveness, and 43 the price and varieties of flexible or inflexible goods should not be ignored in analyzing shopping choice behavior. The co ncept of objective and subjective relationships dividual behavior is supported by Pacione in in­ (1.982). S hopping behavior was also examined through consumer perceptions and decisions made in choosing shopping centers or markets. Pacione (1975), in an empirical study, found that consumers did not actually behave in accord with the rationale of "economic man", but that individuals made d e ­ cisions wit hi n the framework of their own perceptions of the retail environment. ping satisfactions vironmental Individuals try to maximize their shop­ (consumer preferences) perceptions (1975:84,86,91). (cognitive) Cadwallader (1975) through their e n ­ of shopping centers examined the shopping preferences of a sample of lower-middle class families in West Los Angeles toward five adjoining supermarkets. He suggested that the link between an individual's perception (image) ences) of an environment and his overt behavior in that environment, havioral approach. psychological are very important His approach is helpful analysis of individual's (prefer­ in the b e ­ in socio- shopping (choice) behaviors. In his 1979 empirical overt behavior variables in southwest Birmingham study, Williams examined three in a sample of 500 grocery shoppers (mode of travel, and size of center u s e d ) . frequency of trip, He found that grocery shoppers 44 tend to prefer shopping convenience over the range of choice and price competitiveness that are available in larger c e n­ ters. Therefore, iations they use centers near their homes and v a r ­ in distance traveled are low Williams' data analysis of shoppers' preferences toward shopping centers, square probability test, approach to behavioral empirical 1979:160). differential values and an inferential chi- is reasonable and a probabilistic preferences. study of individuals' dispositions) (Williams, in Vancouver, Taylor (1979) retail choices in his (personal has examined the consumers' dispositions toward five selected characteristics of retail shops: fashion orientation, ientation, price orientation, convenience orientation, In his approach, quality or ­ and status orientation. Taylor tried to examine the personalities and perceptions of individual consumers toward these five factors by using an environmental response inventory scale. He found which factor or factors had been more or less pressive (affected personal disposition) im­ to the consumers sampled. This type of research looked at the personal d i s ­ positions (shopping choices) than subjectively, of consumers more objectively wh ic h is useful but not complete, because both subjective and objective factors contribute to c o n ­ sumers' choice behavior. An evaluation of the behavioral studies in the 1970s shows that there has been a m o d i f i c a t i o n ‘of the concept of 45 central place theory by developing and applying the b e h a v ­ ioral perceptions and preferences of analytical framework. of consumers' individuals in an Most studies concentrate on analysis shopping travel patterns, indicating that att rac tivity factors of retail centers, size of town, con ven ie nc e of shopping, qualit y of goods, preferences. such as location and and price and are objective aspects of individuals' In contrast, time, budget, age, income, and the experiences of individuals are subjective factors in 8 their choice behavior. Both subjective and objective aspects are important. The behavioral studies of the early 1980s continued to stress disaggregate and individual behavior attitudes and preferences, although some studies were done on aggregate preferences that consid ere d both consumers' shopping choice behavior. daal (1980), Blommestein, in a Dutch town, examined the shopping images of both consumers and producers. a cce ssi bil ity and price average Nijkamp and V e en en ­ in their empirical analysis of integrated shopping factors sex, and producers' income, Factors such as (objective factors), consumers' and frequency of shopping age, (subjective The grouping of factors into subjective and objective is based on the literature discussed in this research that describes subjective and objective behavior of consumers. If an individual is attracted to shop in a place because of the pcice of goods, it is an objective factor; conversely if an individual seeks a particular shopping center to save money, it is a subjective preference. 46 and personal factors) were examined in a comprehensive e f ­ fort to explain shopping models. Brooker-Gross (1981) In a di fferent study, examined two social groups' models of inshopping and outshopping for shoes and found that d i ss at ­ isfaction with local opportunities caused outshopping by both groups. The groups, however, differed in their out- shopping and inshopping behavior. race and age, Hall (1983) showed that as well as income, were factors in explaining shopping patterns for inferior types of food. To sum up this discussion of shopping behavior a n al y­ sis, Pipkin's evaluation is appropriate. that the, Pipkin believes "consumer-theoretic account of shopping behavior" implied in central place theory, reformulations of, has been linked with the "the late nineteen sixties and with more recent and overtly psychological accounts of store choice," (Pipkin, 1981:315). Further examples are pr ovided in studies of spatial choices of shoppers at women's wear stores (Burnett, grocery stores 1983) . 1973); shoe stores (Louviere, 1981); (Brooker-Gross, and food stores 1981); (Hall, These recent studies of consumer preferences show that each good and service in a central place has its own attributes and attractiveness that will and choice behavior of shoppers. affect the travel Integrated with each in­ dividual's peculiarities and preferences, and subjective attributes of consumers' these objective modal choices a f ­ fect the viability and pattern of spatial di str ibu tio n of 47 central places. preferences Criticisms of behavioral (Bunting and Guelke: 1979) studies of human should be d i s ­ regarded because explanations of individual ences are analytical rather than deterministic applications of a holistic approach Downs, 1983) . 1979; Duncan, spatial p r e f e r ­ (See: Rushton, 1981; 1979; Saarinen, and Couclelis and Golledge, 1979; CHAPT ER TWO PROBLEM AND RESEARCH DESIGN Problem Statement The central villages of southcentral Michigan, di fferent size populations and functions, changes with have seen varied in their via bility and spatial distribution over the pa st. thi rty years. Central villages are trading centers for farmers who are the main consumers of their goods and ser9 vices. Therefore, the relationships between the farmers and central villages activities) include their trade functions (retail and services. This study focuses on identification and investigation of farmers' wholesale, preferences toward central villages' and service activities central place theory. retail, in accord with revised Correspondingly, agricultural rural development influences on central villages' and changes in vi'ability and spatial distribution are examined and e x ­ plained. 9 In prelimi nar y research (1982) on the villages of Fowler, Sunfield and Webberville, 80 percent of the people in the surrounding villages were farmers. During the data collec ti on phase of this research in 1983, only 65 percent were found to be farmers. 49 Rural develop men t in farming activity in the study re ­ gion over the past thirty years has included the increasing percentage of farms equipped with tractors and a c o r re sp on ­ ding decrease in the percentage of farms having horses. Increased farm size, farm specialization arid consolidation and increased farm efficiency have caused farmers' to increase. Consequent to rural income farming development, some central village retail, wholesale and service functions have expanded, such as florists, clothing stores, churches. stores, sporting goods stores, farming equipment stores, Conversely, family banks and other functions such as grocery gasoline stations and jewelry stores have declined dramatically, due to the loss of their viability. Some other functions and services of smaller villages have d e ­ clined, such as schools and funeral homes, consolidated in larger central villages. functions, stores, Several outmoded such as b l a c k s m i t h i n g , shoe repair and general have almost disappeared from the rural Accordingly, study period. landscape. numbers and types of functions have u n ­ dergone diverse changes villages and have been in the central villages over the It needed to be determined how many central (with different functional orders) stabilized or declined in the system. had developed, The factors that had caused these changes also needed to be identified. dicated in the first chapter, As in­ rural development and farmers' 50 preferences we re expected to be major influences in changing the vi ability and spatial distributions of central villages. Hypotheses Concerning Hierarchical Structures Of Central Villages And Their Change Over Time From the evidence offered by Berry and Garrison Bracey (1956, 1962), the hierarchical veloped world, Davies (1967), and Marshall (1958), (1969) of structures of central places in the dev- it was expected that a hierarchical st ru c­ ture would be found among the functional bases of the ce n­ tral villages of the study area. But, because of the in­ crease in the number of functions that are singular in their frequency of occurrence (with high location coefficients) every class of central villages, ical in it is likely that hi er a r c h ­ structures of central villages have changed over the study periods. forshire P a h l , in his empirical in 1964, study of rural Hert- concluded that a change from hierarchical to segregated structure tally) is one of the fringe (Lewis, (expanding of functions h o ri zo n­ important aspects of a metropolitan 1979:139). Similarly, McGranahan (1980:92) states that becau se of the decline in agriculture, farm d e ­ popula ti on and n e w rural activities for nonfarm families, the hierarchical changing. structure of farm-oriented functions It may be predicted that the hierarchical ture of the central villages studied has is struc­ likewise been 51 changed over the study time, due to rural development and the increase of nonfarm populat ion in the study area. Concerning Relationships Betwe en The Population Sizes Of Villages And Their Functions There is a continuous re la tionship between the po pu l a ­ tion size (or population served) their functional ranges (1963) in the central villages and (number of f u n c t i o n s ) . Stafford found the coeffici en t of correlat ion equal to southern Illinois and Joh ansen and Fuguitt r=.87 in 1954 and r=.82 Wisconsin, (1973) found in 1970 in their empirical showing that the regress ion 1970 had shifted downward. .89 in study of lines from 1954 to The same trend was noted in later studies of Americ an villages by Johansen and Fuguitt (1979, 1984). They found r=.80 with the regression curves in 1950 and r=.75 in 1970, shifted downward. Therefore, it was hypothesized that a continuous rel ationship between the population of the villages in this study and their func­ tional ranges existed and was wea ken ed over time, increased population (development of residential in the central villages) tertiary activities and declines (wholesale, due to functions in the number of retail situation implies a significant decline and services). This in the functional viability of central villages. Assuming the existence of a h i er ar chy in the functional order of central villages does not undermine the above 52 mentioned continuous relationships between population and functions in the central villages and Tennant uous) (1962:103) found, studied. As Berry, both hierarchical Barnum (discontin­ and continuous models could be created from the same data. Therefore, exami ning both continuous and hierarchical structures of central villages cedure in this research. maximum functional range each class of villages) is not a contradictory pr o ­ It was, therefore, (maximum number of functions and Gilbert, in and threshold population would ex ­ ist for each class of central villages ature see Berry, expected that a Barnum and Tennant, (for related 1962; Carter, liter­ Stafford 1970) . Concerning The Range Of Functions Later con tributors to central place theory found that consumers do travel dif ferently for different goods and ser­ vices. In other words, order functions and services Ray, (Murdie, 1967; Therefore, Davies, shorter trips are made for lower longer trips for higher order goods and 1965; 1969; Golledge, Rushton and Clark, and Clark and Rushton, 1966; 1970). it is hypoth esi zed that the farm and non-farm families of the study area who live in the areas sur round­ ing the central villages will travel for shopping. Thus, show different patterns of the range of each sampled func­ tion will be diffe ren t and dep endent on the shopping and 53 travel behavior of the consumers (rural farm and nonfarm families). Concerning Rural Development Adoption of technological (farm mechanization, specialization, upgraded farm efficiency, so that farmers have and agricultural tools) and c o n s o l i d a t i o n ) , has pr odu cti on .and farmers' increased their demands ialized and modern goods and services modern agricultural innovations instruments, incomes, for more spec­ (consistent with their tractors, and manufactured and decreased their demands for older and outmoded rural village functions. Hart and Salisbury and Smith, Jr., (1968:345) note that most of the villages of the Middle West that had similar central functions in the horse and buggy era, lost these central functions due to the advent of the automobile. Johansen and Fuguitt (1973) found that Wisc on si n villages lost several of their central functions, which had formerly been responsive to the outmoded agricultural over time. technology, In their places they gained new functions that were demanded by the new lifestyles of the people in the areas surrounding those villages. Similarly, thesized that the farmers of the study area, ion of technological and agricultural demand outmoded functions it is hy p o ­ due to ad op t­ innovations, do not that were locally available to them in the central villages in the past; instead they 54 demand advanced functions farming operations) (responsive to bus ine ss-oriented that are supplied in the larger central places of the study region. It is anticipated that this r e­ orientation has changed the viability and spatial d i s t r i b u ­ tion of the central villages of the study area over the study period. Tr ansportation developments in the region have favored the adoption of mod ern trucks by farmers who use them to d e ­ liver their own products and make trips to central places. Indeed, street and road development in the central villages that has been accompanied by highway development in the su r­ rounding townships, has enhanced farmers' mobility so that they bypass the lower order central villages and do their shopping in higher order central places, causing an increase in the centrality of larger villages and bigger central places and de creased centrality in smaller ones, petition. Moreover, due to c o m ­ the impact of transportation d e ve l o p ­ ment encourages a dormitory function in central villages and their hinterlands, where nonfarm people reside on the farm landscape, work primarily in the urban centers and do their major shopping in the high in the hierarchy, larger central places. Thus, village s with adequate population to support their high order functions, have become more eligible for socioeconomic growth compared with the lower order villages of the study area over the study period. 55 Concerning The Order Of The Functional Viability Of Central Villages According to the earnings data from Dun And Bradstreet Reference B o o k s , (Tables A.l, A . 2 and A . 3) the central v i l ­ lage of the study area have seen severe reductions in the numbers of their retail functions over the past thirty years. It may be expected that the lower order central v i l ­ lages have lost more of their retail viability than the higher order ones. Robertson tion of retail functions (1983) found that the r e d u c ­ in smaller American cities had been more rapid than in the larger central places over the period of 1954 to 1977. Johansen and Fuguitt (1984:202), in their study of American villages found that in a process of func­ tional change from 1950 to 1970, higher rate and had smaller functional larger villages gained at a lower rates of loss than did places of size. Bunce (1983:18) states that when economic development occurs the smaller centers cannot c om ­ pete successfully wi th larger ones. (1978:507) Similarly, Clout notes how the retail outlets have gr adually d i s ­ appeared from smaller villages in favor of larger set tl e­ ments in a sample study of East Anglia. Thus, it is e x ­ pected that the lower order central villages have been more sensitive to development and lost more of their functional viability compared with higher order central villages. The application of economies of scale will be meaningful here. 56 C o nc er ni ng Farmers' Farmers' range of shopping travel type and spatial Therefore, ter, Preferences flexibility of each particular function. farmers do not always shop in the nearest c e n ­ their shopping travel biased. For example, central villages; and boys' is related to the for certain goods and services is gasoline stations exist in most of the they are low threshold functions. clo thing stores as a high threshold function serve a larger range of consumers' shopping model, so these two goods will be treated differently by farmers. fore, Men's Th er e­ it is an tic ipated that farmers will favor larger central places in their shopping behavior and tend to bypass the smaller centers. Farmers' individual characteristics and preferences (overt be havior or ob servable personality) v i r on me nt will affect their decision-making choices and shopping travel vices (e.g., toward their en ­ age, type of land use, in shopping for particular goods or se r­ education, income, average farm size, full-time or part-time farming, of visits to a central place). Therefore, frequency it would be ex ­ pected that these di fferent characteristics and behavioral attributes of farmers will differen ti al ly choice of shopping travel words, influence their for a certain good. In other there will be different degrees of association b e ­ tween farmers' ch aracteristics and preferences and their choice of a central service. village for a certain type of good or It may be hypothesized, then, that farmers' 57 individual characteristics and preferences influence the * viability and spatial distributions of central villages. F a r m e r s ' shopping experiences wi t h the goods and ser­ vices available in central villages, choice of shopping locations. ency in a given place will will also affect their Therefore, length of r e s i d ­ influence farmers' shopping choice behavior and affect their selection or rejection of certain goods in certain central villages. Attractiveness, competing prices of goods, accessi­ bility and size of centers are objective attributes of rural goods and services dis.courage farmers' in central villages that can encourage or decisions to shop in those centers. It can be expectd that higher order central villages and larger central places will be patronized because of the attraction of their competitive goods and services and their ac c e s s i ­ bility resulting from regional development. An hypothesis that is co ncerned with the preferences of nonfarm families toward central villages It is hypothesized that nonfarm families, their decisions for shopping travel is also proposed. like farmers, make independently and use their experience subjectively in choosing to shop in a p ar ­ ticular center. They may also be attracted to a shoping place by its price advantages (an objective b e h a v i o r ) . The nonfarm family guestionnaire serves to determine how such choices are made. 58 Concerning Time Frame Because of significant changes in farming technology and tr ansportation de v e l op me nt in the study area over the period of 1950-1970, portant changes it is hy po thesized that the most im­ in the v i ab il ity of central villages, have occurred during this period, retail and wh ol esa le because several functions in trade have become outmoded and d i s ­ appeared, while several new and modern functions have emerged. Therefore, it is expected that the spatial d i s ­ tribution of the central villages studied has been changed due to changes in their vi ability over the study periods and shows greater differences the 1970-1980 period for the 1950-1970 period, than for (because of greater change in their viability in the first period.of the s t u d y ) . Procedures Study Area and Study Time To test the hy potheses presented in Chapter Two, central Michigan, and general an area wh ich is cha racterized by dairy farming at the present time with south- (Figure 2.1), was selected. This region is typified by dairy and general farming increased part -ti me farming throughout the region. The area Shiawassee, includes the counties of Ionia, Eaton, parts of Washtenaw. Ingham, Livingston, Indeed, Clinton, Jackson and major small portions of Montcalm, 59 Types of Farm ing Areas M IC H IG A N 1. G e n e ra l L iv esto c k a n d C orn 2. D airy, L iv esto c k a n d C o rn 3. S o u th w e s te r n Fruit, D airy an d T ruck 4. D airy, P o u ltry a n d T ru ck 5. Dairy a n d G e n eral F a rm in g 6. D airy, P art-T im e a n d T ru ck 7. Dairy a n d C a sh C ro p s 8. C a sh C ro p s a n d Dairy 9. G e n e ra l L iv esto c k a n d PartTim e 10. D airy, P o ta to e s a n d T ru c k 11. N o rth w e ste rn Fruit a n d Dairy 12 . D airy, P art-T im e a n d P o ta to e s 13. F o restry , P art-T im e a n d C attle 14. C attle, P o ta to e s a n d P art-T im e 15. C attle, H ay a n d P art-T im e 16. Dairy a n d P o ta to e s 17. D airy. P o ta to e s . P art-T im e a n d F o re s try Fig. 2.1 Adapted from Hill and Russell, "Types of Farming in M ichigan’ in Readings in the Geography of M ichigan, 1964, p. 182. 60 Gratiot, Kent, Barry, Calhoun, Hillsdale, Lenawee and Genesee counties are located in the region selected 2.2). (Figure The region selected is a region of homogeneous farm­ ing types in Michigan and is typical .from the point of view of topographic conditions, climate and general flatness of the region encourages agricultural including crops, economy. activities, cash crops and animal husbandry. Drainage has improved the quality of swampy areas and in general region is a favorable place for agriculture. The the The cities of Lansing and East Lansing are located near the center of the study area, while the central villages are located t h r o u g h ­ out the area. There are 46 such central villages in the region (Figure 2.3, 2.4) that range in po pulation from 155 to 3,816 with a mean of 1,019 persons (Table 2.1), thus providing con ­ siderable va riation in central village population sizes. To determine the normality of distribution of populations below, at or above the mean value, to standardize the data. 2.1. a Z score test was used The Z values are shown in Table Dividing the Z scale of those observations equal parts -.43 to +.43 (33.3 percen t of probabilities) into three at the points of Z values distributes the data into three zones. Z-values before -.43 are below the mean, from -.43 to +.43 they are around the mean and beyond +.4 3 they lie above the mean. As a result, 48 percent of the po pulation of Z-values are distributed in the zone below the mean, 26 percent around County Divisions S O U T H -C E N T R A L M IC H IG A N S h i a w a s s e e Genesee n g h a m W a s h t e n a w Hillsdale L e «n✓ a w e e X** Fig. 2.2 C ounty divisions in the study area. Central Villages P e rrin to n SOUTH-CENTRAL MICHIGAN M aple R apids 1980 H u b b a rd sto n Mu,r* „ • • F o w le r , • P ew am o Lyons ; S a ra n a c l ?#*>;■ • O vid V ernon^ : W estphalia .C la rk sv ille C aled o n ia * '. ’• F re e p o rt M o n ta e u t e O d essa * L w inon B ancroft • B yron * . S u n fieid W o o d lan d G am es. • L inden Eagle M uliken W ebberville • • • .V e rm o n tv ille . Fow lerville O im ondale N ashville D ansville • B ellevue S to c k b rid g e P in c k n e y , S p rin g p o rt C h e lse a . P a rm a . G ra s s L a k e : M an c h e ste r * ' C o n c o rd •H om er ' H anover Brooklyn . • • v. ■ C em ent City A d d iso n * Fig. 2.3 Relative location of central villages of South-central M ichigan on th e county division patterns, 1980. D ex ter 63 Rural Townships S O U T H - C E N T R A L M IC H IG A N I T o w n s h i p s in c lu d in g i C e n tra l V illages 1980 Fulton North Plains Venice Dauas Boston C aledonia Shlaw aosee. Games Veriibr Westphalia Campbell Boros Odessa W oodland [R oxaod Sunfieid Castleton Windsor Vermontvilie Handy Ingham 1 Bellevue Stockbridge Putnam Springport Sandstone Concord Homer G rand R a p id s . K a lam azoo. • F li n t .D etroit Hanover Columbia M an ch ester W oodstock A nn Arbor R dlm F ig. 2 .4 T ow nships th a t surround th e central v illag es o f th e study area. i Fenton i 64 TABLE 2.1: Popula tio n of Central Villages in 1980 and Their Z-Values Central Village 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. Brooklyn Dexter Chelsea Fowlerville Saranac Manchester Linden Pinckney Homer Addison Stockbridge Grass Lake Ovid Lake Odessa Bellevue Hanover Nashville Fowler Dimondale Sunfield Caledonia Webberville Cement City Lennon Concord Parma We stphalia Morrice Vermontvilie Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Mulliken Woodland Eagle Population 1,110 1,525 3,816 2,289 1,421 1,686 2,174 1,390 1,791 655 1,213 962 1,712 2,171 1,289 490 1,628 1,021 1,008 591 722 1,535 539 600 900 873 896 733 832 689 698 448 479 618 1,008 708 683 488 675 550 431 155 (Con't) Z-value .134 .748 4.140 1.880 .590 .990 1.710 .550 1.140 -.540 .287 .085 1.025 1.700 .399 -.783 .900 .002 -.017 -.634 -.440 .763 -.711 -.620 -.177 -.217 -.182 -.424 -.277 -.489 -.475 -.845 -.800 -.594 -.017 -.460 -.500 -.790 -.510 -.694 -.870 -1.280 65 TABLE 2.1: Cont Central Villages 43. 44. 45. 46. Clarksville Hubbaardston Gaines Dansville SD SOURCE: 348 421 440 479 1019.348 675.56 Z-Value -.994 -.885 -.857 -.800 o • o X Population 1 Population sizes for the villages were collected from U.S. De partment of Commerce, 1980 Census of Population: Number of Inhabitants vol. 1, Part 24 (Michig an ), January 1982. Z-values calculated by author. 66 the mean and 26 perc e n t in the zone above the mean. distribution of villages population sizes, This implied an a g ­ glomeration of vill a g e popu l a t i o n Z values on the left side of the curve with a positive fore, skeweness of 1.931. There­ most of the central villages were smaller rather than larger in their dev i a t i o n from the p o pulation mean. 46 villages were ch o s e n as rural central places, These because they are easily and p r a c t i c a l l y identified by the U.S. Cen10 sus Bureau of Population. The study of the hierarchical central villages volved a rural in­ settlement approach using some of the c o n ­ cepts of settlement g e o graphy and dealt w i t h the rural part (subsystem) of the w h o l e system of r ural-urban settlements in the study area. The central village s as rural nodes are distributed over the homgeneous region of southcentral Michigan. The physical and agricultural u n iformity in the formal region (hinterlands of central villages) of the study area is a d ­ justable within the assumptions of Christaller's classical 10 All the villages included in this resarch had p o p ­ ulations less than 2,500 persons; only Chelsea with 3,816 persons was an exception. This village was selected because it is called a "village" and is recorded as a township sub­ division in the U.S. 1980 Census Of Population: Number of Inhabitants (MI 1982). The village of Barton Hills was omitted because it was not recorded in Dun and Bradstreet's Reference Book (1950) and also because it was incorporated in 1970 (1980 Census of Population: Number Of Inhabitants, 1982:24-21). 67 central place theory. The highway and super highway d e ­ velopment in the study area, the same relative studied however, which does not allow location for all of the central villages (Figure 2.5), does not coincide with classical c e n ­ tral place theory's rigid assumptions of uniform d i s t r i ­ bution of central places on the network of transportation and marketing. It is the adjustment possible within the later modified central place studies which relaxes this rigid assmption. In defining a time dim e n s i o n for this study, the re­ searcher was c o n cerned w ith the period of the recent past up to the present day, the aim being to determine the processes of change in the v i a b i l i t y and spatial distributions of c e n ­ tral villages present. since 1950, w ith a break It was felt this w o u l d be most helpful ulation on future changes termined a thirty-year this in 1970, up to the study. in the subject area. for spe c ­ It was d e ­ investigation would be adequate for It is p a r t i c u l a r l y important that this c o i n ­ cided wit h the b e g i n n i n g of a significant post-World War II trend of farm mecha n i z a t i o n and modernization that has co n ­ tinued up to the present time. Census of A griculture For congruency of data (U.S. information with U.S. Census P o p u l a ­ tion d a t a ) , 1950 was chosen as the beginning year for the thirty-year study. Another significant point was 1970, be­ cause the income of farmers was raised considerably in the period of 1950-1970 (due to increased farm efficiency and Highway Patterns SOUTH-CENTRAL MICHIGAN 1980 Os 00 C entral Villages C ities of Lansing, East L ansing, a n d Jac k so n 1-94 In terstate R outes U.S. R outes S tate R outes G rand R apids .D e tro it Kalamazoo Fig. 2 .5 T h e relative location o f central villages of South-central M ichigan on the highway patterns of the study area, 1980. A n n A rb o r 69 farm i n p u t s ) . Finally, data were available, rent. 1980 was the last year for which so that information is reasonably c u r ­ The data wer e analyzed at these three points and the intervals in between. Because available data about farming improvements and farm income is identified by counties the U.S. Census of Agriculture, dividual farm figures, in and does not include in­ the farmers' q u e s tionnaire in A p p ­ endix B was the main source for some required data. Ques­ tions related to farm industrialization and management (adopting farm automation, tion) specialization and c o n s o l i d a ­ were key q u estions to identify individual past performances farmer's in farm and rural development. Data Sources General Data To collect the general data needed about rural d e v e l o p ­ ment (agricultural and t r a n s p o r t a t i o n a l ) in the study area, the M i c higan State Unive r s i t y Library and the Michigan D e ­ partment of T r a n s p o r t a t i o n in Lansing were consulted. Gen­ eral materials r e l ating to modified central place theory, behavioral geography, and previous empirical gathered at M i c h i g a n State University. studies were Information about regional super h i g h w a y development and transportation fac­ ilities, regional speed limitations and mileages of local roads and highways of central villages, were obtained from 70 the Library of the Michigan Department of T r a n s p o r t a t i o n in Lansing and through the questionnaires U.S. Department of Commerce, in 1952, 1972 and 1981) (Appendix B ) . Census Of Agricu l t u r e was used only for general The (issued infor­ m ation about trends of agricultural census in the 16 counties studied (Figure 2.2) for the years of 1950, 1969, and 1978, because detailed information c o ncerning a g r i c u l ­ tural development was gathered by the researcher through field surveys. To obtain data on the numbers and types of functions and establishments and Bradstreet, employed. in the villages, Reference Books for 1950, the Dun 1970 and 1980 were In these directories all a g g l o merated settlements (urban and rural) of the U.S. are c ategorized by a l p h a b e t i ­ cal order, and most of the functions for each settlement are depicted. Therefore, were very useful the Dun and Bradstreet directories for comparing data about the functions of each central village at the three points in time. A useful supplementary source was the local Telephone Directories for 1970 and 1980 that included data about current functions and services of settlements, function and service. determining rural arranged in alaphabetical order by These were particularly useful services such as attorneys, for schools and churches that were not mentioned in the Dun and B r a d s t r e e t , Reference Books. To gather the data concerning agricultural development and rural in the rural communities of the study area, two types of questionnaires were developed. questionnaire (Appendix B) that was filled out in i n t e r ­ views with two knowledgeable persons lage in each sampled v i l ­ (such as the clerk of the village or township, teacher, civic One was a public a librarian or other educated person active in the life of the a r e a ) . The interview format of the public q u e s tionnaire was designed to extract information about specific local populations and the social and economic a s ­ pects of particular villages during the study period. sponses to questions Re­ involving the changing functions of grain elevators and railroads in transporting grains and cash crops to central villages were c r o s s-checked wit h m a n ­ agers of elevators. A nother questionnaire was prepared to record interviews w ith individual farmers of the study area This (Appendix B ) . interview format was devised to determine individual characteristics, perceptions, and preferences of farmers, their rationale in farm d evelopment and their functional behavior in regard to the rural in the past and present. services of central villages A nonfarm questionnaire (Appendix B) was also prepared and administered to nonfarm families the study area to determine the individual preferences of nonfarm people toward the central villages sampled. rationale for including nonfarm people as well as the farmers was because of the increase in the nonfarm The in 72 popu l a t i o n in the rural townships of the study area over the study period. .Sample Villages For Field Survey It should be noted that, as a sample, 18 of 46 central villages (39.13 percent) in the study area were selected for 11 the field survey. The eighteen sample villages were drawn from the six hierarchical orders of central villages. 2.2 shows the order of all the villages regard to their functional indices Table in the study area in in 1980 (functional c l a s s i f i c a t i o n is d i s cussed in Chapter F o u r ) . index The purpose of taking a sample of villages from the ordered list was to apply stratified random sampling method, stratum. (Taylor, it was possible to take an equal 1977:75). By this sample from each Villages w i t h i n each stratum were similar and homogeneous, but d i f ferent from villages of other strata. Three villages from each strata were selected randomly for field surveying. Choos i n g three villages for each strata was the best possible choice, because the first group of villages c o n tained only three villages; therefore, this 11 For the rest of the analysis (such as tables of functional index, correl a t i o n and regression models, and patterns of points for nearest neighbor analysis), all 46 villages were used because small samples can cause problems in these measures. 73 TABLE 2.2: Central Villages Ordered by Their Functional dices, 1980 Villages Functional Indices First Order Villages 1. Brooklyn 2. Dexter 3. Chelsea 1,024.45 1.012.23 9 8 6.53 Second Order Villages 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 615.25 563.19 519.41 515.13 484.33 465.47 458.00 Third Order Villages 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 377.21 374.92 369.57 360.68 Fourth Order Villages 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 305.61 290.84 257.45 249.11 225.94 211.86 Fifth Order Villages 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 188.13 18 7.51 173.43 15 2.17 151.05 144,43 144.12 114.48 In­ 74 TABLE 2.2: Cont Villages Functional Indices Sixth Order Villages 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontvilie Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardstoi Gaines Dansville SOURCE: 93.33 86.41 81.66 69.30 51.46 51.21 41.12 40.66 36.02 35.57 35.34 34.66 27.48 17.07 16.46 16.43 15.41 14.41 Author's cal c u l a t i o n s b ased on Appendix A: Table A . 3. 75 method permitted an equal villages. sample size per class of central The selected villages were: First Order Brooklyn Dexter Chelsea Second Order Saranac Pinckney Homer Third Order Stockbridge Ovid Lake Odessa Fourth Order Hanover Nashville Dimondale Fifth Order We b b e r v i l l e Concord Westphalia Sixth Order Byron Maple Rapids Dansville These eighteen sampled villages also served as the s u b ­ jects for individual spatial b e h avior measures to examine how the farm and nonfarm families these villages in townships surrounding interact in their shopping perferences with these villages compared with other central study area. places of the In order to assure the v a l i d i t y of the farm and nonfarm questionnaires a p r e l i m i n a r y survey was done in the townships surrounding the villages of W ebberville and Fowlerville in June personal 1983. The exper i e n c e showed that the interview yiel d e d the highest rate of adequately filled-out questionnaires and also suggested that five c o m ­ pleted farm family questio n n a i r e s (Appendix B) pleted nonfarm family q u e stionnaires best possible goal village. and five c o m ­ (Appendix B) were the for a one day survey in each selected This goal was also supportive of the time and b u d ­ get considerations of the researcher. In order to select the samples of farm and nonfarm families, the Atlases and platbooks of Michigan for each central village and its r e ­ lated township (1980) were used. The technique of random 76 point sampling was chosen because the square patterns of townships and their sections, dotted with isolated farmsteads and rural dwellings, resemble patterns which Taylor recommends for the use of this method (1977:77). The selected farm and nonfarm families of the study area are shown in Figures 6.1.1 and 6.1.2. Sampled Rural Functions (Goods And Services) ' To determine the impact of f a r m e r s ’ individual and p e r ­ sonal characteristics and their shopping habits on changes of v i a b i l i t y and spatial d i s t r ibution of central villages was necessary to take a sample of goods and services, cause there were more than 115 different functions wholesale, and services) nonfarmers' (retail, The selected functions were examined by using the f a r m e r s ’ and questionnaires, with each sampled function o r ­ iented in regard to the subjects' questions. be­ in central villages of the study area at the time of the study. (goods and services) it responses to the related In other empirical works, several different functions have been examined to explain the pattern of shopping choices of consumers. ing, shoes, dentists appliances, banks, in M u r d i e 's work For instance, auto repairs, (1965); groceries, chemist drugs, flowers, pairs and toys in the work of Davies shops in Burnett's wor k hairdressing, (1973); food, cloth­ doctors and kinds of foods, hardware, shoe re- . (1969); women's wear department stores in 77 C a d w a l l a d e r 's research Williams' study Brooker-Gross search (1975); (1979); (1981); grocery purchases shoe stores in the r e s earch of and retail food stores in Hall's r e ­ (1983) . In order to select the rural functions vices) in for this research, (goods and se r ­ the researcher used a stratified r a n d o m sampling of the location coefficients of central functions cited in Table A . 3. These coefficients were ordered by computer and then classified in ten groups using natural breaks classification was used, because servations (Table 2.3). This technique it tended to put the same values of o b ­ in the same group. Table 2.3 shows that eight groups have the same ranges while only the first and second group differ of rural in their upper and lower limits. Ten classes functions were considered reasonable given the time co n siderations and optimal benefit to this research. f u n ction was drawn randomly from each strata. tions drawn (Table 2.4) were nonfarmers' questionnaires. and In order to identify the p r o ­ and nonfarmers' individual characteristics and preferences (hierarchical other central places) The ten f u n c ­ inserted in the farmers' ba b ility of association between farmers' shopping centers Then a toward their order central villages and and these ten selected functions, a chi-square test was applied to each of the ten sampled functions. freedom" The (df) "factors," and the "chi-square values," "amount of probability" "degrees of are shown in 78 TABLE 2.3: Functional Rank Ranks and Classes of Rural Functions (Goods and Services) in the Order of Their Location Coefficients. Lo c a t i o n Coefficient Functions in the Order of Their L o c ation Coefficients Class I 1 2 3 4 5 6 7 8 9 10 11 12 0.51 1.45 1.54 1.56 2.08 2.13 2.63 2.77 2.77 . 3.12 3.12 3.22 13 3.33 14 15 16 3.33 3.70 4.00 17 18 19 4.54 4.76 5.00 Class Church School Grocery Store Doctor's Office Hardware Store Bank Gasoline Service Station Eating Place (Restaurant) Dentist V e t e r inarian Attorney Lumber and Other Building Materials Dealer Motor Vehicle Dealership (New and Used) D rinking Place (Bar) Barber Shop Farm and Garden Machinery and Equipment Drug Store Farm Supplies Grain Elevator II 20 21 22 23 24 6.25 6.66 6.66 7.14 7.69 25 26 27 28 29 30 31 32 8.33 9.09 9.09 9.09 9.09 9.09 10.00 11.11 N o ndurable Goods Florist Sporting Goods Store Furniture Store Miscellaneous General M e r ­ chandise Store Women's Ready-to-Wear Store Gift Shop Liquor Store Radio and Television Store Auto and Home Supply Store Variety Store Automotive Parts and Supplies Optometrist 79 TABLE 2.3: Cont Functional Rank L o c ation Coefficient Functions in the Order of Their L o c ation Coefficients 11.11 11.11 11.11 Repair Shop General Automotive Repair Shop Funeral Service 12.50 12.50 12.50 Clinic Petroleum (W.S.) Durable Goods (W.S.) 14.28 14.28 14.28 14.28 14.28 Radio & T e levision Repair Shop Fuel Oil Dealer Jewelry Store Boat Dealer Retail Nurseries, Lawn and Garden Supply Store 44 16.66 45 46 16.66 16.66 47 16.66 Sewing, Needl e w o r k and Piece Goods Store Floor Covering Store Men's & Boy's Clothing and F urni s h i n g Store C ons t r u c t i o n Materials Class II 33 34 35 Class III 36 37 38 Class IV 39 40 41 42 43 Class V Class VI 48 49 20.00 20.00 50 51 52 20.00 20.00 20.00 53 20.00 Cigar Store Miscellaneous Home Furnishing Store F amily Clothing Store Mobile Home Dealer Petroleum Bulk Stations and Terminals (W.S.) Industrial Supplies 80 TABLE 2.3: Cont Functional Rank Location Coefficient Functions in the Order of Their L o c a t i o n Coefficients 54 55 25.00 25.00 56 57 58 59 60 25.00 25.00 25.00 25.00 25.00 61 25.00 B o w l i n g Alleys R e u p h o l s t e r y and Furniture Repair Data P r o c e s s i n g Service M i s c e l l a n e o u s Retail Store L i q u i f i e d Pet r o l e u m Gas Dealer Used Mercha n d i s e Store Paint, Glass and Wallpaper Store Lumber, Plywood and Millwork (W.S.) Class VII * Class VIII 62 33.33 63 33.33 64 33.33 65 66 33.33 33.33 67 68 69 33.33 33 33 33.33 Class Engineering, Architectural and Su rveying 'Service Electrical and Electronic R e ­ pair Shops R e f r i g e r a t i o n and Air C o n ­ dit i o n i n g Service & Repair M o t o r c y c l e Dealer Motor V e h i c l e Dealer (Used Only) Meat and Fish Market D e p a r t m e n t Store Sporting & Recreational Goods and Supplies IX 70 71 72 50.00 50.00 50.00 73 74 75 76 77 78 50.00 50.00 50.00 50.00 50.00 50.00 79 50.00 Armature Re w i n d i n g Shop Truck Rental and Leasing E q u i p m e n t Rental and Leasing Service A d v e r t i s i n g Agency H otel/Motel and Tourist Courts Hobby Shop Music Store H o u s e h o l d App l i a n c e Store M i s c e l l a n e o u s Apparel & A c c e s s o r y Store A u t o m o t i v e Dealer 81 TABLE 2.3: Cont Functional Rank Class Location Coefficient Functions in the Order of Their Location Coefficients IX 80 50.00 81 50.00 82 83 84 50.00 50.00 50.00 85 50.00 Recreational and Utility Trailer Dealer Candy, Nut and Confectionery Store Meats and Meat Products Groceries, General Line (WS) Professional Equipment and Supplies (WS) . Poultry and Poultry Products Class X 86 87 88 89 90 91 92 93 94 95 96 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 97 98 99 100 100.00 100.00 100.00 100.00 101 100.00 102 100.00 103 104 100.00 100.00 105 106 100.00 100.00 107 108 100.00 100.00 Hospital Weld i n g Repair Car Wash Outdoor Advertising Service Miscellaneous Personal Service Carpet & Upholstery Cleaning Dry Cleaning Plant Power Laundry Fuel & Ice Dealer Mail Order House Drapery, Curtain & Upholstery Store Shoe Store C hildren's & Infants' Wear Miscellaneous Food Store Retail Bakeries, Baking and Selling Fruit Store and Vegetable Market Freezer and Locker Meat Provisioners Beer and Ale (WS) Farm Product Raw Materials (WS) Livestock (WS) Groceries and Related Products (WS) Dairy Products (WS) Industrial and Personal Paper Service (WS) 82 TABLE 2.3: Cont. Functional Rank Location Coefficient Functions in the Order of Their Location Coefficients 109 110 100.00 100.00 111 ' 100.00 112 100.00 113 114 115 100.00 100.00 100.00 Stationery Supplies (WS) Transportation E q u ipment and Supplies (WS) Service Establishment E q u i p ­ ment and Supplies (WS) Industrial Machinery and E q uipment (WS) Plumbing and Heating (WS) Metal Service Center (WS) Furniture (WS) Class X SOURCE: Data was derived from Table A . 3, cl a s s i f i c a t i o n of the functions in 10 groups was done by the natural breaks me t h o d (using computer) 83 TABLE 2.4: Fre­ quency 19 Ranges of Rural Functions' Location Coefficients and the Sample Functions Drawn From Each Range Range of Rural F u n c ­ tions' LocationCoefficients .51 - 5.00 Sample Functions Sampled Functions! Location Coefficient Grocery Store 1.54 Optometrist 11.11 12.50 - 12.50 Clinic 12.50 5 14.28 - 14.28 Jewelry Store> 14.28 4 16.66 - 16.66 Floor C o v ering 16.66 Store 6 20.00 - 20.00 Family Clothing Store 20.00 8 25.00 - 25.00 Paint, Glass & Wallpaper Store 25.00 8 33.33 - 33.33 Department Store 33.33 16 50.00 - 50.00 Automotive Store 50.00 30 100.00 -100.00 Shoe Store 100.00 16 6.25 - 11.11 3 SOURCE: Data was deri v e d from Table 2.3 and samples were selected from each of the ten groups by stratified r andom sampling. 84 r elated tables 6.1.1 and 6.1.2 for each selected function. Finally, a chi-square "probability scale" (Taylor, 1977: 111-113) was constr u c t e d for each function examined 6.1.3). The c h i-square "probability scale" practi c a l l y and (Figure con v e n i e n t l y shows the clustered factors with similar p r o ­ babilities w h i c h contribute to an a ssociation between farmers' and nonfarmers' preferences individual characte r i s t i c s and (observable p e r s o n a l i t y ) , and the selection of one of the ten sampled functions in a certain village or a certain central place of the study area. The results for each examined function can be ge n e r a l i z e d for other func­ tions in the same class of location coefficients. This shows which factors have s i g n ificantly influenced changes of v ia b i l i t y and the spatial distributions of central villages. Maps Diagrams, Tables and Graphs To compare the spatial d i s t r i b u t i o n p a t terns of central villages, 1970, in regard to their hierarchical order, and 1980, maps and diagrams were prepared. discussions of this subject are found in Chap t e r economic M o d eling of Central Villages. show the directions of individual in 1950, Detailed IV: Socio­ Maps are provided to spatial preferences in s election of one of the ten sample functions or services in a certain central village or a certain central place in the study area. This information was obtained from the survey of farm and nonfarm families. 85 Tables and diagrams provide the results of c o r r e l a ­ tions (relations between p o p u l a t i o n and function) square tests and chi- (relation b e t w e e n individual p r eference and selection of a function) using log-linear regre s s i o n and chi-square p r o b a bility scales. Graphs are used to show the changes in frequencies of a cert a i n variable (such as p o p ­ ulation of the villages and agricultural data) over the time period of the study. Data Coll e c t i o n And Analysis To verify the hypotheses proposed for this research, the following analytical methods and techniques were used. 1. A functional index of c l a s s i f i c a t i o n w i t h final grouping by an analysis of v a r iance has b een used to d e t e r ­ mine the accuracy of the hierarchical central villages are classified; order into which the an f-test has been applied. A hypothetical model of functional index cl a s s i f i c a t i o n is shown in Table 4.1. 2. To examine relationships b e t w e e n villages' tion sizes or p o pulation served and numbers of functions (townships' (wholesale, retail popula­ population) and services) in the villages the c o r r e lation and regre s s i o n analyses were used (Figures 4.4, 3. 4.5, 4.6, 4.7 and 4.8). To describe the changes in the agricultural tech­ nology and transport d e v e l opment in the region and their 86 ,impact in changing the viability and spatial distribution of central villages over the study time, Reference Book, U.S. Dun and B r a d s t r e e t , Census Of Agriculture, related regional d e v e l o p m e n t documents and the survey questionnaires dix B) were used. (Appen­ Diagrams and figures have been prepared (Chapters Three and F i v e ) . 4. For determ i n i n g the dot pattern of spatial d i s t r i ­ bution for the central villages the study period, sis" was used in each different class over the technique of "nearest neighbor a n a l y ­ (Table 5.20). The s t andardization of village patterns by this technique was useful toward regul a r i t y 5. (dispersal) in explaining change or irregularity (random). "Chi-square probability scales" were used to d e ­ termine the factors w hich influence the viability and s pat­ ial d i s t ributions of central villages. thesized that there As it was h y p o ­ is an association between the choice b e ­ havior of an individual (farmer or nonfarmer) in shopping' for a cert a i n good at a certain central place and a p a r t i ­ cular factor (such as age, income, distance, etc.), the f a c ­ tors examined in the survey questionnaires were tested by chi-square analysis, tabulated and then arranged on chi- square p r o b a bility scales (a hypothetical model was p r e ­ pared to show the procedure (i.e., Tables 6.1.1 and 6.1.2 and Figure 6.1.3) . 6. Shopping travel mileage for farm and nonfarm fam­ ilies for a certain function (department store, shoe store, 87 etc.) wer e measured and their mean values and s tand­ ard deviations were c alculated nique was helpful (Chapter S i x ) . This t e c h ­ to show the probable ranges of certain functions. All of these techniques are discussed in greater d e ­ tail at the points w here their results are reported in this research. L imitations There were some problems First, in c o nducting this research. pre-1965 Dun and Bradstreet, Reference Books were not available in the M i c h i g a n State University or State of M i c h i g a n libraries. Because they are voluminous and c o n ­ sume so much space, they were available only in the Library of Congress and at Dun and Bradstreet's New York office. Likewise, copies of the Michigan Bell Telephone Directory for the study area w e r e available only for 1980 at the M i c higan State and State of Michigan Libraries; reasons, for the same the former years were not readily available. Therefore, Bradstreet, to obtain the required data from the Dun and R e ference Book for the year visited the Library of Congress, telephone directories for 1970 1950, the researcher in Washington, (Michigan) D.C. The were obtained at the D etroit Public Library. As another problem, the 1950 telephone directories M i c higan were not applicable to this research, for because the 88 rural services for several settlements were listed together. D e l i n e a t i o n of w hich services belon g e d to w hich villages was thus impossible. Therefore, ification of central villages in the functional in 1950 vices men t i o n e d in Dun and Bradstreet, 1950, index c l a s s ­ (Table A.l) only ser­ Reference Book for have b e e n used. The sixteen counties w hich were either wholly or p a r t ­ ially wi t h i n the b o undaries of the study region each had individual (Figure 2.2) listings of p o pulation and agricultural census data for the per t i n e n t points of the study time. Therefore, to be objective in c o llecting the data, lated data for each individual county to be taken and c onsidered as a whole. the r e ­ in the study area had In other words, there was no o b jective and justifiable way to delineate census data for the past of a county wi t h i n the study area a part from data for that w hole county. S ignificance of the Study The applic a t i o n of revised central place theory, with e mphasis on the behavioral preferences of farmers and n o n ­ farmers who are the main consumers (trade centers), pact of rural helps to resolve in central villages issues concerning the im­ d e v e l opment and farmers' shopping behavior on the via b i l i t y and spatial dist r i b u t i o n of central villages in southcentral Michigan, analysis. using comparative and explanatory The ap p l i c a t i o n of the theory at three points in 89 time (1950, 1970, 1980) in a cross-sectional approach helps to identify the rank/size relationship of central villages, the hierarchical structures of central villages, underlying interrelationships between the d i f ferent orders of villages and significant agricultural and transportational d e v e l o p ­ ments that have taken place in the study area 1980). Indeed, tions) 1970, the analysis of individual characteristics and preferences of farmers and nonfarmers ping choices (1950, (biased behavioral choices) in making s hop­ for certain f u n c ­ in the different orders of central villages discloses how much the via b i l i t y of these villages dividual human behavior and preferences. is d e pendent on in­ In general, the results of the analyses of past and present situations will be helpful in suggesting recommendations for the future v i a ­ b ility and spatial dis t r i b u t i o n of central villages. may also be useful in regional p l a nning for settlement d e ­ velopment and establishing new functions, other functions, They or eliminating in the central villages. A significant aspect of this research is that this area (southcentral M i c h i g a n ) , for the t hirty-year period of this research, has not been subjected to examination on the basis of the assumptions of revised central place theory wit h an emphasis on farmers' ences. Indeed, individual characteristics and p r e f e r ­ this -study has con c e n t r a t e d on the rural portion of the study area's rural- u r b a n system (Bra c e y ,1962; 90 and Johansen and Fuguitt, 1973; have studied the h i e r a r c h i ­ cal order of such central villages consin) . In sum, in Engl a n d and W i s ­ this study was intended to determine the existence of hierarchical orders of central villages and their various co m p e t i t i v e reactions to rural de v e l o p m e n t and farmers' choice behavior. changes in the hierarchical over the study period. It was also intended to show structure of central villages C HAP T E R THREE R URAL DE V E L O P M E N T IN SOUTHCENTRAL MICHIGAN E s t a b l i s h m e n t Of Early Rural Settlements E arly rural settlements of white immigrants central M i c higan were b egun after the 1830s. C o n c o r d was e stablished in 1831 (Hinkley, 1832 (Homer's Bicentennial Comm., 1836 (Westp h a l i a Area H i s t o r y , 1976), early 1830s Webberville 1971:31). in 1871 263; 1976), and and S c a n d i n ­ and stopped briefly in New York they migrated to Detroit Stockbridge Area Bicentennial Comm., The pres e n t farmers of southcentral Michigan m i ­ grated from N e w York Germany, in Stockbridge in the the British Isles, using the Erie Canal, 1972:260, 1976:16). Westphalia The early immigrants to the Midwest and southern then, (Hart, Homer in (Webberville Area Centennial Book Comm., They entered the U.S. City; For example, 1976:9), (Stockbridge Bicentennial Comm., Mi c higan came from Germany, avia. 1976:4), in south- England, or Detroit with their family origins in S candinavia and other European countries. Most of the early settlers were farmers who came to M i c h i g a n in search of farm land to grow crops, wheat. The farmers' typical particularly first rural homestead was a 91 92 handhewn log cabin for shelter, surrounded by land that was cleared from dense forests and prepared for cultivation. Oxen were used in the early immigrants' they were cheaper than horses der; settlements because in their use of coarse fod­ horses were used for hauling crops to market. horses became typical work animals on farms. was based on carrying crops stock farming and dairying tennial Committee, pp. (wheat, corn, (Hart, Later, Agriculture p o t a t o e s ) , live­ 1972:266; Homer's B i c e n ­ 4,5; W e s t p h a l i a Area History, 1976). This type of farming has remained dominant in southcentral Michi gan up to the present time, ized by the agricultural but has been r e v o l u t i o n ­ i n d u s t rialization in the region. W hen railroad tracks were ern Michigan it was a vital laid in the 1830s in s outh­ step in c o nnecting the rural settlements to major markets. In some cases villages grew up around the site of a train station in a township, such as Fowler village in Dallas Township w hich was established in 1857 (Fowler Centennial Comm., 1957:4). In other cases the railroad was extended to connect existing villages to the larger centers and cities. For example, the villages of Dexter and' Chelsea were c o nnected by railroad extensions to Ann Arbor in 1840 and Comm., 1976:16). 1841 (Stockbridge Area Bicentennial The gravel primary roads established in the villages and their surrounding townships eventually b e ­ came paved roads for motor t r a nsportation in the study area in later decades. 93 The typical features of early rural southcentral Michigan (1830s and 1840s) streets that gave access smith shops, taverns, to some small grocery stores, garage for livery wagons, as the post office, village doctor. settlements were graveled main stores such as b l a c k ­ a village hotel, and some other rural district school in and services such and the office of the These features were responsive to the limited demands of farmers (new settlers) who countryside around the e a r liest settlements lived in the in southcentral Michigan. Technological d e v e l o p m e n t in agriculture and t r a n s p o r ­ tation facilities has chan g e d significantly the of these farmers and their farming operations tieth century. Technological changes that offered simple specialization; development here. life styles features of the early villages local functions. theses of this research, in the t wen­ in agriculture and transportation a s sociated wit h today's rural have changed these typical lifestyles Regarding the h y p o ­ agricultural m e c h a n i z a t i o n and farm consolidation; and transportation in the region since 1950, will be discussed It will be helpful to investigate the impact of these regional rural developments in chang i n g the v i a bility and spatial d i s t ribution of villages in the study area. 94 Agricultural Mechanization According to the Census of Agriculture in the United States, USDA publications and bulletins and several issues of the Michigan F a r m e r , important farm mechanization took place in Michigan in the period agriculural mechanization, such as tractors, Along with w hich included farm machinery motor trucks, significant advances of farming, 1950 to 1980. and cornpickers, in the chemical such as fertilizers, there were and biological aspects herbicides and h y b r i d i z a ­ tion over the period of the study (Cochrane, 1977). The impact of this agricultural m o d e rnization has been increased farm output and productivity. (1969:71) Moyer, Harris and Harmon note that m e c h anization has been one of the main reasons for a rapid increase of farm output in the U.S. over the past few decades. Draft animals (mules and horses) and tractors provided the wor k power on farms in southcentral Michigan in 1950. A c c ording to the U.S. Census of Agriculture, cent of farms had mules in 1950 only one p e r ­ (.02 overage mules per farm), while 26.7 percent of farms used horses for work power (.61 average horses per farm). the majority (55.83 percent) ated wit h tractors only. ticularly horses of farms According to Table 3.1 in 1950 were o p e r ­ The rest used draft animals, in addition to tractors. of draft horses declined, The total number due to increased tractor use, the study area over the study periods par­ (Figure 3.1). in While 95 TABLE 3.1: Source of work power Total Number Percent Value NOTE: SOURCE: Number and Percentages of Work Animals and Tractors on Farms in 16 Counties of Southcentral Michigan, 1950 No Tractor, Horses or Mules Only No Tractor & O nly 1 Horse or Mule No T r a c ­ tor- & 2 or More Horses Tractor & horses and/or Mules Tractor & No Horses or Mules 8040 966 3592 8532 26706 16.81 2.02 7.51 17.83 55.83 The total number of farms in 1950 was 47,836 in the 16 counties of southcentral Michigan included in the study area. Derived by the author from county data provided in the 1950 U.S. Census Of Agriculture For The State of Michigan. 96 Horses and Colts per County C o u n tie s o f S o u th - c e n tr a l M ic h ig a n : C o lt s 2000- Tota l Horse s 2500- and 3000- 1950, 1 9 6 9 . 1978 1500- 1000500- A 0 -- '■o T o t a l P o p u l a t i o n ol H o r s e s a n d Colts P e r c e n t of F a r m s H a v i n g H o r s e s a n d C olts Average N um ber Per F arm 30.000-| 2 0 .0 000 0- “ } 50 - 10 .0 0 0 - 0-1— 1 ™ F i g u r e 3 t P o p u l a t i o n o f h o r s e s a n d c o l t s by c o u n t i e s a n d t h e i r d i s t r i b u t i o n b y a v e r a g e a n d p e r c e n t a g e v a l u e s rn 16 c o u n h e s o f s o u t h — c o n t r a ) M i c h i g a n D a t a c o l l e c t e d f r o m t h e U .S C e n s u s o f A g r i c u l t u r e for 19 50 1969 a n d 19 78 Wheel Tractors per County C o u n tie s o f S o u th - c e n tr a l M ic h ig a n : 1 9 5 0 , 1 9 6 9 ,1 9 7 8 Tot al W he el Tractors 5000- 4000- 3000- 20001Q00- 0- T o t a l P o p u l a t i o n of W heel T ractors A verage N u m b er Per Farm 10 0 ° * 6 0.000- 4 0.000- 2 0 .0 0 0 - P e r c e n t o f F a r m s H a v in g Wheel Tractors \A ki c-9& V? Qv>& F ig u r e 3 2 P o p u l a t io n o f W h e e l T r a c t o r s tjy c o u n t i e s a n d t h e n d i s t r i b u t i o n bv a v e r a g e a n d p e r c e n t a g e v a l u e s in 16 c o u n t i e s ot s o u t h — c e n t r a l M i c h i g a n D a t a c o l l e c t e d t r o m t h e U S C e n s u s Of A g r i c u l t u r e lo r 1 95 0 1969 a n d 1978 97 the percent of farms with horses was reduced, number of horses per farm increased. This the average increase was re­ lated to scientific horse br eeding and the increased re c re a­ tional use of horses in the study area since 1969. The introduction of the tractor as the work power on farms tury in the United Sates in the very early twentieth c e n ­ (Cochrane, 1979:108 and Wik, 1980:26) the use of draft animals for farm power. crease almost replaced A dramatic in­ in the number of tractors on Ame rican farms in the 1920-1960 period (Cochrane, 1979:108, 122) continued in the 16 cou nties of the study area during the first period of the study (Figure 3.2). tractors 1978 in 1950, 89 percent (Figure 3.2). of wheel power, Seventy percent of farms had wheel in their design and sop histication in the 1950-1980 period in the study area (for related literature, G r e v i s - J a m e s , Jones and Batchelder, Cochrane, in The increased popularity of efficiency tractors was accompanied by advances speed, Bloome, in 1969 and 93.6 percent 1979:122, see 1980:115; 156,197 and Michigan F a r m e r :1970, 1980). Along wi th the significant impact on farm mec hanization of wheel bines) tractors in the study area; cornpickers (corn c o m ­ were the other type of farm machinery adopted in larger numbers by the farmers of the study area 3.3). Ownership of motor trucks, as vehicles (Figure for hauling some farm products also increased among the rural farm families (Figure 3.4). 98 Corn Pickers per County C o u n tie s o f S o u t h - c e n t r a l M ic h ig a n : 1 9 5 0 , 1 9 6 9 , 1978 1200- Tota l C o r n p i c k e r s 1000- 400- V T o t a l P o p u l a t i o n of C ornpickers V P e r c e n t o f F a r m s Ha v in g C ornpickers A verage N um ber Per Farm 15.000- 10000“ 40 -n— ~ m r 5 .0 0 0 - o --------- Ej J i— <£>A* F i g u r e 3 . 3 P o p u l a t i o n o f C o r n p i c k e r s by c o u n t i e s a n d t h e i r d i s t r i b u t i o n bv a v e r a g e a n d p e r c e n t a g e v a l u e in 16 c o u n t i e s of s o u t h c e n t r a l M i c h i g a n D a t a c o l l e c t e d f r o m t h e U.S. C e n s u s of A g r i c u l t u r e for 1 9 5 0 1969 . a n d 1978 Motor Trucks per County 1 9 5 0 , 1 9 6 9 ,1 9 7 8 Tota l M ot or t ru ck s C o u n tie s o f S o u t h - c e n t r a l M ic h ig a n : T o t a l P o p u l a t i o n of M otortrucks A verage N um ber Per Farm P e r c e n t o f F a r m s Ha v in g M otortrucks 30.000 20.000 50%- 10.000- F i g u r e 3 4 P o p u l a t i o n of M o t o r t r u c k s by c o u n t i e s , a n d t h e i r d i s t r i b u t i o n by a v e r a g e a n d p e r c e n t a g e v a l u e s in 16 c o u n t i e s of s o u t h c e n t r a l M i c h i g a n D a t a c o l l e c t e d f r o m t h e U.S . C e n s u s of A g r i c u l t u r e f o r 1950. 19 6 9 1978. 99 Biological and chemical de ve lopments in agricultural techniques included the introduction of better varieties of seeds, new fertilizers, and pesticides and herbicides which increased yields per acre in the study area over the study periods. Greater efficiency in livestock production and specialization of farms (Table 3.2) also changed the rural scene, which in the last thirty years has undergone a v i r ­ tual revolution (particularly from 1 9 5 0 'to 1970) in farming methods with resulting and as sociated changes in rural life, both in the United States as a whole and in the region of this study. In summary, the study region has benefited from a g r i ­ cultural mechani za tio n in the dire ct ion of greater p r o ­ ductivity and ef ficiency in farm operations. Local central villages that supplied functions for the ho rs e-powered farm ­ ing carried out with un so ph isticated farm machinery in the 1950s, had to change their functions to those demanded by the mechanized and sophisticated farm operations prevalent in the area by 1978. Specializ at io n On a map of Michigan, the study area for this research is characterized by dairy and general farming (Figure 2.1). Details drawn from the farm family questi on na ire indicate that feed crops (oats and corn, hay, p a s t u r a g e ) ; cash crops TABLE 3.2: Average Number of Livestock Per Farm and Per ce n­ tages of Farms Raising Livestock in 16 Counties of Southcentral Michigan for 1950, 1960, 1978 Average # of Cattle & Cows Per Farm Percent of Farms Raising Cattle & Cows Average Number of Milk Cows Percent of Farms With Milk Cows Average Number of Hogs and Pigs Percent of farms Raising Hogs & Pigs 1950 11.92 75.27 5.50 69.90 6.78 41.71 1969 19.82 45.41 5.58 19.74 10.57 16.50 1978 21.93 41.84 6.89 15.23 15.32 15.02 SOURCE: (wheat, Data coll ect ed from the U.S. for 1950, 1969 and 1978 beans and soybeans); and h o g s ) ; and dairying, these agricultural farming minority, livestock (beef cattle, steers along with various combinations of activities, in the study area. volved in truck Census Of Agriculture (vegetable) are pre dominant features of The farm families who are in­ and fruit farming are in the although most farmers raise fruits and vegetables for their own consumption. While fruit orchards are more common in w est ern Mi ch ig an and bean farming on the east side of the state, southcentral their it is apparent that most of the farmers region put their fields in the into feed crops to feed livestock. The trend to spe cialization is evident in ies as it is throughout Michigan and the U.S. these c ou nt ­ Durost and 101 Bailey (1970) point out that Am erican farmers are becoming increasingly more specialized co mpared wit h their situation in the past. farfas, Farmers in the past had highly diversified in that farms ap proached self-su ff ic ien cy through a high degree of com pl em en ta ri ty betwee n their livestock en ­ terprises and their p ro du ct ion of feeds for livestock. Spe cialization of agriculture, as a profi ta ble business, is concentrated on the pr oduction of a certa in crop such as wheat, or may cover all phases of producing, marketing a partic ul ar commodity, processing, and such as growing feed for dairy cows and pr o d u c i n g fluid milk or other milk products for the consumer market (Kellogg and Everett, Interviews wi t h farm families 1970:322). in the study area iden­ tified specialized farm operations, including dairying, production, horse raising, raising purebr ed sheep, and truck farming. farming, beef and grain Among these specialized types of dairying is the most expensive and most profitable. The dairy farmers were found to have the highest incomes among farmers 49) in the study area. Stewart and Davis (1980: note that "Dairy produ ct io n is an important agricultural enterprise in the United States, agricultural income placing first to third in in 16 of the 50 states." It should be noted that improvements in agricultural mec hanization and tr an sp o rt at io n have favored the speci al ­ ization of ag ri culture in the st.udy area. milking machines on dairy farms For example, in Mi chigan in 1950 were 102 simple and time-consuming. By 1970 they had become more sophisticated and more efficient. "Milking Parlors" by 1980 were fully au tomated with many time saving improvements and increased fluid milk production 6, 39-71; 1971: September faced S-12; 1950: (Michigan Farmer, 29-213; September February 1980:56; Jan. 1971:20; 1949: March and March 1981:43). The number of farms reporting they had milking machines in the 16 counties of the study area, percent) in 1950 to 7,397 declined from 15,940 (33 12 (23.8 percent) in 1964. This was associated with the overall reduction in dairy farms and the increased number of milk cows per farm. percent of farms had milk cows, 15.23 percent in 1978. farm was 5.5 in 1950, In 1950, 68.9 19.74 percent in 1969 and The average- number of milk cows per 5.58 in 1969 and 6.89 in 1978 Census of Agriculture). (U.S. All these figures supported p r e ­ vious findings on the trend toward increased efficiency and spe cialization in the study area. in better condition, trucks, in bigger and more sophisticated over highways and super highways to milk di s tr i­ buting companies iation, Trucking the fluid milk, such as the Michigan Milk Producers A s s o c ­ has also helped to increase dairy productivity through agricultural specialization in southcentral Michigan. _ The 1964 Census of Agriculture recorded the last data available on farm facilities, including milking machines. 103 To conclude, it may be anticip at ed that the increased trend toward specialization was accompanied by farmers' de ­ mands for more sophisticated farming supplies that could not be made available economically in small However, local villages. specialized farming required the provision of more sophisticated and much more expensive equipment, supplies and services to fewer f a r m e r - c o n s u m e r s . Farm Consol id at io n The decline in the number of farms in the United States since the 1930s and 1940s has continued up to the present day. The number of farms in the counties of southcentral Michigan decreased dra ma tically from 47,836 27,395 in 1950 to in 1969 and continued to decline to 20,659 (Figure 3.5). The decline in the number of farms has been a consequence of farm consolidation, fewer farms that means (large scale agribusiness). (Moyer, Harris and Harmon, larger and The increasing size of farms has been accompanied by improvements tion in 1978 1969:16). in m e c h a n i z a ­ Thus, technology has stimulated farm enlargement, con sistently expanding the production capacities of farming (Sundquist, 1971:374). Large scale farms also benefit from advantages of discounts on bulk purchases, availability, Increases better marketing arrangements, and tax w rite-offs (Sublett, credit 1975:4). in the average sizes of farms have affected all of the counties of southcentral Michigan. The mean farm 104 Number of Farms per County Tot a l N u m b e r of F a r m s C o u n tie s o f S o u t h - c e n t r a l M ic h ig a n : 19 5 0 , 1 9 6 9 , 1978 200CH 100(H II1111111I V<2/ V A verage N um ber of F a r m s 2000H m . F i g u r e 3 . 5 T o t a l n u m b e r of f a r m s b y c o u n t y , a n d t h e i r a v e r a g e v a l u e s in 16 c o u n t i e s of s o u t h - c e n t r a l M i c h i g a n D a t a c o l l e c t e d f r o m t h e U S C e n s u s of A g r i c u l t u r e for 19 50 . 1969 . a n d 19 78 Average Size of Farms (Acres) C o u n tie s o f S o u t h - c e n t r a i M ic h ig a n : 1 9 5 0 , 1 9 6 9 ,1 9 7 8 Average N u m b er of Acres 250-1 M e a n of A v e r a g e S i z e o f F a r m s in A c r e s F i g u r e 3 .6 A v e r a g e s i z e of f a r m s ( a c r e s ) b y c o u n t i e s : a n d t h e i r m e a n v a l u e s in 16 c o u n t i e s o f s o u t h - c e n t r a l M i c h i g a n D a t a c o l l e c t e d f r o m t h e U.S. C e n s u s o f A g r i c u l t u r e fo r 19 50 . 196 9. a n d 1978. 105 size increased from 113.36 acres in 1950 to 152.15 acres in 1969 and 184.70 acres was in 1978 (Figure 3.6). Thus, there 32.2 percent change from 1950 to 1969 and 21.4 percent change during the period of 1969 to 1978. Changes in the average farm size in the study area are also credited with increasing farm incomes and productivity, reducing costs of farm operations and making farming more efficient Harris, and Harmon, 1969:16). counts on bulk purchases, For instance, (Moyer, price d i s ­ including inputs of fertilizer and mach in ery available to large-scale farmers bring economies of scale to large-scale farming Sublett, 1975:4). (Sundquist, 1971:374; The economic problems of small scale fa r m ­ ing are related to the high costs of machinery, and market prices too reasonable profit, over-taxation, low to provide the small farmer with according to data provided by Farm Family Qu estionnaires administered in 1983 (Appendix B ) . Farm c o n ­ solidation in the study area resulted in a significant re ­ ductio n of farm grossing of 1950-1969 and less than $10,000 over the periods 1969-1978, while the numbers of farms grossing $1 0 , 0 0 0 - $ 3 9 ,999 and $40,000 and over have increased (U.S. Census of Agriculture for 1950 , 1969 , and 19 7 8 ) . Farm co ns olidation has meant that many farmers earning less than $10,000 have gone out of business and their lands have been bo u g h t or rented by larger farmers who are mechanized or automated and can profit from economies of scale and spec­ ialization. 106 The process of farm con solidation has accelerated with the increase of par t-o wnerships of farming operations in the counties of southcentral Michigan. Hart (1972:258) notes that part-owner operations have facilitated recent in­ creases in farm size in the Midwest. The percentage of farms under p ar t- ow ne rsh ip in the counties of study area has increased from 18.6 percent in 1950 and 21.0 percent in 1969, to 32.5 percent in 1978 (Figure 3.7). Figure 3.7 shows that both average size and part-own er shi p trends follow an upward d ir ect ion for the 1950-1969 period and in the 1969-1970 period, two variables. implying a relationship between these Conversely, part-time farming has slowed down this trend to in cre asingly larger farms in the United States The importance (Moyer, Harris and Harmon, of off-farm job income is vital est farm operations U.S. 1969:16). to low income or the small­ (less than $2,500 gross income) (Randall and Myers, 1970:25). In fact, in the most off-farm income in recent years has been earned by farm families who operate small farms, while the majority of net farm income is earned by the families who operate larger farms H a n d b o o k , 1980:5). (USDA This indicates that part-time farmers with their ec on omically weak farm operations who depend on off-farm jobs are in danger of going out of the farming business. They operate in competi ti on with full-time farmers who have farm families larger-scale farm operations. interviewed in the study area Among the (1983), there 107 O w n e rs h ip and A v e ra g e Size of Farms C o u n ties of S o u th -c e n tra l M ic h ig a n 1 9 5 0 , 1 9 6 9 , 1978 200 70- Percent of Ownership 150 50- 40- 100 30- 20 - - 50 % Part Owners Average Size of Farms in Acres 60- IQ - 1 950 F ig . 3 .7 1969 1978 P e rc e n t v a lu e s o f fa rm o w n e rs h ip typ es in c o m p a ris io n w ith th e a v erage size of fa rm s in s ix te e n c o u n tie s o f S o u th -c e n tra l M ic h ig a n in 1 9 5 0 ,1 9 6 9 , a n d 1978. D ata is c o lle c te d from th e U .S . C e n s u s o f A g ric u ltu re (1950, 1 9 6 9, 1978). 108 ♦ were 44.2 percent full-time farm operators, part-time operators, 45.3 percent 9.3 percent partially -re tir ed operators and 1.2 percent veterans who had served in post wars. Given the co nt inuation of farm mechani zat ion and consoli dat ion in the study area, pa rt-time farming will be increased, with the extra acreage being consolidated into large-scaled and more specialized agricultural failure of small operations. This implies the scale farmers who cannot depend solely on their farm incomes any more, and eventually leave the farming business or rent their acres to larger farmers, to take full-time jobs in town or retire. Gross Farm Income The increase in farm mechanization, consolidation, sp ecialization and in the counties of southcentral Mi chigan over the study time, has brought about significant increase the p r od uc ti on of farm outputs. This in increase of a g r i c u l ­ tural pr od uctivity has meant a concurrent increase of gross farm income in the region. In general, gross farm income in the 16 counties of southcentral Mi chigan has trended consistently upward over the study period. A cc or di ng to Figure 3.8, farm product sales per farm have sig nificantly increased in each in­ dividual county. The average gross income almost tripled from 1950 to 1969, and tripled again in the period of 1978. 1969- In light of the earlier di scussion of prosperous Sales of Farm Products per Farm (Dollars) C ou n ties o f S o u th -c e n tr a l M ichigan: 1 9 5 0 , 1 9 6 9 , 1978 ril n ■ rl O . rv A v e r a g e S a J e s o f F a rm P r o d u c t s P e r F a rm in D o lla r s 3 0 ,0 0 0 20.000 10,000 F i g u r e 3 .8 F a r m p r o d u c t s s a l e s p e r f a r m (D o lla rs ) b y c o u n t i e s ; a n d t h e i r g e n e r a l a v e r a g e v a l u e s in 16 c o u n t i e s o f s o u t h - c e n t r a l M ic h ig a n . D a ta c o l l e c t e d f r o m t h e U .S . C e n s u s o f A g ric u ltu re fo r 1950, 1969, a n d 1978. 110 developmental improvements in farm mechanization, zation and c on so l ida ti on in the study area, sp ec ia li­ the upward trend of farm income in this area is considered a productive c o n ­ sequence of rural farm development since 1950. were par ticularly go od for American farmers, available markets to sell credit for pu rch as i ng N e w s , Jan. in the 19, because of land and new farm machinery 1983). 1970s their farm products and easy (State The prosperity and farm development 1970s has been blamed for overprodu cti on and a c o ns e­ quent re duction in feed grain and food prices 1980s. The in the early It has been suggested that governmental ward stabilizing farm prices policies to ­ in domestic and international markets and a d el ib er at e policy for retaining foreign m a r ­ kets for Americ an farm products pluses) , ac co mp an ie d by (particularly grain sur­ lower interest rates and easier credit could have hel pe d more farmers survive the c o m p e t ­ ition of big b u s i n e s s - o r i e n t e d farming in the N e w s , Jan. 19, farm families 1983; Cochrane, 1979:162-169). intervi ew ed in this study, 1980s (State Among the it was found that large-scale farming was productive and economically b e n e ­ ficial in the early 1980s, but small farm families faced financial problems. As a co ns eq ue nc e of rural agricultural development in southcentral Michigan, the functions offered in the local central villages were changed. When only 55.83 percent of farms were using tractors exclusively (Table 3.1), the rest Ill were using both trators and draft animals as farm power the 1 9 5 0 s ); and functions (in such as b l a c k s m i t h i n g , shoeing, harness repair and w e ld in g were still available in the c e n ­ tral villages. By 1970 and 1980 these functions had d e ­ clined or disappeared. Farm machinery and supply stores in the area increased in number in the 1950-1970 period, a ss oc ­ iated with farm me ch an iz at io n that requried modern products for farm operations. Grain elevators and feed stores d e ­ clined in their spatial di st ribution over the study time, due to a co nc entration of better and larger grain elevators and feed stores that were more specialized and responsive to farming development. Consequently, small local grain e l e ­ vators were abandoned as fewer but more efficient grain el e­ vators and feed stores became predominant in the study area and were able to take advantage of economies of scale. course, the develop me nt of more modern, Of swifter tr an sp or ta ­ tion has been germane in this spatial dispersion. Likewise, the evolution of transpor ta ti on has been another significant component of rural de ve lopment throughout the study area. The Evol ut io n Of Tra nsportation and Highway Development In Southcentral Michigan The pattern of the rural landscape in southcentral Mic higan has seen important changes in tr ansportation n e t ­ works from the domin at io n of the railroads in the 1950s to a super highway or iented transportatioin network in the 1970s 112 and 1980s. The railroad was a dominant feature in the U.S. transport at io n senger cars, landscape in 1920, but motor vehicles, trucks and buses became dominant in the Their de ve lopment continued in the Soltow and Sylla, 1979:439). 1940s and 1950s 1930s. (Ratner, The total main railway truck in the United States was 254,000 miles clined to 205,000 miles in 1970 roads, pas­ in 1916, which d e ­ (Ibid:442). Michigan r a i l ­ part of the Eastern district railroads of the U.S., lost traffic betwe en Thaller, 1940 and the 1970s 1978:252-254). rural America, (Richards and The decline of railroad traffic portends a continuous reduction by a b a n d o n ­ ment or disconti nu an ce of thousands of miles of rails next few years in (Kaye, 1980:268). The declining railroad function in the United States between related to changes in industrial ulation and markets, in the 1929 and the locations, 1970s was shifts in p o p ­ the development of trucking and the de vel opm en t of new raw material sources that have c o n t r i ­ buted to the prosperity of America's western railroads and railroad bankruptcies and Thaller, in the northeast and Midwest 1978:255). As a result, several (Richards railroad sta ­ tions in the study area have been consolidated and old sta ­ tions abandoned. The decline in the viability of railroads in the M i d ­ west has been accelerated by freeway development and t r u c k ­ ing. Acc ording to the Atlas and platbooks of Michigan co u n ­ ties for the 1950s and the field surveys of this researcher, 113 80.5 percent of 46 central villages of this study were benefitted by the railroa d in the early 1950s. The significance of railroads to central villages in the vital agricultural goods has faded to benefit trucking. central villages surveyed, railroad functions maintaining their villages, shipment of Of the 83.5 percent had lost their that were frequently a vital element in local grain elevators. Some of these including Br oo kly n and Dexter, had lost their railroad functions by Stockbridge, Homer, 1965; several other villages, Nashville, Concord, Hanover and Saranac have lost railroa d service in the past five years. railroad has such as The lost gradu all y its former importance in the central villages due to the prevalence and economies of super hi ghw ay - or i e nt ed transport, pa rt icularly trucking. The number of trucks registered in the U.S. 4.8 million in 1940 to 17.6 million in 1970 and Sylla, 1979:448). This grew from (Ratner, Soltow shows that the popularity of trucking for freight hauling in the U.S. has arisen to sup­ plant the railroad function. This situation was evident in field surveys of the central villages since the railroads, for reasons of e con om y of scale, were no longer stopping in the villages and even their tracks had been removed from some of the central villages. Local elevators depend on trucks for shipment of grain or crops. In some cases, farmers of the study area own their own trucks for marketing 114 their farm products. In addition to being less ex pe n­ sive, in many respects, trucks are preferred over the r a i l ­ road, for their abilit y to deliver produ ct to market more quickly and their flexibility in distri but ing a particular product to a partic ul ar destination. The increased popularity of truck ownership by farmers in the counties of southcentral Mi ch ig an is shown in Figure 3.4. The percentage of farms having trucks was 34.2 percent in 1950 which increased to 72 perce nt in 1969 and increased again to 84 percent in 1978. The quali ty and design of these trucks has also changed since 1950 in response to the demands of more mecha ni ze d and effi ci en t farmers paced farm operations. .The mod er n farm trucks can handle larger loads for fewer trips, saving time and labor expense and creating more profits for the farmers 1950, 1970, farmers 1980). in fast- (Michigan F a r m e r , The increased truck ownership by the in the study area has increased the usage of trucks on the highways and expressways where they often substitute for family cars. Figure 3.9 reveals an almost stable number of automobiles per farm, while there is a noticeable d e ­ crease in the number of farms having automobiles study area, over the study period. number of automobiles in Figure in the The decline in the total 3.9 is again related to the decrease in the number of farms and farm families due to farmers leaving the farming business. In contrast, the n o n ­ farm families interviewed were very likely to have more than Automobiles per County C ounties of South-central Michigan: 19 5 0 , 1969,1978 T o ta l N u m b e r of A u to m o b ile s 4 0 0 0 -1 3000 2000- 1000 - ^ of of # # >P* / cif sf ^ 4? ^ “ Ln T o ta l P o p u l a t i o n o f A u to m o b ile s 6 0 ,0 0 0 A v e ra g e N u m b e r P e r F a rm P e r c e n t o f F a r m s H a v in g A u to m o b ile s 2. 0 - 100% -| 1.0 - 50% 4 0 .0 030 0- 20.000 oo- o— J L ua -0 <£>Vb >P .a P a .' F i g u r e 3 .9 P o p u l a t i o n o f A u to m o b ile s b y c o u n t i e s : a n d t h e i r d i s t r i b u t i o n b y a v e r a g e a n d p e r c e n t a g e v a lu e s in 16 c o u n t i e s o f s o u t h - c e n t r a l M ic h i g a n . D a ta c o l l e c t e d f r o m t h e U .S . C e n s u s o f A g r ic u ltu r e f o r 1 9 5 0 , 1 9 6 9 , a n d 1 9 7 8 . 116 one private car. It may be concluded that highway de ve l o p ­ ment in the study area has been due, in part, of truck-oriented shipment of agricultural to the trend products and also to the increase of private cars due to an increasing nonfarm po pul at ion in the rural townships. grow th has also been an influential ment of regional Of course, metropolitan factor in the d e v e l o p ­ transportation. Population shifts and population growth have also been important factors in the regional development of the United States and its systems of roads and highways. growth, Population its cha racteristics and its di st ribution should be consid er ed in the analysis of any trunk line planning b e ­ cause forecasts of the future growth and patterns of p o p ­ ul ati on and their mode of transportation are vital vel op i ng highway networks Highways, 1970:17). (Michigan Department of State Considerable population increase took place in Michigan and its southcentral and 1970-1980 periods in d e ­ (Table 3.3). counties in 1950-1970 In-migration has been the reason most responsible for population growth in the region, in both its urban and rural areas. Regarding the higher rate of change in population growth in the period of 1950-1970 than 1970-1980, changes it was anticipated that dramatic in highway dev elopment and transport facilities southcentral Mi chigan occurred in the earlier period. in It should be noted that farm depopulation in the study area was compensated by the in-migration of rural nonfarm residents. 117 TABLE 3.3: Patterns of Population in the Counties of Southcentral Michigan in 1950, 1970 and 1980, Showing Percent Change for 1950-1970 and 1970-1980 Total Popula- Percent tion Change 1950 1970 1980 9.5 2,361,552 SOURCE: 34.3 745,074 14.2 7.0 1,510,880 Percent Change 554,674 1,411,816 2,156,890 Rural Popula­ tion 55.1 47.2 19701980 Percent Change 910,104 1,464,778 19501970 Urban Popula­ tion 850,672 Data is compiled by the author from the U.S. De partment of Commerce, Census Of Population: 1 9 5 0 , Vol. II Part 22: Michigan, 1952: U.S. De partment of Commerce, 1970 Census Of P o p u l a t i o n , Vol. 1, Part 24: Michigan, March 1973; and U.S. De­ partment of Commerce, 1980 Census Of P o p u l a t i o n , vol. 1, Part 24: Michigan, January 1982. 118 In a reciprocal relationship, increased population e n c o u r ­ aged transportation system development and improved acce ss­ ibility was attractive to newcomers. Since modern flexibility of movement due to motor v e ­ hicle travel has enhanced transportation by private carrier, freeway (interstate highway) development has created d i s ­ tinguishable interconnections between metropolitan centers (Mackie, 1963:8). The co ns truction of the national system of Interstate and Defense Highways in the United States was approved by Congress 1961). in 1956 (Utah State Dept, The first such interstate highways of Highways, located in Mic hig an were 1-94, to a proposed 1-69, which was partially improved in the early 1960s 1-96 and 1-75, with the later addition (Mackie, 1963:9,10). location of the abovemen tio ne d Michigan. Figure 3.10 shows the interstates in southern 1-94 connects the me tr opolitan center of Detroit to the m e tr opo li tan center of Chicago in Illinois; 1-96 connects Detroit to Muskegon and Benton Harbor in western Michigan; and 1-75 connects Detroit with Michigan's Upper Peninsula and Canada to the North, and to Cincinnati eventually Florida) The approved part of 1-69 connects Marshall, to the South. Mic hig an (passed by 1-94) (and to Indianapolis (Indiana), while the proposed part of 1-69 was a connector from Marshall to Port Huron that passed through Lansing. Most of approved 1-69 was opened to traffi-c in 1973 and it was c ompletely constructed by 1976 (Michigan State Highway Super Highway Networks, Michigan 1963,1969, and 1978 1969 1963 A p p r o v e d (1 9 6 3 ) o r E s t a b l i s h e d (1 9 6 9 , 1978) S u p e r H ig h w a y P ro p o s e d C o n s tru c tio n F ig . 3 .1 0 T h e e s t a b l i s h m e n t a n d d e v e l o p m e n t o f t h e i n t e r s t a t e h ig h w a y s y s t e m in t h e s t a t e o f M ic h i g a n a n d t h e s t u d y r e g io n . S o u r c e s : J o h n C . M a c k ie ( C o m m is ­ s i o n e r ) , M ic h i g a n S t a t e H ig h w a y D e p a r tm e n t, Proposed Extension of Interstate 69, 1 9 6 3 ; M ic h i g a n D e p a r t m e n t o f S t a t e H ig h w a y s , T r a n s p o r t a t i o n P l a n n i n g D iv is io n , Environmental Impact Statem ent for 1-69, Charlotte to 1-96 N orthw est o f Lansing: Clinton and Eaton Counties, M ic h ig a n , 1 9 6 9 ; a n d M ic h i g a n S t a t e H ig h w a y C o m m is s io n , 1977 Annual Report, M ic h ig a n D e p a r t m e n t o f S t a t e H ig h w a y s a n d T r a n s p o r t a t i o n , J a n u a r y 19 7 8 . 1978 120 Commission, 1977:5). Interstate highway patterns in south- central Michigan have favored increasing Michigan farmers' access to the markets of adjoining states, Illinois, Indiana, and Ohio. including Farmers now take advantage of this access to choose the best market for their agricultural products. Expressway construction, in this country has including interstate highways, led to the develop me nt of more capable and efficient modern transportation. cipal trunkline highways, divided roadways, long routes in a manner that facilitates high speed traffic, part ic ula rl y commercial narrower trunklines are appropriate to lower speed ve hicles and sh or ter-trip traffic of Commerce, 1962:25). as p r i n ­ are de signed with multi-lane to cover wide and vehicles, while other, Expressways, Therefore, (U.S. Dept, cons tr uc ti on of the interstate highways in Mic hig an has tended to increase the accessibility of the people of this state and the study area. The increasing a va il ab ili ty and use of expressways in recent years in the State of Michig an reflects the im­ portance of increased regional a cc ess ib il ity and greater population mobility. (expressways) Routes over modern efficient roads that can handle heavy, high speed traffic have been substituted by truckers and travelers for routes over older and narrower highways built in the past. mileage in the State of Michig an Freeway (Michigan charges no high 121 way tolls) in 1977 4). increased from 1,545 miles in 1973 to 1,674 miles (Michigan State Highway Commission, 1973:6 and 1978: Interstate highways totaled about 895 miles in 1969, w hi ch increased to 1,024 miles in 1973 and 1,181 miles in 1977 (Michigan Dept, of State Highways, 1A; Michigan State Highw ay Commission, 1-69-2 (7)62, 1969: 1973:6 and 1978:4). The absence of interstate highways in Michigan in the early 1960s compared to 1969 miles) ways demonstrates (895 miles) and 1977 (1181 that the emergence of interstate h i g h ­ in the 1950-1970 period was dramatic and revolutionary compared to their evolu ti on ar y development in the later p e r ­ iod of the 1970s. These findings suggest that essential changes in the socioeconomic viab il it y of central villages also occurred during the first period of this study. The impact of transport develop me nt on the viability and spatial di st ribution of central villages is discussed in Chapter Five. The Effects Of Rural Development In Changing The Patte rn and Ch ar act eristics of the Rural Population Agricultural industri al iz at ion and transportation in the study region from 1950 to 1970 was a revolutionary d e ­ velopmental process in changing the spatial patterns of po pulation in the central villages and the countryside su r­ rounding them. Agricultural mechanization reduced the nu m­ ber of workers needed on the farms and farm consolidation 122 reduced the number of farms and farm families. the establishment of interstate highways Meanwhile, in the 1960s in­ creased mobility among urban and rural people in southcentral Michigan so that rural farm dep opulation and farm c on solidation was ac co mpanied by an influx of new (non-farm) p opulation who were employed in the cities of southern and mid-Michigan, This but resided in the countryside. influx of non-farm people exceeded farm d e p o p u l a ­ tion to the extent that the counties of southcentral M ic higan ex per ienced an overall population increase (Figure 3.11) from 1950 to 1970 of 47.2 percent for the study re ­ gion. The growth of population in the urban centers was 55.1 percent and 34.3 percent in rural 3.3). This largely due to in- mi gration promoted by the developments in transportation The greater rate of populat ion increase in the urban areas may have been related to greater ities, sectors (See Table significant population growth in southern Mic hig an in the 1950-1970 period was facilities. areas job op po r t u n ­ par ticularly in the m an ufa ct uri ng and government in the period of 1950-1970 was centrally oriented). (when industrial policy Unemployed agricultural workers were drawn to the jobs available in metro pol ita n and urban areas. The increase of rural popula ti on (34.3 percent) in that period was related to the migra tio n of non-farm people from nearby cities and towns. of the study area, All of the central villages and 96 percent of the rural townships 123 T o ta l, R u ra l, and U rban Population C o u n tie s o f S o u th -c e n tra l M ic h ig a n 1 9 5 0 , 1970 , 1980 2,500 Population in T h o u sa n d s 2,000 - 1.500 - 1.000 - R u ra l p a p u l a ] ^ 500 1950 F ig . 3.11 1970 1980 T o ta l p o p u la tio n , u rb a n p o p u la tio n a n d ru ra l p o p u la tio n o f six te e n c o u n tie s of S o u th c e n tra l M ic h ig a n in 1 9 5 0, 1 9 7 0 , an d 1980. D a ta is c o lle c te d fro m th e U.S. C e n s u s of P o p u la tio n (C e n s u s o f P o p u la tio n : 1 9 5 0; 1970 C e n s u s o f P o p u la tio n ; 1980 C e n s u s of P o p u la tio n ). 124 surrounding them, (Figure 3.12). gain ed population from 1950 to 1970 The late 1960s saw the greatest movement of no nf ar m people to the rural areas during this period. Farm consolidation, farm mortgage foreclosures and the increased willing ne ss of farm families to sell all or parts of their farms caused the reduction in the farm acreage in southcentral Mi ch ig an between 1950 and 1970 (Figure 3.13). Over this period there was a 21.9 percent decrease in farm­ lands. Some farmlands were either consolidated or incor­ po ra te d under new managers or farm o w n e r - o p e r a t o r s . Other farmlands were su bdivided for housing tracts and rural apartments and condominiums, villa ge limits. especially those near town and This process of subdivision and conversion of farmlands was con ti nu ed in the later decade of the study peri od (1970-1980). From 1970 to 1980, regi on was 9.5 percent, decades (See Table the po pulation increase in the study much lower than in the two earlier 3.3). Both urban and rural areas of the study region gai ne d population, 7.0 percent in urban areas and 14.2 percent in rural (Table 3.3). areas The increase of po pulation in the area was related to the continuing tra nsportation de ve lo pm en t that promoted more mobility and commu ti ng between home and work. in the rural areas The higher rate of increase in comparison with urban centers may be relat ed to increasing ma nu facturing employment in no nm e t ro ­ p o li ta n areas (decentralization) that was a trend in the 125 Rural V illage Population Po pul a t ion in T h o u s a n d s South-central Michigan: 1950, 1970, 1980 2000- ^ 1000- -8 * /V °'P <3^ F ig u re 3.12a <6°^ ^ ^ ^ ^ 0^ O6^ T h e p o p u l a t i o n of c e n t r a l v i l l a g e s a n d t h e i r s u r r o u n d i n g t o w n s h i p s a t t h r e e p o i n t s in tim e. ^ $> 126 Rural V illage Population P o p u la tio n in T h o u s a n d s South-central Michigan: 1950, 1970, 1980 40 0 0 30002000 1000- S rflrl1 rfim rf1 » r» an rl1 rflrrirfifll rEJL /✓///////////// / Rural Farm and Non-Farm Population S o u th - c e n tr a l M ic h ig a n : 1 9 5 0 , 1 9 7 0 , 1 9 8 0 8000 - P o p u la tio n in T h o u s a n d s 7000 6000 5000 4000 - I111 1 3000 20001000 - / ^ 6°C ^ cf ^ cf d» I 1 ill ri I rfl 111 rrl rll rfl 0A 06^° 0* „Ge o0' 6^° & G° <£■ ^ ^ ^ ^ <1® - >Cr ^ Oa Rural Farm and Non-Farm Population S o u th -cen tral M ichigan: 1950, 1970, 1980 8000 7000- P o p u la tio n in T h o u s a n d s 60005000400030002000- 1000 M s i / / / i i / ✓ / / / il m rfl fll / / f l rrl rft / ✓ / Rural T ow n ship Population S outh-central M ichigan: 1950, 1970, 1980 10000 9000- I | 1950 I | 1970 70006000 5000 40003000 r 1 / V F i g u r e 3 .1 2 c S J * / / / / S / u^ ,and are different. MS between SS B e t w e e n / (J - l ) 13893.15/{3-1)_ ft7. MS Within " SS Within/(N-J) “ 6 9 5 . 9 7 / (10-TT~ ' df of MS between: 2 and df of MS within : 7; calculated F value: 69.87 is greater than the critical F value of 9.55 at p =.01. Therefore, the null hypothesis is rejected and we accept the alternative hypotheses that implies significant difference of means. 135 1 2 3 4 5 6 7 8 9 10 Model 136 In order to learn the functional thetical model (Table 4.1), indexes of the hy p o ­ the ce ntr ali ty of each individ­ ual function in a certa in central place is computed. this purpose, the functional units of a particular function are multiplied by its design at ed Thus, For location coefficient. the centrality of function A at central place #1 has been calculated by m u l ti pl yi ng its 5 functional units by its location coefficient of 4, yielding 20 as the centrality of function A at central place #1. The calculated centrality for functions B, C, D and E in central 20 and 50, respec tiv ely (Table 4.1). place #1 is 20, 20, Summing all these centrality values for functions A, B, C, D, and E yields 130, whi ch is the functional Other functional index for central place #1. indexes are ca lcu lat ed the same way for the rest of the central places in Table 4.1. It should be noted that the summation of all the ce ntr ali ty values tion among the central instance, places studied, will be for a func­ 100. For the total ce nt ra li ty of function A among all central places is 100. Functions B, C, D and E, 100 values of centrality. ities of each function, mation of functional ten thus have The summation of total ce n t r al ­ will be the same amount as the sum­ indexes calcul at ed for each central place. . The Jenks method of cl as sif ic at io n that is based on variations of observations from the mean (less variance w it h i n the groups and higher variance between the groups) 137 was used for classifing the computed functional indexes in this research. To confirm the Jenks c l a ss if ic ati on of func­ tional analysis of variances and F-tests indexes, significance been used. (tests of for the results of analysis of variance) have Such a verified cla ss ifi ca tio n was essential for explaining and generalizing similarities among va riables with in each class of central places and general differences been the classes. Table 4.1 shows the procedure for c a l ­ culating the functional test index classific ati on and applied F- (analysis of v a r i a n c e ) . The functional classification of the data of this re ­ search at three points A .1, A . 2 and A . 3. in time are shown in App endix Tables The selected functions are central place- oriented and include wholesale and retail in the central villages. Dun and Bradstreet, sales and services The data were derived from the Reference Books (1950, 1970 and 1980) and the Telephone Directories of towns and cities of southcentral Michigan (1969-1971 and 1979-1982) tral village studied. The central shown by trade symbols (See Table A.l). they are de picted by Standard for the 46 c e n ­ functions in 1950 are For 1970 and 1980 Industrial Cl as si f i c a t i o n n u m ­ bers as they are printed in the Dun and Bradstreet, Reference Book. Table A.l does not include the rural services shown in Tables A . 2 and A . 3 because it was not possible to d i s t i n ­ guish the rural services related to a pa rticular central 138 place from the 1950 Telephone D i r e c t o r i e s . all the central functions attributed to 1950 in Table A.l were derived data from Dun and Bradstreet, for 1950 (wholesale and retail Lo cation coeff ici ent s and the functional Reference Book sales f u n c t i o n s ) . (L.C.) of each central function index values for each central village are also shown in Tables A.l, tional Therefore, A . 2 and A . 3. These fu n c ­ index values were grouped by the Jenks method of c la ssi fic ati on (using a computer) and the results of the cl as sif ica tio n were tested by analysis of variance The F-test procedu res cl ass ifications 4.2, (1950, 4.3 and 4.4. for the final (F-test). steps of the functional 1970 and 1980) are shown in Tables The results of the F-tests suggest a significant statistical verif ica tio n of each classification of central villages (1950, 1970 and 1980). In order to show the combined picture of central v i l ­ lage clas sif ica tio n according to the order of their fu nc ­ tional index values 1970 and 1980, and their designated classes Table 4.5 has been prepared. in 1950, To visualize the spatial dis tr ib ut io n of each class of central villages at the three points in time 4.2 and 4.3 are provided. (1950, 1970, 1980), Figures 4.1, These figures are used later in this research to ex pla in the change in the viability and spatial distri but ion of the central villages studied. 139 Table 4.2: Villages Order Hierarchical Orders of Central Villages in 1950 in Number of Observations First Order Villages 1 983.70 Second Order Villages 1 656.56 - 656.56 Third Order Villages 7 484 .14 - 379.18 Fourth Order Villages 6 350.53 - 251 .88 Range of Functional Index Values - 983.70 Fifth Order Villages 11 281.61 Sixth Order Villages 20 103.98 - Therefore: F-Test: - 129.03 11 .25 SSW = 41516.40; df : 46-6=40; MSW = 1037.91 SSB = 3,945,951; d f : 6-1=5; MSB = 789192.24 Hq : P 3= /*4= = H-^ : The means of these six groups of central v i l ­ lages are different from each other. Villages have hierarchical orders . Critical Value of F: 99% is 3.51 Calculated Conclusion: F Value The calculated is: F-value than the critical jected and MSB = 789192.24 MSW 1037.91 “ _,rn , is significantly greater F-value; is accepted. therefore, H is re' o This means that the six orders or classes of villages have di fferent means, that differences between classes existed. 140 Table 4.3: Villages Hi era rchical Order of Central Villages in 1970 First Order Range of Functional Index Values Number of Observations in Order 3 884.66 Second Order Villages 4 675.66 - 604 .84 Third Order Villages 5 517.26 - 381 .93 Fourth Order Villages 7 296.06 - 183 .42 Fifth Order Villages Villages 12 Sixth Order Villages 15 Therefore: F-Test: - 792 .87 157.77 66.76 - 77.50 9 .75 SSW = 41986.94; df:46-6=40; M S W = 1 0 4 9 .6735 SSB = 3759839.5; df:6-l=5; MSB=751967.9 Hq : ^ ^ ^ ^ ^ u ^ U g H-^ : The means of these six groups of central v i l ­ lages are different from each other. Villages have hi era rchical orders . Critical Value of F=99% is 3.51 C al cu lat ed value of F is: Conclusion: The ca lc ul at ed than F-value the critical jected and MSB 751967.9 7. f MSW " 1049 .6735“ is significantly greater F-value; is accepted. six orders of villages d i f f er en ces between -,n therefore, H is re' o This means that the have different means; the classes existed. that 141 Table 4.4: Hierarchical Order of Central Villages in 1980 Villages In Order Number of Observations Range of Functional Index Values First Order Villages 3 1024.45 - 986.53 Second Order Villages 7 615.25 - 458.00 Third Order Villages 4 377.21 - 360.68 Fourth Order Villages 6 305.61 - 221.86 Fifth Order Villages 8 188.13 - 114.48 Sixth Order Villages 18 Therefore: F-Test: 93.33 - 14.41 SSW = 40908.3; df : 46-6=40; MSW = 1022 .71 SSB = 4000764 .49; df : 6-1=5; MSB = 800152 .9 Hq : /u 1-/u 2= ^ 3= ^ 4=>i5=/u 6 : The means of these six groups of central villages are di fferent from each other. Villages have hierarchical orders . Critical value of F: 99% is 3.51 Calculated value of F is: Conclusion: The calculated F-value; is accepted. six orders of villages differences 782.38 F-value Is significantly greater than the critical jected and MSB 800152.9 = MSW ~ 1022.71 between therefore, H is reo This means that the have different means; the classes existed. that F u n c tio n a l Viability of C e n t r a l Villages South-Central Michigan 1950 Village Order F ir s t Functional Index 9 8 3 .7 0 Second T h ir d F o u r th 6 5 6 .5 6 4 8 4 .1 4 - 3 7 9 .1 8 3 5 0 .5 3 - 2 5 1 .8 8 F ifth 2 1 8 .6 1 - 1 2 9 .0 3 S ix th 1 0 3 9 8 - 1 1 .2 5 F ig . 4.1 S p a tia l d is tr ib u tio n of d if fe r e n t c l a s s e s of c e n t r a l v illa g e s s tu d ie d in 1950. F u n c tio n a l Viability of C e n t r a l Villages # ^ South-Central Michigan 1970 »• • Village Functional Index F ir s t 8 8 4 . 6 6 - 7 9 2 .8 7 Second £ 6 7 5 .6 6 - 6 0 4 .8 4 5 1 7 .2 6 - 3 8 1 .9 3 F o u r th £ ^ 2 9 6 .0 6 - 1 8 3 .4 2 F ifth ^ 1 5 7 .7 7 -7 7 .5 0 S ix t h • 6 6 .7 6 - 9 .7 5 F ig . 4 .2 £ # S p a tia l d is tr ib u tio n o f d if fe r e n t c l a s s e s o f c e n t r a l v illa g e s s tu d ie d in 1970. F u n c ti o n a l Viability of C e n t r a l Villages • • South-Central Michigan 1980 • .• • • ♦ • * Village Order Functional Index First c i c OR.iicQ n n 615.25-458.00 Second Third Fourth 377.21-360 68 ^ 305.61-221.86 Fifth % 188.13-114.48 Sixth • 93.33-14.41 F ig . 4 .3 A m •• S p a tia l d is tr ib u tio n o f d if fe r e n t c l a s s e s of c e n tr a l v illa g e s s tu d ie d in 1980. 145 TABLE 4.5: Central Villages' Order According to Their Functional Viability in 1950, 1970 and 1980 1950 Central Villaoe Functional Index 1970 Central Village Functional Index 1980 Central Village Functional Index 1. Chelsea 983.70 2. Lake Odessa 656.56 1. Chelsea 2. Brooklyn 3. Dexter 884.66 880.19 792.87 1. Brooklyn 2 . Dexter 3 . Chelsea 1024.45 1012.23 986.53 3. 4. 5. 6. 7. 8. 9. Dexter Fowlerville Nashville Manchester Brooklyn Bellevue Homer 484.14 455.70 453.91 431.31 389.24 384.09 379.18 10. 11. 12. 13. 14 . 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 350.53 299.46 298.86 291.56 279.06 251.88 16. 17. 18. 19. 20. 21. 22’. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clarksville 218.61 206.96 195.45 192.19 187.18 174.53 153.12 145.26 132.51 131.59 129.03 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39 . 40. 41. 42. 43. 44 . 45 . 46. Vermontville Byron Lennon Dimondale Maple Rapids Sunf ield Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansville Perrmton Hubbardston Cement City Eagle 103.98 103.06 100.81 90 .86 87.67 83 .22 79.06 76.93 73 .80 69.36 60 .56 60 .42 59.83 55 .21 44 .92 37.00 26 .51 25 .09 22 .70 11.25 SOURCE: Lake Odessa Ovid Homer Fowlerville 675.66 634.81 633.15 604.84 8. 9. 10. 11. 12 . Addison Manchester Saranac Pinckney Caledonia 517.26 425.60 421.12 382.30 381.93 13 . 14. 15 . 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 296.06 291.07 239.74 237.17 232.12 206.40 183.42 20 . 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31 . Parma Dimondale Woodland Byron Westphalia Vernon Muri Hanover Sunf ield Maple Rapids Perrinton Springport 157.77 143.17 125.26 117.65 111.20 105.38 90.22 87.28 84 .43 80.02 78 .74 77.50 32. 33. 34. 35. 36. 37 . 38. 39. 40. 41. 42 . 43. 44 . 45 . 46 . Webberville Freeport Bancrof t Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons 66 .76 61.66 60 .46 51 .94 51.77 50.45 47.10 39.32 38.31 37.21 35.13 27.06 24 .33 18.23 9.75 4. 5. 6. 7. . Derived from Tables 4.2, 4.3, 4.4 and A.l, A.2 and A.3. 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 615.25 563.19 519.41 515.13 484.33 465.47 458.00 11. 12. 13. 14 . Stockbridge Grass Lake Ovid Lake Odessa 377.21 374.92 369.57 360.68 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 305.61 290.84 257.45 249.11 225.94 221.86 21. 22. 23 . 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 188.13 187.51 173.43 152.17 151.05 144.43 144.12 114 .48 29. 30. 31. 32 . 33. 34 . 35. 36. 37. 38. 39. 40. 41. 42. 43. 44 . 45. 46. Vermontville Byron Muir Perrinton Freeport Bancrort Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville 93.33 86.41 81 .66 69 .30 51.46 51. 21 41.12 40.66 36 .02 35.57 35 .34 34 .66 27.48 17.07 16.46 16.43 15.41 14 .41 146 Structural Modeling The relati on shi p of population and function in the c e n ­ tral places of a study area may be vi sua liz ed and examined through both co ntinuous and discontinuous models O'Farrell, 1969 and Rowley, models have been used. tral villages observations 1971). (see In this study, The hierarchical both grouping of cen ­ in six classes provides a smaller number of in cor re la ti on and regres si on tests of the re lat ionship of p op ul a t io n and function in every class (discontinuous model). To provide complem ent ary results, all 46 central vil lages are also examined in a continuous model of popula tio n and function relationship. Continuous Models Of Population and Function Relat ion sh ip In order to test the hypothesis c o nce rn ing the re ­ lationship betwee n p op ul at ion size (served) and the func13 tional range or numbers of functions of central villages (using the central functions of retail and wholesale ac t i ­ vities) , a co rr el ati on test and a regression analysis were 13 Functional range is equivalent to the number of functions in central places of a study area (See Haggett, 1977:140). In fact, it refers to the total numbers of di fferent types of functions offered in a central place. For instance, central place #1 (in Table 4.1) has a fu n c ­ tional range of 5 (having functions A, B, C, D and E ) , while central place #10 has a functional range of 2 (having only the two functions of A and B ) . 147 applied in this research. analysis The application of correlation shows the variation of population size in re ­ lationship to the va ri at io n of the number of functions of central villages. Compa rin g the calculated correlation co ­ efficients for those two variables (population and function) at three points of time in the study area is helpful justifying the variati ons lated empirical studies, in their relationships. correlation coefficients 1963 and Joh ans en and Fuguitt, 1973) in In re ­ (Stafford, were used to describe the rel ationship of population size and number of functions. Therefore, in testing this notion empirically the Pearson Product Moment this research (correlation coefficient) has been used in (the corr ela tio n coefficient with related tests of significance are discussed in Bacon, 1977 and Till, 1974). Taylor, For determin ing the linear rel ati on­ ship between po pul ati on size (numbers of functions) 1976; (served) and functional range of central villages at three points of time, in the study area the parametric statistical method of simple linear reg re ss io n was used. This method was applied in the work of Joh ans en and Fuguitt (1984) on American v i l ­ lages for det er mi ni ng the linear relationship between any village's po pul ati on and its economic activities. linear regress ion 1974) (See Bacon, 1976; provides a continuous model Taylor, Simple 1977 and Till, of population and function relationship among the central villages of the study area. Compa ris on of the related regression coefficients' 148 variations at three points of time helps to explain this linear relationship. Arranging the variable of p o pu la ti on size (served) of villages and their surrounding townships on the x axis, and the variable of numbers of functions on the y axis, and the Pearson's .782 in 1980 calculated "r" at "r" was (Figure 4.4). (functional range) .901 in 1950, The si gn ificance .821 in 1970 level of .0 0 0 0 1 , showed that the statistically significant relationships existed betwe en the two variables in all three examinations. The important point is that a strong relationship existed be twe en pop ulations and functions of villages at the three points strated by bigh correlation coefficients in time as d e m o n ­ (Figure 4.4). De ­ cline in "r" values from 1950-1980 meant that the population size of the villages accounted for the gr ea te st proportion of variation in their numbers of functions in 1950. This covariation was reduced in 1970 and 1980 implying that the var iation in village populations was more c l os el y correlated with variation of functions in 1950 than in 1970 and 1980. Figure 4.4 is presented to explain the linear relationship between population and function of central villages continuous model. In the figure, of central villages, the number of functions the dependent variable and the populations of the villages the independent variable in a (on the y axis), (in logarithmic scale), (on the x a x i s ) , were tested for linear relationship at the three points of time. 149 Number of Functions and Population Size Central Villages, South-central Michigan 1950, 1970, 1980 46 1950 Y = - 8 6 . 9 5 + 3 7 . 99X ; R = .901 S ig = .0 0 0 0 1 1970 Y = - 7 6 . 5 6 + 3 1 .16X; R = .821 S ig = .00001 1980 Y = - 6 5 . 3 3 + 2 6 . 54X ; R = .782 S ig = .00001 Number of Functions 40 - 30 - 20 - 10 - 2.0 2.5 3.0 3.5 P op ulation of Village (LG10) F ig . 4 .4 T h e c o n tin u o u s lin e a r re la tio n s h ip s b e tw e e n th e c e n tra l v illa g e ’ fu n c tio n a l ra n g e (n u m b e r o f fu n c tio n s ) and t h e ir p o p u la tio n s ize a t th re e p o in ts o f tim e . 4.0 150 The positive regression coefficients b et we en the two variables of function and p op ula ti on in central villlages in 1950, 1970 and 1980 were c on si st en t with the rank size rule of central place theory. The gradual decline of the regression coefficients across three points of time in the study area (Figure 4.4) number of functions meant that the rate of change in the in central village s per unit of p o p u l a ­ tion size was greatest in 1950 and dec reased in 1970 and 1980. Thus, the population size of villages was a stronger determining factor for change in the number of functions in central villages in 1950 than in 1970 and 1980. The direction of the reg ression lines shows a positive relationship between pop ulation and function at all three points of time (Figure 4.4). The shifts in regression lines to the right and downward for the later years indi­ cated generally that the number of functions in central villages declined, increased. although the p o pu la ti on of those villages The continuous model co ns tr uc te d to show the re ­ lationship between population served (township population) and numbers of functions in central villages found the same pattern and explanation. (Figure 4.5) Because townships contain larger populations than central villages 3.12), (Figure the regression lines have shifted even farther to the right. Thus, the greater populations and the same range of functions villages) (in the townships) (as that examined for the resulted in the changes in the regression lines 151 Number of Functions and Population Served Townships, South-central Michigan 1950,1970,1980 1950 Y = - 1 1 9 .3 + 4 2 .6 9 X ; R = .607 S ig = .00001 Number of Functions 40- 30- 20 - 10 - 1970 Y = - 8 9 .0 6 + 3 0 .3 5 X : R = .574 S iq = .0 0 0 0 1 1980 Y = - 8 5 . 4 4 + 2 8 .1 X ; R = .6 0 0 S ig = .00001 2.5 3.0 3.5 Popu lation S erved or Tow nship Population (LG10) F ig. 4 .5 T h e c o n tin u o u s lin e a r re la tio n s h ip s b e tw e e n fu n c tio n a l range (n u m b e r o f fu n c tio n s o ffe re d in c e n tra l v illag e s ) a n d p o p u la tio n s e rv e d (p o p u la tio n o f to w n s h ip s ) a t th re e p o in ts o f tim e. 4.0 152 shown in Figure 4.5. Tests of this re la tionship also showed a strong correlation 1970 and r=.600 for 1980) (r=.607 for 1950; at the .00001 r=.574 for significance level. To conclude, it may be said that due to the strong re ­ lationship betwe en population and the number of functions of central villages, changes in the central villages' have been associated with population changes lages and their surrounding townships. indus­ (discussed in have tended to depopulate farms and increase the number of nonfarm families on the rural study area. in these v i l ­ Agricultural trialization and super highway development Chapter Three) viability landscape of the This has been accompanied by functional changes in central villages that have greatly de creased the numbers of their functions and establishments shops, stores and services time and periods Therefore, (the total in a village) (discussed in detail number of over the study in Chapter F i v e ) . ag ri cu lt ur ally-oriented functions declined in favor of emergency of more nonagricultural sidential and recreational) functions (re­ that are responsive to demands of the changing population of rural landscape. The continuous model of relationship b e tw ee n p o p u l a ­ tion and functions, using log linear re gression analysis, has been applied by Berry and Garrison Souza (1978) and Johansen and Fuguitt (1958), (1984) Foust and de- to predict the 153 required (threshold) population for the survival of a given function in the United States. basic model Berry and Garrison's (1958) for predic ti ng the threshold population for a function, considers popula ti on on the y axis variable) and number of functional units (dependent (establishments) of a certain function on the x axis (independent v a r i a b l e ) . The N model equation is P=A (B) , where P is the threshold p op ­ ulation required for estab lis hin g one establishment of a certain function tablis hment (store) in a central place, and N is one e s ­ of that certain function. second and nth es ta blishment of that function, equal to 2 and n. (store) For the N will be A and B values are parameters that are calculated in a simple regression test by using the p o p u l a ­ tion size of villages and the number of establishments of a certain function in those villages. The threshold popul at ion calculated for a certain fu n c ­ tion by Berry and Ga rrison (1978) (1958) and Foust and deSouza was done for all the central places of a region merely for villages) Fuguitt's (1984) at one point in time. work, however, (not Johansen and deals with American villages in a dynamic approach over the years 1950-1970. Therefore, the results of their work provide better criteria for c o m ­ pariso n with the results of this research. Johansen and Fuguitt, tions According to the threshold population for fu n c ­ such as grocery and paint and wallpaper stores crease d b etw een 1950 and 1970 in American villages. in­ The 154 same trend appears for these functions in the study area for this research. For instance, the threshold po pulation for establishing one grocer y store in each central village of southcentral in 1980; Mi ch ig an was 489 in 1950, 659 in 1970 and 761 for a paint and wallp ape r store it was 708 in 1950; 770 in 1970 and 1,231 in 1980. The reason for the increase in threshold p opu la tio n was related to highway and super highway dev el op me nt in the region which afforded regional ac ce ssibility to the residents of this area. Thus, people have greater mo bi li ty and are able to go greater distances for shopping. Tables 4.6 and 4.7 show the calculated threshold populations for one establ is hm en t of each sampled function (in the field survey) for 1950, 1970 and 1980. To compute the threshold p op ul ati on for establishing the first grocery store in each central village of the study area (in 1950), the A and B values were first derived from a logari­ thmic regression analysis w hi ch yielded 2.60315 as the A value and .08612 as the B value. to their antil og ar it hm ic values These were then converted (401 and 1.22, respectively) N P=A(B) = 401 and then applied to the threshold formula, 1 (1.22) = 489. Thus, the threshold population for a grocery store at the village level was 489 persons in 1950. Accor di ng to Tables 4.6 and 4.7, generally the thres­ hold p op ul at ion for one establishment or one functional unit of a certain fu nction increased from 1950 to 1970 and from 155 TABLE 4.6: Thre sho ld Population for Sampled Functions lage Level) for 1950, 1970 and 1980 1950* Central Functions Threshold Population (Vil­ 1970 1980 Threshold Population Threshold Population G r oc er y Store 489 659 761 Jewelr y Store 946 1418 1228 Family Clothing 945 830 1415 Paint & Wa llpaper Store 708 770 1231 Department Store 1654 1332 1918 Shoe Store 1750 935 896 O pt om etr is t NA 871 1355 Clinic NA 3858 1424 Floor Covering Store NA 921 973 A utomotive Dealers NA 1650 1092 *Data for rural services in 1950 marked "NA" was not a v a i l ­ able from the telephone directories for the study area in 1950. 156 TABLE 4.7: Thre sh ol d P op ula ti on for Sampled Functions (Township Level) for 1950, 1970 and 1980 Central Functions 1950* Thre sh old Popula ti on 1970 Threshold Population 1980 Threshold Population Grocery Store 1668 2270 2862 Jewelry Store 2121 3594 4119 Family Clothing 2076 2162 3157 Paint & Wa llpaper Store 1961 3357 4516 Department Store 2651 3377 5056 Shoe Store 2623 2846 2350 Optometrist NA 1355 3577 Clinic NA 5086 4234 Floor Covering Store NA 3354 3782 Automotive Dealers NA 3017 3377 *Data for rural services in 1950 marked "NA" was not av ai l­ able from the telephone di re ctories for the study area in 1950 . 157 1970 to 1980. It appears, therefore, that in the past (1950), due to the dominance of the local economy, people of the hinterlands (farm families) the were more su p­ portive of the central functions offered in the local m a r ­ ket (central v i l l a g e s ) . Therefore, a local function was able to survive with a pr op ort io nat el y smaller population patronizing that small in southcentral however, local market. Michigan, Regional development pa rt icu lar ly from 1950 to 1970, provided greater mo bility for the people who in the rural landscape of the study area. lived As a result, some local functions declined or dis app ear ed and the survival of other local functions was in doubt because of their c o m p e t ­ itive interaction wi t h facilities central places of the region, Thus, some central in higher order and larger par ticularly urban centers. functions available in lower order c e n ­ tral villages, with smaller populations, declined or c o m ­ pletely disappea red from those centers and became stable or increased in the higher order central villages which had greater threshold populations to support those functions. The dis tribution of grocery stores, order central functions available in the villages, was re ­ duced dramatically in frequency in third, sixth order villages study. one of the lowest (Table 4.8) Consequently, fourth, fifth and in both periods of the the threshold population for grocery TABLE 4.8: Types of Services (Functions ) Some Services Offered Functional U nits _____ ( N ) ____ 1950: Grocery S to res Family C lo th in g S tores P aint b W all­ paper S tores D epar tmerit S t o r e s Shoe S to r e s 19 70: Grocery S to res F a m i 1y C l o t h i n g S tor es p a i n t 6- Wa l 1 p a p e r Stores D epartm ent S to re s Shoe S t o r e s in the Central Location C oefficient LC=1/N.1QQ Villages of Southcentral M i c h g a m , F ir s t Order V illages N* Ave . * * Second Order V illages N Ave . Third Order V illages N Ave. 1950, 1970 and 1980 Fourth Order V illages N Ave . F ifth Order V illages N Ave . S ix th Order V illages N Ave . 116 0.86 9 9.00 4 4 .00 24 3 .00 19 3 .40 25 4 . 20 35 1 .75 2 50 .0 0 0 0 .00 0 0 .00 2 0.29 0 U .00 0 0 .00 0 0 .00 9 3 3 11 . 1 1 33.33 33.33 1 1 1 1 .00 1 .00 1 .00 0 1 1 0 .00 1 .00 1 .00 2 0 1 0.29 0.00 0.14 1 1 0 0.17 0.17 0 .00 2 0 0 0.18' 0 .00 0 .0 0 3 0 0 0.15 0.00 0.00 93 1 .08 15 5 .00 13 3.25 14 2 .80 17 2.43 16 1 .33 18 1 .20 4 25 . 0 0 0 0 .00 1 0.25 0 0 .00 1 0.14 1 0 .08 1 0.07 2 6 4 50.00 16.67 25 .00 0 3 0 0.00 1 .00 0.00 0 1 2 0.00 0.25 0.50 0 0 2 0 .00 0.00 0.40 1 2 0 0.14 0.29 0 .00 1 0 0 0 .08 0 .00 0 .00 0 0 0 0 .00 0.00 0.00 7 1 .75 10 1 .67 14 1 .75 4 .22 0 0.00 1980: Grocery S to res 65 3 . 6 7 19 1 .54 11 2.71 Family C lo th in g Stores 5 20.00 0 0 .00 1 0.14 p a i n t 6. W a l l p a p e r Stores 4 25 . 0 0 1 0 . 33 1 0 .14 Depar tm en t S t o r e s 3 33.33 0.67 0 2 0.00 Shoe S to r e s 1 100.00 0 0 .00 0 0.00 * T o t a 1 N u m b e r o f f u n c t i o n a l u n i t s ( s t o r e s ) o"f a c e r t a i n f u n c t i o n i n • ‘ Average number of f u n c t i o n a l u n i t s ( s t o r e s ) of a c e r t a i n f u n c t i o n S OUKCE: D ata i s s e l e c t e d from T a b le s A .4, A .5 and A .6 2 .50 0 .00 0 1 0.25 0 0.00 a particular cl in a p a r t i c u l a r 2 0.33 0 0 .00 0 0 .00 1 0.12 0 0 .00 0 0 .00 0 1 0.00 0.12 a s s o f c e n t r a l v i 11 a g e s c l a s s of c e n tr a l v i l la g e s 1 0 0 ' 0 .0b 0.00 0.00 159 stores was increased. The appearance of grocery stores all classes of villages in 1950, per ma ne nt survival in 1970 and 1980 implies their in all classes (Tables 4.6, 4.7 and 4.8). Paint and wa llpaper stores also required an increased th re s­ hold po pu l at i on over time among the central villages and were reduced in number in both the first and second period of the study (Tables 4.6, available 4.7 and 4.8). in almost all of the central village classes 1950 and remained available because This function was in in lower order villages in 1970 it required a relatively low threshold of population in 1950 and 1970. The threshold population for this fu n c ­ tion increased significantly in 1980, however, due to d e ­ v el opm ent of the function in the higher order central v i l ­ lages . The threshold population for family clothing stores de ­ creased from 1950 to 1970 (Table 4.6), with an almost stable situation at the township level (Table 4.7). existed at the third order village in other classes of villages, order ones, by 1970 level This function in 1950 and emerged particularly in the lower (Table 4.8). The disappearance of the family cl othing function from fifth and sixth order villages by 1980 (Table 4.8) tion for the revealed the requirements of this fu n c ­ larger threshold populations available in the higher order central villages. The department store, as a higher order (complex) tion, was consi ste ntl y available over time only in the func­ 160 higher order central villages (Table 4.8). In fact, the fifth and sixth order villages of the study area did not offer this fu nction between 1950 and 1980 and fourth order villages were added to that list in 1980. Therefore, the threshold popula ti on required for department stores was always high compared with other functions 4.7). (Tables 4.6 and The lower threshold population for department stores in 1970 was related to an increased number of establishments in the fourth order villages which disappeared from those villages in the second period (1970-1980) when they lost the volume of customers they required to stay in business. sequently, Con­ the threshold po pulation for this function in­ creased in 1980. Shoe stores, as another high order central existed in the higher order villages 4.8). At present, sidents function, in 1950 and 1970 due to the mileage traveled by rural re­ in the study area to shop for shoes in larger c e n ­ tral places (ci ti es ), this function has a high range m a r ­ keting network in the study area (Chapter VI). However, results of threshold population analysis for 1980 4.6) (Table the (Table and the appearance of this function in a fifth order village (Table 4.8) for shoe stores revealed a lower threshold po pulation in 1980. It could be argued, ingness of people surveyed to shop for shoes from the w i l l ­ in big cities that this function is highly competitive and its recent ap ­ pearance in a low order villages is temporary. Some 161 aspects, such as the ing a store lower costs and taxes in a small village, ness operators, involved in op e n ­ are attractive to some b u s i ­ but they face severe problems in attracting the number of consumers required for their survival due to the flexibil ity of a particular function, In summary, order central population. like shoe stores. g r oc ery stores have been shown to be a low functio n requiring the lowest threshold of Therefore, they can be considered an inflex­ ible rural function that can still survive in the smallest villages. Fami ly clo thi ng stores have been upgraded to higher order vi llages since they require greater threshold population. (flexible) Therefore, fun cti on that can be harmed by competition with urban centers. order (flexible) hold p opulation. wallpaper, stores) they are considered a competitive Departm ent stores and shoe stores are high functions that also require greater thr es­ All these functions family clothing, will range models be conside red (Chapter VI) dividual pre ferences (grocery, paint and department stores and shoe later when spatial functional are presented to illustrate in­ in shopping for these functions. Discontinuous Models Of Population And Fu nction Rel ati on sh ip (Hierarchical) The concep t of rank size rule, place theory was hypoth esi zed a component of central in this research and was supported by ex am ina tio n of the continuous relationship 162 between population size and number of functions central villages studied (Figure 4.4). Thus, in all the it was shown that the hypot hes iz ed rel at ionship existed between p o p u l a ­ tion size and number of functions (hierarchical in each class of villages structure or discontinuous m o d e l ) . The hierarchical cla ssification of central places deals wi th the two variables of number of functions places (functional (establishments) hierarchical range) and the total in those central places. for instance, The method of from that used by some in­ vestigators who employed factor analysis 1962 and Smith, 1970) in their research. (Berry, Barnun and and employed the functional index cla ssification used by Davies (1969) functional units clas sif ica ti on of central places used here was different, Tennant, in central (1967) and Marshall Because central place theory is concerned with est ablishing whethe r the size/function re­ lationship are continuous or discontinuous 142), (Haggett, 1977: discontinuous as well as continuous models were c o n ­ structed in the present study to determine the size/function relationships of each hierarchical class of central villages in the study area. Figures 4.6, 4.7 and 4.8 present the discontinuous models which show the maximum range number of different functions) (maximum of each class of central v i l ­ lages and the threshold population for each class. The threshold population of a certain class of villages was d e ­ termined to be equal to the population size of the village 163 Fu nctio n al R ange and Threshold P opulation fo r D iffe re n t Orders o f C e n tra l V illag es: 1 9 5 0 44 - Max. Range: 1st Order Villages Max. Range: 2nd Order Villages 1st Order Villages 2nd Order Villages Max. Range: 3rd O rder Villages Number of Functions 3rd Order Villages Max. Range: 4th O rder Villages 4th Order Villages Max. Range: 5th Order Villages Max. Range: 6th O rder 5th Order Villages I 6th Order Villages Population of Central Villages (LG10) F ig . 4 .6 A d is c o n tin u o u s m o d e l o f lin e a r re la tio n s h ip b etw een n u m b e r o f fu n c tio n s a n d p o p u la tio n s ize o f e a c h class o f c e n tra l villag es in 1950. T h e m axim um ra n g e o f fu n c tio n s a n d th re s h o ld p o p u la tio n (m in im u m size) o f villag es in six o rd e rs a re s h o w n . 164 Functional R ange and Threshold Population fo r D iffe re n t Orders of C en tra l V illages: 1970 36 - M ax. Range: 1st O rder Villages 1st Order Villages Max. Range: 2nd Order Villages Number of Functions 2nd Order Villages 3rd Order Villages Max. Range: 3rd O rder Villages 20 Max. Range: 4th O rder Villages 4th Order Villages - Max. Range: 5th Order Villages 5th Order Villages Max. Range: 6th O rder Villages 6th Order Villages CD I | p Population of Central Villages (LG10) F ig . 4 .7 A d is c o n tin u o u s m o d e l o f lin e a r re la tio n s h ip b etw e e n n u m b e r o f fu n c tio n s a n d p o p u la tio n s ize o f e a c h class o f c e n tra l villag es in 1970. T h e m a x im u m ra n g e o f fu n c tio n s a n d th re s h o ld p o p u la tio n (m in im u m size) o f villag es in six o rd e rs are s h o w n . 165 Functional Range and Threshold Population fo r D iffe re n t O rders o f C e n tra l V illages: 1 9 8 0 Max. Range: 1st Order Villages Number of Functions 1st Order Viiiages Max. Range: 2nd Order Villages 2nd Order Villages Max. Range: 3rd Order Villages 3rd Order Villages Max. Range: 4th Order Villages 4th Order Villages Max. Range: 5th Order Villages | 5th Order Villages Max. Range: 6th O rder Villages l O 6th Order Villages in .cP a> 5 O 1 'inO Population of Central Villages (LG10) F ig . 4 .8 A d is c o n tin u o u s m o d e l o f lin e a r re la tio n s h ip b e tw e e n n u m b e r o f fu n c tio n s a n d p o p u la tio n s ize o f e a c h class o f c e n tra l v illag e s in 1980. T h e m axim um ra n g e o f fu n c tio n s a n d th re s h o ld p o p u la tio n (m in im u m size) o f villag es in six o rd e rs a re sh o w n . 166 of that particular class that had the lowest population. The re gression lines are constructed on the basis of the contin uous re lat ionship of function and population size in central villages of a particular class. structed regression Each of these c o n ­ lines on Figures 4.6, 4.7 and 4.8 shows the direc ti on of the relationship between function and the size of each class of central villages. minimu m (threshold) They also show the and maximum population sizes of villages of that particular class. The re duction in the number of functions among all the classes of central villages has caused a downward relocation of maxim um range of all the classes of central villages (Figures 4.6, 4.7 and 4.8). The maximum range of first and sixth order villages was 46 and 18 in 1950, which declined to 37 and 11 in 1970; 4.7 and 4.8). (Figure 4.4), lages and to 34 and 8 in 1980 (Figures 4.6, As was shown earlier on the continuous model the functional vi ability of the central v i l ­ in 1950 was greater and was significantly related to their p op ul at io n sizes. In 1970 and 1980, however, due to the influx of nonfarm people in central villages and sur­ rou nd in g townships, (residential goods, general the increase of independent functions and recreational boating, etc.) functions such as sporting in some of the villages, decline in the range of functions tional viability) across all classes and the (decline in func­ (Figures 4.6, 4.7 and 167 4.8) the association betwee n number of functions and t hr es ­ hold po pulation was weakened. Therefore, a higher order class of central villages could have had a threshold po p u l a ­ tion less than a lower order class. For instance, the threshold po pulation for third order villages was less than that for fourth order villages (Figure 4.7) populations in the study area in 1970 and fourth order villages had lower threshold than fifth order villages in 1980 (Figure 4.8). In considering the discon ti nu ou s models of re la ti on ­ ship between the po pulation size of villages and their func ­ tional ranges in di fferent classes of villages, the model for 1950 was more salient than those for '1970 and 1980. Moreover, the re gression coefficients show the direction of association between the p op ul at io n size of villages and their numbers of functions was positive 1950; in all cases it was positive for 60 percent of the classes and positive for 83 percent of the classes 4.9 and Figures 4.6, in in 1970 in 1980. (Table 4.7 and 4.8). The negative co r r el a t io n coefficients (Table 4.9) indi­ cated that there was a negative re la tionship between the po pulation size and functional range (number of functions) of a particular class of central villages. In other words, po pulation size was not a de te rm in in g factor of those v i l ­ l a g e s 1 functional viability. tions for residential The increased number of func ­ recreational purposes may have offset the importance of popula ti on size for those villages. TABLE 4.9: Central Village Class Relationship Between the Population Size of Central Villages and Their Numbers of Functions in Regard to Different Hierarchical Classes: 1950, 1970 and 1980 Number of c e n ­ tral villages in a particular class Correlation Coefficient (Pearson 1s r ) Signif icance of r Regression Coeff icient (B Value) 1950: I II III IV V VI 1 1 7 6 11 18 NC* NC .441 .666 .688 .608 NC NC .16120 .07432 .00963 .00404 1970 : I II III IV V VI 3 4 5 7 12 15 - .167 - .472 .972 .191 .591 .589 .44672 .26390 .00254 .34049 .2140 .01038 -1 .86 -52.19 15.22 4.10 12 .86 6 .85 1980 : I II III IV V VI 3 7 4 6 8 18 .083 .759 - .172 .507 .329 .232 .47352 .02380 .41400 .15236 .21341 .17695 0 .79 11 .48 -1.42 11 .23 5 .75 2.33 NC NC 16 29 20 13 .60 .73 .80 .75 *Not computable because there was only one observation in that particular class 169 The majority of central village classes had positive coefficients of correla ti on between population size and functional ranges (Table 4.9); rule in each hierarchical ating, therefore, the rank size class of villages was still o p e r ­ even though the associations we akened over time. An important projection of the change in the h i e r ­ archical time structures of the central villages studied over (See Tables A.l, to be an increase A . 2 and A . 3) was that there was found in the varieties of central a decrease in the total functions and functional units of those central functions in all the central villages. There were 95 v a r ­ ieties of function in central villages studied in 1950, whi ch increased to 97 in 1970 and 104 in 1980, while the total functional units declined from 1301 in 1950 to 907 in 1970 and 763 in 1980 (Tables A.l through A . 6 ). that the d is tr ibu ti on of varieties (types) of functions the central places of the region was horizontal, di str ibution of functional units (stores) It was noted in whi le the of a certain function across the central places of the region is a vertical distribution. For instance, the distr ib ut io n of functional varieties A, B, C, D, and E in each central 1, 2,... 10 on Table 4.1, is horizontal, tion of functional (number of stores) units any other over central places 1, 2, increase in the varieties of central place while the d i s t r i b u ­ of function A or ...10 is vertical. The functions and decreas e 170 in the functional archical units of central villages show the h i e r ­ structure of the central villages of the study area is shortening v e r t i c a l ly and expanding horizontally. tral functions with tional unit) were location coefficients of 100 Cen­ (one func­ important in developing the horizontal expans ion of d if fer en t types of functions amongst the central villages over the study time A . 3). ficient These central cent in 1980. central A . 2 and functions with a 100 location c o e f ­ (high order functions) types of functions (Tables A.l, in 1950, included 14 percent of all 31 percent in 1970 and 28 p e r ­ A dr amatic expansion of these high order functions was seen in the period of 1950-1970. It can be expl ai ne d that due to regional development in the 1950-1970 period in the study region, several new s p eci al ­ ized functions such as whol esa le stores related to m e c h a n i ­ zed farming (farm ma c h i n e r y and equipment s h o p s ) , advanced tran sp or tat io n residential services) (truck rental and leasing a g e n c y ) , increased and h ou seh old demands (rug cleaning and repair were added to the horizontal of the central villages (Tables A.l, functional A . 2 and A . 3). horizontal e xp ans io n of central functions structure The from 1970 to 1980, represe nte d the co nt in u a t i o n of these specialized functions (location c o e f f i c i e n t s = 1 0 0 ) and the addition of rec re at i o n a l- o ri en t ed ing services, functions, in the study area. such as outdoor ad ve r t i s ­ 171 In conclusion, functional the reduction in the total number of units of central functions (vertically) horizontal e xp an sio n of varieties of central are complex and specialized) frame-work, functions (that in a spatial and temporal ver ifi ed the change in the hierarchical tures of central villages studied. It did not, negate the presence of strong hierarchical these central villages. and the st ru c­ however, structure among C H A P T E R FIVE THE ROLE OF RURAL DEVELOPMENT IN CHA NGI NG THE VI AB ILI TY AND SPATIAL DIS TR IB U TI ON OF CENTRAL VILLAGES Change In The Number And Dis tr ib ut io n Of Central Villages Results of the functional clas sif ica tio n of central villages men tioned in Chapte r Four revealed six functional classes of these central vi llages in 1950, (Figures 4.1, 4.2 and 4.3). 1970 and 1980 The number of central villages in each class was found to vary at each of the three points in time (Table 5.1). In order to compare the growth and decline among d i f ­ ferent classes of central villages, have been prepared. Table 5.1 Tables 5.1, 5.2 and 5.3 shows that of all the central villages the first order villages remained fewest and proportion at all three points in number in time, while the sixth order villages remaine d gr ea tes t in number and proportion at those points in the study area. sixth order villages area, The existence of so many in 1950 and 1970 and 1980 in the study implies that h i s t o r i c a l l y the least viable villages have remained a majority, w hi ch does not bode well for the 172 TABLE 5.1: Numbers, Proportions and Percent Change in Proportions of Central Villages Over the Study Time 1950 Number 19 70 Proportion Number Proportion 1950-70 Percent Change 1980 Number 1970-80 Percent Proportion Change First Order Vill ­ ages 1 2.2 3 6.5 4.3 3 6.5 Second Order Vill­ ages 1 2.2 4 8.7 6.5 7 15.2 6.5 Third Order Vill ­ ages 7 15.2 5 10.9 -4.3 4 8.7 -2.2 Fourth Order Vi l l­ ages 6 13.0 7 15.2 2.2 6 13.0 -2.2 11 23.9 12 26.1 2.2 8 17.4 -8.7 -10 .9 18 39.1 6.5 Fifth Order Vill ­ ages Sixth Order Vi l l ­ 15 ages 20 43.5 32.6 Source : Data is collected from Table 4.5 0 174 future development of central villages of this size. the same period, however, the number of fifth, Over fourth and third order villages have changed considerably in proportion to their numbers among the central villages studied. The second order villages fairly consistently represented smaller proportions of the total villages than the third, fourth, fifth and sixth order villages; they exist in greater proportions than the first order villages. In the period from 1950 to 1970 the third and sixth order villages declined in number, while all classes experienced growth in their numbers the other (Table 5.1). should be noted that fourth and fifth order villages It saw propo rt ion at el y smaller increases than first and second order villages. The overall situation implies greater v i a ­ bility among first and second order villages than the third, fourth, cline fifth and sixth order villages. (-10.9 percent) The precipitous d e ­ in numbers of sixth order villages from 1950 to 1970 was related to sufficient growth in some of these villages to lift them to the fifth order level (Table 5.2). However, several to the sixth order level fifth order villages declined in 1970-1980 (Table 5.3). The n u m ­ ber of sixth order villages with their poor functional v i a ­ bility grew over this decade, gaining 6.5 percent in c o n ­ trast to their 10.5 percent decline in the previous years. 20 The increased number of sixth order villages was due 175 TABLE 5.2: Change in Number and Functional Hierarchical Order of Central Villages; 1950-1970 To II From IV III VI II III IV VI Source: 11 Tables TABLE 5.3: 4.5 and A.l, A.2 Change in Number and Functional Hierarchical Order of Central Villages; 1970-1980 To From II III IV VI II III IV VI Source: 11 Tables 4.5 and A.2 and A. 3. 1 76 to decline in the v i a bi lit y of fifth order villages, not to economic progress among sixth order villages. The period from 1970 to 1980 was favorable for the sta­ bility of first order villages and growth of second order ones. Meanwhile third, clined in numbers, fourth and fifth order villages d e ­ some of them growing into the next higher of order villages and others declining to fall sixth order level of villages (Table 5.3). into the It should be mentioned that the stability and increase in number of cen ­ tral villages in the first and second level implies pos i­ tive economic growth in their viability, while the increase in the number of sixth order villages that are economically very weak, implies more economic problems in the future. Regarding the re latively more stable economic conditions in the first and second order villages over both study periods (Table 5.1), it is expected that these highest level v i l ­ lages have been more viable during rural development in the study region, as will be explained later in this chapter. Functional Vi a b i li ty of Different Classes of Central Villages in the Process of Change General Perspective The functional vi ability of central villages in the study region un derwent change over the study periods. tral villages at the top of hierarchy, order villages, Cen­ the first and second experie nc ed growth or stability in numbers from 1950 to 1970 and 1970 to 1980 (Table 5.1) and also 17? showed stable patterns of spatial di st ri b ut io n over the study time third, (Table 5.20 and Figure 5 fourth, ) . In contrast, the fifth and sixth order villages have not been stable in their growth or decline over the study periods (Table 5.1) and, except for the sixth order villages, they have sharply altered their spatial d i st ri bu ti on pattern from random to dispersed or dispersed to random over the study time (Table 5.20). Generally, the growth or decline of c e n ­ tral villages has upgraded or do wn gr ad ed any particular v i l ­ lage to one of the next two prec ed ing or succeeding ranks or classes (Tables 5.2 and 5.3). with Hodge's (1965) This finding was consistent work on trade centers over the period of 1941 in Saskatchewan to 1961 and implied a change in the functional vi ability of central villages wi t h i n their h i e r ­ archical structure. There was a general decline in the range of e s t a b l i s h ­ ments (maximum and minimum) lages studied over time. in all classes of central v i l ­ In a simple presentation, average number of establishments (stores) the per class of villages has declined co ns iderably over the study time (Table 5.4), but the general decline in the establishments of these villages presents a serious economic problem that needs to be consid er ed in greater detail. All -the villages experienced some growth in their populations (Figure 3.12). The populati on /f unc ti on re la tionship was ma intained but was not as strong in 1970 and 1980 as it was in 1950 (Figures 178 TABLE 5.4: Villa ge Class Major Ch ara ct eristics of Different Classes of Central Villages Studied, for 1950, 1970 and 1980 Number of V i l ­ lages Per Class Range of Estabtablishments (Functional Units) Per Class Range of P op u l a ­ tion Per Class Average Number of Total E s ­ tablishments Per Class 1950 1 Class I Class II 1 7 Class III Class IV 6 Class V 11 Class VI 20 86-86 67-67 37-60 29-49 16-31 5-26 86 67 49.4 40.2 23.3 15.4 2580 1596 862-1466 695-1410 339- 730 145- 774 3 4 5 7 12 . 15 49-64 34-52 23-35 25-30 5-17 3-14 55. 7 42 28 26.7 11.25 7.1 1112-3858 1617-1978 595-1650 983-1558 473- 970 175-1251 3 7 4 6 8 18 41-61 20-44 25-30 9-22 7-22 1-8 53.3 30 27.5 17 12.75 4.17 1110-3816 655-2289 962-2171 490-1628 539-1535 155-1008 1970 Class I Class II Class III Class IV Class V Class VI 1980 Class I Class II Class III Class IV Class V Class VI Source: Tables A.l, A . 2 and A . 3; and U.S. Census Of Population For 1950, 1970 and 1980. 179 4.6, 4.7 and 4.8). The weakening importance of the p o p u l a ­ tion size of villages as a factor of their economic growth over the study time, may have been related to the intro­ duction and develop me nt of industrial and recreational a c t ­ ivities in some of these villages over the study time. It has been noted by other researchers that American villages ex pe ri en ced serious losses in their retail ac t iv i­ ties and c o ns eq ue nt ly in their importance as shopping c en ­ ters in the period from 1950 to 1970 and the revival of v i l ­ lage retail bu sinesses was not consistent with their p o p ­ ulation growth in the post-1970 period Fuguitt, 1984:134,135). The central villages of the study area faced the same situation. villages (Johansen and Almost all of the central studied declined in their retail and wholesale functions over 1950-1970 and 1970-1980 the whole period of study (1950-1980), (Table 5.5). Over first order villages had lowest rate of decline and sixth order villages had the highest rate of decline (Table 5.5). that the sixth order villages, hierarchical as the It should be noted lowest rank in the structure of this study, were very vulnerable to rural dev el op me nt and were bypassed frequently by rural families (consumers) in favor of larger central places as a result of regional accessibility and the better selections and prices available for goods and services in urban central TABLE 5.5: Village Class First Order Villages Average Number of Establishments (Total Functional Units) or Stores Per Class of Central Villages and Their Rates of Change Over the Study Periods Average Number Average Number of Es tablish­ of Establish­ ments per ments per Class 1970 Class 1950 Change Rate 1950-1970 Average Num­ ber of E s ­ tablishments per Class 1980 55.7 -35.23 53.3 Second Order Villages 67 42 -37.31 30 Third Order Villages 49.4 28 -43.32 Fourth Order Villages 40.2 26.7 Fifth Order Villages 23.3 Sixth Order Villages 15.4 Source : Change Rate 1950-1980 -4.31 -38.02 -28.57 -55.22 27.5 -1.79 -44.33 -33 .58 17 -36.33 -57.71 11 .25 -51.72 12 .75 +13 .33 -45.28 7.1 -53.90 4.17 -41.27 -72.92 Data is derived from Table 5.4 180 86 Change Rate 1970-1980 181 places (Chapter Six). Johansen and Fuguitt (1979) mention that co mp etition with urban centers was one of the factors that caused the decline services in the retail establishments and in American villages between 1950 and 1970. examina ti on of farm and non-farm families' behavior The shopping travel in the central villages studied confirmed the shopping preferences of the respondents for shopping in the larger central places, Mi chigan (Chapter VI). including the cities of southcentral The reduction in the retail and wh ol esa le activities of central villages over the study time (Tables 5.5 and 5.8) thus resulted from competitive inter­ action betwe en central villages and urban centers due to regional development and rural consumers' ences. As noted earlier, shopping p r e f e r ­ other factors such as te c h n o l o g ­ ical advancement in the study region and agricultural du st ri al iz at io n in­ in farming activities also changed the p a t ­ tern of the rural population in the area and caused the elimina ti on of some central functions (Table 5.6) troduction and increase of other central 5.7) functions or in­ (Table throughout the central villages. In order to investigate and analyze the changes in functional viability of different classes of central v i l ­ lages, their typical central 1980 will be discussed here. terpre ting central changes functions in 1950, 1970 and It should be noted that in in­ functions and their variations and in different classes of central villages the term 182 "typical function" is used in this research to indicate the existence of a functional unit (store) of a certain function oc curring in at least a third of the central villages of a certain class, is that the average number of that function .33 or more. For instance, if there are four drugstores and one weldi ng and repair store in first order villages (three v i l l a g e s ) , the average number of drugstores order villages will be: in first 4/3 = 1.33 and the average number of weldin g and repair stores will be: 1/3 = .33. Thus, the functions of both drugstore and welding and repair store are "typical" in first order villages. age numbers lower than considered typical The functions with a v e r ­ .33 in a class of villages are not in this research. General Change in the Central Functions And Rural Services of Central Villages The hypotheses cited in Chapter Two of this research a nticipated that rural development (including agricultural industrialization and transportation development in southcentral Michigan) of change w ou ld be found to be an important factor in the viability of central villages over the study time. tion that was The impact of an agricultural instrumental tions with new ones industrializa­ in replacing the outmoded f u n c ­ in the villages and small towns of the United States has been examined in empirical studies which found that most of the villages of the Middle West that 183 offered similar rural functions in the horse and buggy era later lost those functions with the popu la riz ati on of the automobile (Hart, Sa lisbury and Smith, Jr., transport replaced the horse and wagon, lated businesses 1930s) (such as auto repair garages) towns and villages and Stafford, As motor horse and wagon re ­ livery and blacks mi th ing in the declined and auto- rel ate d businesses oline service stations, 1968). (such as g a s ­ automobile sales and services, and arose and pros pe re d in American small (Johansen and Fuguitt, 1973; Smith, 1970; 1963) . In order to investigate the situation in the central villages of the study area, Table 5.6 shows those central functions that were available in 1950 in the villages, wh ich had ess ent ial ly di sa ppe are d by 1970. tions, but The older func ­ such as shoe and harness rep airing and blacksmithing, were available in the central villages 55.83 percent of farms in 1950 since only in the study region used tractors e x ­ clusively, while the rest were still using horses for farming (Table 3.1). The higher average number of wheel tractors per farm and increased percentage of farms having wheel tractors by 1970 and 1980 (Figure 3.2), clearly ex ­ plains the disappe ara nc e of the outmoded shoe and harness repairing and b la ck smi th in g functions lages after 1950. from the central v i l ­ The concurrent significant increase in the population of tractors and corn pickers in southcentral Michigan in the 1950 to 1970 period (Figures 3.2 and 3.3) was influential in increasing the number of farm machinery and equipment dealers and the number of fuel oil, petroleum, and gas dealers (Table 5.7). trucks Indeed, (Fugure 3.4) in central villages studied the increase in farmers using motor and the 34.3 percent increase of n o n ­ farm families moving into rural 1950 to 1970 liquified (Table 3.3) southcentral Michigan from and commuting to urban jobs favored the creation of motor vehicle dealerships to eventually re­ place the general machine and supply shops that were common in 1950 in the central villages studied (Table 5.7). continuing but slower rate of change in agricultural The indus­ trialization in the study area in the 1970-1980 period (Chapter T h r e e ) , had almost stabilized the growth of the above functions in central villages by 1980. General stores, a vital and typical function of all the central villages in 1950, were represented by 39 stores (Table 5.6) that disappeared in the later decades. stores were essential for providing household needs, cluding food and nonfood items, pliances. General in­ household supplies and a p ­ They were a locally convenient, general function for rural residents who tended to do their shopping in the small rural places. The function of the general store was replaced by department stores in the 1950-1970 period, when the number of department stores in the central villages doubled (Table 5.7). The department stores themselves d e ­ clined in the 1970-1980 period (Table 5.7), when modern 185 TABLE 5.6: Central Functions Offered in Central Villages 1950 That Had Disappeared by 1970 Number of Func­ tional Units (Es­ tablishments) in 1950 Central Functions * Proportion of Total General Stores 39 3.0 Foodstores & Misc. 38 2 .92 General Hardware 26 2 .0 Publishing & Printing 17 1.3 Shoe & Harness Repair 15 1.15 Radio 14 1.08 Men's Wear Shops 14 1.08 Food Lockers 10 . 77 7 .54 Women's Wear Shop 6 .46 Blacksmith 5 .38 Fuel, (Sales & Service) Coal, Feed, Etc. in * There was a total of 1,301 functional units (establishments) in all the central villages in 1950 (Table A . 4). In c a l ­ culating the proportion of the total represented by each central function, those functional units were divided by 1,301 and then multiplied by 100. SOURCE: Data is derived from Tables A . 4, A.5, and A . 6. 186 TABLE 5.7: Central Selected Central Functions That Increased or E m ­ erged in the Central Villages Over the Study Time. Functions Machine Shop & Supplies (1950); Motor Vehicle Dealers (1970, 1980 ) Oil & Gas (distro) Co: 1950; Fuel oil de al er & petroleum & related dealer: 1970, 1980 Farm m a c h i n e r y (1950): Farm equip, dealer (1970); Farm Supplies (1980)* Sporting Goods Department Store * Family Clothing Store Boat Dealers Radio & TV Repair Shop* Radio & TV St or e * Women's Ready-to-Wear Shop Liquor Store Farm & Garden Machinery & Equip. House Trailer dealer (1970); auto & home supply store (1980) Men's & Boys ’ Clothing Floor Covering Store Industrial Supplies Sewing Store Mobile Home Dealer Hobby, toy and game Shop Outdoor Advertising Service 1950 Functional Units 1970 1980 25 31 32 15 23 24 10 7 3 2 1 0 0 0 0 41 10 6 4 5 17 16 11 7 21 15 3 5 7 7 11 12 11 0 6 25 0 0 0 0 0 0 0 0 6 5 1 1 0 0 0 0 11 6 6 5 6 5 2 1 *. These central functions are selected because they have significant growth or emergence in their numbres of functional units in the first period of study time. Source: Data is derive d from Tables A .4, A.5 and A . 6 . 187 rural super markets offered more specialized goods and more convenient shopping for the rural consumers Indeed, (residents). the huge department stores of rural central places became readily accessible to those rural transportation d e v e l o p m e n t ) • families Some other functions (due to includ­ ing men's wear shops and women's wear stores available central villages in in 1950, were replaced by 1970 with spec­ ialized men's and boys' clothing stores and women's ready- to-wear shops that were more applicable to the new life styles of rural residents (Tables 5.6 and 5.7). Another impact of rural development in changing the viability of central villages was its tendency to reduce residents' depende nce on or use of certain central village functions. Bracey (1956:50) local mentions that the industrialization of agriculture and the development of means of communi cat ion in concert with changes in the habits and customs of local people, tions of small central places have changed the central (towns) in England. func­ Indeed, when the improvement of tr ansportation technology increased the urban accessi bil ity of American rural families they b e ­ gan to patronize tral places large retail establishments of larger ce n ­ (cities) with a resulting decline in the retail sections of villages in the United States in recent decades (Johansen and Fuguitt, 1973, 1979 and 1984). Significant super highway development in southcentral Michigan Three; Figure 3.10) (Chapter and its central villages and local network development (Figure 5.1) du r i n g the periods of 1950 to 1970, and 1970 to 1980 increased the access ib ili ty of larger central places, rural such as Lansin g and Jackson, families of the study area. cess to cities and urban centers, for the W i t h this increased a c ­ a significant decline o c ­ curred in central village functions (retail and w h o l e s a l e ) , as shown in Table 5.8, pa rt icu lar ly in the first period of the study. This decline in functions of economic competit io n with implied the emergence larger central places which could afford both specialized and volume buying and could offer a better va rie ty of goods at lower prices. cept of economies of sale was thus influential The c on ­ in the new spatial di stribution of central functions. All the central functions shown to be declining in Table 5.8 were also found to be declining in the works of Jo ha n s en and Fuguitt on Wisconsin villages lages (1984:118, (1973:211, 119) 212) and other American v i l ­ in the perio d of 1950-1970. In spite of the decline and di sa ppearance of central functions in the central villages of the study area, have been additions there to some ex isting functions or the in­ troduction of new rural functions that are related to new or increased demand for particular goods and services. ample, the 10 farm mach inery shops in 1950 had increased to 41 by 1970 (Table 5.7). For ex ­ in the central villages (termed farm equipment dealers) The significant increase in this fun c­ tion was related to revolutionary nature of the agricultural 189 TABLE 5.8: Selected Central Functions Found to Have Declined in the Central Villages Over the Study Time. Central Functions Grocery Store Gasoline Service 1950 116 Station Functional Units 1970 1980 93 65 107 102 38 Autobody Repair Shops & Garages (1950) or General Auto. Repair s h o p s (1970,1980 ) 54 13 9 Hardware 53 49 48 Elevator (fuel & Feed; grain & bean) and Feed S to r e s : 1950; grain elevator & feed stores: 1970; grain e l e v a t o r s :1980 45 38 21 Drugstore 42 31 22 Electric sup. (sales & serv.) 1950; Electric repair shops & sup. stores:197Q; Electrical & Electronic repair shop:1980 29 4 3 Varie ty & Gift Shops'* 27 20 22 Funeral 26 25 9 Plumbing & Heating 25 4 1 Confectionery 21 3 2 Furniture Store 18 15 14 Auto sup. (1950); auto equip. parts & b a t te ry ,t ir e and acces sory dealers (1970,1980) 17 16 11 Jewelry Store 17 9 7 Meat or meat & fish market 12 6 3 Welding & Repair 12 3 1 Dry cleaning & laundry 11 6 1 Dairy product store 10 7 1 9 2 4 Store Service & Paint,glass and wallpaper store * *. These functions are selected because they experienced great decline in the first period of the study. SOURCE: Data is derived from Tables A. 4, A.5 and A .6 me cha ni za tio n and industrialization that took place from 1950 to 1970 in the study region (Chapter T h r e e ) . velo pme nt and application of new farm machinery, The d e ­ equipment and supplies of increasing sophistication ac ce lerated the developm en t of mechanized, specialized and incorporated farming and provided the impetus and opportu ni ty for in­ cre asing the farm equipment dealerships lages of the study area in 1970. in the central v i l ­ The emergence of six farm and garden machinery and equipment stores in 1970 and their increase to 25 in 1980 (Table 5.7) reflected the new demands of farm and nonfarm families for hobby or small g a r ­ dening tools and supplies. The concurrent decrease in the number of farm equipment dealers from 41 in 1970 to 21 in 1980 reflected the trend to fewer and larger farms and the influx of part-time or hobby farmers whose needs swelled the number of farm and garden machinery and equ ipment dealers from 6 in 1970 to 25 in 1980 (Table 5.7) in the central villages. The increase of sporting goods stores and boat dealers over the three points of the study time (Table 5.7) in­ dicated the increasing demand for leisure time and r e c r e a ­ tional activities that developed in the central villages, parti cu la rl y from 1970 to 1980, due to increase in the rural nonfarm population and the development of recreational tions in the central villages. dealers; hobby, fu n c ­ The emergence of mobile home toy and game shops; and outdoor advertising 191 services in the central villages (1970-1980) related to the in creasing residential was likewise functions of the cen ­ tral villages and their hinterlands and the increasing importance of leisure time pursuits and recreational ac t i ­ vities in the study reg io n in recent years. Overall, the d e c li ni ng functions and their respective establishments across the central villages the new or i n cr ea si ng central iod. studied exceeded functions over the study p e r ­ Acc or di ng to Tables A . 4, A . 5 and A . 6 , the total number of retail and wh o l e s a l e establishments lages was 1,301 (-30.28 percent) in the central v i l ­ in 1950 which declined to 907 in 1970 and to 763 in 1980 (-15.88 percent). The greater re duction in central village function took place in the first period of the study which was most closely a s s o c ­ iated with re vo l u t i o n ar y rural develop me nt in the study region. Change in social or public functions villages came about differently. tions, Public and social including religious and social among general 1963:168). functions in American small towns studied, (Stafford, functions in the for w hi ch data were available, shown in Table 5.9 for 1970 and 1980. found to have little func ­ facilities rank second These pub li c or professional central villages in the central are Most of these were importance in the functional viability of central villages due to their For instance, church, school, veterinarian, attorney, low Lo ca ti on Coefficients. doctor's office, bank, dentist, and barbershop ranked among the 192 Table 5.9: Functional Units of Rural Services, Including Professions, in Central Villages: 1970-1980 Functional Rural Services Including Professions Units 1970 1980 School 97 69 Church 89 195 Bank 36 47 Doctor's Office 28 64 Barbershop 22 27 Dentist 21 36 Attorney 15 32 Veterinarian 11 32 Optometrist 2 9 Clinic 1 8 Hospital 1 1 Source: Data is derived from Tables A . 7 and A .8 lowest order functions in the location c o ef fic ien t cl as s i ­ fication (Table 2.3). Optometrists and clinics fell into the second and third rank of ten classes of functions a c ­ cording to their location coefficients; Were exceptional (Table 2.3). professional and only hospitals for their higher location coe ff ici ent Therefore, functions the increase in these public and (except schools and hospitals) over the period from 1970 to 1980 was not as significant as that of retail and wholesale functions in changing the economic viability of the central villages. This does not lessen their importance, however, because their social influence cannot be ignored. and cultural The increase of these public functions was closely related to the increase of po pulation that resulted from rural development in the study region (Chapter Three). (-28.9 percent) Among these functions, schools declined in response to regional d e v e lo pm en t and a policy of school consolidation in the central villages, ac­ cording to information derived from public questionnaires. It should be noted that consistent with school c o n s o l i d a ­ tion techniques, first order villages gained schools, all other classes of villages ciple of economies of scale lost schools. Thus, establishing a large school, a prin­ (concentrating functions) applied in the region for its economic advantages. while was In fact, which is viable economically, is preferred to having several uneconomical, small and 194 di spersed schools in regional planning for a certain region (Cloke, 1979) . Functional Changes of First Order Villages First order villages, as the strongest class in the functional v ia bil it y classification, had the lowest rate of decline in the average number of their total establishments from 1950-1980 com pa re d with other classes greatest rate of decli ne in retail (Table 5.5). The and who le sa le activities is seen in the first period of study, when it is almost a general 5.5). trend for all of the central villages studied (Table The technological changes in the study area from 1950 to 1970 encouraged the elimination of functions Table 5.11, cellaneous in cluding general stores, (g r o ce ry ) , shoe and harness listed on food stores, and m i s ­ repair and radio shops and services from the first order villages. Pu b l i s h ­ ing and printing d i s ap pea re d from the first order villages probab ly due to the failure of local newspapers ition with those of larger towns and cities that offered more news and a d v er ti sin g for larger stores tral places. in c o m p e t ­ The decli ne in other typical in larger c en ­ functions in first order village s during the first period of study in­ cluding grocery stores, general trend for all and 5.10). gas stations and drug stores was a of the central villages But in all cases, (Tables 5.8 the first order villages had 1 95 more total establishments representing these three fu n c ­ tions . The decline of these three functions in 1950-1970 was related to the decrea si ng demands for them by local people who traveled further and did their multipurpose shopping in the chain depar tm en t stores such as Meijers and K-Marts in nearby cities that offered cheaper goods and were equipped with nearby gasoline service stations. These three central functions declined in all of the central villages periods of study (Table 5.10). But, crease in the number of drugstores in 1970-1980. This in both there was only an in­ in first order villages increase of drugstores in the first order villages was related to their significant decrease in the other classes of villages. Drugstores were a typical function in all classes of central functions in 1950, were typical in all of them except sixth order villages in 1970, but became typical only for first, order villages in 1980 central (Table 5.10). functions of electrical meat and fish markets, duct stores second, third and fourth The decline in typical supplies and repair shops, dry cleaning services and dairy p r o ­ in the first order villages (Table 5.13) was re­ lated to the decline and di sa ppearance of these functions from all of the classes of villages and was continued in the second period of the study (Table 5.10). The decline and di sa ppearance of these functions was related to the pr inciple of economies of scale, meaning that 196 TABLE 5.10: Selected Central Functions That Declined in the Central Villages by Average Value Class for 1950, 1970 and 1930 Central Functions Grocery Store: 1950 19 70 1980 First Order villages Second Order Villages Third Order Villages Fourth Order Villages Fifth Order Villages Sixth Order Villages 9 .00 5.00 3.67 4 .00 3.25 2.71 3 .00 2 .80 1.75 3 .40 2.43 1 .67 4 .20 1.33 1 .75 1 .75 1.20 .22 8 .00 5 .33 2.67 6 .00 3 .00 1.71 6 .10 3 .20 .75 5 .30 3 .43 .67 3 .10 1.42 .75 2.70 1.13 .28 Auto Body Repair Shops or General Auto Repair Shop: 1950 3 .00 1970 .33 1980 1.00 2 .00 .50 .14 1.57 .40 .25 1.17 .43 .17 .73 .08 0.00 1.15 .27 .17 Hardware Store: 1950 1970 1980 2 .00 1 .70 1.33 2 .00 2.25 1.86 1.60 1.20 1.S0 1.50 1.29 1.33 .80 1 .08 .62 1 .00 .47 .67 Grain Elevator & Feed Store: 1950 19 70 1980 1.00 1 .33 .33 1.00 2.00 .57 1.58 .80 1.00 1.01 1.15 .83 .81 .66 .50 .85 .40 .17 Drugstores: 1950 19 70 1980 3 .00 1.70 2.67 2 .00 1.50 1.00 1.57 1.00 .50 1.34 1.00 .50 .91 .42 .20 .40 .20 0 .00 Electrical Supplies & Repair Shops: 1950 1970 1980 1.00 .33 .33 3.00 .25 .25 .57 .20 0 .00 1.17 .14 0 .00 .73 0 .00 0 .00 .30 0.00 0.00 Funeral Services: 1950 1970 1980 1.00 1.70 .67 0 .00 .25 .29 .86 .80 .50 .67 1.00 0 .00 .64 .33 .12 .40 .80 .11 Plumbing s, Heating: 1950 1970 1980 0 .00 .67 0 .00 0.00 0 .00 .14 1.43 0.00 0.00 1.17 .14 0 .00 .36 .08 0.00 .20 0 .00 0.00 Confectionery: 1950 19 70 1980 1.00 0 .00 0 .00 3.00 .25 .29 1 .00 0 .00 0.00 .57 .14 0.00 .09 .08 0.00 .25 0 .00 0 .00 Furniture Store: 1950 1970 1980 0 .00 .67 1.67 1.00 .75 .43 .86 .20 .50 .34 .86 .50 .36 .25 .12 .25 0 .00 0 .00 Auto Supp.S Equip: 1950 1970 1980 2 .00 1.67 1.33 3 .00 1.50 .14 .57 0.00 .75 .34 .14 .17 .36 .16 .12 .10 .14 .06 Jewelry Store: 1950 1970 1980 2 .00 1 .00 1 .33 2.00 .50 .29 1.14 .40 .25 0.00 .14 .17 .27 0 .00 0 .00 .05 .07 0 .00 Meat. & Fish : 1950 1970 1980 1.00 .33 0 .00 0 .00 .50 .14 .86 .20 0 .00 .17 0 .00 .17 .18 .17 .12 .10 0 .00 0 .00 0 .00 .33 0.00 0 .00 0 .00 .14 .71 .20 0 .00 .17 0 .00 0 .00 .27 0 .00 0 .00 .15 .07 0 .00 1.00 .67 0 .00 2.00 .50 0 .00 .57 0.00 .25 .34 .29 0 .00 .09 0 .00 0 .00 .05 0.00 0 .00 1 .00 .33 0 .00 2 .00 .25 .14 .29 .60 0 .00 .50 .29 0 .00 .09 0 .00 0 .00 .05 0.00 0 .00 Gasoline Service Sta 1950 1970 1980 Welding & Repair: 1950 1970 1980 Dry Cleaning: 1950 1970 1980 Dairy Production: 1950 19 70 1980 SOURCE: Data is derived from Tables A.4, A.5 and A.6 and 5.5 Per TABLE 5.11: Selected Central Functions That Essentially Disappeared From the Central Villages After 1950, by Average Number of Total Establishments per Class of Central Villages for 1950 Cen tral Functions First Order Villages Average Number of Total Establishments Second Third Fourth Fifth Order Order Order Order Villages Villages Villages Villages General Store 1.00 0 .00 .71 1.17 1.18 .65 Food Stores & Misc. 2.00 1 .00 1.43 1.17 .82 .45 General Hardware 2.00 1 .00 .57 .83 .64 .35 Publishing & Print. 1.00 1 .00 .86 .67 .18 .15 Shoes & Harness Repair 1.00 0 .00 .57 .67 .27 .15 Radio Shops & Service) 1.00 0.00 .57 .67 .27 .10 Men's Wear Stores 2.00 2 .00 .71 .34 0 .00 .15 Food Lockers 0.00 1 .00 .29 .50 .18 .10 Fu e l , O i l , Feed , etc. 0.00 1 .00 .71 0.00 0 .00 .05 Women's Wear Stores 0.00 2 .00 .29 .17 0 .00 .05 Blacksmithing 0.00 .43 0 .00 .09 .05 SOURCE: Sixth Order Villages (Sales 0.00 Data is collected from Tables A.4, A.5 and A .6 198 these functions lost their viability in central villages and were conso lid at ed in larger cities. Grain elevators and feed stores that declined generally in the central villages studied over the study time functions and 1970 (Table 5.8) were typical central in all of the classes of central villages in 1950 (Table 5.10). They declined dramatically in all of the central villages during the second period of study (Tables 5.8 and 5.10) third, and became typical for first, fourth and fifth order villages in 1980. in these local elevators, second, The decline particuarly in the period of 1970- 1980, was related to the development of fewer but more e f ­ ficient industrialized and specialized grain elevators central villages and urban central places. significant increase Indeed, in the in average farm income was due to farm in du st rialization in 1970-1980 (Figure 3.8) and weal th ie r farmers preferred to deal with larger scale and more e f ­ ficient and economical elevators that were responsive to the advanced industrialized farming in the study area. In the public questionnaires of this research it was revealed that about thirty-five percent of farmers lages' in central v i l ­ hinterlands bypassed their local towns to visit the larger elevators in other central places. Farm ma chinery and farm-and-garden equipment stores) (47 had more than quadrupled in the central villages by 1970 compared with the 10 farm machinery and equipment stores in 1950 (Table 5.7). This function thrived due to 199 agricultural villages i n d us t ri al i za ti on in the hinterla nds of central that required more sophisticated agricultural equipment re sponsive to the rev olutionery progress in m e c h ­ anization in the study area from 1950 to 1970 (Chapter Three). second, This functio n was typical and fourth order vil lages for first, third, in 1950 and became almost typical of all the villages by 1970 and 1980 (Table 5.12). This means that this particu la r function is a viable central function that has ex ist ed at all the levels of central villages over the time of the study. This function is p a r ­ ticularly strong in first order villages. The in tro duction and popular use of te levision by rural residents of the study area in the early 1960s meant the radio stores and repairs in 1950 were replaced by radio and TV stores and repairs at the end of the first period of study in first, second, (Tables 5.12 and 5.13). third and fourth order villages It was still a typical these four classes of central villages period. The ad op ti on of TV by rural in the function of 1970-1980 farm and nonfarm f a m ­ ilies in the study area was a result of technological vancement and change in the over the study period. ad­ lifestyles of these families Any such adoption of a te ch no lo gi ­ cal advancement will be influenced in ch anging the vi ability of central villages. The increase of rural population in both periods of study in the region and in the townships surrounding the 200 TABLE 5.12: Selected Central Functions That Either Emerged or Increased in the Central Villages, by Average Value Per Class of Central Villages for 1950, 1970 and 1980. Central Functions First Order Villages Second Order Villaqes Third Order Villaqes Four th Order Villaqes Fifth Order Villaqes Sixth Order Villaqes Machine Shops or Motor Vehicle Dealers: 1950 5 .00 19 70 3 .03 2.67 1980 1 .00 1 .75 1 .43 .29 1 .00 1.75 1 .00 1 .28 .34 .55 0.00 .62 .25 .07 .06 Oil 4 Gas 4 Petroleum: 1950 1 .00 .67 1970 1980 1 .00 1 .00 2 .25 1 .01 .43 .40 .75 .50 .42 .34 .36 .33 ■2S .15 .20 .12 Farm Equip. 4 Farm 4 Garden Machinery 4 Equip: 1950 1970 1980 2 .00 1.33 1 .66 1.00 3.25 1 .14 .29 .60 2.25 .34 1.72 1.13 .09 .25 .87 .10 .80 .50 Sporting Goods: 1950 19 70 1980 0 .00 .33 1.33 1 ,00 .50 .71 .43 .60 .50 .34 .43 .17 0.00 .08 0.00 .05 0 .00 .17 Family Clothing Stores 1950 0.00 1970 0 .00 0 .00 1980 0 .00 .25 .14 .29 0 .00 .50 0 .00 .14 .33 0.00 .08 0.00 0 .00 .07 0 .00 Boat Dealers: 1950 19 70 1980 0 .00 .33 .67 0 .00 0 .00 .29 0 .00 .40 .25 .17 .14 .17 0.00 .08 .12 0 .00 0 .00 0 .00 Radio 4 TV Store 4 Repair: 1950 19 70 1980 0 .00 2 .00 .67 0 .00 1.00 1 .14 0 .00 1 .80 1.25 0 .00 .43 .46 0.00 .25 .17 0 .00 .07.12 Women‘3 Ready-to-wear Shops: 1950 1970 1S00 0 .00 .67 1 .30 0 .00 .50 .71 0.00 .80 .30 0.00 .29 .17 0.00 0 .00 0.00 0.00 .07 0 .00 Liquor Stores: 1950 1970 1980 0 .00 .67 1.33 0 .00 .50 .29 0.00 0 .00 1.00 0 .00 .14 0 .00 0 .00 .17 .12 0 .00 0 .00 0.00 House Trailer Dealers: 1950 0 .00 1970 .33 .67 1980 .25 .25 .43 0 .00 .40 .75 0 .00 .14 .17 0.00 .08 .25 0 .00 0 .00 0 .00 Men's 4 Boy'3 Clothing Store: 1950 0 .00 1970 .67 1980 .67 0 .00 .50 .43 0 .00 .20 .25 0 .00 0 .00 0 .00 0 .00 0 .00 0.00 0 .00 0 .00 0 .00 Floor Covering Store: 1950 1970 1980 0 .00 0 .00 .67 0 .00 0 .00 .43 0 .00 .20 0 .00 0 .00 0 .00 0.00 0 .00 0 .00 .12 0 .00 0 .00 0 .00 Industrial Supp: 1950 1970 1980 0 .00 .33 1 .00 0 .00 0 .00 .14 0 .00 0.00 .25 0 .00 0.00 0 .00 0 .00 0 .00 0 .00 0 .00 0 .00 0 .00 Sewing Store: 1950 19 70 1980 0 .00 0 .00 .33 0 .00 0 .00 .29 0 .00 0 .00 0 .00 0.00 0 .00 0 .00 0 .00 0 .00 .37 0 .00 0 .00 0.00 Mobile Home Dealer: 1950 19 70 1980 0.00 0 .00 0 .00 0 .00 0 .00 .14 0.00 0 .00 0 .00 0.00 0 .00 .33 0.00 0 .00 .25 0.00 0 .00 0 .00 Hobby Shop: 1950 19 70 1980 0 .00 0 .00 0 .00 0 .00 0 .00 .29 0 .00 0 .00 0 .00 0 .00 0 .00 0.00 0 .00 0 .00 0 .00 0 .00 0 .00 0 .00 Outdoor Advertising Service: 1950 1970 1980 0 .00 0.00 .33 0 .00 0 .00 0 .00 0 .00 0 .00 0 .00 0 .00 0 .00 0 .00 8:88 8:88 8:88 SOURCE: Data is collected from Tables A.4, A.5 and A.6. 201 TABLE 5.13: Typical Central Order Villages: Functions Offered 1950, 1 9 7 0 and Central Functions 1950 Grocery Store 9 .00 Gasoline Service Station (Filling & Service Station) 8.00 Hardware Store 2.00 5 .00 Eating Place (Restaurant) 3 .00 Drugstore 2 .00 General Store Food Stores and Misc. 2.00 Drinking Places (Taverns & Bars) 2 .00 Implements (Agricultural) 3 .00 Electrical Supply Stores (Sales & Service) 1 .00 Variety & Gift Shops 1.00 Auto Body repair Shops & Garages (1950) or general automobile repair shops (1970,1980) 3 .00 Funeral Services 1 .00 General Merchandise Store 0 .00 General Hardware Store 2.00 Machine Shops & Supp. (1950) Motor Vehicle Dealers (1970 1980 ) 5 .00 Confectionery & Misc. 1.00 Jewelry Store 2.00 Publishing & Printing 1.00 Auto Supplies (1950); a u t o ­ mobile equip, parts, battery, tire and accessory dealers (1970,1980) 2.00 Shoes & Harness repair 1 .00 Oil & gas or petroleum and related 1 .00 Radio (Sales, Serivce) 1.00 Men 1s Wear 2.00 Lunchrooms 1.00 Meat or Meat & Fish market 1 .00 Dry Cleaning & Laundry 1 .00 Dairy Product Store 1.00 Farm Machinery (Supplies lor equip, dealers 2 .00 Grain Elevator & Feed Store 1.00 Florist (Greenhouse) 2 .00 Paint, Glass & Wallpaper Stor el .00 Flour Milling 1 .00 1 .00 Billiards in F i r s t 1980 Average Number 1970 5.00 1980 3.67 5.33 1 .70 3 .00 1 .70 0.00 0 .00 2 .67 1.33 3.00 2.67 0 .00 0 .00 2.33 0 .00 1.33 0 .00 .33 1.67 .33 2.67 .33 1 .70 .67 0 .00 1.00 .67 .33 0.00 3 .03 0.00 1 .00 0 .00 2.67 0 .00 1 .33 0 .00 1.67 0 .00 1.33 0.00 .67 0 .00 0.00 0 .00 .33 .67 .33 1 .00 0.00 0 .00 0 .00 0 .00 0.00 0.00 1.33 1.33 .67 0 .00 0.00 0 .00 .33 .33 1.33 .33 0 .00 0.00 202 TABLE 5.13: Cont. Central Functions 1950 Department Store 1.00 1 .00 Shoe Stores Photo or Photofinishing Labs 1 .00 Car Washes 1.00 1.00 Household Appliance Stores Farm and Garden Machinery & 0.00 Equipment Lumber & Building Material 0 .00 Dealers Radio & TV Stores & Repair 0.00 Shops 0.00 Furniture Store Women's Ready-to-Wear Stores 0 .00 0 .00 Sporting Goods & Services 0 .00 Bowling Alleys Lumber & Construction 0 .00 Materials Liquor Stores 0 .00 House Trailer Dealers (Auto & Home S u p p . Store) 0.00 Boat Dealers 0 .00 0 .00 Fuel & Ice Dealers Men's & B o y s ’ Clothing Stores 0.00 Retail Bakeries 0.00 Plumbing and Heating 0.00 Used Car Dealers 0 .00 Paper & Paper P d s . 0 .00 Welding Repair 0.00 Used Merchan di se or Second Hand Store 0 .00 Automatic machinery 0.00 Drapery, Curtain & Upholstry Stores 0.00 Fresh Fruits & V e g s . 0.00 Industrial Supplies 0 .00 General Auto. Shops 0 .00 Retail Nurseries 0 .00 Floor Covering Store 0 .00 Sewing Stores 0.00 Cigar Stores 0 .00 Misc. Home Furnishing Stores 0.00 Data Processing Service 0 .00 Motorcycle Dealers 0.00 Farm Product Raw Materials 0 .00 Metal Service Centres 0 .00 Outdoor Advertising Services 0 .00 Family & Commercial Laundries 0 .00 Service Establishment Equip & 0.00 Supplies SOURCE: Tables A . 4, A . 5 and A. 6. Average Number 1970 1 .00 0.00 .33 .33 .33 1980 .67 0 .00 0 .00 .33 .33 0 .00 1 .33 1 .00 1 .33 2 .00 .67 .67 .33 1.00 .67 1 .67 1 .33 1 .33 .67 .33 .67 .33 1 .33 .33 .33 .33 .67 .33 .67 .33 .33 .33 .67 .67 0 .00 .67 .33 0 .00 0 .00 0 .00 0 .00 .33 .33 .33 0 .00 .33 .33 0 .00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 .33 0 .00 1 .00 1 .00 .67 .67 .33 1 .33 .33 1 .00 .33 .33 .33 .33 .33 0 .00 .33 203 central villages studied recreational (Figure 3.12) and the increase of activities in this area favored some central functions such as sporting goods, boat dealers and ho use ­ hold trailer dealers over the study time (Table 5.12). Sporting goods became a typical function for first order villages in 1970 and had increased by 1980. and house trailers were non-typical central villages in the 1950s, functions introduced to but had become typical some of the classes of villages, villages by 1970 and 1980 Boat dealers including first order (Table 5.12). The emergence of some new typical central such'as data processing services, outdoor advertising services lages in 1980 order villages in (Table 5.13) functions motorcycle dealers, and in first order central v i l ­ implied the development of first in business and rec rea tio n-oriented act iv i­ ties in 1980. At the present time, trial, agricultural, functions. first order villages serve indus­ recreational, social and residential The significant increase in the industrial tion of first order villages began in the 1960s. these industries, such as the Dexter Mill, Some of provide feed and grain for animals and serve the farming population. crease of the non-farm func­ The in­ popula tio n and hobby or part-time farming in the hinterlands of these villages increased the garden supplies and pet supplies functions in first order villages. Grain elevators, agricultural shops and fairs 204 (tractors, implements, farming needs, tools, farm appliances) including gloves and boots for farmers, supplies, and feed for farm animals are central tural functions serving today's farming needs der villages. and other vet ag ri cu l­ in first o r ­ These first order vil lages are visited by about 70 percent of the farmers for el ev at or and feed sup­ plies and are bypassed by other farmers in larger central places. non-farm families' functions Detailed patterns of farm and shopping for certai n sampled central in the central villages Chapter Six. for grain elevators Such patterns studied are di scussed in show the p at ron iz ati on or dis- patronization of central villages for different functions. The increase of rural non-farm p o pul at ion due to r e­ gional development in the farm landscape and co ns equently in the townships surrounding the first order village, was su p­ portive for development of rural socially oriented functions. tors, barbershops, tometrists, dentists, services Schools, attorneys, that are primarily churches, banks, veterinarians, clinics and hospitals grew con siderably order villages in the 1970-1980 period school consolidation, second, third, fourth, sixth order villages witnessed declines number of schools (Table 5.19). (Table 5.19). Thus, The increase of rural also enhanced the residential op­ in first Due to and in their average only first order v i l ­ lages may be considered viable for schools' scale policy. fifth, doc­ economies of non -farm population fu nction of central villages 205 and caused housing and apartment development around first order villages' limits. In conclusion, first order villages have had smaller losses in their retail sections compared with other classes of central villages over the study period. industries (manufacturing) tunities that are positive Their agricultural Their growth in has provided employment o p p o r ­ signs for future development. functions have declined but they have become more efficient and more agri-business oriented. growth in their recreational by newcomers and rural activities has been supported non-farm families and has been he l p ­ ful for the growth of some retail dealers functions such as boat in the first order villages. lages' residential future increases The The first order v i l ­ function will continue to develop due to in non-farm population. It is anticipated acco rdi ng to the public questionnaires, that these first order villages will grow as rural towns in the future. Functional Changes of Second Order Villages Second order villages periods of study increased their numbers (Table 5.4) in both and thus may be considered the second most viable group among the classes of villages studied. The decline (functional units) the greater decline in their retail and wholesale stores in both periods of study in the first period) (particularly was a phenomenon that was consistent for almost all of the central villages 206 in the study periods tral (Table 5.5). functions available miscellaneous, in 1950, food lockers, The disappearance of c e n ­ such as food stores and and fuel, coal and feed re ­ tailers from second order central villages in 1970 was re­ lated to these functions becoming outmoded, been required in 1950 by the rural residents surrounding the second order villages 5.14). For instance, whereas they had in townships (Tables 5.11 and the groceries and food items became available at lower prices in greater variety in super m a r ­ kets or corporate food stores and food lockers were outmoded as new sophisticated refrigeraors and freezers became available in d e pa rt me nt stores and chain stores situated in large towns and cities. Finally, fuel, coal and feed stores were outmoded by 1970, when oil and gas and petroleum dealers had emerged in second order villages (Table 5.12). The reason for these changes may be found in the tech no lo g­ ical advancements and highways and super highway development in southcentral Michigan. The disappearance of general hardware and publi sh in g and printing functions from second order villages in the 1950-1970 period was related to the ope ration of economies of scale for these types of central functions that were then concentrated tral places, the small wh e n increases retail stores in bigger, urban ce n­ in regional accessibility hurt in the villages. explains the second order villages' This reason also declining central 207 TABLE 5.14: Typical Central Functions Available in Second Order V i l l a g e s : 1950 , 1970 and 1980 Central 1950 Functions Grocery store 4.00 Gasoline Service Station (Filling & Service Sta.) 6 .00 2 .00 Hardware Store 2 .00 Eating Place (Restaurant) 2 .00 Drugstore 1 .00 Food Stores and Misc. Automobiles & Tractors 2 .00 Drinking Places (T a v e r n s / B a r s )3 .00 Electric Supply Stores (Sales/ 3 .00 Services) Auto body repair shops & G a r ­ ages (1950) or general a u t o ­ mobile repair shops (1970, 2 .00 1980 ) 1.00 Variety & Gift Shops 1 .00 General Hardware Machine Shops & Supplies (1950); motor vehicle dealers 1.00 (1970, 1980) 3 .00 Confectionery & Misc. 1.00 Grain Elevators & Feed Store 1 .00 Furniture Store 2 .00 Jewelry Store 1 .00 Publishing & Printing Auto Supplies (1950); a u t o ­ mobile equip. & parts and battery, tire and accessory 3.00 dealers (1970,1980) Oil & g a s or petroleum & 1 .00 related 2.00 Men's wear 2 .00 Dry Cleaning & Laundry 2.00 Dairy Product Store Farm Machinery (Equip. & Sup) 1.00 1.00 Food lockers Florist (greenhouse) 1.00 1 .00 Fuel, Coal, Feed, etc. 1.00 Sporting Goods W o m e n 's Wear Shop 2 .00 1 .00 Auto-farm Implement 1 .00 Books and Newspapers 1.00 Fruits 1 .00 Department Store 1.00 Shoe Store 1.00 Tractors Average Number 1970 3.25 1980 2 .71 3 .00 2 .25 .75 1 .50 0 .00 0 .00 1 .50 1 .71 1 .86 1 .29 1 .00 .29 0 .00 .86 .25 0 .00 .50 .50 0.00 .14 .86 0 .00 1 .75 .25 2 .00 .75' .50 0.00 1 .43 .29 .57 .43 .29 0 .00 1 .50 .14 2 .25 0 .00 .50 .25 2 .50 0 .00 .50 0 .00 .50 0.00 0.00 0 .00 0 .00 .25 .50 0.00 1 .01 0 .00 0 .00 0 .00 .57 0 .00 .43 0 .00 .71 0 .00 0 .00 0.00 0 .00 0.00 0.00 0.00 208 TABLE 5.14: Cont. Central Functions______________________ Yarn Lumber and Building Material Dealer Funeral Service General Merchandise Store Radio & TV Store and Repair Shop Women's Ready-to-Wear Store Bowling Alleys Liquor Store Farm & Garden Machinery & Equip. Meat or Meat and Fish Market Fuel and ice dealer Men's & Boys ' Clothing Paper & Paper Products Poultry & Poultry Products House Trailer Dealer (Auto & home S u p p . stores) Boat Dealers Construction Materials Floor Covering Store Sewing Store Upholstry & furniture Repair H o b b y , Toy and Game Shops SOURCE: Tables A . 4, 1950 1 .00 Average Number 1970 0 .00 1980 0 .00 0 .00 0 .00 0 .00 1 .50 .25 .75 1.14 .29 .57 0 .00 0.00 0 .00 0.00 1 .00 .50 .50 .50 1.14 .71 0 .00 .29 0 .00 0.00 0.00 0.00 0 .00 0.00 .75 .50 .50 .50 .50 .50 .57 0 .00 0.00 .43 0.00 .29 0 .00 0.00 0.00 0.00 0 .00 0 .00 0.00 .25 0.00 0 .00 0 .00 0.00 0 .00 0.00 .43 .29 .43 .43 .29 .29 .29 A.5 and A. 6 . 209 functions of auto repair shops, stores, and jewelry stores auto supplies and equipment (Table 5.10). Increasing central functions such as machine shops or motor vehicle dealers, oil and gas and petroleum dealers and farm and garden relat ed machinery rose dramatically in the 1950-1970 period in the central villages studied, light growth in the second period of study ticularly in second order villages but saw (Table 5.7), (Table 5.12). par­ Due to re ­ vo lut ion ary rural de vel op me nt in the study area in the first period of study, agricultural mechanization required new farm equ ipment stores and was associated with an increase of no n-farm populat ion who participated in farm gardening in the study area and second order villages. crease of nonfarm families Indeed, the in­ in rural areas favored the in­ crease of motor vehicl e dealers in second order villages. Therefore, increased farm machinery on the farms and in­ creased private cars bel onging to rural nonfarm families, were influential eum dea lerships in increasing the oil and gas and p e t r o l ­ in second order villages from 1950 to 1970. The decline of these three functions in second order v i l ­ lages from 1970 to 1980 was due to the almost (Table 5.12) stable con dition of their total all the central villages functional units throughout from 1970 to 1980 House trailer dealers, (.Table 5.7). floor covering stores, and hobby shops emerged and de veloped as prosperous central functions in second order villages over the study time (Table 5.12). 210 They resulted from the increase of rural nonfarm po pulation and increased leisure time pursuits among farm and nonfarm families. Second order villag es creational, increased in agricultural, residential and industrial rural residents or rural visitors re ­ functions that serve (recreational v i s i t o r s ) . These villages tended to make av ailable such functions as supermarkets; belts, mills; animal medicine; building and pl um bi ng supplies; some machine parts in auto dealers, modern elevators with new fertilizer services. and About 57 percent of farmers vi sit ed these villages for their elevator, needs. mill, fertilizer, Their industrial and animal feed and medicine (manufacturing) less than the first order villages, functions were much but they still offered some employment opport un it ie s for rural residents. perienced some growth in industries in the 1970s. They e x ­ The housing development that started in the middle of the 1970s involved an increase of rural nonfa rm population in the secon d order villages and their surrounding f a r m - l a n d s c a p e s . Recreational activities including parks and boating in these villages attracted visitors, and were influential pa rti cul arl y during the summer in supporting some retail second order villages. Rural stores in services responsive to the needs of rural residents of second order villages, schools, except emerged or increased in the 1970s in those villages (Table 5.19). Spec ula ti on about the future of second order 211 villages includes growth in residential and man ufa ctu rin g functions and declining or stabilizing retail functions. Public que stionnaires a dministered in this study revealed that knowledgeable local people believe there will be stable economic conditions in second order villages in the future. Functional Change of Third Order Villages Third order central villages declined in numbers during both periods of study (Table 5.1). This continuous decline in the vi ability of third order villages was as sociated with numerous declines in their central those functions which were typical villages functions, pa rt icularly among these third order in 1950, but had disappeared by 1970 (Table 5.11). All of the function in Table 5.11 existed in third order villages in the 1950s but declined and disappeared by 1970, indicating that the impact of rural development has greatly damage d third order villages. The di sa ppearance of general stores and food stores and mis cellaneous shifted the pattern of shopping from these villages to supermarkets and d e p a r t ­ ment stores in larger central places. The need for local depar tme nt stores in third order villages, caused the a p ­ pearance of local depar tment store retailers in these v i l ­ lages by 1980 including shoe (Table 5.15). Other functions and harness repairing and blacksmi thi ng cultural (outmoded by a g r i ­ industrialization in the study a r e a ) ; general hardware and publishing and printing (lost to competi ti on 212 TABLE 5.15: Typical Central Order Villages: F u n c t i o n s A v a i l a b l e in 1 95 0 , 1 9 7 0 a n d 1 9 8 0 Central Functions 1950 Grocery Store 3.00 Gasoline Service Station (Filling & Service Station) 6.10 Hardware Store 1 .60 Eating Places (Restaurant) 1 .70 1.57 Drugstore .71 General Store Food Stores & M i s c . 1.43 Automobiles and Tractors 2 .42 Drinking Places (Taverns & Bars ) 1.29 Implements (Agricultural) 1.14 Electric Supply Stores (Sales and S e r v i c e s ) .57 Auto body Repair Shops & Garages (1950) or general Automobile repair shops (1970, 1980) 1.57 Variety and Gift Shops 1.57 Funeral Service .86 .57 General Hardware Plumbing & Heating 1 .43 Machine Shops & Supplies (1950) motor vehicle deale rs (1970, 1980 ) .29 Confectionery & Misc. 1 .00 Grain elevator & feed store 1.58 Furniture Store .86 Jewelry Store 1.14 Publishing & Printing .86 Auto Supplies (1950); auto­ mobile equip, parts & battery, tire and accessory dealers (1970, 1980) .57 Shoe and harness repair .57 Oil and Gas or petroleum and related .43 Radio (Sales, Services) .57 Men 1s wear . 71 Lunchrooms .43 Meat or Meat and fish market .86 Welding and repair .71 Dry cleaning and laundry .57 Dairy production .29 Farm machinery (equip, dealers or s u p p l i e s ) .29 Food Lockers .29 Florists (greenhouse) .29 Third Average Number 1980 1970 2 .80 1 .75 3.20 1.20 1 .40 1.00 0 .00 0.00 0 .00 .75 1 .50 1 .00 .50 0.00 0 .00 0 .00 1.20 0.00 .50 0 .00 0 .00 0 .00 .40 .40 .80 0 .00 0.00 .25 .50 .50 0.00 0 .00 1 .00 0.00 .80 .20 .40 0 .00 1 .75 0.00 1.00 .50 .25 0.00 0 .00 0 .00 .75 0 .00 .40 0.0 0 0 .00 0 .00 0.00 .20 0.00 .60 .75 0 .00 0 .00 0 .00 0 .00 0.00 .25 0.00 .60 0.00 .20 1 .50 0 .00 .50 213 TABLE 5.15: Cont Central Functions_____ Paint, glass and wallpaper Fuel, coal, feed, etc. Sporting Goods Bakery & M i s c . Misc. General Store Women's wear shop Blacksmith Trucking Bowling Alleys Family Clothing Store Violins (Music Store) Shoe Store Lumber & bu ilding material Dealer Motor vehicle dealer Radio & TV Store General Auto repair shops Women's Ready-to-Wear Stores Radio & TV Repair Shops House trailer d e al ers (auto & home s u p p . store) Boat dealers Men's & boys' clothing Farm and Garden ma chinery and equip Liquor Store Construction materials Engineering Service Department Store SOURCE: Tables A . 4, A.5, and 1950 .29 .71 .43 .71 0 .00 .29 .43 .43 .43 .29 .29 .14 Average Number 1970 0.00 0.00 .60 .60 1.20 0.00 0 .00 0.00 .20 0 .00 0.00 .40 1980 0 .00 0.00 .50 0 .00 .50 0.00 0 .00 0.00 .25 .50 .50 0 .00 0 .00 0.00 0.00 0.00 0.00 0.00 .60 1 .00 1.20 .40 .80 .60 1.25 1 .75 .75 0.00 .50 .50 0 .00 0.00 0.00 .40 .40 .20 .75 .25 .25 0.00 0.00 0.00 0 .00 0 .00 0.00 0.00 0.0 0 0.00 0.00 .75 1 .00 .50 .50 .25 A. 6. 214 with large urban central places due to regional d ev el op ­ ment) ; and radio shops, men's wear, and women's wear shops (lost in modifications to other types of functions because of technological change and new l i f e s t y l e s ) , disappeared from third order villages over the first period of the study. The general decl ine of some of the central tions in central villages over the study periods included the third order villages central functions, auto repair shops, hardware stores (1950-1970), supplies and repair shops, and welding repair shops 5.10 and 5.15). funeral (Table 5.8) in the case of several such as grocery stores, vators and feed stores func­ gasoline service, (1950-1970), grain e l e ­ drugstores, electrical service, jewelry store, in both periods of study (Tables The explanation for these declining fu n c ­ tions in third order villages relates to the consolidation of these small retail functions more efficient functions southcentral Michigan. into fewer but larger and in larger towns and cities in It should be noted that tr ans por ta­ tion development was the important factor in consolidating these functions. Increases tral functions in the number of establishments of some c en ­ in the central villages studied (Table 5.7) included only a few functions that increased in third order villages, such as machine shops or motor vehicle dealers and farm equipment and fa rm-and-garden ma chinery dealers periods of study (Table 5.12). Other functions, in both including 215 oil and gas and petroleum dealers, TV stores and repair shops, dealers (1970-1980) third order villages sporting goods, (1970-1980) and house trailer remained stable typical (Table 5.12). Third order villages, agricultural, industrial residential, less still support in their villages. as small trading centers, and recreational offer functions. the industrial important, Agricultural Compared with first and second order function of third order villages newer and smaller in third order villages. makes available important farm needs including grain elevators with their related services as feed for farm animals and fertilizers supplies, grain driers. for crops, Milling companies, such and milkers and silo services and canning co mpanies are vital farm-oriented services for farmers. questionnaires, A c c or di ng to the public about 54 percent of farmers lands visit these facilities Housing development in the h i n t e r ­ in third order villages, rest of the farmers bypass these villages ters. is functions as important attracti ons of third order central villages, electrical The function is most recent and has been developed since the early 1970s. villages, in implied their utility for farmers and rural residents who functions offered functions The r e t en ti on of these typical functions in third order villages such central radio- for the larger c e n ­ in the third order villages has begun since the early 1970s and was due to increased n o n ­ farm population who commute between their homes and their 216 jobs. Less expen siv e housing in these villages has attracted low income young couples or the elderly. creational villages functions have emerged in some of the third order such as Lake Odessa and Grass Lake due to their natural endowments. Generally, few employment opportunities, third order villages offer and some have lost several businesses over the study periods. centers' Re­ Competit ion with larger retail businesses has been very harmful for third order villages, be cau se local retailers cannot afford volume buyi ng and greater variety, so lesser quantity and quality at higher prices characterizes local goods, with consequent failure to compete successfully wi t h retailers in larger central places. Social and public rural services, except schools, emerged and increased in third order villages have (Table 5.19). It may be noted that most of the social and public rural services at the local level in third order villages are surviving and increasing, while businesses at this level are de c l in in g and in danger of disappearing, comp eti ng spatial a region. villages Thus, local due to interactions between the central places of future economic development in third order is unlikely. Functional Changes of Fourth Order Villages The dev el op me nt of fourth order villages has not been stable over the periods of the study (Table 5.1), 217 par ti cularly their significant decline in retail whole sa le es tablishments in both periods has de creased their economic viability. and (Table 5.9) that Numerous central functions shown in Table 5.11 have disappeared from fourth order villages due to technological change and regional de­ velopment, as discussed earlier for third order villages. While central functions stores, (Table 5.6) gasoline service stations, stores and furniture auto repair shops, (Tables 5.10 and 5.16), (except auto repair shops) as a typical central almost retained their status function in fourth order villages and co ntinued to support, of these villages. drug­ stores declined in fourth order v i l ­ lages over the study periods all of them such as grocery to some extent, As the economic viability in the third order villages, hardware stores de cl in ed in the first period in fourth order villages but saw growth in the second period fore, hardware stores as typical (Table 5.10). functions There­ in fourth and third order villages have been retained and some have even grown. Grain elevators and feed stores declined also but remained a typical study periods (Table 5.10). cluding electrical heating, function and stabilized over the combined Other declining functions, supplies and repair shops, confectionery, plumbing and auto supplies and equipment, cleaning and dairy product stores were typical in­ dry functions of fourth order villages in 1950, but had lost their typical positions in those villages by 1970, and had almost 218 TABLE 5.16: Typical Central Order Villages: F u n c t i o n s A v a i l a b l e in 1950, 1970 and 1980 Central Functions 1950 Grocery store 3 .40 Gasoline Service Station 5.3 (Filling & Service Station) 1 .50 Hardware Store 1 .70 Eating Place (Restaurant) 1 .34 Drugstore 1.17 General Store 1.17 Food Stores & Misc . Automobiles & tractors 1.50 Drinking Places (Taverns & Bars ) .50 Implements (agricultural) .83 Electric supply stores (Sales 1.17 and S e r v i c e s ) 1.17 Variety & Gift shops Auto body repair shops & garages (1950) or general automobile repair shops (1970 1980 ) 1.17 .67 Funeral services General Hardware .83 1.17 Plumbing and Heating Machine shops & Supplies (1950); motor vehicle dealers (1970, 1980) 1 .00 .67 Confectionery & Misc. Grain elevator and feed store 1.01 Furniture Store .34 Publishing & Printing .67 Auto supplies (1950); a u t o ­ mobile equip. & parts & battery, tire & accessary dealers (1970, 1980 ) .34 .67 Shoe and harness repair Oil & Gas or petroleum and related .50 Radio (Sales and Service) .67 Men 1s Wear .34 Lunchrooms .67 Dry cleaning and laundry .34 Dairy product store .50 Farm machinery (equip, dealers or s u p p l i e s ) .34 Food lockers .50 .67 Florist (greenhouse) Sporting Goods .34 Fourth Average Number 1970 1980 2 .43 1 .67 3 .43 1.29 1.14 1.00 0 .00 0.00 0.00 .67 1 .33 .83 .50 0 .00 0 .00 0 .00 .86 0 .00 .83 0 .00 .14 1.00 0 .00 .67 .43 1.00 0.00 0 .00 .17 0 .00 0 .00 0 .00 1.28 0 .00 1 .15 .86 0.00 .34 0 .00 .83 .50 0 .00 .14 0 .00 .17 0 .00 .42 0 .00 0 .00 0 .00 .29 .29 .34 0 .00 0 .00 0 .00 0 .00 0 .00 1.43 0 .00 .57 .43 .50 0 .00 .33 .17 / 219 TABLE 5.16: Cont Central Functions______________________ Flour milling Vegetables House furnishings Lumber & Building materials dealer Radio & TV Store Women's Ready-to-Wear Shop Bowling Alleys Lumber and construction materials Department store Farm & Garden machinery & equip. Retail nurseries House trailer dealer (auto & home supp. store) Family clothing store Jewelry Mobile home dealer Boat dealers SOURCE: Tables 1950 Average Number 1970 1980. .34 .34 .34 0.00 0.00 0 .00 0 .00 0.00 0.00 0 .00 0 .00 0 .00 0 .00 1 .29 .29 .29 .29 .67 .17 .17 .17 0 .00 .17 .29 .29 .17 0 .00 0 .00 0 .00 .29 .17 .83 .33 0 .00 0.00 0 .00 0.00 0 .00 .14 0 .00 .14 0 .00 0 .00 .17 .33 .17 .33 .17 A . 4, A.5 and A.6 2 2 0 disappeared from the scene in fourth order villages by 1980 (Table 5.10). These central functions were in 1950, but due to regional development, locally oriented they were c o n s o l i ­ dated into fewer and more specialized units in larger c e n ­ tral places by 1970 and 1980. Among the increasing functions of central villages (Table 5.7) machine shops or motor vehicle dealers and farm equipment and farm and garden machinery, and sporting goods dealers increased in fourth order villages during the first period of the study the study, lages, (Table 5.12). these functions declined in fourth order v i l ­ but remained typical except for sporting goods. garden machinery, dealers In the second per io d of functions in those villages, Farm equipment and farm-and- which were more typical than motor vehicle in fourth order villages in 1980 (Table 5.12) apparently had greater viability for survival village. It is expected that sporting goods will disappear in the future from this decline to a non-typical Meanwhile, in this size level of village because of its function in 1980 (Table 5.12). some other nontypical functions, such as family clo thing store and women's ready-to-wear shops first a p ­ peared in fourth order villages in 1970. family clothing stores became a typical the other functions remained non-typical Among these, function in 1980 and (Table 5.12). It should be noted that even though family clothing stores b e ­ came a typical function in fourth order villages in 1980, 221 they are likely to be a local function only temporarily, be­ cause the shopping travel maps of farm and non farm families (Chapter Six) for this fun ction show high average travel mileage toward big central places. Therefore, this func ­ tion is unl ikely to survive at this level of villages. Due to great importance of rural housing development in fourth order villages since household trailer dealers mobile home dealers villages. non-typical 1969, some functions such as (non ty pi c a l : 1970 and 1980) (typical in 1980) and emerged in these small The continuous existence of boat dealers as a recreational over 1950-1980 function in fourth order villages (Table 5.12) implied that the recreational activities fu nc ti on in these villages was not typically viable. Fourth order villages, agricultural, functions. residential and, The few small functions per village) 1970s. Local as small trading centers, to some extent, industries retain recreational (three manufacuring stabilized or declined over the elevators are dying, because only 50 percent of farmers use the local elevators and related services in fourth order villages. their own trucks, cities The rest of the farmers, patronize (such as Charlotte). farm equipment, larger elevators However, using in higher order elevators, feed mills, and farm and garden machinery dealers, ha r d ­ ware stores and eating places remain functions of fourth order villages for farm families. Rural public services 222 have been added in the case of churches, dentists and veterinarians. attorneys have declined banks, But schools, (Table 5.19). doctors, barber shops, and The decline of schools is related to school consolidation, but the decline of barber shops has been due to their economic failure. decline of attorneys is likely to be only temporary and will increase again, because it appeared as a typical fifth order villages in 1980. functions function in The future of fourth order villages will not be prosperous, in their central The due to significant declines (establishments) resulting from rural development that enhanced the mo bility of rural people and increased the spatial com petition betwe en the central places in the study area. Functional Changes in Fifth Order Villages Fifth order villages were unstable ment. For example, in their de ve lo p­ they grew slightly in number from 1950 to 1970 and then declined precipit ous ly from 1970 to 1980 (Table 5.1). The reduction in fifth order villages last period was related to a large shift of several order villages dow nward to sixth order villages in the fifth (Table 5.3). The average number of establishments dec lined dramatically in fifth order villages increased somewhat 5.5). in 1950-1970 (13.33 percent) (-51.72 percent) in 1970-1980. and (Table This revealed that fifth order villages dramatically de clined in their central functions in the first period of 223 the study, when rural development was oc curring swiftly in southcentral Michigan. An increase in average number of e s ­ tablishments in fifth order villages from 1970 to 1980, up­ graded this average value from 11.25 to 12.75 but this was still too low for cl as sification of a central place as a viable village. For example, the average number of e s t a b ­ lishments required is close to 9.9 for minimum, trade centers according to Hodge's Saskatchewan. Therefore, (1965) con venience empirical study of the viability of fifth order v i l ­ lages of the study area is questionable in spite of some gains in the 1970-1980 period. The functions appeared from fifth order villages general stores, and printing, lockers, stores, food stores, general hardware, (Table 5.11), weldi ng and repair, well dr illing in 1950-1970 shoes and harness repair, b l a ck s mit hi ng (Table 5.17). classes of central villages, that d i s ­ included p ub li sh in g radio shops, electrical food supply dairy products and poult ry and As explained earlier for other technological regional development brought changes ad va ncements and in the lifestyles of rural residents, w hic h were responsible for this decli ne in the viab il it y of fifth order villages. Among the de clining functions stores, gasoline service stations, (Table 5.10), hardware stores, grain elevator and feed stores had been typical order village functions, vices were typical grocery and in fifth while drugstores and funeral in 1950 and 1970, and then became ser­ 224 TABLE 5.17: Central Functions Typical Central Order Villages: F u n c t i o n s A v a i l a b l e in 195 0, 1970, and 1980 1950 Grocery Store 4 .20 Gasoline Service Station (Filling and Service Sta.) 3 .10 Hardware stores .80 Eating Places (Restaurant) .64 Drugstores .91 General Stores 1 .18 Food Stores & Misc. .82 Automobiles .55 Drinking Place (Taverns & Bars) .36 Implements (Agricultural) .64 Electric Supply Stores (Sales & Service) .73 Autobody repair shops & g a r ­ ages (1950) or general a u t o ­ mobile repair shops (19701980 ) .73 .64 Funeral Services General Hardware .64 Plumbing & Heating .36 Machine Shops & Supplies (1950 ) motor vehicles (1970, 1980) .55 Grain elevator and feed store .81 Furniture store .36 .27 Jewelry store Auto supplies (1950); a u t o ­ mobile equip. & parts and battery, tire and accessory dealers (1970, 1980) .36 .27 Shoe and harness repair Oil and gas or pe troleum and related .36 Radio (Sales & Service) .27 Lunchrooms .36 .27 Welding and Repair Women's & Children's dry .27 goods Farm machinery (equip, dealers or supplies ) .09 Dairy products and poultry .27 .27 Well drilling Lumber & building material dealer 0 .00 House trailer dea le r (Auto & home s u p p . store) 0 .00 Fifth Average Number 1970 1980 1.33 1 .75 1 .42 1.08 .33 .42 0 .00 0.00 0 .00 .75 0.00 .75 .62 .87 .20 0 .00 0 .00 0 .00 .62 0 .00 0 .00 0 .00 .08 .33 0.00 .08 0 .00 .12 0 .00 0 .00 0 .00 .66 .25 0 .00 .62 .50 .12 0 .00 .16 0 .00 .12 0 .00 .33 0 .00 0.00 0 .00 .25 0 .00 0 .00 0 .00 0 .00 0 .00 .25 0 .00 0 .00 .25 0 .00 0 .00 .92 .37 .08 .25 225 TABLE 5.17: Cont Central Functions 1950 Farm and garden ma chinery and equip. Florists Sewing Store Misc. home fu rnishing store Mobile home dealers 0 .00 0 .00 0 .00 0 .00 0 .00 SOURCE: Tables A.^, A.5* and A.6. Average Number 1970 0 .00 0 .00 0 .00 0 .00 0 .00 1980 .62 .50 .37 .37 .25 226 atypical functions for fifth order villages in 1980. F u rn i­ ture stores and auto supplies and equi pm en t were typical only in 1950 in these villages thereafter. 5.12) (Table 5.10) and atypical Among the increasing central functions (Table only motor vehicle dealers and farm equipment and farm-and-garden machinery dealers were typical central tions of fifth order villages in 1980, these two functions were still viable which meant that in those villages. The importance of the increasing d o r mi to ry function func­ (residential) in fifth order villages cau se d the emergence of re­ lated central functions such as house trailer dealers and mobile home dealers (1980) of sewing stores as a typical (Table 5.12). function (1970) The emergence in fifth order v i l ­ lages in 1980, may have been related to the increased p o p ­ ularity of home tailoring among rural housewives to sup pl e­ ment the family's budget. Fifth order villages as small tradi ng centers are both agricultural and residential villages. and related services are still hinterlands. The local elevators important for farmers of the About 48 percent of local farmers visit fifth order villages for their elevator and related services, while the rest of them bypass these villages for larger ele ­ vators in other central places. markets, ments' feed grinding, dealers, Milling, grain storage, and farm related ma chinery and imple­ and hardware stores are the vital and tant functions to farmers who visit these villages. impor­ The 227 residential functions of the villages housing development for new residents Minimal industry per village) Schools, increased with new since the early 1970s. (an average of three industrial existed, churches, functions but was not developed further. banks and doctors were typical in these small communities up to 1970, and dentists, neys and veterinarians were added to them by 1980 5.19). functions at to r­ (Table These represent the increased demands of rural non ­ farm families who increased the populations of these v i l ­ lages and their hinterlands. The future viability of fifth order villages is un likely because of competing spatial in­ teraction with urban and larger central places that are more attractive and practical for farm and nonfarm families of these villages and their surrounding hinterlands. Functional Changes of~ Sixth Order Villages Sixth order villages, the hierarchical as the lowest order villages structure of the central villages in studied, have demonstrated instability in the changes to their numbers over the study periods (Table 5.1). loss of central function establishments both periods of study Indeed, (average values) (-53.9 percent in 1950-1970, -41.27 percent in 1970-1980) their in and represented the greatest amount function loss among the various classes of central villages (Table 5.5). ments The average number of functional es ta bl is h­ in sixth order villages was 15.4 in 1950, 7.1 in 1970 228 and 4.17 in 1980 (Table 5.5). ber of establishments 4.17 in 1980, The decline in average n u m ­ (stores) put them at the lowest ordered class to Ho dge's work in sixth order villages to "hamlet" level that is the in a central place system. (1965) According on trade centers of Saskatchewan, average number of establishments was 3.3 per hamlet, hamlets were categorized with five es tablishments mercial or cultural purposes), order villages, whose central clined, 1980, Therefore, and (for c o m ­ in the work of Brush on the central places of Wisconsin. the (1953) these sixth functions signif ic an tl y d e ­ lost their village positions in the period of 1970- and were downgraded to hamlet level in 1980. The sixth order villages, villages studied, functions like the other classes of were faced with de clining and va nishing in the period from 1950-1970 disapp ea ra nc e of those types of central (Table 5.11). The functions have alrea dy been discussed as the results of technological change in agriculture and transportation in the study area. Among the vanished functions of sixth order villages were general stores, were typical food stores, in 1950 and general hardwa re stores (Table 5.11). These functions d i s ­ appeared due to their outmoded status and com peting in ter ­ actions among the central places of the study area. In the category of declining functions, gasoline service stations, vators grocery stores, auto repair shops, and feed stores and drugstores de clined grain e l e ­ in both 229 periods of the study (Table 5.10). Grocery stores, gasoline stations and grain elevators and feed stores became nontypical or atypical functions in 1980, while the decline of auto repair shops and drugstores from 1950 to 1970, their atypical 1980 status in 1970, (Table 5.10). that remained non-typical confectionery, furniture stores, we ld in g and repair that were non-typical in 1950 later decades. (Table 5.8) (Table 5.10) di sa ppeared completely in the Hardware stores were a de clining function in 1950-1970 were thus co ns is te nt ly in sixth order villages, (1950, in sixth order villages. functions, m ac hin ery places and in sixth order crease d in the second period*(Table 5.10). ing) in Some other de clining functions such as p lu mbing and heating, villages caused 1970, 1980) but in­ Hardware stores a typical In the case of growing function (increas­ only farm equipment and farm and garden (Table 5.12) (Table 5.18) and lumber dealers and drinking maintained typical status in sixth order villages. Among the rural were typical other central schools were churches, services, schools, in sixth order villages villages churches and banks (Table 5.19) (except first order villages) lost due to school consolidation. lumber companies, (drinking places) hardware stores, as in local Banks, refreshments and restaurants remained attractions of sixth order villages. of grain elevators but, Due to the decline and disappearance and feed stores in sixth order villages, 230 TABLE 5.18: Central Functions Typical Central Order Villages: Functions Available 1950, 1970 and 1980 1950 Data is deriv ed from Tables Sixth Average Number 1970 Grocery Store 1 .75 Gasoline Service Station 2 .70 (Filling and Service Sta.) Hardware Store 1.00 Auto body Repair Shops & garages (1950) or general automobile repair shops 1 .15 (1970, 1980) General Store .65 Eating Places (Restaurant) .65 Drinking Place (Taverns & .60 Bars) .40 Funeral Service .40 Drugstores Grain Elevator and Feed Stores .85 General hardware .35 Implements (Agricultural) .35 Electric Supply Stores (Sales & Services) .30 Farm machinery (equipment dealers or s u p p .) 0 .00 Lumber and Building material dealers 0 .00 Farm and Garden machinery and Equipment 0 .00 SOURCE: in A. 4, 1980 1.20 .22 1 .13 .47 .28 .67 .27 0 .00 .20 .17 0 .00 .11 .60 .80 .20 .40 0 .00 0 .00 .44 .11 0.00 .17 0 .00 0 .00 0 .00 0.00 .73 .28 .33 .39 .07 .22 A . 5 and A. 6 231 TABLE 5.19: Typical Rural Services Available V i l l a g e s in 1 9 7 0 a n d 1 9 8 0 Average in Central Typical Rural Services First Order Villages: School Church Bank Doctor Barbershop Dentist Attorney Veterinarian Optometrist Clinic Hospital 1970 Number 1980 3.33 3.67 1.00 3 .00 .67 1.67 2.33 .33 .33 .33 0.00 4.00 10.67 2.67 9.67 1.67 3 .33 3.67 1.67 .67 1.33 .33 Second Order Villages: School Church Bank Doctor Barbersho p Dentist Attorney Veterinarian Optometrist Clinic 2 .50 3.25 1 .00 .75 1 .00 1.25 0 .00 1 .00 0 .00 0.00 2.14 6.71 1.43 1 .86 1 .14 1.57 1.28 1.86 .29 .29 Third Order Villages: School Church Bank Doctor Barbershop Dentist Attorney Veterinarian Optometrist 3 .40 4 .00 1 .20 1 .40 1.60 1 .20 .60 .20 0 .00 2.25 6.75 1.25 2.25 2 .25 1.25 .75 1.00 .75 Fourth Order Villages: School Church Bank Doctors Barbershop Dentist Attorney Veterinarian 3 .00 3 .00 1 .00 .71 .57 .57 .43 .29 1.50 4.50 1.17 1.17 .50 .67 .17 .50 232 TABLE 5.19: Cont Typical Rural Services 1970 Average Number 1980 Fifth Order Villages: School Church Bank Doctor Dentist Attorney Veterinarian 2 .00 1 .00 .83 .33 0.0 0 0 .00 0 .00 1 .63 3 .75 .88 .38 .38 .75 .38 Sixth Order Villages: School Church Bank 1 .00 .80 .40 .61 1 .78 .56 SOURCE: Tables A . 7 and A . 8 233 the farmers of the hinterlands visit grain elevators larger central villages urban centers (such in (such as Fowler and Webberville) as Durand and St. Johns). or Therefore, these tiny villages are almost always bypassed by farmers in favor of facilities in larger central places. lages, important trading centers among the as the least central villages of southcentral Michigan, cultural if any, trial These v i l ­ are small a g r i ­ and residential communities that have very little, manufa ct ur in g activities function per v i l l a g e ) . (as an average: one i nd us ­ These villages have had housin g development since the early 1980s. The populations of these villages have grown very slightly or even declined, but the rural popula ti on in townships surrounding the sixth order villages increased in both periods of study 3.12). Therefore, h ou si ng development was a consequence of populat io n increase, ex plained earlier, places (Figure due to new rural nonfarm residents. As sixth order villages became small central that could only be categorized as hamlets nonviable for future economic development. that are They are likely to co ntinue to support only their do rmitory and community functions. Spatial Di st ribution of Different Classes of Central Villages in a Process of Change Spatial Modeling Christaller and Losch created a hexagonal pattern of mark et in g among the central places of a region and a 234 pred ict ab le rigid p a tt ern of the range of goods and services as a com ponent of central place theory. However, later co n­ tributions relaxed this deterministic concept of original central place theory. The technique of nearest neighbor analysis wh ich can be used to measure the coefficient of d is pe rs io n among the dot patterns (settlements) of a region, is an alternat ive method for determining the range of c e n ­ tral places of a study area. Using nearest neighbor analysis to test a given dot pa tte rn will provide an R value that is called a nearest ne ighbor index. clustered; R=2.149, Silk, When R=0, wh en R=l, the pattern 1979:108). the pattern of dots the pattern is random, is dispersed (Taylor, is closely and when 1977:157; and Repeate d calculations of the R index over time can thus be helpful for comparing the change in the settl eme nt (dot patterns) v ari ati ons of the R index in a certain study area over a per iod of time, of a study area. can provide a measure of the tendency of settlem en t patterns toward clustering, persing. The Z test of R significance level, (shown as ZR) d is pe rs i ng process (functional at an assumed random process, (nearest neighbor analysis in Taylor, Changes randomizing or d i s ­ can determine whethe r dot patterns are ge ne ra te d from a cluste ri ng process, in detail For instance, 1977 and Silk, or is discussed 1979). in the functional vi ability of central villages index values) of the study area over the periods 235 of 1950-1970 and 1970-1980 caused changes distribution in the region (Figures 4.1, in their spatial 4.2 and 4.3). In order to standardize and compare the dot patterns of each class of central villages in 1950, 1970 and 1980, the te c h ­ nique of nearest neighbor analysis was applied in this re ­ search. Thus, it was possible to measure changes in co ­ efficients of dispersion between diff er ent classes of c e n ­ tral villages at the three points 1980). in time (1950, 1970 and Because the scaled boundary of the study area at the three points in time in this research remained the same, limitations of boundary changes in rel ationship to dot p a t ­ tern distribution in a study area were not a concern. Change in the viabilty of central villages thus changed their spatial dis tribution in regard to their class h i e r ­ archy, area but not their geographical (Figures 4.1, situation in the study 4.2 and 4.3) Using nearest neighbor analysis, the following h y p o ­ theses were tested in this research. H : H^: The pattern of points in a certain class order (for example, sixth order villages)_is random The pattern of points in a certai n class order (for example, sixth order villages) is clustered or The pattern of points in a certai n class order (for example, sixth order villages) is dispersed. It was assumed that alpha would equal test and, therefore, Z-critical was .05 on a two-tailed Z- * 1.96. consequently, 236 the calcuted ZR values ranging w i t h i n ± 1.96 or Z-critical were the parameters random for det er min in g that a dot pattern was (acceptance of b e y o n d +1.96 , the null hypothesis). ZR values implied rejection of the null hypothesis and acceptance of H or the alternative hypothesis. ZR values 1 beyond -1.96 thus indicated a clust ere d dot pottern and those beyond +1.96 indicated a disp er se d patte rn of central villages. The application of the nearest ne ighbor test in the central villages of the study area has produced R index values with their related significance of Z R ) . levels (significance It was applied to de termine the dot patterns of central villages of different classes at three points of the study time (Table 5.20). The first and second order v i l ­ lages were no nc omputable in 1950, there was only one central village 5.20). However, due to the fact that in those classes (Table the first order villages showed a random pattern in 1970 and 1980. The R index was .52 in both 1970 and 1980 and the random patte rn tended toward clustering. The variation of the R index from 1 to zero showed the random pattern with a tendency toward aggregating or clustering (See Taylor, 1977:157). first order central villages 5 ) was related to their The closeness of in 1970 and 1980 (Figure location in a highly in­ dustrialized region with access to super highways c o n ­ nected to Detroit. persed pattern The second order villages had a d i s ­ in 1970 and 1980 (Table 5.20 and Figure 5) TABLE 5. 2 0: Spatial Distribution of N R First Order Villages 1950 1970 1980 1 3 3 NC** .52 .52 Second Order Villages 1950 1970 1980 1 4 7 NC 2.09 1.83 Third Order Villages 1950 1970 1980 7 5 4 1 .171 1 .167 1 .52 Fourth Order Villages 1950 1970 1980 6 7 6 Fifth Order Villages 1950 1970 1980 Sixth Order Villages 1950 1970 1980 ZR Villages: 1950, Signifi­ cance of ZR 1970 and 1980* Z-Critical P=.05 including .025 on each tail Dot Pattern NC -1.59 -1.59 NC .0559 .0559 NC -1 .96 -1.96 NC Random Random NC 4.15 4 .20 NC .00003 .00003 NC + 1 .96 + 1 .96 NC Dispersed Dispersed .88 .72 2 .00 .1894 .2358 .0228 + 1.96 +1 .96 + 1 .96 Random Random Dispersed 1 .48 1.28 1 .30 2 .24 1.43 1.43 .0125 .0764 .0764 +1 .96 +1 .96 + 1 .96 Dispersed Random Random 11 12 8 .90 .80 1 .38 - .65 -1.38 2.31 .2578 .0838 .0104 -1 .96 -1.96 +1 .96 Random Random Dispersed 20 15 18 1 .00 .96 .90 .04 - .33 - .81 .4840 .3707 .2090 + 1.96 -1 .96 -1 .96 Random Random Random *The technique of nearest neighbor analysis has been applied using the data from Figure 2.3, 4.1, 4.2 and 4.3. The approximate area of the study area is M=4919.6 sq . miles (from Figure 2.3). **Noncomputable in nearest neighbor analysis because there is only one central village in that hierarchical class of central villages in the study area. 237 Villages in Order and T i m e : Central 238 S p a tia l D is tr ib u tio n of C e n tr a l V illag es in 1 9 5 0 , 1 97 0 , 1 9 8 0 1950 1970 1980 NC Random Random NC Dispersed Dispersed Random Random Dispersed Dispersed Random Random First Order Villages S econ d Order Villages Third Order Villages Fourth Order Villages Random I Random D ispersed Fifth Order Villages Random Sixth Order Villages Approved (1963) or established (1969, 1978) super highway Proposed (1963) or construction ahead (1969, 1978) Figure 5.2 T he g en e ra l pattern of central village in the study area and th e ir relative location against the sup er highw ay network. T h e data is collected from Figure 3.10 and T able 4.10. 239 at a highly sig nif ic ant level of .00003. The decrease in the R index of second order villages from 1970 to 1980 (Table 5.20) shows the greater tendency of the pattern toward randomness. This was related to the increased num ­ ber of second order vi llages (Table 5.20). in the second period of study The third order villages had random pattern in 1950 and 1970, but a dis pe rs ed pattern in 1980. observed sign if ic an ce to critical P=.025. The level was .0228 which was very close Therefore, this di spersed pattern r e ­ tained some tendencies toward the randomness. Fourth order villages had a d i s pe rs ed patte rn in 1950 at a significance level of 1980. .0125, and then showed a random pattern in 1970 and In fact, the important change in the pattern of their spatial d i s t r i b u t i o n happene d from 1950 to 1970 when their dispersed p a tt er n c h an ge d to random. The fifth order v i l ­ lages, with a random pattern in 1950 and 1970, dispersed p a tt er n in 1980 level was 1980. .0104 w h i c h (Table 5.20). changed to a The significance indicated their dispersed pattern in The great r e d uc ti on in the number of fifth order v i l ­ lages from 1970 to 1980 accompa ni ed a change in their p a t ­ tern from random to dispersed. Therefore, the change in the via bility of the fifth order villages was accompanied by a change in the p a tt er n of their spatial distribution. The sixth order villages m ai nt ai ne d a random pattern in their spatial di st ri b u t i o n throughout the study time The gradual decline (Table 5.20). in R indexes of sixth order villages 240 over the three points of time implied a tendency of the p a t ­ tern to alter from random toward clustering over time. great concent ra tio n of sixth order villages The in the northwest portion of the study area was encouraged by the greater agricultural orientat io n of that portion than the south, over the three points of the study time (Figure 5 ) . This encouraged the agglomoration of these least viable villages in that area. As a conclusion, analysis were the results of the nearest neighbor identical for patterns of central villages studied at the three points in the study time in that the pr edicted dispersed pattern implied in central place theory was not always associated with the patterns of central village s studied over time. Generally, there were 25 percent of villages with dispersed pattern in 1950, percent in 1970 and 50 percent in 1980 (Figure 5 ) . meant that the different classes of central villages are not always evenly distributed. tive location and their class order, Changes This studied in their re l a ­ due to rural and re ­ gional development in the study area over time, were ential 16.7 in changing their settlement patterns. influ­ The wide ex ­ istence of random patterning among 83.3 percent of the v i l ­ lages in 1970, may have been caused by the revolutionary period in the region's rural development from 1950 to 1970. 241 Regional Development and Spatial Components The development of local village networks and their connection to regional highways and super highways central Michigan, upg rade d the mob ili ty of rural residents over the past three decades. families interviewed, center were in south- Among the farm and nonfarm average week ly visits to a market increased at the time the study was done c o m ­ pared with the past. It was apparent that the mob ility of these rural increased families was associated with an increase in regional acc essibility due to super highwa y d e ­ velo pme nt in the study region. Agricultural industrialization in association with technological advancement s and significant super highway development and consequent change southcentral Michigan were in population patterns influential in in the di sa ppearance of some rural central functions, others, the increase or emergence of other and, finally, the decline of some of the functions in the central village studied over the study periods. The consequences of the change tions have been changes in the villages' in central fun c­ via bility and created particular spatial distributions for each class of central villages at dif ferent points in time (Figure 5 The growth and spatial distr ibu tio n of central villages the southern part of the study area intersection of 1-69 and 1-96: ). in (situated south of the Figure 5 ), created an urban indusry-oriented districct dominated by the auto industries 242 of Detroit, that varie d from others. noted that the Illinois-Indiana industrial middle west, Hart (1972:278) has line divides the urban/ with the eastern part dominated by Detroit and a ut o- ma nuf ac tu rin g and the western part d o m i n ­ ated by ag ric ul tu ra l ly -o r ie nt ed part of the study area, industries. The southern particularly the southeast, was do mi nat ed by auto industries and related manufacturing. southern districts of the study area of this research uated south of the 1-69 and 1-96 intersection) mediate contact (Figure 3.10) uational (using 1-96 and/or 1-94) The (sit­ was an im­ with Detroit and its related auto industries. These sit ­ factors encouraged the development of light indus­ try in the central villages situated in that part of the study area. First order and second order villages have increased in this sou thern part of the study area over the study period. First order villages were always part of the area (1950, located in the southern 1970 and 1980). Second order villages were not seen in southern part of the area in 1950, but there was one second order villaqe there in 1970, four in 1980 ( Figure 5 ) . fa cturing functions the study time, and Regarding the growth of ma n u ­ in first and second order villages over it should be noted that the relative locations of these villages have been important in their spatial distribution. Third, fourth, in their numbers fifth and sixth order villages declined south of the 1-69 and 1-96 intersection 243 over the study time order villages (Figure 5 ) . in this and two in 1980. There were four third southern part in 1950, Among fourth order villages, three of them in the southern area in 1950, 1970, and two of them in 1980. there were three of them in Four of the fifth order v i l ­ lages were in the southern part in 1950, three in 1980. three in 1970 four in 1970 and Four sixth order villages were in the s ou th ­ ern part in 1950, but declined to two in 1970 and 1980 (Figure 5 ) . fourth, These observations show that the third, fifth and sixth order villages were not as likely to be retained as the first and second order villages development in the southern part, in their south of the 1-69 and 1-96 intersection. The northern part of this study area was more a g r i ­ culturally-oriented and more favorable for the lower order central villages over the study time. that in the future, It may be speculated viable villages will continue to develop in the southern part of study area, and non-viable ones will be likely to belong to the no rthern part of the study area. As a final point, it should be noted that because this research is also c o n ce rn ed wi t h the impact of the shopping behavior of farm and nonfarm families in changing the v i a ­ bility and spatial di st ri b u t i o n of the central villages studied over the study time, the consumer characteristics that influenced the range of sampled goods and services are discussed in Chapter Six. CH A P T ER SIX A SO CI OECONOMIC ANALYSIS OF FARMERS' PREFERENCES IN ES TAB LIS HIN G BEHAVIORAL RANGES FOR CENTRA L VILLAG E GOODS AND SERVICES Range Of Goods And Services The concept of the range of a good or service is a component of classical central place theory cussed in Chapter O n e ) . (dis­ It involves consumer distance m i n ­ imization wi th i n a hexagonal (regular) pattern of marketing. The deterministic aspect of original central place theory is relaxed and mo dified to permit probabilistic that explain consumers' goods and services. interpretations behavioral patterns toward different Classical regular patterns of central central place theory concerns places, rather than including socio-psychological elements that influence consumer per ce p­ tions and preferences 1980:160). (Blommestein, Nijkamp, and V e e n e n d a a l , Contr ibu to rs to revised central place theory have examined the influence of these consumer ch a r a c t e r ­ istics in their shopping preferences at a certain central for a certain function place. In relation to the biased preferences of consumers, spatial range of goods and services may be spatially 244 the 24'5 flexible (competitive functions) (convenience functions). or spatially inflexible Consumers' preferences for shop­ ping in a particular store have been found to be influenced by consumer cha racteris tics and subjective and objective factors in recent studies of revised central In this chapter, place theory. the sho pping preferences of the farm and nonfarm families of the study area for selected functions in a certain central place, families' are rep orted in examining rural characteristics, and their subjective and o b ­ jective shopping choices. Procedure In order to visu al i ze the shopping travel model of farm and nonfarm families toward the sampled functions, data were collected from field survey ques tio nna ire s of 90 farm fam­ ilies and 90 nonfarm families Figures 6.1.1 and 6.1.2 in this research show the locations of the selected rural families who par tic ip at ed in this survey. sampled function, (Appendix B ) . For each one sho pping travel map for farm families and another for nonfar m families have been provided. To measure and compare the mileag e travelled by the rural families for each sampl ed function, descript ive statistical methods were used to dete rmi ne averages and standard dev ia­ tions . Key S e ttle m e n ts o f Shopping and V is tin g fo r Farm ers .Ithaca kCarson City South-central Michigan, 1983 Maple Rapids © ^ Ionia Grand Rapids, £ Flint / S t . Johns F o w le r ^ I Owosso »*?Ovid kSwartz. Creek Durand^ .•S a r a n a c Westphalia Byron • • ■: * •• Lansing _ W illiam ston O kem os® ^ H a s tin g s • Dim ondaie^ *•! Nashville © H o lt •*' M ason® JWebbervilte •••:' Charlotte © E a to n Rapids © H o w e ll © B rig h to n Stockbridgc • «: .. • '.^P in kney Chelsea^ Battle Creek t K alam azoo, M a rs h a ll® # Albion Concord ' • H o m e r* , © Fowlerville .D a n s v iile U r b a n a n d N o n - U r b a n C e n te rs : £ Jackson Dexter *. • D etro it Ann Arbor ** • ho •£- Ypsilanti © S p rin g Arbor . # H o r to n ON Brooklyn * • * Hanover Major Key Settlements for Farmer's Shopping and Visiting Travels • • S a m p le d C e n t r a l V illa g e s : • c o ld w a t e r M inor Key Settlements for Farmer's Shopping and Visiting Travels . Jonesville © H ills d a le Adrianl G r a n d R a p id s K a la m a z o o . S a m p le d F a r m e r s F i g u r e 6 .1 .1 T h e k e y s e tt le m e n ts o f u rb a n a n d ru ra l c e n t e r s f o r s h o p p i n g o r v is itin g tr a v e l m o d e l s o f f a r m f a m ilie s s a m p l e s . >Flinty s .D e tr o it ‘‘Ann Arbor |thaca j^ey S e ttle m e n ts of S hopping and V is itin g fo r Rural N o n -F a rm F am ilies South-central Michigan, 1983 Maple Rapids St. Johns Fow ler, ^lonia Grand Rapids, *A«Ovid ® S w a rtz Creek C o ru n n a ' Saranac Durand Westphalia Lowell 0 Flint kOwosso f Byron Lake O d e s s a * / Grand L e d g e ^ O kem o^ Lansing Dim ondale « Hastings’ . v Nashville £ kHolt ** # Williamston 0 Webberville ® F o w le rv ille • . Dansviile M ason® C h a rlo tte ® • • ^ H o w e ll Brighton’ S to ckbndge* K a la m a z o o 0 • D etro it ** ^ A n n Arbor i Jackson i Albion M arshall’ ® Pinkney D e x te r, Chelsea • . Battle C reek. .Farmington ® Ypsilanti .M anchester * U r b a n a n d N o n - U r b a n C e n te rs : __ M ajor Key Settlements for * Homer Concord Hanover ..Brooklyn ’* N o n -F a rm Families Shopping and Visiting Travels J o n e s v ille ® • S a m p le d C e n t r a l V illa g e s H ills d a le ® A d ria n ® M inor Key Settlements for N o n -F a rm Families Shopping and Visiting Travels . G ra n d R ap id s K a la m a z o o . S a m p le d N o n - F a r m F a m ilie s Figure 6.1.2 The key settlements of urban and rural centers for shopping or visiting travel models of non-farm families sampled. •Flinty } , D e tr o it ^‘Ann Arbor 248 For determining the factors (subjective or objective) that were statistically significant in an individuals' shop­ ping choice behavior for a certain function in a certain 14 the chi-square test, an inferential central place, statistical individual technique, factor has been used exclusively for each (Tables 6.1.1. and 6.1.2). The examined factors are sorted on a chi-square probability scale a c c o r d ­ ing to their probability of association with rural families' selection of a certa in function in a certain central place (Figure 6.1.3). from 0 to 1.00 The scale of observed probabil ity ranges (Figure 6.1.3), but only factors tween 0-.05 are statistically significant confidence level). located b e ­ (at the 95 percent Detailed information of chi-square tests applied in this research is presented in Ap pe ndi x C, while chi-square probability scales and the coefficients of Phi and Cramer's V are presented in this Chapter. The null hypothesis predicts no as so ciation be twe en a certai n factor and the rural function (such as age, families' saving m o n e y , . . .etc.) shopping selection of a certain (such as grocery, d e a l e r ,...etc) distance, department store, in a certain central place, automotive while the _ To determine the strength of association betwe en the two variables examined by a chi-square test, Cramer's sta ­ tistic for larger tables (more than 2x2) and the Phicoefficient for small tables (2x 2 ) that indicate the greater amount of strength of association were used. Both Cramer's statistic and the Phi-coefficient vary from 0 to 1; a greater value implies stronger association (Winkler and Hays, 1975:833-835; and Klecka, Nie and Hull, 1975:78-81). TABLE 6.1.1: A Pilot Pattern* for a Chi-Square Test: Examining the Association Between the Age of Farmers and Their Selection of a Grocery Store in a Certain Central Place Central Other Places Age Groups 1st Order Villages 2nd Order Villages Places 3rd Order Villages 4th Order Villages 5th Order Villages 6th Order Villages * k k k * * * * * * * * * * * * * * * * * * ★* kkkk 25-55 * * * * * * * * ★★* * •k -k -k -k * * * * * * * * k k k k Over 55 ★★★★ * * * * * * * * k k k k * ★★ * kkkk kkkk 2 = ? df:12 Probability of association = ? Cramer's V = ? *In practical Chi-square tests of this research, the columns and rows are combined when there are expected frequencies less than five in a cell or cells of the contingency table. This effort improves the accuracy of the test. Most of the tables examined in this re ­ search included small degrees of freedom. 249 Under 25 250 TABLE 6 . 1 . 2 : A Pilot Program of Factors Related to Farmers' Selection of Grocery Store in Central Places Factors ChiSquare df Observed Probabilities C r a m e r 's V or PhiCoefficient Objective Factors Convenience of Shopping * * .20 > P > .10 * * * .50 > P > .20 * Income ie * .10 > P > .05 * Age * 12 .05 > P > .01 * Length of Residence * * .05 > P > .01 * Trips per Week * * .70 > P > .50 ★ Full Time or Part-time Farming * ★ > P > .70 * Type of Farming * ★ .05 > P > .01 * Subjective Factors Save Money Individual Characteristics 1.0 Factors R elated to Farm ers' Selection of Grocery Stores in C ertain C entral P la c e s a> a> < >» a 0} ■g "« a> £ O) c CL Q. GC O H F u ll T im e o r P a r t T im e F a r m in g T r ip s p e r W e e k CO c o o as u_ (A a > 0.00 F ig u r e 6 .1 .3 a pilot p a tte r n of c h i-s q u a re p ro b ab ility sc a le for g ro cery fu n ctio n . F a c to rs of “ty p e s of f a rm in g ” , “ le n g th of r e s id e n c y ” , a n d " a g e ” a re statistically sig n ifican t o f having a s s o c ia tio n w ith th e se le c tio n of g ro c e ry s to r e s in p a rtic u la r c e n tra l p laces. O th er f a c to rs a r e n o t sta tis tic a lly sig n ifican t. .10 .05 o o P o o -*■ o 252 alternative hypothesis implies an associa ti on between those variables. assuming a significance to .05, Therefore, level equal those factors ranged on the right side of probability scale figure (Figure 6.1.3) .05 on the show a statistically significant a ss oc ia tio n wi t h the choice behavior of rural families (accepting the alternative hypothesis), while the rest of the factors that are ranged on the left side of line (Figure 6.1.3) .05 do not have a statistically significant association with the choice behavior of rural families (ac­ cepting the null h y p o t h e s i s ) . Sampled Goods and Services The sampled goods and services research field survey classified list of the (rural functions) in the (Appendix B) were selected from a location coefficient values of rural functions offered in central places in 1980 (Table 2.3). There were ten such classifications and one rural function was selected ran domly from each strata or class (Table 2.4). The shopping behavior of farm and nonfarm families was then surveyed in regard to ten selected functions. rural families' shopping travel behavior for each of these sampled rural functions have been provided field survey data) function. Models of showing the behavioral (through the range of that The mean values and standard deviations of the mileage travelled by rural families for each function were calculated to determine the different consumer behavioral 253 ranges for the sampled functions. (subjective, objective, personal The hy po thesized factors characteristics) in­ fluencing those shopping travel models were also determined by their chi-square values and the coefficients strength of a s s oc ia ti on the related tables. chi-square tests, showing (Cramer's v and Phi-coefficient) Moreover, on those factors examined in the were sorted on the figures of related chi- square pr ob ab ili ty scales. In order to e x pl ai n the spatial dist ri bu ti on of sampled functions and consumers' ward these functions, (rural families') preferences to ­ the ten sampled functions are arranged in regard to their ex istence in the class order of central villages. typical For instance, the grocery store function was in all classes of central villages, so it is called a sixth order villa ge function. The clinic and optometrist functions were typical second, village functions, village functions in first, and third order therefore they are termed third order in this research. Jewelry and floor c o v ­ ering stores were found to be second order village fu n c ­ tions, paint and d ep ar tm en t stores were first order village functions and family clothing, automotive dealers and shoe stores were town and city level functions. The ten sampled functions are thus di scussed in five separate 254 sections according to their position as typical 15 certain classes of central villages. functions in Sixth Order Village Functions Among the sampled functions in this research, the grocery store function with a 1.54 location coeffici ent was the lowest order function and was almost typical the classes of villages in 1980 store function was typical (Table 6.2). in all of The grocery in sixth order villages in 1950 and 1970, but its average number in sixth order villages 1980 (.22) was only "near typical". As was di scussed in Chapter Five, by 1980 had declined ever, food services hamlet level (Ray, Barnum and Tennant, Clark, (Murdie, 1966). ping travel sixth order villages in viability to the hamlet (grocery) 1967:145) 1962:79) 1965; Ray, level. How­ tend to remain viable at the or the village level (Berry, and have been shown to have the lowest range of consumer travel mileage studies in 1965; In this research, in some empirical Golledge, also, Rushton and the range of shop­ for grocery stores among both farm families (Figure 6.2.1) to be lowest, and nonfarm families (Figure 6.2.2) was shown compared w ith the other sampled functions _ As noted in Chapter Five, typical functions for this research are those that are available in at least one-third of the villages of a certain class. Therefore, the e x i s t ­ ence of at least one-third or .33 functional unit of a function per class of villages defined a typical function for that class of villages. TABLE 6.2: Distribution of Functional Units (N) and Average Number of Sampled Functions in Central Villages: Types of Functions Functional Uni ts (N ) Grocery Store Optometrist Clinic Second Order Villages N Avg. Third Order Vi 1lages N Avg. Fourth Order Vi 1lages N Avg, Fifth Order Vi llages N Avg. Sixth Order Vi 1lages N Avg. 1 .54 11 3.67 19 2.71 7 1 .75 10 1 .67 14 1 .75 4 .22 9 8 11.11 12.50 2 4 .67 1 .33 2 2 .29 .29 3 1 .75 .25 0 0 0.00 0.00 1 1 .13 .13 1 0 .06 0.00 16 .66 2 .67 3 .43 0 0.00 0 0.00 1 .12 0 0.00 14 .28 4 1 .33 2 .29 1 .25 0 0.00 0 0 .00 0 0 .00 25.00 1 .33 1 .14 0 0.00 0 0.00 1 .12 1 .06 33.33 2 .67 0 0.00 1 .25 0 0.00 0 0 .00 0 0.00 5 20.00 0 0.00 1 .14 2 .50 2 .33 0 0 .00 0 0 .00 2 1 50 .00 100.00 0 0 0.00 0.00 0 0 0.00 0.00 0 0 0.00 0.00 1 0 .17 0.00 1 1 .12 .12 0 0 0.00 0 .00 Paint & Wall­ paper Store 4 Depar tment Store 3 SOURCE: First Order Villages N Avg. 65 Floor Covering Store 6 Jewelry Store 7 Family Cloth­ ing Store Automotive De a 1e r Shoe Store Location Coefficient (L.C.) 1980 Data is selected from Tables A.7 and A.B 256 Farmers' Shopping Travel: Grocery S tore S o u th -ce n tra l M ichigan, 1983 | C e n lr a t C itie s ' ( P o p u l a l i o n 5 0 0 0 0 t o POO 0 0 0 i B ig C itie s a n d C e n s u s D e s ig n a te d P la c e s ( P o p u l a t i o n 10 0 0 0 t o 5 0 0 0 0 1 C itie s C o u n ty S e a ts a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n 5 0 0 0 to 1 0 0 0 0 i T o w n s V illa g e s a n d C e n s u s D e s ig n a te d P la c e s ( P o p u l a t i o n L e s s t h a n 5 OOOt C e n tr a l V illa g e s S a m p le d F a rm F a m ilie s S a m p le d G ra n d R a p id s . i S u p e rc ity '( P o p u l a t i o n F ig u r e 6.2.1 M o r e t h a n 1.QOO.OOOI S h o p p in g tra v e l m o d e l o f fa rm fa m ilie s s a m p le d f o r g r o c e r y s to r e s . Rural Non-Farm Fam ilies' Shopping Travel: • Grocery S tore S o u th -ce n tra l M ichigan, 1983 •• ( C e n tr a l C itie s (P o p u la tio n : 5 0 ,0 0 0 to 2 00.000) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s (P o p u la tio n : 10.000 to 50,000) C ities. C o u n ty S e a ts , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 5 ,0 0 0 to 10,000) T o w n s , V illa g e s, a n d C e n s u s D e s ig n a te d P la c e s (P o p u la tio n : L e s s th a n 5,000) C e n tr a l V illa g e s S a m p le d N o n - F a r m F a m ilie s S a m p le d G ra n d R a p id s >S u p e rc ity ( P o p u la tio n : M o re th a n 1,000.000) F ig u r e 6 .2 .2 S h o p p in g tra v e l m o d e l o f n o n - f a r m fa m ilie s s a m p le d f o r g r o c e r y s to r e . D e tro it 257 (Table 6.3). studied, This implied that in the central villages grocery stores were still supported by local farm and nonfarm families with a good percen ta ge of grocery in­ shopping. However, the gr eatest percentage of local grocery shopping was done by farm families parent that further increases (Table 6.3.1). in rural nonfarm population will mean declines for most of these Therefore, the future. efficients It is ap ­ local grocery stores. sixth order villages may lose this function in Functions in the same class of location c o ­ (Table 2.3), such as churches, eating places and grain elevators, hardware stores, may face the same future in sixth order villages. In order to determine the factors of grocery stores, the results of chi-square probability tests are shown in Figures those figures, influencing the range 6.2.3 and 6.2.4. the factors of distance, age, According to length of re ­ sidency a n d 'types of farming were statistically significant for selection of groce ry stores by farm and nonfarm families in central tween places. Distance, at a significance .001-0, with a strong Phi-coefficient, important factor, grocery shopping and 6.2.4). level b e ­ was the most among both farm and nonfarm families, (Tables 6.4.1 and 6.4.2 and Figures This meant that rural for 6.2.3 families value the pr o x ­ imity of a central village for their grocery shopping. Length of residency was also an important factor in the grocery shopping model among both farm and nonfarm families 2 58 TABLE 6.3: Farmers and Nonfarmers' Travel Mileage for Sampled Functions, by Descriptive Statistical Values Sampled Functions Mean Grocery Store Farmers Standard Deviation Mean Nonfarmers Standard Deviatio 5 .22 4.40 6.80 5.60 11 .90 6.30 12.90 7.60 9.10 5 .90 12 .66 9.40 Floor C o v e r ­ ing Store 13 .90 7. 70 15.14 8.03 Jewelry Store 13.50 7.20 13.08 7.90 Paint & W a l l ­ paper Store 11.20 7.00 14 .60 8.90 Department Store 14 .40 7.50 14.53 8.90 Family C l o t h ­ ing Store 15.50 7.40 14 .60 7.60 Automotive Dealer 10 .40 6 .50 13.07 11.70 Shoe 15.10 8.40 16.06 8 .75 Optometrist Clinic Store SOURCE: Data is collected from the farm and nonfarm families' survey q u e s ti on na ir es (Appendix B). 259 TABLE 6.3.1:, Percent of Outshopping and Inshopping by Rural Families for the Sampled Functions Farm Families Sampled Functions Percent of Outshopping (Urban Centers) Percent of Inshopping (Central Villages) Nonfarm Percent of Outshopping (Urban Centers) Families Percent of Inshopping (Central Villages) Grocery Store 42 .0 58.0 64.9 35.1 Optometrist Clinic 85.4 67.0 14.6 33.0 87.5 74 .4 12.5 25.6 8.6 94 .5 5.5 9.5 93 .75 6.2 Floor C o v e r ­ ing Store 91 .4 Jewelry Store 90.5 Paint & Wall paper Store 82.3 Department Store 85.1 Family Cloth ing Store Automotive Dealer Shoe Store SOURCE: 17.7 88.7 11.3 14.9 90.9 9.1 94.1 5.9 97.7 2.3 70 .2 89.9 29.8 10.1 81.0 97.6 19.0 2.4 Data are derived from the farm and nonfarm families' survey questionnaires (Appendix B) which were c o l ­ lected in the summer of 1983 by the researcher. 260 Factors Related to Farmers' Selection of Grocery Stores in C ertain C entral Places E ducation Farm C onsolidation Trips per Week Farm Size Price of G o o d s Fuil Tim e or Part Tim e Farming C h ange to S p ecialization S a v e M oney Tim e of Farm 's A utom ation S p ecia lized G o o d s A ttractiven ess of the Market and Serv ices 1.00 ,70 .50 .20 10 .05 bo® - 28 I00 > a > 0.00 F ig u r e 6 .2 .3 C h i-S q u a r e probability sca le: F actors classified b e tw e e n a ** 0 .0 and 0 .0 5 imply statistically significant a s so c ia tio n s with th e se le ctio n o f grocery sto r e s, an d th e fa c to rs c la ssified b e tw een a « 0.05 to 1.00 d o not have a sig n ifica n t a sso c ia tio n w ith th e se le c tio n o f grocery storea. Factors Related to Non-Farmers' Selection of Grocery Stores in C ertain Central Places E ducation C o n v en ien ce o f Shop ping A ttractiven ess o f th e Market 1.00 .70 .50 1.00 -20 > « > 0.00 F ig u r e 6 .2 .4 C h i-S q u a r e probability s c a le : F actors c la ssified b e tw e e n a - 0 .0 a n d 0 .0 5 im ply statistically sig n ific a n t a s so c ia tio n s w ith the se le c tio n o f gro cer y stores: a n d th e factors c la ssified b etw een a - 0 ,0 5 to 1.00 d o n o t n a v e a sig n ifica n t a sso c ia tio n with th e se le c tio n o f grocery stores. o P 28 TABLE 6.4.1: Factors Related to Farm Families' Factors/Functions Objective Factors Distance Price of Goods Specialized Goods/ Services Shopping Convenience Attractiveness of Market Shopping Travel Models for Sampled Functions: Cramer's V and Phi-Coefficient Grocery Store Floor Opto­ Covering metrist Clinic Store Jewelry Cramer's V and Phi -Coefficients* Paint & Wall­ paper Depart­ ment Store Family Clothing Automo tive Dealer Shoe Store .41496 .18036 .30496 .07788 .41100 .13561 .17324 .20842 .21437 .17171 .16647 .19421 .10295 .31183 .08032 .35093 .52503 .22235 .16053 .33743 .09759 .20576 .41989 .20965 .41197 .24425 .19742 .11114 .20599 .12193 .08047 .23158 .14173 .26015 .11578 .173 72 .21707 .30148 .27907 .24007 .01308 .07630 .02863 .14085 .15090 .12547 .05248 .13625 .12599 .18993 .20296 .21873 .02964 .47284 .11952 .40838 .30732 .13763 .22942 .19672 .35834 .18025 .27315 .16720 .32269 .10981 .25785 .35328 .33743 .17344 .20504 .23191 .10334 .21737 .15754 .22048 .12690 .17503 .07422 .10186 .20494 .09554 .08169 .08108 .04804 .06371 .19723 .05346 .25733 .22736 .02791 .02889 .11485 .24846 .18233 .09664 .00893 .14459 .15227 .00384 .10576 .03181 .10135 .17637 .06412 .29127 .13169 .10100 .04632 .15254 .13326 .03810 .22070 .02296 .00140 .14748 .05065 .22351 .08545 .02776 .01999 .13743 .14517 .16823 .10911 .13221 .02605 .15592 .01881 .22763 .14698 .02094 .16517 .11741 .16038 .23131 .15076 .00262 .07708 .03194 .05263 .01957 .17396 .06637 .34851 .08212 .13023 .28264 .25607 .13697 .27503 .21224 .11965 .14534 .08601 .06587 .07434 .02647 .11726 .02306 .09132 .07325 .04904 .00483 .02409 .03546 .09333 .10488 .01367 .00408 .04095 .06984 .18469 .02734 .15610 .31721 .06387 .02066 .22608 .20787 Subjective Factors Save Money Save Time Farmers' Characteristics Income Age Education Length of Residency Shopping Trips Per Week Farm Size Farm Consolidation Full- or Part-time Farming Type of Farming (Cash crop, dairy. etc.) C h a n g e to specializat ion Time of farm auto­ mation •Cramer’s V was selected for ch i-square tests with more than one degree of freedom; the Phi-coefficient was used for tables having only one degree of freedom. SOURCE: Data is derived from Appendi x C (Tables C.1-C.10) T ABLE 6.4.2: factors Relat ed c o efficient Factors/Functions Grocery Store Objective Factors Distance Price of Goods Specialized Goods/ Services Shopping Conven­ ience Attractiveness of market to No nf arm Families' Opto­ metrist Clinic Sho p ping Tr avel FI oor Covering Store Jewelry Store Model s tor Sam p led Fun ctions: C r amer 's V and Phi- Paint & Depart­ wal1paper ment Store Store Family Clothing STORE Automo 11 ve Dealer Shoe Store Cramer's V and Phi-coeffi c ients* .56387 .28151 .51700 .16896 .50345 .02373 .05676 .05190 .06482 .03976 .09283 .21817 .01760 .26162 .03355 .22479 .38U69 .07358 .17395 .19285 .17314 .32535 .42607 .22616 .12109 .19167 .24250 .27962 .25044 .28813 .12366 .15117 .19905 .08224 .00672 .11435 .12333 .22148 .10631 .21690 .11866 .07564 .03087 .07443 .17094 .16116 .08627 .21272 .06984 .21272 .23428 .16826 .18157 .27594 .01475 .18952 .11888 .15421 .04085 .10445 .16386 .09469 .27292 .11476 .31277 .08364 .05151 .14075 .20420 .21018 .20587 .37817 .10124 .05578 .19760 .23685 .03007 .18099 .17550 .15811 .22131 .04242 .01952 .07024 .13766 .03902 .15476 .27477 .04358 .04545 .06236 .04486 .10557 .05415 .11099 .06618 .15922 .14215 .29680 .10057 .09499 .04603 .11642 .05087 .09077 .13290 .10025 .05340 .1212 3 .08986 .07944 .04340 .01160 .04194 .10148 Subjective Factors Save Money Save Time Non-Farmers' Characteristics Income .08547 Age .14360 Education .18238 Length of Residency .24962 Shopping Trips Per Week .22197 ‘Cramer's V was selected for chi-square tests with more than one degree of freedom; the Phi-coefticient was used for tables having only one degree of freedom. SOURCE: Data is derived from Appendix C (Tables C.11-C.20) 263 (Figures 6.2.3 and 6.2.4). There was a greater tendency toward grocery shopping in the urban central places, local villages, among the rural sided longer in their present rather than families that had re­ location. The greatest p e r ­ centage of o u t s h op pin g of local grocery stores was done by rural families with short residency and nonfarm families co ns iderably ex ce ed ed farm families in this regard. Therefore, future increases of new rural nonfarm residents in the study area, will not be favorable for local grocery stores. The factor of age was also important in the farmers' g r oc er y shopping. The older farmers were more likely to do their groce ry shopping in a nearby central village, while young er farmers were more oriented toward urban central places for grocery shopping. Type of farming was also significant in the grocery shopping be havior of farmers who w ere prod uc in g crops, (Figure 6.2.3). cash crops, More farmers and feed tended to­ ward grocery shopping in central villages than dairy and beef farmers, wh ic h may be related to the convenience of local elevators for cash crop and feed crop farmers. they visit ed the local elevator, When they also tended to do their grocery shopping in that place. Prices of goods were a co m p l e m e n t a r y significant factor in the nonfarm families' grocery shopping be ha vi or (Figure 6.2.4). Because of groce ry price co nsiderations among some of the nonfarm fam­ ilies, there was a greater standard deviation in their 2 64 travel mileage for grocery shopping compared with farmers' grocery shopping patterns (Table 6.3). Rural nonfarm fa m­ ilies thus outshopped the local groce ry stores more than farm families, due to better prices available in urban central places. The factor of income was also hypothesized to be in­ fluential in the individual families. shopping behavior of rural The relations betwe en them were found to be between the .10 and .05 significance with a strong Cramer's coe ff ici ent farm families' Of lower income families, among the Although income was (such as distance, in the grocery shopping of farmers, ential. (Figure 6.2.3), (Table 6.4.1) grocer y shopping model. not as significant as other factors etc.) levels age, it was in flu ­ 59 percent shopped the grocery in their central villages while 41 percent shopped in urban central places. Of higher income farmers, cent shopped the grocer y in the central village, percent shopped in urban central places. show that farmers of any income 56 p e r ­ while 44 These percentages level are likely to do their grocery shopping in their nearby central village, but there is a tendency for outs hop pin g for groceries among the higher income farmers. Income was not statistically significant for nonfarm families' grocer y shopping was also a tendency among higher outshopping. (Figure 6.2.4), but there income people for grocery 265 Trips per week to a local town was hy po thesized to be another factor influencing the grocery shopping of rural families. Although not a statistically significant factor in the grocery shopping model (Figure 6.2.3 and 6.2.4), there was some preference among the most mobile of rural w hile nonfarm families to pa tronize 25 percent local grocery stores, 38 percent of less mobile nonfarm families patronized local groce ry stores. Therefore, more of the most mobile families did their grocery shopping (outshopping). in urban central places Of the farm families, 59 percent of the less mobile families and 60 percent of the more mobile families patron zie d local grocery stores. Overall, the factor of mo bility had little affect on farm families' grocery shop ­ ping behavior. It was found that the grocery store as a sixth order villa ge function is unstable and seems juncture, future. at this to become a fifth order village function in the This is due to the precipitous decline vi ab ili ty of sixth order villages Di ssa tis fac tio n with able likely, in sixth, at least since fifth, 1950, to the hamlet in the level. local rural goods and services a v a i l ­ and fourth order villages has existed, among the rural families of the v i l ­ lage h interlands who demonstrated their lack of sa ti sf ac ­ tion with such local central places. functions by bypassing them for urban The major problem of these smaller rural settlements of study area was related to the limited 266 functions they offered. Thus, the fourth, fifth and sixth order villages were dispatronized by farm and particularly the nonfarm families to the benefit of urban central places in a process of rural development in the region that began around the 1950s. Price considerations in grocery shopping among the rural nonfarm population only encouraged their pa tronage of grocery stores in urban centers. It was found that the sixth order villages were very sensitive to the effects of rural development and the concomitant increase of the nonfarm population (Chapter Five). functions, (urban patronizers) Therefore, in the area maintaining the lowest such as grocery stores, level in the sixth order v i l ­ lages have faced the serious problem of being typical sixth order villages. Further rural development, more new nonfarm families into the study area, in bringin g can be e x ­ pected to result in even more bypassing of local grocery stores, lages ev entually affecting fifth and fourth order v i l ­ in the same way sixth order villages have been a f ­ fected. It is, the future, therefore, not unrealistic to expect that in the fourth and fifth order villages will become as nonviable as the present sixth order villages, rural develop men t and rural families' due to shopping preferences. Third Order Village Functions The two non-retail functions of optometrist and clinic were available almost typically in first, second and third 267 order villages by 1980 (Table 6.2). two optometry est ablishments area's central vil lag es establishments by 1980 in first order vi llages In 1970 there were only (functional units) (Table 5.9) (Table 6.2). in 1970 in the study that increased to nine They were typical only (Table A . 7). The increase of optometrists was related to support of this function by both farm and n on fa rm families (Table 6.3.1). Clinics were increased from one unit to eight units in the study area over the 1970-1980 period typical (Table 5.9). Clinics were a function in only the first order villages but increased to bec om e almost typical villages and near typical (Tables 5.19 and 6.2). clinics in 1970, in second order in third order villages by 1980 The increased number of local is related to their use by a high percentage of both farm and nonfa rm families (Table 6.3.1). The percentage of those invisiting the clinics was greater among farm families than nonfarm families. Rural f a m i l i e s 1travel mileage for both the optometry and clinic functions had greater means and standard deviations than did the groce ry store function (Table 6.3). Optometry and clinic can thus be called spatially flexible rural vices, ser­ compared wi t h the spatially inflexible function of grocery. explain, As Golledge, Rushton and Clark (1966:263, 264) a sp atially flexible function is patronized by people who travel great er distances for that function instead of p at ro ni zin g the nearest place, while spatially 268 inflexible goods are patronized by people who seek the nea r­ est occurrence of those functions. The percentage of rural farm and nonfarm families visiting the were very similar (Table 6.3.1) local optrometrists and the mileage travelled to visit the optometrists at the central places were quite high for both groups the whole, (Table 6.3 and Figures 6.3.1 and 6.3.2). On rural nonfa rm families had a bigger range of travel and de mo nstrated a little less support for local op ­ tometrists compared wi t h farm families. Among the factors examined for modal choice of the o p ­ tometrist function, services, distance, age, specialized goods and and time saving were statistically significant with strong coefficients of as so cia ti on among both the farm and nonfarm families surveyed Tables 6.4.1 and 6.4.2). (Figures 6.3.3 and 6.3.4 and Age was an influential the choice of a local or distant optometrist. factor in There was ob ­ vious patronization of local optomerists among elderly farm and nonfarm families, while middle- ag ed and younger ones tended to patronize optometrists in urban centers. This means that elderly residents were more satisfied wi t h the local optomerists than younger and middle aged families. The factors of distance jective) (objective) and saving time (sub­ were also important among farm and nonfarm fam­ ilies who patronized local optometrists. optometry as a specialized function was Perception of influential in . 269 Farm ers' V isiting Travel: O p tom etrist S o u th - c e n tr a l M ic h ig a n , 1 9 8 3 4 | C e n tra l C itie s ( P o p u la tio n : 5 0 ,0 0 0 to 2 00.000) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 10,000 to 50,000) C itie s, C o u n ty S e a ts , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 5 ,000 to 10,000) T o w n s , V illag e s, a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : L e s s th a n 5,000) C e n tra l V illa g e s S a m p le d F a rm F a m ilie s S a m p le d I F h n l\ %D e tro it ( S u p e rc ity ( P o p u la tio n : M o re th a n 1,000,000) F ig u r e 6 .3 .1 V isitin g travel m o d e l o f farm fa m ilie s s a m p le d for o p to m e tr ist. Rural Non-Farm F am ilies V isiting Travel: • O ptom etrist S o u th - c e n tr a l M ic h ig a n , 1 9 8 3 i C e n tr a l C ities ' ( P o p u la tio n . 50 .0 0 0 to 200,000) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 10.000 to 50,000) C itie s , C o u n ty S e a ts , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 5 ,0 0 0 to 10,000) T o w n s , V illag e s, a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : L e s s th a n 5,000) C e n tr a l V illa g e s S a m p le d N o n - F a r m F a m ilie s S a m p le d G ra n d R a p id s , k S u p e rc ity r |P o p u l a t i o n F ig u r e 6 .3 .2 ^ D etro it M o re th a n 1,000.000) V isiting tr a v el m o d e l o f n o n -fa rm fa m ilies sa m p le d fo r o p to m e tr ist. 270 Factors Related to Farmers* Selection of O ptom etrists in C ertain C entral Places Trips per W eek C h ange to Specialization Full Tim e or Part Tim e Farm ing Time o f Farm's A utom ation E d ucation Farm C o n so lid a tio n Price of G oods A ttractiveness o f the Market Save M oney 1.00 .20 .70 o 6 P - 28 10 0 > « > 0.00 F ig u r e 6 ,3 .3 C h i-S q u a r e probability sca le: F a ctors c la ssifie d b e tw e e n a » 0.0 an d 0 .0 5 imply sta tistica lly sign ifican t a s s o c ia tio n s with th e se le c tio n o f o p to m e trists; a n d th e factors c la ssifie d b e tw e e n a > 0 .0 5 to 1.00 d o n o t have a sig n ific a n t a sso c ia tio n with (h e s e le c t io n o f optom etrists. Factors Related to Non-Farmers' Selection of Optometrists in C ertain'C entral Places Trips per Week L ength o f R esid en cy P rice o f G o o d s C o n v en ie n c e o f S h o p p in g A ttractiveness o f th e Market S a v e M oney 1.00 .70 .50 -20 1.00 > o > 0.00 F ig u r e 6 .3 .4 C h l-S a u a r e probability sc a le ; Factors c la ssifie d b e tw e e n <* > 0 .0 an d 0 .0 5 im ply sta tistic a lly sig n ifica n t a sso c ia tio n s w ith th e se le c tio n o f op to m e trists; a n d th e fa c to rs c la ssifie d b etw e en a > 0 .0 5 to 1.00 d o n o t h ave a sig n ifica n t a sso c ia tio n w ith th e s e le c tio n o f op tom etrists. .10 .05 © © P - 28 271 encouraging farm and nonfarm families to bypass local o p ­ tomerists . Type of farming was statistically significant at the .05-.10 coefficient. level (Figure 6.3.3) with a strong Phi- There was greater support of local op t o ­ metrists by general farmers who plant cash and field crops, compared with dairy or beef farmers. This may be related to more frequent visi ts .t o central villages by cash crop farmers who deal wi th local elevators. Therefore, tied more closely to the local rural services, they are including op ­ tometrist . On the whole, optometry was found to be a function most often ou tvisited by rural families of various incomes, but there was a slight tendency for higher income farm and n o n ­ farm families to favor local optometric services more than lower income farm and/or nonfarm families. that the higher income rural It may be noted families preferred to save time by pa tro nizing a local optometrist (saving time was statis­ tically significant among farm and nonfarm f a m i l i e s ) . was no significant association, nonfarm families' however, between farm and sho pping trips per week and their choice of a local or distant optometrist (Figures 6.3.3 and 6.3.4), indicating that degree of mobility among rural not important in their Optometrists, There families is locational choice of an optometrist. as a flexible function, tion with urban central places' are in c o m p e t i ­ optometrists, which could be 272 harmful for their future survival at the level of third order villages. On the other hand, with increased nonfarm population on the farm landscape of the study area, local optometrists may remain stable at their present level. As mentioned earlier, local clinics were supported by both farm and nonfarm families at a high percentage level compared with other sampled functions except grocery 6.3.1). The mileage (Table travelled and related means and stand­ ard deviations for clinic visits were greater among nonfarm families than farm families (Table 6.3 and Figures 6.4.2). standard deviations On the other hand, 6.4.1 and for the mileage travelled by farmers for clinic visits was moderate. Variations in mileage tr avelled and standard deviations b e ­ tween these farm and non farm groups is a flexible function. and nonfarm families, Wi t h the indicate that clinic local support of both farm local clinics may survive locally, spite of their co mp etition w i t h urban clinics. large increases of nonfarm families, for clinic visits, in However, who had a great range could cast doubt on the stability of local clinics. Highly significant factors that influenced the farm and nonfarm families' distance choice of clinics (proximity) in a central place were and p er ce pt io n of the clinic as a spec­ ialized service, wh ic h y i el de d strong coefficients of as so c­ iation shown by Ph i- co ef ficients and Cramer's statistics 273 (Figures 6.4.3 and 6.4.4 and Tables 6.4.1 and 6.4.2) Time- saving and convenience were statistically significant aspects of farm families' clinic visits, in that some of them visited a nearby clinic for convenience. Time-saving and convenience were highly significant for nonfarmers at an 80-90 percent of probability of association The significance of prox imi ty (distance) (Figure 6.4.4). to a local clinic, and time-saving and convenience aspects were factors that en couraged rural families to visit local clinics. tions of clinics as specialized services, cou rag ed rural families' visitations Pe r ce p­ however, en­ to urban clinics. A future increase of speci alized clinics in urban centers, could cause a decline in local clinics. Level of education was an important factor among the farm families. There was a tendency for less educated farmers to visit the clinics those in central villages rather than in urban central places. Length of residency and age were significant factors influencing nonfarmers' vis iti ng patterns (Figure 6.4.4). clinic The younger nonfarm families with fewer years of rural residency were more likely to visit the local clinics than middle-aged and elderly nonfarm families with more years of residency. Middle-aged, nonfarm families had more local clinic visits than e lderly nonfarmers. The decreased pat ronization of local clinics by elderly nonfarm families may be related to their needs for more specialized professional able in urban clinicis and hospitals. help a v ai l­ The support of local 274 Farm ers' V isiting Travel: Clinic S o u th - c e n tr a l M ic h ig a n , 1 9 8 3 | C e n tra l C itie s ( P o p u la tio n : 5 0 ,0 0 0 to 2 00,000) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 1 0 ,0 0 0 to 50,000) C itie s, C o u n ty S e a ts , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n ' 5 ,0 0 0 to 10.000) T o w n s , V illa g e s, a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : L e s s th a n 5,000) C e n tr a l V illa g e s S a m p le d F a rm F a m ilie s S a m p le d / S u p e rc ity (P o p u la tio n : M o re th a n 1,000,000) F ig u r e 6 .4 .1 G ra n d R a p i d s . I D etro it Kalamazoo V isitin g tr a v e l m o d e l o f fa rm fa m ilie s s a m p l e d f o r c lin ic . Rural Non-Farm Fam ilies V isiting Travel: • Clinic S o u th - c e n tr a l M ic h ig a n , 1 9 8 3 £ | C e n tr a l C itie s (P o p u la tio n : 5 0 .0 0 0 to 20 0 .0 0 0 ) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 10.000 to 50,000) C itie s , C o u n ty S e a ts , a n d C e n s u s D e s ig n a te d P la c e s (P o p u la tio n 5 ,0 0 0 to 10,000) T o w n s . V illa g e s, a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : L e s s th a n 5.000) C e n tr a l V illa g e s S a m p le d N on F a r m F a m ilie s S a m p le d G ra n d R a p id s , >S u p e rc ity (P o p u la tio n M o re th a n 1,000,000! F ig u r e 6 .4 .2 v is itin g tra v e l m o d e l o f non -farm fa m ilie s s a m p le d fo r c lin ic . F lm t\ %D e tro it 275 Factors Related to Farmers' Selection of Clinics in C e r t a i n C e n t r a l P l a c e s Trtps per W eek A ge Length o f R esid en cy o n the Farm Farm C onsolidation Typ es of Farming Fuff Time or Part Time Farming C h ange to Specia liza tio n Price of G oods Tim e of Farm s Autom ation S a v e M oney A ttractiven ess of the Market o o P .70 1.00 - 28 100 > a > 0.00 F ig u re 0 .4 .3 C h i - S q u a r e p ro b a b ility sc a le : F a c to rs c la s s ifie s b e tw e e n a ~ 0 0 a n d 0.0 5 im ply s ta tis tic a lly s ig n ific a n t a s s o c ia tio n s w ith th e s e le c tio n of e im ic s. a n d th e factors c la s s if ie d b e tw e e n a = 0 0 5 to 1 0 0 d o n o t h av e a sig n ific a n t a s s o c ia tio n w ith trie s e le c tio n o f c n m c s. Factors Related to Non-Farmers' Selection of Clinics in C e r t a i n C e n t r a l P l a c e s Education Trips per Week Price of G oods Attractiveness o f the Market S a v e M oney 1.00 .05 1.00 > o > 0.00 F ig u r e 6 .4 .4 C h i - S q u a r e p ro b a b ility sc a le : F a c to rs c la ssifie d b e tw e e n a = 0 .0 a n d 0 .0 5 im ply s ta tis tic a lly s ig n ific a n t a s s o c ia tio n s w ith m e s e le c tio n o f c lin ic s : a n d th e fa c to rs c la s s ifie d b e tw e e n a = 0 .0 5 to t.0 0 d o n o t h a v e a s ig n ific a n t a s s o c ia tio n w ith th e s e le c tio n of c lin ic s o o P -28 2 76 clinics by the young, faction with these nonfarm families reveals their satis­ local health centers. The factor of age was not st atistically significant in the clinic vis iting patterns of farm families. same percentages of young, In fact, there were almost the mi dd le-aged and elderly farmers who patronized the local clinics with a slight preference in favor of the elderly and the young farmers. creases in young rural, Future in ­ nonfarm families in the central v i l ­ lages and their environs wo ul d be encouraging for some of the local clinics. The factors of income and mobility were not found to be statistically significant in "the clinic visiting models of farm and nonfarm families. d is pa tro niz ati on of This means that patron iz at io n or local clinics is unrelated to income level or degree of mobility of rural tors discussed earlier and convenience) families. (such as distance, Other fa c ­ specialization, were more statistically influential in clinic vis iting models than levels of income and mobility. As a conclusion, clinic, rural the importance of proximity to a local con venience and time-saving considerations among the farm and nonfarm families, may be supportive for re­ tention of the local clinics at the level of third order villages. However, because there is a large difference in the standard deviations of clinic travel farm families, for nonfarm and any future increase of nonfarm population could jeopardize the existence of many local clinics. Thus, 277 clinics may event ual ly be ranked at the level of second order villages where they may be more viable than in third order villages. Second Order Village Functions Floor covering stores and jewelry stores were found to be typical retail functions of first and second order v i l ­ lages. A single floor covering store first appeared as a nontypical function in the villages 1980 there were six such stores, studied in 1970, but by maki ng this relati ve ly new function a typical function in first and second order v i l ­ lages (Tables 5.7 and 5.12). were a declining retail were typical in first, 1950 and were still In contrast, function in the study area. second, typical They and third order villages in in those villages but at a r e ­ duced average number of stores by 1970 tinuing reductions jewelry stores (Table 5.10). Con­ in jewelry stores over the next decade did not affect their role in first and second order villages but made them atypical in third order villages by 1980 (Table 5.10). Thus, covering stores increased to the point that both became typical 1980 jewelry stores declined and floor functions of first and second order villages in (Table 6.2). Floor covering stores with a r e lat iv ely high mean and standard de viation for mileage tr avelled by farm and nonfarm families (Table 6.3) and with a low percentage of local 2 78 inshopping 6.3.1), (8.6 percent) by farm and nonfarm families is clearly a spatially flexible function. (Table A greater range of mileage was travelled by nonfarm families than farm families in shopping for floor coverings 6.5.2, local and Table 6.3). inshopping (Figures 6.5.1, There was also a lower percentage of (5.5 percent) b u t e d to nonfarm families for floor coverings a t t r i ­ (Table 6.3.1). However, farm fam­ ilies were a little more supportive of the local floor cov e r i n g stores. Inspite of their growth in the study area, the inshopping percen ta ge for farm families was also low. Thus, the retention of this function at the level of second order villages might be shakey. It seems likely they will be mai nt ai n ed only at the level of first order villages in the future. Among the factors ping of rural families, influencing the floor covering shop­ saving money was statistically significant for farm families, farm families 6.4.2). but not significant for n on ­ (Figures 6.5.3 and 6.5.4 and Tables 6.4.1 and The money saving consideration caused more out- shoppin g among farm families who tended to shop for sales. W hi le money saving was not statistically significant for no nf ar m families, there was a greater tendency for out- shoppin g among nonfar m families who floor coverings Educational no nf ar m families looked for sales of in u rba n central places. level was statistically significant for (Figures 6.5.3 and 6.5.4 and Tables 6.4.1 279 • Farmers' Shopping Travel: Floor Covering Store S o u th -ce n tra l M ichigan, 1983 s ( C e n tr a l C itie s ( P o p u l a t i o n 5 0 0 0 0 t o ? 0 () 0 0 0 ' Bic] C i t i e s a n d O um . s D e s i g n a t e d Pi ( P o p u la tio n t o 0 0 0 to 50 0 0 0 ) C itie s C o u n ty S e a ls and C en su s D e s ig n a te d P la c e s ( P o p u l a t i o n 5 0 0 0 to 10 0 0 0 ) T o w n s V il l a g e s a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n L e s s th a n 5 0001 C e n tr a l V illa g e s S a m p le d F a rm F a m ilie s S a m p le d cr G ra n d R a p i d s . i S u p e rcd y J ( P o p u la tio n F ig u r e 6 .5 .1 K aiam a ro o . •Flint!, & ^D etroit vtfifiw ‘Ann Aitior M o r e t h a n 1 .0 0 0 0 0 0 ) S h o p p in g tra v e l m o d e l o f fa rm fa m ilie s s a m p le d fo r flo o r c o v e r in g s to r e . Rural Non-Farm Families' Shopping Travel: • Floor Covering Store S o u th -c en tra l M ichigan, 1983 ( C e n tra l C itie s ( P o p u la tio n : 5 0 .0 0 0 to 2 00,000) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 10,000 to 50.000) C itie s , C o u n ty S e a ts , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 5 ,0 0 0 to 10.000) T o w n s . V illag es, a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : L e s s th a n 5,000) C e n tra l V illa g e s S a m p le d N o n - F a r m F a m ilie s S a m p le d G rand R apid s (S u p e r c ity ( P o p u la tio n : M o re th a n 1,000,000) F ig u r e 6 .5 ,2 S h o p p in g travel m o d e l o f n o n -fa r m fa m ilies s a m p le d for flo o r c o v e r in g sto r e . 280 Factors Related to Farmers' Selection of Floor Covering Stores in C ertain C entral Places E d u c a tio n F arm C o n s o lid a tio n L e n g th o f R e s id e n c y o n th e F arm T r io s p e r W e e k F a rm S iz e A ge T y p e s o f F a r m in g C o n v e n ie n c e D is ta n c e o f S h o p p in g A ttr a c tiv e n e s s o f th e M ark et M oney F u ll T im e o r P a r t T im e F a r m in g Save C h a n g e to S p e c ia liz a tio n T i m e o f F a r m 's A u t o m a t io n o o° - 28 .50 1.00 t o o > * > 0.00 F ig u r e 6 .5 .3 C h i - S a u a r e p ro b a b ility sc a le : F a c to r s c la ssifie d b e tw e e n a * 0 0 a n d 0 0 5 imply s ta tis tic a lly s ig n ific a n t a s s o c ia tio n s w ith th e s e le c tio n o t flo o r c o v e rin g s to r e s , a n d th e f a c to r s c la s s if ie d D etw e en a * 0 .0 5 to t.0 0 d o n o t h a v e a s ig n if ic a n t association w ith th e s e le c tio n o f flo o r c o v e rin g s to re s Factors Related to Non-Farmers' Selection of Floor Covering Stores in C ertain C entral Places L e n g th o f R e s id e n c y T r ip s p e r W e e k D ista n c e S a v e M oney S a v e Tim e P r ic e o f G o o d s C o n v e n ie n c e o f S h o p p in g A ttr a c tiv e n e s s o f th e M arket .50 1.00 > « > 0.00 F ig u r e 6 .5 .4 C h t - S o u a r e p ro b a b ility s c a le : F a c to r s c la s s if ie d b e tw e e n a ■ 0 0 a n d 0 .0 5 im ply s ta tis tic a lly s ig n ific a n t a s s o c ia tio n s w ith th e s e le c tio n o f Moor c o v e r in g s to r e s : a n d th e f a c to r s c la s s ifie d b e tw e e n a * 0 .0 5 to 1 0 0 d o n o t n a v e a s ig n ific a n t a s s o c ia tio n w ith th e s e le c tio n o f flo o r c o v e n n g s to re s . 281 arid 6.4.2). It was found that more educated nonfarm families outshopped for floor covering. Ed ucation was not a statistically significant factor of store selection for farmers, but there was a preference for outshopping among more highly educat ed farm families. Identification of the floor covering store as a specialized function was c l a s s i ­ fied in the .20-.10 column of probability of association for both farm and nonfarm families with fairly strong phicoefficients 6.4.2). (Figures 6.5.3 and 6.5.4 and Tables 6.4.1 and This id entification was influential in encouraging outshop pin g for floor covering among some of the rural farm and nonfarm families. The income level of farm and nonfarm families was not sta tistically significant in their choices of a floor co ver ing store (Figures 6.6.3 and 6.6.4), but there was a gr eat er preference for outshopping among higher income fam ­ ilies that was stronger in the case of nonfarm families. There was no statist ic all y significant association between the frequency of trips and store choice of farm and non-farm families due to the great amount of outshopping among mobile and more mobile people. less But there was slightly more pa tro niz ati on of local stores by less mobile rural families. The future of floor covering stores may continue to be stable in first order and second order villages, strength of the trend among rural this function is more but the families for outshopping likely to lead to a decline in such 282 stores particularly, in second order villages. The c o n ­ siderable range of the floor covering shopping model nonfarmers, implies for that future growth of the nonfarm pop ­ ulation will be disc ou ra gi ng for local floor covering stores. Jewelry stores, tion, as another second order village fu n c ­ had mean and standard deviations of farm families' shopping travel milea ge that were similar to the shopping models for floor coveri ng stores families, (Table 6.3). For nonfarm jewelry shopping travel was much shorter than for floor coverings. Meantime, the means and standard d e v i a ­ tions of shopping mileage travelled for jewelry stores, was similar among both farm and nonfarm families The pe rcentage of local for farm families, (Table 6.3). jewelry inshopping was 9.5 percent and 6.25 percent for nonfarm families which implied slightly more patronage of local jewelers among farmers than nonfarmers, shopping by both groups. but over 90 percent out- Figures 6.6.1 and 6.6.2 show the jewelry shopping patterns of rural families and indicate the extent to w h i c h villa ge jewelers are being outshopped to the benefit of jewelers in urban central places. These o b s e r ­ vations clearly show the jewelry store to be a spatially flexible function. Chi-sq ua re tests showed that education and length of residency were st atistic ally significant in the jewelry shopping be havior of farm families, but there were no 283 Farmers' Shopping Travel: Jewelry Store S o u th -ce n tra l M ichigan, 1983 C e n tr a l C itie s ( P o p u la tio n 5 0 0 0 0 to 2 0 0 000* B ig C i t i e s a n d C e n s u s D e s i g n a t e d P l a n t 's ( P o p u l a t i o n 10 0 0 0 t o 5 0 0 0 0 1 C itie s C o u n ty S e a ts a n d C e n s u s D e s ig n a te d P la c e s (P o p u la tio n 5 0 0 0 to 10 0 0 0 * T o w n s V il l a g e s a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n L o ss th a n 5 0 00) G ra n d R a p id s C e n tr a l V illa g e s S a m p le d I F a rm F a m ilie s S a m p le d S u p e rc ity (P o p u la tio n F ig u r e 6 .6 .1 M o r e t h a n 1 ,0 0 0 0 0 0 ) S h o p p in g travel m o d e l o f farm fa m ilies sa m p le d fo r jew elry sto r e . Rural Non-Farm Families' Shopping Travel: • Jewelry Store S o u th -ce n tra l M ichigan, 1983 ( C e n tr a l C itie s (P o p u la tio n : 5 0 ,0 0 0 to 200 .0 0 0 ) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s (P o p u la tio n : 10 .0 0 0 to 5 0 .000) C itie s . C o u n ty S e a ts , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 5 ,0 0 0 to 10,000) T o w n s , V illag e s, a n d C e n s u s D e s ig n a te d P la c e s (P o p u la tio n : L e s s t h a n 5,000) C e n tr a l V illa g e s S a m p le d N o n - F a r m F a m ilie s S a m p le d * | S u p e r c ity f ( P o p u la tio n : M o re t h a n 1,000.000) F ig u r e 6 .6 .2 A G rand R a p id s . I K alam a zo o . S h o p p in g travel m o d e l o f n o n -farm fa m ilies s a m p le d fo r jew elry sto r e . A - «Flint( .D e t r o it j p P 'A n n Arbor 284 significant factors to explain the jewelry shopping p r e ­ ferences of rural nonfarm families 6.6.4). (Figures 6.6.3 and A great amount of jewelry outshopping was done by rural nonfarm families who found urban centers more a t t r a c ­ tive than local markets. market" The factors of "attractiveness of and education level, which were those most closely associated with jewelry shopping among nonfarm families, were sorted at the significance level of .50 - .20 with stronger coefficients of strength than other factors 6.6.4). In fact, (Figure there was a 50-80 percent probability of association between these factors and the selection of a central place offering a jewelry store. statistically significant, While this was not it showed a tendency toward more outshopping by highly educated nonfarm families than less educated ones. Among farm families, families were more also, the more educated likely to outshop the local jewelry stores. On the factor of residency, farm families with more years of local residency were more likely to patronize the local jewelry stores in the central villages than farmers with fewer years of local residency. therefore, that more years of residency and less education among farm families shopping). It can be concluded, favored local jewelry shopping Moreover, (in­ full-time farmers showed some ten ­ dency for jewelry inshopping, while part-time farmers a l ­ most always outshopped the local jewelry stores. For farm 285 Factors Related to Farmers' Selection of Jewelry Stores in C e r t a i n C e n t r a l P l a c e s T r ip s p e r W e e k Age C o n v e n ie n c e o f S h o p p in g T im e o f F a r m s A u t o m a t i o n T y p e s o f F a r m in g A ttr a c tiv e n e s s D is ta n c e o f th e M arket C h a n g e to S p e c ia liz a tio n F arm C o n s o lid a tio n P r ic e o f G o o d s S p e c ia liz e d G o o d s a n d S e r v ic e s S a v e T im e 1.00 2 g; ioo>«>o.oo F i g u r e 0 .6 .3 c m - S q u a r e p ro b a b ility sc a le : Factors c la ssifie d b e t w e e n a =■ 0 .0 a n d 0.0 5 im ply s ta tis tic a lly s ig n ific a n t a s s o c ia tio n s w ith th e s e le c tio n o f tew eiry s to re s : a n d th e f a c to rs c la ssifie d b e tw e e n a = 0 05 to 1 0 0 a o n o t nave a sig n ific a n t a s s o c ia tio n w ith th e s e le c tio n o f lew eiry s to re s Factors Related to Non-Farmers' Selection of Jewelry Stores in C e r t a i n C e n t r a l P l a c e s Incom e Age : : : : Length o f R esidency Education Trips per Week S p ecia lized G oods an d S erv ices Distance • Attractiveness o f th e Market Price of G o o d s : : C o n v en ie n c e o f S h o p p in g S a v e Time S a v e M oney 2 §1 1.00 1.00>«>0.00 F ig u r e 6 .6.4 c h i - S q u a r e pro b ab ility sc a le : F a c to rs c la ssifie d b e tw e e n a => 0 .0 a n d 0 .0 5 im ply s ta tis tic a lly s ig n if ic a n t a s s o c ia tio n s w ith tn e se le c tio n o f tew eiry s to re s : a n d th e f a c to r s c la ssifie d b e tw e e n a - 0 .0 5 to 1.00 d o n o t h a v e a s ig n ific a n t a s s o c ia tio n w ith th e s e le c tio n o f tew eiry sto res. 286 families this was a statistically significant factor. As long as the part-time farmers and nonfarm residents continue to increase on the rural landscape of the study area, local jewelry stores can be expected to decline. Income factor levels were not a statistically significant in the jewelry shopping patterns of rural (Figures 6.6.3 and 6.6.4), families but there was a tendency showing that higher income families were more likely to patronize the jewelry stores of urban centers and avoid the local ones. The fr equency of trips was also not statisticaly significant in the jewelry shopping patterns of rural ilies. As a fairly durable, shopping is occasional ity of rural non-consumable item, fam­ jewelry shopping and unrelated to the m o b i l ­ families. As for the future prospects for local jewelry stores, it is likely they will be reduced in numbers as happened in the past and may remain a typical function only in first order villages. rural families, Significant outshopping for jewelry among and par ticularly the nonfarm families, reduced the incidence of this central has function in the shop­ ping centers of local villages. D is sa ti sfa cti on with local functions among rural re s i ­ dents of second order villages in the study area, was found to be a trend that was par ticularly evident in the mid-1970s. The trend was due, in large part, to the continuous decline of farm families and an increase in nonfarm families (who 287 are more city-o rie nt ed in their s h o p p i n g ) . the tendency will favor further decline in the functions of second order villages stores. Con tinuation of such as floor covering and jewelry Retention of these functions, however, is more likely in the first order villages because of the stronger viability of first order villages. First Order Village Functions Among the sampled functions, paint and wall pa pe r stores and de partment stores were found to be typical first order villages in 1980 (Table 6.2). functions of Generally, they are functions that have not been typical or even neartypical of lower order villages. The paint and wallpaper store was c ha ra ct er iz ed by high means and standard d e v i a ­ tions in the mileage travelled by farm and nonfarm families (Table 6.3). The higher means and standard deviations in mileage travelled was observed among the rural nonfarm families (Table 6.3) paper outlets families who tended to patronize paint and w a l l ­ in urban central places more than the farm (Table 6.3.1). However, both farm and nonfarm fam­ ilies reported larger ranges of shopping travel function for this (Figures 6.7.1 and 6.7.2), which served to identify its status as a spatially flexible function. With any fu r­ ther increase of nonfarm popul at io n in the rural of the study area, landscape this function could become more flexible and in greater competi ti on with urban central places. 288 • Farmers' Shopping Travel: Paint and Wallpaper Store S o u th - c e n tr a l M ic h ig a n . 1 9 8 3 | C e n tr a l C itie s ' IP o p u l a ti o n 5 0 0 0 0 to ? 0 0 0 0 0 i B ig C i tie s a n d C e n s u s D e s i g n a te d P l a c e s ( P o p u l a t i o n 10 0 0 0 t o 5 0 0 0 0 1 C itie s C o u n ty S e a ts a n d C e n s u s D e s ig n a te d P la c e s ( P o p u l a t i o n 5 . 0 0 0 t o 10 0 0 0 ) T o w n s V illa g e s a n d C e n s u s D e s ig n a te d P la c e s ( P o p u l a t i o n L e s s t h a n 5 .0 0 0 ) C e n tr a l V illa g e s S a m p le d F a rm F a m ilie s S a m p le d G ra n d R a p id s ( S u p e rc ity ( P o p u la tio n F ig u r e 6 .7 .1 M o re th a n t S h o p p in g travel m o d e l o f farm fa m ilie s sa m p le d fo r p ain t a n d w all p a p e r sto r e. Rural Non-Farm Families' Shopping Travel: • Paint and Wallpaper Store S o u th - c e n tr a l M ic h ig a n , 1 9 8 3 (C e n tr a l C itie s ( P o p u la tio n : 5 0 ,0 0 0 to 200 ,0 0 0 ) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 10 .0 0 0 to 50,000) C itie s . C o u n ty S e a ts , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n . 5 ,0 0 0 to 10,000) T o w n s , V illa g e s, a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : L e s s th a n 5,000) C e n tr a l V illa g e s S a m p le d N o n - F a r m F a m ilie s S a m p le d G rand R ap id s k S u p e r c ity f (P o p u la tio n : M o re t h a n 1,000.000) F ig u r e 6 .7 .2 s h o p p in g travel m o d e l o f n on -farm fa m ilie s s a m p le d fo r p ain t a n d w a llp a p er sto r e . D etroit K atem aroo 289 Of the factors that were influential nonfarm families' stores, in farm and shopping models for paint and wa ll-paper price had an 80 to 90 percent pr ob ab il it y of as soc ­ iation with a fairly strong coefficient of association (Figures 6.7.3 and 6.7.4 and Tables rural consumers' 6.4.1 and 6.4.2). The price considerations were found to be re ­ lated to higher order functions that are typical order central villages. in first Farmers and nonfarmers reported that price considerations favored bypa ss in g local paint and wallpaper stores to the benefit of urban central places. Saving money was a statistically significant factor for farm families, but less important to nonfarm families, with a probability of association betwe en 70 and 80 percent (Figures 6.7.3 and 6.7.4). Both farm and nonfarm families that wanted to save money in shopping for paint and w a l l ­ papers, patronized urban central places rather than shopping at local villages. Taken together, results obtained for these two factors show that events which increase prices and/or increase concern for saving money among rural ilies can be harmful order functions ilies will for local functions, fam ­ espec ia ll y first like paint and wallp ape r because rural fam­ increasingly bypass village es tablishments to save money through the price advantages they perceive to be available in urban central places. Other statistically significant factors for farm fam­ ilies were length of residency and length of automated 290 Factors Related to Farmers' Selection of Paint and Wallpaper Stores in C ertain Central Places S p ecia lized G oods A ge and S e r v ic e s Farm C onsolidation A ttractiven ess o f the Market Full Time or Part Tim e Farming Trips per W eek T yp es of Farm ing C h a n g e to S p ecialization 1.00 .50 t oo > a > 0.00 F i g u r e 6 .7 .3 C h i - S q u a r e p r o b a b ility sc a le : F a c to rs c la ssifie d D etw e en a ■- 0.0 a n d 0 0 5 im ply s ta tis tic a lly s ig n ific a n t a s s o c ia tio n s w ith th e s e le c tio n of p a in t a n d w a llp a p e r s to re s : a n d th e f a c to r s c la s s ifie d b e tw e e n a = 0 .0 5 to I 00 a o n o t h a v e a s ig n ific a n t a s s o c ia tio n w ith th e s e le c tio n o f p a in t a n d w a llp a p e r s to re s . Factors Related to Non-Farmers' Selection of Paint and Wallpaper Stores in Certain Central Places E d ucation Length o f R esidency Sp ecia lized G o o d s and S erv ices Trips per Week A ttractiven ess o f the Market C o n v en ie n c e of Sho p p in g Sa v e M oney Save Time 1.00 70 .50 -20 .10 .05 b b P —• © t .00 > a > 0.00 F ig u r e 6 .7 .4 C h i - S q u a r e p ro b a b ility s c a le : F a c to rs c la ssifie d b e tw e e n a « 0 0 a n d 0 .0 5 im ply sta tis tic a lly s ig n ific a n t a s s o c ia tio n s w itn m e s e le c tio n of o a m t a n d w a llp a p e r s to r e s : a n d m e fa c to rs c la s s if ie d b e tw e e n a - o 05 to i .00 a o n ot n a v e a sig n ific a n t a s s o c ia tio n w itn th e 9 e ie c tio n o f p a in t a n a w a u o a o e r s to r e s 291 farming. The date of farm a ut om at io n was earlier among farm families who had resided longer in the study area. The farmers with shorter residency and co ns qu en tl y fewer years of farm operation, had also auto ma te d years of automated farming. later and had fewer Therefore, the two factors of length of residency and time spent in automated farming were sorted into the same class of significance on the tables of probability scales (Figures 6.7.3 and 6.7.4). There was a good percentage of farmers wi t h longer residency, opted for earlier farm automation, w ho patronized the paint and wallpaper stores of central villages On the other hand, who had local (inshopping). the factor of age was found to be sta ­ tistically significant among rural nonfarm families. was a greater trend to inshopping by rural, nonfarm, There elderly persons. The factor of income level was not statistically s ig ni ­ ficant in the farm families' shopping model for paint and wallpaper and outshopping was high at all income For nonfarm families, however, levels. there was a 50-80 percent probability of association b e twe en income levels and sh op ­ ping models (Figure 6.7.4), with slightly more patroniza- tion of local paint and wallp ape r stores among nonfarmers at higher income levels. On the whole, though, outshopping was so prevalent among the majori ty of nonfarmers of different income levels and most farmers, was essentially non significant. that the factor of income 292 The factor of shopping trips per week was found not to be sta tistically significant among farm or nonfarm families. Outshopping the prevalent at all local paint and wall pa per stores was very levels of mobility. However, local d i s ­ satisfaction and conside ra ti on of paint and wallpaper selection, q ua li ty and price were reported to be the most important reasons for outshopping by the rural families studied. Because paint and wallpaper petitive function, is a flexible and c o m ­ its retention in central villages will be dependent on farm and nonfarm families' future preferences in relation to regional development. Department store is another typical function at the level of first order villages. typical This high order function was in first order and second order villages remained typical (Table 4.8). in first order villages in 1950 and in 1970 and 19.80 The average range of miles travelled by farm and nonfarm families to shop the department stores was high among both groups, (Table 6.3). compared with other sampled functions Ob ser ve d standard deivations were also high among farm and nonfar m families. The greater standard deviation was ob served for nonfarm families who outshopped local depart men t stores in greater percentages than farm families but patterns of department store (Table 6.3.1), shopping for both farm and nonfarm families illustrate their strong preferences for patronizing the urban central places 293 in the study area stores (Figures 6.8.1 and 6.8.2). in rural villages are, Department thus, very flexible and sen ­ sitive to competit ion from urban center depart me nt stores. Since nonfarm families had greater d i sp atr oni zat io n of local department stores, an increase of nonfarm families will tend to encourage more outshopping. Due to local department stores' tages, they are ou tshopp ed by rural ilies for price considerations money. co mp etitive d i s a d v a n ­ farm and nonfarm f a m ­ in their efforts to save These two factors were statistically significant with high strength coefficients partment stores in shopping models for d e ­ (Figures 6.8.3 and 6.8.4). faction of farm and nonfarm families with stores that ge nerally offer fewer items, at higher prices, shoppers. The d i s s a t i s ­ local department of lesser quality, has caused their di s p a t r o ni za ti on by local The larger de partment stores of the study area's urban central places with their advantages of volume buying and ability to supply consumers with better q u ali ty goods at lower prices have proved more satisfaction to most of the area's rural families. The convenience aspect was also st at istically s i gn if i­ cant for farm families (Figure 6.8.3); it had 50-80 percent probability of association as an influential farm families' 6.8.4). shopping travel There is more factor on n o n ­ for d ep ar tm en t stores (Figure local patronage by farm families who value the convenience of local de partment stores. Nonfarm 29^ • Farmers' Shopping Travel: D epartm ent Store S o u th - c e n tr a l M ic h ig a n , 1 9 8 3 I C e n tr a l C itie s ( P o p u l a t i o n 5 0 0 0 0 t o 2 0 0 OOOi B ig C i t i e s a n d C e n s u s D e s i g n a t e d P l a c e s ( P o p u l a t i o n 10 0 0 0 t o 5 0 0 0 0 ) C itie s C o u n ty S e a ts a n d C e n s u s D e s ig n a te d P la c e s ( P o p u l a t i o n 5 .0 0 0 t o 10 0 0 0 ) T o w n s V illa g e s a n d C e n s u s D e s ig n a te d P la c e s ( P o p u l a t i o n L e s s th a n 5 0001 C e n tr a l V illa g e s S a m p le d F a r m F a m i/re s S a m p f e d G ra n d R a p id s ( S u p e r c ity ( P o p u la tio n F ig u r e 6.8.1 D etro it M o re th a n t . 0 00.000) S h o p p in g tra v e l m o d e l o f fa rm fa m ilie s s a m p le d fo r d e p a r t m e n t s to r e . Rural Non-Farm Fam ilies' Shopping Travel: • D epartm ent Store S o u th - c e n t r a l M ic h ig a n , 1 9 8 3 i C e n tr a l C itie s ' ( P o p u la tio n : 5 0 ,0 0 0 to 2 00.000) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 10,000 to 50.000) C itie s , C o u n ty S e a ts , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 5 ,0 0 0 to 10.000) T o w n s , V illa g e s, a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : L e s s th a n 5,000) C e n tr a l V illa g e s S a m p le d N o n - F a r m F a m ilie s S a m p le d Grand R apid s (S u p e r c ity ( P o p u la tio n : M o re th a n 1,000.000) F ig u r e 6 .8 .2 S h o p p in g travel m o d e l o f n on -farm fa m ilie s s a m p le d t o r d e p a r tm e n t sto r e . D etroit 295 Factors Related to Farmers' Selection of Department Stores in C e r t a i n C e n t r a l P la c e s A ge T r ip s p e r W e e k T y p e s o l F a r m in g F arm C o n s o lid a tio n C hange F u ll T im e o r P a r t T im e F a r m in g i i § to S p e c i a l i z a t i o n T im e o f F a r m 's A u t o m a t i o n S p e c ia liz e d G o o d s a n d S e r v ic e A ttr a c tiv e n e s s o f t h e M a r k e t S a v e T im e f SlllSli 2S .5 0 1.00 > c r > 0.00 F ig u r e 6 .8 .3 Chi - S q u a r e p ro b a b ility s c a le . F a c to rs c la ssifie d b e tw e e n a = 0 0 an d 0 0 5 im ply s ta tis tic a lly s ig n ific a n t a s s o c ia tio n s w ith th e s e le c tio n o f d e p a r tm e n t s to re s : a n d th e f a c to r s c la ssifie d b e tw e e n a = 0 05 to t.0 0 d o n o t n av e a sig n ific an t a s s o c ia tio n w ith th e s e le c tio n o f d e p a rtm e n t s to re s . Factors Related to Non-Farmers' Selection of Department Stores in C e r t a i n C e n t r a l P l a c e s In com e L e n g th o f R e s id e n c y E d u c a tio n A ge A ttr a c tiv e n e s s o f C o n v e n ie n c e o f S h o p p in g th e M arket S a v e T im e T r ip s o e r W e e k D is ta n c e 1.00 .70 .50 .20 1.00 > a > 0.00 F i g u r e 6 .8 .4 C h i - S q u a r e p ro b a b ility s c a le : F a c to r s c la ssifie d b e tw e e n or = 0 .0 an d 0 .0 5 imply s ta tis tic a lly s ig n ific a n t a s s o c ia tio n s w ith th e s e le c tio n o f d e p a r tm e n t sto re s; a n d th e f a c to r s c la ssifie d b e tw e e n a = 0 .0 5 to 1.00 d o n o t n a v e a s ig n ific a n t a s s o c ia tio n w ith th e s e le c tio n o f d e p a r tm e n t s to re s . .1 0 .0 5 o 000 .70 1.00 t i 1 i1 ili 296 families' co nve ni enc e concerns are directed mostly toward the selection of department stores in urban central places. The factor of income was not statistically significant in rural farm and nonfa rm families' partment stores shopping model (Figures 6.8.3 and 6.8.4), for d e ­ but there was some tendency toward outshopping by higher income farm and nonfarm families. In freguency of shopping per week, neither statistical evident. Therefore, shopping models significance nor any tendencies were income level had little influence on for de partment stores, while differences of mo bility among rural families had no effect on outshopping or inshopping. In conclusion, rural families' preference for shopping at urban de par tme nt stores with greater selection and better prices, was more influential come and mobility. Local department stores, order village function, order villages than other factors such as in­ as a first may remain at the level of first in the coming years, the extent of any further declines but this will depend on in farms and farm families and future increaes of nonfarm families in the study area. The first order villages with their relatively strong viab ili ty among the classes of central villages have had smaller losses in their retail (Chapter Five). However, functions over the study time due to the increase of rural n o n ­ farm families who prefer shopping in urban central places, 297 first order village functions including paint and wallpaper stores and departm ent stores, may become atypical to first order villages and be ranked as town and city level f u n c ­ tions . Town and City Level Functions The functions of family clothing, automotive dealers, and shoe stores ev idenced considerable instability as typical functions of particular clases of central villages over the study time. There was also considerable evidence that rural families pref err ed to patronize urban area es tab ­ lishments for these functions. in rural villages, and city levels. Although sometimes appearing these functions were stable only at town Due to the peculiarities of each function, they are discussed separ at el y here. The family cl ot hi ng store function increased in f r e ­ quency of functional (Table 5.7), units in the central villages studied but its existence as a typical function in di f­ ferent classes of central villages was very unstable over the study time near typical (Table 4.8). For instance, only in the third order villages, typical only in the second order villages become typical (Table 4.8). in 1950 it was it was near in 1970 and had in third and fourth order villages by 1980 This implies that the present family clothing stores in lower order villages have a somewhat shakey viability that does not bode well - for their continued existence 298 in those villages, pa rti cul arl y because this function is very competitive. The average range of farm and nonfarm families' ping travel for family cl othing store was high compared with other sampled functions 6.9.2). shop­ (Table 6.3 and Figures 6.9.1 and The very small percentage of inshopping cent for farmers, (5.9 pe r ­ 2.3 percent for nonfarm families)- for family clo thing implied that this function was highly flexible and was a town or city level function due to the considerable willingn es s of rural travel families' preference to to urban central places to shop for family clothing (Table 6.3.1). The grea ter standard de viation for nonfarm families compared with farm families that nonfarmers outshop the local (Table 6.3) indicates family clothing stores more than the farm famil ies by 97.7 percent to 94.1 percent, respectively (Table 6.3.1). With future increases nonfarm po pulation of the study area's rural elimina ti on of local family clothing stores in the landscape, is probably unavoidable. The rural farm and nonfarm families' prices and saving money were of urban central places' influential concerns about in their patronage family clothing stores. Saving money was found to be st at istically significant among both farm and nonfarm families factor of price was families' (Figures 6.9.3 and 6.9.4). statistically significant for the farm shopping model of family clothing stores 6.9.3), but it was The (Figure less statistically significant with 80 299 Farmers' Shop p in g Travel: Family C lothing Store S o u t h - c e n t r a l M ic h ig a n , 1 9 8 3 | C e n lr a i C itie s ( P o p u l a t i o n 5 0 0 0 0 t o 2 0 0 OOOl B ig C ilie s ancl C e n s u s D e s i g n a te d P l a c e s i P o p u l a l i o n 10 0 0 0 t o 5 0 0 0 0 ! C itie s C o u n t y S e a l s a n d C e n s u s D e s ig n a te d P la c e s ( P o p u l a t i o n 5 0 0 0 t o 1 0 OOOi T o w n s V il l a g e s a n d C e n s u s D e s ig n a te d P la c e s ( P o p u l a t i o n L e s s t h a n 5 OOOi C e n tr a l V illa g e s S a m p le d F a rm F a m ilie s S a m p le d Grand R ap id s . .D e t r o it > S u p e r c ily ( P o p u la tio n F ig u r e 6 .9 .1 M o r e t h a n 1 .0 0 0 ,0 0 0 ) S h o p p i n g tra v e l m o d e l o f fa rm fa m ilie s s a m p l e d f o r fa m ily c l o th in g s to r e . Rural N on-Farm Fam ilies' S hopping Travel: • Family C lothing S tore S o u th - c e n tr a l M ic h ig a n , 1 9 8 3 ( C e n tra l C itie s ( P o p u la tio n : 5 0 ,0 0 0 to 20 0 ,0 0 0 ) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s (P o p u la tio n : 10 ,0 0 0 to 5 0 ,000) C itie s, C o u n ty S e a ts , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 5 ,0 0 0 to 10,000) T o w n s , V illag es, a n d C e n s u s D e s ig n a te d P la c e s (P o p u la tio n : L e s s t h a n 5,0 0 0 ) C e n tra l V illa g e s S a m p le d N o n - F a r m F a m ilie s S a m p le d G rand R ap id s i S u p e r c ity f ( P o p u la tio n : M o re th a n 1,000,000) F ig u r e 6 .9 .2 S h o p p in g travel m o d e l o f non -farm fa m ilies s a m p le d fo r fam ily c lo t h in g sto r e . Detroit 300 Factors Related to Farmers' Selection of Family Clothing Stores in C e r t a i n C e n t r a l P l a c e s Length of R esidency on the Farm. Trips per W eek T yp es of Farming S p ecia lized G o o d s and Services Farm S iz e C h a n g e to Specialization Save Time Farm C o n so lid a tio n A ttractiven ess o f the Market Tim e of Farm's Autom ation 1.00 .7 0 .20 .5 0 1.00 > <* > o © ® - 2S 0.00 F ig u r e 6 .9 .3 C h i - S a u a r e p ro b ab ility sc a le : F a c to r s c la ssifie d b e tw e e n a * 0 .0 a n d 0.0 5 im ply s ta tis tic a lly sig n ific a n t a s s o c ia tio n s w ith th e se le c tio n o f fam ily c lo th in g s to r e s : a n d th e fa c to rs c la ssifie d b e tw e e n a = 0.05 to 1.00 d o n o t h a v e a sig n ific a n t a s s o c ia tio n w ith th e s e le c tio n o f fam ily clo th in g sto re s Factors Related to Non-Farmers' Selection of Family Clothing Stores in C e r t a i n C e n t r a l P l a c e s Age Trips per Week C o n v en ie n c e o f S hop ping D istance 1.00 70 .5 0 .2 0 1.00 > a > 0.00 F ig u r e 6 .9 .4 C h i- S o u a r e p ro b a b ility sc a le : F a c to rs c la s s if ie d b e tw e e n a * 0 .0 a n d 0 .0 5 im ply sta tis tic a lly s ig n ific a n t a s s o c ia tio n s w ith th e s e le c tio n o f fam ily c lo th in g s to re s : a n d th e f a c to r s c la ssifie d b e tw e e n a > 0 .0 5 to 1.00 d o n o t h a v e a s ig n ific a n t a s s o c ia tio n w ith th e s e le c tio n o f fam ily clo th in g sto re s. .1 0 .0 5 o o ® - 28 301 percent to 90 percent p robability of association 6.9.4) for nonfarm families. (Tables 6.4.1 and 6.4.2) and nonfarm families. (Figure Strong phi-coefficients were obtained for both rural Thus, farm price can be considered an in­ fluential factor in family clothing store shopping models for rural families of the study area. and saving money among rural shopping in the urban central Concerns about price families encouraged more outplaces at the cost of central villages. The factor of full-time or part-time farming was also significant for the rural clothing shopping farm families' (Figure 6.7.3 and Table model of family 6.9.2). A greater propor ti on of full-time farmers than part-time farmers in­ shopp ed the local family clothing stores. tion of these local The patroniza- stores by some full-time farmers may be related to a lower conce rn for fashion and style than many part-time farmers who work in the cities. However, the ma jority of farm families and all of the part-time farm families outshopped the local family clothing stores for the previously me ntioned factors of price and money saving c o n ­ siderations. Future increases in part-time farming in the study area will tend to encourage more dispatronization of local family cl ot hi ng stores to the benefit of these stores in the urban central places. Consider in g family clothing as a specialized function helped to influence the shopping model for rural families, 302 was found to have 90-95 percent of pro ba bil ity of a s so c i a ­ tion (Figure 6.9.4) 6.4.2). with a strong phi-c oe ffi ci ent This factor was less significant for farm families at 30-50 percent of probability of as so ciation 6.9.3) (Table and a moderate p h i-c oe ffi ci ent (Figure (Table 6.4.1). Thus, the specialization of family clothin g stores at the urban central places has been an influential ilies' outshopping. factor of rural It was more influential fam ­ in the shop­ ping behavior of nonfarm families who tend to be more cityoriented in their shopping than farm families. The income factor had only a low probability of a ss oc ­ iation with the shopping model families for rural farm and nonfarm (Figures 6.9.3 and 6.9.4). But, the coefficient of strength of association was mo de r a t e l y strong and 6.4.2), (Table 6.4.1 so there was a prefer enc e for outshopping among the higher income farm and nonfar m families. For mobility, there was no statistically significant association between their weekly shopping trips and the shopping models of family clothing stores (Figures 6.9.3 and 6.9.4). There was not even any preference for ou ts hopping by more mobile over the less mobile ones. This means that ou ts hopping for family clothing stores in urban centers was dominant at all levels of mobility. Family clothing stores are a town and city level tion which was func ­ locally di sp at ron ize d by the farm and nonfarm families of the study area. Lim it ati on s on variety and 303 quality and the higher prices of local family clothing increased the dissatisfations of rural families and e n ­ couraged outshopping. outshopping of local The nonfarm families did even more family clothing stores due to their city ties. Automotive dealers, with a high location coefficient (Table 6.2), were a high order function in central villages over the study time. They appeared as a nontypical in central villages in 1970 and were retained in 1980 (Tables A . 4, A . 5, A .6 and 6.2) as a nontypical function function. The failure of automotive dealers to become a typical tion in any class of central villages func ­ implied that the urban automotive dealers have been responsive to the needs of the rural families of study area. There was con siderable v a r i a ­ tion in the shopping models of farm and nonfarm families for automotive dealers. The average mean shopping travel automotive dealers was fairly low among farm families, was high among nonfarm families The percentage of rural to but (Table 6.3). farm families who supported local automotive dealers was much greater than the rural nonfarm families (Table 6.3.1) and there was an extremely high standard de viation of the rural nonfarm families' travel mileage among all the sampled functions This implied that not only were rural supportive of local (Table 6.3). farm families more automotive dealers, but nonfarm fa m­ ilies travelled much greater distances to automotive dealers 304 in large urban central places, Detroit partic ula rly the supercity of (Figures 6.10.1 and 6.10.2). One of the reasons for these differences was related to the farmers tendency to do their own repairs w hi ch reduced their need to visit the more remote urban centers. N on fa rm families were concerned with both sales and services at the automotive dealers' shops. Most of these families had two private cars and they were very tied to city automotive dealers. motive dealer was flexible The function of au t o ­ in regard to farm families' travel models and was ex tremely flexible in regard to n o n ­ farm families' travel models toward automotive dealers. presence of automotive dealers, as only a nontypical tion in fourth and fifth order villages is evidence of their unstable situation. tion had a large location co ef fi ci en t in 1980 The fu n c ­ (Table 6.2) Because this func ­ (Table 6.2), co nsidered a flexible or competi ti ve function, it was particularly among nonfarm families. Among the factors influencing the shopping or visiting model of rural farm and n o nf ar m families for automotive dealers, distance was statistically important with a strong coefficient of association (Figures 6.10.3 and 6.10.4). Distance was more statis ti ca ll y significant among farm fam­ ilies than nonfarm families Tables 6.4.1 and 6.4.2) preferences (Figures 6.10.3 and 6.10.4 and for reasons related to farmers' for shorter travel distances and their ability to do their auto repairs themselves at their farms. Time 305 Farmers' Shopping Travel: A u tom otive D ealer S o u th - c e n tr a l M ic h ig a n , 1 9 8 3 ( C e n tra l O lio s ( P o p u la tio n 50 0 0 0 to 2 0 0 0 0 0 1 B ig C itie s a n d C e n s u s D e s i g n a te d P ( P o p u l a t i o n 10 0 0 0 t o 5 0 OOOi C itie s C o u n ty S e a ts a n d C e n s u s D e s ig n a te d P la c e s ( P o p u l a t i o n 5 0 0 0 t o lO O O Oi T o w n s V illa g e s a n d C e n s u s D e s ig n a te d P la c e s ( P o p u l a t i o n L e s s t h a n 5 .0 0 0 i C e n tr a l V illa g e s S a m p le d F a rm F a m ilie s S a m p le d G ra n d R a p id s * D e tro it | S u p e rc ily '( P o p u l a t i o n F ig u r e 6 .1 0 .1 M o r e t h a n 1 .0 0 0 0 0 0 ) S h o p p in g tra v e l m o d e l o f fa rm fa m ilie s s a m p le d fo r a u to m o tiv e d e a l e r Rural Non-Farm Fam ilies' Shop p in g Travel: • A utom obile D ealer S o u th - c e n tr a l M ic h ig a n , 1 9 8 3 i C e n tra l C itie s ' ( P o p u la tio n : 5 0 .0 0 0 to 2 00.000) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 10.000 to 50.000) C itie s . C o u n ty S e a ls , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 5 .0 0 0 to 10.000) T o w n s . V illa g e s, a n d C e n s u s D e s ig n a te d P la c e s (P o p u la tio n : L e s s t h a n 5,000) C e n tr a l V illa g e s S a m p le d N o n - F a r m F a m ilie s S a m p le d G ra n d R a p id s . (S u p e r c ity ( P o p u la tio n : M o re th a n 1.000.000) F ig u r e 6 .1 0 .2 S h o p p in g travel m o d e l o f non -farm fa m ilie s s a m p le d for a u to m o tiv e d ea ler . .D e t r o it Arbor 306 Factors R elated to Farmers' S election of A u tom otive D ealers E ducation Types o f Farm ing Trips per Week A ttractiven ess o f th e Market Farm C onsolidation p P D istance in C e r t a i n C e n t r a l P la c e s o E o 5 no 0 u. u<. _ _t> C h ange to Specialization t oo > « > o o° .20 .50 - 2 8 0.06 F i g u r e 6 . 1 0 .3 C h i - S q u a r e p ro b a b ility sc a le : F a c to rs c la ssifie d b e tw e e n a * 0 .0 a n d 0 0 5 im ply s ta tis tic a lly s ig n if ic a n t a s s o c ia tio n s w ith tn e s e le c tio n of a u to m o tiv e d e a le r s ; a n d t n e fa c to rs c la s s ifie d b e tw e e n a = 0 0 5 lo t 00 d o n o t h a v e a sig n ific a n t a s s o c ia tio n w ith th e s e le c tio n o f a u to m o tiv e d e a le rs. F actors R elated to N on-Farm ers' S electio n of Autom otive D ealers in C e r t a i n C e n t r a l P l a c e s Length of R esid en cy Trios per Week • • ; A ttractiveness of the Market j Save M oney : Price o f G o o d s A ge C o n v en ien ce of S hop ping O o ’> £ (/) Education <0 V) O O CP ■D M "s u a cn Save Time £ o c a> u «7) 5 / •70 50 .20 1.00 > o > 0.00 F ig u r e 6 .1 0 .4 C h i - S a u a r e p ro b a b ility sc a le : F ac to rs c la ssifie d b e tw e e n a « 0 0 a n d 0 .0 5 im ply s ta tis tic a lly s ig n ific a n t a s s o c ia tio n s w ith m e s e le c tio n o f a u to m o tiv e d e a le r s , a n d th e f a c to rs c la s s ifie d b e tw e e n a = 0 .0 5 to 1.00 d o n o t h a v e a sig n ific a n t a s s o c ia tio n w ith th e s e le c tio n o f a u to m o tiv e a e a ie rs 10 .05 b o o “ 28 3 07 savings and convenience were also found significant in shop ­ ping models of farm families for automotive dealers and are compleme nt ary factors to distance considerations among the farm families. Length of residency was a statistically significant factor in the automotive shopping travel of farm families (Figure 6.10.3). A greater percentage of farm fam­ ilies with longer residency patronized local automotive dealers than farmers with shorter residency. however, On the whole, urban patronization was most frequent at all of residency. Full-time or part-time farming had 90-95 p e r ­ cent of probability of association coefficient) levels (with a strong phi- with the shopping models of farm families for automotive dealers (Figure 6.10.3 and Table 6.4.1). A greater percentage of full-time farmers than part-time farmers patronized local automotive dealers. Thus, an increase of part-time farming is likely to cause increased local dispatronization. The factor of income was statistically significant in the shopping model of nonfarm families fact, (Figure 6.10.4). In there was a significant trend toward out sh op pi ng by higher income nonfarm families who visited an automotive dealer in a city to buy their new cars. Income was not sta tistically significant for farm families' shopping travel toward automotive dealers which meant that farmers of all income levels have similar shopping travel models for 308 automotive dealers. such as distance, Therefore, convenience, the other factors discussed etc., were influential. Shopping trips per week was not statistically s ig ni ­ ficant or strongly as sociated with the farm and nonfarm fam­ ilies' visits to au tomotive dealers, but there was some slight preference for outshopping among more mobile farm and nonfar m families. Spec ula tin g on the future of automotive dealers, should be noted that with future decreases families, in farms and farm and increases of rural nonfarm families with their closer ties to the city, in the study area, local for this function will be likely to decline. may be the final Shoe stores, highest 1980 support Outshopping solution. another town and city function, had the location coefficient among the sampled functions for (Table 6.2) and has been unstable as a typical of a certai n class of central village in the past 4.8). it Its nontypical function (Table nature in the fifth order villages in 1980 par tic ul ar ly implied a nonviable status in the central villages rural studied. farm There was only a small percentage of (10.1 percent) who pa tro niz ed local and nonfarm families (2.4 percent) shoe stores in the study area (Table 6.3.1). The pre se nc e of very high means and standard d e ­ viations in range of travel toward shoe stores among the farm and nonfar m families indicated that this function is highly flexible and competitive (Table 6.3). The shopping 30 9 travel models of both groups revealed significant p r e f e r ­ ences for shoe shopping in the urban central places (Figures 6.11.1 and 6.11.2). The greater urban p a t r o n i z a ­ tion of nonfarm families compared with farm families, im­ plies that increases in the nonfarm population of the re ­ gion will further decrease the already small proportion of local residents who support this function at the village level. Therefore, the elimination of shoe stores from low order villages will be unavoidable. The avilability of the shoe store function only in urban central places seems to be the only probable outcome. The percep ti on of shoe stores as a specialized f u n c ­ tion, was important ilies to outshop the in the trend for farm and nonfarm fam ­ local shoe store. In fact, there was a st at istically significant association betwe en the perception of shoes as specialized goods and the selection of a certain shoe store in a pa rticular central place by both farm and nonfarm families (Figures 6.11.3 and 6.11.4). The d e v e l o p ­ ment of the shoe industry toward greater specialization will further encourage shoe shopping at urban central places by the farm and nonfar m families of the study area. The price of goods and saving money were also s t a t i s ­ tically significant factors encouraging an outshopping p a t ­ tern among farm families (Figure 6.11.3). While prices and money saving con siderations were not statistically s i gn i f i ­ cant for nonfarm families, there was a moderate coefficient 310 Farmers' Shopping Travel: S h o e Store S o u th - c e n tr a l M ic h ig a n . 1 9 8 3 C e n tr a l C itie s ( P o p u l a t i o n 5 0 0 0 0 t o POO 0 0 0 ) B i g C i t i e s a n d C e n s u s D e s i g n a t e d Pi; i P o p u l a t i o n 10 0 0 0 t o 5 0 0 0 0 ) C itie s C o u n ty S e a ts and C ensus D e s ig n a te d P la c e s ( P o p u la tio n 5 0 0 0 to 1 0 0 0 0 ) T o w n s V illa g e s a n d C e n s u s D e s ig n a te d P la c e s ( P o p u l a t i o n L e s s t h a n 5 .0 0 0 ) C e n tr a l V illa g e s S a m p le d F a rm F a m ilie s S a m p le d G ra n d R a p id s ( S u p e rc ity (P o p u la tio n Figure 6.11.1 - D e tr o it M o r e t h a n 1 .0 0 0 0001 Shopping travel model of farm families sampled for shoe store. Rural Non-Farm Fam ilies' Shopping Travel S h o e S tore S o u th - c e n t r a l M ic h ig a n , 1 9 8 3 C e n tr a l C itie s ( P o p u la tio n : 5 0 ,0 0 0 to 2 00.000) B ig C itie s , a n d C e n s u s D e s ig n a te d P la c e s ( P o p u la tio n : 10,000 to 5 0 ,000) C itie s , C o u n ty S e a ts , a n d C e n s u s D e s ig n a te d P la c e s (P o p u la tio n : 5 ,0 0 0 to 10,000) T o w n s , V illa g e s, a n d C e n s u s D e s ig n a te d P la c e s (P o p u la tio n : L e s s than 5,000) C e n tr a l V illa g e s S a m p le d N o n - F a r m F a m ilie s S a m p le d Grand R ap id s i S u p e rc ity f (P o p u la tio n : M o re t h a n 1,000,000) F ig u r e 6 .1 1 .2 S h o p p in g travel m o d e l for n o n -fa r m fa m ilies s a m p le d for s h o e sto r e . Detroit 311 Factors Related to Farmers' S election of S h oe S tores in C e r t a i n C e n t r a l P l a c e s E ducation Save M oney Trips par W eek Types of Farm ing Full Tim e or Pari Time Farming C h ange to Sp e c ia li za tio n Oistance Farm C on solidation S a v e Time .70 1.00 .50 Price of Goods A ge .20 e 1 00 > a > 0.00 F ig u r e 0 .1 1 .3 c r ii- S a u a r e oroDab a > 0-00 F ig u re 6 .1 1 .4 C h i - S o u a r e p ro b a b ility s c a le - F a c to rs c la ssifie d o e tw e e n a » 0 .0 a n d 0 0 5 im p ly sta tis tic a lly s ig n if ic a n t a s s o c ia tio n s w ith m e s e le c tio n o f s h o e s to re s : a n d th e f a c to r s c la ssifie d b e tw e e n a * 0 .0 5 to 1.00 d o n o t n a v e a sig n ific a n t a s s o c ia tio n w ith th e s e le c tio n o f s h o e s to re s . s ; 312 of strength and 50 to 80 percent probability of association between price and money saving considerations to indicate these factors had some influence in the shoe shopping p a t ­ tern of rural nonfarm families (Figure 6.11.4 and Table 6.2.4) . Shopping convenience and attractiveness of the market were also significant influences on farm and nonfarm f am ­ ilies' shoe shopping 6.4.1 and 6.4.2). (Figures 6.11.3 and 6.11.4 and Tables The factor of attractiveness of the m a r ­ ket tended to encourage outshopping for shoes. Shopping convenience had some influence on inshopping among farm families. The convenience factor among nonfarm families was interpreted to mean the convenience of shoe shopping of the urban central shoe stores. in one places— without any reference to local This implies that nonfarmers are more city- oriented in their shoe shopping than farmers, to the extent that they almost fail to perceive that a local shoe store exists. The factors of income level and frequency of shopping trips were not statistically significant for farm and n o n ­ farm families (Figures 6.11.3 and 6.11.4). This was related to the high frequency of shoe store outshopping by the m a j ­ ority of families at all income and mobility The future prospects for shoe stores villages of the study area are not bright. earlier, levels. in the central As noted shoe stores were a high order flexible function 313 that was not locally patronized. As such it is likely to be a nonviable function in the central villages. It was found to be almost ex cl us iv el y a town and city level function c on ­ sisten t with the preference of farm and nonfarm families for the shoe stores in urban centers. The increase of the n o n ­ farm p o pulation who have the greater preferences for outsho pping shoes, tirely, may eliminate the l o c a l shoe stores e n ­ to the benefit of shoe stores at urban central places. General Funding of Factors Influencing the Sh opping Models of Rural Families • Accor di ng to classical central place theory, distance min im i z a t i o n was always decisive in the behavior of c o n ­ sumers toward shopping o pportunities in central places. This de te rministic and confusing concept was fied, first by Losch (1939) later mo d i ­ who believed that the consumers are bi ased in their shopping choices for different goods and services. Golledge, This was verified in the empirical Rushton and Clark (1966). study of Other contributors to revis ed central place theory found that objective factors, such as distance and site attraction ping convenience (Taylor, 1979), (Williams, 1979), (Rushton, (Burnett, shop­ and price orientation and subj ective factors, time considerations 1971), 1973), such as money and are important variables that influence the shopping choices of consumers. Indeed, 314 personal experiences and attributes of individual consumers, such as their income class of residency (Burnett, (Davies, 1973), 1969), and age and race were also found to be influential in individual preferences for a certa in function. influential variables characteristics) age, (objective, and length (Hall, 1983) shopping The impact of these subjective and personal thus create varied ranges of shopping for different goods and services. These ranges for several functions have been examined and found to differ due to consumers' behavioral biases and their individual or social peculiarities 1965; Ray, (Golledge, Rushton and Clark, 1967 and Davies, 1966; Murdie, 1969). It was found in this study that objective and sub­ jective factors and individual characateristics of farm and nonfarm families are influential in their shopping choices toward di fferent sampled functions available in a certain class of central places of the study area. The factor of distance was found to be statistically significant in shopping travel models of farm and nonfarm families toward stores, lower order functions optometrist, and clinic. such as grocery Therefore, distance is a factor in the support of such functions at the level of sixth order villages (grocery) (optometry and c l i n i c ) . and third order villages Distance considerations were not significant for higher order functions, of automotive dealers with the exception (city level function) whose proximity 315 to rural residents was important due to local needs for auto repair. Price was another influential factor that was found to be sta tistically significant in farm and nonfa rm families' shopping travel models toward the first order villa ge fu n c ­ tions and town and city level functions (paint and w a l l ­ paper stores, department store, shoe s t o r e ) . The automotive dealer was again an ex ception because of its dual however, ilies' family clothing store, function of sales and service. and Price, was statistically significant among the farm fam­ choices of automotive dealers; ance among the nonfarmers. it had In general, less imp or t­ the price influence' on high order functions was responsible for the relative flexibility of these functions that compete with similar functions in the urban central places of the study area. These local goods, functions tend to be dis advantaged in qualit y of qu antity of selection, and prices co mpared with stores in urban central places that profit from economies of scale and volume buying. Shopping convenience was found to be important for a l ­ most all of the sampled functions that existed at different levels of central places. Farm families were influenced more by convenience aspects than nonfarm families. Thus, the convenience of being able to shop locally for a fu n c ­ tion generated some local farm families, support for various functions from but the same functions, available in urban 316 central places, families. were co nsidered convenient by the nonfarm This factor in particular illustrates the rural no nf ar m families' families. close ties to the city compared with farm The special ize d nature of functions such as clinics and op tom etrists floor covering stores par t m e n t stores stores (third order village f u n c t i o n s ) , (second order village functions), de­ (first order village f u n c t i o n ) , and shoe (town and city level functions) was an influence that e nco ura ged o ut sh op pin g by the farm and nonfarm families, pa rt ic ul ar ly the nonfa rm families. Saving money was ilies' statistically significant in farm fam ­ shopping for a second order village function c o v e r i n g ) , first order village function and dep ar tm en t store) (floor (paint and wallpaper and the town and city level functions (family clo thing and s h o e s ) . It was an influential factor for nonfa rm families but not statistically significant. The reaso n is related to the greater percentage of outshopping at u rb an central places done by the rural nonfarm families. Saving time was observed to be statistically signi fi ­ cant for farm families shopping models for third order v i l ­ lage functions fu nc t i o n (optomery, clinic) (automotive d e a l e r ) . and town and a city level It was found to be influen­ tial but non significant among nonfarm families. The re­ sults of this differe nc e are evident in the farm families' str onger p at ro n iza ti on of the nonfarm families, local enterprizes compared with who generally travel longer distances 317 and whose shopping preferences are generally oriented toward urban central places. Therefore, to save time they choose the most ac cessible urban central places. The factors of age and years of residency in present location were found statistically significant in some of shopping or vis iti ng models of rural families. The factors of age and years of residency were found statistically significant for farm and nonfarm families' sixth order village function shopping for the (grocery stores). There was a greater pe rcentage of grocery outshopping by young farm and nonfarm families who had had shorter residency compared with the middle aged and elderly. For visits to the optomerist, a third order villa ge function, the elderly farm and nonfarm families tend not to patronize the local optometrist. clinics (thrid order village function) heavil y by young nonfarm families. w al lp ape r stores are patronized The local paint and (first order villager functions) especi al ly favored by the nonfarm elderly. visitations Local were Meanwhile, to local clinics and paint and wallpaper by farmers were not statistically significant. stores In fact, farm families of diff er en t age levels patronized these functions almost equally. changes As a conclusion, in the age structure, lage functions. any future length of residency and n o n ­ farm proportion of rural residents viab il it y of sixth order, local is likely to affect the third order, and first order v i l ­ 318 The factors related to the characteristics of farm fam­ ilies, including farm consolidation and types of farming, were not found to be statistically significant in farmers' shopping models, but had some influence. There was some pr eference for inshopping among the farmers who had c o n ­ solidated their farms and those in general farming. Con­ sidering the present decline of farming and farm families, this local support is not likely to be very influential in the future developm ent of the villages. Full-time or part-time farming was an attribute of farm families that was found to be important in their shopping models for third (clini c) , second (jewelry) and first (de­ partment store) order village functions and town and city level functions (family clothing, store). automotive dealer and shoe There was a greater tendency for inshopping by full-time farmers. Given the continuous decline of full ­ time farmers and increased part-time farming, the viability of central villages can be expected to decline further in coming years. Income examined, levels and frequency of shopping trips were also but there were no statistically significant as so c­ iations between these factors and rural models for diffe ren t class of functions. ever, f a m i l i e s ’ shopping There were, h ow ­ some tendencies noted in preferences for outshopping local goods and services by higher income and more mobile farm and nonfarm families. The major influence in weakening 31 9 the importance of farm and nonfarm families' income level or mobility level was related to their pr eference for outshopping (bypassing) and mobility level the central villages at every income in favor of shopping at the urban c e n ­ tral places. Overall, it was found that the rural shopped the central villages, families out- due to the absence of needed goods and services and because of greater selection o p p o r ­ tunities in larger central places (urban c e n t e r s ) , with more variety and better prices and the a v a il ab il ity of numbers of shops in an urban mall or shopping center. rural families' In fact, the satisfactions and dissat is fa ct io ns with the local opportunities available in the central villages were the most important factor in their shopping models of sa m­ pled functions. The presence of a high percentage of out- shopping among rural (Table 6.3.1) families for all sampled functions implied their preference for selection o p ­ portunities existing in large central places of the study region. This supports a similar finding in the empirical study of Brooker-Gross (1981) for outshop pi ng the shoe stores available in local towns by permanent and n on ­ permanent (student) residents. From the questionnaire data ga th e r e d in the survey, was found that 37 percent of farm families completely b y ­ passed the central villages and 50 percent of the nonfarm families did so. faction of rural The evidence implied that the d i s s a t i s ­ families in study area with local it 320 functions started very early in the smaller central villages and only appeared later in the larger and more viable c e n ­ tral villages of southcentral Michigan which offered more varied functions. As discussed in Chapters Three and Five, regional development has brought regional ac ce ss ib il it y to the rural families of the study area and provided a co m p e t i ­ tive marketing space for all these central villages. fore, locational There­ factors and individual preferences have in­ fluenced outshopping of the local central functions of these villages. The regional development of the study area over the study time has brough t increased income and mo bility to the farmers that have encouraged outshopping, but, the drawing power of urban central places that offer more sophisticated shopping opportunities, with better quality merchandise, greater variety and cheaper prices has been the major in­ fluence on families at all income and mobility was evident in the inferential levels. This chi-square pro ba bil it y tests that were used to examine the factors of income and mobility and found them to be statistically no n- sig nificant ping models of rural families. Indeed, the decline of farms and farm families and increase of nonfarm families study area tial (due to rural development) in sh o p ­ in the has been very influen­ in the de clining viability of central villages. tinuation of this trend will cause further decline class order of central villages. Con­ in the CHAPTER SEVEN SUMMARY, CONCLUSIONS AND FUTURE SPECULATION The purpose of this research was to examine and analyze changes in the viabi lit y and spatial di st ribution of the central villages of southcentral Michigan over the periods of 1950-1970 and 1970-1980, significant rural parti cul arl y in response to and regional development in the study region. The southcentral Michigan area offers a homogeneous physical environ men t ch ar acterized by general and dairy farming, as well as substantial nonfarm rural settlement. Fo rty-six villages we r e distributed over the study area and it was hy po thesized that the spatial di st ribution arrangements) of these central villages, velo pm en t and farmers' time. Indeed, preferences, (geometric due to rural d e ­ would have changed over it was hy po thesized that the rank size rule (a continuous relationship between the population size of villages and the number of their functions) archical and the h i e r ­ structure that existed had been changed over the periods of the study. Rural development in the study area, including agricultural industrialization, ve lo pme nt and consequ ent changes transportation de ­ in the pattern of 322 population d is tri bu tio n over the two periods of 1950-1970 and 1970-1980 was hy pot hesized to be one of the most es ­ sential factors of change in the vi a b i l i t y and spatial d i s ­ tributions of central villages. It was further hypothesized that changes in the viability and spatial dist ri bu ti on of central villages wo ul d be found to derive from certain p re ­ ferences of rural families. Significant agricultural in du st rialization of the farm landscape with concur re nt super highw ay development has o c ­ curred in southcentral Michigan. The increase of regional accessibility and the increase of farm families' comes were the consequences of rural study region. Farm de po pulation dustrialization) gross in ­ development in the (due to agricultural in­ was accompanied by rep opulation with n on ­ farm families who commuted to jobs in the cities, but took advantage of super highway dev elopments to live in less e x ­ pensive, less crowded rural areas. To compare the functional changes of central villages due to rural dev el op me nt over the study periods, tional a fu n c ­ index classific at io n was chosen that provided an o b ­ jective method and showed the hierarchical pattern of c e n ­ tral functions in central places. classific ati on gave the values of each central Using a functional location coefficients function and the functional each central village. index The functional for index values for index values were then divided into six classes using the Jenks method and F-tests 323 (analysis of variance) that showed a strong hierarchical structure among the six classes of central villages at three points in time (1950, central villages 1970 and 1980). The classifi ca tio n of into these six groups at three points of time became the me chanism for modeli ng and analyzing them in a spatial and temporal framework. Due to rural development and conseq ue nt changes rural functions, the decline of farmers and increase of n o n ­ farm families in the study area, archical in the model of the h i e r ­ structure of central villages changed over the study periods. Changes in the types and numbers of rural functions and number of functional units different models of the hierarchical villages. Indeed, (s tores), created structure of central the threshold popul at ion for each h i e r ­ archical class of villages lost its importance as a factor of economic growth of a particular class over time. continuous models to show the general Using trends of population and functional relationships of central villages over the study time, revealed a strong linear relationship and p o s i ­ tive correlation coefficients among the variables. continuous This linear relationship between population and fu n c ­ tion in central villages we akened over the study time due to the declining importance of po pulation as a factor of ec o n ­ omic growth and viability in central villages. The continuous model was also used to determine the threshold population for some sampled functions over the 324 study time with the result that threshold populations were found to differ for different orders of central functions. Accordingly, it was found that lower order functions, as grocery stores, could survive with the support of a small population, while the higher order functions, partment stores, port. such such as d e ­ required a larger range of population sup­ Since the impact of transportation development in­ creased the regional accessibility of the rural the study area over the study periods, families of the threshold pop ­ ulation required for the survival of a central function g e n ­ erally increased as that function came into greater spatial com pe tition with similar establishments tral places of the study area. in the larger cen­ The temporal di mension for this empirical useful study was in examining the changes in the spatial distribution (geometric arrangement) of the six orders of central v i l ­ lages over the study times. (dispersed) It was found that the regular pattern implied in original central place theory did not.exist for all the classes of villages at the three points in the study time. there was a general central villages Using nearest neighbor analysis, tendency toward random patterning of in the period from 1950 to 1970, while the pattern varied from random toward dispersed patterning from 1970-1980. ilies' Regional preferences development in relation to rural fam­ for inshopping or outshopping the cen ­ tral villages was responsible for these spatial changes. 325 The adoption of agricultural in du st rialization among the rural farm families of southcentral Michigan and the significant super highway development in the region over the study periods was responsible for changing the viability and spatial distribution of central villages. functions that were required by the rural Several older farm families in 1950 then became outmoded and disappe ar ed from the central villages studied by 1970. The disappearance of general stores from these villages over the 1950-1970 period, for example, was accelerated by the increased practicality and popularity of local and urban departm ent stores that had been established in the study region by 1970. development of rural super markets in the period between Indeed, the in the central villages 1970 and 1980, in their turn, reduced the demand for local department stores in favor of urban d e ­ partment stores. The function of b l a c k s m i t h i n g , and shoe and harness repair, also available 1950, were demanded locally by farmers who were still using horses for farm work. central villages by in central villages in These functions had disappeared from 1970, when tractors and other machinery had taken the place of horses as farm work power. The increase of tractors and cornpickers bringing agr i­ cultural industrialization to the farm landscape in the period of 1950-1970 was also influential number of farm and machinery dealers, and gas dealers in increasing the fuel oil and petroleum in central villages during that period. The 3 26 old farm machinery shops available in central villages in 1950 were replaced by or developed into farm equipment dealers (in 1970), who introduced the most recent and so p h ­ isticated farm m a c hi ne ry and supplies to the farmers. This trend was supplemented by the appearance of another farmoriented function, 1970-1980 period, farm and garden machinery stores, in the w h i c h were related to an increasing in­ terest in part-time and hobby farming among the rural ilies. Technological advancements fam ­ in trucks and automobiles and the increased usage of trucks by farmers and motor v e ­ hicles by rural n o nf ar m families, their jobs, who commuted to cities for over the periods of the study also caused the disappearance of general machine shops that were available in cental villages in 1950 and the introduction of motor vehicle dealers by 1980. Meanwhile, 1970 and their increase from 1970 to the decline in the number of gasoline service stations and auto supply and equipment in the central villages over the study periods was related to the consolidation of these functions in larger central places (economies of scale) due to the greater accessibility p r o ­ vided by super highw ay dev el op me nt in the region. technological tial advancements Thus, in tr ansportation were influ en ­ in changing the spatial distr ib ut io n of central func­ tions in the central villages over the study periods. It was found that, in the central villages studied, retail and wholesale reductions were consistently more 3 27 severe in lower order central villages than in higher order villages over the study time. stores, hardware stores, stores, furniture stores, examples of reductions The declines in grocery gasoline service stations, drug­ jewelry stores and the like were in retail functions in the central villages caused by rural families preferences for urban shopping. It should be noted that first and second order villages of the study area were less affected than lower order central villages by the process of regional rural development. In fact, experienced decline urban centers, higher order central villages also in retail but it was central villages, functions in competing with less severe than the lower order whi ch are pre sently economically non- viable central places in the study region. Significant changes in agriculture and transportation in southcentral Michigan increased part-time farming and the nonfarm populat ion in the rural townships of the study area. Farm mec hanization and consolidation caused the exodus of many farm families from the rural farming landscape as large-scale (consolidated and corporate farms) resulted in eco n­ omic hardship and finally the disappearance of many small farming operations. This trend was accompanied by an in­ crease in part-time farmers who do not depend entirely or even mostly on their farm incomes. For part-time farmers, their increased mo bility has been helpful to take jobs in the cities. in allowing them The depopulation of the rural 3 28 landscape (due to agricultural industrialization) has been accompanied by repop ula ti on since the 1960s with rural nonfarm families w h o have jobs in the urban centers of southcentral area, Michigan. Of the rural townships of the study 96 percent ga in e d population between 1950 and 1970 and all of them gained popula ti on in 1970-1980. All of the c e n­ tral villages gai ned population in the first period and 65 percent of them increased their populations period. in the second The trend of rural population growth was e n co ur ­ aged and promoted by the transportation development in the region. seekers Nonfar m residents since since the 1960s and recreation 1970s have sought rural villages for cheaper living and housin g costs and the quiet, of the rural atmosphere. The increase of part-time farmers and rural nonfarm families decline in the study area accompanied a in pat ro ni za ti on of some central villages. local central On the other hand, crease of mobile home dealers, ver tising services beauty and pleasures functions in the emergence and in­ hobby shops, and outdoor ad ­ in the central villages between 1970 and 1980 were also related to the increasing rural population and the significance of rural recreational rural population growth was residential influential The in increasing the function in central villages and rural' services or professions such as churches, (except schools and hospitals) studied. activities. doctors, and attorneys in the central villages It should be noted that declines in the retail and 329 whol es al e ac tivities of these villages as a result of re ­ gional development were sidential, slightly offset by increased re ­ social and community functions. The impact of rural developm ent and bypassing of the central villages by rural families was more decisive in the first period of the study (revolutionary period) retail activities than the second period the six orders of central villages. in reducing (evolutionary) This hierarchical in order of central villages was important in changing their v i a ­ bili ty and c on se que nt ly their spatial distribution. It was found that first order villages were the most viable centers and the sixth order villages were the least viable centers among the central villages tral villages studied. ex per ienced reductions All six classes of c en ­ in their retail sections but they wer e generally most harmful order central villages. First order villages, viable central villages, offered industrial agribusiness, well recreational and residential for the lower as the most (manufacturing), functions, as as job opportu nit ies and some specialized farm-oriented stores and fairs. The second order villages also grew in both periods of the study. They also faced declines tail activities, status hierarchical but their in the second rank of the structure of central villages, their economic via bil ity for survival. industrial functions in re ­ (manufacturing), helped to retain They offered some agribusiness, 330 recreational and residential functions. opportunities were fewer and they were Whi le their job less economically important than the first order villages, they may tend to remain stable in the future de ve lop me nt of this region. Third, fourth, fifth and sixth order villages, ranks of the hierarchy, combined agricultural tial functions with wea k economic viability. as the lower and r e s i d e n ­ Considerable decline in their viability over the study periods indicated that they were very sensitive to the influences of regional development. The decline of sixth order villages to the level of a hamlet particularly rev ealed the weaknesses of low order central villages development. The fifth, in the face of rural and regional fourth and third order villages may also gradually decline to hamlet level in the future d e ­ velopment of the study area. The changes of viability in the central villages caused changes ally, in their number and spatial distribution. Gener­ the first and second order villages grew or stabilized in their numbers in the study periods, central villages underwent various while the rest of the fluctuations. The sp a t ­ ial dis tribution of first and second order villages and their development in the southern part of the study region (below the intersection of 1-69 and 1-96) was due to the attraction of the super highways and auto industries of Detroit and indicated that industrial and manufac tu ri ng growth was supportive for their economic viability. versely, Con­ the spatial distribution and developm ent of third, 331 fourth, fifth and sixth order villages of the study area was in the southern part limited and they were more likely to be found north of the 1-69 and 1-96 intersection in areas that were more agriculturally oriented. In fact, highway development has promoted industrial high order central villages, while the super orientations in lower order villages have not benefitted to the same extent from this advantage for their economic growth. There is no doubt the rural de ve lopment in the study region was accompanied by increased regional accessibility and gross farming incomes over the study periods. It was also found that rural families were more mobile than in the past due to technological developments Thus, in transportation. they have been able to bypass most of the central villages in favor of shopping in the urban centers where the selection of goods and services of better quality and qua n­ tity has.been made co nv eniently available to them. The gross income of farm families was found to have s i gn if i­ cantly increased (due to agricultural industrialization) in the countries of southcentral Michigan over the study periods. This increase of farmers' gross income and mobility occurred at the same time as the central villages' retail and overall decline in viability, were not shown to be closely related. and income but the two events Increased mobility levels of rural families were found not to be statistically significant in most of their shopping models. 332 It was found that the important factor of outshopping passing) the local central functions (by­ in the villages was related to the pa tr onization of urban centers by the m a j o r ­ ity of all rural farm and nonfarm families, those from any particular rather than level of income or mobility. There was some preference for outshopping noted among higher income rural ficant. families, Therefore, but it was not statistically s i g n i ­ it could be said that the increased mo bi li ty and income of farm families over the study periods accompanied the severe decline in the retail vi ability of central villages that occurred when the villages were b y ­ passed by the farmers. This finding was based on a non- statistical examination, tory of residents' due to a lack of data on the h i s ­ shopping performances in the past. The concept of various ranges for diferent functions was found to be relevant as the research showed that rural families were biased in their shopping travel central functions. Rural for different families employed shorter ranges of travel for lower order functions and longer ranges of shopping travel for higher order functions. The nonfarm families co ns istently had greater ranges of shopping travel co mpared with the farm families in the study area. fore, the nonfarm families' marily city-oriented, shopping behavior that was p r i ­ provided for greater spatial action among local central Th er e­ in te r­ functions and the central tions of urban central places. Farm families, fun c­ who had 333 shorter ranges of shopping travel, provided for the o b s e r ­ vation of limited spatial interaction between local economic businesses and urban businesses. It should be noted that the increase of regional ac ce ssibility for rural farm and nonfarm families has been an important factor in producing the longer ranges of shopping travel over the study time. for different functions Rural development, rural nonfarm families and individual the increase of and social differences betwe en farm and n on fa rm families have been influential the growth or decline of central villages. in It was found that greater ac ce ss ibi li ty favored the outshopping of local functions by rural families; and that rural nonfarm families have played the g r ea te r role in local dispatro niz ati on of village functions. The grocery store as an inflexible sixth order village function had the smallest standard de viation in shopping travel rural and highe st percen ta ge of local farm and n on fa rm families. third order village functions second order vi lla ge functions inshopping by the The spatial flexibility of (optometrist and c l i n i c ) , (floor covering store and j e w e l r y ) , first order village functions (paint and w a l l ­ paper store and d ep ar tm ent s t o r e ) , and the town and city level functions and shoe store) travel (family clothing store, automotive dealer, re su lt ed from greater ranges of shopping and p r op ort io nat ely greater outshopping by the rural nonfarm families com pared with rural farm families. Further - 334 increase in rural nonfa rm families will be harmful, for the present order of rural central (polarization) central functions and a concentration of these funcions at the next higher class of villages may be the best possible solution. was observed that decline It in the viability of central functions has been acc om pa ni ed by loss of their status as typical functions of a certain class of central villages to typical functions of the next higher order class over the study time. These experiences can aid future speculation on this research. In order to de termine the factors influencing the shop ­ ping models of rural tion, families in regard to a certain func­ chi-squ are tests were applied to test the hypothesis that individual differences were statistically significant in creating those shoppi ng models. The results showed that the distance was statist ica lly significant for rural ilies' fam­ shopping models of sixth order and third order v i l ­ lage functions. The distance aspect was more significant among farm families than nonfarm families. However, for future reall oc at ion of sixth order village and third order village functions, distance (proximity) considerations in regard to the p ro po rt io n of farm and nonfarm families in the study area, should be taken in account. Price was found to be statistically significant among the rural families' shopping models for first order village and town and city level functions. Price considerations 335 were related to the better quality and qu an ti ty of goods at lower prices that were available in urban central places. The price influence on the shopping decisions of farm fam­ ilies was related to their choice b et wee n local urban stores; among nonfarm families, stores or price considerations were mostly related to a selection of stores among d i f f e r ­ ent urban central places. This greater dispatronage of local is consist ent wit h the stores by nonfarm families. Convenience of shopping a central place function was found almost to be statistically significant and highly influential among the rural farm families' families of the study area. The concern for shopping con ve ni en ce was more ob ­ vious and they were village and city oriented. But, non-farm families were city-oriented in making the most convenient choice of shopping centers. The specialized nature of some goods and services of central places also encou ra ged outshopping the local stores. This was more prev ale nt among the rural nonfarm families. Saving time in shopping travel models of rural families was found to be influential for sixth and third order village functions and was more important for farm families than no n­ farm families. However, rural particularly farmers, families, order local functions. the time saving con siderations of tend to support low Saving money was found to be signi­ ficant in shopping models of rural families, par ticularly 336 the farm families, for second and first order village fu n c ­ tions and town and city level functions. Money saving c o n ­ siderations are thus employed for high level are more competitive. functions that Concern for saving money is a factor in outshopping the local stores of first and second order villages. Factors such as age, and length of residency, were found statistically significant for some of the sampled functions. There was generally a greater pa tr onization of local functions by y oun g nonfarm families ency) and older farm families (with short r e s i d ­ (with long r e s i d e n c y ) . cause the percentage of young nonfarm families is low percent of nonfarmers) supportive as the older Be­ (8.7 their local patronage will not be as (elderly) farm families who re ­ present 24.3 percent of farm families. Thus, the future d e ­ cline of farm families and continuing increase of nonfarm popula tio n will not be likely to generate central village development. The attributes related to farm families were not statistically significant in most cases although there was a greater tendency toward inshopping among full-time farmers than part-time farmers. deeper socioeconomic tral villages urban centers. Generally, and cultural full-time farmers have ties with the local ce n­ than part-time farmers who have jobs in the The farmers and decline increase in the number of part-time in the number of full-time farmers in 337 the study area over the study time was another aspect of the continuing disp atr ona ge of local functions at the central village level to the benefit of urban central places. Rural residents' ping opportunities dissatisfaction with the local shop­ in central villages was influenced most by more convenient and economical access to urban centers with varied, high quality, lower priced goods in attractive malls and shopping centers. tial in the rural families' This factor was most influ en ­ shopping and visiting models and was prominent th roughout the explanations of rural families surveyed. The d i ss at is fa ct ion of rural nonfarm families with shops was much greater and started earlier than local the farm families. It is appropr ia te to speculate briefly on the future prospects for the vi ability of these central villages and their cha racteristic functions in this study. con solidation (polarization) of central First, the functions in higher order central villages seems to have been a function of the application of economies of scale in this area. It was found that school consolidation in the first order villages was more efficient and economical than the dispersed d i s ­ tribution of smaller schools lages. in all classes of central v i l ­ School consoli dat ion upgraded the average number of schools in the first order villages and decreased the average number of schools in other classes of central v i l ­ lages. However, the consolidation and concentration of 338 rural schools in the first order villages, polarization for future development, tages and may be unavoidable. as a policy of has economic a d v a n ­ Grocery stores which were another sixth order vill a ge function remained typical functions in all classes of central villages over the study time. The continuous and co ns iderable decline in grocery stores has reduced their status as the sixth order village function to the fifth order village function. grocery stores and all the central class of location coefficient, gasoline service stations, tors, functions Therefore, in the same such as hardware stores, dri nking places and grain e l e v a ­ may be future fifth order village functions able at fifth, fourth, third, (avail­ second and first order v i l ­ lages) . Increases clinics in the number of local optometrists and (third order village functions) lages studied, in the central v i l ­ had chang ed their status as first order v i l ­ lage functions to third order village period from 1970 to 1980. visita tio n of rural Due to co ns iderable nonfarm families, likely to be polarized only functions over the local out- these functions are in second and first order v i l ­ lages . Jewelry stores were conso li dat ed over the study time to become a typical by 1980. function of first and second order villages The strong typicalness of jewelry stores in first order villages and their wea k typicalness in second order villages, in light of the small percentage of jewelry 339 inshopping by rural farm and nonfarm families, suggests this function is likely to be polarized wit hi n the first order villages in the years ahead. Other second order village functions such as the floor covering store and radio and TV repair shops may similarly be polarized at the level of first order villages in the coming years. Department stores, a typical function of first and second order villages in 1950, was typical only in first order villages in 1970 and 1980, which suggests that the concentration or po la rization of this function in first order villages has already been necessary. villages The central studied can rely on maintain ing department stores only in the first order villages; should not be anticipated. their future development The other first order village functions such as paint and wallp ape r stores, ing services, electrical motorcycle dealers, data pr o c e s s ­ and electronic repair shops and like department stores, may be retained at their present status as first order village functions, otherwise they may be town or city level functions. The presence of town and city level functions such as family clothing stores, automotive dealer, low order central villages stable situation. in 1980, and shoe store in represented a highly un ­ Regarding the increase in the study area's nonfarm families who widen the range of spatial in­ teractions between central villages and urban central places, these high level functions can not survive in that 340 big competition. Thus, their po la riz ati on in the towns and cities of the study area is the ul timate so lution to their declining viability. First order villages are the best pos sible centers for concentrating or polarizing flexible central functions; second order villages would be the next best choice. least viable third, fourth, The fifth and sixth order villages cannot be considered appropriate centers for co nc entrating or polarizing flexible functions as they are only ma rginally viable for inflexible and low order functions. Since the various aspects of consumer behavior were found to be quite influential tions, area in determining the v i ab il ity of central future rural retail or service d e ve lop men t in this (microscale region) Indeed, should con sider these findings. the changing pattern of rural population, the farm and nonfarm families, in the future. including of the study area should be c onsidered seriously in any regional central villages fu nc ­ pla nni ng of these A P P E N D I X :A TABLE A.I.CENTRAL FUNCTIONS, LOCATION COEFFICIENTS AND FUNCTIONAL INDICES OF CENTRAL VILLAGES, 1950. Village T A T B T C 1 . Chelsea 9 1 2 2. Lake Odessa 4 3. Dexter Fowlerville Nashville 6. Manchester 7. Brooklyn 8. Bellevue 9. Homer 5 3 5 1 1 4 3 1 2 1 4. 5. 10. 11. 12. 13• 14 . 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 16. 17. 18. 1 9. 20. 21. 22. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clarksville 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43• 44. 45. 46. Vermontville Byron Lennon Dimondale Maple Rapids Sunfleld Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansville Perrinton Hubbardston Cement City Eagle 3 A 1 1 1 3 1 1 2 5 1 3 6 1 5 5 1 3 3 7 2 3 1 1 6 1 - 3 1 2 3 6 4 4 4 1 6 1 1 1 2 C 2 C* D C' 1 3 E 1 1 1 3 2 3 2 1 1 1 2 2 1 1 2 1 1 1 1 1 3 1 1 1 2 2 2 1 2 3 4 2 3 2 2 1 2 2 1 4 2 1 3 3 1 1 2 3 2 2 2 2 C’ 2 3 1 2 2 1 1 2 1 1 1 2 1 2 1 3 1 2 1 4 3 2 1 4 4 4 1 1 2 2 1 1 1 1 1 5 2 1 4 5 C* B 5 3 3 2 2 c* 8 1 4 1 2 5 2 T D 1 2 1 1 1 1 1 2 1 1 1 2 1 1 3 2 1 1 1 2 1 1 2 2 2 1 1 4 2 1 1 1 1 Total Functional Units 116 12 38 1 70 107 28 15 26 Location Coefficient .86 8.33 2.63 100 1.43 .93 3.57 6.66 3.85 Source: Author's collections based on Dun A Bradstreet Reference Book, 1950. 3*H 34 2 TABLE A.I. (CONTINUED) Village C* F C* G C* H C* I C* J 1 1. Chelsea 2 2. Lake Odessa 3 2 2 1 1 2 3 2 4 3 2 1 3. Dexter 4. Fowlerville 5.' Nashville 6. Manchester 7. Brooklyn 8. Bellevue 9. Homer 10. 11. 12. 13. 14. 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clartesville 27. 28. 29. 30. 31• 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Lennon Dimondale Maple Rapids Sunfield Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansville Perrinton Hubbardston Cement City Eagle Total Functional Units Location Coefficient 1 1 1 1 1 C* K C* L 11 11 A B 1 1 1 1 1 • 4 2 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 •1 1 2 1 1 1 1 1 1 1 1 1 5 2 20 50 17 5.88 37 4 2 2.7 25 50 1 15 100 6.66 20 5 3^3 TABLE A.I. (CONTINUED) Village 1. Chelsea 11 C 1 11 D 1 11 E E 1 Dexter Fowlerville Nashville Manchester Brooklyn Bellevue Homer 10. 11. 12. 13. 14. 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 16. 17. 18. 19• 20. 21. 22. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clarksville 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Lennon Dimondale Maple Rapids Sunfield Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansville Perrinton Hubbardston Cement City Eagle Total Functional Units Location Coefficient B 1 E C [ A [ B 1 2. Lake Odessa 3. 4. 5. 6. 7. 8. 9. E A [ C 1 3 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 5 5 10 29 14 20 20 10 3.45 7.14 8 12.5 3 3 3 33.33 33-33 33.33 344 TABLE A.I.(CONTINUED) Village D [ E F [ G ) A 1 . Chelsea 5 1 1 2 1 2 . Lake Odessa 2 3. 4. 5. 6. 7. 8. 9. Dexter Fowlerville Nashville Manchester Brooklyn Bellevue Homer 2 2 10. 11. 12. 13. 14. 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 16. 17.. 18. 19. 20. 21. 22. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clarksville 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Lennon Dimondale Maple Rapids Sunfield Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansville Perrinton Hubbardston Cement City Eagle C Total Functional Units Location Coefficient C 1 2 1 1 2 2 1 4 1 2 2 3 1 1 1 2 1 1 1 1 3 1 1 1 1 1 % B 3 1 1 1 1 3 1 1 1 2 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 % A 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 ) c 1 3 3 1 1 ) B 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 2 1 1 2 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 1 49 2.04 4 25 13 33 26 1 18 21 6 7.69 3.03 3.85 100 5.55 4.76 16.67 3^5 TABLE A.I. (CONTINUED) Village I I A B 1. Chelsea 2. Lake Odessa 1 1 3. 4. 5. 6. 7. 8. 9. Dexter Fowlerville Nashville Manchester Brooklyn Bellevue Homer 1 1 1 10. 11. 12. 13. 14. 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clarksville 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Lennon Dimondale Maple Rapids Sunfield Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansville Perrinton Hubbardston Cement City Eagle Total Functional Units Location Coefficient X 0A • B 0 A 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 A 2 2 2 1 2 1 1 2 1 0 C 1 3 1 1 1 1 2 1 1. 1 1 3 0 B 1 2 2 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 7 10 9 15 3 8 14.28 10 11.11 6.66 33.33 12.5 25 4 1 27 100 3.7 346 TABLE A.I. (CONTINUED) Village > ♦ 1. Chelsea 2 2. Lake Odessa 2 3. 4. 5. 6. 7. 8. 9. Dexter Fowlerville Nashville Manchester Brooklyn Bellevue Homer 1 2 1 1 1 1 1 10. 11. 12. 13. 14. 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clarksville 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Lennon Dimondale Maple Rapids Sunfield Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansvilie Perrinton Hubbardston Cement City Eagle 2 Total Functional Units Location Coefficient A 5.88 C D E U A 2 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 10 11 17 50 B 100 9.09 50 16.67 100 33.33 10 3^7 TABLE A.I.(CONTINUED) _ Village A _ B _ C = D 1. Chelsea 2. Lake Odessa 3. 4. 5. 6. 7. 8. 9. Dexter Fowlerville Nashville Manchester Brooklyn Bellevue Homer 10. 11. 12. 13. 14. 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clarksville 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Lennon Dimondale Maple Hapids Sunfield Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansville Perrinton Hubbardston Cement City Eagle Total Functional Units Location Coefficient z A z B 1 1 1 z D z E 3 1 2 1 1 1 1 1 1 1 2 2 2 1 1 2 1 1 1 1 1 1 1 2 1 1 2 1 1 1 1 1 1 1 1 1 1 2 1 1 z C 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 4 25 3 33.33 4 25 17 2 3 42 1 1 5.88 50 33.33 2.38 100 100 348 TABLE A.I. (CONTINUED) Village * * * A B C P A P B 1. Chelsea 1 2. Lake Odessa 2 3. 4. 5. 6. 7. 8. 9. Dexter Fowlerville Nashville Manchester Brooklyn Bellevue Homer 10. 11. 12. 13. 14. 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clarksville 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Lennon Dimondale Maple Rapids Sunfield Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansville Perrinton Hubbardston Cement City Eagle Total Functional Units Location Coefficient P C P D P E 4 4 4 2 25 25 25 50 + A 2 1 1 1 2 1 39 3 6 2.56 33.33 16.67 7 1 0 14.28 10 3^9 TABLE A.I. (CONTINUED) ■ A ■ B ■ C 2 2 2 2 2 2 1 2 1 1 1 1 1 2 1 1 1 1 1 2 1 1 2 2 2 Village + B + C + D 1. Chelsea 1 1 2. Lake Odessa 3. 4. 5. 6. 7. 8. 9. Dexter Fowlerville Nashville Manchester Brooklyn Bellevue Homer 10. 11. 12. 13. 14. 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clarksville 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Lennon Dimondale Maple Rapids Sunfield Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansville Perrinton Hubbardston Cement City Eagle Total Functional Units Location Coefficient S 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 1 1 2 2 ■ D ■ E 1 1 1 1 2 1 2 1 1 2 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 2 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 2 2 1 1 1 1 11 3 14 9.09 33.33 7.14 5 20 26 53 10 2 3.85 1.89 10 50 1 100 350 TABLE A.I. (CONTINUED) Village ■ F 1. Chelsea 1 ■ G ■ ■ H ■ I ■ J Dexter Fowlerville Nashville Manchester Brooklyn Bellevue Homer 10. 11. 12. 13• 14. 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 16. 17. 18. 19• 20. 21. 22. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clarksville 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Lennon Dimondale Maple Rapids Sunfield Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansville Perrinton Hubbardston Cement City Eagle Total Functional Units Location Coefficient A 3 2. Lake Odessa 3. 45. 6. 7. 8. 9. V K 5 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 Autolundry 1 1 2 1 V B 3 1 1 2 1 1 1 1 1 2 1 1 1 1 » 1 1 2 3 1 2 1 1 1 1 1 1 1 1 1 1 3 1 1 2 2 1 1 1 2 1 1 100 3 3 33.33 33.33 4 25 7 14.28 30 3-33 25 4 12 1 8.33 100 351 TABLE A.i. (CONTINUED) Village Antiques 1. Chelsea Photo Bowling Boats 1 Recreation 1 2. Lake Odessa 3. 4. 5. 6. 7. 8. 9. Dexter Fowlerville Nashville Manchester Brooklyn Bellevue Homer 10. 11. 12. 13. 14. 15. Stockbridge Linden Grass Lake Pinckney Saranac Ovid 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. Webberville Fowler Parma Pewamo Springport Caledonia Addison Muir Concord Morrice Clarksville 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Lennon Dimondale Maple Rapids Sunfield Woodland Bancroft Muliken Westphalia Gaines Vernon Hanover Freeport Lyons Dansvilie Perrinton Hubbardston Cement City Eagle Total Functional Units Location Coefficient Function; Index 983.70 656.56 1 1 484.14 455.70 453.91 431.31 389.24 384.09 379.18 1 1 350.53 299.46 298.86 291.56 279.06 251.88 1 1 218.61 206.96 195.46 • 192.19 187.18 174.53 153.12 145.26 132.51 131.59 129.03 1 103.98 103.06 100.81 90.86 87.67 83.22 79.06 76.93 73.80 69.36 60.56 60.42 59.83 55.21 44.92 37.00 26.51 25.09 22.70 11.25 2 2 3 1 1 50 50 33.33 100 100 352 TABLE A.l*: I. Meaning of the Trade Symbols** Food and Beverages A. P (Food Production) PA - Produce company: Distributing, wholesale products and grocery PB - Dairy products PC - Dairy products and poultry PD - Vegetables (onion, potatoes, mint, pickle) PE - Fruits (fruit and confectionery, fruit and livestock, wholesale and retail sale: fruit) B. T (Grocery and Meat) TA - Grocery and food market TB - Meat TC - Grocery and related (miscellaneous food stores) TD - Farm grocery C. 11 (Elevator and Feed) 11A- Elevator (grain, beans, soybeans) 11B- Elevator (implements, fuel, feed, 11C- Flour mill (mill company) 11D- Flour and feed H E - Feed D. % E. [ (Eating and Drinking Places) [A - Cider and vinegar [3 - billiards [C - Beverages' dealers (wine, beer, [D - Restaurant [E - Hotel and miscellaneous [F - Lunch and miscellaneous [G - Tavern and miscellaneous lumber) (Bakery and Confectionery) %A - Confectionery and related %B - Bakery and related I I , Textiles, liquer) Dress Shops and Apparel A .^^( Textiles and Dress Shops) A - Yarn B - Dry goods and wear (women and children) C - Dress shop D - Women's wear shop and furnishing E - Millinery *Dun and Bradstreet Reference B o o k , 1950. **For better recognition of each individual function in 1950, the proper alphabetical order has been used in su b ­ divisions . 353 TABLE B. A.l: Cont +(Clothing) +A - Clothing (cloth, shoes) +B - Cleaners and dry cleaning +C - Men, women and children wear and furnishings and shoes +D - Men's wear, cloth and furnishing C . A (Shoes) I a - Shoes and harness repair 0 B - Shoes III.Chemicals, Drugs, Paints A. Z (Chemicals and Drugs) 2A - Chemicals and allied products ZB - Patent medicine ZC - Drugs, and miscellaneous ZD - P h a r m a c y (pharmaceutical preparations) ZE - Remedies (hospital equipments) B. X (Paint) X - Paint and wallpaper I V . Construction Works and Wood Products A. B. V. 0 (Construction Works) 0 A - Plumbing supply and plumbing O B - Plumbing and heating 0 C - Heating ) (Wood Products) ) A - Funeral home and mortician ) B - Upholstering ) C - Furniture (used, gifts, repair) Transportation Equipment A. C * (Automobiles and Related) C‘A - Filling station C'B - Service station G C - Garage C-D - Oil and gas (distribution co . ) G E - Autobodies (body shop, repair, collision) G F - Trucking G G - Hauling C*H - Auto supply and auto parts (sales and service) C-I - Automobiles and tractors C-J - Auto farm implements G K - Trailers O L - Bicycle 35 ^ TABLE B. A.l: Cont S (Blacksmith and Related) S - Blacksmith or horse and mule dealer V I . Metal Products, A. V (Metal Products) VA - Machinery, machine shops- and machinists supplies VB - Welding & repair B. B ■ | ■ ■ ■ I ■ ■ ■ | •| C. Machinery and Electrical Products A B C D E F G H I J K (Machinery) - General hardware (hardware and implements) - Hardware stores (hardware and miscellaneous ) - Farm machinery (appliances) - Tractors - Pumps - Household specialties - Household goods - House furnishing - Well driller (bowling and well drilling ) - Sporting goods - Implements (agricultural) E (Electrical Products) E.A - Electrical supplies and equipments services and repair) EB - Radio (sales, service or repair) EG - Telephone Company and service VII.General Merchandise Distribution A. B. * (General Stores) * A - General store *B - Department store *C - General store and miscellaneous A( Va ri et y stores) \ - Variety and gift shops VIII.Other Businesses A. = (Book, Publishing, Printing) = A - Books, bookbinders, newspapers = B - Publishing = C - Printing = D - Publishing and printing 3. U (Nurseries, Greenhouse) U A - Nurseries (horticulture) U B - Florist (greenhouse, flowers) (sales, 355 TABLE A.l: Cont (Jewelry) (Jewelry) D.l (Fuel, feed, food lockers, refrigerators) IA - Fuel, coal, feed, etc. |B - (Food lockers or wood, frozen food lockers, refrigerators) E.> >- (Music or Musical) Violins (manufacturing and repair) TABLE A.2. CENTRAL FUNCTIONS, LOCATION COEFFICIENTS AND FUNCTIONAL INDICES OF CENTRAL VILLAGES, 1970. Village 5013 5014 5042 5043 5044 5045 5047 5048 5049 4 3 2 7 3 1 3 1 1 14.29 33.33 100 33.33 100 100 1. Chelsea 2. Brooklyn 3. Dexter 4. Lake Odessa 5. Ovid 6. Homer 7 . Fowlerville 8. 9. 10. 11. 12. Addison Manchester Saranac Pinckney Caledonia 13* 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 20. 21. 22. 23• 24. 25. 26. 27. 28. 29* 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfleld Maple Rapids Perrinton Springport 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webbervllle Freeport Bancroft Lennon Cement City Vermontvllle Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons Total Functional Units Location Coefficient Source: 25 33.33 50 Author'3 c o l l e c t i o n s based on Dun A Bradstreet Reference Book, 1970 and Telephone Directories, 1969 to 1971. 356 357 TABLE A.2. (CONTINUED) Village 1. Chelsea 2. Brooklyn 3. Dexter 4. 5. 6. 7. Lake Odessa Ovid Homer Fowlerville 8. 9. 10. 11. 12. Addison Manchester Saranac Pinckney Caledonia 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapid3 Perrinton Springport 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons Total Functional Units Location Coefficient 5053 5054 5072 5074 5082 5083 5084 5085 5086 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 7 1 14.29 100 1 100 1 100 1 1 100 1 100 1 100 1 100 100 358 TABLE A.2. (CONTINUED) Village 5092 1. Chelsea 2. Brooklyn 3. Dexter 2 4. 5. 6. 7. 2 1 2 Lake Odessa Ovid Homer Fowlerville 8. 9. 10. 11. 12. Addison Manchester Saranac Pinckney Caledonia 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapids Perrinton Springport 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons Total Functional Units Location Coefficient 5093 5094 5095 5096 5098 5099 3 1 1 1 1 1 2 1 2 1 1 2 1 1 1 1 1 1 1 5211 5221 1 1 2 1 1 1 1 2 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 2 1 1 2 1 1 1 1 2 1 1 1 1 1 1 1 1 1 13 7.7 1 1 1 3 8 100 100 100 33.33 12.5 19 5.26 37 4 2.7 25 359 TABLE A.2. (CONTINUED) Village 5231 1. Chelsea 2. Brooklyn 3. Dexter 4. 5. 6. 7. 5241 1 Lake Odessa Ovid Homer Fowlerville 1 5251 1 3 1 2 2 2 3 2 2 2 1 *2 5 1 8. 9. 10. 11. 12. Addison Manchester Saranac Pinckney Caledonia 1 2 1 1 1 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 1 1 1 1 1 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapids Perrinton Springport 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons 5311 5321 5331 5341 1 1 1 1 1 5399 1 1 1 3 1 1 1 1 1 2 1 2 1 2 1 2 3 1 1 1 2 2 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3 1 Total Functional Units Location Coefficient 5252 50 50 49 41 2.04 2.44 12 16.57 100 8.33 24 100 4.17 360 TABLE A.2. (CONTINUED) Village 1 . Chelsea 2. Brooklyn 3. Dexter 5411 5 2 8 Lake Odessa Ovid Homer Fowlerviile 4 4 3 2 8. 9. 10. 11. 12. Addison Manchester Saranac Pinckney Caledonia 2 3 2 4 3 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 1 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapids Perrinton Springport 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons 4. 5. 6. 7. Total Functional Units Location Coefficient 5421 5441 5451 5462 1 1 1 1 1 1 1 1 1 1 1 1 5511 5 2 1 2 1 1 2 5521 1 5531 1 2 8 3 5 3 3 3 3 3 1 3 4 4 3 2 2 1 2 2 2 1 4 2 4 2 4 1 2 1 1 2 1 1 4 2 3 3 7 3 2 1 2 1 1 1 2 1 1 4 5541 1 1 1 2 1 2 1 3 2 2 1 1 2 2 1 2 1 1 3 1 2 1 1 1 1 1 3 2 2 1 1 1 1 3 1 1 1 1 1 93 6 3 2 5 1.08 16.67 33.33 50 20 28 3 9 102 3.57 33.33 11.11 .98 361 TABLE A . 2 . (CONTINUED) Village 1. Chelsea 2. Brooklyn 3. Dexter 4. 5. 6. 7. 5591 Addison Manchester Saranac Pinckney Caledonia 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapids Perrinton Springport 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons Total Functional Units Location Coefficient 5599 5611 1 5621 2 5631 5651 5661 5699 2 1 1 Lake Odessa Ovid Homer Fowlerville 8. 9. 10. 11. 12. 5592 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 5 20 6 1 16.67 100 5 20 11 1 9.09 100 4 4 25 25 1 100 362 TABLE A .2.(CONTINUED) Village 1. Chelsea 2. Brooklyn 3. Dexter 4. 5. 6. 7. Lake Odessa Ovid Homer Fowlerville 8. 9. 10. 11. 12. Addison Manchester Saranac Pinckney Caledonia 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapids Perrinton Springport 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons Total Functional Units Location Coefficient 5712 5713 5714 5722 1 1 1 1 5732 5812 ' 5813 1 1 1 3 5 1 4 1 2 2 1 2 2 T 2 2 2 1 1 2 2 1 2 2 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 2 1 2 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 2 1 3 2 1 1 1 5912 1 1 2 1 2 1 2 2 1 5921 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 15 1 1 3 16 31* 43 31 6.67 100 100 33.33 6.25 2.94 2.33 3.23 7 14.29 36 3 TABLE A.2. (CONTINUED) Village 1. Chelsea 2. Brooklyn 3. Dexter 4. 5. 6. 7. 5932 1 1 5933 Addison Manchester Saranac Pinckney Caledonia 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapids Perrinton Springport 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons Total Functional Units Location Coefficient 5953 5962 5969 1 2 1 Lake Odessa Ovid Homer Fowlerville 8. 9. 10. 11. 12. 5952 1 1 1 1 2 1 1 1 1 1 5971 5982 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3 2 1 1 5983 1 1 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 3 2 10 1 31 6 9 33.33 50 10 100 3.23 16.£7 11.11 5 20 6 16.67 3 64 TABLE A.2. (CONTINUED) Village 5984 1. Chelsea 2. Brooklyn 3. Dexter 4. 5. 6. 7. Lake Odessa Ovid Homer Fowlerville 8. 9. 10. 11. 12. Addison Manchester Saranac Pinckney Caledonia 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapids Perrinton Springport 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons Total Functional Units Location Coefficient 5992 2 1 5997 2 1 5999 7011 1 1 1 7216 7217 7261 7311 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 4 25 9 11.11 8 12.5 6 16.67 2 50 6 1 16.67 100 25 4 1 100 365 TABLE A.2. (CONTINUED) Village 7319 7394 Lake Odessa Ovid Homer Fowlerville 8. 9. 10. 11. 12. Addison Manchester Saranac Pinckney Caledonia 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapids Perrinton Springport 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Caines Lyons Total Functional Units Location Coefficient 7399 7513 7531 7538 7542 1 1. Chelsea 2. Brooklyn 3. Dexter 4. 5. 6. 7. 7395 1 1 7622 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 3 1 1 1 2 1 100 100 100 50 100 2 13 50 7.7 1 10 100 10 366 TABLE A. 2.(CONTINUED) Village 7629 7631 764T 1. Chelsea 2. Brooklyn 3. Dexter 4. 5. 6. 7. Addison Manchester Saranac Pinckney Caledonia 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapids Perrinton Springport 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons 7694 7933 1 1 1 3 4 1 Attorney 3 1 3 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 ‘ 1 1 1 1 1 1 1 1 1 Total Functional Units Location Coefficient 7699 1 Lake Odessa Ovid Homer Fowlerville 8. 9. 10. 11. 12. 7692 17 50 50 100 33.33 50 5.88 8 12.5 15 6.67 367 TABLE A.2. (CONTINUED) Village Bank Barber Shops 1. Chelsea 2. Brooklyn 3. Dexter 1 1 1 4. 5. 6. 7. Lake Odessa Ovid Homer Fowlerville 1 1 1 1 8. 9. 10. 11. 12. Addison Manchester Saranac Pinckney Caledonia 1 1 1 1 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 1 1 1 1 1 1 1 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapids Perrinton Springport 1 1 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons 1 Total Functional Units 36 22 89 2.78 4 .54 1.12 Location Coefficient 1 1 1 1 1 1 1 1 1 Church 1 2 1 1 2 2 2 1 1 5 2 4 Clinic 1 Dentist 3 2 2 1 1 1 5 3 5 7 4 2 3 4 2 1 2 1 1 1 1 2 2 4 6 3 1 4 1 2 1 1 Hospital 1 1 2' 1 2 1 1 3 1 1 1 1 1 1 2 2 2 1 1 1- 1 1 1 2 1 1 21 100 4.76 100 368 TABLE A.2. (CONTINUED) Village 1. 2. 3. 4. 5. 6. 7. Chelsea Brooklyn Dexter Lake Odessa Ovid Homer Fowlerville Optome­ trist Doctors Offices Schools 1 7 1 1 4 2 4 1 .1 2 3 4 1 2 1 1 1 1 Veterinerians 8. 9. 10. 11. 12. Addison Manchester Saranac Pinckney Caledonia 3 1 1 1 1 2 3 3 4 5 1 13. 14. 15. 16. 17. 18. 19. Linden Stockbridge Nashville Concord Grass Lake Fowler Bellevue 1 1 5 4 3 1 4 3 1 1 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Parma Dimondale Woodland Byron Westphalia Vernon Muir Hanover Sunfield Maple Rapid3 Perrinton Springport Webberville Freeport Bancroft Lennon Cement City Vermontville Morrice Clarksville Pewamo Muliken Hubbardston Eagle Dansville Gaines Lyons Total Functional Units Location Coefficient 1 2 1 3 1 1 1 1 1 1 3 3 1 2 1 2 4 4 1 2 1 1 1 3 1 2 1 2 1 1 1 2 50 28 97 11 3.57 1.03 9.09 Functional Index 884.66 880.19 792.87 675.66 634.81 633.15 604.84 517.26 425.60 421.12 382.30 381.93 296.06 291.07 239.74 237.17 232.12 206.40 183.42 157.77 143.17 125.26 117.65 111.20 105.38 90.22 87.28 84.43 80.02 78.74 77.50 66.76 61.66 60.46 51.94 51.77 50.45 47.10 39.32 38.31 37.21 35.13 27.06 24.33 18.23 9.75 369 TABLE A.2: 1. SIC (Standard Industrial Classification) Wholesale Trade 5013 5014 5042 5043 5044 5045 5047 5048 5049 5053 5054 5072 5074 5082 5083 5084 5085 5086 5092 5093 5094 5095 5096 5098 5099 2. Meaning of Numbers - Automotive equipment Tires and tubes Frozen foods Dairy products Poultry and poultry products Confectionery Meals and meat products Fresh fruits and vegetables Groceries and related products, n.e.c.** Grain (elevator company) Livestock Hardware Plumbing & heating equipment and supplies Construction and mining machinery and equipment Farm machinery and equipment Industrial machinery and equipment Industrial supplies Professional equipment and supplies Petroleum and petroleum products Scrap and waste materials Tobacco and its products Beer, wine, and distilled alcoholic beverages Paper and its products Lumber and construction materials Wholesalers, n.e.c. Retail Trade A. Building Materials, Hardware and Farm Equipment 5211 - Lumber and other building materials dealers 5221 - Plumbing, heating and air conditioning equipment dealers 5231 - Paint, glass and wallpaper stores 5241 - Electrical supply stores 5251 - Hardware stores 5252 - Farm equipment dealers B. General Merchandise 5311 - Department stores 5321 - Mail order houses 5331 - Variety stores 5341 - Automatic merchandising, machine operators 4399 - Miscellaneous general merchandise stores *Dun and Bradstreet Reference Book 19 70. ** Not elsewhere classified indicated by n.e.c. 370 TABLE A . 2: CONT C. Food 5411 5421 5441 5451 5461 - Grocery Stores Meat and fish (seafood) market Candy, nuts and c o n f e c t i o n e r y stores Dairy pro du cts stores Retail bakeries, baki ng and selling D. Automotive Dealers and Gasoline Service Stations 5511 - Motor vehicle de al er s (new and used cars) 5521 - Motor vehicl e de a l e r s (used cars only) 5531 - Tire, ba t t e r y and acce ss ory deale rs 5541 - Gasoline s e rvi ce stations 5591 - Boat de ale rs 5592 - House hol d trailer deale rs 5599 - Aircraft and aut om ot iv e d e a l e r s , n . e . c . E. Apparel and Accessor ie s 5611 - Men's and boys ’ cl ot h i n g and f u r n i s h i n g stores 5621 - Women' s r e a d y - t o - w e a r stores 5631 - Women's a c ce ss ory and s p ec ia lty stores 5651 - Family c l o t h i n g stores 5661 - Shoe stores 5699 - M i sc e ll an eo us apparel and ac cessory stores F. Furniture, Home Fur nis hin gs and Equipment 5712 - Fu rniture Stores 5713 - Floor co v e r i n g stores 5714 - Drapery, cu rta in and u p h o l s t e r y stores 5722 - Household ap pl ian ce stores 5732 - Radio and te le v i s i o n stores G. Eating and Dr ink in g Places 5812 - Eat ing places 5813 - Dr ink in g places (alcoholic beverages) H. M i s c e ll an e ou s Retail Stores 5912 - Drug store and- pr o p r i e t ar y stores 5921 - Liquor stores 5932 - Antique stores 5933 - Second hand stores 5952 - Sporting goods stores 5953 - Bicycle shops 5962 - Hay, grain, and feed stores 5969 - Farm and gar de n supply stores, n.e.c. 5971 - J ew e l r y stores 5982 - Fuel and ice dealers, except fuel oil d ea ler s and b o t t l e d gas d e al er s 5983 - Fuel oil de a l e r s 5984 - Li quified p e t r o l e u m gas (bottled gas) d e al er s 5992 - Florists 5997 - Gift, no vel ty and souvenir shops (gift shops) 5999 - M i s c el l a n eo us retail stores, n.e.c. 371 TABLE A.2: Cont 3. Services A. Hotels, Rooming Houses, Camps and Other Lodging Places 7011 - Hotels, tourist courts, and motels B. Personal Services 7216 - Dry cleaning and dyeing plants, except rug cleaning 7217 - Rug cleaning and repairing plants 7261 - Funeral service and crematories C. Miscellaneous Business Services 7311 - Advertising agencies 7319 - Miscellaneous advertising 7394 - Equipment rental and leasing services 7395 - Photofinishing laboratories 7399 - Business services, n.e.c. D. Automotive Repair, Automobile Services, and Garages 7513 - Truck rental and leasing, without drivers 7531 - Top and body repair shops 7538 - General automobile repair shops 7542 - Automobile laundries E. Miscellaneous Repair Services 7622 - Radio and television repair shops 7629 - Electrical repair shops 7631 - Watch, clock and jewelry repair 7 6 4 1 - Re-upholstery and furniture repair 7692 - Welding repair 7694 - Armature rewinding shops 7699 - Repair shops and related services, n.e.c. F. Amusement and Recreation Services, Pictures 7933 - Bowling Alleys Except Motion TABLE A.3. CENTRAL FUNCTIONS, LOCATION COEFFICIENTS AND FUNCTIONAL INDICES OF CENTRAL VILLAGES, 1980. Village 1. Brooklyn 2. Dexter 3. Chelsea 5013 5021 5031 5041 5051 5074 2 1 Fowlerville Saranac Manchester Linden Pinckney Homer Addison 1 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 1 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46, Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville 5083 5084 2 2 1 1 1 4. 5. 6. 7. 8. 9. 10. 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 2 2 * 1 1 1 2 1 1 1 1 1 1 1 1 1 1 Total Functional Units 10 1 4 Location Coefficient 10 100 25 Source: 5039 6 3 16.66 33.33 1 1 25 1 100 100 4 100 Author's collections based on Dun 4 Bradstreet Reference Book, 1980 and Telephone Directories, 1979-1982. 372 373 TABLE A.3. (CONTINUED) Village 1. Brooklyn 2. Dexter 3. Chelsea 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville Total Functional Units Location Coefficient 5085 5086 5087 5088 5099 1 5112 5141 5113 5143 3 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 5 2 1 20 50 100 1 100 8 1 12.5 100 1 100 2 1 50 100 374 - table A.3.(CONTINUED) Village 5144 5147 5149 1. Brooklyn 2. Dexter 3. Chelsea 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville Total Functional Units Location Coefficient 5153 5154 5159 5171 1 5172 5181 1 1 2 1 1 1 1 2 1 1 2 1 1 1 1 1 2 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 2 1 50 50 100 21 4.76 1 1 5 100 100 20 8 12.5 1 100 375 TABLE A.3 . (CONTINUED) Village 1 . Brooklyn 2. Dexter 3. Chelsea 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville Total Functional Units Location Coefficient 5191 5199 2 1 1 1 2 1 5231 1 2 1 1 1 1 1 1 1 5211 1 3 3 2 3 1 1 1 1 1 2 1 1 1 1 1 2 3 1 2 2 2 2 1 5261 5271 5311 1 1 1 1 1 1 1 1 1 1 3 2 2 1 5331 2 2 1 1 1 1 1 5251 2 3 1 1 1 1 1 2 1 2 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 2 2 1 1 2 1 1 2 1 1 1 1 2 1 1 1 1 21 16 31 4.76 6.25 3.22 4 25 48 7 2.08 14.28 5 20 3 11 33.33 9.09 376 TABLE A.3. (CONTINUED) Village 1. Brooklyn 2. Dexter 3. Chelsea 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville Total Functional Units Location Coefficient 5399 1 1 1 1 1 2 1 5411 5422 5423 5431 5441 2 2 7 5462 5499 2 1 5 1 1 6 1 2 3 3 2 2 5511 1 3 1 2 1 1 1 1 2 2 2 1 2 2 1 2 2 2 1 3 2 1 1 1 1 2 2 1 1 2 1 2 1 1 4 1 2 1 1 1 1 1 1 1 1 1 1 13 65 7.69 1.54 1 3 1 2 1 1 100 33-33 100 50 100 100 30 3.33 377 TABLE A.3.(CONTINUED) Village 5521 1. Brooklyn 2. Dexter 3. Chelsea 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville Total Functional Units Location Coefficient 5531 2 1 1 1 2 2 5541 2 2 4 3 3 1 2 1 1 1 5551 2 5561 1 5571 5599 1 5611 1 5621 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 t 1 1 3 11 38 7 33.33 9.09 2.63 14.28 2 50 3 33.33 2 50 6 12 16.66 8.33 378 TABLE A.3. (CONTINUED) Village 5641 5651 5661 5699 1. Brooklyn 2. Dexter 3. Chelsea 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville Total Functional Units Location Coefficient 5712 5713 2 5714 1 5719 5722 1 2 3 1 2 3 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 5 1 2 100 20 100 50 14 6 7.14 16.66 1 5 2 100 20 50 379 TABLE A.3. (CONTINUED) Village 1. Brooklyn 2. Dexter 3. Chelsea 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville Total Functional Units Location Coefficient 5732 5733 1 1 1 1 2 5812 5813 2 3 2 4 2 4 3 3 1 1 2 5912 3 3 2 1 1 1 2 2 5921 1 3 5931 1 5941 3 1 5944 3 1 1 1 1 4 1 2 2 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 3 2 1 1 1 3 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 2 1 11 9.09 50 36 30 22 11 2.77 3-33 4.54 9.09 15 25 6.66 14.28 380 TABLE A.3. (CONTINUED) Village 5945 1. Brooklyn 2. Dexter 3. Chelsea 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville Total Functional Units Location Coefficient 5947 2 1 2 5949 5961 5982 5983 5984 5992 2 1 1 1 5993 4 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 50 1 1 11 6 1 1 7 9.09 16.66 100 100 14.28 4 25 15 6.66 5 20 381 TABLE A.3. (CONTINUED) Village 5999 7011 1. Brooklyn 2. Dexter 3. Chelsea 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville Total Functional Units Location Coefficient 7211 7216 7217 7261 7299 7311 7312 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 4 2 1 25 50 100 1 100 1 9 100 1 11.11 100 2 1 50 100 382 TABLE A.3. (CONTINUED) Village 7374 7394 7513 7538 7542 7622 7623 7629 7641 1. Brooklyn 2. Dexter 3. Chelsea 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville Total Functional Units Location Coefficient 1 1 1 4 2 2 9 1 7 3 3 25 50 50 11.11 100 14.28 33.33 33-33 4 25 383 TABLE A.3- (CONTINUED) Village 7692 7694 1. Brooklyn 2. Dexter 3. Chelsea 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville 7699 7933 8911 1 1 1 1 1 Bank 3 1 4 2 3 1 1 1 2 1 2 1 1 1 1 1 1 1 2 3 1 3 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 Barber Shop 1 4 6 3 1 1 2 2 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Total Functional Units Location Coefficient Attorney 100 50 11.11 25 33.33 1 1 32 47 27 3-12 2.13 3.70 384 TABLE A.3. (CONTINUED) Village 1. Brooklyn 2. Dexter 3. Chelsea Church 7 8 17 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 7 3 12 12 5 6 2 11. 12. 13. 14. Stockbridge Gras3 Lake Ovid Lake Odessa 5 7 7 8 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 4344. 45. 46. Clinic 2 2 1 1 Dentist 1 5 4 Hospital Optome­ trist Doctor's Office 1 1 1 1 3 1 2 2 2 1 7 22 2 1 5 3 1 1 1 1 1 1 1 3 2 6 2 8 3 4 ' 4 1 2 1 Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 11 3 2 2 4 4 3 1 2 1 Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville 2 3 1 1 4 3 1 2 3 1 1 1 1 1 1 1 1 1 1 3 4 4 1 1 1 2 1. 1 1 9 64 11.11 1.56 4 3 3 1 Total Functional Units 195 8 36 Location Coefficient .51 12.5 2.77 1 100 385 TABLE A .3.(CONTINUED) Village 1. Brooklyn 2. Dexter 3. Chelsea Schoo 1 Veterinerian Functional Index 2 4 6 1 1 3 1,024.45 1,012.23 986.53 8 4. 5. 6. 7. 8. 9. 10. Fowlerville Saranac Manchester Linden Pinckney Homer Addison 3 3 2 2 2 2 1 2 1 2 615.25 563.19 519.41 515.13 484.33 465.47 458.00 11. 12. 13. 14. Stockbridge Grass Lake Ovid Lake Odessa 3 1 2 3 1 1 1 1 377.21 374.92 369.57 360.68 15. 16. 17. 18. 19. 20. Bellevue Hanover Nashville Fowler Dimondale Sunfield 2 2 2 2 21. 22. 23. 24. 25. 26. 27. 28. Caledonia Webberville Cement City Lennon Concord Parma Westphalia Morrice 4 2 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Vermontville Byron Muir Perrinton Freeport Bancroft Vernon Lyons Maple Rapids Pewamo Springport Muliken Woodland Eagle Clarksville Hubbardston Gaines Dansville 2 1 Total Functional Units 69 32 1.45 3.12 Location Coefficient 1 2 1 1 2 2 1 1 1 1 1 2 2 1 1 2 1 1 1 1 305.61 290.84 257.45 249.11 225.94 221.86 188.13 187.51 173.43 152.17 151.05 144.43 144.12 114.48 93.33 86.41 81.66 69.30 51.46 51.21 41.12 40.66 36.02 35.57 35.34 34.66 27.48 17.07 16.46 16.43 15.41 14.41 386 TABLE A.3: 1. Meaning of Numbers SIC (Standard Industrial Classification) Wholesale Trade A. Durable Goods 5013 - Automotive parts and supplies 5021 - Tires and tubes 5031 - Lumber, plywood and millwork 5039 - Construction materials, n.e.c.** • 5041 - Sporting and recreational goods and supplies 5051 - Metal service centers and offices 5074 - Plumbing and heating eguipment and supplies (hydronics) 5083 - Farm and garden machinery and equipment 5084 - Industrial machinery and equipment 5085 - Industrial supplies 5086 - Professional equipment and supplies 5087 - Service establishment equipment and supplies 5088 - Transportation equipment and supplies, except motor vehicles 5099 - Durable goods, n.e.c. B. Nondurable Goods 5112 - Stationery supplies 5113 - Industrial and personal service paper 5141 - Groceries, general line 5143 - Diary products 5144 - Poultry and poultry products 5147 - Confectionery 5149 - Groceries and related products, n.e.c. 5153 - Grain (elevator company) 5154 - Livestock 5159 - Farm product raw materials, n.e.c. 5171 - Petroleum bulk stations and terminals 5172 - Petroleum and petroleum products wholesalers, except bulk stations and terminals 5181 - Beer and ale 5191 - Farm supplies 5199 - Nondurable goods, n.e.c. *Dun and Bradstreet Reference Book, 1980. **Not elsewhere classified indicated by n.e.c. 387 TABLE 2. A . 3: Cont: Retail Trade A. Building Materials, Hardware, Garden Supply, and Mobile Home Dealers 5211 - Lumber and other building materials dealers 5231 - Paint, glass and wallpaper stores 5251 - Hardware stores 5261 - Retail nurseries, lawn and garden supplies stores 5271 - Mobile home dealers B. General Merchandise Stores 5311 - Department stores 5331 - Variety stores 5399 - Miscellaneous general merchandise stores C. Food 5411 5422 5423 5431 5441 5462 5499 D. Automotive Dealers and Gasoline Service Stations 5511 - Motor vehicle dealers (new and used) 5521 - Motor vehicle dealers (used only) 5531 - Auto and home supply stores 5541 - Gasoline service stations 5551 - Boat dealers 5561 - Recreational and utility trailer dealers 5571 - Motorcycle dealers 5599 - Automotive dealers, n.e.c. E. Apparel and Accessory Stores 5611 - Men's and boys' clothing and furnishings stores 5621 - Women's ready-to-wear stores 5641 - Children's and infant's wear stores 5651 - Family clothing stores 5661 - Shoe stores 5699 - Miscellaneous apparel and accessory stores F. Furniture, Home Furnishings and Equipment Stores 5712 - Furniture stores 5713 - Floor covering stores 5714 - Drapery, curtain and upholstery stores 5719 - Miscellaneous home furnishing stores 5722 - Household appliance stores 5732 - Radio and television stores 5733 - Music stores Stores - Grocery stores - Freezer & locker meat provisions - Meat and fish (seafood) markets - Fruit stores and vegetable markets - Candy, nut and confectionery stores - Retail bakeries, baking and selling - Miscellaneous food stores 388 TABLE 3. A . 3: Cont G. Eating and Drinking Places 5812 - Eating Places 5813 - Drinking places (alcoholic beverages) H. Miscellaneous Retail 5912 - Drug stores and proprietary stores 5921 - Liquor stores 5931 - Used merchandise stores 5941 - Sporting goods stores and bicycle shops 5944 - Jewelry stores 5945 - Hobby, toy and game shops 5947 - Gift, novelty and souvenir shops 59^9 - Sewing, needlework and piece goods stores 5961 - Mail order houses 5982 - Fuel and ice dealers, except fuel oil dealers and bottled gas dealers 5983 - Fuel oil dealers 5984 - Liquified petroleum gas (bottled gas) dealers 5992 - Florists 5993 - Cigar stores and stands 5999 - Miscellaneous retail> s t o r e s , n.e.c. Services A. Hotel, Rooming Houses, Camps and Other Lodging Places 7011 - Hotels, motels and tourist courts 3. Personal Services 7211 - Power laundries, family and commercial 7216 - Dry cleaning plants except rug cleaning 7217 - Carpet and upholstery cleaning 7261 - Funeral service and crematories 7299 - Miscellaneous personal services C. Business Services 7311 - Advertising agencies 7312 - Outdoor a dvertising services 7374 - Data processing services 7394 - Equipment rental and leasing services D. Automotive Repair, Services and Garages 7513 - Truck rental and leasing, without drivers 7538 - General automotive repair shops 7542 - Car washes E. Miscellaneous Repair Services 7622 - Radio and television repair shops 7623 - Refrigeration and air conditioning service and repair shops 7629 - Electrical and electronic repair shops, n.e.c. 389 TABLE E. F. .3 : Cont Cont. 7641 7692 7694 7699 - Reupholstery and furniture repair Welding repair Armature rewinding shops Repair shops and related services, Amusement and Recreation Services, Pictures 7933 - Bowling Alleys n.e.c. except Motion Miscellaneous Services 8911 - Engineering, architectural and surveying services TABLE A.4: Services Offered in the Central Villages of Southcentral Michigan, 1950 Types of Functional Location CoServices Units efficient {Func tions )______ (N )___________ LC = 1/N*100 Rank .86 1 116 Grocery Stores 107 .93 2 Service Stations 1.43 Filling Stations 70 3 Hardware Stores 53 1 .89 4 Res tau ran t 49 2 .04 5 42 2.38 6 Drugs & Misc. 7 2 .56 General Store 39 2.63 Food Stores & Misc. 36 8 2 .70 Automobiles & Tractors37 9 Taverns 33 3.03 10 Implements (Agricul.) 30 3 .33 11 Electric Supplies 29 3.45 12 (Sales & Service) Gar ages 3.57 28 13 3 .70 Variety & Gift Shops 27 14 26 Auto Body Shops 3 .85 15 Funeral Homes & Mor tic ians 26 3 .85 15 General Hardware 26 3 .85 15 Plumbing & Heating 25 4 .00 16 Machine Shops & Supplies 25 4 .00 16 Confectionery & Misc. 21 17 4 .76 Elevator (Implements Fuel, Feed & Lumber) 20 5 .00 18 Furniture Stores 18 5 .55 19 Jewelry Stores 17 5 .88 20 Publishing & Printing 1 7 5 .88 20 Auto Supply (Sales & Ser vice ) 17 5 .88 20 Shoe & Harness Repair 15 6 .66 21 Elevator (grain. beans, soybeans) 15 6 .66 21 Oil & Gas (Dist.Co) 15 6 .66 21 Radio (Sales & Serv.) 14 7.14 22 Men's Wear & Misc. 14 7.14 22 Lunchrooms 13 7.69 23 Mea t 12 8.33 24 Welding 6. Repair 12 8 .33 24 First Order Villages N Average 9 9 .00 8 8.00 0 0.00 2 2.00 5 5 .00 3 3 .00 1 1 .00 2 2.00 0 0 .00 2 2 .00 3 3 .00 1 1 .00 Second Order Third Order Fourth Order Villages Villages Villages N Average N Average N Average 4 4 .00 24 3 .00 19 3.40 1 1 .00 28 4 .00 21 3 .50 15 5 5 .00 2.10 11 1 .80 2 2.00 11 1 .60 9 1 .50 2 2 .00 12 10 1 .70 1 .70 2 11 2 .00 1 .57 8 1 .34 0 7 1.17 0.00 5 .71 1 7 1 .17 1 .00 10 1 .43 17 2 2 .00 9 1 .50 2.42 3 3 .00 9 3 1 .29 .50 0 0.00 8 5 1.14 .83 7 1.17 3 4 .57 3.00 Fifth Order Villages N Average 25 4 .20 23 2.10 11 1 .00 9 .80 7 .64 10 .91 13 1.18 9 .82 6 .55 4 .36 7 .64 8 .73 Sixth Order Villages N Average 35 1.75 26 1 .30 28 1 .40 20 1 .00 13 .65 8 .40 13 .65 9 .45 3 .15 12 .60 7 .35 6 .30 0 1 3 0 .00 1 .00 3 .00 2 1 0 2.00 1 .00 0 .00 3 11 8 .43 1 .57 1.14 2 7 5 .34 1 .17 .83 6 2 2 .55 .18 .18 15 5 8 .75 .25 .40 1 2 0 1 .00 2 .00 0 .00 0 1 0 0 .00 1 .00 0.00 6 4 10 .86 .57 1.43 4 5 7 .67 .83 1.17 7 7 4 .64 .64 .36 8 7 4 .40 .35 .20 5 1 5 .00 1 .00 1 3 1 .00 3 .00 2 7 .29 1 .00 6 4 1 .00 .67 6 1 .55 .09 5 5 .25 .25 0 0 2 1 0.00 0 .00 2 .00 1 .00 1 1 2 1 1 .00 1 .00 2.0.0 1.00 6 6 8 6 .86 .86 1 .14 .86 2 2 1 4 .34 .34 .17 .67 3 4 3 2 .27 .36 .27 .18 8 5 1 3 .40 .25 .05 .15 2 1 2 .00 1 .00 3 0 3 .00 0.00 4 4 .57 .57 2 4 .34 .67 4 3 .36 .27 2 3 .10 .15 0 1 1 2 1 1 0 0 .00 1 .00 1 .00 2 .00 1 .00 1 .00 0.00 0 1 0 2 0 0 0 0.00 1 .00 0 .00 2.00 0 .00 0 .00 0 .00. 3 3 4 5 3 6 5 .43 .43 .57 .71 .43 .86 .71 1 3 4 2 4 1 1 .17 .50 .67 .34 .67 .17 .17 5 4 3 0 4 2 3 .45 .36 .27 0 .00 .36 .18 .27 6 3 2 3 1 2 3 .30 .15 .10 .15 .05 .10 .15 TABLE A .4 : Cont Types of Functional Location CoServices Units efficient (Functions )______ (N )___________ LC=1/N*100 Rank Dry Cleaners & Laundry 1L 9.09 25 Women’s 6. Children’s 11 9 .09 25 Dry Goods Dairy Products 10 10.00 26 Farm Machinery 10.00 26 10 Feed Stores 10.00 26 10 Food Lockers 10.00 26 10 Florist (Greenhouse) 10 10.00 26 27 Paint & Wallpaper 11 .11 9 28 Plumbing 8 12 .50 12.50 28 Telephone Co.& Service 8 Fuel, Coal, Feed,etc. 7 14.28 29 7 Produce Co. 14 .28 29 7 29 Sporting Goods 14.28 16.67 Bakery & Misc. 30 6 General Store & Misc. 6 16.67 30 Women's Wear Shop 16.67 30 6 B1acksmi th 20.00 31 5 Flour & Feed 20 .00 5 31 Flour Mi 11ing 5 20 .00 31 Trucking 20.00 31 5 25.00 32 Auto-Farm Implements 4 Books & Newspapers 25 .00 4 32 Dairy Products & Pou11ry 4 25 .00 32 Fr u its 25 .00 32 4 Hotel & Misc. 25 .00 32 4 Pr int ing 25 .00 4 32 Vegetables 4 25.00 32 Wei 1 Dri 11 ing 25.00 32 4 Beverage Dealers 33 .33 3 33 Bi11iards 3 33.33 33 Bowling 3 33. 33 33 Cider & Vinegar 33.33 33 3 Department Store 33 .33 33 3 33.33 33 House Furnishings 3 Household Goods 33.33 33 3 Men’s, Women's & Child133.33 33 3 ren's Wear First Order Second Order Third Order Fourth Order Villages Villages Villages Villages N Average N Average N Average N Average Fifth Order Sixth Order Villages Villages N Average N Average 1 1 .00 2 2.00 4 .57 2 .34 1 .09 1 .05 2 1 2 1 0 2 1 2 0 0 0 0 0 1 0 0 1 1 0 0 0 2 .00 1 .00 2.00 1 .00 0 .00 2.00 1 .00 2 .00 0.00 0.00 0.00 0.00 0 .00 1 .00 0.00 0.00 1 .00 1 .00 0.00 0 .00 0.00 1 2 1 0 1 1 0 1 0 1 2 1 0 0 2 0 0 0 0 1 1 1 .00 2.00 1.00 0.00 1.00 1 .00 0.00 1 .00 0.00 1 .00 2.00 1 .00 0.00 0.00 2 .00 0 .00 0.00 0.00 0 .00 1 .00 1 .00 2 2 2 2 2 2 2 0 2 5 1 3 5 3 2 3 2 1 3 0 0 .29 .29 .29 .29 .29 .29 .29 0.00 .29 .71 .14 .43 .71 .43 .29 .43 .29 .14 .43 0.00 0.00 1 3 2 3 3 4 1 2 2 0 2 2 1 2 1 0 1 2 0 0 0 .17 .50 .34 .50 .50 .67 .17 .34 .34 0.00 .34 .34 .17 .34 .17 0 .00 .17 .34 0.00 0.00 0.00 3 1 1 1 2 0 2 3 2 0 2 0 0 0 0 1 1 1 1 2 3 .27 .09 .09 .09 .18 0.00 .18 .27 .18 0.00 .18 0.00 0.00 0.00 0.00 .09 .09 .09 .09 .18 .27 2 1 2 3 2 1 3 0 2 1 0 1 0 0 1 1 0 0 1 1 0 .10 .05 .10 .15 .10 .05 .15 0 .00 .10 .05 0.00 .05 0 .00 0.00 .05 .05 0.00 0 .00 .05 .05 0 .00 0 0 1 0 0 0 0 1 0 0 1 0 0 0 .00 0.00 1 .00 0.00 0.00 0 .00 0.00 1 .00 0 .00 0 .00 1 .00 0 .00 0 .00 0 1 0 0 0 0 0 0 0 0 1 0 0 0.00 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0 .00 0 .00 1 .00 0.00 0 .00 0 0 1 0 0 0 2 0 3 2 0 1 1 0 .00 0.00 .14 0.00 0.00 0.00 .29 0 .00 .43 .29 0 .00 .14 .14 1 1 0 1 2 1 0 1 0 1 1 2 1 .17 .17 0 .00 .17 .34 .17 0.00 .17 0.00 .17 .17 .34 .17 3 2 2 1 1 3 1 0 0 0 0 0 0 .27 0 .18 0 .18 0 .09 2 .09 1 .27 0 .09 0 .09 0 0.00 0 0 .00 . 0 0.00 0 0.00 0 0.00 1 0 .00 0 .00 0.00 .10 .05 0.00 0 .00 0 .00 0 .00 0 .00 0.00 0.00 .05 1 1 .00 0 0 .00 1 .14 1 .17 0 0.00 0 .00 0 TABLE A.4: Cont Types of Functional Services Units (Functions) (N) Nurseries 3 Patent Medicines 3 Publishing 3 Shoes 3 An tiques 2 Chemical & Allied Products 2 Family Clothing 2 Dress Shops 2 Hauling 2 Photo 2 Tractors 2 Trailers 2 Viol ins 2 Auto Wash 1 Bicycles 1 Boats 1 Farm Grocery 1 Heating 1 Household Special ties 1 Millinery 1 Pharmacy 1 Pumps Recreation 1 Hospi ta1 Equlpment 1 llphois ter ing 1 yarn 1 Total Functional Uni ts SOURCE: Table A .1 1301 Location Coefficient LC=1/N*10G Rank 33.33 33 33.33 33 33.33 33 33.33 33 50.00 34 First Order Second Order Third Order Fourth Order Villages Villages Villages Villages N Average N Average N Average N Averaqe 0 0.00 0 0.00 2 .29 1 .17 0 0.00 0 0.00 0 0.00 0 0 .00 0.00 0 1 1.00 1 .14 1 .17 1 1 1 .00 1 1 .00 .14 0 0 .00 0 0 .00 0 0.00 0 0.00 1 .17 Fifth Order Villages N Average 0.00 0 .09 1 0.00 0 0 .00 0 .09 1 50 .00 50 .00 50.00 50.00 50.00 50.00 50.00 50 .00 100.00 100.00 100.00 100.00 100.00 100 .00 100 .00 100 .00 100.00 100 .00 100.00 100 .00 100.00 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 34 34 34 34 34 34 34 34 35 35 35 35 35 35 35 35 35 35 35 35 35 0.00 0.00 0.00 0.00 1 .00 0.00 0.00 0.00 1 .00 0.00 0.00 0 .00 0 .00 1 .00 0.00 0.00 1 .00 1 .00 0 .00 0 .00 0.00 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0.00 0.00 0.00 0.00 0.00 1 .00 0.00 0.00 0.00 0.00 0.00 0.00 0 .00 0 .00 0.00 0 .00 0 .00 0.00 0 .00 0 .00 1 .00 2 2 1 1 1 0 1 2 0 0 0 1 0 0 1 1 0 0 1 0 0 .29 .29 .14 .14 .14 0.00 .09 .29 0.00 0.00 0.00 .14 0.00 0.00 .14 .14 0.00 0.00 .14 0.00 0.00 0 0 1 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0.00 0.00 .17 0.00 0.00 .17 0.00 0.00 0 .00 0.00 .17 0.00 .17 0.00 0.00 0.00 0 .00 0.00 0.00 0 .00 0.00 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 0.00 .09 0.00 0.00 .09 0.00 0.00 .09 0.00 0.00 0.00 0 .00 0 .00 0.00 0 .00 0 .00 0 .00 .09 0.00 Sixth Order Villages N Average 0 0.00 2 .10 0 0.00 0 0.00 0 0.00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0 .00 0 .00 0.00 0.00 0 .00 0 .00 0 .00 0.00 0.00 0 .00 0 .00 0 .00 0.00 0 .00 0 .00 0.00 0 .00 0.00 0 .00 0.00 TABLE A.5: Services Offered in the Central Villages of Southcentral Michigan, Types of Functional Location CoServices Units efficient (Functions)______ (Nj___________ LC=1/N*100 Rank Gas Service 1 Stations 102 .98 2 Grocery Stores 93 1 .08 Hardware Stores 49 3 2 .04 Drinking Places (Bars and Taverns) 43 2.33 4 5 Farm Equipment dealers 41 2 .44 Lumber & Building Materials Dealers 37 2.70 6 Eating Places 34 7 2 .94 Drug Stores 31 3.23 8 Feed Stores 31 8 3.23 Motor Vehicle Dealers 28 3.57 9 Funeral Services & Cremator ies 25 10 4 .00 Misc. General Merchan­ dise Store 4.17 11 24 Wholesalers 19 5 .26 12 Repair Shops & Services 17 5.88 13 Radio & TV Stores 16 6 .25 14 Furniture Stores 15 6.67 15 General Automobile Repair Shops 16 13 7.70 Petrol. & Petrol. Products 13 7.70 16 Variety Stores 17 12 8.33 Women's ready-to9 .09 wear Stores 11 18 Radio/TV Repair Shops 10 10.00 19 Sporting Goods Stores 10 10.00 19 Florists 9 11 .11 20 Jewelry Stores 9 20 11.11 Tire. Battery & Accessories Dealers 20 9 11.11 Bowling A1leys 8 12 .50 21 Gift Shops 12.50 8 21 1970 First Order Villages N Average Second Order Third Order Fourth Order Villages Villages Villages N Average N Average N Average Fifth Order Sixth Order Villages Villages N Average N Average 16 15 5 5.33 5 .00 1 .70 12 13 9 3 .00 3.25 2.25 16 14 6 7 4 2.33 1 .33 6 10 1 .50 2 .50 3 9 5 3 8 1 .00 3 .00 1 .70 1 .00 2.70 6 3 6 7 6 5 1 .70 2 3 3.2 2.8 1.2 24 17 9 3 .43 2.43 1 .29 17 16 13 1.42 1 .33 1 .08 17 18 7 1.13 1 .20 .47 6 3 1 .2 .60 6 10 .86 1 .43 9 3 .75 .25 9 11 .60 .73 1 .50 .75 1 .50 1 .75 1 .50 3 7 5 4 5 .60 1 .40 1 .00 .80 1 .00 9 8 7 6 8 1 .29 1 .14 1 .00 .86 1 .14 11 4 5 7 0 .92 .33 .42 .58 0 .00 5 3 3 4 1 .33 .20 .20 .27 .07 1 .25 4 .80 7 1 .00 4 .33 4 .80 .67 1 .00 3 5 .75 1 .25 6 3 1 .20 .60 6 5 .86 .71 2 2 .17 .17 5 1 .33 .07 7 3 2 2.33 1 .00 .67 3 2 3 .75 .50 .75 1 6 1 .20 1 .20 .20 1 2 6 .14 .29 .86 4 2 3 .33 .17 .25 1 1 0 .07 .07 0.00 1 .33 2 .50 2 .40 3 .43 1 .08 4 .27 2 2 .67 .67 5 2 1 .25 .50 2 1 .40 .20 1 5 .14 .71 1 1 .08 .08 2 1 .13 .07 2 3 1 2 3 .67 1 .00 .33 .67 1 .00 2 2 2 2 2 .50 .50 .50 .50 .50 4 3 3 1 2 .80 .60 .60 .20 .40 2 1 3 4 1 .29 .14 .43 .57 .14 0 1 1 0 0 0 .00 .08 .08 0.00 0 .00 1 0 0 0 1 .07 0.00 0 .00 0 .00 .07 3 3 3 1 .00 1 .00 1 .00 3 2 0 .75 .50 0 .00 0 1 1 0 .00 .20 .20 1 2 2 .14 .29 .29 1 0 0 .08 0 .00 0 .00 1 0 2 .07 0.00 .13 TABLE A.5: Cont Fourth Order Villages N Average Fifth Order Sixth Order Villages Villages N Average N Average 2 2 2 1 2 2 .29 .29 .29 .14 .29 .29 2 0 1 2 0 0 .17 0 .00 .08 .17 0 .00 0.00 1 0 2 0 0 0 .07 0 .00 .13 0 .00 0 .00 0.00 2 1 .29 .14 0 1 0 .00 .08 1 1 .07 .07 1 0 0 1 1 .14 0.00 0.00 .14 .14 1 2 1 1 0 .08 .17 .08 .08 0 .00 0 0 1 0 0 0 .00 0 .00 .07 0 .00 0 .00 0 0 0 1 0 .00 0.00 0 .00 .14 0 0 1 1 0 .00 0 .00 .08 .08 0 0 0 1 0.00 0 .00 0 .00 .07 1 1 0 0 .14 .14 0 .00 0 .00 2 1 0 1 .17 .08 0 .00 .08 0 0 0 0 0.00 0.00 0 .00 0.00 1 .14 1 .08 0 0 .00 1 0 1 .14 0 .00 .14 0 2 0 o o o Types of Functional Location CoFirst Order Second Order Third Order Services Units efficient Villages Villages Villages (Functions)______ (N)___________ LC=1/N*100 Hank N Average N Average N Average Lumber & Const, Materials 12.50 21 1 .33 1 .25 .20 8 1 Dairy Products 7 14 .29 22 1 .33 1 .25 3 .60 Grain Elevators 7 14 .29 22 1 .33 1 .25 0 0 .00 Liquor Stores .67 7 14 .29 22 2 2 .50 0 0.00 Department Stores 6 16.67 23 3 1 .00 1 .25 0 0 .00 .67 Dry Cleaning 6 16.67 23 .50 0 0 .00 2 2 Farm/Garden Supply Stores 16.67 23 0 0.00 .75 0 .00 6 3 0 Fuel Oil Dealers 16.67 23 0.00 .75 0 .00 6 0 3 0 House Trailer 16.67 23 .33 Dealers 6 1 1 .25 2 .40 Meat & Fish Market 16.67 23 .33 6 1 2 .50 .20 1 Misc. Retail Stores 6 23 1 .00 16.67 3 1 .25 0.00 0 Boat Dealers 20.00 0 .00 5 24 1 .33 0 2 .40 Fuel & Ice Dealers 20 .00 5 24 1 .33 2 .50 1 .20 Men 's 6, Boy s * Clothing Store 5 20.00 24 2 .67 .50 .20 2 1 Retail Bakeries 5 20 .00 24 1 .33 1 .25 .60 3 Automotive Equipment 4 25.00 25 .67 2 1 .25 0 0 .00 Family Cothing Stores 4 25 .00 25 0 0.00 1 .25 0 0.00 Liquified Petro/Gas Dealers 25.00 25 .25 0.00 4 0 0.00 1 0 .67 Plumbing & Heating 25 .00 25 2 0 .00 0 0.00 4 0 Shoe Stores 4 25 .00 25 0 0.00 .50 .40 2 2 26 .67 Antique Sthores 3 33.33 2 0.00 0 .00 0 0 Candy/Confee tionary Stores 3 33.33 26 0 0 .00 0 .00 1 .25 0 Household Appliance Stores 26 3 33.33 1 .33 0 0 .00 .20 1 Meat & Fish Products 3 33.33 26 1 .33 0 0.00 0 0 .00 Used Car Dealers 33.33 26 .33 3 1 1 .25 0 .00 0 Paper & Paper Produc ts 33.33 26 1 .33 .50 3 2 0 0 .00 Poultry 6, Poultry 0.00 33.33 26 0 2 .50 0 .00 Products 3 0 26 0 0.00 0 .00 Tires & Tubes 33.33 2 .50 3 0 33.33 26 1 .33 0 0 .00 .20 Melding Repair 3 1 .1 7 0 .00 0 0 0 0 .00 0.00 0.00 0 0 .00 0 0 .00 0 0 .00 1 0 0 .14 0.00 0 .00 0 0 0 0 .00 0 .00 0 .00 0 1 1 0 .00 .07 .07 TABLE A .5: Cont Types of Functional Location CoServices ' Units efficient (Func ti o n s )______ (N)___________ LC=1/N*100 Rank Armature Rewinding 2 50.00 27 Business Services 2 50 .00 27 Dairy Product Stores 2 50.00 27 Electrical Repair 50 .00 27 Shops 2 Electrical Supply Stores 27 2 50 .00 Frozen Poods 2 50.00 27 Hotels, Tourist Courts 6, Motels 2 50.00 27 Paint, Glass & Wall­ paper Stores 2 50.00 27 Second Hand Stores 2 50.00 27 Top & Body Repair Shops 2 50.00 27 Watch, Clock 6, Jewelry Repair 2 50 .00 27 100 .00 Advertising Agency 1 28 Aircraft 6. Auto­ motive Dealers 1 100.00 28 Automatic Machinery 1 100.00 28 Car Washes 100.00 1 28 Beer, Wine, Beverages 1 100.00 28 Bicycle Shops 1 100.00 28 Confee tionery 1 100.00 28 Construction 6, Mining Equipment 100.00 1 28 Drapery, Curtain & Upholstery Stores 100.00 1 28 Equipment Rental & 100.00 Leasing 1 28 Farm Machinery & 100.00 Equ ipmen t 1 28 Floor Covering Store 1 100.00 28 Fresh Fruits & Veye tables 100.00 28 1 Groceries 6* Related 100.00 28 Products 1 First Order Villages N Average Second Order Third Order Fourth Order Villages Villages Villages N Average N Average N Average Fifth Order Sixth Order Villages Villages N Average N Average 0 0 1 0.00 0.00 .33 1 0 0 .25 0.00 0.00 0 0 0 0.00 0 .00 0.00 0 1 1 0 .00 .14 .14 1 1 0 .08 .08 0.00 0 0 0 0 .00 0 .00 0.00 0 0.00 0 0.00 1 .20 1 .14 0 0.00 0 0.00 1 0 .33 0 .00 1 0 .25 0.00 0 0 0.00 0 .00 0 1 Q.OO .14 0 1 0 .00 .08 0 0 0 .00 0 .00 0 0 .00 0 0 .00 0 0 .00 1 ,14 1 .08 0 0 .00 0 1 0.00 .33 0 0 0.00 0.00 0 1 0.00 .20 1 0 .14 0.00 1 0 .08 0.00 0 0 0.00 0 .00 0 0.00 0 0.00 0 0.00 0 0.00 2 .17 0 0 .00 0 0 0 .00 0.00 1 0 .25 0 .00 1 1 .20 .20 0 0 0.00 0.00 0 0 0 .00 0.00 0 0 0.00 0.00 0 1 1 1 0 0 0.00 .33 .33 .33 0.00 0.00 1 0 0 0 1 1 .25 0.00 0.00 0.00 .25 .25 0 0 0 0 0 0 0.00 0 .00 0.00 0.00 0.00 0.00 0 0 0 0 0 0 0.00 0.00 0 .00 0.00 0.00 0.00 0 0 0 0 0 0 0 .00 0 .00 0.00 0 .00 0.00 0.00 0 0 0 0 0 0 0 .00 0.00 0 .00 0.00 0 .00 0.00 0 0.00 0 0.00 1 .20 0 0.00 0 0.00 0 0 .00 0.00 0 0.00 0 0.00 0 .00 1 .33 0 0.00 0 0.00 0 0 0 .00 0 0 .00 0 0 .00 1 .14 0 0.00 0 0 0 0.00 0 .00 1 0 .25 0 .00 0 1 0 .00 .20 0 0 0.00 0.00 0 0 0 .00 0 .00 0 0 0.00 0 .00 1 .33 0 0 .00 0 0.00 0 0.00 0 0 .00 0 0 .00 0 0.00 0 0.00 1 .20 0 0 .00 0 0 .00 0 0 .00 TABLE A.5: C ont: Types of Functional Location CoFirst Order Second Order Third Order Fourth Order Fifth Order Sixth Order Services Units efficient Villages Villages Villages Villages Villages Villages (Functions) (N) Average N LC=1/N*l00 Rank N Averaqe N Averaqe N Averaqe N Average N Averaqe Hardware (wholesale) 1 100 .00 28 0 0.00 1 .25 0 0.00 0 0.00 0 0.00 0 0.00 Industrial Mach­ inery £. Equipment 1 100.00 28 0 0.00 0 0 1 0 0.00 0.00 0.00 .14 0 0.00 100 .00 Industrial Supplies 1 28 1 .33 0 0.00 0 0.00 0 0 .00 0.00 0 0 0.00 Livestock (wholesale)1 100.00 28 0.00 0 0 0 0.00 1 .20 0.00 0 0 .00 0 0.00 Mail Order Houses 100.00 1 28 0 0.00 1 0 0.00 0 0.00 .25 0.00 0 0 0.00 28 Misc. Advertising 1 100.00 0 0.00 1 0 0.00 0 0 0.00 .25 0.00 0 0.00 Misc. Apparel & Accessory 1 100.00 28 0 1 0 0.00 .25 0 0 .00 0 .00 0 0.00 0 0 .00 Pho tof inishing Laboratory 1 100.00 28 1 .33 0 0 .00 0 0 .00 0 0.00 0 0 .00 0 0.00 Plumbing 6. Heating Equip. 6. Supplies 1 100.00 28 0 0 .00 1 .25 0 0.00 0 0 0 .00 0.00 0 0.00 Professional Equlpment 6. Supplies 1 100.00 26 1 0 .33 0.00 0 0 .00 0 0.00 0 0 .00 0 .00 0 Reupholstery & Furniture Repair 1 100.00 28 0 0.00 0 0 0.00 1 .20 0.00 0 0 .00 0.00 0 Rug Cleaning £> Repair 1 100.00 28 0 .00 0 0 0 0.00 1 .20 0.00 0 0 .00 0 0.00 Scrap & Waste Materials 1 100 .00 28 0.00 1 0 0 .25 0 0.00 0.00 0 0.00 0 0.00 Tobacco £. Tobacco Produc ts 28 1 100.00 0 0.00 0 0 .00 .20 0 1 0.00 0 0.00 0 0 .00 Truck Rental & Leasing 1 100 .00 28 0 0.00 0 0.00 1 0 .20 0.00 0 0 .00 0 0 .00 Women’s Accessory and1 Specialty Store 1 100.00 28 0 1 .33 0.00 0 0.00 0 0 0.00 0.00 0 0.00 Total Functional Units 907 SOURCE; TABLE A.2 services taken from telephone directories (Attorneys to Veterinarians) that are used in the tables of functional indexes for the villages in 1970 and 1980 are not shown here due to the lack of data for 1950. TABLE A.6; Services Offered in the Central Villages of Southcentral Michigan, 1980 Types of Functional Services Units (Functions) (N) 65 Grocery Stores 48 Hardware Stores 38 Gas Service Stations 36 Eating Places Lumber & Building Materials 31 Drinking Places (Bars £. Taverns) 30 Motor Vehicle Dealers (New and Used) 30 Farm 6. Garden Machinery25 Drug Stores 22 Farm Supplies 21 Grain Elevator 21 Nondurable goods 16 Florists 15 Sporting Goods Stores 15 Furniture Stores 14 Misc. General Merchan­ dise Stores 13 Women's Ready-to-Wear Stores 12 Auto £• Home Supply Stores 11 Gift Shops 11 Liquor Stores 11 Radio & TV Stores 11 Variety Stores 11 10 Auto Parts/Supplles Funeral Services & Crema tor ies 9 General Auto Repair Shops 9 Repair Shops 9 Durable Goods 6 Pet roleuin 8 7 Boat Dealers 7 Fuel Oil Dealers 7 Jewelry Stores Radio & TV Repair Shops 7 Location Coeff icient Lt=l/N*100 Rank 1 .54 1 2.08 2 2.63 3 2 .77 4 First Order Vi 11 ages N Average 11 3.67 4 1 .33 8 2.67 9 3 .00 Second Order Vi ilages N Average 19 2.71 13 1.86 12 1 .71 9 1 .29 Third Order Villages N Average 7 1 .75 6 1 .50 3 .75 4 1 .00 Fourth Order Villages N Average 10 1.67 8 1 .33 .67 4 5 .83 Fifth Order Villages N Average 14 1 .75 5 .62 6 .75 .87 7 Sixth Order Vi 11 ages N Average .22 4 .67 12 5 .28 2 .11 3 .22 5 4 1 .33 8 1 .14 5 1 .25 4 .67 3 .37 7 .39 3 .33 6 4 1 .33 6 .86 2 .50 5 .83 5 .62 a .44 3 .33 4 .00 4 .54 4 .76 4 .76 6.25 6 7 8 8 4 7 4 4 2 3 5 3 1.14 .57 1.00 .57 .57 .29 .43 .71 .43 1 5 3 3 5 1 2 1 3 .17 .63 .50 .50 .83 .17 .33 .17 .50 5 5 2 2 4 1 4 0 1 i 4 4 2 2 2 1 .75 .75 .50 1 .50 1 .00 1 .00 .50 .50 .50 .62 .62 .25 .25 .50 .12 .50 0 .00 .12 4 0 5 3 5 0 3 7.14 2.67 1 .33 2.67 .33 .33 1 .00 1 .33 1 .33 1.67 7 3 9 10 11 11 12 8 4 8 1 1 3 4 4 5 0 .06 .22 0.00 .28 .17 .28 0 .00 .17 0.00 7 .69 13 1 .33 4 .57 2 .50 1 .17 2 .25 3 .17 8.33 14 4 1 .33 5 .71 2 .50 1 .17 0 0 .00 0 0 .00 9 .09 9.09 9 .09 9 .09 9 .09 10.00 15 15 15 15 15 16 2 5 4 2 3 3 .67 1 .67 1 .33 .67 1 .00 1 .00 3 4 2 4 2 1 .43 .57 .29 .57 .29 .14 3 0 4 3 2 3 .75 0.00 1 .00 .75 .50 .75 1 1 2 0 1 0 1 1 .25 0 .00 .12 0 .00 .12 .12 0 0.00 1 3 1 .17 .17 0 .00 .17 .50 .17 1 0 1 0 1 .06 0 .00 .06 0 .00 .06 11.11 17 2 .67 2 .29 2 .50 0 0 .00 1 .12 2 .11 11.11 17 17 18 18 19 19 19 19 3 1 5 3 2 0 4 0 1 .00 1 1 2 3 2 2 2 4 1 2 0 1 1 2 1 2 .25 .50 0 .DO .25 .25 .50 .25 .50 1 1 .17 .17 0 .33 1 .67 1 .00 .67 0.00 1 .33 .14 .14 .29 .43 .29 .29 .29 .57 0 .00 .25 3 2 0 1 0 0 .17 .11 0.00 .06 0.00 0.00 0 0 .00 1 .06 6.66 6 .66 11 .11 12.50 12.50 14 .28 14 .28 14.28 14 .28 9 0 .00 2 6 0 2 1 0 0 .00 0 1 0.00 .17 .17 0 1 2 .12 0.00 .12 .25 0 .00 0 .00 0 0 0 .00 0 .00 1 0 0 TABLE A.6: Cont Types of Functional Services Units (Functions) (N) 7 Retail nurseries Construction Mater ials 6 Floor Covering Stores 6 Men*s & Boys'Clothing 6 Sewing Stores 6 Cigar Stores 5 Family Clothing Stores 5 Indus tri al Suppli es 5 Misc. Home Furnishings 5 Mobile Home Dealers 5 Petrol (Bulk) Stations 5 Bowling Alleys 4 Data Processing Services4 Liq.. Petrol. Gas Dealers 4 Lumber, Plywood and Miliwork 4 Misc. Retail Stores 4 Paint, Glass & Wall­ paper Stores 4 Reupholstery & Furni­ ture Repair 4 Used Merchandise Stores 4 Department Stores 3 Electrical and Electron­ ic Repair Shops 3 Engineering Services 3 Meat & Fish Markets 3 Motorcycle Dealers 3 Used Car Dealers 3 Re frig. & Air Condi­ tioning 3 Sporting & Recreational Goods/Supplles 3 Adver tising Agencies 2 Armature Rewinding Shops2 Automotive Dealers 2 Candy and Confectionery 2 Confectionery 2 Equipment Rental/Leasing2 Groceries (Gen.Line) 2 Location Co­ efficient LC=1/N*l00 Rank 19 14 .28 First Order Villages N Average 2 .67 Second Order Third Order Villages Villages N Averaqe N Average 1 0.00 .14 0 Fourth Order Villages N Average 2 .33 Fifth Order Villages N Average 1 .12 Sixth Order Villages N Averaqe 1 .06 16 .66 16.66 16.66 16 .66 20 .00 20.00 20.00 20 .00 20 .00 20.00 25 .00 25 .00 25.00 20 20 20 20 21 21 21 21 21 21 22 22 22 1 2 2 1 4 0 3 1 0 0 2 3 0 .33 ..67 .67 .33 1.33 0.00 1 .00 .33 0 .00 0.00 .67 1 .00 0 .00 3 3 3 2 0 1 1 0 1 2 0 1 2 .43 .43 .43 .29 0.00 .14 .14 0 .00 .14 .29 0.00 .14 .29 2 0 1 0 0 2 1 0 0 0 1 0 0 .50 0.00 .25 0.00 0.00 .50 .25 0 .00 0 .00 0.00 .25 0.00 0 .00 0 0 0 0 0 2 0 1 2 1 1 0 1 0.00 0.00 0 .00 0 .00 0 .00 .33 0 .00 .17 .33 .17 .17 0 .00 .17 0 1 0 3 1 0 0 3 2 0 0 0 0 0 .00 .12 0 .00 .37 .12 0 .00 0 .00 .37 .25 0.00 0.00 0 .00 0 .00 0 0 0 0 0 0 0 0 0 2 0 0 1 0.00 0.00 0 .00 0 .00 0.00 0.00 0 .00 0 .00 0.00 .11 0.00 0.00 .06 25.00 25 .00 22 22 0 0 0.00 0.00 1 2 .14 .29 0 1 0.00 .25 1 1 .17 .17 1 0 .12 0 .00 1 0 .06 0.00 25 .00 22 1 .33 1 .14 0 0.00 0 0 .00 1 .12 1 .06 25 .00 25.00 33 .33 22 22 23 0 1 2 0 .00 .33 .67 2 1 0 .29 .14 0.00 1 0 1 .25 0 .00 .25 1 0 0 .17 0 .00 0.00 0 2 0 0 .00 .25 0.00 0 0 0 0 .00 0 .00 0.00 33.33 33.33 33.33 33.33 33.33 23 23 23 23 23 1 0 0 1 0 .33 0 .00 0 .00 .33 0.00 1 0 1 0 2 .14 0 .00 .14 0.00 .29 1 2 0 1 0 .25 .50 0.00 .25 0.00 0 1 1 0 1 0 .00 .17 .17 0.00 .17 0 0 1 0 0 0 .00 0 .00 .12 0 .00 0.00 0 0 0 1 0 0 .00 0 .00 0.00 .06 0.00 33.33 23 0 0 .00 1 .14 0 0.00 1 .17 0 0 .00 1 .06 33.33 50.00 50.00 50.00 50,00 50.00 50.00 50 .00 23 24 24 24 24 24 24 24 0 0 0 0 0 0 0 0 0 .00 0 .00 0.00 0 .00 0.00 0 .00 0 .00 0 .00 2 .29 .14 0.00 0.00 .29 .29 .14 .29 0 1 0 0 0 0 0 0 0.00 .25 0.00 0.00 0.00 0.00 0.00 0 .00 1 0 1 1 0 0 1 0 .17 0 .00 .17 .17 0 .00 0 .00 .17 0 .00 0 0 0 1 0 0 0 0 0 .00 0 .00 0.00 .12 0 .00 0 .00 0 .00 0.00 0 0 1 0 0 0 0 0 0 .00 0 .00 .06 0.00 0.00 0.00 0.00 0 .00 1 0 0 2 2 1 2 TABLE A .6 Cont : Types of Functional Services Units (Func tions) {N ) Hobby, Toy £. Game Shops 2 Hotels, Motels & Tourist Courts 2 Household Applianee Stores 2 Misc. Apparel & Accessory Stores 2 Music Stores 2 Poultry 6. Poultry Products 2 Professional Equipment 6, Supplies 2 Recreational & Utility Trailers 2 Truck Rental & Leasing2 Beer 6. Ale Stores 1 Carpet Cleaning 1 Car Wash 1 Children's, Infant's Wear Stores 1 Dairy Products Store 1 Drapery, Curtain & Upholstery Store 1 Dry Cleaning 1 Farm Product (Raw Materials) 1 Freezer 6. Locker Meat Provisions 1 Fruit 6. Vegetable Market 1 Fuel 6. Ice Dealers 1 Groceries & Related Products 1 Industrial&Personal Paper Products 1 Industrial Machinery and Equipment 1 Livestock 1 Mail Order Houses 1 Metal Service Centers 1 Misc. Food Stores 1 Location Coefficient LC=1/N*100 Rank First Order Village N Average Second Order Third Order Village Village N Average N Average Fourth Order Village N Average Fifth Order Sixth Order Village Village N Average N Averaqe 50.00 24 0 0.00 2 .29 0 0 .00 0 0 .00 0 0 .00 0 0.00 50.00 24 0 0.00 0 0 .00 1 .25 1 .17 0 0 .00 0 0.00 50 .00 24 1 .33 0 0.00 0 0.00 0 0 .00 1 .12 0 0.00 50.00 50.00 24 24 0 0 0 .00 0 .00 0 0 0.00 0.00 1 2 .25 .50 1 0 .17 0 .00 0 0 0 .00 0 .00 0 0 0.00 0.00 50 .00 24 0 0 .00 2 .29 0 0.00 0 0 .00 0 0 .00 0 0.00 50.00 24 0 0.00 0 0.00 0 0.00 0 0 .00 1 .12 1 .06 50 .00 50.00 100 .00 100.00 100.00 24 24 25 25 25 1 0 1 0 1 .33 0.00 .33 0 .00 .33 0 •1 0 1 0 0 .00 .14 0.00 .14 0.00 0 0 0 0 0 0 .00 0.00 0 .00 0 .00 0 .00 1 1 0 0 0 .17 .17 0 .00 0.00 0 .00 0 0 0 0 0 0 .00 0.00 0 .00 0 .00 0 .00 0 0 0 0 0 100.00 100.00 25 25 0 0 0.00 0 .00 0 1 0 .00 .14 0 0 0.00 0 .00 0 .17 0.00 0 0 0.00 0 .00 0 0 0 .00 0.00 100.00 100.00 25 25 1 0 .33 0 .00 0 0 0.00 0 .00 0 1 0 .00 .25 0 0 0 .00 0 .00 0 0 0 .00 0 .00 0 0 0.00 0.00 100.00 25 1 .33 0 0 .00 0 0.00 0 0 .00 0 0 .00 0 0 .00 100.00 25 0 0.00 0 0 .00 0 0 .00 1 .17 0 0 .00 0 0 .00 100 .00 100.00 25 25 0 0 0 .00 0.00 0 1 0 .00 .14 0 0 0 .00 0.00 0 .17 0 .00 0 0 0 .00 0 .00 0 0 0.00 0.00 100.00 25 0 0 .00 0 0 .00 0 0 .00 0 0 .00 1 .12 0 0.00 100 .00 25 0 0 .00 0 0 .00 1 .25 0 0 .00 0 0 .00 0 0 .00 100.00 100.00 100.00 100.00 100.00 25 25 25 25 25 1 0 0 1 0 .33 0.00 0 .00 .33 0 .00 0 1 1 0 1 0 .00 .14 .14 0 .00 .14 0 0 0 0 0 0 .00 0.00 0.00 0 .00 0 .00 0 0 0 0 0 0 .00 0.00 0 .00 0 .00 0 .00 0 0 0 0 0 0 .00 0.00 0 .00 0 .00 0 .00 0 0 0 0 0 0 .00 0.00 0.00 0.00 0.00 0 .00 0.00 0.00 0.00 0.00 TABLE A .6: Cont Total Functional Units SOURCE: Location Co­ efficient LC=1/N*100 Rank First Order Village N Average Second Order Third Order Villages Villages N Average N Average Fourth Order Villages N Average Fifth Order Sixth Order Vi 11 ages Villages N Average N Average 100.00 100.00 100.00 25 25 25 0 1 0 0.00 .33 0.00 1 0 1 .14 0.00 .14 0 0 0 0 .00 0.00 0.00 0 0 0 0.00 0.00 0.00 0 0 0 0.00 100 .00 100.00 25 25 1 1 .33 .33 0 0 .00 0 .00 0 0 0.00 0.00 0 0.00 0 .00 0 0 100.00 100.00 100.00 100 .00 25 25 25 25 1 0 0 1 .33 0 .00 0 .00 .33 0 0 1 0 0.00 0.00 .14 0.00 0 0 0 0 0.00 0.00 0.00 0.00 0 0 .00 0.00 0.00 0.00 0 100 .00 100.00 25 25 0 0 0 .00 0.00 0 1 0.00 .14 0 0 0.00 0.00 0.00 0.00 0 0 0 0 0 0 0 0 0 0 .00 0.00 0.00 0 .00 0 .00 0 0.00 0.00 0 .00 .12 0.00 0 .00 0 1 0 0 1 0 .12 0 .00 0 0 0.00 0.00 0 0 0 0 0 0 .00 0.00 0.00 0.00 0.00 0.00 76 3 TABLE A .3: Services from telephone directories used in tables of functional indexes for villages are not shown here due to lack of data for 1950. 00*7 Functional Types of Units Services (N) (Funct ions) Misc . Personal Services 1 Outdoor Advertising 1 Plumb. & Heating 1 Family & Commercial Laundries 1 Retail Bakeries 1 Service Establishment Equipment & Supplies 1 Shoe Stores 1 Stationery Supplies 1 Tires & Tubes 1 Transpor tat ion Equipmen t 1 Welding Repair 1 TABLE A.7: Other Services offered in Central Villages, Southcentral Michigan, Types of Functional LocationServices Units Coefficient (Functions) (N) (L.C.) First Order Villages Avg . N Second Order Villages N Avg . Third Order Villages N Avq . 17 3 .40 1970 Fourth Order Villages N Avg. Fifth Order Villages N Avq . Sixth Order Villages Avq . N Schoo 1 97 1.03 10 3.33 10 2 .50 21 3.00 15 89 1.12 11 3.67 13 3.25 20 4 .00 21 3 .00 24 12 2 .00 Church 1 .00 12 .80 Bank 36 2 .78 3 1 .00 4 1 .00 6 1 .20 7 1.00 10 .83 6 .40 28 22 3.57 3 .75 7 .71 4 .33 0 0 .00 .67 4 1.00 8 1 .40 1 .60 5 4.54 9 2 3.00 Barbarshop 4 .57 3 .25 1 .07 Dentist 21 4.76 5 1.67 5 1 .25 6 1 .20 4 .57 1 .08 0 0.00 At torney 15 6.67 7 2.33 0 0.00 3 .60 3 .43 1 .08 1 .07 Veter inar ian 11 9.09 1 .33 4 1.00 1 .20 2 .29 1 .08 2 .13 Doc tors 1 Of f ice 1 .00 Optometrist 2 50.00 1 .33 0 0.00 0 0.00 0 0.00 1 .08 0 0.00 Clinic 1 100.00 1 .33 0 0.00 0 0 .00 0 0.00 0 0 .00 0 0.00 Hospital 1 100.00 0 .33 0 0 .00 1 .20 0 0 .00 0 0 .00 0 0.00 SOURCE: Data is derived from Table A.2 TABLE A.8; Other Services Offered in Central Villages, Southcentral Michigan, Types of Functional LocationFirst Order Services Units Coefficient Villages (Functions) (N)__________ (L.C.)______ N_____ Avq ♦ 1980 Second Order Third Order Fourth Order Villages Villages Villages N .______ Avq ♦____ N______ Avq .____ N_______ Avq . Fifth Order Sixth Order Villages Villages N______ Avq .____ N_____ Avq . Church 195 .51 32 10.67 47 6.71 27 6.75 27 4 .50 30 3.75 32 1 .78 School 69 1 .45 12 4 .00 15 2.14 9 2.25 9 1.50 13 1.63 11 .61 .17 64 1 .56 29 9.67 13 1 .86 9 2.25 7 1 .17 3 .38 3 Bank 47 2.13 8 2.67 10 1.43 5 1.25 7 1 .17 7 .88 10 .56 Den list 36 2 .77 10 11 1.57 5 1 .25 4 .67 3 .38 3 .17 At torney 32 3.12 11 3.33 3.67 9 1.26 3 .75 1 .17 6 .75 2 .11 Veter inarian Barbershop 32 3.12 5 1.67 13 1 .86 4 1 .00 3 .50 3 .38 4 .22 27 3.70 5 I .67 8 1 .14 9 2.25 3 .50 1 .13 1 .06 Optometrist Clinic 9 11 .11 2 .67 2 .29 3 .75 0 0.00 1 .13 1 .06 8 12 .50 4 1 .33 2 .29 1 .25 0 0 .00 1 .13 0 0.00 Hospital 1 100.00 1 .33 0 0.00 0 0.00 0 0 .00 0 0 .00 0 0 .00 SPOURCE: Data is derived from Table A.3 402 Doc tors' Off ice A P P E N D I X sB 403 Village Date Name Public Questionnaire Cultural and Social Aspects: 1. D o y o u h a v e a n y h o u s i n g a n d m o b i l e h o m e d e v e l o p m e n t in y o u r v i l l a g e ? If y e s , w h e n Y esD NoD ? and why? 1a. Is t h a t m o s t l y r e l a t e d t o t h e m i g r a t i o n of r e t i r e d f a r m e r s t o your v i l l a g e ? 1b. Is t h a t b e c a u s e o f s o m e j o b o p p o r t u n i t i e s in t h i s c o m m u n i t y ? Y esD N oD Y esD N oD 1c. Is t h a t b e c a u s e o f i n c r e a s e d m o b ility a n d c o m m u t i n g o p p o r t u n i t i e s f o r p e o p l e w h o h a v e t h e i r j o b s o u ts id e th e village? Y esD N oD 2. Did y o u h a v e a n y f a r m d e p o p u l a t i o n in t h e a d j o i n i n g f a r m s ? Y esD N o D If y e s , w h e n ? and why? 3. D o y o u still h a v e t h e d i s t r i c t s c h o o l in t h i s v i l l a g e ? Y esD N oD 3 a . Is t h e d i s t r i c t s c h o o l c o n s o l i d a t e d w i t h o t h e r d i s t r i c t s c h o o l s ? If Y e s , w h e n ? w ith w h ic h o n e s Y esD N oD ? an d why? 3 b. D o e s t h e c o n s o l i d a t e d s c h o o l f u n c t i o n b e t t e r t h a n t h e d i s t r i c t s c h o o l s ? 4. Did y o u h a v e a n y c h u r c h c o n s o l i d a t i o n ? w ith w h i c h o n e s Y esD N oD Y esD N oD If y e s , w h e n ? ? an d why? Functional and Economic Aspects: 1. W h i c h s e r v i c e s o f t h i s v i l l a g e a r e vital t o f a r m e r s : F o o d D ? H o u s e h o l d s N e e d s D ? A g r i c u l t u r a l D ? S o c ia l D ? E d u c a tio n a l D ? H ealth C e n te r s D ? C o m m e r c ia l D ? E le v ato r D ? B a n k D ? E m ploym ent D ? O thers D ? 2. D o y o u b e l i e v e t h a t t h e i n c o m e o f f a r m e r s h a s b e e n i n c r e a s e d s i g n i f i c a n t l y in t h e s e v e n t i e s ? Y esD N o D 2 a . D id t h e i n c r e a s e o f f a r m e r ' s i n c o m e e n c o u r a g e t h e m t o visit t h i s v illa g e m o r e o f t e n t h a n t h e p a s t ? 2 b. Did t h e i n c r e a s e of i n c o m e e n c o u r a g e t h e f a r m e r s t o b u y b e t t e r a n d s p e c i a l i z e d g o o d s ? If y e s , f r o m h e r e Y esD N oD Y esD N oD D ? o r o th e r c e n t e r s D ? P le a s e give th e n a m e s ? 3. D o y o u t h i n k t h a t t h e r e c e n t d e c r e a s e of f a r m e r s i n c o m e ( 1 9 80 's ) h a s c h a n g e d t h e i r s h o p p i n g b e h a v i o r t o w a r d t h i s com m u n ity ? Y e s D N o D If y e s , e x p l a i n : 3 a . D o t h e f a r m e r s v is i t t h i s v i l l a g e l e s s o f t e n in p r e s e n t t i m e r a t h e r t h a n t h e p a s t ? Yes D N oD 3 b . Will t h e r e c e n t r e d u c t i o n o f f a r m e r ' s i n c o m e i n f l u e n c e s i g n i f i c a n t l y o n t h e i r f u t u r e p u r c h a s i n g p o w e r ? Do Y esD N oD not know D 3 c . Will t h e d e c r e a s e o f f a r m e r ' s i n c o m e c h a n g e t h e i r m a r k e t c e n t e r s in t h e n e a r f u t u r e ? Y e s D N o D Do not k n o w D If y e s , p l e a s e e x p l a i n : 3 d . D o y o u t h i n k t h a t t h e c h a n g e s of f a r m e r s i n c o m e h a s i n f l u e n c e d o n t h e e c o n o m i c c o n d i t i o n s o f t h i s v i l l a g e ? N o D D o n o t K n o w D If y es , p l e a s e e x p l a i n : Y esD 404 4. P l e a s e c o m p l e t e t h e f o l lo w in g t a b l e t h a t i n c l u d e s t h e f u n c t i o n a l c h a n g e s of y o u r c o m m u n i t y : F unctions P r e s e n t T im e U p t o 10 Y e a r s A g o 1 0 - 3 0 Y ears Ago A griculture □ □ □ □ □ □ □ □ □ □ □ □ □ □ □ □ □ □ T rade C e n te r M i n e ra l Industrial D o rm ito ry R e crea tio n al Transportations! Developments: 1. W h e n d i d y o u h a v e a s i g n i f i c a n t h i g h w a y d e v e l o p m e n t in y o u r c o m m u n i t y ? H o w w a s its i m p a c t o n retail s a l e s of t h i s v i l l a g e ? Is t h a t f a v o r e d □ o r r e d u c e d □ so m e certain b u s in e s s e s ? P le a s e explain. 2. D o y o u h a v e a n y h i g h w a y t h a t g o e s t h r o u g h t h e v illa g e o r b y p a s s i t ? Yes □ NoD 2 a . Is t h a t f a v o r e d o r r e d u c e d t h e e c o n o m i c p o t e n t i a l i t y o f t h i s v i l l a g e ? F a v o r e d □ 2 b . W a s it e n c o u r a g i n g o r d i s c o u r a g i n g f o r f a r m e r ' s v i s i t i n g of t h i s v i l l a g e ? R educed□ E ncouraging □ 3. D o t h e f a r m e r s s h o p m o s t l y in t h i s v illa g e o r t h e y b y p a s s it t o r e a c h o t h e r c e n t e r s ? D isco u rag in g □ S h o p p in g H e r e O B ypassing H e r e D If t h e y b y p a s s , w h a t a r e t h e a d v a n t a g e s of o t h e r c e n t e r s ? 4. D o y o u h a v e a n y p a r t i c u l a r g o o d s a n d s e r v i c e s in t h i s v i l l a g e t h a t a t t r a c t f a r m e r s fo r v i s i t i n g in h e r e ? Y esD N oD If y e s , g i v e t h e n a m e s o f t h e s e g o o d s a n d s e r v i c e s : 5. H a s t h e r a i l r o a d l o s t i ts f o r m e r s i g n i f i c a n c e ? Y esD NoD 5 a . H a d it i m p a c t m o s t l y o n t h e t r a n s p o r t i n g of p a s s e n g e r s ? If y e s , w h e n ? and why? D G o o d s D ? o r B o t h of T h e m D ? 5 b. Are t h e e l e v a t o r s still i m p o r t a n t f o r b u y i n g t h e g r a i n s a n d t r a n s p o r t i n g t h e m by t h e r a i l r o a d ? If n o t , s i n c e w h e n Y e s D No D ? an d why? Perspectives of the Future: 1. W h a t d o y o u p r e d i c t f o r t h e f u t u r e o f f a r m i n g in t h e s u r r o u n d i n g a r e a s of y o u r c o m m u n i t y ? 2. W hat d o you p re d ic t for th e fu tu re d e v e lo p m e n t of y o u r c o m m u n ity ? a n d w h a t a r e your s u g g e s tio n s ? 405 County Township Distance to the Central Village Distance to Lansing Farm Family Questionnaire 1. H o w l o n g h a v e you b een here ? W h e r e d i d y o u live b e f o r e ? S in c e w h e n have you b e e n a farm o p e r a to r? 1a. H a v e y o u a b a n d o n e d y o u r f a r m s t e a d f o r a w h i l e ? Y esD N oD 1b. D o y o u k n o w a n y a b a n d o n e d f a r m s t e a d s in y o u r n e i g h b o r h o o d ? If y es , w h e n ? a n d why? Y e s D N o D If y e s , s i n c e w h e n and why? 1 c. D o y o u k n o w a n y f a r m s in y o u r n e i g h b o r h o o d t h a t a r e m e r e l y r e s i d e n t i a l ? Y e s D N o D If y e s , w h a t p e r c e n t a g e o f y o u r n e i g h b o r i n g f a r m s is r e s i d e n t i a l ? 2. W h o is ( a r e ) t h e m a i n f a r m o p e r a t o r ( s ) ? M a l e h e a d o f h o u s e h o l d D F e m a l e h e a d o f h o u s e h o l d D B o t h D O t h e r s D ( S p e c i fy ) 3. A re y o u a f u l l - t i m e f a r m e r O p a r t - t i m e f a r m e r O r e t i r e d f a r m e r D o t h e r ( s p e c i f y ) ? 4. W h o is ( a r e ) t h e o w n e r ( o w n e r s ) o f y o u r f a r m ? 5. H o w l a r g e is y o u r f a r m ? acres. 5a. H ave you i n c r e a s e d you f a r m la n d s by p u r c h a s i n g o r ren tin g s o m e l a n d s ? Y e s D N o D If y es , w h e n ? and why? 5 b . Did t h e i n c r e a s e o f y o u r f a r m s i z e i m p r o v e t h e f a r m o u t p u t s ? Y esD NoD 6. W h a t t y p e of f a r m i n g d o yo u c a r r y o n ? P l e a s e n a m e it: 6 a . Did y o u h a v e s o m e c h a n g e s in y o u r f a r m i n g t y p e ? Y e s D N o D If y es , w h a t w a s t h a t and why? 6 b . Did y o u s w i t c h f r o m t h e g e n e r a l f a r m i n g t o s p e c i a l i z e d f a r m i n g ? Did it i m p r o v e t h e f a r m o u t p u t s ? Y e s D N o D If y e s , w h e n ? w hen? ? and why? Y esD N oD 7. H o w l o n g h a s y o u r f a r m b e e n a u t o m a t e d ? 7a. Do yo u u s e th e m o d e r n t r a c t o r s ? Yes D N o D If y e s , s i n c e w h e n a r e y o u u s i n g t h e 2 - 3 w h e e l dr ive t r a c t o r o r 4 w h e e l drive t r a c t o r ? 8. H o w i m p o r t a n t h a v e t h e f o l lo w in g b e e n in y o u r f a r m d e v e l o p m e n t ? L ittle I m p o r t a n c e Im portant Ver y I m p o r t a n t F a rm 's A u to m atio n N ew Farm E q u ip m e n t 4 W h e e l D r iv e T r a c t o r □ □ □ □ D ^ 2 - 3 W h e e l Drive T r a c t o r □ □ □ C orn C o m b in e □ □ □ N ew D e s ig n e d T rucks □ □ □ New S e e d s □ □ □ N ew F ertilizers O E □ New H erbicides New P esticid es □ □ D □ □ □ O th e r s (Specify) □ □ □ 9. T o w h a t e x t e n t t h e s e f o l lo w in g s o u r c e s h a v e b e e n i m p o r t a n t in c h a n g i n g y o u r f a r m m a n a g e m e n t ? S o m e E xtent G r e a t E x te n t M e d i a ( M a g a z i n e s , TV, R a d i o , e t c . ) V ery Little □ □ □ N e ig h b o rs, Friends, R e la tiv es □ □ □ D ealers, S a le s m e n , B uyers □ □ □ Farm O rganizations □ □ □ C o o p e ra tiv e E x te n sio n S erv ice □ □ □ 406 10. W h i c h o f t h e f o l l o w i n g g r o s s a g r i c u l t u r e s a l e s c a t e g o r i e s b e s t d e s c r i b e s y o u r f a r m ? Over $ 50,000 □ $ 2 0 , 0 0 0 t o $ 4 9 ,9 9 9 □ $ 1 0 , 0 0 0 t o $ 1 9 ,9 9 9 □ $5,000 to $9,999 □ $ 2 , 5 0 0 t o $ 4 ,9 9 9 □ $1 ,0 0 0 to □ $2,499 U n d e r $1,000 □ 1 0 a. H o w m u c h is t h e p e r c e n t a g e o f y o u r i n c o m e f ro m f a r m and o ff-farm 10 b . Did y o u h a v e a n y c h a n g e s o f f a r m i n c o m e in t h e p a s t t h r e e y e a r s ? ? Increase □ No C hange □ D ecrease □ S ignificant D e c r e a s e Q 11. D o y o u b e l i e v e t h a t y o u r a c c e s s i b i l i t y t o m a r k e t c e n t e r s h a s b e e n i n c r e a s e d ? Y e s D N o D If y es , s i n c e w h e n ? and why? 11a. W h i c h o f t h e f o l l o w i n g h a v e b e e n i m p o r t a n t in i n c r e a s i n g y o u r a c c e s s i b i l i t y t o m a r k e t c e n t e r s ? H aving m o r e th a n o n e private c a r M odern vehicles that are faster D D H ighw ay d e v e lo p m e n t □ S e c o n d a ry road d ev e lo p m e n t D I n c r e a s e o f s p e e d l i m i ta t io n D 12. D o y o u b y p a s s a n y s m a l l t o w n s t o r e a c h t h e l a r g e r o n e s f o r y o u r s h o p p i n g ? If y e s , s i n c e w h e n Y esD N oD ? and why? 13. H a v e y o u e v e r c h a n g e d y o u r m a j o r s h o p p i n g c e n t e r s ? Y esD N oD If y e s , w h e n ? from w here to w h ere and why? 14. D o y o u t h i n k t h a t y o u u s e d t o b u y b e t t e r q u a l i t y a n d m o r e s p e c i a l i z e d i t e m s o f t h e f o l l o w i n g in t h e p a s t ? D F o o d s , D C lo th in g , D F u rn itu re . D F a rm M achinery & S u p p lie s, O O t h e r s , 15. H o w m a n y t i m e s in a w e e k d o y o u visit t h e m a r k e t c e n t e r s n o w ? and b efore? 15a. W h e r e d o y o u visit for t h e s e f o l lo w in g g o o d s a n d s e r v i c e s ? G rocery S to re , D ep artm en t S tore P aint & W allpaper S to re , Fam ily C l o t h i n g , Clinic , O p to m etrist , S h o e S tore , Jew elry , F lo o r C o v e r i n g S t o r e , A u to m o tiv e D ealer 16. P l e a s e i d e n t i f y y o u r r e a s o n s f o r s h o p p i n g o r visiting c h o i c e of t h o s e g o o d s a n d s e r v i c e s in t h a t p a r t i c u l a r m a r k e t center: G o o d s a n d Services S pecialized C o n v e n ie n ce A ttractiv en ess S av e Save of Goods & of of M on e y T im e Goods S ervices S h opping M a rk e t G rocery S tore D D D D □ D D D ep artm en t Store □ □ □ □ □ O D D D D D D D D D □ □ O □ □ □ D D D □ □ D □ D □ □ □ D D Paint & W allpaper Store D D D D D C linic D O p to m etrist O D D Fam ily C lo th in g S h o e S to re F loor C o v e rin g S tore Jew elry A u to m o tiv e D ealer 17. P ri c e D istance W h at is y o u r a g e a n d your s p o u s 's a g e ? □ D □ D ■ D D D D D O M aleD F e m a le O □ 0 1 8 - 2 5 , D O 2 6 - 3 5 , D 0 3 6 - 5 5 , 0 0 5 6 - 6 5 , D Q 65 an d Over □ □ □ □ D □ O D D D 18. Please identify the educational level of you and your spouse: □ O L ess than High School M aleD Fem aleO □ O H i g h S c h o o l G r a d u a te o r E q u iv a le n t D O B e y o n d High S c h o o l D O S o m e C o lleg e o r T rain in g □ O C o lleg e G raduate □ O G r a d u a t e W ork 1 9. W h a t c h a n g e s d o y o u e x p e c t in y o u r f a r m o p e r a t i o n in t h e n e a r f u t u r e ? □ N o n e □ S e l l i n g y o u r farm □ F i n d i n g an o f f - f a r m jo b □ E x t e n d i n g y o u r fa rm 2 0 . H o w s u r e a r e y o u t h a t y o u c a n k e e p r u n n i n g y o u r f a r m in t h e n e a r f u t u r e ? □ A little s u r e , □ M o d e r a t e l y s u r e , D S u r e , □ C o m p l e t e l y s u r e 21. Y o u r c o m m e n t s f o r t h e f u t u r e d e v e l o p m e n t of y o u r c o m m u n i t y : 408 County Township D istance to Central Village Distance to Lansing N on-Farm Family Questionnaire 1. H o w l o n g h a v e y o u b e e n h e r e ? W h e r e d i d y o u live b e f o r e ? W hy d id y o u c h o o s e th is p la c e fo r y o u r living? 2. H o w m u c h is t h e a r e a of y o u r p r o p e r t y ? s q u a r e feet. 2a. W h o o w n s yo ur h o u s e ? 2b. Was it used as a farm before? Y esD N oD If yes, are you an ex -farm er? If yes, why did you change your job? Y esD N oD 3. W h a t is t h e p e r c e n t a g e of n o n - f a r m f a m i l i e s in y o u r n e i g h b o r h o o d ? 4. W h i c h o n e of t h e f o l l o w i n g is c l o s e r t o y o u r i n c o m e l e v e l ? D O v e r $20,000 □ $ 5 , 0 0 0 t o $ 9 , 9 9 9 D $1,000 t o $ 2 , 4 9 9 D$10,000 t o $ 1 9 , 9 9 9 D $ 2 , 5 0 0 t o $ 4 ,9 9 9 D $ U n d e r $1,000 4 a . Is y o u r i n c o m e c o m p l e t e l y D o r p a r tly D f r o m o f f - f a r m job. 4 b . W h a t is y o u r o f f - f a r m J o b ? a n d in w h i c h t o w n d o y o u w o r k ? 5. W h i c h o n e o f t h e f o l l o w i n g h a v e b e e n i m p o r t a n t in i n c r e a s i n g y o u r a c c e s s i b i l i t y t o m a r k e t c e n t e r s ? D H aving m o re th a n o n e private c a r ? D S e c o n d a ry R oad D evelopm ent D I n c r e a s e of S p e e d L im i t a t i o n D M o d e r n V eh icles th a t are F a ste r D H ig h w a y D evelopm ent 6. D o y o u b y p a s s a n y s m a l l t o w n s t o r e a c h t h e l a r g e r o n e s f o r y o u r s h o p p i n g ? If y e s , s i n c e w h e n Y esD N oD and w hy? 7. H a v e y o u e v e r c h a n g e d y o u r m a j o r s h o p p i n g c e n t e r s ? Y esD N oD If y e s , w h e n ? from w h e r e to w h e r e ? and why? 8. D o y o u t h i n k t h a t y o u u s e d t o b u y b e t t e r q u a l i t y a n d m o r e s p e c i a l i z e d i t e m s of t h e f o l lo w in g t h a n t h e p a s t ? D F o o d s D C I o th in g D F urniture D O thers 9. H o w m a n y t i m e s in a w e e k d o y o u visit t h e m a r k e t c e n t e r s n o w a n d before ? 9 a . W h e r e d o y o u visit fo r t h e s e f o l lo w in g g o o d s a n d s e r v i c e s ? G rocery S to re , D epartm ent S tore Paint a n d W allpaper S to re , F am ily C l o t h i n g , C linic , O p to m etrist , S h o e S to re , Jew elry , Floor C o v e rin g S to r e , A utom otive D ealer 10. P l e a s e id e n t i fy y o u r r e a s o n s f o r s h o p p i n g o r visiting c h o i c e o f t h o s e g o o d s a n d s e r v i c e s in t h a t p a r t i c u l a r m a r k e t centers: G o o d s & S ervices G rocery Store D ep artm en t Store Fam ily C lo th in g S h o e S to re F loor C o v e rin g S to re P aint & W allp ap er S to re C lin ic O p to m etrist Jew elry A u to m o tiv e D ealer D istance D D D D D D D D D D Price S pecialized C o n v e n ie n ce A ttractiveness Save Save of Goods & of of Money T im e Goods S ervices S hopping M a rk e t D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D D 409 11. W h a t i s your age and your sp o u se's age? M aleD Fem aleO □ 0 1 8 - 2 5 , 0 0 2 6 - 3 5 , [ 3 0 3 6 - 5 5 , 0 0 5 6 - 6 5 , 0 0 6 6 and O v e r 1 2. P l e a s e i d e n t i f y t h e e d u c a t i o n a l level o f y o u a n d y o u r s p o u s e : M aleO F em aleO □ O L e s s t h a n H i g h S c h o o l , O O H i g h S c h o o l G r a d u a t e o r E q u iv a le n t 1 3. □ O B e y o n d High S c h o o l O O S o m e C o lleg e o r T raining □ O C o lleg e G raduate O O G ra d u a te W ork Y our c o m m e n t s of th e fu tu re d e v e lo p m e n t of your com m unity: A P P E N D I X : G 410 TABLE G.l : F a c t o r s R e l a t e d to Farmer Families' Selection o f G r o c e r y S t o r e in a P a r t i c u l a r C e n t r a l P l a c e (A C h i - S q u a r e Tes t) Factors ChiSquare df Obsev. Prob * Cramer 1s V Or PhiCoef­ ficient ** Objective Factors Distance Price of Goods Specialized Goods/ Services Shopping C o n v e n ­ ience Attractiveness of market 13.09437 1 2.99282 2 .00l> p >0 .5 > p >2 .41496 .18036 .35376 1 .7 > P>5 .09759 > p>l .20576 > p> .7 .01308 .5 > p > .2 .10 > p > .5 .20296 .21873 .10 .05 1 .05 > > > > .20504 .23191 .10334 .21737 4 4 4 .7 1 .5 > p > .5 > p > .7 > p >.2 .13326 .03810 .22070 .24931 2 1 > .05263 2.70204 1 .2 0 1 1 3.74862 3.04084 3 1 Subjective Factors Saves Money Saves Time Farmers’Characteristics 7.65134 4 17.85507 8 3.69478 6 16.15951 6 3.16086 .26421 4.52995 A i —1 o a .05 > A 6.95918 2 p > .05 p > .01 p > .7 p>. 01 a Income Age Education Length of Residence Shopping, Trips per week Farm Size Farm Consol id at io n Full- or Part-time Farming Type of Farming (Cash crop, dairy, e t c .) Change to s p e ci a l­ ization Time of farm au t o ­ mation .27503 .27277 1 .7 > p>. 5 .09132 .30517 4 1 > P > •7 .04095 *The critical value of alpha for rejecting the null h y p o ­ thesis and ac cepting the alternative hypothesis was assumed at .05. * * C ramer's V was s e l e c t e d for c h i - s q u a r e tests with t h a n one d e g r e e of f r e e dom ; the P h i - c o e f f i c i e n t w as for t a b l e s w i t h having one d e g r e e of f reedom. more used 411 TABLE Cl.2 : Factors Related to Farmer Families' Selection of Optometrist in a Particular Central Place (A Chi-Square Test) Factors df Obsev. Prob * 6 .52932 .09273 1 1 .05> p > .01 1 >p>.7 .30496 .07788 13 .08686 1 .01>p >.001 .41989 2 .60842 1 .2 >p>.l .20965 0 1 1 >p>. 7 .07630 0 17.41803 1 1 1 >p>.7 .001>p> 0 .02964 .47284 1.39920 7.97255 2 .68927 4.90184 1 2 2 3 .5 > p>. 2 .05> p>.01 .5 >p>.2 .2 > p >. 1 .15754 .22048 .12690 .17503 0 1 0 1 1 .18990 1 1 >p>.7 1 >p>. 7 •5 £>p •2 .02296 .00140 .14748 .74620 2 .7 >p>. 5 .09157 .1 >p >. 0 5 .21224 .05464 1 1 > P >• 7 .07325 .14335 1 1 >p>. 7 .06984 ChiSquare Cramer's V Or Phi- Coef­ ficient ** Objective Factors Distance Price of Goods Specialized Goods/ Services Shopping C o n v e n ­ ience Attractiveness of market Subjective Factors Saves Money Saves Time Farmers* Characteristics Income Age Education Length of Residence Shopping, Trips per week Farm Size Farm Consolidation Full- or Part-time Farming Type of Farming (Cash crop, dairy, e t c .) Change to speci al ­ ization Time of farm au to ­ mation 2.91472 1 *The critical value of alpha for rejecting the null h y p o ­ thesis and accepting the alternative hypothesis was assumed at .05. * * C r a m e r ' s V was s e l e c t e d for c h i - s q u a r e t e s t s w i t h t h a n one d e g r e e of freedom; t he P h i - c o e f f i c i e n t was for tables w i t h having one d e g r e e of freed om. more used 412 TABLE G .3 : F a c t o r s R e l a t e d to Farmer Families' Selection of C l i n i c s in a P a r t i c u l a r C e n t r a l P l a c e (A C h i - S q u a r e Te st ) Factors Chie S quare df Obsev. Prob * Cramer's V Or Phi- Coef­ ficient ** Obj ective Factors Distance Price of Goods Specialized Goods/ Services Shopping C o n v e n ­ ience Attractiveness of market 12 .98534 1 .40451 1 .001> p =0 .7 > p >. 5 .41100 .13561 14.76590 .001> p =0 .41197 .05 > p >. 01 .24425 1 > p >. 7 .02863 .5 > p > . 2 .0 0 l>p > 0 .11952 .40838 .48475 4 3.32044 4 6.88784 2 1.45143 2 1 .7 .05 .5 > > > > .07422 .10186 .20494 .09554 .21547 2 4 .34610 2 .61333 2 1 .2 1 > p >. 7 > p >. 1 > p >. 7 .05065 .22351 .08545 2.57218 2 .5 > p >. 2 .17396 1 .24524 2 .7 > p >. 5 .11965 1 > p >. 7 .04904 .5 > p >. 2 .18469 2 4 .18667 1 1 0 Subjective Factors Saves Money Saves Time .48549 1 12.67836 1 Farmers’Characteristics Income Age Education Length of Residence Shopping, Trips per week Farm Size Farm Consoli dat ion Full- or Part-time Farming Type of Farming (Cash crop, dairy, e t c .) Change to sp eci al­ ization Time of farm au to ­ mation .00814 1 2.96770 2 p p p p >. 7 >. 5 >.01 >. 2 *The critical value of alpha for rejecting the null thesis and accepting the alternative hypothesis was at .05. **Cramer's V was selected for chi-square tests with than one degree of freedom; the Phi-coefficient was for tables with having one degree of freedom. hypoassumed more used 413 TABLE C.4 : F a c t o r s R e l a t e d to Farmer Families' Selection of F l o o r C o v e r i n g S t o r e in a P a r t i c u l a r C e n t r a l P l a c e (A C h i - S q u a r e T es t ) Obsev. Prob * Cramer 1s V Or Phi- Coef­ ficient ** ChiSquare df 1.29118 2 .32127 1 1 .5 .2 > p > .2 > p > .1 .17324 .20842 1.99867 1 .2 > i —1 Factors .19742 .41989 1 .7 > p 2*.5 .11114 .56886 1 .5 5 .97978 .73906 1 1 .05 > p >.01 .5 > p > .2 .08070 .99929 .09454 .29322 1 2 1 1 1 .7 1 1 > > > > p > .7 p 1*.5 p > .7 P> •7 .08169 .08108 .04804 .06371 .74480 1 1 1 1 1 .5 > p > .7 > p > .7 > p>. 2 .02776 .01999 .13743 .05948 1 1 > p>. 7 .06637 .94136 1 .5 > P>. 2 .14534 0 1 1 > p>. 7 .00483 0 1 1 > p>. 7 .02734 Ob jective Factors A • A CM a > a Distance Price of Goods Specialized Goods/ Services Shopping C o n v e n ­ ience Attractiveness of market .14085 Subjective Factors Saves Money Saves Time .30732 .13763 Farmers'Characteristics Income Age Education Length of Residence Shopping, Trips per week Farm Size Farm Consolidation Full- or Part-time Farming Type of Farming (Cash crop, dairy, e t c .) Change to specia l­ ization Time of farm auto­ mation 0 0 *The critical value of alpha for rejecting the null h y p o ­ thesis and accepting the alternative hy pothesis was assumed at .05. * * C r a m e r ' s V was s e l e c t e d for c h i - s q u a r e t e sts w i t h t h a n o n e d e g r e e of f r e e d o m ; t h e P h i - c o e f f i c i e n t w a s for tables with having one d e g r e e of freedom. more used klk TABLE c.5 : F a c t o r s R e l a t e d to Farmer. F a m i l i e s ' S e l e c t i o n of J e w e l r y S t o r e in a P a r t i c u l a r C e n t r a l Pl ace (A C h i - S q u a r e Tes t ) Factors Obsev. Prob * Cramer 1s V Or PhiCoef­ ficient ** ChiSquare df 1 .41866 .86349 1 1 . 5 > p > .2 .5>p> .2 .21437 .17171 1.442240 1 ■ >R> *^ .20599 .24154 1 .7>p> .5 .12193 .38133 1 . 7 V .5 .15090 1 .86513 1.08823 1 1 .2 > p > .1 .3 >p> .2 .22942 .19672 1.17081 .04096 5 .90104 4 .42834 1 1 1 1 .5>p> .2 1 > p> .7 .05>P-> -01 .05>f>>.0l .19723 .05346 .25733 .22736 .47886 .72559 .18452 1 1 1 .5 >p> .2 .5 >p> .2 • 7^.p> .5 .14517 .16823 .10911 5.15993 1 JO5 >P> *01 .34851 .07858 1 1 >p> .7 .08601 1 1 >p> .7 .02409 1 . 5> p> .2 .15610 Ob jective Factors. Distance Price of Goods S pecialized Goods/ Services Shopping C o n v e n ­ ience Attractiv ene ss of market Subjective Factors Saves Money Saves Time Farmers’Characteristics Income Age Educatio n Length of Residence Shopping, Trips per week Farm Size Farm C o n s o li da ti on Full- or Part-time Farming Type of Farming (Cash crop, dairy, e t c .) Change to s p e c i a l ­ ization Time of farm a u t o ­ mation 0 .64857 *The critical value of alpha for rejecting the null thesis and accepting the alternative hypothesis was at .05. **Cramer's V was selected for chi-square tests with than one degree of freedom; the Phi-coefficient was for tables with having one degree of freedom. hypoassumed more used 415 TABLE C .6 :Factors Related to Farmer Families' Selection of Paint and Wallpaper Store in a Particular Central Place (A Chi -Square Test) Factors ChiSquare Cramer's V Or PhiCoef­ ficient ** Obsev. Prob * df Objective Factors Distance Price of Goods Specialized Goods/ Services Shopping C o n v e n ­ ience Attractiveness of market 1 .31251 1 2 .27743 1 .5 >p > .2 .2 >p > .1 .16647 .19421 .18648 1 .7 >p > .5 .08047 .1 >p > .05 .23158 .7 >p > .5 .12547 .01 >p > .001 .2 >p > .1 .35834 .18025 3.40512 1 .30677 1 Subjective Factors Saves Money Saves Time 8 .80420 1 1.81810 1 Farmers’Characteristics Income Age Education Length of Residence Shopping, Trips per week Farm Size Farm Con solidation Full- or Part-time Farming Type of Farming (Cash crop, dairy, e t c .) Change to sp ec ia l ­ ization Time of farm au t o ­ mation .62330 .12606 2.03137 9 .63025 2 2 2 3 .77010 1 .05701 2 1.27400 1 0 1 >p 1 >p .5 >p .05>p > > > > .7 .7 .2 .01 .02791 .02889 .11485 .24846 .5 > p > .2 1 > p > .7 .5 > p > .2 .13221 .02605 .15592 .55979 2 1 > p > .7 .08212 .35578 2 1 > p > .7 .06587 1 1 > P > -V .03546 8.35187 2 .05> p > .01 .31721 *The critical value of alpha for rejecting thei null thesis and accepting the alternative hypothesis was at .05. **Cramer's V was selected for chi-square tests with than one degree of freedom; the Ph i-coefficient was for tables with having one degree of freedom. hypoassumed more used Ll6 TABLE C.7 . ’F a c t o r s R e l a t e d t o Farmer F a m i l i e s 1 .S e l e c t i o n of D e p a r t m e n t S t o r e in a P a r t i c u l a r C e n t r a l P l a c e (A C h i - S q u a r e T es t ) ChiSquare Factors Obsev. Prob * df C r a m e r 's V Qr Phi- Coef­ ficient ** Objective Factors 1 1 .7 > P > .5 .01>p > .001 .10295 .31183 1 .5 > P > .2 .14173 1 .05>p > .01 .26015 1 1 1 1 .05> p > .01 .5 > P > .2 .27315 .16720 2 2., 2 2 .5 > p > .2 .5 > p > .2 1 > p > .7 .2 > p > .1 .18233 .09664 .00893 .14459 1 1 1 > p > .7 .1 > p > .05 .5 > p > .2 .01881 .22763 .14698 1 .5 A 1 1 1 1 A a A Distance .38522 Price of Goods 6.84839 Specialized Goods/ Services .99020 Shopping C o n v e n ­ ience 4.36504 Attractiveness of market .02999 .7 .05248 Subjective Factors Saves Money Saves Time 4.93674 1.392 70 Farmers’Characteristics 1 .2 .13023 > p > .7 .07434 1 > p > .7 .09333 1 > p > .7 .06387 a A Income 2.892 40 Age 1.58776 Education .01330 Length of Residence3.49158 Shopping, Trips per week 0 Farm Size 3.13705 Farm Consolid ati on 1 . Ill 76 Full- or Part-time Farming .77701 Type of Farming (Cash crop, dairy, etc.) .13377 Change to s pe ci al­ ization .11428 Time of farm a u t o ­ mation .07813 *The critical value of alpha for rejecting the null thesis and accepting the alternative hypothesis was at .05. **Cramer's V was selected for chi-square tests with than one degree of freedom; the Phi-c oe ff ic ie nt was for tables with having one degree of freedom. hy p o ­ assumed more used kY? TABLE : F a c t o r s R e l a t e d to Farmer Families' Selection of F a m i l y C l o t h i n g S t o r e in a P a r t i c u l a r C e n t r a l P l a c e (A C h i - S q u a r e Test) Factors ChiSquare df Obsev. Prob * Cramer's V Or Phi- Coef­ ficient ** Objective Factors .05497 7 .95011 1 1 .37912 1 1.73597 1 > p >. 7 •01>p >.001 r~ Distance Price of Goods Specialized Goods/ Services Shopping C o n v e n ­ ience Attractiveness of market .08032 .35093 1 .2 > p >-X .173 72 .66775 1 .5 >p .13625 6 .99010 .22143 1 1 .0 1> p >.001 .7 > p >.5 Income ■ .78328 Age 0 Education .99718 Length of Residence .01031 Shopping, Trips per week 0 Farm Size 1.10690 Farm Co ns olidation .46614 Full- or Part-time Farming 4.84497 Type of Farming (Cash crop, dairy, e t c .) 0 Change to s p ec ia l­ ization .11488 Time of farm au t o ­ mation 0 1 1 1 1 .5 .1 .5 1 >p >p >p >P >.2 >.7 >.2 >.7 .15227 .00384 .10576 .03181 1 1 1 1 >p .5 > p .5 > p >.7 >•2 >.2 .02094 .16517 .11741 1 •05> p >.01 .28264 1 1 > p >•7 .02647 1 1 > p >.7 .10488 1 1 > p >.7 .02066 a .11578 A >.5 >•2 Subjective Factors Saves Money Saves Time .32269 .10981 Farmers'Characteristics *The critical value of alpha for rejecting the null h y p o ­ thesis and accepting the alternative hypothesis was assumed at .05. * * C r a m e r ' s V w a s s e l e c t e d for c h i - s q u a r e tests w i t h t h a n o n e d e g r e e of f r e e d o m ; t h e P h i - c o e f f i c i e n t w a s for t a ble s w i t h having o n e d e g r e e of f r e e d o m . more used 418 TABLE C.9 :Factors Related to Fanner Families' Selection of Automotive Store in a Particular Central Place (A Chi-Square Test) Factors ChiSquare Obsev. Prob* df Cramer 1s V Or Phi- Coef­ ficient ** Objective Factors Distance Price of Goods Specialized Goods/ Services Shopping C o n v e n ­ ience At tr activeness of market .001=’p> 0 .1 > p > .05 .52503 .22235 4 .09952 2 •2 > P>-1 .21707 6 .63024 1 .0 5 > p >.01 .30148 21.74145 3 .28534 1 1 .34921 1 .7 > p > .5 .12599 5 .65142 9.23094 2 1 .1 > P > •0 5 .0 1 > p >.001 .25785 .35328 p > .7 p > .05 p>.7 p >.001 .10135 .17637 .06412 .29127 Subjective Factors Saves Money Saves Time Farmers'Characteristics .86277 3 Income 4.85248 2 Age .67024 2 Education Leng th of Residence 13 .48952 2 Shopping, Trips per 2 .18634 2 week 4.60129 2 Farm Size 1.95455 2 Farm Consol id at io n Full- or Part-time 5 .77039 2 Farming Type of Farming (Cash crop, dairy, 1 .19615 2 e t c .) Change to s p ec ia l­ 0 1 ization Time of farm au t o ­ 4 .49782 2 mation 1 > .1 > 1 > .0 1 > .5 > p > . 2 .2 > p>. 1 •5 > P > •2 .16038 .23131 .15076 .1 > p>. 05 .25607 .7 > p > .5 .11726 1 > p 5*. 7 .01367 ■2 > p>.l .22608 *The critical value of alpha for rejecting the: null thesis and ac cepting the alternative hypothesis was at .05. **Cramer's V was selected for chi-square tests with than one degree of freedom; the Ph i-coefficient was for tables with having one degree of freedom. hypoassumed more used *H9 TABLE G.10 :Factors Related to Farmer Families' Selection of Shoe Store In a Particular Central Place (A Chi-S qu ar e Test) ChiFactors Obsev. P ro b* df Square C r a m e r ‘s V Or Phi- Coef­ ficient ** O b j ec ti ve Factors Di stance Price of Goods Sp e c i al iz ed Goods/ Services Sh op pi ng C o n v e n ­ ience A tt ra ct iv en es s of market .5 > p> .2 .01 > p> .001 .16053 .33743 .05 > P>.01 .27907 3 .60768 1 .1 > p> .05 .24007 2 .07792 1 .2 > p> .1 .18993 8.05686 1.59484 1 1 .01 > p > .001 .5 > P>-2 .33743 .17344 .78447 1.64223 .09431 2 .95268 1 2 1 1 .5 .5 1 .1 > > > > .13169 .10100 .04632 .15254 1 1 1 > p>. 7 > p>.7 > p >. 7 .00262 .07708 .03194 .5 > p >. 2 .13697 1 .29450 1 8 .05686 1 4 .69803 1 Subje ct iv e Factors Saves Money Saves Time Farmers1Characteristics Income Age E d u ca ti on Len gt h of Residence Shopping, Trips per week Farm Size Farm Co ns o l i d a ti on Full- or Part-time Farming Type of Farming (Cash crop, dairy, e t c .) Change to s pe ci al ­ ization Time of farm au t o ­ mation 1 .10736 1 1 0 0 .49 762 1 p>.2 p > .2 p > •7 p > .05 0 1 1 > p>. 7 .02306 0 1 1 > P>-7 .00408 2 .62401 1 .2 > p >. 1 .20787 *The critical value of alpha for rejecting the null thesis and accepting the alternative hypothesis was at .05. **Cramer's V was selected for chi-square tests with than one degree of freedom; the Ph i-coefficient was for tables with having one degree of freedom. hypo­ assumed more used ^20 TABLE C.ll : Factors Related to Nonfarm Families' Selection of Grocery Store in a Particular Central Place (A Chi-Square Test) Factors ChiSquare df Obsev. Prob * 1 2 .001> p>0 .05 > p>.01 .56387 .28151 1 .2 > p>.l .17314 1 .5 > p >. 2 .12366 1 .5 > p>.2 .11866 2 1 .1 .2 > p >. 0 5 > p >. 1 .23428 .16826 4 4 4 2 1 .2 .5 .01 >p >p >p >p .08547 .14360 .18238 .24962 2 .2 > p >.<1 Cramer 1s V Or Phi- Coef­ ficient ** Objective Factors Distance 25 .81318 Price of Goods 7.05281 Specialized Goods/ Services 1 .76725 Shopping C o n v e n ­ ience .79128 Attractiveness of market .74591 Subjective Factors Saves Money Saves Time 4.88489 1 .73895 Non- Farmers 1Characteristics Income 1 .32964 Age 7.01125 Education 5 .78757 Length of Residence io. 34355 Shopping, Trips per week 4.48349 >. 7 >. 1 >. 2 >.001 .22197 *The critical value of alpha for rejecting the null h y p o ­ thesis and accepting the alternative hypothesis was assumed at .05. **Cramer's V was selected for chi-square tests with more than one degree of freedom; the Phi -coefficient was used for tables with having one degree of freedom. 4-21 TABLE C.12: Factors Related to N o nfa rm Families' Selection of Optometrist in a Ce rta in Central Place (A Chi-Square Test) Factors Obsev. Prob * Cramer's V Or Phi- Coef­ ficient ** ChiSquare df 19 .38320 1 .09292 1 1 .OO^p^ .5 >p >. 2 .51700 .16896 6 .20501 1 .05 > p >. 01 .32535 .5 > p >. 2 .15117 >p>.7 .07564 Objective Factors Distance Price of Goods Specialized Goods/ Services Shopping C o n v e n ­ ience Attractiveness of market .99802 1 0 1 1 1.41832 4.47353 1 1 .5 > p >. 2 .05 > p >. 01 .18157 .27594 1.98095 19.73611 .93443 .14418 1 2 1 1 .2. >p >. l .0 01> p > 0 .5 > p >. 2 1 >p>.7 .20587 .37817 .10124 .05578 .30174 1 .7 .10025 Subjective Factors Saves Money Saves Time Non-Farmers 'Characteristics Income Age Education Length of Residence Shopping, Trips per week >p .5 *The critical value of alpha for rejecting the null hy p o ­ thesis and accepting the alterna ti ve hypothesis was assumed at .05. **Cramer's V was selected for chi-square tests with more than one degree of freedom; the P hi -c oe ff ic ien t was used for tables with having one degree of freedom. 422 TABLE C.13 : Factors Related to Nonfar m "Fami 1 ies 1 Selection of Clinics in a Certain Central Place (A Ch i-Square Test) Factors ChiS quare df Obsev. Prob * Cramer 1s V Or Phi- Coef­ ficient ** Objective Factors Distance Price of Goods Specialized Goods/ Services Shopping C o n v e n ­ ience Attractiveness of market 19.15314 1 1 0 .001>p SO 1 >P >•7 .50345 .02373 13 .31884 1 .001 >P SO .42607 .2 >p > 1 .19905 1 >P >•7 .03087 1 .2 >P > 7 >P >.1 .01475 .18952 .5 .05 1 .05 >p >p >P >p .19760 .23685 .03007 .18099 1 >P >.,7 2.36989 1 1 0 Subjective Factors Saves Money Saves Time 1 0 2 .16026 1 Non-Farmers 'Characteristics Income Age Education Length of Residence Shopping, Trips per week 3.20188 8.47088 .14105 10 .08912 2 2 2 4 .22526 2 >.2 >01 >.7 >.01 .05340 *The critical value of alpha for rejecting the null h y p o ­ thesis and accepting the alternative hypothesis was assumed at .05. **Cramer's V was selected for chi-square tests with more than one degree of freedom; the Phi-coefficient was used for tables with having one degree of freedom. 423 TABLE C.14: Factors Related to Nonfarm Families' Selection of Floor Covering Store in a Certain Central Place (A Chi-Square Test) Factors Objective C r a m e r 's V Or P h i - Coef­ ficient ** df .00811 .00030 1 1 1 1 > p>. 7 > > .05676 .05190 2 .39724 1 .2 > p> .l .22616 .07784 1 1 > p >. 7 .08224 .02911 1 1 > p >. 7 .07443 .37916 .52998 1 1 .7 > p >. 5 .5 > p >. 2 .11888 .15421 1 1 1 1 .5 > .2 > .05> 1 > 1 .7 > p >. 5 Factors Distance P r i c e of G o o d s S p e c i a l i z e d G oo d s / Services Shopping Conven­ ie nc e A t t r a c t i v e n e s s of market Subjective Saves Saves Ob se v. Prob * ChiSquare Factors Money Time Non-Farmers' Characteristics Income .74491 Age 2 .48264 5.29552 Education .03810 L e n g t h of R e s i d e n c e S h o p p i n g , T r i p s p er .41613 week p p p p >. 2 >. 1 >.01 >. 7 .17550 .15811 .22131 .04242 .12123 *T he c r i t i c a l v a l u e of a l p h a for rej e c t i n g the null t h e s i s a n d a c c e p t i n g the a l t e r n a t i v e h y p o t h e s i s was at .05. hypoassumed **Cramer's V was selected for chi-square tests with more than one degree of freedom; the Phi-coefficient was used for tables with having one degree of freedom. T A B L E 0.15 : F a c t o r s R e l a t e d to N o n f a r m F a m i l i e s ' S e l e c t i o n of .Jewelry S t o r e in a C e r t a i n C e n t r a l P l a c e (A C h i - S q u a r e Test) ChiSquare Factors Objective Ob s ev . Prob * C r a m e r 's V O r Phi-- Coefficient ** Factors Distance P r i c e of G o o d s Speci al iz ed Goods/ Services Shopping Conven­ ience A t t r a c t i v e n e s s of market Subjective Saves Saves df Money Time .01476 1 1 1 >p > .7 1 >p > .7 .06482 .03976 . 20 43 7 1 - 7>p > -5 .12109 1 1 >p > .7 .00672 . 77528 1 .5>p > .2 .17094 .00862 1 1 1 >p > .7 1 >p > .7 .04085 .10445 1 1 1 1 1 >p 1 >p .5 >p 1 >p .7 .7 .2 .7 .01952 .07024 .13766 .03902 1 1 >p > .7 .08986 0 0 Factors 0 N o n - F a rm e rs ' Characteristics Income 0 Age .00094 Education 1 .40663 L e n g t h of R e s i d e n c e 0 S h o p p i n g , T r i p s pe r week . 0 388 44 > > > > *T he c r i t i c a l v a l u e of a l p h a for r e j e c t i n g the null h y p o ­ t h e s i s a n d a c c e p t i n g t he a l t e r n a t i v e h y p o t h e s i s w a s a s s u m e d at .05. * * C r a m e r 's V was selected for chi-square tests with more than one degree of freedom; the Phi-c oe ff ic ie nt was used for tables with having one degree of freedom. ^25 TABLE C.l6 : Factors Related to Nonfarm Families' Selection of Paint and Wallpaper Store in a Certain Central Place (A Chi-- S qu a re Obsev. P r ob * ChiFactors Test) df Square Objective Factors Distance P r i c e of G o o d s S p e c i a l i z e d G oo d s / Services Shopping Conven­ ience A t t r a c t i v e n e s s of market Subjective Saves Saves C r a m e r 's V O r P h i- Coef­ ficient ** Money Time .13254 2.16857 1 1 1 .2 > p>. 7 > p > .l .09283 .2 1817 1 .45084 1 .5 > p>. 2 .19167 .27296 1 .7 > p > .5 .11435 .73052 1 .5 > p>.2 .16116 .94204 .07937 1 1 .5 1 > p> .2 > p> .7 .16386 .09469 1 1 1 1 > .5 p> .2 .01 > p> .001 > p> . 7 1 1 > P> • 7 1 1 Factors N o n - F a r m e r s ' Characteristics Income .50486 Age 8.79263 Education .04839 L e n g t h of R e s i d e n c e .04771 S h o p p i n g , T r i p s p er week .06330 > p> . 7 .15476 . 27 47 7 .04358 .04545 .07944 * The c r i t i c a l v a l u e of a l p h a for r e j e c t i n g the null t h e s i s a n d a c c e p t i n g the a l t e r n a t i v e h y p o t h e s i s w as at .05. hypo­ assumed * * C r a m e r 's V was selected for chi-square tests with more than one degree of freedom; the Phi-coefficient was used for tables with having one degree of freedom. 426. TABLE C.17 : Factors Related to Nonfa rm Families' Selection of Department Store in a Certain Central Place (A Chi-Square Test) Chi- Factors df Ob se v. Prob * Square Objective Cramer's V Or P h i - Coef­ ficient ** Factors Distance P r i c e of G o o d s S pecialized Goods/ Services Shopping Conven­ ience A t t r a c t i v e n e s s of market 1 0 4 .39617 1 > p>.7 1 .Q5> p > . 0 1 .01760 .26162 3 .76456 1 .1 > p>.05 .24250 .61253 1 .5 > P > •2 .12333 .19214 1 .7 > p>. 5 . 08627 4.70471 .46417 1 1 > p > .01 .05 .5 > p >. 2 .27292 .11476 .01571 .33806 1.10154 .17736 1 2 1 1 1 1 .5 .7 > > > > p >. 5 .06236 .04486 . 10557 .05415 .00115 1 1 > p>.7 .04340 Subjective Factors Saves Saves Money Time Non- F a r m e r s ' Characteristics Income Age Education L e n g t h of R e s i d e n c e S h o p p i n g , T r i p s per week p >. 7 p>.7 p > .2 * T h e c r i t i c a l v a l u e of a l p h a for r e j e c t i n g the n u l l t h e s i s and a c c e p t i n g the a l t e r n a t i v e h y p o t h e s i s w a s at .05. hypo­ assumed **Cramer's V was selected for chi-square tests with more than one degree of freedom; the Phi-coefficient was used for tables with having one degree of freedom. 427 TABLE C.18 { Factors Related to N o nfa rm Families' Selection of Fam ily Cl othing Store in a Certain Central Place (A Chi-Square Test) ChiSquare Factors Objective Factors Subjective 0 2.27725 1 1 1 .2 > p >. 7 >P>-1 .03355 .22479 3 . 73778 1 .1 > p >. 05 .27962 1.64017 1 .5 >p>.2 .22148 1 .87705 1 .2 > p >. 1 .21272 4 .80715 0 1 1 a Distance P r i c e of G o o d s Specialized Goods/ Services Shopping Co n ve n ­ i en ce A t t r a c t i v e n e s s of market .05 > p >. 7 1 .31277 .08364 .02318 .01309 2 .57471 1 .94284 1 1 1 1 1 1 .2 .2 p .7 >p>. 7 > p >. 1 > p >• 1 .11099 .06618 .15922 .14215 0 1 1 > p >. 7 .01160 Factors i —I o ' a Money Time A Saves Saves C r a m e r 's V Or P h i - Coef­ ficient ** Ob s ev . Prob * df Non- F a r m e r s ' Characteristics Income Age Education L e n g t h of R e s i d e n c e S h o p p i n g , T r i p s per week ^ "7 * Th e c r i t i c a l v a l u e of a l p h a for r e j e c t i n g t he null t h e s i s a n d a c c e p t i n g the a l t e r n a t i v e h y p o t h e s i s w a s at .05. hypo­ assumed **Cramer's V was selected for chi-square tests with more than one degree of freedom; the Phi-coefficient was used for tables with having one degree of freedom. 428 c.19 TABLE : Factors Related to Nonfarm Families' Selection of Automotive Dealer in a Certain Central Place (A Chi-Square Test) nuj ChiSquare Factors Objective Cramer's V Or P h i - Coef­ ficient ** Factors Distance P r i c e of G o o d s S p e c i a l i z e d G oo d s / Services Shopping Conven­ ience A t t r a c t i v e n e s s of market Subjective Saves Saves Ob s ev . Prob * df 10.55332 .15017 1 1 .01 > p >. 001 .7 > p >. 5 3 .71905 1 .1 > p >. 05 .25044 .42776 1 .7 >p>.5 .10631 1 1 >P>-7 .06984 1 1 1 .5 > p >. 7 > p > .2 .05151 .14075 5 .08678 1 .57790 1.46187 .33470 1 2 2 2 .05 .5 .5 1 >P >p >p >p .29680 .10057 .09499 .04603 .00707 1 1 > p >. 7 0 .38069 .07358 Factors Money Time .02182 .96230 N o n - Fa rm er s ' Characteristics Income Age Education L e n g t h of R e s i d e n c e S h o p p i n g , T r i p s per week >*oi >.2 >. 2 >. 7 .04194 *T he c r i t i c a l v a l u e of a l p h a for r e j e c t i n g the null t h e s i s an d a c c e p t i n g the a l t e r n a t i v e h y p o t h e s i s w a s at .05. hypoassumed **Cramer's V was selected for chi-square tests with more than one degree of freedom; the Ph i- coe fficient was used for tables with having one degree of freedom. TABLE G.20 : F a c t o r s R e l a t e d to N o n f a r m F a m i l i e s ' S e l e c t i o n of S h o e S t o r e in a C e r t a i n C e n t r a l P l a c e (A C h i - S q u a r e Test) Factors Objective C r a m e r 1s V Or P h i - Coef­ ficient ** df .23656 1.55461 1 1 .7 .5 4 .07477 1 .05 >p >.01 .28813 1 .94825 1 .2 >P >.1 .21690 1 .87705 1 .2 >P >.1 .21272 1 .27690 .49069 1 1 .5 .5 >P > 2 >P >.2 .20420 .21018 1 1 1 1 1 1 .5 .5 1 1 Factors Distance P r i c e of G o o d s S p e c i a l i z e d G oo d s / Services Shopping Conven­ ie nc e A t t r a c t i v e n e s s of market Subjective Saves Saves Obsev. Prob * ChiSquare Money Time >p >.5 >P >.2 .17395 .19285 Factors N o n - F a r m e r s 1Characteristics Income .03200 A ge 0 Education .57276 L e n g t h of R e s i d e n c e 1 .57379 S h o p p i n g , T r i p s per week 0 > >.2 >.2 .11642 . 05 08 7 . 09077 .13290 > P >.7 .10148 P >P >P >P >.l >.l * Th e c r i t i c a l v a l u e of a l p h a for r e j e c t i n g t he n ul l t h e s i s a nd a c c e p t i n g the a l t e r n a t i v e h y p o t h e s i s w a s at .05. hypo­ assumed **Cramer's V was selected for ch i-square tests with more than one degree of freedom; the P h i - c o e ffi cie nt was used for tables with having one degree of freedom. BIBLIOGRAPHY Abler, Ronald; Adams, J ohn S .; and Gould, Peter. S pa ti al Organization: The G e o g r a p h e r ' s V i ew of the W o r l d . E n g l e w o o d Clif fs , N.J.: P r e n t i c e - H a l l , Inc., 1971. Agnew, J o h n A. and Duncan, J a m e s S. 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