{IT/figs W? K: 1343 1 2 197.3% x / W N metal?»- W has £4“; #9 ABSTRACT ANALYSIS OF SELECTED SOCIO—ECONOMIC VARIABLES AND THEIR EFFECT ON CONSUMER TEMPORAL BEHAVIOR IN DIFFERENT SIZE SHOPPING AIEAS By Alfred Morton Falthzik Central business districts of central cities, regional, community and neighborhood shopping centers differ with respect to the number of stores contained within them as well as the variety and quality of goods sold. There exist constraints on consumers who shop in them with respect to the time devoted to shopping. One such constraint is the time devoted to travel to the shopping facility. Other vari— ables which may correlate with or influence shopping time include family income, occupation and the head of the house— I10](], inhisekuvlcl lifke cyrile ratarus, vvifTé w(nl§inp:<>ut;xide iflie honw: and time nunnuer of'zritonwfl>iles (nvned km; the lunuse1ufihi. Therefore, five questions are investigated. One, does the amount of time devoted to travel on a single shopping trip influence the amount of time devoted to shopping in a central business district and in different size shopping centers? Two, is the size of the shopping area related to Alfred Morton Falthzik the average amount of time consumers devote to shopping on a single shopping trip? Three, do some consumers shop more frequently in one kind of shopping area than another? Four, can differences between the average amount of time consumers devote to shopping on a single shopping trip in the areas in which they do shop be explained by selected socio-economic variables? Five, can differences between the part of the day and part of the week in which consumers shop where they do shop be explained by selected socio-economic variables? The data used in the study were obtained from an origin and destination study conducted in a tri-county area of centralMichigan. The size of the sample consisted of 6,933 households derived from a 5 percent systematic sample design. The major findings of the study indicate that the average amount of time consumers devote to in-store shopping on a single shopping trip increases as the size of shopping area increases. Twenty percent of all consumers sampled shopped in a central business district. Sample consumers most frequently shopping there came from households whose incomes are less than $5,000 and $10,000 and over and whose heads are professional, managerial and white collar employees. The income groups referred to above also devoted the greatest amount of time on a single shopping trip. More than twice as many of the consumers sampled shopped in a regional shopping center than shopped in a central business district. Sample consumers who most frequently shopped in a regional Alfred Morton Falthzik shopping center came from households whose annual incomes are under $7,000 and $15,000 and over and whose heads are pro- fessional, managerial and blue collar employees. More than 18 percent of all consumers sampled shopped in a community shopping center. Sample consumers who most frequently shopped there came from households whose annual incomes are between $7,000 and $15,000 and whose heads are blue collar employees. More than 19 percent of all consumers sampled shopped in a neighborhood shopping center. Sample consumers who most frequently shopped there came from households whose annual incomes are between $5,000 and $7,000 and $10,000 and over and whose heads are professional, managerial and white collar employees. The sample data demonstrated an inverse relationship between household level of income and the average amount of time household members devote to shopping on a single shopping trip to a neighborhood shopping center. A majority of the consumers sampled shopped in the middle of the week and in the afternoon, with approximately equal amounts in the morning and evening regardless of the size of shopping area. ANALYSIS OF SELECTED SOCIO-ECONOMIC VARIABLES AND THEIR EFFECT ON CONSUMER TEMPORAL BEHAVIOR IN DIFFERENT SIZE SHOPPING AREAS By Alfred Morton Falthzik A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Marketing and Transportion and Administration 1969 ACPHJOWIJCDGPNHPPS I wish to thank many individuals and organizations for their aid. 1 wish especially to thank Professor Bernard J. LaLonde, Professor William J. E. Crissy, Professor Donald Taylor, all of the Michigan State University College of Business and Professor Lawrence McNitt of the University of Maryland, Department of Business Administration, for their cooperation and advice. I also wish to give special thanks to the Tri-County Planning Commission for permitting me to use data it had collected in another study. Finally, I want to express my continuing debt and appreciation to my wife, Betty, whose personal sacrifices and continuing enthusiasm were vital contributions to the project's completion. Having acknowledged the assistance I received from various people and organizations, I naturally hasten to absolve them of any responsibility for misconceptions or errors in the finished product. ii TABLE OF CONTE IJTS ACKNOWLEDGMENTS LIST OF TABLES LIST OF FIGURES Chapter I. INTRODUCTION The Market Place The Consumer . Scope of the Problem Statement of Hypotheses Method of Approach Limitations Possible Contributions Organization II. CONSUMER SPATIAL AND TEMPORAL BEHAVIOR Theory Theory of Central Places Laws of Gravitation . . , Theories of Consumer Intraurhan Travel Behavior Shopping Time General Considerations in Shopping WIMV Shopping in Cential Business Districts Shopping in Shopping Centers summary . . 0 I o 0 III. RESEARCH DESIGN Summary of Data Collection NethOdOIOQy Organization and Purpose Methods of Collecting Data Public Relations Procedure iii _‘ ((1 Chapter Utilization of Data . . . . . . Data Inputs . . . . . . . Central Business Districts and Shopping Center Listings . . Influence of Travel Time on Shtndpirn; dene . . . . . . Time Per Trip Between Shopping Areas Frequency of Trips Between Shoppi Areas . . . . . . . . Time Per Trip Within a Centra Business District . . Part of Week and Part of Day Within Central Business District . . Time Per’Tdei, Part of Week, Part llay iditlrin Ehegicnial_, Ccunmiurity and Neighborhood Centers . . Summary . . . . . . . . . FINDINGS . . . . . . . . . . . Travel Time and Shopping Time . . Hypothesis One . . . . . . Shopping Time Per Trip Between Shopping Areas . . . . . . . Hypothesis Two . . . . Frequency of Shopping Trips to Different Size Shopping Areas . . . . Hypothesis Three . . . . . Shopping Time, Part of Week and Part Day in a Central Business District Hypothesis Four . . . . . . Hypothesis Five . . . . . . Hypothesis Six . . Shopping Time, Part of Week and Part Day in a Regional Shopping Center Hypothesis Seven . . . . . Hypothesis Eight . . . . . Hypothesis Nine . . . . . . Shopping Time, Part of Week and Part in a Community Shopping Center . Hypothesis Ten . . . . . Hypothesis Eleven . . . Hypothesis Twelve . . . . . Shopping Time, Part of Week and Part in a Neighborhood Shopping Center Hypothesis Thirteen . . . . Hypottmxyis Fourimnni . . . Hypothesis Fifteen . . . . . iv “S of Page 52 52 53 S7 58 59 61 62 63 66 66 66 Chapter V. INTERPRETATIONS, SUMMARY AND CHHCLHSIDHS Central [fins 1,; L: s 1‘) 13.5 t L‘i C t ifiinu Pcrr ’Prig) iii (lericiwil Frequency of Shopping Tr p, Time Per Trip by Selected Loo;o« Economic Variables Part of the Week and Part of i , Hey Regional Shopping Center . Time Per Trip in General Fhmyquency (3f Shoppfimng'fréps Time Per Trip by Selected th1; Economic Variables . Part of the Week Part of the Inn! . . Community Shopping Center Time Per Trip in General Frequency of Shopping Trips Time Per Trip by Selected Sowic Economic Variables . Part of the Week . . . Pari;(3f tine Day . . . Neighborhood Shopping Center Time Per Trip in General , Frequency of ShOpping Triy, . Time Per Trip by Selected Socio~ Economic Variables . Part of the Week . . a Part of the Day . . . , Summary of Significant Findings Time per Trip in General . Central Business District: frequcnry, time, part of week and day ReSional Shopping Center: fchUonoy, time, part of week and day Community Shopping Center: fvwguvww’ time, part of week and day Neighborhood Shopping Center: time, part of week and day Implications and Conclusions . Suggestions for Future Research fiIBIJINSRAlWiY . . . . . . . . . APPENDICES A B Definitions . . . . . . . Sample Selection Procedures . frequaniy, M II“ rs.) ., l L...J r\ z I ' g (c .2 c APPENDICES Page C Arrangement of Household Universe Information . . . . . . . . . . . 1H6 D Accuracy Checks and Public Relations Procedures . . . . . . . . . . . 1A8 E Questionnaire . . . . . . . . . . . 15M F Derived Statistics and Supportive Data . . . 160 vi 11.3 15.14 14.5 14.6 LIST OF TABLES Incidents of Downtown Shopping by Women City Dwellers and Suburbanites Shopping Center Traffic Zones . . . Summary of Statistical Values Derived From Testing Relationships Between Shopping Time and Travel Time to Different Size Shopping Areas . . . . . . Average Shopping Time Per Trip Between Shopping Areas Summary of Statistical Values Derived From Testing Differences Within Selected Socio—Economic Variables and Frequency of Shopping Trips Made to a Central Business District, Regional, Community and Neighborhood Shopping Centers Summary of Statistical Values Derived from Testing Differences Within Selected Socio—Economic Variables and Average Amount of Time Devoted to Shopping Fer Trip to a Central Business District Summary of Statistical Values Derived from Testing Differences Within Selected Socio—Economic Variables and Part of the Week Shopping Occurs in a Central Business District . Summary of Statistical Values Derived from Testing Differences Within Selected Socio-Economic Variables and Part of the Day Shopping Occurs in a Central Business District . . . . vii 70 7A Table 14.7 14.8 14.9 I4.10 U.ll “.12 “.13 13.114 Summary of Statistical Values Derived from Testing Differences Within Selected Socio—Economic Variables and Average Amount of Time Devoted to Shopping Per Trip to a Regional Shopping Center Summary of Statistical Values Derived from Testing Differences Within Selected Socio—Economic Variables and Part of the Week Shopping Occurs in a Regional Shopping Center Summary of Statistical Values Derived from Testing Differences Within Selected Socio-Economic Variables and Part of the Day Shopping Occurs in a Regional Shopping Center . . . . Summary of Statistical Values Derived from Testing Differences Within Selected Socio—Economic Variables and Average Amount of Time Devoted to Shopping Per Trip to a Community Shopping Center Summary of Statistical Values Derived from Testing Differences Within Selected Socio—Economic Variables and Part of the Week Shopping Occurs in a Community Shopping Center Summary of Statistical Values Derived from Testing Differences Within Selected Socio-Economic Variables and Part of the Day Shopping Occurs in a Community Shopping Center . . . . . . Summary of Statistical Values Derived from Testing Differences Within Selected Socio-Economic Variables and Average Amount of Time Devoted to Shopping Per Trip to a Neighborhood Shopping Center Summary of Statistical Values Derived from Testing Differences Within Selected Socio— Economic Variables and Part of the Week Shopping Occurs in a Neighbor— hood Shopping Center . . . Summary of Statistical Values Derived from Testing Differences Within Selected Socio-Economic Variables and Part of the Day Shopping Occurs in a Neighbor— hood Shopping Center . . . . viii 82 Q 1’ U U 88 90 9M Table F—U F-5 F-6 F-7 F-8 F—9 .16 Summary of Rejected Null Hypotheses for Central Business District, Regional, Community and Neighborhood Shopping Centers Frequency of Shopping Trips Made to Different Shopping Areas by Various Income Groups Frequency of Shopping Trips Made to Different Shopping Areas by Various Occupational Gitmnrs Frequency of Shopping Trips Made to Different Shopping Areas by Various Household Life Cycle Groups Frequency of Shopping Trips Made to Different Shopping Areas by Occupa— tional Status of Wife Frequency of Shopping Trips Made to Different Shopping Areas by Various Automobile Ownership Groups Average Time Devoted to In—Store Shopping Per Shopping Trip in a Central Business District by Various Income Groups Average Time Devoted to In—Store Shopping Per Shopping Trip to a Central Business District by Members of Households Whose Head Falls in Various Occupational Categories . Average Time Devoted to In—Store Shopping Per Shopping Trip to a Central Business District by Various Life Cycle Stages Average Time Devoted to In-Store Shopping Per Shopping Trip to a Central Business District by Members of Households in Which the Wife Does or Does Not Work Average Time Devoted to In—Store Shopping Per Shopping Trip to a Central Business District by Various Automobile Owner— ship Groups Response of Consumers in Various Income Groups to the Part of the Week Shopped in the Central Business District ix Page l6u 165 166 166 167 167 168 16 \O F—lA F-16 F-l9 F—2O F-21 F-22 F-23 Response of Consumers in Various Income Groups to the 3art of the Week Shopped in the Central Business District Response of Consumers in Households Whose Head Falls in Various Occupational Categories to the Part of the Week Shopped in a Central Business District Response of Consumers in Various Life Cycle Stage Groups to the Part of the Week Shopped in a Central Business District Response of Consumers in Various Life Cycle Stage Groups to the Part of the Week Shopped in a Central Business District Response of Consumers in Households of Work— ing and Non—Working Wives to the Part of the Week Shopped in a Central Business District . . . . . . . Response of Consumers in Various Automobile Ownership Groups to the Part of the Week Shopped in a Central Business District Response of Consumers in Various Automobile Ownership Groups to the Part of the Week Shopped in a Central Business District . . . . . . Response of Consumers in Various Income Groups to the Part of the Day Shopped in a Central Business District . . . . . . Response of Consumers in Various Income Groups to the Part of the Day Shopped in a Central Business District . . . . . Response of Consumers in Households Whose Head Falls in Various Occupational Categories to the Part of the Day Shopped in a Central Business District . . . . Response of Consumers in Various Life Cycle Stage Groups to the Part of the Day Shopped in a Central Business District Response of Consumers in Various Life Cycle Stage Groups to the Part of the Day Shopped in a Central Business District 170 171 172 173 17A 17a 176 177 178 179 Table F-2A F—26 F-29 F-30 F-31 F—32 F-33 F-3A Response of Consumers in Households of Working and Non—Working Wives to the Part of the Day Shopped in a Central Business District Response of Consumers in Various Automobile Ownership Groups to the Part of the Day Shopped in a Central Business District Response of Consumers in Various Automobile Ownership Groups to the Part of the Day Shopped in a Central Business District Average Time Devoted to In—Store Shopping per Shopping Trip to a Regional Shopping Center by Various Income Groups Average Time Devoted to In~Store Shopping per Shopping Trip to a Regional Shopping Center by Various Occupational Groups Average Time Devoted to In—Store Shopping per Shopping Trip to a Regional Shopping Center by Various Life Cycle Stages Average Time Devoted to In-Store Shopping Per Shopping Trip to a Regional Shopping Center by Members of Households in Which the Wife Does or Does Not Work Average Time Devoted to In—Store Shopping Per Shopping Trip to a Regional Shopping Center by Various Automobile Ownership Groups . . . . . . . . . . Response of Consumers in Various Income Groups to the Part of the Week Shopped in a Regional Shopping Center . . Response of Consumers in Various Income Groups to the Part of the Week Shopped in a Regional Shopping Center . . . . . Response of Consumers in Various Occupational Groups to the Part of the Week Shopped in a Regional Shopping Center . . . . . Response of Consumers in Various Life Cycle Stage Groups to the Part of the Week Shopped in a Regional Shopping Center Xi Page 18A 187 188 189 Table F-35 F-36 F-37 F-38 F-39 F-AO F-Ul F—U2 F-A3 F-UU F-AS F-U6 F—u7 Response of Working and Non-Working Wives to the Part of the Week Shopped in a Regional Shopping Center . . Response of Consumers in Various Automobile Ownership Groups to the Part of the Week Shopped in a Regional Shopping Center Response of Consumers in Various Automobile Ownership Groups to the Part of the Week Shopped in a Regional Shopping Center Response of Consumers in Various Income Groups to the Part of the Day Shopped in a Regional Shopping Center . . Response of Consumers in Various Income Groups to the Part of the Day Shopped in a Regional Shopping Center . Response of Consumers in Various Occupational Groups to the Part of the Day Shopped in a Regional Shopping Center . Response of Consumers in Various Life Cycle Stage Groups to the Part of the Day Shopped in a Regional Shopping Center Response of Working and Non—k orking Wives to the Part of the Day Shopped in a Regional Shopping Center . . . . . . Response of Consumers in Various Automobile Ownership Groups to the Part of the Day Shopped in a Regional Shopping Center Response of Consumers in Various Automobile Ownership Groups to the Part of the Day Shopped in a Regional Shopping Center Average Time Devoted to In— Store Shopping per Shopping Trip to a Community Shopping Center by Various Income Groups . Average Time Devoted to In—Store Shopping per Shopping Trip to a Community Shopping Center by Various Occupational Groups . Average Time Devoted to In—Store Shopping per Shopping Trip to a Community Shopping Center by Various Life Cycle Stages xii H1 191 19? 196 198 19G ./ POO QOO Table F-UB F-u9 F—SO F-52 F-53 F-SA F-SS F-56 F-57 F-58 F-59 Average Time Devoted to In—Store Shopping per Shopping Trip to a Community Shopping Center by Members of Households in which the Wife Does or Does Not Work . Average Time Devoted to In—Store Shopping per Shopping Trip to a Community Shopping Center by Various Automobile Ownership Groups. Response of Consumers in Various Income Groups to the Part of the Week Shopped in a Community Shopping Center . Response of Consumers in Various Income Groups to the Part of the Week Shopped in a Community Shopping Center . Response of Consumers in Various Occupational Groups to the Part of the Week Shopped in a Community Shopping Center . . Response of Consumers in Various Life Cycle Stage Groups to the Part of the Week Shopped in a Community Shopping Center Response of Consumers in Various Life Cycle Stage Groups to the Part of the Week Shopped in a Community Shopping Center Response of Working and Non-Working Wives to the Part of the Week Shopped in a Community Shopping Center . Response of Consumers in Various Automobile Ownership Groups to the Part of the Week Shopped in a Community Shopping Center Response of Consumers in Various Automobile Ownership Groups to the Part of the Week Shopped in a Community Shopping Center Response of Consumers in Various Income Groups to the Part of the Day Shopped in a Community Shopping Center . Response of Consumers in Various Income Groups to the Part of the Day Shopped in a Community Shopping Center . xiii Page 201 201 202 203 20“ 205 206 207 208 209 210 211 Table F—6O F-61 F—62 F—63 F-6A F-65 F-66 F—67 F-68 F—69 F-7l Response of Consumers in Various Occupational Groups to the Part of the Day Shopped in a Community Shopping Center Response of Consumers in Various Life Cycle Stage Groups to the Part of the Day Shopped in a Community thopping Center Response of Consumers in Various Life Cycle Stage Groups to the Part of the Day Shopped in a Community Shopping Center Response of Working and Non-Working Wives to the Part of the Day Shopped in a Community Shopping Center Response of Consumers in Various Automobile Ownership Groups to the Part of the Day Shopped in a Community Shopping Center Response of Consumers in Various Automobile Ownership Groups to the Part of the Day Shopped in a Community Shopping Center Average Time Devoted to In—Store Shopping Per Shopping Trip to a Neighborhood Shopping Center by Various Income Groups Average Time Devoted to In—Store Shopping Per Shopping Trip to a Neighborhood Shopping Center by Various Occupational Groups . . . Average Time Devoted to In-Store Shopping per Shopping Trip to a Neighborhood Shopping Center by Various Life Cycle Stages . . . . . . . . . . Average Time Devoted to In-Store Shopping Per Shopping Trip to a Neighborhood Shopping Center by Members of Households in Which the Wife Does or Does Not Work Average Time Devoted to In-Store Shopping Per Shopping Trip to a Neighborhood Shopping Center by Various Automobile Ownership Groups . . . . . Response of Consumers in Various Income Groups to the Part of the Week Shopped in a Neighborhood Shopping Center xiv Page 212 213 21“ 215 216 217 218 218 Table F-72 F-73 F-7U F-75 F-76 F-77 F-78 F-79 F-80 F-81 F-82 F-83 F-8H Response of Consumers in Various Income Groups to the Part of the Week Shopped in a Neighborhood Shopping Center . Response of Consumers in Various Occupational Groups to the Part of the Week Shopped in a Neighborhood Shopping Center Response of Consumers in Various Life Cycle Stage Groups to the Part of the Week Shopped in a Neighborhood Shopping Center Response of Consumers in Various Life Cycle Stage Groups to the Part of the Week Shopped in a Neighborhood Shopping Center Response of Working and Non— —Working Wives to the Part of the Week Shopped in a Neigh— borhood Shopping Center . . . . . . Response of Consumers in Various Automobile Ownership Groups to the Part of the Week Shopped in a Neighborhood Shopping Center Response of Consumers in Various Automobile Ownership Groups to the Part of the Week Shopped in a Neighborhood Shopping Center Response of Consumers in Various Income Groups to the Part of the Day Shopped in a Neighborhood Shopping Center Response of Consumers in Various Income Groups to the Part of the Day Shopped in a Neighborhood Shopping Center . . . Response of Consumers in Various Occupational Groups to the Part of the Day Shopped in Neighborhood Shopping Centers . . Response of Consumers in Various Life Cycle Stage Groups to the Part of the Day Shopped in a Neighborhood Shopping Center . . Response of Consumers in Various Life Cycle Stage Groups to the Part of the Day Shopped in a Neighborhood Shopping Center . . Response of Working and Non-Working Wives to the Part of the Day Shopped in Neighbor- hood Shopping Centers . . . . . XV Page 221 222 223 224 225 226 227 228 . 229 230 231 232 233 Table F-85 Response of Consumers in Various Automobile Ownership Groups to the Part of the Day Shopped in Neighborhood Shopping Centers F-86 Response of Consumers in Various Automobile Ownership Groups to the Part of the Day Shopped in Neighborhood Shopping Centers xvi 235 CHAPTER I INTRODUCTION The temporal aspects of consumer behavior are an area which has received little attention in the marketing litera- ture. Yet there have been and continue to be changes both in the market place and in the consumer which indicate opposing forces operating to influence the amount of time consumers devote to shopping activity. Greater leisure, increased automobile ownership, higher incomes and new products are indications that the consumer has the opportunity to devote more time to shopping. Yet more product information available through the various communications media and an increase in catalog, telephone and vending machine buying are factors which indicate a lessening of the time and effort devoted to shopping. In addition, the increase in shopping centers, the growth of the suburbs and the decline of retail sales in the central business districts of most large metropolitan areas are indicative of the growing number of decentralized areas in which consumers may shop. Background' The following indicates some specific changes that I have taken place both in the market place and with the consumer . The Market Place The market place has experienced considerable change in recent years with respect to new products, retail sales in central business districts and new methods of retailing. Currently the consumer has a wider range of product choices than ever before. New products are being introduced so rapidly that 50 percent or more of them were not even in the planning stage five to ten years earlier. Also taking place in the market is a decentralization of retail sales from the central business districts of large metropolitan cities outwards to their suburbs and even beyond. Retail sales in central business districts are de— clining on a per capita basis and many are declining on an absolute basis. At the same time, retail sales in suburban areas are increasing at a rate greater than population changes in these areas, while non-metropolitan areas are gaining retail sales at a rate greater than their population increases. lJerome E. McCarthy, Basic Marketing, A Managerial Approach (Homewood, Illinois: Richard D. Irwin, Inc., 1968), p. 202. 2 Eli P. Cox and Leo G. Erickson, Retail Decentralization (East Lansing, Michigan: Michigan State University, Bureau of Business and Economic Research, 1967), pp. 18—19. (‘2) Other changes have taken place in methods of retailing. Within the past decade, the number of shopping centers has grown from 1000 in 1955 to more than 10,000 in 1967 with a 3 predicted increase to more than 25,000 by 1977. The most important reasons given by consumers for shoppingfin them are more convenience for one stop shopping, nearer to home, less traffic congestion, easier parking and more convenient store hours. Another change in retailing methods that is receiving increased emphasis in recent years is the increase in cata- log and telephone selling. The major catalog companies, Sears and Montgomery Ward, have upgraded the merchandise selection in their catalog, built new catalog stores and promoted order-by—phone services in metropolitan areas. For example, Sears has increased the number of its catalog sales offices from 950 in 1959 to 1,93“ in 1968.5 During the same period, Montgomery Ward has increased the number of its catalog stores from A07 to l,A99.6 Still another aspect of changing retail methods is the rapidly expanding sales of the vending machine industry. 3"Decade of Opportunity Seen for Shopping Center Industry," Chain Store Age, Executive Edition (July, 1967), E3U. “C. T. Jonassen, Downtown Versus Suburban Shopping (Columbus, Ohio: Ohio State University, Bureau of Research, 1955), p. 58. 5 Sears, Roebuck and Co., 1968 Annual Repprt, p. 2A. 6Marcor, 1968 Annual Report, p. 60. Most recent census year comparisons show an increase in vending sales from $8U2 million in 1958 to $1.A5 billion in 1963 representing a percentage gain of 73 percent versus a percentage gain of 22 percent for total retail trade.7 These trends are expected to continue as evidenced by the following quotation: A large portion of our consuming public wants to save shopping time and shopping weariness. . . . Hence, a counter trend towards shopping at home is evolving. Closed-circuit television and the 'phone will play an important role in spreading thig ‘ development. So will coin vending machines. An important development contributing to shopping at home has been the establishment, through national and local advertising, of thousands of brand names. Such knowledge has served not only to establish standards of quality in the minds of consumers but also to establish a basis for price comparison. Thus, the consumer can.make many impor— tant purchases with lessening amounts of shopping effort. The Consumer The consumer is also experiencing change in the form of greater leisure, higher income and greater mobility. In less than fifty years, the amount of leisure time available \JJJ the average Anericmullurs approximaicdif<finub1ed. This has \d 7Bernard J. Lahonde, "The Retailer's Dilemma: Full I ice and Full Employment," Journal of Retailing (Winter 1‘: T'V 1966—67), H3. P ‘ ‘ '"Arfiridoten: to fnioppiru; Weaxnrrsss,"(1rey Nkflrter, (rrey Advertising, Inc., Volume 3”, Number 12, December, 1963. been the result of a number of trends. First, earlier retirements are much more frequent than they were a few years ago; and with social security and pensions, the average retiree's income has not been drastically impaired. Second, both work days and work weeks have been shortened. Third, there has been a tremendous increase in labor saving devices in the home. With some variation, these trends have occurred throughout the whole population regardless of location, occu— pation and income; and they have occurred without any impair— ment of purchasing power. Along with increased leisure there also has been an increase in family incomes and expenditures. Between 1950 and .1966, per capita disposable income based on 1958 prices had increased from $1,6A6 to $2.29U.9 During the same period and with 1958 prices as a base, per capita consumption expendi- i tures increased from $1,520 to $2,111.10 In terms of constant dollars, there were relatively fewer families at the lower income levels and more at the upper levels. Incomes of over $10,000 were reported by only seven percent of the families in 1959, but by 196U this had increased to 22 percent. In 19A9 more than 50 percent of Economic Report of the President (Washington, D.C.: United States Government Printing Office, January, 1967), p. 232. Mlbid., p. 232. ‘ all families had incomes of under $5,000, but by 196A only .— . .. -1"; 3) percent were below that amount., Coupled with greater leisure and higher incomes, the consumer has acquired more mobility due to his increased automobile ownership. Thanks to installment credit and the almost universal tendency to regard the automobile as a necessity, ownership has spread throughout all income classes. As of 1960, there were approximately 1.9 adults for every automobile registered, and by 1980 the forecast - 73‘. 18 for 1.1 adults for every automobile registered.“’ Fur~ thermore, as income increases, so does the possibility of a household owning more than one automobile. The incidents of second car ownership increased from one percent in house~ holds at the lowest levels of income to 39 percent among .1 households in the $10,000 plus bracket.lt A new consumer has emerged~—one with more money, a wider choice of goods to spend it on, more mobility, more leisure to enjoy his affluence and new retailing methods to cater to his wants. ! i l 110. S. Department of Commerce, Americans at Mid— Decade, Series P. 23, No. 16 (Washington, D. C.: Government Printing Office, 1960), p. 28. l2Hans H. Lansberg, et a1., Resources in Ameripan's Future (Baltimore, Md.: Johns Hopkins Press, 1963): p. 129. ’15 “\ l”Ibid., p. 130. a Scope of the Problem The marketing literature reflects a number of distinct approaches to studying the consumer, namely, demographic, psychological, sociological, spatial and temporal or some I I. “i ‘7 ff. 1 0 “V“ o combination of these.‘KThe demographic approaeh cons1sts of delineating consumers' behavior with respect to age, sex, “ncolor, income, level of education and kindred variables. ;The , 3 .’ ('3 "' :. 1’ . , } ,-— ’ . ,psychological approach consists of primarily of viewing the —-—-—..-a._ ._.. _.__ __ .. _ _ _ _4-. influence of such molar variables as motives, beliefs, atti- tudes, expectations, learning and personality on consumer {/22} ” .1 ' behavior. ‘Theflsociological,approach postulates the existance of reference groups and attempts to determine‘the effects of group influences on consumer choice and behavior. The spatial approach to consumer behavior is a study of the day-to-day travel patterns of consumers for the purpose of determining those factors which cause differences in propensities for travel. The temporal approach to consumer behavior deals rimarily with the amount of time consumers devote to the 'O (l hopping activity. Inasmuch as little research has been devoted to studying the temporal aspect of consumer behavior, the present investigation focusses on this. Statement of the Problem Shopping areas differ with respect to the number of stores contained within them as well as the variety and quality of goods sold. A central business district normally contains more stores and a greater variety of goods than does a regional shopping center which in turn contains more stores and a greater variety of goods than a community shopping center. At the same time, a community shopping center contains more stores and a greater variety of goods than does a neighborhood shopping center. Since the size of shopping areas differ, a relationship may exist between the average amount of time consumers devote to shopping on a single shopping trip and the size of the area in which shopping occurs. There exist constraints on consumer shopping time which might explain variations among individual households with respect to the time devOted to shopping in the areas in which they shop. One such constraint is the location of consumers in relation to shopping facilities which they most generally use. The time devoted to travel as a result of the distance to the shopping area as well as the varying road conditions which may exist may influence shopping time. Other variables which may correlate with or influence shop— ping time include family income, occupation, stage in the life cycle, wife working outside the home and automobile availability. Therefore, there are five questions which will be investigated: 1. Does the amount of time devoted to travel on a single shopping trip influence the amount of time devoted to shopping in a central business district and in different size shopping centers? 2. Is the size of the shopping area related to the average amount of time consumers devote to shopping on a single shopping trip? 3. Do some consumers shop more frequently in one kind of shopping area than another? u. Can differences between the average amount of time consumers devote to shopping on a single shopping trip in the areas in which they do shop be explained by selected socio-economic variables? 5. Can differences between the part of the day and part of the week in which consumers shop where they do shop be explained by selected socio—economic variables? Statement of Hypotheses The hypotheses are presented in the following order. One, the relationship between travel time and shopping time in a central business district and different size shopping centers. Two, the general difference in shopping time as related to different size shopping areas. Three, the relationship of selected socio-economic variables and the frequency of shopping trips made between a central business district and different size centers. Four, the relationship between selected socio-economic variables and the average _. .- u-L \_. lO amount of time households devote to in-store shopping on a single shopping trip in a central business district as well as the part of the week and part of the day shopping occurs. Five, the relationship of selected socio-economic variables to average amount of time households devote to in-store shopping on a single shopping trip in different size shopping centers as well as the part of the week and part of the day shopping occurs. 1. As the amount of time devoted to travel to a A. central business district B. regional shopping center C. community shopping center D. neighborhood shopping center increases, the amount of time devoted to in— store shopping on a single shopping trip increases. - 2. .There is no significant difference between a central business district, regional, community and neighborhood shopping centers and the average amount of time consumers devote to in-store shopping on a single shopping trip. 3. Frequency of shopping trips made to central business district, regional, community and neighborhood shopping centers is independent of household level of income occupations of heads of households household life cycle stages the wife working outside the home the number of automobiles owned by households. LTJUOUJZD U. There is no significant difference between the average amount of time household members devote to in-store shopping on a single shopping trip to a central business district and A. household level of income B. occupations of the heads of households C. household life cycle stages CD 11 . the wife working outside the home E. the number of automobiles owned by households. There is no significant difference between the part of the week household members shop in a central business district and household level of income occupations of the heads of households household life cycle stages the wife working outside the home the number of automobiles owned by households. [UUOCDZD There is no significant difference between the part of the day household members shop in a central business district and household level of income occupations of the heads of households household life cycle stages the wife working outside the home the number of automobiles owned by households. LTJUO’OUZD There is no significant difference between the average amount of time household members devote to in-store shopping on a single shopping trip to a regional shopping center and household level of income occupations of the heads of households household life cycle stages the wife working outside the home the number of automobiles owned by households. LTJUOCJZD There is no significant difference between the part of the week household members shop in a regional shopping center and A. household level of income B. occupations of the heads of households C. household life cycle stages D. the wife working outside the home E. the number of automobiles owned by Inuiseluolds. 'flnerw; is n!) :3ig:ni.fl C?lntl (lit‘ft‘r par4;rvf tlmatlay lurisehcfl(lrnembewuz:zhop irn a regirwnfl shoppiru; center’anul 10. 11. 12. 12 household level of income occupations of the heads of households household life cycle stages the wife working outside the home the number of automobiles owned by households. WUOWID There is no significant difference between the average amount of time household members devote to in—store shopping on a single shopping trip to a community shopping center and household level of income occupations of the heads of households household life cycle stages the wife working outside the home the number of automobiles owned by households. TUDOW3> There is no significant difference between the part of the week household members shop in a community shopping center and household level of income occupations of the heads of households household life cycle stages the wife working outside the home the number of automobiles owned by households. ETJUO'CD'JD There is no significant difference between the part of the day household members shop in a community shopping center and household level of income occupations of the heads of households household life cycle stages the wife working outside the home the number of automobiles owned by households. FCCOCUID There is no significant difference between the average amount of time household members devote to in—store shopping on a single shopping trip to a neighborhood shopping center and household level of income occupations of the heads of households household life cycle stages the wife working outside the home E. the number of automobiles owned by households. UOCDZD l3 lu. There is no significant difference between the part of the week household members shop in a neighborhood shopping center and A. household level of income B. occupations of the heads of households C. household life cycle stages D. the wife working outside the home E. the number of automobiles owned by households. 15. There is no significant difference between the part of the day household members shop in a neighborhood shopping center and ID household level of income occupations of the heads of households household life cycle stages the wife working outside the home the number of automobiles owned by households. Fv-I LL. 0 LTJ'CJO To summarize the dependent and independent variables and their relationships to each other, the chart on the following page is presented. Method of Approach The Data used in this study were obtained from another study.lu The sample from which the data were compiled was taken from April through June of 1965 and consisted of a 5 percent, systematically selected quota sample of households living within a tri—county area. The size of the sample consisted of 6,933 households. Origin and destination data were compiled including trip purposes, the time of trip with respect to start and luLand-Use-Natural Resources—Transportation Study, Lansing, Michigan, Tri-County Regional Planning Commission, November, 1965. 1U Dependent Variables Time Per Part of Part of Independent Variables Trip Week Day Income Level of Income Occupation Blue collar White collar Mgr. Professional Working Wife Hon-working wife Stage in Life Cycle Single Married/no children Married/Children preschool Married/elementary school children Married/high school children or older Retired Automobile Ownership None owned One owned More than one owned U o p Q o .a > w L (DCCD-P U-Hr4 (imam m QEIC m OriH 4—)..CUJQ4 Sta Q c L o H OGJS E~p£Lm Minutes devoted to travel Figure l.l.——Independent and dependent variables used in testing hypotheses dealing with a central business dis- trict and different size shopping centers. .15 arrival, mode of travel, car availability, number of passengers and type of parking utilized. Socio-economic data for each household sampled were coupled with the above information. The effect of distance on the time devoted to in—store shopping will be minimized by analyzing the sample data to arrive at a travel time to shopping facilities which does not significantly effect the amount of time devoted to in— store shopping. The analysis will be performed for different size shopping centers and a central business district. Limitations 1. Any trips which resulted in the respondent travel- ing less than two blocks, or any destination to which the respondent walked were not recorded in the Land Use Study. 2. No distinction was made between single purpose and multiple purpose shopping trips in the Land Use Study. Therefore, the time devoted to shopping on both single and multiple purpose shopping trips are combined for purposes of computing the average time devoted to shopping. This could have the effect of increasing averages in some cases and decreasing them in others. 3. The findings resulting from the investigation will reflect the shopping behavior of households residing in a tri—county area in a midwestern state. The typicality of the data and their application to other areas can be inferred bUt not proven. 16 Possible Contributions The investigation will fill at least part of the void? that exists in the marketing literature concerning the temporal aspects of consumer shopping behavior. It will also provide a benchmark against which future research on consumer temporal behavior can be compared to determine if any changes have occurred. Knowledge of consumer temporal behavior would be valuable to merchants comprising a retail complex with respect to any accommodations they might wish to make in order to serve more effectively the needs and wants of shoppers. Previous research has indicated the decline of the central business districts of large communities. This decline has been attributed to the growth of shopping cen- ters competing with the central business district as well aS~ to the growth of suburbs. If the central business district is to impede or to stop its rate of decline, one must identify both those shoppers who shop most frequently and devote the greatest amount of their shopping time downtown as well as those who do not. Thus, retailing strategies could be developed which would be used as a means of maintaining pre- sent customers as well as luring former cuStomers to return. Knowledge of the amount of time consumers devote to shopping and to where they shop would not only be of aid to the central business district but also to shopping center developers. If shopping center markets can be segmented in 1? terms of types C' customers and customer shopping habits, retail strategies could be developed to more closely appeal to consumers in those particular segments. Organization This research paper is organized into four additional chapters and four appendices. The second chapter is con— cerned with the search of the literature including a brief discussion of appropriate theory applicable to the research and a detailed discussion of other research findings related to the variables utilized in the investigation. The third chapter is concerned with a summary discussion of how the Tri—County data were collected and how the data are used in testing the hypotheses. The fourth chapter deals with the acceptance or rejection of hypotheses and the fifth chapter with a summary and conclusions reached. In Appendix A is a list of definitions. Appendix B includes a detailed dis— cussion of the universe, sample design and how the sample households were selected in the Tri—County study. Appendix C is a map showing cities and townships of Ingham, Clinton and Eaton counties. Appendix D is a discussion of the pub- lic relations procedures used in gaining the cooperation of households in the Tri-County area. In Appendix E is the questionnaire used in the Tri-County study. Appendix F contains the data utilized in testing the hypotheses in the form of contim-{oncy tables for Chi-square and tables for Analysis of Variance. CHAPTER II CONSUMER SPATIAL AND TEMPORAL BEHAVIOR The literature review will be presented in two main sections. The first section covers theory relevant to spatial behavior; the second section deals with relation- ships between the independent and dependent variables utilized in the research. Theory Theory of Central Places Central Place theory assumes that (1) identical con- sumers are distributed at uniform densities over an unabounded plane and can move freely in any direction they choose, (2) prices of goods increase in direct proportion as distance from the point of supply increases, (3) goods are purchased from the closest place, (A) all consumers must be served and (5) complete freedom of entry of stores. Because the price to the consumer increases as the distance to the store increases, a circle may be drawn around a store depicting the distance beyond which consumers will not travel to purchase goods. Since all consumers must he served, a number of stores will be established across the 18 19 plane each having its own circular trading area. Each store's circular trading area is tangential to six others. However, because of the geometric nature of tangential circles, open spaces exist between circles and therefore some consumers are not served. To meet the requirement that there be no un— served area between market areas, the circles must overlap. Businessmen will compete for consumers within the area of overlap. Since consumers will visit the closest store to save transportation costs, the areas of overlap will be bisected, and each store's trading area will become a hexa- gon. The number of hexagonal market areas will increase up to the point where all businessmen are earning normal profits. A large number of goods and services have to be pro- vided for each of the consumers on the plane. All such goods and services are provided for consumers living within each of the hexagonal trading areas described above. However, some goods and services can be profitably provided by busi- nessmen through smaller hexagonal market areas than would be necessary for other goods. Given that existing centers already provide all goods, the most profitable location for businessmen providing a lower order of goods would be at the center of three tangential larger trading areas. Thus, every higher — order center is surrounded by a ring of six centers of next lower order located at the six points of its hexagon. The size of the hexagonal market area for the next lower order of goods is equal to the market area for 20 for the same goods as provided by the larger center. As many lower order centers are established as are profitable to do so. Thus, a hierarchy of centers based upon market area sizes are established providing lower and lower orders of goods with the larger centers providing the same goods 1 2 as smaller ones, but more of them. ’ Laws of Retail Gravitation Central place theory deals primarily with alternative urban centers. Reilly and Converse utilized a gravitational model to explain the movement of retail trade among cities. ”I The studies conducted by Reilly and Converse have led to the development of models which are termed laws of retail gravitation. These laws apply specifically to the purchase of shopping and specialty goods rather than convenience goods. The original law developed by Reilly states: Two cities attract retail trade from any inter— mediate city or town in the vicinity of the breaking point approximately in direct proportion to the popu— lation of the two cities and in inverse proportion to the square of the distances from these two cities to the intermediate town. 1W. Christaller, Die Zentralen Orte in Suddeutschland (Jena: Gustav Fisher Verlag), 1933. 2August Losch, Die raumliche Ordnung der Wirtschaft. 2nd Ed. Jena: Gustav Fisher Verlag.‘ Translated by w. H. Woglom and w. F. Stolper, as The Economics of Location (New Haven: Yale University Press), 195U. 3W. J. Reilly, The Law of Retail Gravitation (New York: William J. Reilly Company, 19317, p. 9. 21 Figure 2.l--Maximum packing of tangent circles. Figure 2.2--(left) Overlapping circles create areas of competition. Figure 2.3--(right) Consumer choice leads to hexagonal market areas. Figure 2.A--Hierarchy of market areas. 22 This statement can be expressed mathematically as follows: 1. Ba is the proportion of retail trade from the intermediate town attracted by City A. 2. R is the proportion attracted by City B. 3. P is the population of City A. a A. Pb is the population of City B. 5. Da is the distance from the intermediate town to City A. 6. Db is the distance from the intermediate town to City B. A second formula, derived from Reilly's formula and used to measure the movement of shopping goods trade, was developed by Converse and his associates. It is known as the breaking point formula and is written as follows: In this formula the breaking point between two cities is the intermediate community which divides its shopping goods 0 O u trade equally between the two Cities. Thus, the Converse 1: _ I George Schwartz, Development of Marketing Theory -’Jltrsigr>, I] lin<)1s: {huutlu~e:rter71 PLdili;dliru5 Cc>., 19(335, D- 12. 23 formula can be utilized to determine the trading area of a city and the Reilly formula to determine the extent to which retail trade from intermediate towns should be divided between two trading centers. Another law of retail gravitation developed by Converse concerns the proportion of retail trade a smaller town will lose to a larger trading center. The law is stated as follows: A trading center and a town in or near its trade area divide the trade of the town approximately in direct proportion to the populations of the two towns and inversely as the square of the distance factogs, using A as the distance factor of the home town. Theories of Consumer Intraurban Travel Behavior The Reilly and Converse laws of retail gravitation are related only to alternative urban centers and the transporta— tion networks linking them. Other theories attempt to ex— plain consumer travel behavior within a city. Troxel suggests that travel habits are formed by a desire to maxie mize net return of travel over a period of time.6 That is to say, increased travel costs may be incurred if expectations of greater returns from trips are possible. Thus, consumers 5Paul D. Converse, "New Laws of Retail Gravitation," Journal of Marketing, Vol. XIV (October, 19A9), p. 382. Emery Troxel, Economics of Transport (New York: Rinehart and Company, Inc., 1955), ch. 7. 21: will travel further to a shopping area as the likelihood of achieving greater success in shopping increases. An extension to Troxel's theory suggests that the minimum number of items necessary to induce a customer to 7 That shop at a given store will increase with distance. is, the high shopping costs of the distant customer can be overcome only by a high probability of a successful shopping trip. Furthermore, for every value N (the number of items carried) there will be a maximum distance the consumer will be willing to travel to a store. A more definitive expression of the above theories is based upon the gravity concept indicated below. A. -..=k——J—— lJ D ija where: Fi' = expected frequency of interaction J between point i and destination j Aj = attraction to the jth destination DiJ = distance from the point of origin i to the jth destination k = a constant a = a parameter to be estimated 7William L. Garrison et al., Studies of Highway Develop- ment and Geographic Change (Seattle: University of Washington Press, 1959), p. 53. 8 Ibid., p. 165. 25 The above formulation is based on the postulate that the potential interaction that exists between a consumer and various locational sources within an urban area varies directly with the size or attraction of each of these sources and inversely with the distance separating each of these sources from the consumer's point of origination.9 "Huff points out, however, that the gravity concept is essentially an empirical notion and has very little, if any, theoretical substance. "It tells nothing about why observed regularities occur as they do under various situations and, as a consequence, leaves one at a loss when discrepancies occur that cannot be accounted for."10 In light of the lack of theory surrounding the gravity concept, Huff presents a conceptual analysis of consumer spatial behavior which includes five important factors that affect the spatial patterns of consumers.11 The first of these is the impact of merchandise offerings. Consumers generally do not know in advance whether particular shopping areas will necessarily fulfill specified purchase desires. 9David L. Huff, "Ecological Characteristics of Con- sumer Behavior," Papers and Proceedings, Vol. 7 (Philadelphia, Pa.: Regional Science Association, 1951), p. 19. 10 Ibid., p. 20. 1For a broader conceptualization of consumer spatial behavior see David L. Huff, A Topalogical Model of Consumer Space Preferences, Occasional Paper Number 11, Seattle, Wash.: University of Washington, College of Business Administration, Bureau of Business Research, December, 1959. 26 However, they do have an a priori knowledge of the likeli- hood that various shopping areas might satisfy their needs and wants. This likelihood increases or diminishes depend- ing upon the number of items of the kind that are desired and felt are carried by various shopping locations. Thus, the greater the number of items carried by a particular shopping area, the greater is the consumer's expectation of making a successful shopping trip. "Therefore, consumers will show a willingness to travel further distances for various goods and services as the number of such items available at various locational sources increases."12 The second is the impact of travel costs. As the con— sumer devotes more time to traveling to various shopping locations, the less time he has available to shop.‘ Thus, in making a shopping trip the consumer will consider the benefit derived from incremental travel time against the possible loss of shopping time. Therefore, "The anticipated cost of transportation, the time and effort involved in i I preparing for, as well asfmaking the trip, and other oppor- i.ur1itixas tinit nur;i, hr: fY)rew{orue, t(?n HmHQOHoo m: .mNmHm zoaafiz :ma cmwoq mHHOh. mmm mnmam oaofimxoosm mmm smpcmo ampsmam omH popcmo :mmoq 2mm Loccmpm ocoN meow mcow oammmpe poocponzwflmz oammwpe szQSEEoo OHQMmLB HMCOmem .mmcom oagmmse poucmo mafiaaonmln.a.m mqm¢e 56 Influence of Travel Time on Shopping Time The amount of time consumers devote to in-store shop- ping on a single shopping trip can be influenced by both the amount of time necessary to reach the shopping desti- nation as well as the amount of time necessary to reach the next following destination other than for shopping. The amount of travel time to and from the shopping desti- nation can in turn be affected by the nature of the roads utilized and the amount of traffic congestion occurring at different times of the day. One of the purposes of the investigation is to determine the average amount of time per shopping trip consumers devote to in-store shopping in different size shopping areas. Therefore, it was necessary to remove the effect of travel time on in-store shopping time in order to minimize any influence caused by travel time. Linear correlation analysis was used to determine the extent and nature of relationship between travel time and in-store shopping time as the latter occurs in the central business district or in shopping centers. The time de— voted to shopping is the dependent variable and defined as the time actually spent at a single shopping area. The time devoted to travel is the independent variable and defined as the time involved in traveling from an origin to a single shopping destination. When a non-shopping destination immediately follows a shopping destination, 57 the time devoted to travel to the non-shopping destination was considered as part of the travel time. To the extent travel time influenced shopping time as shown by the correlation analysis, all the shopping time. data used in the testing of hypotheses dealing with a particular shopping area were adjusted. For example, if the relationship between travel time and shopping time at 'a shopping area was positive, the part of total shopping time influenced by travel time was deducted from the shop— ping time of each consumer shopping in the area. If the relationship was negative, the part of total shopping time influenced by travel time was added to the shopping time of each consumer shopping in the area. The net effect of the additions to or subtractions from each consumer's shopping time was shopping time for each consumer void of the influ- ence of travel time. It was the adjusted shopping times that was used in the computation of the average amount of time devoted to shopping by consumers in each of the shop— ping areas. Time Per Trip Between Shopping Areas Once the effect of travel time on shopping time has been determined and appropriate adjustments made to the shopping data, the testing of other hypotheses took place. The first hypothesis tested was the relationship of size of shopping area to average amount of time devoted to in-store shopping. The procedure for testing the hypothesis involved 58 the summation of all in—store shopping times for each shopping trip made to a central business district and different categories of shopping centers. The-average amount of time devoted to in—store shopping on a single .shopping trip made to each of the shopping areas mentioned above was derived by dividing the total shopping time in each shopping area by the number of shopping trips made to each area. Analysis of variance was used and a 5 percent level of confidence set in testing for significance. Frequency of Trips Between Shopping Areas The second set of hypotheses tested deal with the relationship of selected socio-economic variables and the frequency of shopping trips made between a central business district, regional, community and neighborhood shopping centers. For each socio—economic variable utilized in the investigation a separate hypothesis was tested. For example, a test was made of the relationship between household level of income and frequency of shopping trips made by household members between different size shopping areas. Other tests. were made dealing with the relationship of frequency of shopping trips made between different size shopping areas by household members and the occupation of the head of the household, household life cycle stages, wife working outside the home and the number of automobiles owned by the house- hold. To test the hypothesis dealing with level of house— hold income and the frequency of shopping trips made between a central business district, regional, community and neighborhood shopping centers, shopping trips were compiled by household level of income made to each type of shopping area. Chi-square analysis was used and a 5 percent level of confidence set in testing for significance. Other hypotheses dealing with the relationships of the remaining socio—economic variables to the frequency of shopping trips made between shopping areas were tested using the same procedure described above. The only differ- ence was the substitution of the appropriate socio-economic variable for level of income. yTime Per Trip Within a Central Business District The third set of hypotheses was tested dealing with the relationship of selected socio-economic variables and the average amount of time devoted to in-store shopping on a single shopping trip to a central business district. As with the previous set of hypotheses, all socio-economic variables utilized in the investigation were tested separately. Therefore, the first in the set of hypotheses tested was the relationship between household level of income and the average amount of time household members devote to in—store shopping on a single shopping trip to a central business district. 60 In order to test the hypothes.s, all central busi- ness district trips were identified. Then each household sampled was placed in its appropriate income category. The time devoted to in-store shopping per single shopping trip by each member of a household falling within each category was compiled. The total of shopping time per income cate- gory was divided by the number of shopping trips made to determine the average amount of in-store shopping time per trip by consumers of each income category. The following is an example of the procedure. Income category $5,000-$6,999 $7,000—$9,999 Total shopping time 80,000 min. 180,000 min. No. of trips 1,000 2,000 Average time per trip 80 min. 90 min. Once the averages were determined, analysis of variance was used and a 5 percent level of confidence set in testing for significance. The procedure, statistical methodology and level of significance utilized for testing the hypothesis dealing with level of income and the average amount of time devoted to shopping per trip was used as a model for testing the hypo— theses relating to level of occupation, working wives, stage in the life cycle and number of automobiles owned and shop- ping per trip. The only difference in the procedure was the different categories into which household shopping time was compiled. For example, when testing the hypothesis dealing with level of occupation and shopping time per trip, household shopping time was compiled by occupational category.. 61 When testing the hypothesis dealing with whether the wife works or not and the time devoted to shopping per trip, household shopping time was compiled into two categories, namely, working wife and non-working wife. When testing the hypothesis relating stage in the life cycle with house- hold shopping time per trip, household shopping time was compiled by life cycle categories. When testing the hypo- thesis relating number of automobiles owned and household shopping time per trip, household shopping time was compiled by the number of automobiles owned by a household. Part of Week And Part of Day Within a Central Business District The fourth and fifth sets of hypotheses tested deal with the relationship of selected socio—economic variables and the part of the week and part of the day shopping occurs in a central business district. As before, all socio- economic variables utilized in the investigation were tested separately for both the part of the week and part of the day. The following methodology was used in testing hypo- theses dealing with the relationship of selected socio-’ economic variables to part of the week and part of the day. shopping occurs in a central business district. To test the hypothesis dealing with level of income and part of the week shopping occurs, each household shopping trip was compiled by income level and part of the week categories. 62 For example, the part of the week each household resident's shopping trips occur were placed in the appropriate income level and part of the week cell. Chi-square was used and a 5 percent level of confidence set in testing for signifi- cance. Other hypotheses dealing with the relationships of the remaining socio—economic variables to part of the week shopping occurs in a central business district were tested using the same procedure described above. The only differ— ences were the substitution of the appropriate socio- economic variable for level of income. The same methodology described above was used to test hypotheses relating selected socio-economic variables to part of the day shopping takes place in a central business district. The only change from the above procedure was to substitute part of the day categories for part of the week. Time Per Trip, Part of Week, Part of Day Within Regional, Community and Neighborhood Centers . The last sets of hypotheses tested deal with the relationship of selected socio-economic variables and the average amount of time consumers devote to in—store shopping on a single shopping trip to regional, community and neigh- borhood shopping centers. Other hypotheses tested deal with the relationship of selected socio-economic variables and the part of the week and part of the day shopping occurs in the aforementioned centers. All socio-economic variables 63 utilized in the investigation were tested separately for shopping time and when shopping occurs for each category of shopping center. The same procedures, statistical methodologies and levels of significance utilized above in testing hypotheses dealing with a central business district were used also in testing hypotheses for each category of center. Summary The data utilized in the investigation were supplied by the Tri—County Planning Commission located in Lansing, Michigan. The Commission had performed a transportation study during April through June, 1965, interviewing 6,933 households scattered throughout Eaton, Clinton and Ingham counties. Extensive data on household Socio-economic characteristics was collected along with origin and desti- nation of trips taken during the previous twenty—four hours by members of each household. The time each trip began and ended was also collected. A systematic sampling technique was used to select sample households from a universe list- ing supplied by the electrical power companies serving the tri-county area. Selected household socio-economic and shopping trip time data was used for purposes of testing hypotheses. The hypotheses were tested utilizing Linear Correlation, Analy- sis of Variances and Chi-square. 614 s v a a g : ’umd- I ' - x i ’3. p .0! (MIL ' Jug. -.- T U who? U | % “I 'I'. Figure 3.1—-Lansing Central Business District traffic zones. . “‘"rsx' u?“ ' 1 ! l/Wht A :LA Figure 3.2--Lansing-East Lansing traffic zones. CHAPTER IV FINDINGS The previous chapter discussed the research methodology and the statistical methods to be utilized in the testing of hypotheses. The discussion which follows reports the find— ings related to each hypothesis. Travel Time and Shopping Time Hypothesis One As the amount of time devoted to travel to a central business district regional shopping center community shopping center neighborhood shopping center U0w> increases, the amount of time devoted to in- store shopping on a single shopping trip increases. Table 4.1 shows the statistical values derived from testing of the aforementioned hypothesis as well as the outcome of each test. The relationship between shopping time and travel time to different size shopping areas was found to be significant for a community shopping center only. As a consequence, only the time per shopping trip to a community shopping center need be adjusted for the influence of travel time. 66 67 soucoo wcfiqaocm ooocponcmfioz u G popcoo mcfiaaocm zuHcsEEOQ u o soucmo mafiaoocm Hmcofimom u m pofisumfio mmosamsn Hespcmo u < "hex pomwmm mo.x mm.H mmfi H mHoH.o a mac pamooe Ho.v mm.:m msa H smmm.o 0 mac pommmm mo.A mo.o ma: H mHHo.o m mco somfimm mo.x mm.H mad H :mm.o a mac @500pso mucoam>wswm OHpmm m LoomcHEOCoo Loomsoesz pcoHOHmmooo mommnpoamm m oousoeoo Eoooopm Eoomopm cofipmaonsoo mo momswmo mo mompuoo .mmmp< mNHm pcosmmmfia on oEHB Ho>mpe ocm oEHE wcfiaqonm cmoZpom 68 Shopping Time Per Trip Between Shopping Areas Hypothesis Two There is no significant difference between a central business district, regional, community and neighborhood shopping centers and the aver— age amount of time consumers devote to in-store shopping on a single shopping trip. Table “.2 shows the tabulation of overall mean shop- ping time per trip to a central business district, regional, community and neighborhood shopping centers regardless of the SOCio-economic status of household members. The hypo- thesis is rejected and it can be inferred that a signifi- cant difference exists between the average amount of time devoted to in-store shopping by sample consumers per shopping trip made to a central business district, regional, community and neighborhood shopping centers. TABLE u.2.--Average Shopping Time Per Trip Between Shopping Areas. Central Regional Community Neighborhood Shopping Business Shopping Shopping Shopping Area District Center Center Center Time in Minutes 76.72 59.96 58.12 33.92 F ratio = 7.80, d.f. numerator = 3, d.f. denominator = 968, p <.Ol. 69 Frequency of Shopping Trips To: Different Size Shppping Areas Hypothesis Three Frequency of shopping trips made to central business district, regional, community and neighborhood shopping centers is independent of ‘ - household level of income occupations of heads of households household life cycle stages the wife working outside the home the number of automobiles owned by households sidcdunb Table “.3 is a summary table showing the statistical values derived from the performance of Chi-square analyses on the aforementioned hypothesis.. The acceptance or rejec- tion of each hypothesis also is stated in the table. The results indicate that the frequency of shopping trips made to a central business district, regional, community and I neighborhood shopping centers by household members is signi- ficantly related to household level of income and occupation of the head of the household. Significant relationships were not found for household life cycle stage, wife working outside the home and the number of automobiles owned by households. Tables F-l through F—5 are contingency tables for each of the selected socio-economic variables utilized. The tables are located in Appendix F. 70 moaocowsoc 2o omczo moafipoEOpsw no popesz u m mEoz esp oofimpso wcfixsoz omfiz n O mwwum macho mafia oaonmmsom u o oaozomson mo ommz no cofiprSooo u m Ho>ma oEOUCH oaonomsom u < ”hex uqooo< mo.A o.m m m moans pamooe mo.x m.m m. a amaze pamoo< mo.A m.w ma 0 money pomnmm moo.v e.mm e m mates somntm mo.v a.mm mH e amass oeoopzo mucmfim>fisvm osmsdmnfico Eoomohm mmwonpoazm m oousasoo no mompwoa .mpmucoo wcfiaaocm poo: upopnmfimz ocm zpficsEEoo .Hmcofiwom .uoasumfio mmocfimsm Hmspcoo m 0» wow: wafise weaaoocm mo mucosuopm one moanmfipm> oHEocoomuoHoom ompooamm cfizufiz moocopommfio wcfiumoe Eosm pm>fipmo mosHm> HmOHpmempm mo memessmlu.m.= mqmmH oEoocH oaozomsoz I ¢ "hex pamoo< mo.x Ho.H mmH m m pace pamooa mo.x Hm.o mmH H a psom pqmooe mo.x so.H mmH m u uses pqwoo¢ mo.A oo.a mmH m m psom_ pomnmm mo.v om.m mmH s < pace oEoouso mucmHm>Hscm oprm m LoamcHEocoQ poumsmesz mfimonpoazm m oousasoo Eoomopm Eoommpm mo mooswoo no mmmpwoo .pofisumfia mmmcfimsm ampucmo m on nape pom wcHannm on oouo>mm oEHB mo pesoE< owmso>< cam moanmfism> oHEocoomlofioom omuomaom :anfiz mmocohmmmwo wcfipwme Eosm om>fisoa monam> HmofipmHQMum mo mamEEzmun.:.: mqm Table “.5 is a summary table showing the statistical values derived from the performance of Chi-square analysis on the aforementioned hypotheses. The acceptance or rejec- tion of each hypothesis also is stated in the table. Hypo- theses B and D are rejected and an inference may be drawn that significant differences exist between the occupations of heads of households and whether the wife is employed out- side the home and the part of the week household members . shop in a central business district. The remaining hypotheses are accepted and thus no significant relation can be postulated regarding household level of income, household life cycle stage and the number of automobiles owned by households and the part of the week household members shop in a central business district. Tables F—ll through F-18 are contingency tables for each of the selected socio-economic variables tested and may be seen in Appendix F. Included are both tables showing the original frequency and percentage distributions as tabulated from the original data and collapsed versions. 7M moHonomson an ooczo onHpoEousm no Lonezz u m oEoc opp oonpso wszpoz oMHz u Q ommpm oHomo omHH oHonomzom u o oHonomson no omen no :oHmeSooo u m Ho>oH oEoocH oHonmmzom u < "Hex paooo¢ mo. A mm.o H m o>Hm poohom mo.v mm.: H a o>Hm poooo< mo.A mm.m m o o>Hm poofiom moo.v m:.:H m m o>Hm poooo< mo.A Hm.= : < o>Hm oEoOpso mucon>Hsom opmsvmlHno Eoooopm mowonuoozm m oopSQEoo no mooswoo .poprwHQ mmmchsm Hespcoo w :H manooo mcHoqocm xooz ecu mo whom was mmHansm> oHEocooMIOHoom oopooHom :anHz moocopmmmHo wcHumoB.Eosm oo>HsoQ mosHm> HmoHpmempm mo mameesmul.m.z mqmoH oEoocH oHonomsom u < "hex uaooo< mo.A mH.H m m me uaoooa mo.A :m.o m D me pamooa mo.x H:.m m o me pamooa mo.x mo.m : m me pamooa mo.x m:.: H a me o500pso mucon>Hsom osmSUmlHno Eoooopm womocpoomm m poHSQEoo no newswoo .pOHHumHQ mmochsm Hmppcoo m CH wagooo wcHooonm moo ecu no poem use onanHm> OHEocoomloHoom oouooHom chsz moocopommHo wchmoB Bosh oo>HHoQ mosHm> Honuprmum Mo Ahmeesmln.m.: mgmoH oEoocH oHonmmsom n < ”mom poooo¢ mo.x mo.N NH: N m co>om poooo< mo.A mH.o NH: H O co>om pamooa .mo.x as.H NH: m o cm>mm poooo< mo.A mm.o NH: N m co>om pamooa mo.x :m.H NH: A < cm>mm oEoopso mpcon>Hsvm oHpmm m LoomcHEocmo Loamsossz momonpoozm m consoEoo Eoooopm mo Eoooohm no moogwoo moogwoo .smpcoo wcHoaonm Hmconom m on QHHB pom mcHooocm op oouo>oo oEHB no pesos: owmpo>¢ new moHanpm> oHEocoomIOHoom oouooHom :Hcsz moocopommHo mchmoB Bosh oo>HpoQ mous> HooHpmHumum mo szEESmI|.s.: mqm<9 79 Hypothesis Eight There is no significant difference between the part of the week household members shop in a regional shopping center and household level of income occupations of the heads of households household life cycle stages . the wife working outside the home the number of automobiles owned by households. [TJUOUJ> Table “.8 is a summary table showing the statistical values derived from the performance of Chi-square analysis on the aforementioned hypotheses. The acceptance or rejec- tion of each hypothesis also is stated in the table. In each instance the hypothesis is rejected and an inference may be drawn that significant differences exist between all of the selected socio-economic variables and the part of the week household members shop in a regional shopping center. Tables F—3l through F—37 are contingency tables for each of the selected socio—economic variables tested and may be seen in Appendix F. Included are both tables show- ing the original frequency and percentage distributions as tabulated from the original data and collapsed versions. onocomsoc mp oocso mmHHnoEOpsm mo amassz u m oEo: on» oUHmpso wcproz oMHz n D owmum oHozo omHH UHonomsom u o oHocomson mo women no coHme:ooo n m Ho>oH oEoocH oHonomsom n H “hex somnmm mo.v 00.: H m pstm pomHmm moo.v mm.mH H a peme Homhmm mNo.v om.NH m o uanm potemm moo.v NH.mH N m pngm sometm moo.v :m.NN m a peme oEoOpso mucon>Hsom onSUwIHco Eoooopm momonpoomm m popsaeoo mo moopwoo .poucoo wcHQoocm HMCOHwom m :H mpsooo wcHooocm xooz on» No whom one moHpmHam> QHEocoomuoHoom oopooHom :Hcsz moocopmmmHo mcHumoB soon oo>Hsoo mosHm> HmoHumHumpm no assessmln.m.: mHmoH oEoocH oHonomsom u ¢ ”hex udmoo< mo.x m:.o . N m ocHz paooo< mo.A mN.N N a ocHz poonmm mNo.v om.0N OH 0 ocHz pamoo< mo.x :N.m : m mcHz pqmoo< mo.x Nm.m OH a mcHz oEoopso mucon>Hsom whosomIHno Eoooosm monocuoamm m ooHSQEoo mo mooswmo .popcoo mcHooosm HMCOHwom m :H mpsooo wcHaaonm hem on» no whom one moHansm> OHEocoomIOHoom couooHom chsz moocmpomuHQ wcHuwoB Eopm oo>HHmQ mosHm> HmoHpmeMum no zmeESmuu.m.: mqm1J1g center. However, the remaining hypotheses are accepted 811ci thus no significant relationships can be postulated regarding the other selected socio-economic variables. Tables F-“5 through F-“9 show the tabulation of over- all. mean shopping time per trip to a community shopping center for each of the selected socio-economic variables tested . 8“ moHonomsoc mp ooczo moHHpoEOpsm no Lopesz u m @505 on» oonpso wcHxLos omHz u D owmpm oHozo oMHH oHozomsom u o oHozomson no memo: no COHquSooo u m Ho>oH oEoocH oHonomoom u < "mom pamooe _ mo.x om.o NNH N m ewe pamooa mo.x mm.H NNH H a :09 powwow mo.v ::.N NNH m 0 see poooo< mo.x HN.o NNH N m see pamooe mo.x NH.H NNH m a ewe oEOopso mpCon>Hsom Oprm m nonwcHEocoo Loompoesz momozpoam: m .oopsoeoo Eoooopm Eoooosm mo woosmom mo mmopwoo .Hopcoo wcHQoocm mpHCSEEoo m on QHHB pom wcHQoonm on popo>om oEHB mo pesoE¢ owmpm>< ocm moHomHHm> oHEocoomIoHoom wouooHom cHesz mmocthHHHo wchmme gosh em>Htmo mmsHm> HmOHumempm Ho Htmsesm-u.OH.: mHmae 85 Hypothesis Eleven There is no significant difference between the part of the week household members shop in a community shopping center-and household level of income occupations of the heads of households household life cycle stages the wife working outside the home the number of automobiles owned by households. WUOUJID Table “.11 is a summary table showing the statistical values derived from the performance of Chi-square analysis on the aforementioned hypotheses. In each instance the hypothesis is accepted and hence no inferences can be drawn regarding the selected socio-economic variables and the part of‘the week sample household members shop in a community shopping center. Tables F-50 through F-57 are contingency tables for eeach of the selected socio—economic variables tested and may be? seen in Appendix F. Included are both tables showing the OIfiiginal frequency and percentage distributions as tabulated flrcnn the original data and collapsed versions. 86 wUHO£®WSO£ he poczo moHHnoEousm no Lonesz u m @505 on» no oonuso wcHxLos omHz u o owmpm oHozo omHH oHonomsom u o eHonomsoc no use: mo coHpmo3000 u m Ho>oH oEoocH oHocomsom u < "hex pamooa mo.x ON.o H m cm>mHm pamooe mo.x Ne.o H a cm>mHm autos: mo.x mm.: m o co>mHm pamooa mo.x om.m N m cm>mHm pqmooe mo.x NN.o m < cm>mHm oEoopso mucon>Hsom osmsomano Eopoopm momocpoamm m ooHSQEoo mo moopmoa .Lmucoo wcHoQosm mpH::EEoo m cH whoooo wcHaoopm xoo3 one no open new moHpmHLm> oHEocoomIOHoom oouooHem cHssz moocmsomoHQ mchmoe Eosm oo>HsoQ mosHm> HNOHpmHumpm mo mmeESmII.HH.: mqmoH mEoocH oHocomsom u < "hex poooo< mo.A mm.o N m o>Ho38 poooo< mo.A NN.H N D o>Ho39 pamooe mo.x mo.N m o m>Hmze paooo< mo.x Nm.H : m o>Ho39 Homnmm Ho.v NH.HH m a m>Hmze oEoouso mucon>H3dm opmsomlHno Eoooosm monocuoazm m oopsoeoo mo moopwoa .goucoo wcHaoonm muH::EEoo m CH wpsooo wcHooocm mom on» mo when one moHansm> oHEocoomuoHoom ompooHom cquHB wmocoHoNMHo wchwoB Eopm oo>HLom mosHm> HmOHpmeMum No mmeE:m||.NH.: mHmoH oEoocH oHonomsom u < "mom pamoo: mo.x mw.o mmH N m cmmppHce pamooa mo.x mm.H mmH H a comptHne pamooe mo.x Hm.H mmH m o cmmptHse poooo< mo.A m:.o mmH N m coopanB poohom . mo.v Hm.N me N 4 cooppHne oEoopso mucon>Hsom OHpmm m LoomcHEocoQ LoomHoEsz mommzpoazm m Ump:gEoo Eoooosm Eoooohm mo moonwoo mo mompmoo .Hmpcmo wcHooonm ooonpopanoz m ou QHHB pom wcHancm on ompo>om mEHB mo pczoE¢ mwmpo>< one moHpmem> oHeocoomIOHoom oouooHom chqu moocmsommHQ wchmoB Eopm oo>HgoQ mosHm> HmOHumHumpm mo assessmnl.mH.: mqmoH oEoocH oHocomoom u < "hex peeve: mo.A m:.o H m coopssom HomHmm mo.v mm.: H a cmmptsom pqooo< mo.A mm.m. m o cooppsom poooo< mo.A mN.o N m cooppoom poooo< .mo.A NH.H : a coopssom oEoouso mucon>Hsom osmsomcho Eoooosm momonpoomm m popsoeoo mo mooswoa .soucoo wcHoQonm poonsonszoz m CH manooo wcHQoocm sooz on» no puma new mmHanpm> oHEocoomIoHoom pouooHom cngHz moocopmMMHQ mchmoB Eopm oo>Hsoo mosHm> HmOHpmHumpm mo >pm853mnu.:H.: mHmoH oEoocH oHocomsom u < ”hex powwow mo.v m:.m N m cooHMHm poooo< mo.A :m.N N D coopmHm pamooa mo.x mm.o m o cmmpHHm patooe mo.x mm.m : m cmmpHHm somHmm mNo.v :m.mH e < cmmpon oEoopso mucon>Hsvm oLmSUmIHno Eopomsm momozpoomm m ooHSQEoo mo mooswoa .Hopcoo wcHQoonm ooonponszoz m CH mHSooo mcHooosm use on» no used was moHanLm> OHEocooMIOHoom popoonm :Hesz mmocmthuHo wcHumme Sosa et>Htmo mmsHm> HmOprHHmpm Ho scaggsmu-.mH.: mHmee mHmonuoozm oopoonom 95 n * popcoo wcHorom ooozponcwHoz n .z popcoo wcHannm zuHCSEEoo u .0 popcoo wcHooosm HmCOHwom u .m uoHpumHo mmochsm Hmpucoo u .o.m.o ”hex * x . gonzo oHHnoEOps< * * x , mmHz wcfixhoz * * * owmwm oHomo omHH * * mmMHo COHHmooooo * x x a * Ho>oH oEoocH .z .o .m .Q.m.o .z .o .m .Q.m.o .z .o .m .Q.m.o . wommmHo oHEocoomuoHoom mmm mo pawn xooz mo ppmm oHLE pom oEHB .mpopcoo wcHaoocm ooozsoncwHoz one zuHc:EEoo .Hmconmm .pOHHomHQ mmocstm Hoppcoo pom momenpoozm HHsz oouoonom mo mpmsezmla.mH.: mum<& CHAPTER V INTERPRETATIONS, SUMMARY AND CONCLUSIONS The previous chapter was concerned with the testing of hypotheses and the presentation of results. This chapter is concerned with the interpretation of findings, summary, implications and conclusions reached. Central Business District Time Per Trip in General In Table “.1 is presented the average time devoted to shopping per trip between a central business district, regional, community and neighborhood shopping centers by consumers in the sample. The different times between shop- ping areas was found to be significant with the greatest average time, 76.72 minutes, devoted to in-store shopping in a central business district. Frequency of Shopping Trips Significant differences were found between both house- hold level of income and occupational class of the head of the household with respect to the frequency of shopping trips made to a central business district by sample household members. However, no significant differences were found within 96 97 household life cycle stage, wife working outside the home and the number of automobiles owned by household categories and the frequency of shopping trips made to a central busi- ness district. V Income.—-The data in Table F-l suggests that 20 per- cent of all consumers sampled shopped in a central business district. When data on consumers are classified by annual household income, the data indicate that those earning less than $5,000 and those earning $10,000 and over are. more likely to shop in a central business district than consumers of households earning between $5,000 and $10,000 per year. Two inferences seem warranted. First, lower income groups are more likely to live nearer to a central business, district than are other income groups and are likely to shop more frequently therein as a matter of convenience. Second, because what one buys is more socially Significant as income increases, high income groups shop more frequently in a central business district because of the greater variety and superior quality of merchandise carried by the merchants in most central business districts. Occupational Class.--The data in Table F—2 relating frequency of shopping trips made to various shopping areas by members of households whose heads were of different occupational categories were found to be significant. The data tend to indicate that consumers of professional and 98 managerial households as well as consumers of white collar households are more likely to shop in a central business district than are consumers from blue collar households. Time Per Trip by Selected Socio-Economic Variables A significant difference was found between household level of income and the average amount of time sample house- hold members devote to in-store shopping on a single shopping trip to a central business district. No significant differences were found within the remaining socio-economic. household classifications. Income.--Tab1e F-6 shows the average amount of time devoted to in-store shopping in a central business district by consumers of households of various income levels. Differ- ences between households were found to be significant. The data tend to indicate that consumers from sample households earning less than $5,000 and households earning between $15,000 and $25,000 devote the greatest amount of time per shopping trip to a central business district. The least amount of time is devoted by consumers from households earning between $5,000 and $7,000 and $25,000 and over. Part of the Week and Part of the Day Significant differences were found between the occupa— tion of the head of the household classes and the part of the week sample household members shop in a central business district. Similar findings were made with respect to the 99 occupational status of the wife. However, significant differences were not found within the remaining selected socio-economic variables of household level of income, household life cycle stage, the number of automobiles owned by household and the part of the week shopping occurred. No significant differences were found within any of the selected socio—economic variables and the part of the day shopping occurred in a central business district. The data in Tables F-12 and F-20 do indicate, however, that 82.7 percent of consumers sampled shop in the middle of the week while 58.6 percent shop in the afternoon, 23.6 percent shop in the morning and 17.8 percent shop in the evening in a central business district. Occupational C1ass.--The data in Table F-l3 shows the relationship between head of the household occupational cate- gories and the part of the week household members shop in a central business district. The data in the table tend to indicate that consumers from professional and managerial and blue collar households are more likely to shop in a central business district in the middle of the week than are consumers from white collar households. Emplgyment Status of Wife.--Table F-l6 shows the relationship between employment status of the wife and the part of the week sample household members shop in a central business district. The data in the table suggest that con— sumers from sample households in which the wife is employed 100 tend to shop more frequently in the end of the week in a central business district than do consumers from sample households in which the wife is not employed. Regional Shopping Center Time Per Trip in General .As was pointed out earlier, significant differences were found with respect to the average amount of time sample consumers devote to shopping on a single shopping trip with— in different size shopping areas. The data in Table “.1 indicate that consumers on the average devoted 59.96 minutes to in-store shopping per trip to a regional shopping center compared to 76.72 minutes in a central business district. I Frequency of Shopping Trips Significant differences were found to exist between both household level of income and occupational class of the head of the household with respect to the frequency of shop- jping trips made to a regional shopping center by sample household members. However, no significant differences were found within the remaining selected socio—economic variables of household life cyclestage, wife working outside the hcmm~and the number of automobiles owned by households. Income.--The data in Table F-l indicate that “2.6 permant of all consumers sampled shopped in a regional shopping 101 center compared to 20 percent who shopped in a central business district. When consumers are classified by annual household level of income, the results indicate that con- sumers from sample houSeholds earning less than $7,000 are more likely to shop in a regional shopping center than con- sumers from households earning $7,000 and over. .The data tend to show lower income groups, under $7,000, shopping frequently in both a central business district and regional shopping center. It is likely that consumers of such income groups shop for lower priced mer- chandise. Regional shopping centers would most likely have a wide selection of such merchandise and therefore, the high frequency of shopping in a regional shopping center by such groups. Occgpational Class.-—The data in Table F72 relate frequency of shopping trips made to a regional shopping center by members of sample households whose heads are of different occupational categories. The data suggest that professional and managerial and blue collar households are more likely to shop in a regional shopping center than are households whose head is a white collar worker. 'Pime Per Trip by Selected Socio-Economic Variables Relationships were tested between the average amount V of’time consumers devote to shopping on a single shopping ‘trip to a regional shopping center by household level of 102 income, occupational class of the head of the household, household life cycle stage, occupational status of the wife and the number of automobiles owned by households. No significant differences were demonstrated. Part of the Week Significant differences were found with respect to all of the selected socio-economic variables and the part of the week in which shopping occurred in a regional shopping center. Income.--The data in Table F-32 indicate that differ- ences exist between household level of income and the part of the week sample household members shop in a regional shopping center. The data suggest that consumers from sam- ple households earning $3,000 to $5,000, $7,000 to $10,000 and $15,000 and over are more likely to shop in the weekend at a regional shopping center than consumers from households earning less than $3,000, $5,000 to $7,000 and $10,000 to $15,000 per year. Taking all sample income groups as a whole, 76.2 percent shop in the middle of the week in a regional shopping center compared to 82.7 percent in a central business district. Occupational Class.--The data in Table F-33 indicate that differences tend to exist between occupational cate- gories of heads of households and the part of the week household members shop in a regional shopping center. The data suggest that consumers from sample households whose 103 head is a white collar employee are more likely to shop 0n the weekend than are consumers from sample households whose heads are either professional and managerial or blue collar employees. Life Cycle Stages.—-The data in Table F-3“ indicate that differences exist between consumers from households in various life cycle stages and the part of the week they shop in a regional shopping center. Consumers from households in which there is at least one preschool child and consumers from households in which there is at least one high school child or older are more likely to shop in the middle of the week than are consumers from households in other life cycle stages. Employment Status of Wife.--The data in Table F-35 indicate that differences exist between members from sample households in which the wife does or does not work outside the home and the part of the week they shop in a regional shopping center. The data indicate that consumers from sam- ple households in which the wife is employed tend to shop more frequently in the end of the week in a regional shop- ping center than do consumers from sample households in which the wife is not employed. Number of Automobiles Owned.——Differences were found to exist between the number of automobiles households owned and the part of the week household members shop in a regional shopping center. The data in Table F-37 suggest that 10“ consumers from households in which two or more automobiles are owned are more likely to shop in the middle of the week in a regional shopping center than are consumers from households owning one automobile or less. Part of the Day Of the selected socio-economic variables included in the investigation, only differences between household life cycle stages were found to be significant with respect to the part of the day members from sample households shopped in a regional shopping center. However, when taking con- sumers as a whole regardless of household life cycle stage, 52.1 percent shopped in the afternoon in a regional shopping center, 26.5 percent in the evening and 21.“ percent in the morning. Life Cycle Stage.-—The data in Table F—“l tend to indicate that consumers from single and retired households as well as consumers from households in which there are no children and at least one preschool child are more likely to shop in the afternoon at a regional shopping center than are households in which there exists at least one elementary school child or at least one high school child or older. Consumers from households in which there is at least one elementary school child or at least one high school child or older are more likely to shop in the evening than con- sumers from households of other life cycle stages. Con— sumers from households in which the head is retired as well 105 as consumers from households in which there is at least one elementary school child or at least one high school child or older are more likely to shop in the morning at a regional shopping center than are consumers from households in other life cycle stages. Community Shopping Center Time Per Trip in General The data in Table “.1 indicate that consumers on the average devoted 58.12 minutes to in-store shopping per trip to a community shopping center compared to 59.96 minutes to a regional center and 76.72 minutes to a central business district. Significant differences also were found with respect to the frequency of shopping trips made to a commun- ity shopping center by members from sample households having various socio-economic characteristics. Frequency of Shopping Trips Significant differences were found to exist between both household level of income and occupational class of the head of the household with respect to the frequency of shopping trips made to a community shopping center by sample household members; However, no significant differences were found within the remaining selected socio-economic variables utilized in the investigation. Income.--The data in Table F-l suggest that 18.1 per- cent of all consumers samples shopped in a community shopping 106 center compared to “2.6 percent who shopped in a regional shopping center and 20 percent who shopped in a central business district. When consumers are broken down by annual household level of income, the data indicate that consumers from sample households earning between $7,000 and $15,000 are more likely to shop in a community shopping center than consumers from households of other income levels. Consumers in the cited income levels probably live nearer to a community shopping center and just as a matter of con- venience shop there more frequently when shopping for foods, drugs and other convenience types of merchandise. Occppational Class.--Significant differences were found between occupational classes of the heads of households and the frequency of shopping trips made by members from sample households to a community shopping center. The data in Table F-2 suggest that consumers from blue collar households are more likely to shop in a community shopping center than consumers from professional and managerial and white collar households. lime Per Trip by Selected S Clo-Economic Variables Significant differences were found between various household life cycle stages and the average amount of time members from sample households devote to shopping on a Single shopping trip to a community shopping center. However, SiSnificant differences were not found within the other SOClo-economic variables utilized in the investigation. 107 Household Life Cycle Stage.--The data in Table F-“7 suggest that households in which the head is retired and households in which there are no children or at least one preschool or elementary school child devote more time per shopping trip to a community shopping center than do house— holds in which the head is single and households in which there is at least one high school child or older. Part of the Week Significant differences were not found to exist within, any of the selected socio-economic variables utilized in the investigation and the part of the week members from sample households shop in a community shopping center. However, Table F-51 does indicate that when taking sample consumers as a whole, 70.5 percent shopped in the middle of the week at a community shopping center. Part of Day Household level of income is the only one of the selected socio-economic variables in which a significant difference exists with respect to the part of the day members from sample households shop in a community shopping center. However, when taking consumers as a whole, the data in Table F-59 indicate that “8.6 percent shopped in the afternoon compared to 30 percent in the evening and 21.“ percent in the morning. 108 Income.——The data in Table F-59 suggest that consumers ffieom households earning between $7,000 and $10,000 are more Itikely to shop in the morning than are consumers from inauseholds of other income levels. Consumers from households eerrning less than $7,000 are more likely to shop in the Eifternoon while consumers from households earning $7,000 and crver are more likely to shop in the evening at a community Sldopping center than are consumers from households of other ildcome levels. Neighborhood Shopping Center 'Ifilme Per Trip in General The data in Table “.1 indicate that consumers on the erverage devoted 33.92 minutes to in-store shopping per trip t<3 a neighborhood shopping center compared to 58.12 minutes tco a community shopping center, 59.96 minutes to a regional Sliopping center and 76.72 minutes to a central business (iistrict. Significant differences also were found with rwespect to the frequency of shopping trips made to a neigh- tHDrhood shopping center by members from sample households C>f'various income levels and occupational categories. F52equency of Shopping Tripa Significant differences were not found between house- hc>Ild life cycle stages, occupational status of the wife, the Iquunber of automobiles owned by the household and the fre— quency of shopping trips made by household members to a 109 neighborhood shopping center. However, when taking sample consumers as a whole 19.3 percent shopped in a neighborhood shopping center compared to 18.1 percent who shopped in a community shopping center, “2.6 percent who shopped in a regional shopping center and 20 percent who shopped in a central business district. Income.-—The data in Table F-l suggest that consumers from sample households earning between $5,000 and $7,000 and $10,000 and over are more likely to shop in a neighbor- hood shopping center than consumers from households of other income levels. Nearness to a neighborhood shopping center is probably the primary reason for the above income groups to shop there more frequently when shopping for food, drugs and other convenience type merchandise. Occupational Class.--The information in Table F-2 relates frequency of shopping trips made to a neighborhood shopping center by members from sample households whose heads are in different occupational categories. The data suggest that consumers from professional and managerial and white collar households are more likely to shop in a neighborhood shopping center than consumers from blue collar households. Time Per Trip by Selected Socio-Economic Variables 0f the selected socio—economic variables utilized in the investigation only household level of income was found to be significant with respect to the average amount of time devoted to shopping per trip. 110 Income.—-The data in Table F-66 show the relationship between household level of income and the average amount of time members from sample households devote to shopping on a single shopping trip to a neighborhood shopping center. The data tend to indicate an inverse relationship between level of income and time. As income increases, the amount of time devoted to in-store shopping decreases. Consumers from sample households earning between $3,000 and $5,000 devote the greatest amount of time per trip to a neighborhood shopping center. Yet according to the data in Table F-l, the $3,000 to $5,000 group make the least number of trips. Part of Week Occupational status of the wife is the only one of the selected socio-economic variables utilized in the investiga- tion showing significant differences with respect to the part of the week household members shop in a neighborhood shopping center. : Employment Status of Wife.--The data in Table F-76 tend to indicate that consumers from households in which the wife is employed shop more on a weekend at a neighborhood shopping center than do consumers from households in which the wife is not employed. When taking consumers as a whole regardless of socio—economic category, 7“.7 percent shopped in the middle of the week compared to 25.3 percent who shopped at the end of the week. 111 Part of the Day Significant differences were found within household level of income and the number of automobiles owned by household socio—economic categories and the part of the day members from sample households shop in a neighborhood shopping center. Income.-—The data in Table F—80 indicate that con- sumers from households earning under $7,000 are more likely to shop in the morning than are consumers from households of other income levels. Consumers from households earning less than $5,000 and $10,000 and over are more likely to shop in the afternoon, while consumers from households earn- ing between $7,000 and $10,000 are more likely to shop in the evening at a neighborhood shopping center than are consumers from households of other income levels. When taking sample consumers as a whole regardless of income level, 52.2 percent shopped in the afternoon at a neighbor- hood shopping center compared to 28.2 percent who shopped in the evening and 19.6 percent who shopped in the morning. Numbep of Automobiles Owned.--The data in Table F—85 indicate that a significant difference exists between the number of automobiles owned by sample households and the part of the day household members shop. Consumers from households owning two or more automobiles are more likely to shop in the afternoon and evening in a neighborhood shop- Ding center than consumers from households which own one or 112 less. Consumers from households owning one or less auto- mobiles are more likely to shop in the morning than are- consumers from households owning two or more. Summary of Significant Findings Time Per Trip in General The sample data tend to indicate that as the size of the shopping area increases so does the average amount of time devoted to in-store shopping on a single shopping trip. The findings of other research indicated that the larger the shopping area the farther consumers will travel to shop in them. Since larger shopping areas have a greater variety of stores as well as a greater variety of merchandise, it seems logical that consumers would devote more time on.a single shopping trip where the opportunity to choose from a greater variety of stores and merchandise exists. Central Business District: frequency, time, part of week and day. Twenty percent of all consumers sampled shopped in a central business district. Sample consumers most frequently Shopping there came from households whose annual incomes are less than $5,000 and $10,000 and over and whose heads are professional, managerial and white collar employees. Not measure future research along the same lines to deter- mine changes that might take place with respect to the temporal aspects of consumer behavior. Because of the occupational inconsistencies with level of income which were encountered in the investigation, a more detailed occupational categorization will have to be formu- lated. The occupational categories need to be more consis- tent with annual incomes. Distance traveled and time devoted to shopping on a single shopping trip are related to size of center. How- ever, research needs to be performed to determine the relationship of size of shopping area to per trip expendi-' tures. Further research needs to be performed with respect to consumer product search activity. For what types of pro- ducts and to what extent does product searching occur? Are there any particular demographic characteristics that are related to the searching activity? Such research would be important in terms of channel selection as well as possible new retailing techniques. 123 Further research should be performed on the multi— purpose shopping activities of consumers. What types of goods are more often shopped for compared to other goods? Research in the area would be important for purposes of determining the most efficient arrangement of stores for purposes of making shopping trips most convenient for consumers . BIBLIOGRAPHY 1214 BIBLIOGRAPHY Alevizos, J. P. and Beckwith, A. E. Downtown and Suburban Shoppinngabits of Greater Boston. Boston: Boston University, College of Business Administration, l954. "Antidotes to Shopping Weariness." Grey Matter. Grey Advertising, Inc. Vol. 3“. No. 12. December, 1963. Armstrong, R. H. "Changing Downtown Patterns." Urban Land. Vol. 16. No. 6. June, 1957. Barton, S. V. "The Life Cycle and Buying Patterns." The Life Cycle and Consumer Behavior. Edited by L. H. Clark. New York: New York University Press, 1955. 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Small Business Management Research Reports. University of Nebraska, 1960. Rich, Stuart U. ShoppingBehavior of Department Store Customers. Boston, Mass.: Harvard University, Divi- sion of Research, 1963. Rich, S. U. and Jain, S. C. "Social Class and Life Cycle as Predictors of Shopping Behavior." Journal of Marketing Research (February, 1968). Sato, N. G. and Sato, G. "Estimating Trip Destinations by Purpose—Shopping." C.A.T.S. Research News, Vol. 8. No. 3. Chicago, Ill. September 30, 1966? H 130 Schwartz, (knsrge. lkevclopnmrfl,()f Munketllng'Vhenry. (Haicagu: Southwestern Publishing Co., 1963. Sears, Roebuck and Co. 1968 Annual Report. Sharpe, Gordon B. Travel to Commercial Centers of the Washington, D. C. Metropolitan Area. Bulletin 79, Washington, D. C.: Highway Research Board, 1953. '1 "Shopping Center Trends and What They Mean to the Chains. Chain Store Age. Exec. Ed., Vol. “1, Part 2. May, 1965. Stoll, Walter. "Shopping Center Characteristics." C.A.T.S. Research News. Vol. 8. 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C.: Highway Research Board of the National Academy of Sciences, National Research Council, 1966. U. S. Department of Commerce. Americans at Mid-Decade. Series P-23. No. 16. Washington, D. C.: U. S. Government Printing Office, January, 1966. Voorhees, Alan M. Shopping Habits and Travel Patterns. Technical Bulletin No. 2“. Washington, D. C.: Urban Land Institute. March, 1955. 131 Wagner, Louis C. Economic Relationship of Parking to Business in Seattle Metropplitan Area, Part 2, Parking_as a Factor in Business.» Special Report 11. Washington, D. C.: Highway Research Board of the National Academy of Sciences, National Research Council, 1953. Warner, W. L.; Meeker, M.; and Eells, K. Social Class in America. Chicago: Science Research Associates, 19“9. Worthy, James C. "The Next Ten Years in Retailing." Changing Patterns in Retailing. Edited by John W. Wingate. Homewood, 111.: Richard D. Irwin, Inc., 1956. Yamane, Taro. Statistics: An Introductory Analysis. 2nd ed. New York: Harper and Row, 1967. Zwick, Charles. "Demographic Variation: Its Impact on Consumer Behavior." The Review of Economics and Statistics. Vol. 39, 1957. APPENDICES 132 APPENDIX A DEFINITIONS 133 DEFINITIONS Time devoted to shopping is defined as that time devoted to in-store shopping. Single trip is defined as any shopping trip that begins at any destination (including the home) and ends at a shopping destination. Travel time is defined as the time involved in travel— ing from an origin to a single shopping destination. If a non-shopping destination immediately follows a shopping destination, the time devoted to travel to the non-shopping destination will be considered as part of the travel time. ‘ Central Business District is defined as an area of very high land valuation, an area characterized by a high concentration of retail businesses, offices, theaters, hotels and service businesses and an area of high traffic flow. Regional shopping center is defined as a planned shop- ping development under common ownership with off-street parking provided on the property and consisting of 50 stores or more. Community shopping center is defined as a planned shop— ping development under common ownership with off-street parking provided on the property and consisting of at least 15 stores but less than 50. A neighborhood shppping center is defined as a planned shopping development under common ownership with off— street parking provided on the property and consisting of less than 15 stores. Planned shopping center is defined as a shopping center .initiated by a private or collective organization and is so planned that its development may be registered in terms of adequate parking facilities, balanced shopping facilities, controlled competition and attractive appearance. 13“ 10. 11. 12. 13. 1“. 15. 16. 17. 18. 19. 135 Household is defined as a person or group of persons living together with a common budget. Level of income is defined as before tax annual family income derived from all sources and is to be classi—- fied as follows: Under $3,000, $3, 000 to $“, 999, $5, 000 to $6,999, $7, 000 to $9, 999, $10, 000 to $1“, 999, $15, 000 to $2“, 999 and $25, 000 and over. Occupation is defined as blue collar, white collar and managerial and professional workers. Blue collar workers include craftsmen, foremen and kindred workers, operatives and kindred workers, private household workers and other service workers. White collar workers include clerical and kindred workers and sales workers. Professional and managerial workers include professional, technical and kindred workers, farmers and farm managers, and managers, officials and proprietors. Single household is defined as a household in which the head is not married, widowed or divorced and in which no children reside. Married - no children is defined as a household in which the head is under age sixty-two. Preschool children household is defined as a household in which any member is under the age of six. Elementary school childrenvhousehold is defined as a household in which the youngest member is between the ages of six but less than twelve. High school children or older household is defined as a household in which the youngest member is twelve or older. Retired is defined as a household in which the head is unemployed and sixty-two years of age or older. Part of day is divided into morning, afternoon and evening. Morning is defined as the hours between 8 a.m. to 12 noon. Afternoon is defined as the hours between 12 noon and 6 p.m. Evening is defined as the hours after 6 p.m. Part of week is divided into middle of the week and week- end. Middle of the week is defined as Monday through Friday. Week-end is defined as Saturday and Sunday. APPENDIX B SAMPLE SELECTION PROCEDURES 136 SAMPLE SELECTION PROCEDURES Sample Size Five percent of the Region's approximately 90,000 households were selected as the sample. The percentage yielded approximately “,500 household interviews. The basis for the percentage was that, according to our trans- portation consultant, Alan M. Voorhees and Associates, it would yield sufficient data to facilitate the necessary statistical expansions and analyses for the Region as a whole and its 6“ analysis areas. Sampling Methods When selecting a sample to represent the total popula- tion, the method with the highest probability is a com- pletely random one. That is, people selected in a random sample would be more likely to give answers which represent the travel habits and attitudes of the remainder of the Region's inhabitants than other sampling methods. This method consists of (1) selecting the first sample n from an unordered population N, (2) intermixing the population N, and (3) selecting sample n+1. This procedure is repeated until the desired number of samples are obtained. 137 138 Unfortunately, the size of the population is quite large and intermixing the population prior to each sample selection would prove cumbersome. This, plus the fact that the population is heterogeneous, led to selecting the sys- tematic sampling technique. While the probability of this method is lower than the random sampling technique, it still yields highly satisfactory results. In the selection of a systematic sample, a sampling rate must be determined based on the estimated total popula- tion and the total number of samples desired. As previously mentioned, a five percent household sampling rate was selected. In order to obtain the percentage of completed interviews, and it was necessary to oversample to allow for such circumstances as vacant houses, refusals, and unusable interviews. Therefore, a household sampling rate of one in every thirteen was used, yielding 6,933 samples. Sources of Information The population is only as complete as the sources used to obtain it. In determining the household population the following sources were considered: 1. Field selecting the sample by driving the entire Region, following a prescribed pattern, was con- sidered. However, due to the sparsely settled character of much of the Region and the vase area encompassed (1700 square miles), the field as an information source was rejected. 2. Using 1962 land use maps, prepared by the Tri- County Regional Planning Commission, and Sanborn Atlas Maps to select the sample was considered. 139 These information sources were rejected as the land use maps were not up-to-date and the Sanborn Atlas Maps did not cover the entire Region. 3. Power company electrical records were explored as a possible source. It was found that the resi- dents of the Region are served by four power com- panies, with two areas in the Region being served indirectly by these power companies. These two areas are the City of Eaton Rapids and Michigan State University, both of which received their power from Consumers Power Company but do their own billing. As all the households in the entire Region at the present time are represented in these power company records, this information source was selected. Therefore, the information sOurces from which the sample was selected consisted of the following: 1. Consumers Power Company (excepting Eaton Rapids City and Michigan State University) 2. Detroit Edison Company 3. Tri-County Electrical Cooperative “. Lansing Board of Water and Light 5. City of Eaton Rapids 6. Michigan State University The areas for which each of these sOurces have information are indicated on Figure B-l. Refinement of Information When the meter address cards were received from the various power companies, they represented many land uses. Since only households were to be interviewed, the residential meter address cards were the only ones of significance. Due to the fact that Consumers Power Company provided the infor- mation for their service area on keypunched cards, a sorter 1’40 N EENBUSN . aouuo m- l D 1 am ’ x ‘ r “a. ’ ’ *r‘" -1," r‘ . i I ' i a \ ‘ . ' $1,, I“ '1', ‘ ,. a ;_ . p ' ' -. , . ’ i o :21 All "' ‘ Ii \ ‘7 "'29:; i ’ ALAIEDON v v cutsv E ., V¥Lla. " ”"0505 cum . ,R. 1 , > ‘ I . ‘ 'a‘ , a ~__._ ‘- 1 l' _ . L1IAIH a c :1 ; I ' ' En ' snow AUIELIUS | __-‘ ""31““ 1 ll " nuao ‘ CAN-EL « mos 1 ‘- L“ . manna ' ‘ 4. \\ vows I _.._.—~_- I . —‘__ .__‘ V - I . ‘ ,, . ( - \ I I I i ozusvuc 3511’ cu woo-mun pu guano.“ ' '“"“"' “M srocxan IDGE J _ I”. ‘1 , ‘uua ' .I . l..EJ‘ [ L Jam“ J x l . " I non-m. .. LI. M l ‘ _ l l I m Lansing Board of Water and Light E Consumers Power Company $8888 Detroit Edison Company Illllmlllmmllll City of Eaton Rapids“ Tri-County Electrical Cooperative E Michigan State University“ Figure B.1--E1ectric service areas. 1“l was used to remove the non-residential meter address cards from their records. Most of the non-residential cards had been removed from the Detroit Edison Company keypunched card records by their staff. Non-residential cards discovered in a Tri-County staff field check were removed manually. Since Lansing Board of Water and Light and the Tri- County Electrical Cooperative data were not on keypunched cards, manual sorting of these cards was required. There were approximately “9,500 address cards to be sorted manual- ly. Of these, “7,900 were from the Lansing Board of Water and Light and 1,600 from Tri—County Electric Cooperative. It was not economically feasible to allocate manpower from the full-time staff of the Planning Commission to complete the Job, so part—time help was employed. The City of Eaton Rapids, using their staff, selected each thirteenth household from their billing records which, at our request, included inactive meters. Non-residential meters were excluded when selecting the sample. Therefore, no refinement of the data obtained from the City of Eaton Rapids was required by the Commission's staff, as was also the case with the data obtained from Michigan State Univer— sity and all group quarters information sources. Sample Selection Prior to selecting the sample, the population was ordered. An attempt was made to pick the first sample from 1“2 the northeast corner of the Region and then sample the Region following a serpentine pattern. (See Appendix C.) Each information source was completely sampled before samp- ling the second source, as the state of the data varied sub— stantially among the different information sources. In order to maintain, as closely as possible, the serpentine pattern of sample selection, the six household information sources were sequenced as follows: 1. Tri-County Electrical Cooperative 2. Lansing Board of Water and Light 3. Michigan State University “. Consumers Power Company combined with the City of Eaton Rapids sample 5. Detroit Edison Company After the population was placed in this order, the number of the first sample was determined. A random number was chosen from a table of random numbers. The number chosen was three. Therefore, the third card in the Tri—County Electrical Cooperative deck was the first sample selected, the second sample was the sixteenth card, and the third the twenty—ninth card. When the last sample had been obtained from the Tri-County Electrical Cooperative deck, there re- mained a number of cards (necessarily less than 13). This remainder constituted the first part of the count in sampling the second information source, the Lansing Board of Water and Light. For example, if five cards remained in the Tri- County deck after the last sample, then the first card in 1“3 the Board of Water and Light deck would be number six and the first sample would actually be the eighth card in the Board of Water and Light deck. The cards within the deck of each information source were ordered when possible in the township sequence portrayed in Appendix C. For instance, meter addresses in Greenbush Township on Tri-County Electri- cal Cooperative 3 x 5 cards would come first, followed by Essex, Lebanon, Dallas and Bengal Townships in that order. The actual selection of the sample was accomplished manually, even though a number of meter addresses were on punched cards. The reasons for the manual selection were as follows: (1) a number of the punched cards were bent too badly to be machine processed, and (2) this provided an additional edit as the individual selecting the sample verified that only residential cards were in the decks. Below is an outline of the general procedures followed in selecting the household sample: 1. The sampling began with Box No. l, which con- tained Tri—County Electrical Cooperative records, and continued through all sources of information in sequential order until the last sample card was obtained. 2. A stack of cards was removed from the front of the first box. 3. The stack removed did not exceed three inches in height. “. Each stack was placed face up on the table in the position designated. "All-Residential Deck." 10. 11. l2. l3. 1“. 15. 16. 17. 12m The designated positions for the cards were as follows: Non—Sample Sample Cards Deck All-Residential Deck Twelve (12) cards were taken from the top of the stack, one at a time, and placed face down in position indicated as "Non-Sample Cards." The 13th card was placed face down in the position indicated as "Sample Deck." The next 12 cards were then removed from the top of the stack and placed face down on top of the 12 removed previously. The 13th card was again placed face down on top of the 13th card removed previously. This procedures was continued until the stack con: tained 12 or less cards. The stack of "Non-Sample Cards" (face down on the table) were replaced in the box in the same sequential order as removed. The next stack of cards were removed from directly behind the stack replaced in step No. 11. The (less than 12 cards) stack was removed from the "All—Residential" position, and the new stack was placed face up in this same location. The (less than 12 cards) stack was placed face up on top of the new stack. The procedure outlined in steps 5-10 was then repeated. The procedure for handling the 1ess-than-l2-card portion of each stack (steps ll-l“) was followed also when changing from one box to the next. The sample deck cards were kept in groups of 25 (for coding purposes) and placed in boxes in the same order in which they were selected. 1“5 Use of Computers By using a computer, many man hours were saved during the pre-interview phase of the Home Interview Survey. A 1“01 computer was used to extract the name, postal address, and sample number from the punched cards. The computer then reproduced this data on two sets of perforated 3 x 5 cards and one set of gum labels. The two sets of 3 x 5 cards were given to National Analysts, Inc., the firm con- tracted with to conduct the Home Interview Survey. One set of cards was retained by them as a written record of each sample. The additional set was given to the individual interviewers to take into the field. The gum labels were used to mail pre-interview materials to each household and group quarters resident selected to be interviewed. The sample number was recorded on each 3 x 5 card and gum label to assist in keeping record of interview assignments and processing undelivered pre-interview letters. APPENDIX C ARRANGEMENT OF HOUSEHOLD UNIVERSE INFORMATION l“6 APPENDIX - C ARRANGEMENT OF HOUSEHOLD UNIVERSE INFORMATION v T v L I. y: 'M {I 4 I 1 :‘ '5‘: nod “was 1 “l, Tanya». ‘. (sssx ‘ ’ ”L,“ / (1qu no “a”? 3 ‘ on EENBUSbh ‘ //‘ 1 ‘ i I t? 7 7 7 i _J._ _ _ 11 ka~ .4 l \ . . ,5. Narnia-I l I” ‘zv mung \ \~\_;mn,l I. ' ‘ A L.J . t‘ \ j’ J \, i :,:- , ovao Jun,” anon i . 2"” If T "a , r:“"'$ ,flx‘ific ~A~7 ‘ ‘8 ,, ,1, 1,,‘,,_,,,, ,,,A.,,. it r’lnswnim , T l . ‘ ats'nmui 1 mu, ' 0L IVE ‘ mum: 12 11' :10 . 9 , 1L1 _ We, 7 ‘ A_ ,; ”iifi‘E‘IZ/I/ | r-‘I ,"KI‘V . . ill;— 0 5 10 7301174 ,. «y r IcALEtNXILE ”Heidi: i on ITY I . I :A!’ N 14 15 l y la _—--,—.; "a r“ I ""7 . , 7 ‘ . I; J l i .., . ’i w l, I W 37L. 1 1 ' no 5 u l" flunk: ;’ .41 l 1’ I A“ , , .i... l ,, “~5on ' fl , .‘ N, LUCIE I nouns ONEIDA 7' ,‘Jnv j‘ } W'LLVAMSVDW ' . L .... , , I swung 23 [:2 v. ' “mugs " 18 i 17 1 [INS us . " "L ,1 ,. m , ,.... ,1 , , ,_ , . 4, , ‘4 _‘ , fl ‘ k . ‘ can. . ‘ g ~—»——‘§g IL\105W , ”A I ‘ a‘m.‘ ‘7 A ~~—#—~‘ ~ 3 1 \ , I“- ‘. ~ vsuuourvutt if “pup" 1!! “Manon ‘ WHEAYFIELO 1 L(ROY I n , . ("jut-urn . ’Elt‘dr‘ Dnm I, i ‘ ' vu . . t i r. Ag» . - .i. a : 31 l 32 ‘25/ 29 .‘ . so __1_ ,1 ,1 i ._'77,~ i ,7) ‘, ; nusoo ‘ l .1 1 i Auwulus L I V 4 ”9‘5” ' 'W’t on | in. V5“, men-u SUNKE‘i HILL ouonoAsA . [5“; swcxan we: - ".i 471‘ I'Mlllflla 8 46 J i i i l l I ”'3 I 5‘ ”Luna 1 l l Note: The housing units in Duplain Township and Elsie Village were sampled first and those in Stockbridge Township and Stockbridge Village last. 1“? APPENDIX D ACCURACY CHECKS AND PUBLIC RELATIONS PROCEDURES 1H8 ACCURACY CHECKS AND PUBLIC RELATIONS PROCEDURES During the course of the Home Interview Survey cer- tain checks were made to assure reliable and adequate survey results. These checks were made not only during the sample selection, coding and processing phases, but also during and following the actual interviewing period as well. These checks are discussed in the accuracy checks section of this chapter. Due to the fact that some of these checks have a secondary function of cementing good public relations, the discussion of public relations procedures has been included in this appendix. Accuracy Checks The checks made by the Tri—County staff on all ques— tionnaires during the various phases of the Home Interview Survey include the following: 1. All steps followed in the refinement of infor- mation, selection of sample and coding of sample phases were checked by a person differ- ent from the one who did the original work. 2. All completed questionnaires were submitted by National Analysts, Inc., the firm doing the interviewing, to the Commission staff for review. Each interview was checked for accur- acy and completeness. All deficiencies were noted on a separate correction sheet. No marks were made on the questionnaires by any Commission 1A9 150 staff member without permission from National Analysts, Inc. Inadequate questionnaires were returned to the field supervisor for National Analysts, Inc., for correction and resubmittal to the Commission. Each completed questionnaire, after receiving final Commission approval, was plotted on overlays for one of two maps . . . the l"= 1,000' Lansing Area map or the l"=l mile Tri- County Region map. As the traffic zones had also been drawn on overlays at the same scale as these maps, the volume and distribution of completed approved questionnaires within each zone were compared to the 1960 census popula— tion and 1962 land use maps. Deficiencies were noted and discussed with the home interview survey field supervisor. In two areas, the village of Ovid and southeast Lansing, addi— tional interviewing was necessary as these two areas had been inadvertently omitted when ob- taining the household universe. As each completed questionnaire received approval, the household sample number and other information were recorded and tabulated. Total trips per household, auto driver trips per household and other statistics were compared with the results obtained in studies conducted elsewhere in the Nation. Low trip reporting was one of the items revealed by this check. The field supervisor was informed and corrective measures were taken. The number of housing units in certain designated small areas were enumberated and compared using the following sources and techniques: (a) the number of samples for each census tract and minor civil division in the Region was multiplied by thirteen (the sampling rate used to obtain the 6,9“? samples) to obtain the number of housing units in Spring, 1965; (b) the number of housing units in each census tract and minor civil divi— sion in the Region in April, 1960 was obtained from the 1960 census of population and housing; (c) the number of housing units in each census tract in the Lansing area, includes East Lansing, for the Spring of 1965 was obtained using resi— dential building permits to update the 1960 census; (d) the number of housing units in each census tract in the cities of East Lansing and Lansing in Fall l96u were obtained using 196U R. L. Polk Company canvas results; and (e) the number of housing units in 1962 in each census tract and minor civil division in the Region was obtained using 1962 land use survey results. Many discrepancies were noted among the differ- . ent housing unit totals obtained in (a) through (e). Field checks were made to determine which figures represent the true picture. In addition, approximately ten percent of the house- hold questionnaires were verified by telephone. The follow— ing procedures were followed in making this telephone verification. a. No question is to be asked which is likely to antagonize the respondent. b. Do not call a respondent before 10:00 a.m. c. Call one of every five respondents. d. Calls should be brief (about one minute in length). ' e. Have the questions you are checking in front of you before you call the respondent. f. It is permissible to ask other questions if they will serve to clarify answers. g. Give your closing comments a personal touch; do not give the respondent a stereotyped, memorized statement. One question asked of most respondents pertained to how the interview was conducted. The response was favorable in most instances. Other questions were structured to investi- gate low trip reporting, incomplete information and apparent inconsistencies. Finally, once the interviewing was completed and the keypunched card formats determined, the Commission staff 152 prepared edit specifications to assure that coding of the Survey results was complete and accurate. Public Relations Procedures Good public relations were considered to be a vital ingredient in the Home Interview Survey program as such relations affect the success realized in each interview, the image of the Tri-County Planning Commission in parti- cular, and the planning effort in general. The attempt was made to inform the general public before the Home Interview Survey began and to keep them informed as the Survey progressed. A Approximately a week before the first interview were taken, a press conference was held to inform the various news media in the Region including eight radio stations, three television stations and nineteen newspapers of the purpose and significance of the Survey. The Chairman of the Plan- ning Commission, the Executive Director and Assistant Dir- ector of the Planning Commission staff and the Vice-President and Director of the Social Science Department of the National Analysts, Inc., were present to provide information on the details of the Survey. An information packet was distributed to each of these 30 news agencies. These packets contained (1) a letter from Governor Romney expressing the need for and his support of the Home Interview Survey, (2) a brochure entitled "Home Interview Survey" explaining the purpose, financing and 153 other aspects of the Survey, and (3) three information reports entitled "Regional Planning Program: an Overview," "Background and General Information on the Tri-County Regional Planning Commission," and "Background and General Information on the Regional Planning Program." A In addition, two radio appearances were made explaining the Survey. Prior to the beginning of the Survey, the Assist- ant Director of the Commission staff and the Vice-President and Director of National Analysts, Inc., answered questions from the listening audience regarding the Survey on an hour long local radio show. During the course of the Survey, a Senior Planner on the Commission staff, in’a fifteen minute radio interview, described the Home Interview Survey, how the Survey was progressing and some preliminary findings. Also, the progress of the Survey was followed closely by the local newspapers, who were aided by news releases dis- tributed by the Commission staff. Besides informing the general public, each household to be interviewed was mailed the Governor Romney letter and "Home Interview Survey" brochure about one week prior to the day of the interview. The gum labels obtained from the computer program mentioned in Appendix B was used to address the envelopes. After the Survey was well underway a slip was added to the letter contents emphasizing that, in the event of questions, the Tri-County Regional Planning Com- mission should be contacted by telephone or letter. APPENDIX E QUESTIONNAIRE 15A National Analysts, Inc. Study #1-5h3 Philadelphia, Penna. Spring, 1965 TRANSPORTATION AND ACTIEIILPLS STUDY EATON. INGRAM AND CLINTON COUNTIES, MIQHIGAN Time interview began: 11.11. 12.14. Time interview ended: A.M. P.M. Household # Name Address MEMflON: I am from National Analysts, Inc. a research organization, conducting a study among people in Eaton, Ingham and Clinton Counties. I presume you received a letter a few days ago from Governor Runney informing you of this study and telling you that an interviewer would come by to talk to you about trips and activities of members'of this household. Interviewer: Date: \ 155 156 hp ..w.o .935...) hp 5.5 .350 cued“ has om 3 :88 $33980 Am .qoo 2H rmEmDQZH a mmHBbav won «000 xuo> ho IIII‘ l, Digs... 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Am .80 fi n 808 paganism» cages—now Egii\aaud§ A«I Him .6» :33! £3 «5 32a wad—43m Ago g .65 EH: .5493 "g ho fi not: so» on v.3 woo-An .350 has son . ~aa mo and“ hug «nu and J: 3 ab» muons: and." 05 35 coil 16:0: 3.3 05 5258 :8 7.8.0 Oahu Gama Ema 9% mo Omma a! 8.0 :H was .mH u dwé OE 810 no mafi— Emu—Hy .mN .aN APPENDIX F DERIVED STATISTICS AND SUPPORTIVE DATA 160 161 .Hamo 20mm go LwCLco 62m: pzme.mmon :H CZOLm mpm mmwmpcmopwm :Ezfioo .HHmo 20mm no HmCHOQ nzm: puma Lmuu: :H zm>wm ma asses mocmzvmpm "mpoz OOH OOH OOH OOH OOH OOH OOH HmwOB mmO mm Omm omm OOm mOH NO m.OH O.mm O.Hm a.mH m.Hm p.3H m.mH pmpcmO wCHuuonm OOH Om Om HO m: mH HH ooogpopanmz H.OH O.O 0.0H O.mm O.mH p.mH p.mH mmpcmo mcflqmonm MOH O O: Om Om OH NH OOHOOquO O.mz O.m: 0.0m 0.0: m.OO H.OO 0.0m pmpcmo , mcHQQonm OO: O: NO OOH NO NO Om HOOOHmmm 0.0m O.mm p.mm 0.0m O.mH m.mm 0.0H OOprmHO mmmcfimsm HOH Hm Om om Om mm mH ngpcmo Hmuoe pm>O O OOO.OHO OO0.00 OOOHOO OOO.OO OOO.mO mcHOOogm -OOO.mHO _-OOOnOHO -OOO.OO -OOO.mO -OOO.MO mecO macho mEoocH .deOLw mEoocH mSOHLm> mp mmmg< wcHaQonm pampmmmfio on mums mqfine wcfiaqocm no mocmsvopmnn.anm mqm¢e ¢BHEmommDm Q2< mQHBmHE¢Bm Qm>Hmmo 162 TABLE F-2.--Frequency of Shopping Trips Made to Different Shopping Areas by Various Occupational Groups. Occupational Group Shopping Professional White Blue Area & Managerial Collar Collar Total Central 83 39 75 197 Business District 21.8 22.7 18.0 20.3 Regional 167 70 176 U13 Shopping Center “3.8 No.7 u2.3 u2.6 Community U6 26 101 173 Shopping , Center 12.1 15.] 2H.j 17.9 Neighborhood 85 37 6“ 186 Shopping Center 22.3 21.5 15.uv l9 2 381 172 A16 969 Total . 100 100 100 100 Note: Frequency count is given in upper left hand corner of each cell. Column percentages are shown in lower right hand corner of each cell. l‘fll‘ll'l 1‘. .HHOO zoom 90 LOCLOO can: ugwwp amzofl :H :zozm ppm mmwmpcmogmu casaop .Hamo nose mo &OCL00 use: puma among Cw zm>Hw ma ucsoo zocozdopm "mHoz OO OOH OOH OOH OOH . ‘ OOH OOH - HOOOO OOO OO OOH HOH OHm Omm Om. O.OH 0.0H O.HO 0.0H ‘ H.OO . 0.0H O.OH OOOOOO mcfiooonm OOH HH Om Om OO 9 HO O OOOOOOO:OHOZ O.OH O.OH O.OH O.OH O.OH O.OH O.OH OOOOOO _ mcfiuaonm OOH O ON ON HO OO O OOHOOEEOO Mm 0.00 O.Om H.OO 0.00 0.00 . H.mO 0.00 OOOOOO 1 msfiooonm OH: mm mm OO NO HOH Om HOOOHOOO 0.00 H.5O O.OH O.OH O.Hm O.OH H.Om OOHLOOHO mmmcfimsm OOH OH mm Om NO HO OH HOpOcmO HOOOO OOOHOOO OOOHO OOOOHHOO :OOOHHOO OOOOHHOO OHOOHO OOOO OOHOOOOO Lo umppafino Hoocom Hoonomopm oz Hoonom awfim mumpcmsmam \OOHLLOE \omfippmz \pmwppmz \UoHLLmz OHOOO OOHO OHonmmsom w .. .mosopo macho mqu oaonmmzom OonLm> an mmmp< mcfiuoocm pcmLmMMHQ on com: Omaha wcfiaaocm mo mocosvmpmlu.MIm mqm<9 l6u TABLE F—u.--Frequency of Shopping Trips Made to Different Shopping Areas by Occupational Status of Wife. Wife Employed or Not Shopping Area Not Employed Employed Total Central 162 35 197 Business District 20.9 18.0 20.3 Regional 323 90 “13 Shopping Center Ul.7 U6.“ b2.6 Community 136 37 173 Shopping Center 17.5 19.1 17.9 Neighborhood 15“ 32 186' Shopping Center 19.9 16.5 19.2 775 19“ 969 Total 100 100 100 Note: Frequency count is given in upper left hand corner of each cell. Column percentages are shown in lower right hand corner of each cell. Val. 165 TABLE F-5.--Frequency of Shopping Trips Made to Different Shopping Areasby Various Automobile Owner- ship Groups. Automobile Ownership Groups None Two or Shopping Area Owned One Owned More Owned Total Central 6 109 82 197 Business District 28.6 20.9 19.2 20.3 Regional 8 221 18“ “13 Shopping Center 38.1 “2.“ “3.1 “2.6 Community 3 8“ 86 173 Shopping Center 1“.3 16.1 20.1 17.9 Neighborhood “ 107 75 186 Shopping Center 19.0 20.5 17.6 19.2 21 521 “27 969 Total 100 100 100 100 Note: each cell. Frequency count is given in upper left hand corner of Column percentages are shown in lower right hand corner of each cell. 166 20.m ‘». () mo.Om (J L{\ H ([1 wouSCHH CH mEHB mwmhm>< 8 smaaoonmsHu anH00|OpHn3 Hmfinmwmcmz a Hmcofimmmmopm . onno HOCOHpmasooo .mmfipommumo HmcoHuOQ:ooo msonnmb ca OHHmm Ummm mmonz meonmmzom mo mumpEmz an poapumHo mmmchzm Hmnwumu m up QHLB wcHQQonm new wcfiomocw mnoumucH on ompo>mm mafia mmmnm>¢uu.mnm mqm< OO>HO OOOO O OOO.OOO OO0.0HO OOO.OO OO0.00 OOOHOO OO0.00 nacho Ooz OO0.0NO. nOOO.mHO uOO0.0HO uOO0.00 nOOO.mO -OOO mO amass oeoocH .masono meoocH nsoHnm> an OOHLOOHQ Ommchsm Happcmo ca dHne wcHQoocm Lad wcfiduocm mpoumncH on omuo>ma mafia mwmnm>¢ omzoaoam oonHQEm mmfiz mo Odompm p02 “cosmoaaem .xpoz Ooz mmoa no mmoo mafia map cOsz CH Ovaocmwsom no mpmnEmz an uoahpmHm mwmcfimsm Hmnucmo m on maps mcHuqonw pom wcfiaaocm mnoumncH o» nmuo>mm mafia mwmnm>O umpfipmm LOUHO no cmnoafico cmpoaano conuafico mflwcfim :mnoHHQO Hoonom aoonommpm oz mwmpm Hoozomncwfim zpwpcoEmHm \UOHLLOZ \omfippms macho mafia \omfinnmz \omfinpmz .mmwmpm macho mgfiq msofipm> an pOHmeHo mmmcfimsm ngpcmo m on QHLB wcHaqonm pom wcfiddozm mpoumncH 0p ompo>mo mEHB wwwpm>mm ma ucsoo mocwsomLm “muoz ooH ooH ooH 00H 00H 00H ooH OOH OCH OCH kuoe OOH O O OH am on Ow mm HH m O.Hw 0.0m o.ms 0.00 a.mm o.ow m.mm O.mm m.om ooa xmmz HOH m m OH O: c: on 0H 0H N no manna: m.mH 0.0m a.mm m.mm o.HH o.om 0.0H :.OH H.m o xwm: «0 cam Om m H o O OH m a H o HOOoe eOSO LO>O O OOO.OOO OOc.OHO OOO.OO OOO.OO OOO.OO OOO.OO escocH gem: co OLOO Ocz uOO0.0mO -OOO.OHO uOOO.OHO -OOO.OO -OOO.OO -OOO.OO Lacs: oz asoso OEQOCH nmwcfimsn Hagucmo on» :H . .OOHLOOHQ Umddczn xmo: on» go pnwm on» o» masons wEoocw wzowsm> CH whoasmcoo no omcoawomll.amlm mqm OmemHHoO O OH mHum memem .HHmo comm mo pmcpoo cam: panL pmon :H czonm mum mmwm tummopmu cusHoo .HHmo 20mm Mo pmcpoo cams pmmH Loan: :H cm>Hw OH pcsoo mocmsumpm "muoz OOH OOH OOH OOH OOH OOH Hmpoe HmH Hm Om om Om Om O.mm 0.0m 0.00 0.0m m.mm H.Om xmmz OOH OH O: O: OO Hm Oo OHOOHz m.OH 0.0m H.HH 0.0m 0.0H O.MH mm xmmz mo Ocm O O OH O O HOOOO OOOO O OOO.OHO OO0.00 OO0.00 OOO.OO goo: Oo OOOO OOO.OHO -OOO.OHO -OOO.OO -OOO.OO nous: nacho mEoocH .poHpumHQ mmmchsm Hmpucmo map CH Omaaonw xmmx On» O0 phmm ms» 0p masogo meoocH OsoHpO> :H mpwesmcoo mo wmcoammmnumenm mamHw wH pcsoo moCmsmem smuoz OOH OOH OOH OOH OOH OOH OOH Hmuoe OmH .OH mm Om OH HO OH O.Hm O.mm O.mm m.mO 0.00 O.mm 0.00 xmmz HOH mH mH mm Om Hm OH mo mHOOHz m.OH . m.O 0.0H m.Om m.Hm 0.0H m.mH A xmms Co ncm Om H a O OH OH m Hmpou . OOCHpmm COOHO COCOHHCO COCOHHCO COCOHHCO meCHm xmmz Co ummm Co COCOHHCO Hoocom Hoozommpm oz Hoocom Cme mCmpCmEmHm \OOHCCOS \OmHCsz \OOHCCOE \anCCOz QCOCO mHomO muHH mg» C0 OCOO On» Op .poHprHO OOOCHmsm HmCuCoo m CH Omaaocm xmo3 mQCOCO mmmpm mHoao OOHH msoHCm> CH mCmECOCOO «0 mmCoammmul.zHIm mam49. .zHIm memB mo CoHOCm> OOOCOHHoo O OH mHnm OHCOBO .HHmo Comm no COCCOo OCOC prHC szoH CH CzoCO ma Omwm aOCmoCmC CECHOO .HHmo Como no COCCoo OCOC pumH Coma: CH Cm>Hw OH HCsoo zoCmsomCm "muoz OOH OOH OOH OOH OOH kuoe OOH am am O: OO O.HO O.OO O.OO O.OO O.OO Ommz . o m HOH Om Om Om OO O HOOHz m.mH a.mH m.Om m.Hm O.mH xmmz no ch Om - m O OH mH Hmpom COOHO Co COCOHHCO COCOHHCO COCOHHCO COCOHHCO oz xmmz mo upwm Hoozom Cme Hoozom Hoonommpm \OOHCCOE \OOHCCOZ mCmquEmHm \OOHCCOZ OCm meCHm OCO OOCHumm_ \OOHCCOS QSOCO mHozo OMHH .OOHCOOHO OOOCHOCO HmCuCoo m CH Omaaonm xmmz OCO Mo ppmm OCu o» OOCOCO ommpm mHomO OOHH OCOHCO> CH OCoECOCoo mo mOCoaOmmulmeIm mHmHw OH ucsoo zoCosomCm "mpoz OOH OOH OOH OOH OOH OOH OOH OOH OOH OOH HOooe OOH O O OH OO Om Om mm HH m O.OH O O O.HH O.OO O.OO O.OO O.O . O O OOOHceHz OO O O m HH OH O O O O .EOW O 0.00 OOH O.OO 0.00 H.HO O.OO O.OO O.OO O.OO OOH .e.d O OHH O O OH Om Om OH OH .OH O cmwz O.OO O O 0.0H 0.0H 0.00 O.OO O. H.O O cooz OO O O O OH OH O O H O .EOM O O.O O O.OO O O O O O O O .e.o O H O H O O O O O O O OOOMWOH: HOOoO co>HO peso O OOO.OOO OOO.OHO OOO.OO OOO.OO OOo.OO OOO.OO eeoocH OOO Oo OOOO Ooz OOO.OOO nOO0.0HO -OO0.0HO -OO0.00 -OOO.OO . -OOO.OO goes: oz ozoCO oe0oCO .uoHCuOHQ OOOCHOCm HOCOCOO m CH Oooqocm OOO may go OCOO on» Op OQCOLO osooCH OsoHCm> CH OCOESOCOO no omcoamomuu.mHlm mqmHw wH pczoo mucosaopm ”mpoz OOH OOH OOH OOH OOH OOH OOH . Houoe OOH OH mm Om O: HO OH , m.OH m.O O.Hm 0.0H 0.0H 0.0H 0.0m pstchz 0» Om H O O O NH O .e.o O 0.00 0.00 0.00 0.00 O.OO O.OO O.OO .s.o O on OHH OH OH OH Om Om OH :002 m.mm m.Hm 0.0 :.mm 0.0m m.Hm m.mH cooz . on OO O O OH OH OH O pancon HOOoO oopHOom OOOHO OOOOHHOO :OOOHHOO copoHHnO OHmon Own Oo puma so COLUHHLO Hoozom Hoonommhm oz Hoonom szm mumpcmEmHm \UOprwz \Umeme \OOHOOOE \ooHopmz qsoau mHomo ouHH on» Oo Oomm on» oo .poHpumHo mmmchsm Hmpucmo m CH omaaocm awn masons ommum OHOOO omHH msoHpm> 2H whoezmcoo mo omcoammmll.mmnm mamde upCooCoa CECHoo .mmnm meme no COHma>.meOmHHoo O OH mmnm OHmem ..HHoo Como mo CmCCoo OCOC uanC Coon CH CzoCm mCm wwwm .HHoo Como no COCCoo OCOC ummH Coma: CH Cm>Hw mH pCsoo zoCosdopm "muoz OOH OOH OOH OOH OOH Hmpoe OOH Om Om OO OO 0.0H O.OH O.OH 0.0H 0.0m pstoOHz op OO O O O OH .E.O O 0.00 O.OO 0.00 O.OO 0.00 .e.o O o» OHH Om OH Om O: Cooz OW O.OO O.OH 0.0m O.OO O.OH :ooz l 0» OO O OH OH OH OOOHOOHZ HOOoO OOOHO Co OOOOHHOO copoHHnO OOOOHHOO coCOHHOO oz OOO Oo OOOO HooCom Cme HQOCom HooComopm \OOHCCOE \OmHCsz OCmpCmEmHm \OOHCCOE OCm meCHm oom OOCHOOO \OOHOOOS QCoCO mHozo OOHH .OOHCpmHQ mwoCHmsm HmCuCoo m CH commonm Own on» mo OCOO 0:» on masoCO mwmum OHomo OOHH OCOHCO> CH mCmECmCoo mo mmCoawomlnwmmnm mum¢ CmHHoo msHm mmHHoo muHC3 HmHmemaz OCO HmConmmmohm Ozone HOCOHumasooo .masoCO HOCOHumasooo mdoHCm> an nmpCmO wCHanCm HOConom m 0» CHLB wCHOQoCm pom wCHaQoCm mpoumiCH op Omuo>oa oEHE owmnm>¢ll.Omlm mHmOB 189 mouscHz HO.OOH OO.OO O0.00 OH.OO O0.00 OO.HO mO.mO OO.OO 2H osHO mwmpo>< cm>HO OO>O oom OOO.ONO OOO.OHO OO0.00 OO0.00 OOO.OO OO0.00 ImwoCO Ooz OOO.OmO -OOO.OHO -OOO.OHO -OO0.00 -OO0.00 -OOO.OO Coos: ogooeH .mqsoCO «sooCH OOOHCO> an Coucmo mCquocm HmConmm m on CHCB wCHCOoCm Log wCanoCm onoumncH 0p nouo>mm mEHB owmpm> On meCoo wCHanCm HmConwm m on QHCB wCHQOoCm Com mCquoCm mCoumuCH ou Omuo>ma mEHB mwmpo>¢ll.mmrm mHmOB 186 TABLE F-29.—-Average Time Devoted to In—Store Shopping Per Shopping Trip to a Regional Shopping Center by Members of Households in Which the Wife Does or Does not Work. Employment Status of Wife Not Employed Employed Average Time in Minutes 59.19 64.17 TABLE F-30.—-Average Time Devoted to In-Store Shopping Per Shopping Trip to a Regional Shopping Center by Various Automobile Ownership Groups. Automobile Ownership More than Group None Owned One Owned one owned Average Time “5.95 69.32 50.03 in Minutes .HHwo Como O0 COCCoo OCm; HCwHC CmsoH CH Croum OCO mmmeCOOLmO CO3H3O .HHmO :Oxo Ho COCOOO 7:3: OOOH COCO: CH Cw>Hm mH pCzoo Ooszvam umpoz m Kb 15‘ m 0 m Q) N (\J (V t\. \ _) \-) (\I K.) “in C) (‘ J (O- 7'“ X (\I (‘Y’ Li‘ H :T [\ O O H OOH OOH OOH OOH OOH OOH OOH OOH OOH OOH HOOOO OHO O OH Om HO OOH O. OO Om O Ooo3 Oo OHOOHE Ln *4 \V) L: ‘ /\1 H 1\ H 1.x", t\ {O r‘ LI\ (‘J O (\l 0" . Oooz Co ocm OO H H O OH Om OH mm O O Hmpob Cm>HO Ca>m O OOOHOOM OO0.0HO cwc.wm OOC.OO OOO.OO OOO.mO mEooCH xmm3 Oo pCmm \. o. i . ) ) i o. . .1, n ) x. .. .. i p H: x. x, 1 pt; OOO OnO -(CO OHO -OOO OHO -OOC.OO -atc.u« -0,0.00 Loos: oz OOOCO masoCH .COOCOO mCHQOOCm Hmconom m CH Owaaonm xmom OCH Oo OCOO OCH CH mCOoCc o50oCH msoHCm> CH mCOEOmCOO no mmcodmmmln.Hmlm mqm<5 188 .Hmum oHnwe ho ConCm> omemHHoo m mH «mum oHpmew .HHmo Como mo CmCCoo CCOC pCmHC Hoon CH CzoCm mum mmww :uCoOCmQ CssHoO .HHmo Como ho CmCCoo OCmC uuoH Coma: CH Cm>Hw mH uCnoo zoCosuoCm "0902 OOH OOH OOH OOH, OOH. . OOH OOH , Hmooa OOO 0: OO OOH OO O: Om 0.00 0.00 0.00 0.00 O.Hm m.mm 0.00 zoo: OHm Om OO NO OO ON . ON Ho mHoqu O.OO ‘O.ON O.OH O.OO O.OH O.OO O.OH . x003 mo.ccm OO OH NH .mm OH mm O Hmpoe Ho>o O OOO.OHO OO0.00 OO0.00 OOO.OO OO0.00 How: we puma -OOO.OHO -OOO.OHO uOOO.OO -OOO.OO N-OOO.OO Omen: QCOHO mEooCH .CoquO wCHaConm HOCOHmom a CH ooaaonm xmmz on» mo upmm on» ou masopo osooCH OCOHHO> CH mCmECOCoO no omCOCmomsummm mamHw mH pcsoo moCmsvam ”mpoz OOH OOH OOH OOH OOH OOH OOH HOOOO mHO mm mO OO OO HOH ON 0.00 O.mO 0.00 O.HO 0.00 O.mO 0.00 HOB... mo mHm . OH O: OO mO mOH OH OHOOHE O.mm H.Om m.HH 0.00 H.OH 0.0m 0.00 Homz mo OO O O Om OH Om OH ocm Hmpoe OOHHpmm CoOHo Ho COHOHHCO COHOHHCO COLOHHCO oHwCHm xmoz COHOHHCO HooCom HooComopm oz Mo OCOO HooCom Cme OHOHCoEOHm \UOHCCOE \OOHLCOS \OOHHHOZ \OOHHCOE QsoHO mHoOO OOHH .HmpCmO wCHaaoCm HmConmm m CH OmOOoCm xmoz OCH mo pCmm OCH op OOCQCO mmmpm mHozo OOHH msoHCm> CH mHoECOCoO mo mmCoamomul.Omnm mqmdh 191 TABLE F-35.--Response of Working and Non-Working Wives to the Part of the Week Shopped in a Regional Shopping Center. Wife Employed or Not Part of Week Not Employed Employed Total 4 62 36 98 End of Week 3 19.2 40.0 23.7 Middle of 261 5“ ‘ 315 week 80.8 60.0 76.3 323 90 413 Total 100 100 100 .Note: Frequency count is given in upper left hand corner of each cell. Column percentages are shown in lower right hand corner of each cell. TABLE F-36.—-Response of Consumers in Various Automobile Ownership Groups to the Part of the Week Shopped in a Regional Shopping Center. Automobile Ownership Group None Two or . Part of Week Owned One Owned More Owned Total . 2 61 . 35 98 End of Week ' . 25.0 27.6 19.0 .23.? Middle of 6 150 149 _ 315 week 75.0 72.4 81.0 76.3 8 221 184 413‘ Total . 100 100 100 100 Note: Frequency count is given in upper left hand corner of each cell. Column percentages are shown in lower right hand corner of each cell. 192 TABLE F-37?--Response of Consumers in Various Automobile Ownership Groups to the Part of the Week Shopped in a Regional Shopping Center. Automobile Ownership Group One or Two or Part of Week Less Owned More Owned Total ’ 63 35 98 End of Week . 27.5 19.0 . 23.7 Middle of 166 1"9 315 Week 72.5 ' 81.0 76.3 229 184 413 Total 100 100 100 r Note: Frequency count is given in upper left hand corner of each cell. Column percentages are shown in lower right hand corner of each cell. aTable F—37 is a collapsed version of Table F-36. 193 W.;. .HHoo Como no COCCoo OcmC quHC Coon CH Czosn OCw nowmpCOOCOO CCOHOO .HHmo Como no COCCoo OCOC HOOH Coma: CH Co>Hm mH uczoo AQCOCOOCO "mpoz OOH OOH OOH OOH OOH OOH OOH OOH OOH OOH Hmuofi MHO O OH Om OO OOH OO OO Om O HON O O O.OO H.O,o. O.OO O.OO O.Hm H.HH 0.00 EOHOOH: op OOH O O HH Hm mm Om OH O m .e.d O O.OO 0.00 0.00 0.00 0.00 O.HO O.OO H.HO O.OO 0.00 .55. O 0p OHm O O OH OO HO HO Om OH O Cooz H.Hm m.mm 0.00 a.mm O.mm 0.0H 0.0H 0.0m 0.00 O Cooz 0» Om m O O Om OH OH MH O O .E.m m 0.0 O O O O O H.m O O O .E.m O on N O O O O O N O O O quHCOH: H38. S38 .85 .H O.OO.OOO OOO.OHO SOHO OOO.OO OOOJO OOO.OO meoocH COO pox OOO.mmm IOOO.OHO OO0.0Hm IOOO.OM nOO0.0m uOOO.mO COOCO 02 O0 upmm OOOCO oE oCH .COOCOO wCHQOOCu HmcoHnom O CH Ooauocu mg“ C6 OCOO OOH OH monogo mEooCH msoHLm> CH WLMESWCOU .HO QWCOQmmmll .mmlh mqm UUmQNHHOO w WH mme 0Hflmhd .HHmo Como mo ponoo nCmC prHn pmSOH CH Czonm ohm wmwm nquopma CasHoo .HHmo Comm no pmcpoo OCOC uOmH puma: CH Cm>Hw mH pcsoo OoCmsumpm "muoz OOH OOH OOH OOH OOH OOH OOH , . pr09 OO: O: OO OOH OO O: Om 0.00 0.00 H.=m 0.00. 0.00 O.HO 0.0H unmficqu 0» OOH HH Hm mm Om OH O .E.q O H.mm O.OO O.OO O.Hm 0.00 H.HO 0.00 .s.a O , on mHm OH O: HO HO am mm C002 =.Hm 0.0m O.mm 0.0H 0.0H 0.0m 0.0H Cooz , on Om NH om OH OH mH O panCUHz ,proa no>o a OOO.:HO OO0.00 OO0.00 OOO.=O OOO.mO Own mo 99am -OOO.OHO -OOO.OHO -OOO.OO -OO0.00 -OOO.mO yucca asopo mEOoCH .nmpCmo mCHnaonm HmCOmem m CH nuanonm . Ode 0:» mo upmm mCu ou masopo mEooCH mslom> CH mamssmcoo no mmCoammmulwmmlm mamHw mH pCCoo zoCosuopm ”opoz OOH OOH OOH OOH OOH OOH OOH Hmpoe mHH mm mm HO OO HOH mm 0.00 m.: H.mm 0.0H 0.0H H.HO 0.0m pOmHCOHz op OOH H OH HO OH Om m .s.a O 0.00 0.00 O.OH O.Om 0.00 m.mm 0.00 .s.a O , ou OHm OH mm mm mm OO mH cooz O.Hm H.Om O.Hm 0.00 O.mH 0.00 0.00 cooz o» OO O mH HO OH mm m OCchon Hmpoe OmCHpmm CmOHo Co :mCOHHCo :muOHHOO COCOHHOO «chHm man go upmm CmCOHHCo HOOCom Hoosommnm oz HOOCom anm mpmquEmHm. \OwHACm: \OoHCCmE \Omepmz \OmHepmz adopo oHoOo mmHH map Co OCOO mg» 09 .CmpCoo wCHaaonm HOCOHwom m CH commonm Owe masomu ommum mHoOo mOHq OCOHLO> CH mAmECmCoo mo owCoammm||.Hzlm mqm< omCHpmm CmvHo Co CmCoHHCo CoCCHHCo CanHHCo meCHm mwmpm cmaOHHco Hoonom Hoonononm oz, oHoOO oqu Hoonom Cme OpmquEmHm \OoHpsz \OwHCsz \CoHCsz \OmHCsz .mowmpm oHoOo mmHH mCOHCm> On Cmpcoo wCHaaonm OuHCsssoo m on QHCB wCHaQOCm Cog wCHaaonm opoumnCH op omuo>oo,osHB mmmuo><||.O=Im mqm¢ 200 CmHHoo oCHm . CmHHoO mpan HmHmewaz ocw HOCOHnmmmoCm Ozone HwCoHumaCooo .masoac HOCOHpmqsooo msoHnm> an popCmo wCHCCOCm OpHCCEEoo a on QHCB wCHaaoCm non wCHaQOCm mCOpmncH on Oopo>mo mEHB owwpm>¢ul.Oznm mqm< co>HO po>o O OOO.HNO OOO.=HO OO0.00 OO0.00 OOO.OO OOO.mO ooooo ooz OOO.ONO -OOO.mHO , -OOO.OHO -OO0.00 -OOO.mO uooo.mO _ soon: oeoocH .nasoao «sooCH OCOHCm> On pmpCoo wCHaaonm OOHCCEEoo a on CHCB mCHqucm Con wCHaCosm mCOOOaCH op copo>on meHB mmmpo>Hm mH pCCOo moszdmLm "mpor 202 OOH O O OOH OOH OOH OOH OOH OOH OOH . . Hmpoe mOH O O O O: OO Om OH HH H 0.00 O O 0.00 H.mO O. O H.HO O.OO 0.00 OOH xooz 1 I O mmH O O O ma O: Om HH O H C oHoqu O.OO O O O.OO O.Hm 0.00 O.OO O.OO m.Om O - xmoz go new HO O O O OH OH O O O O HsooO coOHO LOOO O OOO.OOO COO.OHO OOO.OO OOO.OO OOO.OO OOO.mO oeoocH xooz Co puma oo: OO0.000 -OO0.0HO -OOO.OHO -OOO.OO -OOO.OO -OOO.mO page: oz QCOCO OEQOCH .CmprO mCHuaocw .pHCCCEoo m CH OOQQOCW xwms mCu Co CCOC szp ou OCCCCO OEOoCH OonCm> CH mCosswCoo no mmCoammmII.OOIm mqm¢9 nucooamq CECHoo .Omnm oHnt no COHmCm> cmmamHHow a OH Hmsm oHntm .HHmo Como no poCCoo OCmC quHn szoH CH CzoCm mam mama .HHmo Como no CoCCoo OCwC-puoH Oman: CH Cm>Hw mH pCsoo OoCosuoCm Oouoz OOH OOH OOH OOH OOH Houoe mOH mm mm om mm O.OO. H.OO O.HO 0.00 0.00 xooz q. OOH Om ms mm ON Co oHOOHz m O.OO O.Om O.OO O.OO O.Hm zoo: go new Hm OH OH m m Hmuoe po>o a OO0.00 OO0.00 ooo.mO sou: Co unam OOO.OHO -OOO.OO uooo.mO sons: Cacao oEooCH .CopCoo MCHaaonm OuHCCEEoo m CH umqaonm £003 020 .HO phdm was. 0». wad—0&0 ”EOOCH mfiofihdxw CH mkflESmCOU MO mmCOQnOmIIWHth mdm<9 20“ TABLE F-52.--Response of Consumers in Various Occupational Groups to the Part of the Week Shopped in a Community Shopping Center. Occupational Group . Professional White Blue ' Part of Week & Managerial Collar Collar , Total 17 19 21 148 End of Week _ 37.0 38.5 20.8 27.7 Middle of 29 16 80 125 "99“ 63.0 61.5 79.2 72.3 #6 26 101 173 Total 100 100 100 100 , Note: Frequency count is given in upper left hand corner of each cell. Column percentages are shown in lower right hand corner of each cell. uquoCmQ CECHoO .HHmo Como no CmCCoo OCOC quHC szoH CH Czonm 0pm wmwm .HHoo Comm ho noCCoo CCmC.pOmH Oman: CH Co>Hw mH pCsoo OoCoCaonm. "opoz OOH OOH OOH OOH OOH OOH OOH Hopoe mOH m mm mm H: OO O O.OO O.HH 0.00 0.00 0.00 0.00 0.00 vH.,..sz Co mmH ..H OH ,Hm mm H: m oHOOHz O.OO O.OO O.HH O.OO O.OH H.Hm O.OH Home HO O O O O on m no new Hsuoe OmsHpmm poOHo no cosOHHno smpOHHno soaOHHso onsHm Coo: ConoHHCo HooCom HooComopm oz no chum Hoonom OOH: Ogupcoson \OoHngaz \OoHanmz \OmHgosz \ooHnaw: .Aopcoo wCHanCm OuHCCEEoo.w CH omnqonm 3003 on» no Chum on» on masopm owwum oHoOo mqu msoHnm> CH mumssncoo no omCoamomII.mmum.mqm cmmawHHoo m wH 3min mHnmew .HHmo Comm no CmCCOO CCmC quHC CmBOH CH CzoCm mam wmwm uquoCma CECHoo .HHmo Comm no CmCCoo ccmn pmmH Cmaas CH Cm>Hw mH.pCCoo moCosumCm ”mpoz OOH OOH ooH 00H 00H O Haves mpH mm mm H: N» m.OO 0.0m O.mH m.OO H.OO xmoz mmH OH HO mm O: CO OHOOHC MOON O.OH 9mm O.OH O.Hm 2 xmms no CCm Hm mH w m mm . Hmpoe CmcHo Co CmCuHHCo CmnnHHCo CmchHCo CmCoHHCo oz 3mm: no puma Hoosom Cme HooCom Hoonommpm \anCsz \UmHCsz znmquSmHm \cmHCsz UCw meCHm OCm cmCHpmm, \cmHnsz muons mHomo mMHA .CmuCoo wCHaaoCm muHCCEEoo m CH Umnaonm gums mCu mo onmm 0C» on mazopu mwMum mHozo mqu msoHCm> CH mCmECmCoo no meoammmuuwamum mamHw mH ucsoo zoCmsvam umpoz 210 OOH OOH OO OOH OOH OOH OOH OOH OOH OOH - Hdooe meH O O O a: CO OH OH HH H 0.0m O O 0.00 O.OO H.Om m.ma O.HH m.sm O quHcOHz do mm O O O OO OH O m m O .E.O O c.mz c o m.mm w.m: 0.:w 0.0m w.ow m.mm OOH .E.Q w OO OO O O a On HO OH OH O H cooz 0.00 O O 0.0H O.OH O.OO m.mH O.OH H.O O cooz o» OH O O H O OO O m H O .E.d m O.O O O O O O m.H O O O .e.m O O» H O O O O O H O O O OOOHCOHE HOOOO OOOHO COO: O OO0.000 OOO.OHO OOO.OM OOO.OO OOO.OO OOO.mO meoocH Odo Cd: OOO.OaO -OO0.0HO -OOO.OHO uOOO.Hm -OO0.00 -OO0.00 COOOO oz do Opmd H Czopo cubecH Dilrlu. v ,Ilnllrll mcwuaczu muwcsfificc w :H Twadtzu >34 mfip Ho HLCC mg» «C agsoso assocH mnoHLm> CH CLQECwCCU no mmcoawmmtl.mmlm mumCE COHHUHHLR)‘ r 211 TABLE F-S9?—-Response of Consumers in Various Income Groups to the Part of the Day Shopped in a Community Shopping Center. Income Group Part of Under $5,000- $7,000- $10,000 Day $5,000 $6,999 $9,999 & Over Total Midnight H 5 20- 8 37 to Noon 13.8 16.7 , 33.9 19.5 2l.h Noon 20 18 23. 23 8A to 6 p.m. 69.0 60.0 39.0 A1.8 u8.6 6 p.m. 5 7 16 2h 52 to Midnight 17.2 23.3 27.1 “3.6 30.0 ' 29 3o 59 55. 173 Total - 100 100 100 100 100 Note: Frequency count is given in upper left hand corner of each cell. right hand corner of each cell. a - . Table F—59 is a collapsed version of Table F-58. Column percentages are shown in lower 212 TABLE F-60.-—Response of Consumers in Various Occupational . Groups to the Part of the Day Shopped in a Community Shopping Center. . Occupational Groups Professional White Blue Part of Day & Managerial Collar Collar Total Midnight 10 ' 7 20 37 to Noon 21.7 26.9 19.8 21.9 Nggn 20 . 11 53 8A 6 p.m. “3.5 M2.3 52.5 . h8.6 6 p.m. 16 8 28 52 to Midnight 3A.8 30.8 27.7 30.0 #6 - 26 101 173 Total . 100 100 100 100 Note: ‘Frequency count is given in upper left hand corner of each cell. Column percentages are shown in lower right hand corner of each cell. 3 l 2 .HHmo Como mo CoCCoo ncmC quHC Hmon CH CzoCm mum wmwm nquoCma CECHoo .HHmo Comm mo CmCCoo UCmC puoH Coda: CH Cm>Hm mH pCCoo moCmCdmCm "opoz OOH . OOH OOH OOH OOH OOH OOH . Hmuoe meH m mm mm HO HO w m.om o H.mm O.Hm m.mm =.=m m.>m prHCOHz - 8 mm O O O OH mm m .a.d O O.OO H.OO O.HH H.Hm O.OH O.HH 0.0m .e.d O . 09 :m m 0H mH om mm 3 C002 m.om m.mm 0.0H =.Hm o.mm m.Hm m.mH Cooz op mm m z m m OH H quHCon Hmuoe OmCHumm CmOHo Co CmCoHHCo CoCOHHCo CmCoHHCo meCHm has no whom CmCoHHCo HooCom HooComoCm oz HoOCom Cme mpmpCmEmHm \omHCsz \UmHCsz \omHCCm: \ooHCsz nacho oHomo mmHH on» mo upmm on» on masopw mwmpm .CmpCmo wCHaaonw auHCCEEoo m CH omaaonm hon oHomo ouHH mCOHCm> CH mCmSCmCoo no mmC0Qm0m7|.Hmnm mHmCB .Hmlm mHnt mo COHmCo> comawHHoo m wH mmum OHmem .HHoo Comm no CoCCoo OCmC quHC Coon CH CzoCm mum mowm anooCoa CesHoo .HHmo Como mo CoCCoo OCOC pmoH Coon: CH Co>Hw mH pcsoo OoCozumCm “opoz OOH OOH OOH OOH OOH ) , Hmuoe MOH 7 NO mm H: NO 0.0M H.Om O.Hm m.mm m.mm pCmHCUHz . on NO O O OH Om .a.O O O.OH O.OO H.HO O.OH O.HH .s.d O on HO OH OH ON wm Cooz 0.0N O.Hm O.Hm O.mm H.Om Cooz op OO O O O OH uandOHz Hmuoa CmOHo Co COCOHHCO CmCOHHCo CmpoHHCO CmCoHHCo 02 man no upwm Hoocow Cme HooCom Hoonommnm \omHCsz \OOHCsz OprCmEmHm \OmHCsz w onCHm OCO OmCHpmm \omHCCms asono mHozo mMHq «Cu mo pmmm on» on mosopc mwmpm .CopCoo wCHanCm szCCEEoo m CH omaaocm Own oHoOo mMHA msoHCm> CH mCoECmCoo no omCoammmaummmIm mam< OOOHOOO OOOHO do OOOOHHOO OOCOHHOO OOOOHHOOA OHmch _ omdpm CmCoHHCo Hoonom HooComoCm oz mHozo oqu HooCom zmHz OCmpCoCmHm \ooHCsz \ooHCsz \ooHCsz \OmHCsz .mommum OHomo oMHa msoHCm> zo CmoCoO mCHQQOCm ooOCCoOCwHoz w o» QHCB wCHooocm Coo mCHaooCm opomeCH op oopo>mm mEHB mwmao>< 8 m .5300 msHm OOHHOO OOHO: HOHmemsz a HmConmomoCm Cooke HOCoHqusooo .mosouo HmCoHmesooo msoHCm> an pouCoo wCquoCm oooCCoonHoz w on QHCO mCHooonm Con mCHaaoCm onopmuCH on Oouo>oa oEHB owwno>< do>HO OO>O O OOO.ONO OOO.OHO OO0.0» OO0.0» OOO.O« OOO.m» «soocH Ooz OOO.ON« uOO0.0HO uOO0.0HO uOO0.00 -OO0.00 uOOO.m» noon: .mosonu oEooCH msoHCm> an CopCoo mCHoqum oooCCoonHoz m on QHCB wCHaqocm Coo wCHaQOCm oCOmeCH op oouo>oa oEHB owwno>Hw mH quoo zocoscopm ”muoz OOH OOH OOH OOH OOH OOH OOH OOH OOH OOH HOOoO OOH O O OH OO HO ma OH OH O.HH OOH OOH O OH O.OO O.OO O.OO O.OO O.OO OOH How: Co \ 0 OOH O O OH Om OO mm OH O H HOOHz O.OO O O O.OO O.OO O.OO 0.00 0.00 O.Om O :60: OH O O O OH OH OH O O O Oo ocm HmOoO OO>HO OO>O O OOO.ONO OOO.HHO AOO.OO OOO.OO OOO.OO OOO.mO deoocH x663 Ooz OOO.ONO uOOO.OHO -OOO.OHO -OOO.HO -OOO.OO -OOO.mO OOOOO oz Oo spam CCOCO oaooCH .CmuCoo wCHaoocm OoocpoonHoz m CH vmdoonm xwmz ozo Oo oCmO on» o» mQCOCo_oEoocH msoHCm> CH meECwCoo Co mucoamomln.HOam mqm OOOOOHHOO O OH O0-0 OHOOOO .HHmo Comm mo CoCCoo OCOC prHC Coon CH CzoCm mam mmwm .HHmo Como mo CoCCoo OCmC umoH Coon: CH Co>Hw OH quoo zoCosuoCm ”mpoz OOH OOH OOH OOH OOH OOH HOOOO OOH Om OO HO OH Om H.HO O.OH O.OH O.OO O.OH O.OO Ommz OOH OH Om Om mm OH Co OHOOHs O.OO O.OO O.OO 0.00 0.00 O.OO Omms Oo Odm OH O OH OH OH O HOOOO ,COOO O , OOO.OHO OO0.00 OO0.00 OO0.00 gum; Co OCOO -OOO.OHO -OOO.OHO -OOO.OO uOOO.OO Owns: qsoCO osooCH .CouCoo wCHaoonm OoonhoonHoz m CH ooaooCm xomz on» no upmm on» o» masons oEooCH msoHCm> CH mCoesmCoo mo mmConmomllmeIm mqmHw mH OCCoo zoCmsompm "mpom OOH OOH OOH OOH OOH OOH OOH Hauoe OOH HH Om mm O: HO O 0.00 0.00 0.00 H.HO H.HO m.~m m.mm xmos OOH OH HO mm .7 HO HO O Co OHOOHO O.OO H.O O.OO 0.00 0.0H 0.00 0.00 xmmz no nCm O: H O OH O ON m Hmpoa OmCHpmm chHo no CmCOHHCo COCCHHCO CmCCHHCo onCHm xmmz no pawn CmCOHHCo HoOCom Hoonowmpm oz Hoozom CmHm mpmpCmEmHm \omHhsz \OOHCsz \OmHCsz \vaCsz nacho OHomo mmHH «no no OCOO 0:» on .Coquo wCHoaoCm CooCConCmHoz m CH condonm xmm3 OQOOCO mwmum OHozo mMHH msoHCm> CH mCoECOCoo mo omCoamoqu.=~Im mHmCB 22M .Ownm mHnt no COHmCo> ommCmHHoo O OH O0-0 OHOOOO .HHmo Como no CmCCoo OCOC prHC szoH CH CzoCm mCm wmwm anmoCmu CCCHOO .HHoo Como no CmCCoo nCmC uumH Coma: CH Co>Hw mH ucsoo zoszomCm ”ouoz OOH OOH OOH OOH OOH - HOpoe OOH mm my x: mm . 0.00 O.Hw H.HO H.:m O.OO xom3 \ o omH Hm mm pm on m chqu m.mm 0.0H 0.0m 0.0H 0.00 xmmz no UCm O: O OH O mm Hmpoe CmOHo Co CmCUHHCo CmCOHHCo CmCoHHCo oz xmmz mo unmm CoCOHHCo HooCom Hoosommpm. \OoHCpmz HOOCow Cme zpmquEmHm \OmHCsz OCm meCHm \OOHCsz \omHCsz OCm OmCHpmm asopo mHoOo mMHH .Cmpcoo mCHannm CoonnonCmez m CH omnoonm xmms me mo pCmm me on OCCOCO mwmum mHomo mmHH mCOHCm> CH mCoECmCoo no mmCoammmlsmmwum mamHm mH pcsoo zonsumpm Houoz 228 OOH OOH OOH OOH OOH OOH OOH OOH OOH OOH HOOOO OOH O O OH OO HO O: OH OH H O.OO O 0.00 0.0H 0.00 O.OO O.OO 0.0H O OOH OcchoH: on OO O O O OH OH OH O O H .e.o O O.OO OOH 0.00 H.HO O.OO H.HO O.OO O.OO O.OO O .e.d O 0» mm N O HH mm OH om O O O Cooz O.OH O O O.OO O.OH O.OH O.OO O.OO . 0.0m O cooz o» OO O O O O O OH O N O .e.m O 0.0 O O O O O O.O O O O - .e.O O . 8 H O O O O O H O O O OCOHCOHE HOOoO OOOHO COOO H OOO.OOO ee..OHO eOO.eO OOO.OO OOO.OO OOO.OO osoocH HOO Ooz OOO.OOO -OOO.O O -OOO.OHO -OOO.OO IOOO.OO -OOO.OO COOOO oz Co OCOO azozo COCOCH .CmpCoo wCHuqocm OOQCCOCCOHOZ a CH Oduuczu mag esp Co OCOC mg» 0O OCJCCG QEOOCH OonCm> CH maezmcoo ao omcoamomll.owum mHmCB .mwum oHpme ho ConCo> OomumHHoo O OH omum oHomb .HHmo Comm no CmCCoo CCOC pcmHC Coon CH Czozm mpm mmww uquoCmu CECHoo .HHmo Comm mo COCCoo OCOC ummH pmaqs CH Cm>Hw mH pCsoo moCmsamCm ”ouoz OOH OOH OOH OOH OOH proe OO O» HO OO ON 0.00 0.00 O.OO 0.00 O.HH OOOHCOHS on. NO OH OH OH O .e.O O m.mm 0.00 H.OO m.OO 0.00 .E.C O on mm O: OH om mH Cooz w.mH m.mH m.mH m.mm 0.0m Cooz op mm m m HH m prHCcH: HmOom pm>o O OO0.00 OO0.00 OOO.OO man no OCOO OOO.OHO -OO0.00 uOO0.00 nouns Qsouo mEooCH .Copcoo mCHaQoCm OoonuonCmez a CH Ooaaonm Own an» no pCmm on» on masonu macoCH msoHCw> CH mumssmCoo Co mmCoammmulmomum mamHm mH pCsoo OoCmsamCm “muoz OOH OOH OOH OOH OOH OOH OOH Hmpoe OOH HH Om mm O: HO O 0.0m O 0.0m 0.0m 0.0m H.Hm m.mH prHCOHz on OO O O OH OH OH H .e.O O 0.00 0.00 0.00 O.OO 0.00 O.OO 0.00 .E.O O on OO O OH OH mm Om m C002 1 m.m.mH m.m: H.HH H.OH m.OH 0.0H 0.0m Cooz on OO O O O O OH O OCOHOOHE Hmpoe OOCHpmm COOHO Co COCOHHCO COCOHHCQ COCOHHCO meCHm mam mo pnmm COCOHHCO Hoonom Hoonommnm oz \ Hoozom CmHm OpmpCmEmHmr .\Umesz \Omesz \OOHCCOE \OmHCsz asopo mHoOo ohHH .CmpCmo wCHQQOCm noosponCmez m CH Omdaonm Own OCu mo ppmm me 0p masoCO mmmpm mHoOo OMHH OCOHCO>.CH mCmECOCoo mo meoammmll.mOlm mqm OmmmmHHoo OH mmnm mHimhu .HHmo Comm mo COCCOO OCOC OCOH CmaoH CH Czogm m mmmm squoCmO CECHoo .HHmo Comm Oo LOCCoo OCOC pmmH Cmaas CH .m>Hm mH OCsoO m wmpm “mpoz OOH OOH OH OO OOH HOOOB OOH OO OO OO OO 0.0m 0.0m 0.0m 0.0m 0.0m prHCOHz on. OO O OH OH Om .ed O O.OO O.OO O.OO O.OO O.OO .e.O O on Om Hm OH mm mm Cooz 0.0H H.Hm H.OH 0.0H m.om Cooz on OO O O O OH 235:: Hmpoe COOHO Co COCOHHCQ COCOHHCO COCOHHCO oz zmm mo phmm COCOHHCO HooCom HOOCommCm \OmHCsz HOOCom COHO OCOpCmEmHm \OOHCCOE OCO meCHm \OOHCCOZ \OmHCsz OCO omCHpmm mzopo mHoOo mmHH .CmpCmo OCHQQoCm OOOCCOQCOHmz m CH OOQQOCO OOQ me mo pCmm me ou mQCOCO mwmpm mHoOo muHH msoHCm> CH mCmECOCoo mo mmCoammmIIWMOum mqm¢e 233 TABLE F-8h.--Response of Working and Non-Working Wives to the Part of the Day Shopped in Neighborhood Shopping Centers. Wife Employed or Not Part of Day Not Employed Employed Total Midnight - 29 7 36 to , Noon 18.8 21.9 l9.h Noon 78 20 98' to 4 6 p.m. 50.6 62.5 52.7 6 p.m. A7 5 52 to Midnight 30.5 15.6 27.9 15h 32 186 Total 100 ,100 100 Note: Frequency count is given in upper left hand corner of each cell. Column percentages are shown in lower right hand corner of each cell. 234 TABLE F-85.--Response of Consumers in Various Automobile Automobile Ownership Group Ownership Groups to the Part of the Day Shopped in Neigthrhood Shopping Centers. None One Two or Part of Day Owned Owned More Owned Total Midnight 0 l 0 l to 8 a.m. 0 0.9 0 0.5 8 a.m. 0 27 8 35 to Noon 0 25.2 10.7 18.8 Noon 1 55 “2 98 to 6 p.m. 25.0 51.u 56.0 52.7 6 p.m. 3 2A 25 52 to Midnight 75.0 22.“ 33.3 28.0 u 107 75 186 Total 100 100 100 100 -¥ Note: Frequency count is given in upper left hand corner of each cell. Column percentages are shown in lower right hand corner of each cell. 235 TABLE F-86.a--Response of Consumers in Various Automobile Ownership Groups to the Part of the Day Shopped in Neighborhood Shopping Centers. Automobile Ownership Group One or Two or 9 Part of Day Less Owned More Owned Total Midnight 28 8 36 to Noon 25.2 10.7 19.4 Noon 56 M2 ' 98 to 6 p.m. 50.5 _ 56.0 52.7 6 p.m. 27 25 52 to ' Midnight 2H.3 33.3 27.9 111 75 186 Total 100 100 100 Note: Frequency count is given in upper left hand corner of each cell. Column percentages are shown in lower right hand corner of each cell. a 7 Table F-86 is a collapsed version of Table F-85. "Illlllllll'l’lll‘TS