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Filmed as Xerox University Microfilms 300 N orth Zesb Road Ann Arbor, Michigan 48106 I I 76-18,690 YU* Jong-Tswen, 1939A SPATIAL ANALYSIS OF COMERCIAL CAMPGROUNDS IN MICHIGAN. Michigan S ta te U n iv e rs ity , P h .D ., 1976 Economics, a g ric u ltu r a l Xerox University Microfilms , Ann Arbor, Michigan 40106 A SPATIAL ANALYSIS OF COMMERCIAL CAMPGROUNDS IN MICHIGAN By Jong-Tswen Yu A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Resource Development 1976 ABSTRACT A SPATIAL ANALYSIS OF COMMERCIAL CAMPGROUNDS IN MICHIGAN By Jong-Tswen Yu This study was designed to investigate the location problem of private campground enterprises in Michigan. Its primary objective was to provide information on the spatial distribution pattern of commercial campgrounds and to delineate campground location decision factors. Methodologically, the study began with an investi­ gation of significant spatial characteristics which were considered to be associated with the existing distribution pattern. Then, an attempt was made to determine which locational factors were statistically significant in explaining location decision behavior of private camp­ ground enterprises. The investigator approached the study from the standpoint of the commercial campground developer as a producer, and analyzed the problem within the con­ ceptual framework of microeconomic theory. Two types of research techniques were used in this study. First, the investigator applied geographic analysis Jong-Tswen Yu techniques such as computer-mapping and nearest neighbor analysis to describe and analyze the existing pattern of commercial campground development in Michigan. The geogra­ phic unit chosen for this analysis was the county, and thus county data were the main inputs for the analysis. Second, multiple linear regression analysis was employed to identify significant campground location decision factors and analyze the degree and direction of their relationships with the campground occupancy rate as the dependent variable. Results of this study reveal that the private campground industry in Michigan was spatially characterized by a clustered distribution pattern. This distribution pattern was positively correlated with highway convenience and accessibility, location of quality water resources, and recognized tourist attractions. But since campground operations were extensive enterprises with modest financial returns, land costs were found to be important constraints on commercial campground development. Results also indicate that both water resources and population variables played a key role in determining campground occupancy, and the former seemed to have much greater influence than the latter. But the higher occupancy rate was associated with campgrounds having both quality water resources and good access to population centers. These two factors together seem to indicate that urban fringe areas having a quality water resource base could be Jong-Tswen Yu desirable locations for commercial campground development— provided, of course, that land costs are modest. The influence of public campgrounds on private campground occupancy rate was also found to be statistically significant. Private campgrounds often share advantages of natural wonders with public neighbors, but they are in fact, competing for customers. Mo evidence was found to support the argument that private campgrounds were benefited by the overflow of campers from their public neighbors. ACKNOWLEDGMENTS The author wishes to express his sincere gratitude to his major professor and dissertation director, Dr. Daniel E. Chappelle, Professor of Resource Economics and Regional Science, for his guidance and help in improving the author’s educational training and dissertation research Gratitude is also extended to Dr. Eugene F. Dice, Associate Professor of Recreation Resource Development, whose helpful suggestions have been invaluable in the author’s study of comme rc ia1 c ampgrounds. Special thanks are expressed to the members of the author's guidance and dissertation committee: Dr. Robert J. Marty, Professor of Resource Economics and Programming, Dr. Lewis Moncrief, Associate Professor of Park and Recreation Resources, and Dr. Milton H. Steinmueller, Professor of Resource Conservation and Development, for providing valuable review of the dissertation. Gratitude is also extended to Dr. Robert I. Wittick, Associate Professor of Geography, for his advice in developing computer maps, and to Dr. James G. Ahl who read the entire manuscript of this report and made many helpful suggestions Sincere appreciation is extended to Mrs* Linda R. Boyer for typing and preparing materials for the mail questionnaire survey, and to Mr. J. Paul Schneider for his help in preparing drawings and reproduction of computer maps. Finally, the author sincerely appreciates the understanding and patience of his wife who gave the author great encouragement and support throughout his entire graduate program and dissertation research. iii TABLE OF CONTENTS TABLES ....................................... vi FIGURES ..................................... ii INTRODUCTION: THE STATEMENT OF THE PROBLEM . . . . .......................... 1 The Role of Location in Private Campground Development ............... 3 The Problem Context 7 .................... Objective of the Study ................. 13 The Study Area .......................... 14 Assumptions 17 ............................ Organization of the Study 19 ............. RESEARCH METHODS AND DATA SOURCES ......... 20 A Brief Methodological Review ......... 20 Methods for Spatial Description . . . . 25 .................... 32 Data Sources for the Study ............. 40 The Analysis Method Primary Data Sources ............. . Secondary Data Sources ............. PRIVATE CAMPGROUND DEVELOPMENT IN MICHIGAN . 41 47 50 Growth in Campground Industry ......... 50 Types of Campground Operation . . . . . 53 iv CHAPTER Page Campground Distribution ................. Regional Characteristics IV. .......... 58 Spatial Patterns of Campground D e v e l o p m e n t ........................ 63 ANALYSIS OFPRIVATE Geographic CAMPGROUND DISTRIBUTION . 76 Unit forA n a l y s i s .............. 77 Developing Hypotheses V. 55 .................... 78 The Analytical Model ...................... 85 The Statistical Findings .................. 88 Discussion ^nd Conclusions ............... 94 FACTORS IN THE PRIVATE CAMPGROUND LOCATION D E C I S I O N ........................................ 103 The Analytical Model and ItsVariables . . 104 The Dependent Variable ............... 106 Independent Variables ............... 107 Statistical Findings ...................... 113 D i s c u s s i o n ....................................118 VI. SUMMARY AND CONCLUSIONS ...................... 127 Summary of the P r o b l e m ...................... 127 Summary of the M e t h o d s ...................... 128 Summary of the F i n d i n g s .................... 129 General Conclusions . .................... 134 Uses and Limitations of this Study . . . . 136 Implications for Future Research ......... 139 BIBLIOGRAPHY ............................................ 143 APPENDICES . . . . . 151 ................................... v LIST OF TABLES Summary of Survey Responses 43 ............... Distribution of Complete Responses and All Campgrounds Surveyed ............... . 44 Distribution of Complete Responses Among Different Size Classes ............. 46 Growth in Private Campground Industry in Michigan .............................. 51 Regional Distribution of Campgrounds in Michigan ................................... 56 Regional Characteristics of Private Campground Distribution ................. 61 Diffusion of Private Campground Development .............................. 65 Nearest Neighbor Measures of Private Campground Locations ...................... 74 The Independent Variables Included in the County Model .......................... 89 A Summary Table of Regression Results 91 <. . . Distances from Private Campgrounds to State or Federal Highway ................. 96 Summary of Private Campground Distribution by Different Adjacent Water Bodies . , . . 98 Water-Oriented Recreational Activities Provided by Private Campgrounds ......... 100 Summarized Regression Results of Significant Variables for the Campground Model . . . . 114 vi Table 15. Page Campground Location Determining Factors as Viewed by Michigan Private Camp­ ground O p e r a t o r s ................................. 123 vii LIST OF FIGURES Figure Page 1. Study Area Showing Regional Subdivisions ... 15 2. The Mapping P r o c e s s ............................ 28 3. A Flow Diagram Indicating Regression Model Building Process Used in this S t u d y ......................................... 37 The Distribution of Private Campgrounds and Major Municipalities in Michigan . . . . 59 Diffusion of Private Campground D e v e l o p m e n t ................................... 66 Distribution of Private Campgrounds in Michigan, 1964 69 Distribution of Private Campgrounds in Michigan, 1969 70 Distribution of Private Campgrounds in Michigan, 1973 71 Maps Showing Water Surface and Private ............. Campsite Distribution Patterns 80 Maps Showing Highway Density and Private Campsite Distribution Patterns ............. 83 Elements in the Campground Developer's Location Decision Model ...................... 105 4. 5. 6. 7. 8. 9. 10. 11. viii CHAPTER I INTRODUCTION: THE STATEMENT OF THE PROBLEM Outdoor recreation has been an important segment of American life. Over the past years, the demand for outdoor recreation opportunities has grown rapidly as population and leisure time have increased, as outdoor recreation equipment and transportation facilities improved, and as increase in disposable income makes it possible for more people to travel and recreate more often and at a farther distance. In addition, growth of outdoor recre­ ation demand has been also accelerated by the sales pro­ motion of outdoor recreation equipment manufacturers, as well as by the availability of outdoor recreational areas and facilities to meet the needs of many people. Along with a growing demand for recreational services in general, there has been a rapid increase in the private supply of outdoor recreational services. This may be partially due to the fact that the outdoor recre­ ation opportunities provided by the public sector have not been able to cope with the growing demand, and as a con­ sequence, most of public outdoor recreation areas and facilities have been overloaded. Meanwhile, the public 2 sector has encouraged private development of outdoor recreation services.^- The federal government, for example, has established a number of programs to assist private recreation development. To mention some important ones, they include credits, technical aids, training and educational services, and research. 2 As a result, many pri­ vate enterprises have taken an opportunity to engage in outdoor recreation development, and in fact, have satis­ fied a significant part of the outdoor recreation needs. Many rural lands retired from agricultural production or in an idle state have been developed into outdoor recre­ ation use. These changes deeply affect use made of such natural resources as land, water, woodlands, wildlife, and related natural environments and have increased incomes or other forms of satisfaction to rural land owners. 3 It should be recognized also that fee settings and intensive promotion of many public outdoor recreation services may create barriers for private entry in the outdoor recreation business. However, to new entrants public assistance, especially financial aid, may provide more encouragement than barrier and the pressures of public competition are oftentime realized after private enterprises have been in business. 2 For a detailed discussion on the federal govern­ ment assistance to private recreation development, see Clayne R. Jensen, "Outdoor Recreation in America" (Minneapolis, Minn.: Burgess Publishing C o . , second edition, 1973), pp. 57-100. Also see, Clodus R. Smith, Lloyd E. Partain, and James R. Champlin, "Rural Recreation for Profit" (Danville, 111.: The Interstate Printers & Publishers, Inc., 1966), Chapter 11, pp. 247-260. 3Smith, Partain, and Champlin, Ibid., p. 11. 3 Among the wide range of outdoor recreation activ­ ities and facilities provided by the private sector, com­ mercial campgrounds are perhaps the most feasible and widespread outdoor recreation enterprises. They provide campers, families for the most part, with campsites for tents, trailers, or campers and other related services for a fee. In addition to camping, many private campgrounds also offer a variety of outdoor recreation activities such as swimming, picnicking, fishing, boating, and hunting on the campground or nearby. Some large campgrounds even provide recreation-room type of activities and facilities 4 along with campsite rental. Facing such a dramatic change and rapid growth in the campground industry, pro­ spective campground developers may require additional information and decision techniques to facilitate their investment and management decision-making. As emphasized in the following section, campground location information is a necessary input to such decisions, and thus, requires a more rigorous investigation. The Role of Location in Private Campground Development Location has been emphasized in almost every dis­ cussion of the demand and supply of outdoor recreation 4 For example, they may include such facilities as pool tables, table tennis, television set, or just a com­ fortable place where people can relax and chat with each other. 4 activities. Location of a campground and its relation to the location of potential customers is critical in esti­ mating demand for campground services for several reasons. First, to obtain campground services, a camper must travel from home to a campground and back, and this takes time and money, sometimes relatively a lot of each. If a camper rationalizes his travel costs, the distance between the campground and his home would be important to him in deter­ mining whether he is going to visit the campground or not. As a result, demand for campground services is affected by the location of a campground relative to its potential customers. Second, most people have preferences as to the type of physical characteristics associated with a camp­ ground location, including the type of tree cover, or of topography and natural beauty. Most physical character­ istics are fixed at a particular location, and each loca­ tion often has a different type of physical features.5 The site may consist of an area of land, with or without tree cover; it may be a body of water or a flowing stream; or it may have other natural features, such as a cave or a rolling hill. These natural characteristics are important in studying demand for campground services because they affect the willingness of people to use the campground 5 To certain degree, the physical environment can be modified by landscaping treatment. However, large scale treatments are usually costly and may not be feasible for campground operators to conduct. 5 for outdoor recreation. Third, the importance of location in studying demand for campground services can also be expressed in terms of spatial interdependence. The dif­ ferent campgrounds may lie at different distances from their customers and may also vary in the degree of physical attractiveness. Two or more campgrounds in the same area may be competitive for services to a given group of campers; in this situation, an increase in visits to one campground will be offset by a reduction in visits to the others. On the other hand, different recreation areas and facilities may also be complementary to each other. Tourist attractions, for example, may favorably affect the number of visits and the length of stay per visit to the campground located in the same area because they provide campers with different opportunities for a variety of experiences and make the campground more attractive. Therefore, demand for campground services is also affected by locational interdependence which is an important con­ cept in location analysis. The supply of outdoor recreation services also depends on natural resources such as land, water, and other physical features. The physical characteristics define limits to certain types of recreational experiences that can be gained at a site. Hence, they define the type of recreational services that can be supplied. of water-oriented activities, The types for example, vary from one 6 campground to another, depending upon the quality and area of water surface available at different campgrounds. To provide snow-skiing activity, for another example, the area where the campground is located must have sufficient slope and snow cover during the season. In addition to activity-mix, the campground location choice may also affect the supply costs of campground operation. This can be understood by considering the location decision as a selection of inputs such as land, labor, and other neces­ sary supplies to support campground operation. Improper campground location has been pointed to as one factor associated with low return level in the operation of campground business. It is important that campground enterprises facing the problem of increasing business competition re-evaluate their locations. If a manager finds that campground location has disadvantages for market competition, he may try to design a management strategy to overcome locational disadvantages. If loca­ tional disadvantages cannot be overcome by a new manage­ ment strategy within reasonable cost, management may con­ sider relocation of campground facilities or termination of the campground operation and conversion of the camp­ ground into other more lucrative uses. ^Malcolm I. Economics," iji "The ings," USDA, Forest ment Station, Upper Therefore, Bevins, "Private Recreation Enterprise Forest Recreation Symposium Proceed­ Services, Northeastern Forest Experi­ Darby, PA., 1971, p. 34. 7 campground location information is important to existing campground enterprises, as well as new ones. When planning a new campground development, prob­ lems concerned with the determination of location, design capacity and layout of the site will have to be solved before the investment can be properly carried out. The determination of location is the first and the most crucial decision to be made by the campground developers. Such a location decision must be based upon well-studied locational information such as physical environment and market potentials. The Problem Context It has been contended that locational factors may play a significant role in private campground development. Proceeding from such a premise, this study focuses on commercial campground enterprises in Michigan in an attempt to describe and analyze the spatial distribution patterns of the industry and the influence of location on business performance of individual campgrounds. 7 In contrast to most studies concerning recreation location problem, this study approaches the problem from the viewpoint of the campground developer as a producer. 7 The private campground enterprise considered in this study may be defined as a business venture, under­ taking or operation which pursues a commercial motive seek ing to gain a profit or sustain itself from user fees, by offering camping opportunities on a parcel or tract of land as a principal product of that venture. 8 The campground developer Is considered important in the study of location problem because he is the decision­ maker actually making the locational choice. The idealized consumer’s choice in campground location is limited in practice by the availability of campground alternatives substantially determined by the developers. In all cases, campground developers are mainly responsible for locating and purchasing land for campground development. Their locational behavior in providing campground services plays a key role in shaping the spatial distribution patterns of the campground industry. With the above focus in mind, this spatial analy­ sis of private campground locations and business perform­ ance necessarily involves three specific questions con­ cerning the general problem of public outdoor recreation planning and private campground location decisions. They are: (1) Where are the existing private campgrounds located? (2) What are the major location factors that affected the existing private campground distribution pattern? (3) What are the essential relationships that exist between the business performance of a private campground enterprise and its location choice? 9 Among these questions, the first two are concerned pri­ marily with an understanding and interpretation of the existing distribution pattern of the private campground industry as a whole. An inquiry into these questions will involve considerations of some spatially distributed phenomena such as spacing, diffusion, and relative loca­ tion of private campgrounds to themselves, to public campgrounds, and to other cultural activities and natural resources. Two methodological questions that are critical in the analysis of spatial distribution must be resolved before the analysis can be proceeded. First, what sort of measures can be used to characterize the distribution, and second, for which pair of distributions ought these mea­ sures be established? The third question consists of evaluation of location decision factors with respect to campground business performance. To investigate this question, it is first necessary to determine the performance measures so that contributions made by individual location factors can be evaluated. To be useful, such a performance measure must have two basic functions. First, it must be sen­ sitively responsive to relative contributions of individ­ ual location factors. And second, it must be consistent with the investment objectives pursued by the prospective campground developers. In the present situation, we have no way of knowing the identity of prospective campground 10 developers and their investment objectives. This may impose some difficulty in determining what would be appropriate performance measures. However, this task can be completed in two alternative ways. In one case, the performance measures may be chosen on the basis of business operation goals cited by the current campground operators. On the other hand, we may simply follow the convention of assuming that as a commercial enterprise, the private campground would be operated in such a manner as to maxi­ mize profit. In this study, we examine campground loca­ tion decision factors in the usual microeconomic framework of profit maximization. To begin with, let us assume, for purposes of emphasis on the location decision, that we are investi­ gating the production of a recreational service measured p by a unit of "campsite-day" and that the campground location decision can be treated as an essential part of the developer's overall selection of inputs and outputs which determine profit. In selecting the campground location, it is also assumed that the private campground developer is guided by his desire to maximize profit within some constraints posed by his enterprise's "pro­ duction function." Underlying these assumptions, we can Q The term, "campsite-day," is used here as a measure of unit output "produced" by the private camp­ ground enterprise which is defined as any use of a camp­ site within 24 hours by a camper or group of campers who rent(s) the site. 11 express, in a simple mathematical notation, the private campground developer's behavior as follows: Maximize Subject to: F(x^, #*n f • fy^) = 0 where: P = the campground enterprise's profit for providing campground services. R ( y ^ y ^ ) is the revenue function whose value depends upon the prices, level and mix of outputs y^,....,yjt which may include site rental and other related incomes. C(x^,....,x ) is the cost function whose value depends upon the prices, level and mix of inputs x^,....,xn some referring to physical and locational characteristics of the site, some referring to material, labor, and capital. F{x^,....,xfi,y^,...,y^} = 0 are the tech­ nical constraints governing the rela­ tionships between inputs and outputs in the "production function." The campground location decision can thus be treated as an important and complex part of the campground developer's overall selection of inputs, outputs, and con­ straints for campground operation. And consequently, we can hypothesize that the choice of location for campground development is conceptually equivalent to a multiple selection of locational characteristics. These locational characteristics are assumed to be reflected in three sets 12 of locational decision factors: (1) those relating to individual campground site such as topography, vegetation cover, etc.; (2) those relating to local and immediate surroundings of the area; and (3) those which describe the relative locations of market areas and alternative recre­ ation sites and facilities. These locational factors may affect campground outputs, either in terms of campsite-day or monetary income, in one or more ways. Tney may influ­ ence the output as inputs to the "production function." They may also act as parameters which influence the tech­ nical relationships between inputs and outputs, or as con­ straints which place a limit upon the outputs. Based upon the above preliminary analysis, we can derive the following hypotheses: (1) The distribution of private campground development is substantially affected by spatial character­ istics and these serve as location decision factors. (2) The optimal solution to the campground location decision can be substantially explained by the selected locational characteristics which act as inputs to, parameters in, or constraints on the production function closely relating to such decision. 13 (3) The campground locational choice would involve a selection of an array of relevant characteristics rather than a single locational factor. These hypotheses must be carefully investigated, and this constitutes the main part of the problem in the present study. Objective of the Study This study is primarily designed to provide an understanding of the existing private campground location pattern and a systematic inquiry into campground location factors and their relationships to private campground performances. The main objective of this study is thus to generate campground location information and develop analytical models for private and public outdoor recreation planning. In addressing the questions mentioned in the problem context, this study specifically attempts to: (1) describe and explain the spatial distribution of private campground development in Michigan; (2) determine whether multiple regression analysis techniques can be successfully used to analyze the influence of locational forces on private camp­ ground development and business performance; and (3) discuss and evaluate the practical implications of locational influences for private campground location decisions and public outdoor recreation planning. 14 The Study Area The area under present study consists of the entire state of Michigan. This study area was divided into three regions to examine regional differences. The entire Upper Peninsula was designated as Region 1, the northern half of the Lower Peninsula as Region 2, and the southern half of the Lower Peninsula as Region 3. The regional bound­ aries and the counties contained in each region are shown in Figure 1 on page 15. This scheme of regional division is currently used by the Michigan Department of Natural Resources to organize field offices and staff positions for managing natural resources and the state park system. Administrative efficiency was claimed to be the main rationale underlying this regionalization scheme. g Adoption of this regional division for the present study is not based upon administrative efficiency as in the case of the Michigan Department of Natural Resources. It is instead based upon two essential reasons. First, there are differences in both physical and socio-economic settings between regions that may reflect differences in the patterns of both campground development and use. The Upper Peninsula is remote from major population centers, 9 No description was found in the official or academic reports to rationalize this regionalization scheme. This rationale was suggested by a staff member of the Department. L _ awta** r oseoci THAV- | ,,0*° *oico« REGION M ECO STA | l t A , < ‘- L * h | i O t . A l i D ^ i 1 ]XUST >**■••• kill j i ;— > l :REGJ 0NJ 3 fATOM ««*» ^ w i , 1OAtfLAMD HA60M C*l*4U« .JAClIfOt 1 t( Ml CM J t eiii lav. C t A l M »0M*t F i g • 1.--Study Area Showing Regional Su bd iv i s i o n s . 16 and is, in addition, very scarcely populated. The entire region is characterized by extensive forest cover and a low level of economic development. Moreover, since it is situated at the northern tip of the state, the early arrival of winter means that the camping season in the Upper Peninsula is shorter than the other two regions. In terms of campground development, as noted by Dice and Wang, the Upper Peninsula "is influenced by major eastwest travel arteries serving non-native users. The northern Lower Peninsula has a natural environ­ ment for campground development similar to the Upper Peninsula. Since it is more accessible to major popu­ lation centers, most campgrounds may be used by the Michigan residents. As in the Upper Peninsula, most tourist attractions in this region are oriented to natural scenery and points of historical significance. With a locational advantage of high quality water resources and reasonable distances from major population centers, many points within the region have been developed into resort or vacation home areas. In Some cases, competition of land resources for private campground development and alternative uses may be considered significant. Eugene F. Dice and Darsan Wang, "Economic Scale and Dollar Exchanges in the Michigan Privately Owned Campground Industry," Research Report No. 228, Agricul­ tural Experiment Station, Michigan State University, East Lansing, Michigan, p. 4. 17 The southern Lower Peninsula is characterized by population concentration and relatively intensive economic development. According to the 1970 Census of Population, nearly 89 percent of the state population reside in this region, and 10 of 11 Standard Metropolitan Statistical Areas are located within the regional boundaries. In their report. Dice and Wang remarked that Mregion C (same as region 3 in this study) draws heavily on the vast population as a market resource and has high patronage from the states directly s o u t h . I t is hypothesized that private campground development and use patterns in this region are different from those in the other two regions. Assumptions The basic assumptions underlying this study con­ sist of two types. The first type includes general assump­ tions which may be viewed as premises for the study. The second type includes specific assumptions which are related to the analytical model particularly designed to solve the problem. Component parts of each type of assumptions are listed as follows. General Assumptions 1. Private enterprises will continue to enter in the campground business and the public sector will continue ^ I b i d . , p. 5. 18 to provide assistance to private enterprises in developing campground services. 2. The camper's behavior in engaging in camping activity will remain in the same trend as before and the camping consumption pattern will be constant over time. 3. Campground location is not a matter of indif­ ference, and proper location choice is a necessary con­ dition for a successful campground business operation. 4. Campground developers require relevant loca­ tion information to evaluate prospective campground locations and deficiencies exist in the availability of such campground location information. Specific Assumptions 1. Campground operation is expected to be oriented toward a primary income generating enterprise and gener­ ation of profit will receive major emphasis in campground investment. 2. Campground developers' location decisions are economically "rational" and based upon past experience and knowledge of existing areal characteristics. 3. Economic and physical characteristics of an area are important in location decisions of private camp­ ground establishments. 4. It is possible to correctly specify relevant independent variables and relationships in the framework of linear multiple regression analysis. 19 Organization of the Study This study consists of three major parts. Part 1 discusses the data sources and describes methods used in the study. This can be seen in Chapter II. Part 2 pro­ vides a general description of private campground develop­ ment in Michigan. Data are summarized and displayed in tables with proper descriptions to highlight the essence of the private campground industry in Michigan. stitutes the main context of Chapter III. core of this study. This con­ Part 3 is the It provides an empirical analysis of campground distribution and location decision factors. Multiple regression analysis is employed to estimate relationships between campground performances and spatial characteristics involved in location decision. Statis­ tical significance of the hypothesized relationships is also examined within the same analytical framework. results are reported in Chapter IV and Chapter V. The Finally, in Chapter VI, conclusions and implications are presented, and the study results summarized. CHAPTER II RESEARCH METHODS AND DATA SOURCES Determination of research methods and data sources is of crucial importance to any research activities. There is a need for a special attention to the choice of research methods and data collection. This chapter will describe the methods and data sources involved within this study and discuss the rationale underlying choices of specific techniques. This discussion is intended to be general and focuses on the overall research framework rather than specific operating procedures. The opera­ tional procedure of a particular analytic technique will be described in more detail within the chapter in which it is applied. A Brief Methodological Review The importance of location in determining demand and supply of outdoor recreation opportunities has been recognized since the emergence of recreation economics. But rigorous research on the location problem of outdoor 20 21 recreation development is a relatively recent attempt.^ During past years locational factors such as those relat­ ing to region, area, and site characteristics were often studied in conjunction with other socio-economic variables associated with recreationists. They were either used to construct attractiveness indices measuring the relative pulling power of recreation sites constraints on recreation travel. 2 or treated as spatial In many cases, distance measures between a recreation site and the location of customers are used to approximate the "prices" which are then employed to derive the basic demand curve for an outdoor recreation opportunity.^ In all these studies, locational factors are treated as demand factors and thus examined in the framework of consumer's choice or from the standpoint of the recreationist as a consumer. Methodologically there are two general approaches to spatial allocation of recreational participation or ^The investigator found, from a review of studies concerning location decisions and spatial analysis of outdoor recreation development, that only few studies on this aspect had been attempted before 1965. For further reference, see research reports and bulletins listed in the bibliography. 2 Carlton S. Van Doren, "Destination Models: Devel­ opment of a Camping Attraction Index for Michigan State Parks," in Department of Resource Development, Michigan State Univ., "Michigan Outdoor Recreation Demand Study," Technical Report Number 6, 1966, pp. 5.1-5.2, and 5.49-5.79. 3See, for example, Marion Clawson and Jack L. Knetsch, "Economics of Outdoor Recreation" (Baltimore: The Johns Hopkins Press, 1966), pp. 61-85. 22 demand. A The first approach usually assumes that the location points of population and recreation resources are fixed, as are the channels of transportation, and conceives of space as a friction to the flow of recreation travel. Analytic models which are often used in this approach are gravity models and systems theory models. 5 This approach is commonly undertaken in the studies which involve macrogeographic recreation planning and which have a common objective to estimate recreation travel flows in an origin-destination network system.® The second approach can be denoted as a somewhat typical locational analytic approach. It emphasizes the heterogeneity of the spatial system and assumes that recreational resources and population are not scattered 4 Simply speaking, participation, as applied to a specific area or facility, means the total number of visi­ tors, whereas demand, in a strict sense, means a schedule of quantity demand in relation to a price and other vari ables. 5 See, for a comparison, J. B. Ellis and C. S. Van Doren, "A Comparative Evaluation of Gravity and Systems Theory Models for Statewide Recreation Travel Flow,” Journal of Regional Science 6(2): 57-70, 1972. ®See, for example, Michael Chubb, "Outdoor Recre­ ation Planning in Michigan by a Systems Analysis Approach: Part III— The Practical Application of Program RECSYS and SYMAP," Resource Planning Series, Technical Report No. 12, Michigan Department of Commerce, 1967, 298 pp. Also see, M. E. Tadros and R. J. Kalter, "A Spatial Allocation Model for Projected Outdoor Recreation Demand: A Case Study of the Upstate New York Region,” SEARCH-AGRICULTURE, Vol. 1, No. 5, New York State College of Agriculture at Cornell University, Ithaca, New York, 1971, 22 pp. 23 evenly and continuously over geographic space. Under such assumptions, recreation locational analysts seek to explain why recreational facilities and areas are located at one place rather than another. From the same reasoning, they attempt to determine the best location for development of a particular recreation activity. Analytic techniques being used in this approach vary, depending upon the nature of the problem under study. However, there are basic 7 techniques such as comparative cost analysis, the economic? 8 9 rent approach, and various site evaluation techniques. in most cases, recreation researchers taking this approach tend to focus on the location problem at the individual firm level. Frequently they will base their analysis on some objective function which is to be optimized. The analysis of recreation location is a relatively new field of research. Theoretical foundation and analytic tools particularly designed for analyzing location prob­ lems of recreation development are still at a developmental 7 See, for example, Walter Isard, C. L. Choguill, J. Kissin, R. H. Seyfarth, and R. Tatlock, "Ecologiceconomic Analysis for Regional Development" (New York: The Free Press, 1972), 235 pp. Q See, for example, E. Boyd Wennergren and Herbert H. Fullerton, "Estimating Quality and Location Values of Recreation Resources," Journal of Leisure Research, 1972, 4(3): 170-183. g See, for a discussion on this topic, Keith McClellan and Elliott A. Medrich, "Outdoor Recreation: Economic Consideration for Optimal Site Selection and Development," Land Economics 45(2): 174-182. 24 stage. However, there are potential sources of theore­ tical framework and analytic tools that can be applied in this field of inquiry. One such source is the locational and regional economic theory which can provide a sound methodological basis for scientific inquiry into the recreational location problem.10 Additionally, the con­ ceptual frameworks and analytic techniques used by econ­ omic geographers in spatial analysis and description are also applicable to recreation location problems. Carto­ graphic techniques, for example, can be used to enhance visual examination of spatial pattern and facilitate development of explanatory hypothesis for statistical testing.11 Moreover, the statistical techniques commonly used in geographical research may help the recreation analyst understand the nature of spatial distribution and derive an inductive generalization concerning covariance between recreation development and other spatial character­ istics. ^ 10See, for a concise statement of general approaches to regional and locational analysis, Harry W. Richardson, "Regional Economics" (New York: Praeger Pub­ lishers, 1969), pp. 5-7. 11See, for example, Edwin N. Thomas, "Maps of Residuals from Regression," in Brian J. L. Barry and Duane F. Marble (eds.), "Spatial Analysis” {Englewood Cliffs, N.J.: Prentice-Hall, 1968), pp. 326-352. 12 See, for a more detailed discussion, Leslie J. King, "Statistical Analysis in Geography" (Englewood Cliffs, N.J.: Prentice-Hall, 1969), pp. 117-164. 25 Methods for Spatial Description Let us now focus on the specific techniques that are presently applied in the description of campground location patterns. The phrase "location pattern" as used in geographic literature is a concept consisting of loca­ tional arrangement and spatial distribution of various kinds. As King points out, there are two approaches often used by geographers to the definition of location pat­ terns. First, they treat locations as points on a map and analyze the distances separating them, the density of points, the distribution and arrangement of points, and the degree of correspondence between different point pat13 terns. This approach is often used by the geographer to describe and analyze locational data which involve spatial phenomena defined only at certain points on the earth's surface. The second approach treats a location pattern in terms of a set of areal units such as grid squares or county units. 14 This approach is appropriate for describing and analyzing areal data which consist of observations of spatially continuous phenomena. two approaches, Among the it appears that the first one is more suitable to the present study in which observations made at each private campground are locationally discrete in 13 Leslie J. King, "Statistical Analysis in Geog­ raphy" (Englewood Cliffs, N.J.: Prentice-Hall, Inc., 1969), p. 87. 14Ibid., p. 88. 26 nature. We treat private campground locations as points on a map, analyze the distances separating them, and assess their density. To describe and analyze campground location data, computer-mapping techniques were employed. The use of mapping techniques in this study can be justi­ fied by three essential reasons. First, maps of various kinds have been used to enhance visual understanding of physical and socio-economic characteristics on land. To use a map as a tool for descriptive statements about spatial distribution is a fundamental practice in geo­ graphic research, and in fact, has been proved u s e f u l . ^ Perhaps a map is one of the best descriptive tools to display and convey to others the end results of a study concerning spatially distributed phenomena. Second, it is possible to use a map as an analytic tool to enhance inquiry during the conduct of a study. Computer-prepared maps can be effectively used to develop, test, and evalu­ ate alternative hypotheses and assumptions during the course of research.16 This allows researchers to select a 15 Geographers have used maps for a long time to communicate and store their findings. They use maps to show vegetation distribution, topography, population density, social class distribution, land use activities, etc. 16 See, for a more detailed discussion. Laboratory for Computer Graphics, "A Report on the Feasibility of Using Mapping Techniques as an Aid in the Processing of Mortgage Insurance Applications, ** Graduate School of Design, Harvard University, Cambridge, M a ss., 1970, pp. 1-2. 27 better set of variables and improve the efficiency of inquiry. Finally, a computer-mapping system is currently available for use with easy access and relatively low cost. The computing system at Michigan State University is capable of processing most mapping jobs, usually with satisfactory results. Along with the hardware system, there are many well-documented computer-mapping packages. The GEOSYS, an information system for the description and analysis of spatial data, currently maintained by the Computer Institute for Social Science Research at the University, contains a set of computer routines which allows users to manipulate, describe, and analyze data defined in terms of spatial locations or geographic coordinates. 17 Users can select from the system one or more computer routines to generate maps and related sta­ tistical summaries so long as the locational coordinates are stored along with data values coded in machine read­ able form. There is considerable flexibility in most computer routines within the system to permit handling changes of size, content, and scale of the map as required by any study. With an aid from such a computer-mapping Robert I. Wittick, "GEOSYS: An Information Sys­ tem for the Description and Analysis of Spatial Data— Version 2," Technical Report Number 7 3-6, Computer Insti­ tute for Social Science Research, Michigan State University, 1973, p. 1. 28 system, the satisfactory maps can be produced with a reasonable cost. Methodologically, a complete process of mapping can be viewed as a series of transformations involving selection of data from the real world, transformation of these data into a graphic map, and the retrieval of information through an interpretative map reading process. X 8 This process is further illustrated by Muehrche schem­ atically as shown in Figure 2 below. Real data Raw world collection data mapping Graphic map Map reading retrieve Map Image Fig. 2.— The Mapping Process Conventionally when mapping the cartographer's task is to devise better approximations or transformation of raw data into a graphic map such that the map image can represent data input. 18 In a computer mapping system, the Phillip Muehrche, "Thematic Cartography," Commission on College Geography Research Paper No. 19 (Washington, D.C.: Association of American Geographers, 1972), pp. 3-4. 29 investigator and computer-mapping routines together take the place of cartographer, and perform the mapping job. Therefore, the researcher using a computer-mapping system must realize that selecting an appropriate mapping routine is as important as choosing a skillful cartographer. Moreover, he must also emphasize interdependencies between data collection, mapping, and the map reading process so that maps produced from the system can give accurate images as intended. Following the mapping process described above, the present study has created two types of maps for describing and analyzing private campground location patterns. The first type of map is generated by the program "SYMBOL" which is designed in such a way that a circle symbol is drawn at each interested point location on the Calcomp 19 plotter. This type of map shows the location and rela­ tive sizes of private campgrounds in Michigan and is expected to give an image of locational arrangement in a point pattern. The second type of map is created by the "SYMAP" package which is the best known and most widely used line-printer computer-mapping. 20 The "SYMAP" 19 This computer-mapping program was developed by Robert I. Wittick, Computer Institute for Social Science Research, Michigan State University. See Wittick, op. cit., pp. 41-42. 20 The name "SYMAP" is for SYnagraphic MAPping Program which was first developed in 1963 by Howard Fisher at Northwestern University. Fisher later established the Laboratory for Computer Graphics at Harvard University, 30 package offers three basic map outputs: contour map, con­ formant map, and proximal map. It contains some 35 options which allow users to change map size, data levels, external information to be printed on map, e tc., and up to 10 levels of shading can be provided by superimposing two or more characters. 21 But the maps created by the "SYMAP” package can only show overall patterns. cisely represent the actual data set. 22 They do not preIn addition, in this study, areal interpolation was made with respect to some selected county data which were treated as points geographically central to each of the counties under study. Therefore, we use "SYMAP" outputs mainly for the purpose of comparing overall spatial patterns and to facili­ tate development of hypotheses rather than to display actual data. In most cases, computer maps provide only an image of the overall pattern of spatially distributed phenomena. It is important that they are accompanied with statistical information that can provide a relatively precise statement where the latest revision of "SYMAP" was maintained and improved. 21C. Young, "SYMAP" Technical Report No. 100, Computer Institute for Social Science Research, Michigan State University, 1972, p. 3 and pp. 30-47. 22 "SYMAP" mapping is based on an artificial grid rather than the actual areal units. Grids are inter­ polated by a sophisticated algorithm contained in the package. 31 about the exhibited spatial pattern. Therefore, in this study, the investigator has selected two statistical tech­ niques to facilitate spatial description and analysis. First, an attempt is made, using a statistical analysis technique known as "Near-neighbor Analysis," to describe and analyze distribution patterns of private campgrounds in Michigan. Focusing upon distance measures between each point and its nearest neighbor, the near-neighbor analysis indicates the degree to which any observed distribution of points deviates from what might be expected if the points were distributed in a random manner within the same area. 23 In practice, a ratio known as "nearest-neighbor statistic" is computed such that: R = rA/rE, where R is the nearest neighbor statistic, rA is the observed mean distance, and 24 rE is the expected mean distance. The ratio, R, provides a measure of the departure from randomness. It has a range in value from zero to 2.15 and is interpreted as follows: 23 The near-neighbor analysis was originally developed by plant ecologists who were concerned with the distribution patterns of species over the surface of the earth. See P. J. Clark and F. C. Evans, "Distance to Nearest Neighbor as Measure of Spatial Relationships in Population," Ecology 35(1954): 445-453. 24 By assuming that the n points in an area are distributed randomly in accordance with a Poisson Proba­ bility function with density X, and the distribution of distance between points and their nearest neighbors is , normal, the expected mean distance can be equal to 1/2X . See Ibid., pp. 451-452. 32 Magnitude of R R < 1 R = 1 R > 1 Nature of pattern clustered random uniform The Analysis Method Multiple regression analysis was selected to analyze campground distribution and locational decision factors in this study. The basic purpose of using this method is to help "explain” the variance of campground distribution and occupancy as response variables. It does this, in part, by estimating the contributions to this variance of two or more spatial characteristics as inde­ pendent variables. There are two major reasons that support the selection of multiple regression analysis for the present study. First, multiple regression analysis is appropriate for this study because it is capable of analyzing both the collective and separate contributions of two or more inde­ pendent variables to the variation of a dependent variable. As long as we accept the assumptions of the method, we can rely on the analysis method to estimate overall effects as well as individual relationships, and to test them within the same analytical framework. As such, the multiple regression analysis may generate satisfactory results con­ sistent with the objective. Secondly, since the computer technology of both software and hardware has been highly sophisticated, the computational aspect of regression 33 analysis is no longer a difficult problem. Many well- designed computer programs for regression analysis effi­ ciently provide options for researchers to experiment with a wide variety of problem conditions without making the use of them overly difficult or complicated. For example, the SPSS multiple regression program currently operating on the CDC 6500 computing system at Michigan State Univer­ sity combines standard multiple regression and stepwise regression in a manner which provide both considerable control over the inclusion of independent variables in the equation and sufficient flexibility for the researchers to 25 experiment with different options. Regression equations can take several different forms of which the linear type is most often used. As used here, the linear multiple regression model is most suitable for developing a working hypothesis and preliminary investigating relationships between variables simply because it is simple and easy to interpret. The basic form of a multiple linear regression equation can be expressed as follows: 3 Z b-X i=1 i 13 + U. 3 j * 1, 2, ........... . Y. = a + N 25 See, for a detailed discussion of the program, Norman Nie, Dale H. Bent, and C. Hadlai Hull, "SPSS— Statistical Package for Social Science" (New York: McGrawHill Book Co., 1970), pp. 174-195; and also, Computer Laboratory, Michigan State University, "SPSS— 6000: Revision Package, 5.5 Version" (based on SPSS 1973 Version, Northwestern University), pp. 184.1-188.2. 34 where Y^ is the dependent variable; a is the intercept of Y axis (or the constant); b^'s are the partial regression coefficients for k independent variables; IK is the error term associated with the dependent variable; and N is the number of observations. There are three main types of regression models which are often used by researchers, the functional model, the control model, and the predictive model. 26 The functional model is considered for a problem situation where the true functional relationship between a dependent and the independent variables is known, whereas the con­ trol model is a functional model which contains variables under the control of the researcher. The predictive model is often obtained in a problem situation where the func­ tional relationship is unknown or uncertain and the ability to obtain independent estimates of the effects of the con­ trol variables is limited. In their book. Draper and Smith describe the usefulness of the predictive model as follows: The predictive models are very useful and under certain conditions can lead to real insight into the process or problem. It is in the construction of this type of predictive model that multiple regression techniques have their greatest contribution to make. These problems are usually referred to as "problem with messy data"— that is, data in which much inter­ correlation exists. The predictive model is not neces­ sarily functional and need not be useful for control 26 See, for a discussion, N. R. Draper and H. Smith, "Applied Regression Analysis" (New York: John Wiley & Sons, Inc., 1966), pp. 234-236. 35 purposes. This, of course, does not make it useless, contrary to the opinion of some scientists. If nothing else, it can and does provide guidelines for further experimentation, it pinpoints important vari­ ables, and it is a very useful variable screening device.27 Comparing the problem situation presently under investi­ gation, it is apparent that the regression model developed within the present study is a predictive model in nature. Within the framework of the predictive model, an attempt is made mainly to explain in a statistical way relation­ ships that may exist between selected dependent variables and the independent variables. The model is not neces­ sarily functional and may not be useful for control pur­ poses . To construct a regression model for prediction purposes often involves several phases. Draper and Smith suggest that three major phases— planning, development, and maintenance must be considered. 28 They emphasize in the planning phase that a regression analyst must care­ fully define the problem, select among all conceivable variables the appropriate set of dependent and independent variables, and establish goals for the analysis. In the development phase, they focus on the statistical skills that are required to estimate the parameters, to examine the residuals, and to select the regression equations. 27 Draper and Smith, Ibid., p. 2 35. 28 Draper and Smith, Ibid., pp. 236-241. And 36 finally, the fitted regression model must be verified for the stability of its coefficients and the practical mean­ ingfulness and usefulness. The entire model building process, as it has been applied here, is illustrated in Figure 3 on page 37. Note that the process begins with definition of the problem and development of hypotheses. Simply put, the specific hypotheses under investigation in this study were that the campground location decisions can be substantially explained by the selected location characteristics. These hypotheses were developed both from the conceptual framework described earlier and from the existing body of knowledge concerning spatial phenomena of outdoor recreation development. Once hypotheses were developed they were then expressed as dependent and inde­ pendent variables for empirical analysis. This part of study will be discussed in Chapters IV and V. Once variables were properly specified, the investigator then determined data sources and selected appropriate methods for data collection. Since data were collected from mail-questionnaire survey, some of them were inconsistent and required careful examination. Usable data were then processed into machine readable form for computer calculation. After carefully examining the data, the investi­ gator moved on to conduct an initial regression calcula­ tion. The correlation matrix and other essential 37 Developing work­ ing hypotheses and specifying variables Gathering data for initial regression run and analyzing preliminary results Stating goals: standard error, and significance level ^ --------- ^ < --------- < --------- Constructing new variables and/or improv­ ing specifica­ tion of rela­ tionships Feedback Formulating a new regression model and evaluating the model for better result No Yes \/ Analyzing and interpret ing the results Feedback Fig. 3.— A Flow Diagram Indicating Regression Model Build­ ing Process Used in this Study. 38 statistics of such a regression run was examined. This provided further insight into analytical problems and could conceivably eliminate many independent variables from additional analysis. A new regression equation was then formulated and final evaluation began. At this stage of investigation, the stepwise regression procedure was used to help select the "best" regression equation. This regression procedure involves re-examination of the vari­ ables already in the equation at every step of the regression when a new variable is included. 29 The stepwise regression method is a useful variable selection procedure, but it must be used with sufficient statistical knowledge and good subjective judgement. In many cases, it is desirable to consult experts for advice. During the evaluation stage, the regression equation was continuously examined and modified until it has reached a satisfactory result. To be satisfactory, a regression equation must not only confirm the basic assumptions'*® but 29 See, for a detailed discussion, Draper and Smith, Ibid., pp. 171-172. 3®In order that the least-square estimates are unbiased, a regression equation must confirm or, at least, not exhibit a denial of the basic assumptions that, in the model: Y^ = a + bjX j + e j , (1) e. is a random variable with zero mean and constant variance, and (2) e. and e. are 3 K uncorrelated, j / k. The consistency of a regression equation with these assumptions may be examined by plotting and analyzing the residuals e.. See, for a detailed dis­ cussion on this aspect. Draper and Smith, Ibid., pp. 17-35 and pp. 86-95. 39 also meet the pre-stated goal with respect to the level of statistical significance error of estimate- (a) and the allowable standard The statistically satisfied regression equation must then be examined for stability of the regression coefficients and consistency in the practical senses. In this study, however, we can only examine the practical sense of the model. Stability of the regression coefficients cannot be verified now because we lack timeseries data. The computational method used here to select the "best" regression equation is the stepwise regression pro­ cedure. The method recursively constructs a regression equation one independent variable at a time in a step-bystep fashion. The first step is to choose the single independent variable which has the highest simple corre­ lation with the dependent variable. This is followed by adding the second independent variable to the regression equation. The order in which the independent variables are added to the equation is controlled by two pieces of information. The first is the F statistic which measures the significance of the regression coefficients. If the value of the F statistic for a regression coefficient is too small, then there is little reason to bring that vari­ able into the equation. The second piece of information 40 is the value known as the tolerance. 31 The stepwise regression procedure never adds an independent variable to the equation if the value of the tolerance is too small. Based upon these two pieces of information, the stepwise regression proceeds in a recursive fashion until no other variable will make a significant contribution to the improvement of the regression equation. The stepwise regression is considered by many researchers the most powerful technique for selecting final regression equation. 32 As the authors of the SPSS manual point out, "this procedure does not always yield the true optimum, but it usually does fairly well."33 Data Sources for the Study Data used in this study were of two major types, primary and secondary data. Primary data were obtained directly from a mail-questionnaire survey of private camp­ ground operators in Michigan. Secondary data were obtained 31 The tolerance is an index computed at each step during stepwise regression. It is used here to check singularity of the covariance matrix at each step. If the tolerance is too small, this indicates that the covariance matrix is nearly singular and the regression program would have a difficulty inverting it. Consequently, stepwise regression never brings a variable into the equation if the tolerance is too small than a specified level. 3 2The stepwise regression is not as good as com­ paring all possible regression equations in k variables. However, it is much less expensive. 33 Nie, Bent, and Hull, op. cit., p. 180. 41 from a variety of sources including various publications of campground and trailer park directories, published and unpublished governmental statistical data records, and census publications. Each of the data sources will be discussed in more detail in the following sections. Primary Data Sources As noted above, primary data were obtained from a mail survey of private campground operators in Michigan. The definition of a private campground used in this study is essentially that of Michigan Public Act 171, 1970. The act implies that a private campground means a parcel or tract of land which is under control of a private person or persons and upon which campground facilities are estab34 lished for public camping services. The services mentioned are offered primarily for the campers whose equipment consists of tent, travel trailer, camping trailer, motor home, or truck camper. The source listing of private campgrounds in Michigan was compiled primarily from the Campground License Records of 197 3, maintained by the Michigan Department of Public Health. 35 In addition, data were ^ S e e Michigan Act 171 of the Public Acts of 1970, Section 1(a) and 1(f). 35Michigan Public Act 171, 1970 requires all per­ sons planning to operate a campground in Michigan must obtain an annual campground license from the Michigan Department of Public Health. The license records provided 42 also obtained from various publications of commercial camp­ ground and trailer park directories. These include: {1) Campground and Trailer Park G u i d e , Hand McNally & Company, 1973. (2) Outdoor Guide, Automobile Club of Michigan, 1973. (3) Campground Directory of Michigan Association of Private Campground Owners, 1973. After a careful check on the consistency and accuracy of the names and addresses from various sources, a final listing of 530 private campgrounds was obtained. 3 6 Questionnaires (see Appendix I) were then sent to camp­ ground operators in an effort to obtain a complete survey of all private campgrounds which have ten or more campsites. 37 As indicated in Table 1 on page 43, 29 3 complete responses were received from the 530 private campgrounds the best listing of private campgrounds for this survey research. 3 6Campgrounds which have fewer than 10 campsites were excluded from the survey. This exclusion was based on the assumption that campgrounds smaller than this limit may not be operated with economic motivations. 37 The complete mail survey is selected for three essential reasons. First, with a population of 530 sample units, the census mail survey seems to cost less than any other survey methods, particularly the personal interview survey. Under the financial constraint, it was considered most appropriate survey method. The sample mail survey costs much less but it involves sampling error. Second, this survey is a survey of the facts rather than of an opinion. Hence, the bias toward high responses from those who strongly favor the subject of the survey may not exist. Third, certain techniques may be used to encourage response if non-response imposes a serious problem. Table 1.— Summary of Survey Responses* n Responses Initial Mailing ^ ----- % Complete response 123 23.2 101 25.8 69 24.3 293 55.3 15 2.8 8 2.0 6 2.2 29 5.4 Total response 138 26.0 109 27.8 75 26.5 322 60.7 Total non­ response 392 74.0 283 72.2 208 73.5 208 39.3 Total mailings 530 100.0 392 100.0 283 100.0 530 100.0 Incomplete response First* Follow-up No. * Second* Follow-up No. *4 _ , , .. 0 a No- *The first follow-up questionnaires were sent to the non-respondents 20 days after the initial mailing, and the second follow-ups were sent 28 days after the first follow-up mailing. 44 surveyed, a 55 percent of response. This response rate is considered adequate for analysis and reporting. 38 More­ over, it is also important to recognize that the complete responses are fairly well representative of the total population in terms of regional distribution, campground types, and size classes. This is indicated in Table 2 in which the frequency distributions of the complete responses and the total campgrounds surveyed are compared. Table 2.— Distribution of Complete Responses and All Campgrounds Surveyed. Distribution Complete Response NO. % All Campground Surveyed NO. % By Region: Region 1 37 12.6 65 12.3 Region 2 117 39.9 202 38.1 Region 3 139 47.4 263 49.6 By Campground Type: Seasonal Campground 197 67.2 390 73.6 Year-round Campground 96 32.8 140 26.4 293 100.0 530 100.0 State Total 38 According to Babbie, "a response rate of at least 50 percent is adequate for analysis and reporting. A response rate of at least 60 percent is good. And a response rate of 70 percent is very good." This suggestion is, of course, based on his personal judgement rather than any particular statistical principle. See Earl R. Babbie, 45 In Table 3 (see page 46) it can be seen that the percentage distribution of complete responses among size classes is fairly close to that of the total campgrounds surveyed. This could mean that the survey has received complete responses which can reasonably represent each of the size classes. However, it should also be admitted that the relatively high average of campsites in the non­ response group may indicate that we could have left out some large campgrounds. 39 Data originally proposed to be obtained from the survey were included in four major categories. They are: (1) general characteristics of campground operation, (2) locational characteristics, (3) spatial relationships, and The responses to the first (4) financial information. three categories are fairly complete, and perhaps more consistent as compared to data in other similar surveys. 40 The last category was poorly responded to because most private campground operators are reluctant to disclose their financial data. For the same reason, even those "Survey Research Methods" (Belmont, Calif.: Wadsworth Publishing Co., Inc., 1973), p. 165. 39 We were able to check the size distribution of non-respondents from other data sources such as Camp­ ground License Records and Campground Directories. 40 Two similar surveys of private campgrounds were conducted in 1972, one was conducted by Roger D. Murray, and the other was by Eugene F. Dice, both of the Depart­ ment of Park and Recreation Resources, Michigan State University, East Lansing, Michigan. 46 Table 3.— Distribution of Complete Responses Among Different Size Classes. s* Complete Response No. % All NonResponse No. % All Campground Surveyed No. % 10 - 30 108 36. 9 72 34.6 201 37. 9 31 - 60 85 29.0 55 26.4 145 27. 4 61 - 90 40 13.6 25 12.0 68 12. 8 91 - 120 38 13. 0 31 14. 9 69 13. 0 121 - 150 8 2.7 12 5.8 20 3.8 151 - 180 6 2.0 5 2.4 11 2.1 181 - 210 0 .0 2 1.0 2 .4 211 - up 8 2.7 6 2.9 14 2.6 208 100. 0 Total Average CS per CGc 293 99. 9a 60. 63 67. 25 530b 100. 0 61.72 aBecause of rounding error, the total percentage is not exactly equal to 100. bThe siom of the numbers of complete responses and the non-responses is less than the number of total camp­ grounds surveyed because 29 incomplete responses are not included for tabulation. °Average CS per CG = average numbers of campsites per campground in each category. 47 cases of response, one must be suspicious that answers may not be accurate enough for analysis and reporting. Consequently this category was dropped from the analysis. Data obtained in this survey were used primarily in the analysis of relationships between campground business performances and the locational factors that might affect them. They were processed into a form appropriate for regression analysis. Procedures and results of the analysis are discussed in Chapter V where the campground location-performance relationships are dis­ cussed. Secondary Data Sources In addition to obtaining data from the mail survey, this study also required data from various secondary sources. The most important sources were, of course, various commercial campground and trailer park directories. Most directories currently available provide information concerning location, size, operational season, and physical facilities of the campgrounds for a given year. Once the problems of incompleteness and occasional errors are solved, the directories can together provide reliable data for spatial description and analysis. A second source was the information brochures pub­ lished by the individual campgrounds. Although these brochures often provide information similar to that indi­ cated in the commercial campground directories, they 48 usually describe in great detail the exact location of the campground. The brief road map printed on the brochure was extremely helpful to the investigator in determining the campground location coordinates necessary for computer mapping. Besides, the information brochures can provide a basis for checking on consistency and accuracy of the campground information obtained from various sources. The third source was census publications which included the 1970 Census of Population and the 1969 Census of Agriculture. They provided part of the county data needed to analyze spatial patterns of private campground development. In some cases, census data were used directly in the analysis. In other situations, they required pro­ cessing to generate a specific value for a variable included for the study. In addition to census publications, county data required for analysis of location patterns were also drawn from various published and unpublished governmental reports and statistical records which were relevant to this study. A complete listing of data obtained from these sources may be found in Appendix IV. As noted above, data used in the analysis of camp­ ground location patterns were obtained mostly from a variety of secondary sources. This made it very difficult to examine the nature of the errors that might exist in the data, and thus impossible to determine the accuracy of 49 the analytical results. However, like most studies using secondary data, one must believe that the data employed are reasonably accurate, and thus assume that variation in the response variable is a reflection of the actual variations in the specified set of the input variables and not due to the measurement and observation errors of the data. CHAPTER III PRIVATE CAMPGROUND DEVELOPMENT IN MICHIGAN The foregoing serves to define the research prob­ lem and provides a discussion of the research methods and data sources used in the present study. Let us now des­ cribe some general characteristics and spatial patterns of private campground development in Michigan. In doing so, we have used computer mapping and statistical techniques along with descriptive analysis to provide an overview of private campground development in Michigan. The effort made in this chapter should provide a better understanding of the rigorous statistical analysis in the following chapter. Growth in Campground Industry The development of private campgrounds for com­ mercial purposes has a long history. According to the survey, the oldest private campgrounds provided for com­ mercial purposes were established during the 1930s. But large-scale developments in the campground industry are a relatively recent phenomenon. In particular, during last 50 51 decade, campground enterprises in Michigan were growing both in size and scale. For example, as shown in Table 4 below, about 50 percent of private campgrounds in Michigan were established or licensed in 1970 and after, which is approximately two times larger than those established or licensed in 1964 and before. The growth of the private campground industry may be characterized by a certain pattern in various stages of development. As observed by Bevins, like many other industries, the private campground enterprises will pass through at least three stages of growth enroute to maturity. Bevins explained the three stages as follows: Table 4.---Growth in cl^Private Campground Industry in Michigan. Time Period By Campground No. % By Campsite No. % Avg. Sites per Camp. 1964 and before 103 19.4 4666 14. 3 45.3 1965-69 159 30. 0 10255 31.4 64. 5 1970-73 268 50. 6 17768 54. 3 66. 3 Total*5 530 100. 0 32689 100. 0 61.7 a This table was compiled from the following data sources: (1) private campground license records, Michigan Department of Public Health, 1973; (2) campground and trailer park guide, Rand McNally & Co., 1966 and 1973; and (3) private campground mail survey of the present study. ^Campgrounds which consist of 10 or less campsites were not included in the tabulation. 52 . . . The first stage is development characterized by rapid growth, wide experimentation and considerable amount of trial and error. This happens in all industries. During this period we have general inef­ ficiency. I think the campground industry has passed through this stage. This was the decade of the 60s. Now, in 1972, the campground industry has pretty much moved into developmental stage two. Still grow­ ing fast. However, we now see greater enterprise refinement and differentiation of product. Innova­ tions are taking place. Campground managers are developing new techniques. Sure it's competition An eye to the future sheds some light on what's ahead in the developmental stage three, which as some people see it will come about eight years from now, somewhere around 1980. Rapid growth will be over, individual enterprises will be large, capital require­ ments are going to be extensive. The small, inef­ ficient operators will have been left by the wayside. Those remaining are going to be highly-skilled people . . . .* The implication of this observation is important. As it is in the second developmental stage, the private camp­ ground industry in Michigan will face a great challenge of business innovation and more competition. Some painful shifting will take place; there will be numbers of owner­ ship changes or even some going out of business. But there also will continue to be new entrants into the business. It can be expected that these new entrants will be well-organized and develop relatively large-scale operations. In contrast to previous investors, they are also expected to seriously consider their campground Malcolm I. Bevins, "Focusing on the Future," in Eugene F. Dice (ed.), "The Private Campground Business; A Forward Focus," Proceedings of the Michigan Campground Business Seminar at Michigan State University, East Lansing, MI, 1972, p. 13. 53 location choice. During early stages of campground devel­ opment, many campground enterprises joined the business without taking a critical step to rationalize their location choice. They either developed their campgrounds on marginal land or retired farmland which had few uses. Types of Campground Operation Private campgrounds in Michigan come in a variety of types, depending upon: (1) the function they serve; (2) the facilities they provide; or (3) the length of operating season. As Dice suggests, private campgrounds in Michigan may be grouped into three types according to the function they serve. They include: (1) overnight campgrounds— those which are mostly for a night's rest or short stays by campers; (2) destination campgrounds— those which function as away-from-home vacation headquarters and provide the family or group campers with opportunities for a variety of experiences; and (3) semi-summer-residence campgrounds— those which function as temporary residential units and offer services, mostly on seasonal basis, for 2 those who commute back and forth to work. This classifi­ cation is conceptually sound and provides a better under­ standing of the campground functions, but it is not 2 Eugene F. Dice, T. W. Chiang, and Timothy Smythe, "An Introductory Study on Privately Operated Campgrounds in Michigan," Natural Resources Series Ext. Bui. E-717, Coop. Ext. Service, Michigan State University, East Lansing, MI, 1971, pp. 3-4. 54 operational for data collection or grouping purposes. In actuality, the campground types are not as clear-cut as this classification indicates, even though we realize that there exist different campground functions. In fact, a campground may serve both overnight and destination campers, and this causes a difficulty to group the camp­ grounds by functions. Campgrounds may be also classified into two basic facility types, primitive campgrounds and modern camp­ grounds. Generally speaking, a modern campground is one which offers electricity, water under pressure, and sewage disposal systems, whereas primitive campgrounds only pro­ vide the basic hand pump water supply and pit toilet facilities. According to this definition, most private campgrounds would be classified as modern campgrounds. 3 They tend to focus on providing improved facilities and sophisticated indoor and outdoor recreation activities at the campground. This trend toward more modern facilities may be encouraged by the fact that people have increasingly used campgrounds as substitutes for motel facilities. The better facilities would make a campground more like a motel and thus attractive to more campers. 3 To say a campground is modern only implies that the majority of the campsites on the campground are modern campsites. Many campgrounds which are considered to be modern campgrounds do provide certain primitive campsites along with the modern ones. 55 Private campgrounds may also be distinguished from each other by the nature of seasonal operation. Some pri­ vate campgrounds are referred to as seasonal campgrounds if they only operated in a particular season of the year. Others are considered year-around campgrounds since they operate throughout the entire year. According to camp­ ground directories and license records, the majority of private campgrounds in Michigan are operated on a seasonal basis. One reason for this may be that camping is a seasonal activity which usually takes place during the warm months (i.e., June, July, and August) in Michigan. Campground Distribution There were 97 5 campgrounds which provided a total of 62,761 campsites in Michigan in 1973. Among the total number of campsites, 52 percent were provided by the pri­ vate sector. As we shall see in the following discussion, the private campgrounds in Michigan are not distributed the same as those publicly owned. A sharp distinction between them is that publicly owned campgrounds tend to concentrate in northern regions of the state, whereas privately operated campgrounds are more clustered in southern Michigan where population is highly concentrated. Table 5 on pages 56 and 57 shows the distribution of pri­ vate and public campgrounds by regions in the state. As indicated in the table, about 90 percent of total private campsites were located in Region 2 (northern Lower Table 5.— Regional Distribution of Campgrounds in Michigan.3 Region Region 1 Private Campground No. CG b No . CS1 70 per CG Region 2 208 12593 85 60.5 274 17527 % Distrib. 53.4% (65.2%) AVG per CG 64.0 108 58 11972 1989 All Campground No. CG No. CS 227 19.7 116 2430 47.2% (44.4%) 53.5% (9,0%) 140.9 20.9 9229 121 36.4% (34.3%) 2.7% (0.5%) 159.1 17.3 8883 14.2% (100.0%) 43.8% (22.4%) 132.1 38.3% (46.6%) AVG per CG 4161 16.4% (46.8%) 39.1 % Distrib. Region 3 49 8.3% (30.8%) % Distrib. AVG 2733 Public Campground Park CGc Forest CGc No. CG No. CS NO. CG No. CS 64.4 409 27001 43.0% (100.0%) 66.0 339 26877 42.8% (100.0%) 79.3 u» c\ Table 5.— Continued. Private Campground No. CG& No. CSb Region 552 All State 32853 % Distrib, 100.0% (52.4%) AVG per CG 59.5 Public Campground Park CG Forest CGc No. CG No. CS No. CG No. CS 192 25362 100.0% (40.4%) 132.1 231 4546 All Campground No. CG No. CS 975 62761 100.0% (7.2%) 100.0% (100.0% 19.7 64.0 Sources of Data: (1) 1973 Campground License Records, Michigan Department of Public Health, September, 1973. (2) Michigan Outdoor Guide, Automobile Club of Michigan, 1973. (3) 1973 Campground Directory, Michigan Association of Private Campground Owners. (4) Campground and Trailer Park Guide, Rand McNally & Co., 1973. aThe information indicated in this table was summarized from Appendix II which contains a table showing the distribution of private and public campground facilities by counties with regional and state totals. See Appendix II for county statistics. L CG = campground CS = campsite AVG = average number of campsites cPark campground category includes those campgrounds which are operated by state, county, township, or municipal authority and are located in a park. Forest campground category includes both state and national forest campgrounds. The percentage figures in the parentheses are computed on the basis of row totals. 58 Peninsula) and Region 3 (southern Lower Peninsula), and only less than 10 percent were in Region 1 (the entire Upper Peninsula). Public campgrounds, on the contrary, were located more in Regions 1 and 2 where woods, waters, and natural scenery are more attractive to a great many people. Region 2 is unique. It has both public and pri­ vate campgrounds in an even distribution. Perhaps this can be explained by the fact that Region 2 is not only unique in its natural setting but also reasonably acces­ sible to large population concentrations in the state. Regional Characteristics Campground development in Michigan is characterized by its regional differences. In this section, we are to discuss these differences on the basis of campground size, seasonal operation, and selected spatial relationships. The number of campsites on a campground can be used as an indicator of its scale of business operation. Different scales of operation usually require different locations with access to markets of various sizes. In Michigan, large market areas are located in the southern region where population is concentrated. Hence, it is expected that campgrounds in this region will be large in size as compared to other regions. From an examination of survey data, we have found some truth to this argument. As noted in Table 5 on pages 56 and 57, and Figure 4 (see page 59) Region 1 which is far removed from the major 59 Fig. 4.— The Distributions of Private Campgrounds and Major Municipalities in Michigan. This map was drawn by the computer mapping routine, "SYMBOL," and includes 5 30 private campgrounds and 130 major municipalities with population 5,000 or more. 60 population centers in the state does have the smallest average campground size among all regions. In contrast, Region 3, which is close to large population concentra­ tions, has the largest average campground size, compared to all other regions. The regional differences in private campground distribution can also be examined in terms of some important statistical measures associated with campgrounds. An inspection of Table 6 on pages 61 and 62 reveals that seasonal campgrounds tend to concentrate in Region 3, whereas year-around campgrounds are more heavily repre­ sented in Region 2. The reason for this may be that Region 2 has more winter recreation resources and sport activities such as snow-skiing and deer hunting which attract a great many of visitors. But for the level of facility improvement, Region 3 seems to have a slightly higher percentage of modern campsites on each campground than any other region. Moreover, from Table 6 we can see that the average increase in the number of campsites is also higher in Region 3, and this indicates that private campground development has grown faster in Region 3 during past years. Now let us take a look at some distance measures which are often used to express spatial relationships. The average distance from a private campground to its nearest private neighbor is 6.7 miles for the state, but Table 6.— Regional Characteristics of Private Campground Distribution. Items 1. Total number of campground Region 1 65 Region 2 202 Region 3 263 All Stati 530 2. Percent of seasonal camp­ ground 12.5% (49)a 33.1% (129) 54.4% (212) 100.0% (390) 3. Percent of year-round campground 11.5% (16) 50.9% (73) 36.6% (51) 100.0% (140) 4. Average percent of modern campsites per campground 62.1% (37) 70.6% (117) 74.1% (139) 68.9% (293) 5. Average number of campsiteg differed since established*1 8.4(sites) (37) 9.3 (117) 15.8 (139) 11.2 (293) 6. Average number years a campground has been in 6.9(years) (37) 6.6 (117) 8.3 (139) 7.4 (293) 7. Average distance to nearest private campground 8.2(miles) (37) 7.0 (117) 5.6 (138) 6.7 (292)d 8. Average distance to nearest public campground0 12.9(miles) (36) 9.4 (114) 16.0 (129) 12.8 (282)d 9. Average distance to nearest national lake 1. 4 (miles) (36) 2.2 (114) 1.9 (134) 1.9 (284) operation Table 6.— Continued. Items 10. Average distance to nearest primary highway0 Region 1 Region 2 Region 3 All State 2.7(miles) (37) 4.8 (117) 3.2 (139) 3.7 (293) Sources: (1) Data sources for item 1, 2, and 3 are as follows: (a) Private Campground License Records, Michigan Department of Public Health, 1973; (b) Campground and Trailer Park Guide, Rand McNally & Co., 1966 and 1973; Campgrounds with less than 10 campsites are not included in this Table. (2) Data for item 4 through 10 are obtained from the mail survey of private campgrounds particularly designed for this study. aThe figures in the parentheses are the number of valid observations used to compute the statistic. bThese numbers were computed by taking an average for all campgrounds in a region the differences between the number of campsites initially established and that available in 1972. CThe distances were measured in the actual mileage as reported by respondents. ^Some respondents did not completely report the information and thus, were not taken into computation. 63 only 5.6 miles for Region 3 which is the shortest among all regions. Average distance from a private campground to its public neighbor is generally higher as compared to that to the private neighbor. The shortest distance on average between private and public campgrounds is in Region 2 where a relatively large number of public camp­ grounds are evenly distributed. Data also reveal that Region 1 has the shortest average distance measuring from a private campground to its nearest natural lake or pri­ mary highway. One possible explanation for this may lie in the fact that since Region 1, the Upper Peninsula, is located remote from major population centers, private campgrounds in this region must be located close to major highways to catch more overnight camj ars or near a scenic lake area to attract more destination customers. Spatial Patterns of Camp­ ground Development This section consists of a description of spatial patterns of private campground development, using computer maps. In this part of the analysis, campgrounds were treated as points on a map, and distances separating them were measured and analyzed. Two techniques commonly used by geographic researchers were used here, and the results are discussed in the following paragraphs. First, the computer program, "LOCATE," was employed to establish a system of zones around a selected base 64 point and to count the number and the percentage of campsites falling in each zone. 4 From this, we are able to describe the campground distribution pattern in terms of spatial diffusion about an origin. The base point chosen here to determine the zones and the values is the populationweighted geographic mean center of the Detroit Metropolitan Area, which is approximately located at the center of the Highland Park City.5 The computational results are pre­ sented in Table 7 on page 6 5 and Figure 5 on page 66. It is interesting to note from Table 7 that three-fourths of the total private campsites are located within 196 miles straight-line distance from the Detroit Metropolitan Area, an area which includes about 40 percent of the state total population. If the driving speed is constant at 55 miles per hour, this can be interpreted to mean that the majority 4 The computer program, "LOCATE," was originally developed by D. F. Marble, Department of Geography, North­ western University. For further reference, see R. I. Wittick, "GEOSYS"— An Information System for the Descrip­ tion and Analysis of Spatial Data, Version 2," Technical Report No. 73-6, Computer Institute for Social Science Research, Michigan State University, East Lansing, Michigan, 1973, pp. 16-17. 5The basis point was determined by the computer program, "CENTRO," with inputs of Cartesian coordinates and population data of 42 municipalities in Detroit Metropolitan Area. For further reference on this computer program, see R. I. Wittick, Ibid., pp. 18-20. 65 Table 7.— Diffusion of Private Campground Development. Zone Number Distance from basis point9 1 2 8 (miles) 2 Number of campsites % campsites of total Cumulative percentage 195 .60 .60 56 3565 10. 96 11.56 3 84 3879 11. 93 23.49 4 112 2171 6. 68 30.17 5 140 4630 14. 24 44.41 6 168 5997 18.44 62. 85 7 196 3910 12.02 74. 87 8 224 3054 9. 36 84.26 9 252 2287 7. 03 91.29 280 & up 2834 8.71 100.00 10 Data Sources: (1) 1973 Campground License Records, Michigan Department of Public Health, September, 197 3. (2) Michigan Outdoor Guide, Automobile Club of Michigan, 1973. (3) 1973 Campground Directory, Michigan Association of Private Campground Owners. (4) Campground and Trailer Park Guide, Rand McNally & C o . , 1973. aThe distances are measured in straight-line dis­ tance in miles from the basis point (BP) to the outer boundary of each zone. ^The small campgrounds with less than 10 campsites are not taken into consideration. 66 Mil I WCI rr !#t**ClAM alii r- L ^ _ NAlMMI Fig. *M MAM P«A|«T( 5.— Diffusion of Private Campground Development. The d i f ­ fusion of private campground development from the Detroit Metropolitan Area considered as base point. The m a p is based on the information presented in Table 7. 67 of Michigan private campsites are within the reach of 3.5 hours or less driving from the major population centers.6 In Table 7 (see page 65), it can also be observed that there is an intensive campground development in zone 2 which immediately surrounds the Detroit Metropolitan Area. This zone is attractive to private campground developers not only because it is located at the door of a large market area but also because it abounds in high quality recreational water resources. This zone consists of a large portion of Oakland and Livingston counties. In contrast to zone 2, zone 4 has only few private campground developments, even though it is located less than two hour driving distance from Detroit. This can probably be explained by the fact that this zone is characteristic of productive farm land rather than recreational resources. In this particular case, agricultural production may com­ pete favorably with campground development for the use of land resources. The location pattern of private campground develop­ ment may change over time. In order to examine such a change, a series of maps showing locations and sizes of private campgrounds were constructed. These maps were drawn by the computer mapping program, "SYMBOL," with inputs of data point values and Cartesian coordinate data 6Since straight-line distance was used to deter­ mine zone boundaries, this calculation may underestimate actual driving time. 68 provided by the investigator. 7 Coordinate data for the state outline and the campground location points were obtained by reference to a series of county general highway p maps overlaid with transparent grid paper. The scale of the base maps is at 1" = 2 . 8 miles, and the minimum grid size is one-tenth of an inch. The point symbolic maps developed here can facili­ tate a visual understanding of private campground location patterns. In a more direct way these maps provide a clear statement of the distribution of private campground devel­ opment at a given time so that a map at one time can be compared to a map at another time. This is illustrated in Figure 6 (see page 69), Figure 7 (see page 70), and Figure 8 (see page 71); each represents a location pattern at a given time period. As noted on the maps, the specific years presently considered for comparison purposes are 1964, 1969, and Q 1973. The distribution pattern for 1964, as it is shown 7Robert I. Wittick, Ibid., pp. 41-42. Q The whole set of the base maps was made available by courtesy of the Michigan Department of State Highways. g To select these years for comparison is somewhat arbitrary. However, like many other economic activities, growth of the private campground business has been gradual. The determination of observation years may be justified by reference to stages of business growth. In the early sixties and before, private campground development was characterized by wide experimentation, a series of trials and errors, and small scale of operation. It was made mainly by the private sector with very little assistance 69 MICHIGRN PRIVATE CAMPGROUND LOCATION PATTERN 1964 PRIVATE CAMPGROUNDS ESTABuSHEO DR LICENSED IN AND BEFORE 1964 :* or *<« (. , SO l- M O o °° Fig. 6.— Distribution of Private Campgrounds in Michigan, 1964. This map was drawn by the computer mapping routine "SYMBOL," and was based on data compiled from: (1} Private Campground License Records, Michigan Department of Public Health; and (2) Private campground mail survey designed for this study. The m a p includes 103 private campgrounds which were estab­ lished or registered in and before 1964. Small campgrounds with less than 10 campsites were not included. 70 MICHIGAN PRIVATE CAMPGROUND LOCATION PATTERN 1969 Oo PRIVATE CAMPGROUNDS ESTABLISHED OR LICENSED IN ANO BEFORE IK 9 »or CP o Fig. 7.— Distribution of Private Campgrounds in Michigan, 1969. This m ap was drawn by the computer mapping routine, "SYMBOL,” using data compiled from: (1) Private Campground License Records, Michigan Department of Public Health; (2) 1969 and 1973 Campground and Trailer Park Guide published by Rand McNally & Co.; and (3) Private campground mail survey designed for this study. The map includes 262 private campgrounds which were established or registered in and before 1969. Small campgrounds with less than 10 campsites were not included. 71 1 ; >• I f ' K I VHT r L. 1-1M F ' r K J 1 V. J . ~i 1 I irj t h 1 1 P * h i 1 '.17 3 # P R IV 1T E CAMPGROUNDS E S T A B LIS H E D Oft LIC E N S E D IN AND BEFORE 1 9 7 J Fig. 8.— Distribution of Private Campgrounds in Michigan, 1973. This map was drawn by the computer program, "SYMBOL," using data compiled from the same sources as Figure 7. The m a p includes 530 private campgrounds and omitted small campgrounds having less than 10 campsites. 72 in Figure 6 on page 69, seems to have a tendency toward concentration. An examination of Figure 7 on page 70, and Figure 8 on page 71 reveals that this tendency did occur and it appears that private campground development in later years for the most part expanded from initially concentrated areas rather than uniformly spreading over the entire state. As a result, distribution of private campgrounds has become concentrated in some areas but remained sparse, in many other areas. At this point, it seems logical to ask whether such a distribution pattern has occurred randomly or has been influenced by some identifiable forces. In order to test for randomness, a statistical technique known as the "near­ neighbor analysis" was employed to provide an index of the degree of departure from r a n d o m n e s s . ^ The index (R), known as nearest-neighbor statistic is a ratio of the mean observed distance (rA) between each point and its nearest and encouragement from the public sector. However, after 1962, the government became interested in promoting pri­ vate outdoor recreation development to cope with the rapidly growing demand at that time. The federal govern­ ment, for example, has established a number of programs for assistance to private outdoor recreation developers. This assistance included credit, technical aid, educa­ tional services and research. Consequently, both public and private campground developments grew rapidly. Then in the seventies, the campground business became larger and more complex. Development at this stage was character­ ized by an improved management and product differentiation. Rapid growth continues. *®See page 31 of this report for a discussion on the concept of near-neighbor analysis. 73 neighbor to the expected mean distance (rE) obtained in the same relationship from a random d i s t r ibution.^ The ratio has a range in value from zero to 2.15 and is less than, equal to, or greater than one, depending upon whether the pattern tends to be clustered, random, or uni­ form respectively. As previously indicated, the computed values of the nearest-neighbor statistic R are presented in Table 8 on page 74. An examination of Table 8 reveals that the com­ puted values of the nearest-neighbor statistic R for regional subdivisions and for selected years are all less than one. This does confirm the tendency toward a clustered campground location pattern as expressed on the point symbolic maps. Intuitively it was also expected that values of R would vary in magnitude from one region to another, for it would seem that variations in physical geography, economic base, and transportation infrastruc­ tures would likely to influence the spacing of private campground development. As we see from Table 8, the empirical results seem to support the intuitive reasoning, but the interregional variations in R is not as signifi­ cant as it was expected. Such insignificant variation in the values of the regional nearest-neighbor statistic may have resulted from the possible association of private ^ F o r computation of rE, see footnote 24 on page 31. Table 8.— Nearest Neighbor Measures of Private Campground Locations.3 Number of Observations Year or Region Observed Mean Distance (mile) (rA) Expected Mean Distance (mile) (rE) NearNeighbor Statistic (R) Nature of Pattern By year, all state: 1964 103 9.694 17.648 0.549 clustered 1969 262 5.989 11.522 0.520 clustered 1973 530 4.270 8.347 0.512 clustered 66 6.398 11.676 0. 548 clustered Region II 202 4.402 6.731 0.654 clustered Region III 262 3.693 6.919 0.534 clustered All state 530 4.270 8.347 0.512 clustered By region, 1973 Region I • aThe distance measures and near-neighbor statistics shown in the above table were computed by the computer program, "NABOR," which was originally devel­ oped by Dierk Rhynsburger, Department of Geography, University of Michigan, and modified by R. I. Wittick, Department of Geography, Michigan State University to operate on MSU CDC-6500 Computing System. For further reference, see R. I. Wittick, "GEOSYS— An Information System for the Description and Analysis of Spatial Data, Version 2," Technical Report No. 73-6, Computer Institute for Social Science Research, Michigan State University, 1973, pp. 21-22. Distances are measured in straight-line mileage between a pair of points. 75 campground locations with some areal characteristics which are common in all regions. An inquiry into this question and the factors influencing clustering of private camp­ ground development will be carried out in the next chapter wherein the spatial relationships are considered. CHAPTER IV ANALYSIS OF PRIVATE CAMPGROUND DISTRIBUTION In the foregoing discussion, it has been found that the distribution of private commercial campgrounds tends to be more clustered than random. This can be interpreted to mean that some areas have been more attractive to pri­ vate campground development than any other areas. If such is the case, certain areal characteristics may be used to describe and explain spatial variations in private camp­ ground distribution. But which areal characteristics are to be used in such description and analysis? What are the relationships between selected areal characteristics and the spatial pattern of private campground distribution? Answers to these questions take the form of hypotheses which may be posed for testing. Therefore, in this chapter, an attempt is made, using multiple regression analysis techniques, to identify significant areal characteristics and analyze the degree and direction of their relation­ ships with spatial variations in private campground dis­ tribution. 76 77 Geographic Unit for Analysis The geographic unit chosen for analysis in this chapter is the county. This determination was arrived at from the following reasons: (1) The county is a convenient subregional grid which retains reasonable homogeneity with respect to area characteristics for purposes of outdoor recreation analysis. (2) The county has authority to influence land use within its territory. If a county authority decides to encourage outdoor recreation activ­ ities, this would create a favorable "climate" for private campground development, and vice versa. (3) Most data concerning area characteristics are collected on the county basis. To select the county as the geographic unit for analysis does, to a great extent, ease data collection efforts. (4) The 83 counties of Michigan form a reasonable grid system for description and analysis of spatial data by computer-mapping techniques. As we shall see, computer- mapping techniques are used to facilitate development of hypotheses for statistical testing. On the other hand, the county also has some limitations when used as the observation unit in analysis. First, differences in size among counties may introduce statistical bias because it may disturb randomness of the observations. That is, large county units may have a greater change for private small ones. campground development than If such is the case, the accuracy of regression 78 estimates would be reduced. Second, the campground devel­ opment in a specific county may, in fact, be influenced by area characteristics spread across county boundaries. As a result, the accuracy of statistical inference would be reduced. Developing Hypotheses The spatial pattern of private campground develop­ ment is a composite result of numerous physical, cultural, and socio-economic "influences." Because of the complexity of the problem, it seems unlikely that anyone could com­ pletely understand relationships between them. It is possible, however, that one may sort out what seems likely to be dominant factors by analyzing hypotheses developed from intuitive reasoning, existing knowledge and past experiences. And operationally, the "SYMAP" mapping routine can be used to facilitate development and selec­ tion of hypotheses for analysis. The following is a listing of selected hypotheses and a discussion of the rationale and component parts of each hypothesis under consideration. (1) Private campgrounds tend to be located in areas where recreational water resources are available. The rationale underlying this hypothesis is simply that water resources are the essential base for most out­ door recreation activities. A lake, stream, river, or 79 shoreline is frequently the center of outdoor recreation activities. In campground development, size and quality of the water resources base for recreation may govern the types of activities to be provided and scale of operation to be established at a campground. As generally conceived, the water resource base with high recreation quality tends to attract more private campground development. It is expected that the water resource base will have a positive relationship with private campground development. To test this hypothesis, we considered its component parts repre­ sented by such county statistics as: water bodies, (1 ) number of inland (2) acres of inland water bodies, (3) miles of streams, and {4) miles of great lake shoreline. The selection of variables to represent the hypoth­ esis for analysis was made by considering the practical meaning of the variables and by comparing the maps created by the "SYMAP" package. Figure 9 on page 80, for example, contains two maps showing spatial patterns of water sur­ face acreage and private campsite distribution. By com­ paring the maps, it is possible to obtain a rough image of how the two variables are related. This practice was applied to every possible variable during the hypothesis development stage. (2) Private campground development tends to orient to the area where tourist attractions and highly desir­ able public recreation areas are located. Fig. 9.— Maps Showing Water Surface and Private Campsite Distribution Patterns. These maps were developed by the "SYMAP" routine with the county geographic centers as data points. They provide an approximate image of how the two variables were related, and thus are helpful to variable selection. However, these maps can only show overall spatial pattern, and must not be viewed as precise representation of the actual data. 81 The rationale underlying this hypothesis is that private campgrounds may be served as away-from-home vaca­ tion headquarters which allows campers to visit tourist attractions in the area and enjoy a variety of leisure activities with little additional cost. A campground located in or near an area of land having distinctive natural characteristics, historical significances, and cultural activities usually has the added advantage of complementary attractions. Such an area would have great appeal to campground developers if it is available for private campground development at a reasonable price. For empirical testing, this hypothesis may be represented by a set of independent variables such as acres of public recreation land in the county, availability of public and private recreation facilities in the county, and number of tourist attractions in the county. (3) Private campgrounds tend to be located in the area of land having highway convenience and easy access to major population centers. The rationale underlying this hypothesis is that accessibility is an important factor in determining demand and supply of outdoor recreation services, and that trans­ portation convenience affects time and monetary costs of 82 travel as well as the character of recreation experience.^ Travel from home to the campground and back requires time and money. A campground with poor access to potential users and inconvenient transportation incurs relatively large time and monetary costs of campers, as well as sometimes causing them discomfort. their expenditures, If campers rationalize it can logically be expected that accessibility will bear a positive relationship with the intensity of private campground development in an area. To examine this hypothesis, we may consider such county data as: (1 ) distance from the geographic center of a county to the population center of the Detroit Metropolitan Area, (2) the density of highways interstate, and federal highways) major regional subdivisions. (including county, state, in a county, and (3) Preliminary screening was made to select a set of variables which are considered most representative of the hypothesis. Figure 10 on page 8 3 contains two maps showing spatial patterns of highway density and private campsite distribution. It pro­ vides an example of how visual comparison of maps created by the "SYMAP" package was implemented. (4) Private campground development tends to orient away from the area where land costs are high. ^For a more extended discussion as to how trans­ portation affects outdoor recreation, see Marion Clawson and Jack L. Knetsch, "Economics of Outdoor Recreation" (Baltimore: The Johns Hopkins Press, 1966), pp. 96-102. Fig. 10.— Maps Showing Highway Density and Private Campsite Distribution Patterns. These maps were developed by the "SYMAP" routine with the county geographic centers as data points. They provide an approximate image of how the two variables were related, and thus are helpful to variable selection. However, these maps can only show overall spatial pattern, and must not be viewed as precise representation of the actual data. .ititUMti: 84 The rationale underlying this hypothesis is that land is a substantial part of campground business invest­ ment. If land costs are high, campground investment would involve large initial capital and high opportunity costs. Associated with high land costs may be also higher prop­ erty taxes which represent an additional annual cost of operating a campground. in an area of land having high costs, land owners may attempt to seek more lucrative uses for their land and other resources rather than for camp­ ground development. On the other hand, prospective camp­ ground developers may hesitate to establish campground facilities in that area because of high land costs. Accordingly, we can hypothesize that the higher the land costs of an area, the fewer the private campgrounds expected to be located in the area. Variables considered relevant to the test of this hypothesis include: (1 ) aver­ age dollar value of farm land per acre in a county, (2 ) average property tax per acre of land in a county, and (3) annual increase in real assessed value in a county. (5) Private campground development tends to orient away from an urbanized and/or industrialized area. Like any other economic activity, private camp­ ground development must compete for land resources with other land use alternatives. In a market economy, land resources under competition usually go to the use which 85 has the highest productivity and thus can bid the highest price. In order to compete for use of land resources, private campground enterprises must be able to produce a return that will enable them to bid the highest price. However, in urbanized and industrialized area where land use competition is often intense, extensive enterprise such as the campground business have difficulty competing for use of land resources with intensive land use activ­ ities. Therefore, the greater the degree of urbanization and industrialization, the less likely it will be developed into campground use. Moreover, from an esthetic point of view, an urbanized or industrialized area does not seem to provide the atmosphere desirable for camping activities. Examples of county data relating to this hypothesis include: (2) (1 ) number of political subdivisions in a county, county population density, (3) percentage of urban population to total county population, and (4) ratio of industrial employment to farm employment in a county. The Analytical Model The analytical method selected for investigating the above hypotheses is multiple regression analysis, which is capable of isolating the collective and separate contributions of two or more independent variables towards explaining variation in a dependent variable. Structure of the regression model designed for the present study is as follows: 86 Y. = a + : I b. x . . + U . i=l x ^ 3 j -1,2,. . .. N and i ~ l ,2 ,.. .K where: Yj is the dependent variable representing the number of total private campsites in a county, x ij is an independent variable; each represents a county characteristic (a detailed description of each variable will follow), a is the Y-axis intercept, b^ is the regression coefficient for each of the k independent variables, Uj is the error term associated with each estimated value of the dependent variable, i is the subscript representing a specific independent variable, j is the subscript representing an observation, N is the number of observations, i.e., the total county units under investigation, N = 83, and K is the number of independent variables to be anal­ yzed, K = 13. The Dependent Variable The dependent variable selected for analysis is the number of campsites provided by the private sector in each county. The number of private campsites in a county is assumed to reflect the private campground locational 87 pattern which is an outcome of aggregate location decisions of private campground enterprises. If location decisions of private campground developers were economically "rational" and were based on past experiences and knowl­ edge of existing area characteristics, it is possible to establish a meaningful relationship between the number of private campsites and the selected county characteristics. For this reason, the investigator considered that the number of private campsites would be an appropriate dependent variable for analysis of campground areal associ­ ations . Independent Variables In order to examine the relationship between pri­ vate campground development and county characteristics, a set of county data was developed into 30 independent variables which were considered indicative of the hypotheses discussed above. 2 Moreover, through a preliminary screen­ ing process, thirteen (13} variables among them were con­ sidered appropriate for final regression analysis. The selection was made by a pairwise comparison of simple correlation coefficients between independent variables and by a visual comparison of the maps created by the "SYMAP” computer mapping program as mentioned before. 2 If two See Appendix III for the listing and descriptions of the 30 variables originally considered for the county model. 88 independent variables were highly correlated (i.e., r^j = 0.7), only the one most closely related to the dependent variable was selected. Table 9 on pages 89 and 90 lists and describes the 13 independent variables included. The Statistical Findings As mentioned above, the statistical method used to estimate coefficients associated with independent variables and in testing the hypotheses is the SPSS Step­ wise Multiple Regression Program currently operating on the CDC 6 500 computing system of Michigan State Univer­ sity. The final equation was determined at the .10 level of statistical significance ,3 and the results are presented in Table 10 (see pages 91 and 92). 3 The selection of the statistical significance level is one of many controversial statistical problems. Although some criteria for selection significance level have been suggested (see Sanford Abovitz, "Criteria for Selecting a Significance Level: A Note on the Sacredness of .05," in Denton E. Morrison and Raman E. Henkel, "The Significance Test Controversy" (Chicago: Aldine Publishing Co . , 1970), pp. 166-171), there is no rule of thumb for selecting an appropriate significance level. The level of significance selected here for testing hypotheses is .10 which is larger than the conventional levels of signifi­ cance such as .05 and .01. The selection of relatively large level of significance for this study can be justi­ fied by three essential reasons: (1) From the standpoint of practical consequences, errors incurred in establishing the relationship between campground development and area characteristics have few long lasting and extreme effects on policy decision-making. (2) The present study focuses primarily on the exploration of a set of interrelations in private campground location decisions. In this explora­ tory stage, a large significance level increases the probability of accepting the investigator's hypotheses which may well become a scientific basis for further study. (3) Power of the test varies directly with sample size, 89 Table 9.— The Independent Variables Included in the County Model. Variable Notation Variable Description Unit of Measurement Water Resources: X, Inland water bodies over 200 acres number Total length of streams miles Total length of Great Lake shoreline miles Other Recreation Resources (areas and facilities) Publicly owned campsites (including both park and forest campgrounds) number Acreage of public recreation land acres Nationally significant tourist attractions number Accessibility X., k8 Distance from the geographic center of each county to the population center of the Detroit Metropolitan Area miles Density of highways (including county, state, federal, and interstate highways) miles per sq. mile of area Total length of state, inter­ state, and federal highways miles Average value of farm land dollars per acre (1969) Land C o st s : X10 90 Table 9.— Continued. Variable Notation Variable Description Unit of Measurement Level of Urbanization: X., Population density, 1970 persons per sq. mile X 12 Proportion of land in farm and forest percentage Employment Condition: X 1 -a Average unemployment rate (1969-1972) For data sources, see Appendix IV. percentage Table 10.— A Summary Table of Regression Results.3 Variable Number Variable Description Regression h Coefficients Beta Weights STD error of reg. coeffi. 25.196 .418 5.795 .244 19.978 .868 81.380 -.562 2.897 Water Resources: X. No. of ponds and lakes over 200 acres Miles of streams Xj Miles of GL shoreline POS-NS POS-NS Other Recreation Resources: X^ No. of public campsites POS-NS Xg Acre of public land POS-NS X, No. of nat’l. tourist attractions 39.309 Accessibility: NEG-NS X? Distance from county to Detroit X fi H HWY density— M. per sq, mile Xg Miles— major HWY POS-NS AVG. dollar value per acre of farmland -9.562 481.443 Land Costs: X.Q Table 10.— Continued. Variable Number Variable Description Regression . Coefficients Beta Weights STD error of reg, coeffi. — - Degree of Urbanization: X 12 Population density NEG-NS Percent of land in farm and forest POS-NS Employment Condition: AVG unemployment rate Constant POS-NS -450.890 131.303 Number of valid observations - 81 Multiple regression coefficient (R) = .612 Multiple determination coefficient (R 2) = ,374 Standard error of estimate - 284.368 aFigures are rounded to 3 decimal places. Overall F value = 11.366 See Appendix V. The variables not significant at .10 level are indicated only by the direction of relationship. POS = positive relationship, NEG - negative relation­ ship, and NS = not significant at .10 level (F value of 2.79). 93 As Table 10 on pages 91 and 92 shows, the coef2 ficient of multiple determination, R , a measure of the overall statistical explanation power of the regression equation, for the equation including four significant variables was .374. This means, in practice, that about 37 percent of variation around the mean in the number of campsites provided by the private sector was accounted for by the four variables in combination. The same table also indicates the regression coef­ ficient and beta weight for each of the four independent variables significant at the .10 level. The regression coefficient measures the impact of each individual vari­ able, whereas the beta weight is used to compare the rela­ tive importance among the variables. These measures will make sense only when there is no severe multicolinearity problem involved in the estimates because oftentimes such a problem restricts our ability to determine the separate impact of variables. However, an examination of the correlation matrix obtained from the regression calcula­ tion in this study reveals that only density) (population is highly correlated with X^ q (average dollar that is, as N increases there is a greater probability of correctly rejecting the null hypothesis, as compared to an alternative hypothesis. For these reasons, we con­ sidered the larger significance level appropriate. More­ over, since data used for this regression analysis were obtained mostly from census sources, it should be noted that the test significance in this case may not be as meaningful as in well-designed experimental research. 94 value of farmland per acre) and Xg (number of tourist 4 attractions with national significance). This suggests that the intercorrelation between independent variables does not create serious problems in assessing their individual impacts. Discussion and Conclusions According to the regression results, the variation in the number of campsites provided by the private sector is significantly related to four county characteristics: highway density, average dollar value per acre of farm­ land, number of lakes with size over 200 acres, and number of tourist attractions with national significance, order. in that The consistency in sign and significance of various statistics shown in the regression results seem to support the basic hypotheses regarding the orientation of private campground development. The following conclusions can be drawn from the regression analysis: (1) Highway convenience and accessibility appear to be the most important factors associated with the distribution of private campground facilities. Private campgrounds tend to be developed in an area where highway transportation is convenient, other things being equal. 4 If two independent variables have a simple correlation coefficient of .6 or more, they are considered here as highly correlated. In this case, only r(x^., Xg) .74485 and r(x 1 1 ,x^Q ) = .77098 are above .6 level. 95 This statement is also strongly supported by the survey results which, as presented in Table 11 on page 96, show that about one-third of the respondent campgrounds are located within one mile distant from a state or federal highway, and up to 82.6 percent are within 5 miles of the distance. There are also good reasons to believe that such an association exists. Campgrounds located near a highway or in an area where highway density is high are likely to receive more campers, particularly those wanting to stop for a night's rest and perhaps limited sightseeing. Also, campground developers have realized that highway convenience and good access could mean savings in both time and monetary costs, and oftentimes comfort, for a camper traveling by automobile with trailer and other camping equipment, and accordingly they establish camp­ grounds in areas convenient to highways. In this case, if we assume that campers are rational and hence try to minimize their time and monetary costs, it is reasonable to say that orientation of private campground development toward highway access is consistent with the rational behavior of campers. (2) As hypothesized, the number of campsites pro­ vided by the private sector in a county is negatively related to the dollar value per acre of farmland in that county. High dollar value of land means high land cost to the campground developer. As this cost increases, the 96 Table 11.— Distances from Private Campgrounds to State or Federal Highway. Distance 3 in Miles Number of Observations Percent Distribution Cumulative Percent 1.0 - less 105 35.8 35.8 1.1 - 5.0 137 46.8 82. 6 5.1 - 10.0 36 12. 3 94.9 10.1 - 15.0 6 2.0 96. 9 15.1 - 20.0 4 1.4 98. 3 20.1 - 30.0 3 1.0 99. 3 30.1 - up 2 .7 100.0 293 100.0 Total Valid Observations Average Distance 3.751 railes Standard Deviation 7 .387 miles Source: Based on responses from the private camp­ ground survey conducted as part of this study. a Distances are measured in actual mileage as reported by campground operators. 97 campground developer's initial capital investment and annual property taxes also tend to increase. For a business with modest financial return such as a campground opera­ tion , developers would hesitate to establish campgrounds in a high land-cost area. Moreover, in an area where land values are high, land owners would be expected to seek uses for their land and other resources more lucrative than campground development. Consequently, it may be expected that few campgrounds would be developed in high land-cost areas. (3) As expected, those variables (see Table 10 on pages 91 and 92) indicative of a water resource base showed a positive relationship with the number of campsites provided by the private sector. However, among the three selected variables, only the number of inland water bodies over 200 acres was statistically significant. This may be due to the fact that sizable lakes are more flexible for various water-oriented activities, and thus more attractive to private campground development. Moreover, it is also possible that relatively restrictive use of Great-Lakes shoreline has limited its possibility for private campground development. The importance of water resources to campground development is shown by the results of the survey. As indicated in Table 12 on page 98, about two-thirds of the total respondent campgrounds are located adjacent to either 98 Table 12.— Summary of Private Campground Distribution by Different Adjacent Hater Bodies. Type of Adjacent Water Bodies Number of Observations Percent Distribution 147 50.5 Artificial lake 36 12.4 River 30 10.3 Small stream 34 11.7 Not adjacent to any water body 44 15.1 291 100.0 Natural lake Total Valid Observations Source: Based on the responses from the private campground survey conducted as part of this study. The term, "adjacent" refers to a distance measure which is 200 feet or less between two relevant location points. 99 natural or artificial lakes, and only 15 percent of the total respondents are not located adjacent to any water body. In referring to types of activity provided by private campgrounds, the survey (see Table 13 on page 100) also indicates that most respondent campgrounds have pro­ vided one or more water-oriented activities listed in the questionnaire, and only 12 percent of them have not pro­ vided any of the listed water-oriented recreation activ­ ities. Based upon both regression analysis and survey results, we may conclude that camping has been usually associated with water, and private campground development tends to orient toward recreational water resources. (4) As the analytical results indicate, there could be a complementary relationship between private campground development and other recreational resources such as public campground facilities, public recreation land areas, and tourist attractions. However, among these variables, only the number of tourist attractions with national significance was found to be statistically sig5 nificant at .10. Public park resources and campground facilities add to the general attractiveness of an area, but at current state of development, they do not seem to 5 The tourist attractions considered here include both unique natural features and cultural facilities and activities. The ranking of significance of a tourist attraction was suggested by Mr. Charles E. Budd, Tourist Promotion Manager, Michigan Tourist Council, on the basis of frequencies of tourist inquiry for the attraction and his personal judgement. 100 Table 13.— Water-Oriented Recreational Activities Pro­ vided by Private Campgrounds. Water-Oriented Activities Number of Percent . Observations 3 Distribution Total Valid Observations Motor boating 140 48.1 291 Water skiing 104 35.7 291 Canoeing 161 55.7 291 Swimming 204 70.1 291 Fishing 228 78.4 291 Row boat & paddle boat 191 65. 6 291 None of the above 36 12. 4 291 Source: Based on the responses from the private campground survey conducted as part of this study. aOne campground may provide more than one activity. bBased on the total valid observations of each activity. 101 impose a significant influence upon spatial distribution of private campground industry. (5) As hypothesized# population density was found to have a negative relationship whereas the percentage of land in farm and forest had a positive relationship with the number of campsites provided by the private sector in the county. Both variables were selected to indicate the degree of urbanism or ruralism of the county. Although not statistically significant# their relationship with the dependent variable may have some practical implications. First, since competition for land and other resources is more intense in urbanizing areas, extensive enterprises such as campgrounds would have difficulty competing as a resource use. In addition# because camping for many people is to experience outdoor living in close association with nature, the orientation of private campground develop­ ment to rural areas may be considered a reflection of the desirability of such an environment for camping activity. Throughout this chapter we have described and analyzed in considerable detail the spatial pattern of the private campground industry in Michigan. Summarizing, it can be said that the spatial distribution of private camp­ grounds in Michigan is more clustered than random. There have been locational forces at work to shape the existing distribution pattern. From the results of our survey and analysis, we have found that private campground development 102 has been oriented to those areas where highway transpor­ tation is convenient, and where recreational water resources and significant tourist attractions are available. More­ over, since campground operations are extensive enterprises with modest financial returns, land costs have been impor­ tant constraints on the choice of private campground locations. CHAPTER V FACTORS IN THE PRIVATE CAMPGROUND LOCATION DECISION The conceptual basis and analytical method for determining private campground location decision factors have been discussed in previous chapters relating to hypothesis development and research method. In this chap­ ter we focus on the empirical analysis that was designed to: (1) isolate a set of key variables associated with the location of private campground development; (2) test the hypothesis that the profit-motivated campground location decision can be substantially explained by spatial char­ acteristics; and (3) investigate the hypothesis that solution to the campground location decision will depend on a combination of various spatial characteristics which act as inputs to, parameters in, or constraints to the production function rather than any single individual factor that dominates the decision. The analytical model, including its dependent and independent variables, and the empirical results will be systematically presented in the following sections. 103 104 The Analytical Model and Its Variables In an attempt to carry the concepts of location decision-making a step further for statistical analysis, we have formulated a campground developer conceptual model Figure 11 on page 105 illustrates the elements which are believed important to the campground developer's location decision. These elements were developed into measurable variables so that they would be suitable for statistical analysis. As previously mentioned, the method employed in this analysis to determine campground location decision factors is multiple regression. The basic form of regression equation used here can be written as follows: Y * a + b.x.. + b_X_ + ..... + b-X. + .... 1 1 2 2 11 + b X nn + e where: Y = the dependent variable represented by occupancy rate (in percentage), X^(i=l,n) = the independent variables represented by a set of various spatial characteristics, a, and b^ = parameters; a is the intercept of Y axis, and b^ are partial regression coefficients which determine the slope of the equation, and e = the error term. 105 CAMPGROUND OPERATION CHARACTERISTICS 1. Years in business 2. Size of campground 3. Daily rental charge per campsite-day 4. Types of facility 5. Types of recre­ ational activities A MODEL RELATING CAMPGROUND OPERATION CHARACTER­ ISTICS AND LOCATIONAL CHARACTER­ - > LOCATIONAL CHARACTERISTICS 1. Proximity to a recre­ ational water body 2. Availability of other recreational areas & facilities in the local area ISTICS TO THE CAMP­ GROUND LOCATION DECISION OUTPUTS: A set of key vari­ ables which guide devel­ opers in making a desirable campground location choice INDICATOR 3. Relationship with nearest neighbors (e.g., distance, operating character­ istics , e t c .) 4. Characteristics of nearest neighbors 5. County characteristics 6 . Region in which the site is located Fig. 11.— Elements in the Campground Developer's Location Decision Model. 106 The Dependent Variable The only dependent variable selected for the present analysis is the percentage occupancy rate. This form of occupancy rate has been used in many campground studies as an indicator of campground performance or camper preferences.1 Conceptually, such an occupancy rate is defined as the ratio of total number of campsite-days sold during a specific time period to the total number of campsite-days available in a campground for rent during the same period of time. For example, if a campground has 100 rental campsites available in June, the total number of campsite-days available for rent in that month would be 3000 (30 days x 100 campsites). Accordingly, if the operator of that campground has rented out 1800 campsitesdays during that month, then the occupancy rate of his campground in June would be .60 or 60 percent. As stated, computation of the occupancy rate seems very easy. In fact, it is, but the real data for com­ puting such an occupancy rate are difficult to obtain either because campground operators did not keep occupancy records or because they were unwilling to disclose their records. Therefore, in this study, we did not ask for the direct campsite-day records from campground operators. ^For example, see David W. Lime, "A Spatial Analy­ sis of Auto-Camping in the Superior National Forest of Minnesota: Models of Campground Selecting Behavior" (unpublished Ph.D. dissertation, University of Pittsburgh, 1969), pp. 43-58. 107 Instead, we asked for their estimates of monthly occu­ pancy rate, and from these monthly estimates, we derived the seasc^al average for each respondent campground. In doing this, we implicitly assumed that each respondent understood the concept of relative occupancy rate and reported their estimates consistently and accurately. 2 Data used in computing the dependent variable were restricted to a three-month season including June, July, and August of 1972. The reason that only seasonal data were considered is that camping is a seasonal activ­ ity in Michigan, and it takes place mostly during the summer months.3 Independent Variables There are a number of campground operating and spatial characteristics which may, to a variable degree, affect the desirability or performance of a campground. However, previous studies have suggested that three general factors are most important. These are (1) accessibility, 2 The investigator tested this assumption by asking many campground operators attending the campground owners conference held at Michigan State University and found that the concept of relative occupancy rate used in this study was generally understood. 3As stated in the report of "Michigan State Park Camper Study," approximately 85 percent of the campers visited state campgrounds during the warmest months which in Michigan include June, July, and August. See Michigan State University and Michigan Department of Conservation, "Michigan State Park Camper Study," unpublished manu­ script, 1967, p. 54. 108 (2) unique natural environment, and (3) cultural or man4 made environment. Based upon these findings and survey data, we developed a set of 34 variables for the present analysis. They are described as follows. Campground Operating Characteristics X^--Years in business: measured by the number of years the campground has been in operation, counting from the date of establishment to December 31, 1972, rounded to the nearest tenth of a year. X ^— Size of campground: measured in number of camp­ sites available for rental during the 197 2 season. X^— Proportion of modern facilities: measured in per­ centage of modern campsites to total campsites in 1972. X^— Daily rental charge: measured to the nearest tenth of a dollar. This was the basic fee charge per site per day during the 197 2 season. If the fee charge varied according to site location or facility type, the average rate for the campground was used. 4 For further discussion, see Carlton S. Van Doren, op. cit., p. 5.2 and David W. Lime, op. c it., pp. 61-68. 109 Proximity to Recreational Water Body Xg— Proximity to a natural lake: coded as 1 if the campground is located adjacent (i.e., within 200 feet of distance from the campground) to a natural lake, and as 0 if not. Xg— Proximity to a river: coded as 1 if the campground is located adjacent to a river, and as 0 if not. X 7— Proximity to an artificial (man-made) lake or pond: coded as 1 if the campground is located adjacent to an artificial lake or pond, and as 0 if not. X Q— Proximity to a small stream: coded as 1 if the O campground is located adjacent to a small stream, and as 0 if not. Availability of Various WaterOriented Recreation Activities Xg— Availability of motor-boating: coded as 1 if motor-boating is available at the campground, and as 0 if not. — Availability of swimming: coded as 1 if swimming is available at the campground, and as 0 if not. X ^ — Availability of fishing: coded as 1 if fishing is available at the campground, and as 0 if not. Xj^— Availability of canoeing: coded as 1 if canoeing is available at the campground, and as 0 if not. 110 — Availability of water-skiing: coded as 1 if waterskiing is available at the campground, and as 0 if not. — Availability of row or paddle boating: coded as 1 if row or paddle boating is available at the camp­ ground , and as 0 if not. Availability of Golfing or Campground Facilities in the Immediate Surrounding Area X 15— Availability of a golf course: coded as 1 if golf course is available within 15 minutes of driving distance from the campground and as 0 if not. — Availability of public campground: measured in number of publicly operated campsites available within 15 miles of the campground. X 17— Availability of private campgrounds: measured in number of privately operated campsites within 15 miles of the campground. Accessibility to Nearest Neighbor and Primary Highway X^g— Distance to nearest public campground: measured to the nearest tenth of a mile. X^g--Distance to nearest private campground: measured to the nearest tenth of a mile. X£ q — D istance to state or interstate highway: measured from the campground to the nearest exit of a state Ill or interstate highway, and rounded to the nearest tenth of a mile. Population of the Immediate Surrounding Area X^'- T o w n s h i p population density: measured in number of persons per square mile of the township area in which the campground is located. X 22— Population of nearest city: measured in number of persons resident in the nearest city. Population was weighted by the reciprocal of the distance in miles from the campground to the center of the nearest city.^ Selected County Characteristics X23— National tourist attractions: measured in number of nationally significant (as defined by the Michigan Tourist Council) tourist attractions in the county. X 24 — State-level tourist attraction: measured in number of state-level Council) (as defined by Michigan Tourist tourist attractions in the county. X 2 j.— Inland Water Body: measured in number of inland water bodies 200 acres or more in the county. 5 The development of this variable was based on the concept of gravity as applied in spatial interaction analysis. According to this concept, one would expect the effects of events or conditions to be smaller the greater the distance between the two points concerned. 112 X 2 g— Stream length: measured in number of miles of stream in the county. X 27— Great Lake shoreline: measured in number of miles of Great Lake shoreline in the county. X^g— Public Recreation Land: measured in acreage of public recreation land in the county. x 29— Highway density: measured in mileage of highways (including county, state, and interstate highways) per square mile of the county area. Selected Characteristics of Nearest Neighbor X 3Q— Size of nearest public campground: measured in number of campsites weighted by the reciprocal of the distance in miles between the campground and the nearest public campground.^ X^^— Occupancy of nearest public campground: measured in the 1972 percentage occupancy rate weighted by the reciprocal of the distance in miles between the campground and the nearest public campground.^ X^j— Size of nearest private campground: measured in number of campsites weighted by the reciprocal of the distance in miles between the campground and the nearest private campground. g Xjj— Occupancy of nearest private campground: measured in the 1972 percentage occupancy rate weighted by ®For explanation, see footnote 5 on page 111. 113 the reciprocal of the distance in miles between the campground and the nearest private campground. 7 Regional Location — Regional location: coded as 1 if the campground is located in southern Lower Peninsula (Region 3), as 0 if the campground is located in northern Lower Peninsula (Region 2), and as -1 if the camp­ ground is located in Upper Peninsula (Region 1). Statistical Findings After data were assembled and prepared into machine readable form, they were analyzed by the SPSS Stepwise Multiple Regression Program to estimate the coefficients associated with the independent variables and to determine the and of each statistical significance of the model individual variable. The final equation was determined at the .10 level of statistical significance and the results are summarized in Table 14 (see pages 114 and 115). Inspection of Table 14 reveals that there exists a significant relationship at the .10 level of probability between the private campground occupancy rate as dependent variable and six hypothesized independent variables including: (1 ) proximity to natural lake, of water-skiing, (2 ) availability (3) township population density, (4) size of nearest public campground, weighted by distance, 7 For explanation, see footnote 5 on page 111. Table 14.— Summarized Regression Results of Significant Variables for the Camp­ ground Model. Variable Notation Variable Description X^ Year in business3 Xj. Regression Coefficients Beta Weights coefficients .674 .211 .272 Proximity to natural lake 13.262 .254 4.304 X., Availability of waterskiing 13.797 .239 4.876 X 21 Township population density .036 .144 .019 X^q Size of nearest public campground, weighted .193 .653 .050 X^ Occupancy rate of nearest public campground, weighted Xj^ Occupancy rate of nearest private campground, weighted X^4 Regional location3 Constant Number of complete observation Multiple regression coefficient -.879 -.744 .202 .027 .161 .013 6.932 .173 3.246 34.545 3.619 128 .522 Table 14.— Continued. Variable Notation Variable Description Regression Coefficients Beta Weights r ST° G si°r Multiple determination coefficient ..................... .305 Standard error of estimate ............................................... 23.671 ........................................... 8.913 Overall significance (F-value) V a r i a b l e X. was significant at .10 before X-Q entered into the equation, and the significance of variable X_. reduced from .04 to .14 level when entered into the equation. They are presented here along with other significant variables in the above table for they are considered to be consistent with the prevailing hypothesis, even though their level of significance is slightly lower than the others. ^The least highly significance value of F (P = .01) with 128 and 6 degrees of freedom is approximately 2.95. 116 (5) occupancy rate of nearest public campground, weighted by distance, and (6 ) occupancy rate of nearest private campground, weighted by distance. Together these variables explain about 30 percent of the variation in campground occupancy rate as dependent variable. All other inde­ pendent variables were found to be statistically non­ significant and to add only infinitesimally to the explana­ tory power of the total model. It may be noted that the coefficient of determination, R , is only .305 which is rather low, even though the overall F-statistic is significant at the onepercent level. The low coefficient of determination is not in itself particularly disconcerting; it is not the pur2 pose of present analysis to "maximize R ," but rather to investigate the effect of certain spatial characteristics as independent variables upon campground occupancy rate as the dependent variable. p The value of the regression coefficient of each significant variable indicates the existence and degree of association of that variable with the campground occupancy rate, when variations in the other variables are held constant. However, since the independent variables were measured in different units, it is difficult to use this p However, it is obvious that certain variables which do affect campground occupancy have been omitted from the model. It is believed that if the model is extended to include some measurable management variables, the coef­ ficient of determination would be increased considerably. 117 coefficient to ascertain the relative importance of each variable in influencing campground occupancy. One way to access such a relative importance is to use beta coefficients indicated in Table 14 on pages 114 and 115 as beta weights. Beta coefficients are merely net regression coefficients adjusted by expressing each variable in units of its own standard deviation. This adjustment eliminates the effects of the different measurement units and types of the variables and puts regression coefficients on a comparable basis. Based on this concept, it is clear from Table 14 on pages 113 and 114 that X 31 and X ^ 0 have a greater effect on the campground occupancy than any other variables, and X ^ , X,., and X ^ are approximately at an equal level of importance. Finally, it should be noted that the standard error of estimate is approximately 23.7 percent. This is the average amount of error incurred when the equation is used as a description of the campground occupancy rate. This amount of error is rather high in that it represents almost one half of the mean campground occupancy rate estimated directly from mail survey data. Imperfect specification of the model and omission of certain influ­ ential variables likely contributed to such a high standard error of estimate. 118 Discussion In the present analysis, we have investigated some hypothesized relationships between spatial character­ istics and the private campground occupancy rate. As regression results indicate, there are only eight hypoth­ esized relationships found to be statistically significant. Generally speaking, empirical results support the pre­ vailing hypothesis that a high campground occupancy is closely related to high quality recreation water resources and access to population concentration. Looking closer at the significant variables, we find that proximity to a natural lake and availability of water-skiing, both quality indicators of water resources for recreation, have a positive relationship with campground occupancy. This implies that the occupancy rate tends to be higher for a campground locating adjacent to natural lake having sufficient capacity for motor-boating and water-skiing activity. Positive coefficients of these two variables substantiate the prevailing hypothesis about the support of water resources in Michigan's campground development. Michigan public campgrounds are often found in areas where woods, water, and natural scenery are abundant. It is also generally true that relatively large public campgrounds tend to be established at those locations where natural wonders are unique. Accordingly, a large size public campground at a particular location may be good 119 indicator of availability of unique natural character­ istics or an important tourist attraction at that location. Based upon such an inference, we may interpret the posi­ tive coefficient for the size of nearest public campground to mean that a private campground may share the advantages of natural wonders with the public campground by locating close to it. But there is a limit to this. The negative coefficient for the occupancy rate of nearest public campground implies that private and public campgrounds are competing for campers. If its nearest public neighbor provided high quality services to attract more campers, this may result in loss of customers for the private camp­ ground. The negative coefficient associated with the occupancy rate of the nearest public campground does not support the prevailing hypothesis that a private campground may enjoy the overflow of campers from its public neighbor. The positive coefficient for the occupancy rate of the nearest private campground implies that increasing occupancy rate of a private campground may benefit its nearest neighbor, and the closer they are, the greater this effect will be. In theory, firms locating close to each other may enjoy external benefits from each other's sale promotion. It is also likely in campground operation that a private campground may benefit from its nearest neighbor's intensive sales-promotion. seems rare. But this situation It is doubtful whether such a positive 120 coefficient is a true relationship. Perhaps there may be an unknown third factor which has worked to influence the occupancy rate for both related campgrounds and thus contributed to such a strong positive relationship. The coefficient for township population density is positive. This implies that campground occupancy rate tends to be higher for those campgrounds which are located close to population concentrations. As indicated earlier, camping is a short-term experience, and in most cases, camping itself is not the only purpose of the trip. Many people use a private campground as a stop for overnight rest or as a vacation headquarters which will conveniently allow them to visit friends and relatives, as well as various tourist attractions. They often find campgrounds in populated areas more convenient for their cultural or social activities. The positive coefficient for township population density is consistent with our conclusions concerning campground orientation discussed in the last chapter. In addition to variables mentioned above, the number of years in business and the regional location are also helpful in explaining the campground occupancy rate. The positive coefficient for the number of years in busi­ ness implies that campground occupancy rate tends to be greater for those campgrounds which stay longer in the business. This relationship is self explanatory. As is 121 true in many other businesses, time is always required to build up management experience and customer relations. The positive coefficient for regional location is as expected. coded, 9 According to the way the variable was this implies that campgrounds locating in Region 3, the southern Lower Peninsula, tend to have a higher occu­ pancy rate than the other r e g i o n s . ^ A positive coef­ ficient, in this case, provides strong support for the hypothesis concerning the population effect on campground occupancy because nearly 89 percent of the Michigan popu­ lation is concentrated in Region 3. Now let us compare statistical findings to results of the mail questionnaire survey. Surveyed campground operators were asked to give their opinions about location g The regional location variable, X - ., is a category variable which was coded as 1 if the campground is located in Region 3, as 0 if the campground is located in Region 2, and as -1 if the campground is located in Region 1. 10Data collected by mail questionnaire survey, indicates that the average campground occupancy rates for each region are as follows: Occupancy Rate in Percentage 3-Month Season 5-Month Season Region I 46.06 34.39 Region II 46.43 37.79 Region III 55.69 52.49 All State 49.33 41.49 122 decision factors. Among other things, respondents were shown a list of ten locational factors and asked to identify and rank those three they considered most crucial in locating their campground.- As indicated in Table 15 on pages 123 and 124, for both those who developed their own land into campgrounds and those who rented or purchased land for campground development at the time of investment, availability of quality water resources was most frequently mentioned as their first choice. second in the order of frequency. Personal preference was Easy access to primary highway and proximity to population centers were far less important campground locational factors, compared to water resources and personal preference. However, it should be noted that personal preference was less frequently mentioned for those who rented or purchased land for campground development than those who developed their own land into a campground. This seems to imply that the former is more serious about campground locational choice than the latter. These survey results reveal a predominant role of quality water resources in determining campground location. Although variables relating to quality water resources were found to be extremely important in the statistical a n a l y s i s , ^ the investigator still feels that existing ^ V a r i a b l e s including both proximity to natural lakes and availability of water-skiing account for 13.92 percent of the variation in the campground occupancy rate which is nearly half of the total variation explained by the final equation. Table 15.— Campground Location Determining Factors as Viewed by Michigan Private Campground Operators. Campground Locational Factors Proximity to a population center Availability of quality water base As Viewed by the Operators Who Developed Own Purch. or Rented Land for CG Deve. Land into CG 5 3.85% 4 2.96% All 9 3,40% 75 57.69 83 61.48 158 59.62 Easy access to primary highway 7 5.38 15 11.12 22 8.31 Remote from urban environ­ ment 2 1.54 4 2.96 6 2.26 Proximity to a public park or other tourist attrac­ tions 3 2.31 4 2.96 7 2.64 Purely personal preference 31 23.85 22 16.30 53 20.00 2.22 10 3.77 Others Total usable responses Total non-responses 7b 130 23 5.38 100.00 3C 135 34 100.00 265 100.00 57 Table 15,— Continued. Campground Locational Factors Total questionnaires returned As Viewed by the Operators Who Developed Own Purch, or Rented Land into CG Land for CG Deve. 15, 16g A .. operators 322 Source: Based on data collected in 1972 by mail survey conducted as part of this study. a Only those locational factors ranked first in importance were counted and are presented in this table. Campground owners bought the site with campground facilities already on it. cThese include a variety of considerations such as: (1) to make use of the land; (2) to use the property more productively; (3) no alternative use is more profitable than campground operation. 125 campground operators have over-emphasized the resource base on the one hand, and overlooked the importance of potential market location (i.e., population centers) on the other hand. With some understanding of the fact that population and neighborhood effects are often difficult to be realized, it is contended that campground operator's opinions are helpful but not suitable for testing the above hypothesis. Based on the results of statistical analysis and inferential discussions, we may now derive the following conclusions: 1. Both water resources and population variables play a key role in determining the campground occupancy rate; and the former seems to have a much greater influence than the latter. But the higher occu­ pancy rate is associated with campgrounds having both quality water resources and good access to population centers. 2. The influence of public campgrounds on private campground occupancy rate is significant. Private campgrounds often share advantages of natural wonders with the public neighbors, but they are in fact, competing for customers. 3. The campground developer's location selection is equivalent to the selection of an array of spatial characteristics. But within such an array, certain 126 characteristics are more important than others. It is these important characteristics that make campground location different, not the entire array. Campground developers would probably achieve higher profit levels by concentrating on key characteristics identified in this study. 4. Immediate surroundings have a much greater influ­ ence on the campground occupancy rate than county characteristics. 5. The existing pattern of campground distribution seems to be consistent with variables significantly associated with the campground occupancy rate. Shifts in the spatial distribution do not appear to be helpful in improving campground business performance. CHAPTER VI SUMMARY AND CONCLUSIONS This final chapter consists of a summary of the entire study and highlights of major findings. In addi­ tion, limitations of the study are indicated and impli­ cations for both campground management decisions and future research possibilities are discussed. Summary of the Problem The location of private campground enterprises is not a matter of indifference to prospective investors. When attempting to invest in a campground business, a campground developer will face both long-run location decision and short-run management decisions, with the former decision restricting the range of latter oppor­ tunities. This study was primarily designed to provide an understanding of the spatial distribution pattern of the private campground industry in Michigan, and to inquire into campground location decision factors. The study was first carried out to investigate what kind of areal characteristics could be used to explain the existing 127 128 distribution pattern. Then an attempt was made to seek an answer to the question as to which of the selected location factors are most important and to what extent they can explain campground location choice behavior. This study approached the problem of private camp ground location decision from the standpoint of the camp­ ground developer as a producer, and viewed the campground developer as the enterpreneur supplying and selling camp­ ground services. Conceptually the study analyzed the campground location decision factors within a microeconomic framework of production function and profit motivation. The study area includes the entire state of Michigan, which was divided into three major regions for observing regional differences. Summary of the Methods The basic observation unit under study is the private campground operation unit which was defined in this study as a parcel or tract of land that is under control of a private person or persons and upon which campground facilities were established for commercial camping services. Data required for this study were obtained from both a mail questionnaire survey of camp­ ground operators and secondary sources such as campground directories, private campground registration records maintained by the Michigan Department of Public Health, 129 and various government statistical reports. These data were first summarized in tables and displayed in illus­ trations that offered visual examinations and statistical interpretations. The second major use of the data was for testing hypotheses generated from observed spatial associations, from a priori reasoning from theory, or from a combination of the two. Hypotheses were then developed into variables and relationships suitable for statistical testing. Two types of statistical techniques were used in this study. First, the "near-neighbor analysis" commonly used in geo­ graphical research was employed to test the campground distribution pattern for randomness. Second, multiple linear regression analysis was used to test selected locational factors or areal characteristics for their relationships with campground performance and spatial distribution patterns. In addition, computer mapping techniques were used to facilitate data display and the development of hypotheses. Summary of the Findings Information gained from statistical interpretation and analysis provides numerous findings relevant to ans­ wering previously stated questions. These findings can be summarized in three major categories relating to (1 ) campground distribution, (2 ) spatial associations, and (3) campground location decision factors. 130 (1) Findings Relating to Campground Distributions There were 975 campgrounds consisting of 62,761 campsites in Michigan in 1973. Among them, 552 campgrounds with 32,8 53 campsites were owned and operated by individ­ uals in the private sector. About half of these private campgrounds were located in Region 3 where state popu­ lation concentration was nearly 90 percent in 1970, and only slightly over 8 percent were in Region 1, the Upper Peninsula, and the remainder in Region 2. Of Michigan's total of 530 private campgrounds having ten or more campsites, 390, or 73.6 percent were operated on a seasonal basis in 197 3. campgrounds, Of these seasonal 212, or 54.4 percent were located in Region 3, and this was 80 percent of Region 3's total private camp­ grounds. Region 3 private campgrounds were found to have larger mean campground size, a higher percentage of improved campsites, and greater expansion since establish­ ment, as compared to the other two regions. Campgrounds located in Region 1 were about one-third smaller than those located in Region 2 or Region 3. Throughout the state, private campgrounds were located, on the average, about 3.7 miles from a primary highway (such as a state, interstate, or U.S. highway), 1.9 miles from a natural lake, 6.7 miles from the nearest private campground, and 12.8 miles from the nearest publicly 131 owned campground. By regional comparison, private camp­ grounds in Region 1 were located much closer to a natural lake (1.4 miles) and a primary highway (2.7 miles) than the state average and any other region. Region 3 had the shortest average distance (S.6 miles) between two closest private campgrounds but the largest average distance (16 miles) between a private campground and its nearest public campground, as compared to the other two regions. Approximately three-fourths of the private camp­ grounds were located within 200 miles of the Detroit Metropolitan Area where 4 4 percent of the state's total population was concentrated in 1970. Private campgrounds were seldom developed in urbanized areas, but there were intensive private campground developments surrounding major population centers. One example of such a develop­ ment pattern was found in the Oakland and Livingston counties which are located about 28 to 56 miles distant from Detroit Metropolitan Area, respectively. (2) Findings Relating to Spatial Associations Spatial distribution of the private campground industry in Michigan was found to be more clustered than random. This is a statistical indication of existing spatial associations. Thirteen variables, nine relating to general attractiveness of the county for outdoor recreation development and four relating to county 132 socio-economic characteristics, were isolated using multiple regression analysis and their relationships with the distribution of private campground development were determined. Four variables, highway density, average dollar value of farmland, number of lakes including 200 or more acres, and number of tourist attractions, were found to be significantly related to development of camp­ sites by the private sector in the county. Results of the regression analysis followed a logical pattern. Positive correlations were found between number of campsites provided by the private sector and variables relating to highway convenience, water resources, tourist attractions, and availability of public recreation areas, which are generally favorable to outdoor recreation. Since the return to the private campground business has been modest, those variables such as which tend to increase the costs of investment and operating the camp­ ground, showed a negative relationship with the develop­ ment of campsites in a county by the private sector. (3) Findings Relating to Camp­ ground Location Decision Factors Determination of private campground location is assumed to be based upon three standard levels of spatial characteristics— region, area, and site— which act as inputs to, parameters of, and constraints on the cost and production functions. With this conceptual basis, we can 133 hypothesize that campground location decisions can be sub­ stantially explained by a list of spatial characteristics. Occupancy rate, which has often been used to indicate private campground performance, was selected to measure the outcome of a campground decision. Thirty-four vari­ ables considered to be significantly related to the camp­ ground occupancy rate were chosen. A multiple linear regression model was specified and applied to 1972 camp­ ground survey data to estimate relationships between occu­ pancy rate as dependent variable and spatial character­ istics as independent variables. It was found that eight variables were significantly related to the campground occupancy rate. significant at the .10 level include: Variables (1) proximity to a natural lake {X^}, (2) availability of water-skiing {3) occupancy rate of nearest public campground (X13) , (X^) , (4) number of campsites of nearest public campground {Xj q ) , (5) occupancy rate of the nearest private camp­ ground (X^^), and (6) population density of the township in which the campground is located * Among these variables only occupancy of nearest public campground was found to be negatively related to campground occupancy rate. The variable “number of years in business" was sig­ nificant at .10 before X^g entered into the equation, and the significance of X ^ , ground, regional location of the camp­ shifted from .04 to .14 level when X^3 entered 134 into the equation. the .15 level. Variable X^ and were significant at All other variables did not appear to be statistically significant, and they added only infinitesimally to the explanatory power of the overall model. As indicated in Table 14, the campground model of six significant variables was statistically significant at the .01 probability level, and explained approximately 30 percent of the variation in campground occupancy rate. The model with eight variables was still significant at .01 level but it explained only about 3 3 percent of the variation in the campground occupancy rate. General Conclusions Results of this study reveal that Michigan's pri­ vate campground industry is spatially characterized by a clustered distribution pattern. This locational pattern is primarily related to the highway system, and the loca­ tion of recreational water resources and notable tourist attractions. The highway system is likely to form a linear distribution pattern, whereas water and tourist attractions tend to shape a point location pattern. The campground location decision can be viewed as a selection of an array of spatial characteristics. But within such an array, certain characteristics are found to be more important than others. It is these important characteristics that make campground location different, not the entire array. When making locational choice. 135 campground developers may selectively concentrate on these key factors identified in this study. On a fairly general level, private campgrounds in Michigan are water-oriented. Presence of easy access to high quality recreational water is a key factor to the development and success (in terms of occupancy rate) of private campground enterprises. Despite some advantages which can be obtained by locating campgrounds near a major highway, the need for access to high quality recreational water would favor development of private campgrounds in lake resource areas. Easy access to population centers was found to be another significant factor positively related to the campground occupancy rate. This seems to confirm such a behavioral observation that camping for most families is a short-term experience which usually takes place in areas close to metropolitan areas. The urbanized area can never be a suitable location for campground development because of high land costs, and a lack of suitable environment for outdoor living. But urban fringe areas can be desirable sites for establishing private campgrounds--provided, of course, that land costs of these areas are modest, and that they have a quality resource base to enhance the camping experience. The influence of public campgrounds on private campground occupancy rate is significant. Private 136 campgrounds often share the advantages of unique natural characteristics with their public neighbors, but they are in fact, competing for customers. Finally, it is contended that campground location cannot be a matter of indifference to prospective investors, developers, and operators. Campground developers will face both long-run location decisions and short-run management decisions, with the former decisions restricting the range of latter opportunities. A poor campground location choice may not result in immediate and complete collapse of the enterprise; however, all campground enterprises may be affected in their profitability and in their consequent capacity for growth by the location choice. Uses and Limitations of This Study Multiple regression analysis in this study iden­ tified four major campground location factors as being important: (2) area (1) individual campground characteristics; (local and immediate) environment; characteristics; and (4) interdependence. (3) regional Analytical results derived from this study can be used to improve locational decisions of both private campground developers and public recreational planners. Determination of campground location factors can provide private campground developers with a basis for identifying attributes that are likely to be favorable or unfavorable to campground development in any area under 137 consideration. Private campground operators currently engaging in the business can also use the locational information to re-evaluate their campground locational advantages and determine their future investment plans and management strategies. For example, operators of those campgrounds suffering from low occupancy rate may re­ evaluate their campground location on the basis of the significant location decision factors. If they find that such low occupancy rate is due to, say, lack of quality water resource base to support their water-oriented activities, they may develop other popular recreational facilities such as tennis courts and swimming pools to attract more customers. For public recreation planning, this study can be used at two levels: the results of (1) by the local recreational planner to develop a preliminary evaluation of the prospects for encouraging private campground devel­ opment; and (2) by the regional analyst to predict the spatial distribution of campground growth. For example, the local recreational planner can use information devel­ oped in this study to help identify a set of attributes indicative of whether or not an area is suitable for private campground development. If a recreational planner has locational information for various recreation activ­ ities, he may devise a list of attributes for each activity to facilitate planning decisions. 138 There are a number of limitations of this study that deserve special attention. First, like most studies using statistical techniques, analysis of campground location patterns and location decision factors can give only statistical explanation based upon correlation between variables. In this sense, it should be realized that relationships derived from such an analysis are not neces­ sarily of the cause-effect type, and need not be useful for control purposes. As just mentioned, analytical results can be wisely used only to develop guidelines for preliminary evaluation of campground locations and for further experimentation that possibly would yield more insights into the campground location decision process. Second, explanatory variables associated with past campground location decisions may not assume the same patterns in future years. Predicting errors thus can be introduced into future campground location decisions if they are based upon outdated empirical relationships,^ In the present analysis, most data were collected before the gasoline shortage became a serious problem, and hence analysis based on such data may be underestimating the effect of relative location between private campground and potential market areas. ^There are two types of problem here: (a) the specification of the model may become outdated--structural change or (b) coefficients associated with the specified variables may change over time— outdated data. 139 Third, the present analysis is handicapped by the absence of financial data concerning campground operation. Such financial data are important because they would provide a more precise and meaningful explanation of profit-maximizing campground location decision. Lack of such financial data has required the analysis of camp­ ground location decision factors on the basis of the camp­ ground occupancy rate. Therefore, it was necessary to draw inferences about the profitable campground location from relationships based upon the campground occupancy rate. Making such inferences necessarily involves the assumption that a high campground occupancy rate is consistent with a profitable campground location. But the campground occupancy rate can be a meaningful indicator of a pro­ fitable campground location only when all campgrounds under investigation are operated at an efficient scale. Since we do not know whether or not the campgrounds included in this study were operated at the most efficient scale of operation, consistency of high campground occu­ pancy rate with a high level of profits is a questionable assumption. There could be a considerable gap between profitability and the occupancy rate. Implications for Future Research In realizing the limitations of this study and the needs for more precise investigation of locational impacts, 140 the investigator believes that the following research topics deserve special attention: 1. Research concerning definition and measurement of campground performance. What are the most effective and sensitive measures or indicators of campground business success, both in an absolute and relative sense? derived? How can such measures be What kinds of data are involved and how can these data be collected? A well-designed research study should be implemented to answer these questions. Methodologically, a comparative study may be designed to assess strengths and limitations of several potential measures, particularly under various assumed decision rules. 2. Research concerning determination of the trade­ off between management and locational effects. In studying private campground economics, there are arguments between those who emphasize management and those who pay more attention to locational choice. In fact, both management and location are important to a private campground business and are interrelated. The question that should be involved here is not a dispute between the two in terms of relative importance, but a consideration of the trade-off point between them. To what extent can management strategies be used to overcome locational disadvantages? How much additional profit can locational advantages bring for the campground owner or 141 operator? These appear to be the most crucial questions deserving special research attention. 3. Research concerning techniques for integrating locational effect into management programs. How to fully utilize locational information in the design of campground management programs is the most important question to be answered in this kind of research. Findings from such research could help campground opera­ tors fully utilize locational advantages to promote busi­ ness or design strategies to overcome locational dis­ advantages. It is important to discover from such a study how locational information can be used as a basis for improving campground management decisions. Success of any research program requires sufficient data of good quality. The present study was unfortunately handicapped by circumstances that make it difficult to obtain consistent and accurate data, particularly on camp­ ground income and costs. In future studies concerning private campground economics, effective ways and means for collecting primary data must be thoroughly developed before actual field work proceeds. Moreover, it would be very helpful if high quality secondary data could be made available on a consistent basis. Existing campground directories may provide a good source for secondary data. But they have problems of incompleteness and inconsistency. For better results, an annual private campground directory 142 should be compiled on the basis of license records which must consist of: specifications, (1 ) date of establishment, (3) facility types, and (2 ) locational (4) total area and size of each campground currently in operation. It is hoped that research topics outlined above will be carried out in the future with consistent and high quality data. It seems clear at this time that the implications for future study lie in the direction of further refine­ ment of the analytical model and improvement of data collection and organization methods. It would be useful to try to extend the present analysis to additional aspects of relationships, particularly those relating to manage­ ment strategies and activity programming. In analysis more attention should be directed to the formulation of specific models for different campground types, and less to the kind of general analysis achieved in this study. BIBLIOGRAPHY BIBLIOGRAPHY Books Babbie, Earl R. 1973. Survey Research Methods. Belmont, California: Wadsworth Publishing Company, Inc. Berry, Brian J. L. and Duane P. Marble. 1968. Spatial Analysis: A Reader in Statistical Geography. Part II, IV, & V. Englewood Cliffs, N .J.: Prentice-Hall, Inc. Carpenter, Betty S. 1971. Practical Family Campground Development and Operation. Martisvllle, Indiana: American Camping Association. 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The Role of Customer Satisfaction in "Managing Commercial Campgrounds^ USDA Forest Service Research Paper NE-105. Upper Darby, Pennsylvania: Northeastern Forest Experiment Station. 1968b. The Role of Fees in Camper1s Decisions. USDA Forest "Service Research Paper NE-118, Upper Darby, Pennsylvania: Northeastern Forext Experi­ ment Station. 1969a. "The Family Camping PhenomenonMotivation-Ways and Means-Accommodations," Proceedings for Fourteenth Annual Southeastern Park and Recreation Training Institute for Planning Maintenance and Operation. Raleigh: North Carolina State University ^February 25-28): 14-19. 1969b. Campground Marketing: The Heavy-Half Strategy. USDA Forest Service Research Note NE-93. Upper Darby, Pennsylvania: Northeastern Forest Experiment Station. and Dale P. Ragain. 1971a. Trends in Camping Participation. USDA Forest Service Research Paper NE-183. Upper Darby, Pennsylvania: North­ eastern Forest Experiment Station. and Dale P. Ragain. 1972. Campground Marketing— The Impulse Camper. USDA Forest Service Research Note NE-150. Upper Darby, Pennsylvania: North­ eastern Forest Experiment Station. , Paula L. Cormier, and Steven C. Maurice. 1972. The Commercial Campground Industry in New Hampshire: A Report on a 1971 Campground Census. USDA Forest Research Paper NE-255. Upper Darby, Pennsylvania: Northeastern Forest Experiment Station. 148 ________ . 1973. Growth Potential of the Family Camping Market, USDA Forest Service Research Paper NE-2§2. Upper Darby, Pennsylvania: Northeastern Forest Experiment Station. ________ and A. C. Haaland. 1974. Annotated Bibliography of Camping Market Surveys. USDA Forest Service General Technical Report NE-11. Upper Darby, Pennsylvania: Northeastern Forest Experiment Station. Lime, David W. 1971. Factors Influencing Campground Use in the Superior National Forest of Minnesota. USDA Forest Service Research Paper NC-60. St. Paul, Minnesota: North Central Forest Experiment Station. McClellan, Keith and E. A. Medrich. 1969. "Outdoor Recreation: Economic Considerations for Optimal Site Selection and Development," Land Economics 45 (2): 174-182. Moeller, George H. 1971. Growth of the Camping Market in the Northeast. USDA Forest Service Research Paper NE-202. Upper Darby, Pennsylvania: North­ eastern Forest Experiment Station. Montville, Francis E. 1964a. Private Campgrounds in Maine: Part 1, Location, Characteristics, Facilities. Agricultural Business and Economics Extension Bulletin 122. Orono: University of Maine, Cooperative Extension Service. ________ . 1964b. Private Campgrounds in Maine: Part 2, General Characteristics of the Users of PrivateCampgrounds in Maine. Agricultural Business and Economics Extension Bulletin 123. Orono: Univer­ sity of Maine, Cooperative Extension Service. Muehrche, Phillip. 1972. Thematic Cartography. Commis­ sion on College Geography Research Paper Number 19, Association of American Geographers, Washington, D.C. Peucker, Thomas K. 197 2. Computer Cartography. Commis­ sion on College Geography, Resource Paper No. 17, Association of American Geographers, Washington, D.C. 149 Tadros, M. E. and R. J- Kalter. 1971. "A Spatial Allocation Model for Projected Outdoor Recreation Demand: A Case Study of the Upstate New York Region," SEARCH-AGRICULTURE, Vol. 1, No. 5, New York State College of Agriculture at Cornell University, Ithaca, New York. "The Profits in Campgrounds." 2232 (June 10): 42. 1972. Business Week, No. Van Doren, Carlton S. 1966. "Destination Models: Development of a Camping Attraction Index for Michigan State Parks," in Michigan Outdoor Demand Study, Technical Report Number 6 , Department of Resource Development, Michigan State University, East Lansing, Michigan. Van Lier, H. N. 1973. Determination of Planning Capacity and Layout Criteria of Outdoor Recreation Projects. Agricultural Research Reports 795. Centre for Agricultural Publishing and Documentation, Wageningen. Wager, J. Alan. 1963. Campgrounds for Many Tastes. USDA Forest Service Research Paper INT- 6 . Ogden, Utah: Intermountain Forest and Range Experiment Station, June. Wennergren, E. B. and H. H. Fullerton. 1972. "Estimating Quality and Location Values of Recreation Resources, Journal of Leisure Research 4 (3): 170-183. Wilder, Robert L . , comp. 1972. Campground-Development Guide: Planning Recreation Opportunities for Income and Tourism!! Special Report 37 0. Corvallis: Oregon State University, Extension Service, October. Wilkins, Bruce T. and Clifford W. Loomis. 1971. A Study of Campground Businesses in New York State. Agricultural Economics Research Bulletin 329. Ithaca, New York: Cornell University, Agricultural Experiment Station, May. Unpublished Materials Hehn, Donald Russell. 1968. "Fundamental Social and Economic Aspects of Commercial Outdoor Recreation Enterprises in Michigan." Master’s thesis, Michigan State University. 150 Hodgson, Ronald Wayne. 1971. "Campground Features Attractive to Michigan State Park Campers.” Master’s thesis, Michigan State University. Michigan Department of Public Health. 1971. Publicly and Privately Owned Campgrounds: Act 171! of tne Public Acts of 1970 and Administrative Rules. Lansing, October. _________. "Licensed and Proposed Campgrounds in Michigan." 1972. Lansing, February. Wang, Darsan. 1971. "Camper Preferences and Campsite Characteristics at Ludington State Park, Michigan." Master's thesis, Michigan State University. wittick, Robert I. 1973. GEOSYS; An Information System for the Description~and Analysis of Spatial Data— Version 2 . Technical Report Number 7 3-6, Computer Institute for Social Science Research, Michigan State University. East Lansing, Michigan. APPENDIX I INTRODUCTORY LETTER AND QUESTIONNAIRES APPENDIX I INTRODUCTORY LETTER AND QUESTIONNAIRES Introductory Letter for Initial Mailing Michigan State University East Lansing Department of Resource Development Building Michigan 48823 Natural Resources September 21, 1973 Dear campground operator; We are conducting a location study of the private camp­ ground enterprises in Michigan. The primary objective of this study is to investigate the relationship between campground business performance and location of campgrounds in the state. The information derived from this study will enable us to develop guidelines that may have value to you in making future management decisions. Your campground has been randomly selected for this loca­ tion study. Please assist us by completing the enclosed questionnaire and return it to us with the stamped selfaddressed envelope. We can assure you that your answers will be held in the strictest confidence. They will only be used in a pool with all other replies to show the relationship in question. Please give us your full support and accurate response to this inquiry. Your enthusiasm is the key to the success of this study. The results of this study will be forwarded to you as soon as it is completed. Sincerely yours, Rex J. T. Yu Graduate Research Assistant Department of Resource Development 151 152 Introductory Letter for the First Follow-Up Mailing Michigan State University East Lansing Michigan 48823 Department of Resource Development Natural Resources Building October 12, 1973 Dear Campground Operator: This is a letter to remind you of our Campground Location Survey. You recently received a questionnaire from the Department of Resource Development, Michigan State Univer­ sity, for the study of private campground locations. The information derived from the study will be used to develop an extension bulletin which will assist private campground operators in making management decisions. He believe the results of this study will be of value to you. Your report is needed to make this study as accurate as pos­ sible. If you have tionnaire to us, and support. If and return it to already completed and returned the ques­ we sincerely appreciate your assistance not, please complete the questionnaire us promptly. Thank you. Sincerely yours. Rex J. T. Yu Graduate Research Assistant Resource Development Department 153 Introductory Letter for the Second Follow-Up Mail Survey Michigan State University East Lansing Michigan 48823 Department of Resource Development Natural Resources Building November 9, 197 3 Dear Campground or Trailer Park Operator: About three weeks ago we sent you a questionnaire regard­ ing a locational study of both private campgrounds and trailer parks in Michigan. The information derived from this survey study will enable us to develop a research bulletin which may have value to you in making your future management decisions. To insure that the results of this study are accurate and relevant to your management decisions, we need your infor­ mation inputs. Your accurate response is the key to the success of this study. Please give us your full support and assistance. In case you mislaid the original questionnaire that we sent you, we have enclosed an additional copy. Please complete this copy and return it to us with the enclosed envelope as soon as possible. Thank you. Sincerely yours, Rex J. T. Yu Graduate Research Assistant Resource Development Department RJTYilb Enclosure 154 Private Campground Location Study Department of Resource Development Michigan State University * * * * * * * * * * * * * * * * * * Date:_______________ ITEM: GENERAL CHARACTERISTICS 1. When did your campground first open? ____ ,_______ month year 2. Didyour campground stay open year around in 1972? Yes___ , please skip to question 5 No____ , please continue with question 3 3. When did your campground open for the season day 4. month When did your campground close for the season in 1972? day 5. month How many campsites were included in your campground at the beginning of the season in 1972? modern sites, 6. in 1972? primitive sites, total sites Did your campground provide separate sites for tent and trailer campers in 1972? Yes No If yes,please indicate the number of sites of each type in your campground: tent sites, 7. trailer sites, total sites. Was your basic fee charged in 197 2 varied according to campsite location? Yes No___ If yes, please give only the average rate for a site If no, please give the basic rate for a site Per day Modern site: $ Primitive site: $ Per week $ $ Per season $ $ 155 8. What was the average occupancy rate at your campground in each of the following months of 1972? (Note: Please give your best estimates.) Average Occupancy Rate for the month, in % Month May % June % July % August _________ September * % ITEM II: LOCATIONAL CHARACTERISTICS 9. Is your campground located in a heavily wooded area? Yes 10. 11. No___ Is your campground located adjacent to a natural lake? Yes , skip to question 13 No , continue with question 11 What is the distance from your campground to the nearest natural lake? miles 12. Which of the following best describe the location of your campground? Located adjacent to an artificial lake or pond Located adjacent to a river Located adjacent to a small stream Not located adjacent to any body of water 156 13. Which of the following water-oriented activities were available on your campground in 1972? (Please check whatever you have) (1) motor boating, (4) canoeing, boating, 14. water skiing, (3) (6 ) fishing, row paddle boats. No___ Was snowmobiling activity available in 1972 on your campground or within one mile of distance from your campground ? Yes 16. swimming, Was snow-skiing activity available in 1972 on your campground or within one mile of distance from your campg ro und ? Yes 15. (7) (5) (2) No___ Was there any golf course located within 15 minutes of driving distance from your campground in 1972? Yes No___ ITEM III: SPATIAL c h a r a c t e r i s t i c s 17. What is the distance from your campground to the nearest tourist attraction? _________ miles Name of the tourist attraction: ________________________ 18. What is the distance from your campground to the nearest publicly operated campground? _________ miles Name of thepublic Type of service it provides: modern, campground: _________________________ (please check one) primitive-rustic 157 19. What is the distance from your campground to the nearest privately owned campground? miles Name of the private campground: _____________________ Type of service it provides: 20. modern, primitive What is the distance from your campground to the nearest state or inter-state highway exit? miles Name of the highway: Where to exit: 21. What is the distance from your campground to the nearest city or town? ______________ miles Name of the city or town: _______________________ ITEM IV: FINANCIAL ASPECTS 22. Approximately how much did you have invested in your campground facilities by the end of 1972? (Please base your estimates on the 1972 price Tevel and account for all buildings, structures, and installa­ tions you invested for your campground business operation, except land property.) $________________________ 23. Approximately how much did you spend on advertising your campground business in 1972? $________________________ 24. What was the approximate total expenditure for operating your campground business in 1972? (Note: If you didn't record your expenditure in the following categories, please answer item 3 only.) (1) Total expenditure for operating rental campsites: $ 158 (2) Total expenditure for operating other related income activities on the campgrounds: $ _________________________ {3} Total expenditure for all business operations on your campground (that is# (1 ) + (2 ): $ _________________________ 25. What was the approximate total slaes income from your campground business operation in 1972? (Note: If you didn't record your income in tHe following cate­ gories, please answer item 3 only.) (1) Total sales income from campsite rentals: $_________________________ (2) Total sales income from other related income activities on your campground: $_________________________ (3) Total sales income from all business operations on your campground (that is, (1 ) + (2 ): $_________________________ 26. Which of the following statements best describes the owner's goals for operating the campground? To give myself and/or my family something interesting to do. We enjoy operating the camp­ ground. To receive additional income from the campground business to supplement my family income. The campground business is my secondary source of income. To receive enough income from the campground business to support my family for the entire year. The campground business is my primary source of income. Others (write in) 159 27. Was the land which you developed into a campground originally owned by you and/or your family7 Yes No or Other___ (Please explain:________________________________________ ) If yes, please continue with question 28 If no and other, please skip to question 29 28. What are the reasons that you decided to develop your land into a campground? (Please identify three main reasons and indicate their priority by filling the number (such as 1 for the highest priority, 2 for the second priority, and 3 for the third priority) in the corresponding space.) Because the land is located close to a population center. Because the land is located close to a quality water body such as lake or river for recreational use. Because it has an easy access to state or inter­ state highway. Because the land is located far away from an urban environment. Because the land is located close to a publicly owned park or other tourist attraction. Purely personal preference Other 29. (write in) What are the reasons that you chose to develop your campground at the present location? (Please identify three main reasons and indicate their priority by filling the number (such as 1 for the highest priority, 2 for the second priority, and 3 for the third priority) in the corresponding space.) Proximity to a large population center Availability of a quality water body such as lake or river at the location for recreation use 160 Easy access to state or inter-state highway Remote from urban environment Proximity to a publicly owned park or other tourist attraction Relatively low property tax Relatively low labor costs {wages, productivity) Purely personal preference Others (write in) ___________________________________ Thank you for your time and effort in completing this important phase of our research. If you have any further questions on this research project, please contact me: Rex J. T. Yu Research Assistant Department of Resource Development Michigan State University East Lansing, MI 48823 Tel: (517)-353-7982 161 Introductory Letter for Mail Survey of Public Campgrounds Michigan State University East Lansing Michigan 48823 Department of Resource Development Natural Resources Building September 7, 197 3 Dear Sir: We are conducting a campground location study in which the relationship between publicly and privately operated camp­ grounds will be investigated. The information derived from this study will help both private and public sectors plan for additional campgrounds and for improvement of their camping services in the future. Enclosed herewith is a stamped self-addressed envelope and a questionnaire for each of the campgrounds or trailer parks you operate, please assist us by completing the questionnaires and return them to us. The results of this study will be forwarded to you as soon as it is completed. Your cooperation and accurate responses to this inquiry will be greatly appreciated. Sincerely yours, Rex J. T. Yu Graduate Research Assistant RJTY:lb Enclosure 162 Private-Public Campground Location Study Department of Resource Development Michigan State University Name of campground or trailer park:________________ Location: 1. Date: When did this campground first open? month 2. year Does this campground stay open year around? Yes No___ If yes, skip to question 5 If no, continue to question 3 3. When does this campground open for the season? date 4. month When does this campground close for the season? date 5. month How many campsites were included in this campground at the beginning of the season in 1972? modern sites, 6. total sites How many campsites does this campground have now? modern sites, 7. primitive sites, primitive sites, total sites Does this campground provide separate sites for tent and trailer campers? Yes No If yes, please indicate the number of sites of each type in this campground: tent sites, trailer sites, total sites 163 8. 9. What was the daily charge per campsite at this camp­ ground in 197 2? Modern site: $_________ Primitive site: $________ Tent site: Trailer site: $ ______ $________ Did you limit the length of stay for the camper at this campground in 1972? Yes No___ If yes, please indicate the limit: ________ days 10* Did you require that each camper obtained a permit to camp at this campground in 1972? Yes No___ If yes, please indicate the number of permits issued in each of the following months of 1972? Month May Number of Permits Issued _______ June___________________ _______ July___________________ _______ August September 11. _______ _______ What was the average occupancy rate at this camp­ ground in each of the following months of 1972? Month Average Occupancy Rate for the month, in % May % June % July % August % September % 164 12. What: is the distance from this campground to its nearest privately operated campground? _______________ miles Name of the private campground: _________________ Location of the private campground: _____________ APPENDIX II DISTRIBUTION OF PRIVATE AND PUBLIC CAMPGROUND FACILITIES BY COUNTY, WITH REGIONAL AND STATE TOTALS APPENDIX II DISTRIBUTION OF PRIVATE AND PUBLIC CAMPGROUND FACILITIES BY COUNTY, WITH REGIONAL AND STATE TOTALS vAfhM) pACi^lTf^r: r«**IVJh-TI' cant OlftTftlAUTIOCOUNT N or .IAIK TOTAL. . i|VATF P U O L TC * M l FH MO c fu ttr v w r - iO ft c rt N ti 36 4? 4ft 49 A? t * k r * |* - jftr -n O 4 A A 4 lo |^ fO C W V T f^C ) 1 14 4 s 3 ft 3 1 ? 1? r»1 cm |nf,o^*u* r,orrm r -iif* m 'TiFr,h TiiP'ibu P 1a ^ t - i rf > rr vrr ‘ 1 iw-tiP 1_iirr -i■> w Ar 9» ir T Tr *Uft F,f l*ir*"»-ur* ftHUl'lA^i* r'PAFT nf GtfiMftL t o t a l AVrPAGT A r n o N if ALrONA ALffNft ANTOt** AUTN1C ft*V *FN?tr fM^ri r vot* S9 ♦ ft TA U li Aft It4 76 30 161 ftTM 7*> 137 99 ji ft i o 70 ?73 1 3^i 04 4 — 7 * r*.*o-.,TN 15AM *"L1. * 3 3 L i ^ r L tF L tM U m I n I M T F m a *>ON 11 7 9 13 1*6 3l 0* |O 1 9O 6 7?l> iiftCO^Ti f t7 *N n.*NL Oftcrf 6 wii 4 0 • f l M T , n ( 4 * NPVAVOOJF»*cv 64 OC* A N * 43 JO 60.3 tp p n ^ r n ’.mos* t-| ft! t I 3 13 7 ft * r^i- I N P f* |O N tl |1 t \ | p k|6ANCH |7 rAt.^OiJM tl 4 ri's to in r u i» to m ? n M i c ’i t 96 ftOATtOT 3 ft H |iL 4 0 A |.r 3* h f.rN-tM f jm 1I 34 3ft 33 |TW1|A £ PI 3 44 IIP ffO l F n I ^ ff L J v l* "M O N 41 rnir 7 10 £9£ 3 6 7 ft 19? ?F-, P 13 £ * 0 O 4VFOAGF ?7A fv lrAT F TOTAL A PAr^* ■'St IJ.-* ini 1 T* >?7 ^ a T ^ t * a , *k in A f f i “ ( ‘T , i > ' ' u * i r i T>f- i < * ft + m if f f 11 A j ' * r f r ' — — — —■ — — — — • _ — — » 61*97 v n M G®*Gt 1— — *» 6??«* I S O * 1? Li 4 i Orf.tfHlAt T O T A L 3 <".ft 3 tft ? TUVTCX-A I £1 I. 6 *6 16 IS 30*^ £1 0 t;T ST 9 ?ft a ?S 7 VAN M'Jf'f'M HAvNr 779 t t ftl7 Jft 7 4 WAr MT|NAW ft 1 3 J 1 t J 77 7ft 79 7 M 463 e,«r.|MAw a 1 1S4 3 OTTAWA 73 C l.A O jn ^ 'P H 10 144 7?9 1 39 6*1 7(1 76 ■‘4MU 7 * «, r v A r/.rt 34 19? £ t 673 £097 OTJ *1 60 12 2 3 107 97 36 £0 ) 16 1£ 1 62 32 ■‘ O ts 1 16 1*4 66 96 64 £430 t O * 9 ft — 1 I 3 9 4 6 3 4 1 s l £ 1 ft 7 a t £ 1 0 7 3 S 3 1 16 ■v — 4*; i 611 374 1 3 m u *r * f.r,N — 09 63 161 At 122 _•6 14 ft 160 — - H 6 W'>jrOr MONTC41 ** 6 | 46 67 to 4 7 7 ?6A S® a £ i m 4 £ 6 4 30 | ftfl £31 406 76 in £6 161 |9 * W 10 *4 ? 94 7 7 «*rrvp z its 1O f * 13ft 671 r w 13 Ift n 6 4 i IS 1o n _ n4n •j 30 3® 7 « *r*| A-UTfvO 1 60 67 41 I 4 [Nf-Him AO 0| At 1?SS 47ft TSft 6 7 7 h 714 6?1 no 1 *0 SM t l* I 04 41 £73 3<» I6 N — 7 4 7 A S 11 4 6 _ JtlS 9 14 SO t?M3 6n «Sft l i t A H * GAm n *n o ¥ 47 a *4 too 0 *6 63 44? it A 3 U tV 39ft £ AVr°*&F £f t 'S4 ?ns 4 4 T 0I3 S3 2 46 161 JO regional total 120 4?4 SO | 7 7ft £ r tnt-t- -y *■• I 2 t 67? t3S a S* rtT '-F 3 0 107 £43 6 tQ 470 19 0 14 0 220 9ft O fi6 4 139 37? to o 4ft I £4 7 799 •z ^ o I 1972 l* r i* 6 f t 6 70 tos - 37 4 f> * i 4* S | S i ns^OfiA 3 3 £ 4 t | t 13 9 1 s t P t 3 4 OS 1 I VO •rao II fte.f-rCH-fc 779 ISO 171 1 Of) tftS ?3L AT-i 7f>0 IfeO 44 400 *s 6 6 ft A ?4 7ft ft4 4ft9 *67 ft fp^MT r 6ft 6® t 3 3 I I ? 3 3 1 1 4 J ? 3 1 1 ?64 * I» I I 4 47 tlft to 7 ft '*4 | ML 1 Pft 13 7 1/ I l c,t 1*3 to t 3 »t if t9 . 407 l^ ft in s 4 16 1 6 4 *V t 101 6 6 t ft A Tl>4VFP^ as £ 6 t 3 T 3 3 A 4 3 1 J* 1 •; a 5 ? 49 ft | a rvnovGan (ft f L ^ ,r {4 ttft V' "'OT I I* 1 s ? Fitirpp'F'Mft ftP'Ll ft-lJF* I'jf i y r i 1 ') — * — — i. _ It — 7 t l £7| 1£ 1 1 7 * ?9 If* I * CitH ■, T f r a m •(<■'M ■'t ►MJWfFW r 'r D I V J ! |M r, r.fftA -c" 1|1 ( *« 1. f A M O f i f f T U f F i ^ | 9 | " " L V J ' ** ''* f ' O I M ‘ >T A T l -' M i l * ' , «' Uf t Tr “ I I I r * - ' i N r r r ^ r .71 ,a i> ,|tc * , rr ® 6 1 * 64 £■ £ £ t *2 6 1 -2 9 0 *6 4 iii* * 0 **s £ 0 3 I *6® £6 10 11 # t 7 20 £ t 6 0 6 £1 * £ £6 4 13 >6 12 10 1 7 14 9 19 t 1 0 6 4 6 16 3 13 ft 1 3 39 1 336 1036 10 *1 1 304 443 ftftft 60 47 44S 0 44 4 I6 ft4 397 it s £66 S £66 «7| *r» a (41 | 9 7 l (. ' " ‘ I - . ’ ! ** fti# r 165 t fv* A T r f t TufcH -H|P I O** 4 , __ , T f*H '0F-W*IFVP |r. if l1V ,u u a u i: rAM ^'iOW N ft r ft^J 'i,t '-up- M i‘|p.p ln'.'Tt •iJi'Hlif/’jA* -Of I A T I<1W <-M r I- .■ p.-'i A “ 1' •11 i•A m # *?4 6 ^ 7 ft 1 4 4 * 17 1 ir»M V t »i A H ( n w ' M i i i r t ' >■■ « " j j m | i . " k m | , • ■11 . jv+■» r -UT ^ f u m 1 W t f ' t f ^ I | r > 7 1 1* ft*** ■.i •^ - 1 f.r i P■* , ' A l l . P ,J | 1ft ■^ **1#hIF.a*4 r i A * - r T * **<■ P »A t * T J *60 t-(M 1 « v® ? ** 3 Oa S'J \ *6 ® O* 1 t 0 * is 0*6 ® 0 *0 0 0 * 74 £ •0 4 f l* 7 | 0 * t£ 3 *7 4 0*1 * 1* 0 0 0 *6 9 1 t-r.s 0i> s6 t * )A 0 *6 7 2 *O t 1 *£ 6 £ •2 7 r> 0 .4 1 *7*^1 1 *1 1 1 *?'< 0 * 1i I *4 *t 0*4 7 6« I ft ®63 1440 £66 643 6£3 1047 ts ^ s 1296 0 607 It® 664 AAt 1 1o 6.;= £I,TPR 1* "E*j*E ..31 .37(64 ,13*62 .13*97 .37365 12.41/46 .Li; .4325! ,26365 .1*451 ,2*392 15.6*til •tl, ,56417 ,34243 ,(567* •lUJt 6.(NllS ..53 .61140 .37*30 ,031|7 ,041*6 3,6/141 Note: For description of variables, see Appendix III. OVERALL £ IISNI'IS 12.*1*46 15.*4212 13.3655} 11,3*634 •061 .03! ! *ta» APPENDIX VI SELECTED CAMPGROUND STATISTICS APPENDIX VI SELECTED CAMPGROUND STATISTICS This appendix provides a set of statistical sum­ maries which serve to facilitate a better understanding of the general characteristics of the private campground industry in Michigan. These statistical summaries were based on data obtained from the mail questionnaire survey specifically conducted as part of the present study. For convenience of presentation and discussion, data are arranged in two major categories, enterprise characteristics and spatial relationships. Specific values in each cate­ gory are displayed in tabular form accompanied by a brief description. 174 175 Enterprise Characteristics Appendix Table 1.— Goals of Michigan Private Campground Owner. Number of Observations % Distribution Cumulative % As primary source of income 76 34.55 34. 55 As secondary source of income 90 40. 91 75.46 Personal prefer­ ence or others 54 24 .54 100.00 220 100.00 Goals Total valid observations This group includes all respondents indicating that they were not operating their campgrounds under income motivation. Rather, they claimed that they operated camp­ grounds for providing services for club members, for family activities for personal satisfaction by meeting people and friends, or for a retirement hobby. 176 Appendix Table 2.— Number of Years in Business Operation. Years in Business 3.0 - less Number of Observations % Distribution Cumulative % 119 40.6 40. 6 3.1 - 6.0 58 19.8 60.4 6.1 - 9.0 47 16.0 76. 5 9.1 - 12.0 13 4.4 80.9 12.1 - 15.0 19 6.5 87. 4 15.1 - up 37 1 2 .6 100.0 293 1 0 0 .0 7.435 Standard Deviation Total Valid Observations Average Number of Years 8 .658 177 Appendix Table 3.— Basic Daily Charge of Campsite Rental. Daily Rate Number of Observations % Distribution Cumulative % 2.00 - less 26 9.8 9.8 2.01 - 2.50 45 16.9 26. 7 2.51 - 3.00 87 32.7 59.4 3.01 - 3.50 61 22. 9 82. 3 3.51 - up 47 17.7 100.0 Total Valid Observations Average Daily Charge 266a $3,111 100.0 Standard Deviation $.756 aExcluded 23 campgrounds which provided service only on a seasonal-lease basis. 178 Appendix Table 4.— Summary of Monthly Average Occupancy Rate® for Public and Private Campgrounds, 1972. „ ________ , SSSXhi!? H Number of Valid Observations State parkb campground 70 60.63 45.85 County,c township, municipal, and village campground 46 56. 83 44. 72 250 49. 33 41.49 Private^ campground 3-month season (June-August) average (in %) 5-month season (May-Sept.) average (in %) aThe occupancy rate is defined in percentage terms which may be computed by dividing the total number of campsite-days actually occupied by the total number of campsites days available for rental during the season. ^This occupancy rate was estimated from state park campground statistical records which were made avail­ able by courtesy of the Park Division, Michigan Department of Natural Resources. cOccupancy rate was computed from responses obtained from the mail survey of public campgrounds in this category. ^Occupancy rate was computed from responses obtained from the mail survey of private campgrounds. 179 Appendix Table 5.— Summary of Monthly Average Occupancy Rates for Michigan Private Campgrounds. _______ _ . inpercent v 3-month season Uuly-August, No. % 5-month season (May - S e pt., No. % 1.0 - 10.0 15 6 .0 23 9. 3 10.1 - 20.0 23 9. 2 33 13.4 20.1 - 30.0 40 16. 0 50 20.2 30.1 - 40.0 40 16. 0 37 15.0 40.1 - 50.0 30 1 2 .0 32 13.0 50.1 - 60.0 22 8.8 26 10.5 60.1 - 70.0 21 8.4 7 2.8 70.1 - up 59 23.6 39 15.8 250 1 0 0 .0 247 1 0 0 .0 Total Valid Observations Average Occupancy Rate 49.327% 41.485% Deviation 27.716% 25.924% aFor sources and definition, see Appendix Table 4. Appendix Table 6.— Relationships Between Occupancy and Water-Oriented Recrea tional Activities,3 3-month occupancy rate Number of Campgrounds Percentage of Campground Having: Motorboating Swimming Fishing Canoeing Waterskiing 15 20.0% 20.0% 53.3% 33.3% 13.3% 10.1 - 20.0 23 56.5 73.9 91.3 65,2 43.5 20.1 - 30.0 40 27.5 62.5 70.0 52.5 15.0 30.1 - 40.0 40 57.5 72,5 85.0 65.0 37.5 40.1 - 50.0 30 40.0 73.3 76.7 36.7 26.7 50.1 - 60.0 22 59.1 90,9 90.9 77.3 40.9 60.1 - 70.0 21 33.3 76.2 81.0 61.9 28.6 70.1 - up 59 72.9 84.7 86.4 64.4 62.7 250 50.0 72.8 80.8 58.4 37.2 1,0%- 10.0% Total Campgrounds aFor data sources, see Appendix Table 4. 181 Appendix Table 7.— Size Distribution of Private Campgrounds by Different Periods of Establishment.® No. of Campsites 1964 & before No. % 1965- 1969 No. « 1970- 1973 No. % 10 - 30 59 57.3 57 35. 8 88 32. 8 31 - 60 22 21.4 45 28. 3 76 28. 4 61 - 90 8 7.8 24 15. 1 36 13. 4 91 - 120 5 4.9 18 11. 3 46 17. 2 121 - 150 5 4.9 4 2.5 11 4.1 151 - 180 3 2.9 5 3.1 3 1.1 181 - 210 1 1.0 0 0.0 1 0.4 210 - up 0 0.0 6 3.8 7 2.6 Observations 13 103 1 0 0 '0 159 1 0 0 -° 268 100-° 1 Average Number of CS per CG 45.3 64.5 66.3 This table is compiled on the basis of the follow­ ing data sources: (1) Private Campground License Records, Michigan Department of Public Health, 1973. (2) Campground and Trailer Park Guide, Rand McNally & Co., 1969 and 1973. (3) Private Campground Survey designed as a part of the present study. ^Campgrounds have less than 10 campsites are not included in the above table. 182 Appendix Table 8 .— Size Distribution of Seasonal and YearRound Campgrounds in Michigan (private).a No 0 £ _ campsites Seasonal Campgrounds Nq^ % Year-round Campgrounds Nq< % Total Campgrounds Nq> % 10 - 30 163 41. 79 38 27.14 201 37.92 31 - 60 107 27. 44 38 27. 14 145 27.36 61 - 90 48 12. 31 20 14. 29 68 12. 83 91 - 120 47 12.05 22 15. 71 69 13. 02 121 - 150 11 2.82 9 6 .43 20 3.77 151 - 180 8 2. 05 3 2. 14 11 2 .08 181 - 210 2 .51 0 .00 2 .38 211 - more 4 1. 03 10 7.14 14 2.64 390 100.00 140 100.00 530 100.00 Total Average 54. 59 81 .56 61 .72 Campgrounds with less than 10 campsites are not included in the above table. For data source, see Appendix Table 7. 183 2. Spatial Relationships Appendix Table 9.— Summary of Distance Measures from Private Campground to a Natural Lake Location. Distance 13 in miles Number of Observations % Distribution Cumulative % 0.0 - 0.2 175 61. 6 61.6 0.3 - 1 .0 32 11. 3 72.9 1.1 - 2.0 12 4.2 77.1 2.1 - 5.0 31 10. 9 8 8 .0 5.1 - 1 0 .0 22 7.7 95. 8 10.1 - 20.0 12 4.2 100.0 284 1 0 0 .0 Total Valid Observations Average Distance . .969 miles Standard Deviation 4.158 miles aSources: Based on responses from the private campground survey designed as a part of present study. ^Distances are measured in actual mileage as reported by the campground operator. 184 Appendix Table 10.— Distribution of Private Campgrounds by Distance to Nearest Competing Private Campground.a Distance in miles Number of Observations % Distribution Cumulative % 0 .1 - 1.0 54 18. 5 18. 5 1.1- 5.0 112 38.4 56. 8 5.1 - 10.0 74 25.4 82. 2 10.1 - 15.0 27 9.2 91. 4 15.1 - 20.0 17 5.8 97. 3 20.1 - 30.0 6 2.1 99. 4 30.1 - 90.0 2 .6 100.0 292 100.0 Total Valid Observations n 'ZmZ Distance 6 .535 miles Standard Deviation 6.287 miles a„ Source: Based on responses from the private campground survey designed as a part of the present study. Distance are measured in actual mileage from the campground to its nearest neighbor as reported by the campground operator. 185 Campgrounds by Appendix Table 11.— Distribution of Private 1 Distances to the Nearest Public Campground. Distance *5 in miles Number of Observations % Distribution Cumulative % 0.1 - 1.0 19 6.7 6.7 1.1 - 5.0 68 24.1 30. 9 5.1 - 10.0 72 25.5 56.4 10.1 - 15.0 45 16.0 72. 3 15.1 - 20.0 28 9.9 82.3 20.1 - 30.0 28 9.9 92. 2 30.1 - 90.0 22 7.8 100.0 282 1 0 0 .0 Total Valid Observations Average Distance .- .873 miles Standard Deviation 11.859 miles Source: Based on responses from the private c ground survey designed as a part of the present study. ^Distances are measured in actual mileage as reported by the campground operator. 186 Appendix Table 12-— Distribution of Private Campgrounds by Township Population Density.a Persons per sq. mile Number of Observations Q ^ . . •. . • % Distribution ^. Q Cumulative * 40 13.7 13.7 30. 0 78 26. 6 40. 3 - 50. 0 58 19. 8 60.1 50. 1 - 1 0 0 .0 84 28.7 8 8 .7 1 0 0 .1 - 150. 0 17 5.8 94. 5 150.1 - 2 0 0 .0 5 1.7 96. 2 200.1 - 300. 0 5 1.7 98. 0 300.1 - up 6 2.0 1 0 0 .0 293 100.0 1 0 .0 - 10.1 - 30. 1 less Total Valid Observations aSource: Based on the responses from the private campground survey designed for the present study. APPENDIX VII FACTORS INFLUENCING PUBLIC CAMPGROUND DISTRIBUTION APPENDIX VII FACTORS INFLUENCING PUBLIC CAMPGROUND DISTRIBUTION STliarOF PRIVATE CA^SITES 4nQC3U*Tr C-<*RAlTERtSTICS FILE MMHE (CREATION DATE • C7/J//74 I ....... * * ...................... * t • • SEPEhDtNT variable., varccj pjc* V 1 » ! a 3 L E < S 1 E M E h ED O n S T E P N U M B E R multiple s *5CLaRE .*a*7* .463J? s : ; tev;i.rion 27i.*:2G3 LES B VARI ABL E 07/;7/74 " 0 1 T I P L E f to eute* 7.. VALUft 2,J9s:oo.. tolerance or 7. reiiojal 7j, I N T*E STD e r r o r 3 7.7453716 ;m 4 :9 :« VAPOi * 337.66165 1.2.342*5 .■a p ; i : -11:341566 1.6973231 * a» ; ; * -,753*17*1 VAPcat ,7955745: .1276574; VA*0;6 >65 21471 24754344* 2*T9037a9 2*4,47122 ( CONSTANT) f»level rr t o l ER a n c E -level 7.1*1569766:-J2 i his-irrici=n' VARI ABLE EME'Eo removed vacc Ta vap;:t va»;:» VARCIC v**;:* v a r ;o* VA R9 1 * E „*i' . for 16.3i?:t 3.7L2J4 4.71656 .7»:js 7.3J122 3.6631* 4.2*533 t .31* 5 . 7 . 1 <274 J 11,66*4 > .75*9* .3317957 . m i * . 3 . n’ 1. t u r t ^ er c 3 t p u Ta : a.:e ,09 .56 ,32 2& i"s* ..*2 Pa r t i a l I* T(,i Eil F tolerah: e v ,29(3173 2 i . ! l >7;; . =Lc 12.523429 t sihifica.oi 9,2(6;* : 7H3»,ia9s: Va A ' A B l E 6 . 1 .43472 s *.34‘ ::o i t ,:;«63 , 2 9 ; 5 j :9 .36*37 -.36*7044 :.f7*73 5.93925:3 .'1? *,295J3ul . 0 42 a.«2*;-455i-0J . 925 r to EhTER C * " c ^ S V s u .eas scjaae 6*3*75,21576 53* 7331.91417 BE ' a 7n A STEP sui of so-anes 476*726.519*6 • V a R I A B l ES h ot F s i t . i f : : av: e * r: : 7 • »••(»» .gauge., r rs *emB« EOJ ATI OV ............................ 6.3733047 1 4 : i ?* C6* • • •t r • • * • • A DIST-DETRO11 AMt»s;i ;f vaaus:* RECESSION * a s 005 v r<£C8iSS10*f PA6E H VAR001 .11361 .661*1 VAR( 11 ,02307 ,16776 VA«tl3 .05:91 .79951 VA f i { 1 7 •.12919 .26565 VAR021 .,(10*3 .15317 VAR023 •.14214 .3*719 : ; m .-;:al: e :t*;*:7 {) .33! 3:6 3 *.:jT ]E -ti .0*3 l l * Ti ! 4 I i .if 7 1.22?:;:; .273 *;i> 3 j:i9 tE -:j .7.4 41261150* .731 T[3r . R pjl 1 T A R L E TIP.E R .*1375 t ti , 5 L 477 .5*736 ,63913 .6*153 ,*447* R SO- j a Rc R SJl a f E Cm a v i E .17119 .17119 ,0557* .254*9 ,35*91 ,40649 ,437*2 ,4*16 7 .0 375* ,04605 .09611 .05755 .#2911 .93125 5 14P.E R .41375 .2*35: .,02:9* ..33°i: •.0**73 .12*05 ,9**31 overall f 1 * . 3 l 7:« i:.2 *i7 j 6.77565 10-27165 10 . 1 5 6 * 0 9.5973* 9.20*2* .::i .a:: ■9J1 .a:: i a Note: VAROOl represents total number of private campsites in each county, and see Appendix III for description of all other variables. APPENDIX VIII MAP SHOWING PRIVATE AND PUBLIC CAMPGROUND DISTRIBUTION PATTERNS APPENDIX VIII MAP SHOWING PRIVATE AND PUBLIC CAMPGROUND DISTRIBUTION PATTERNS These maps were developed by the "SYMAP" mapping routine with county geographic centers as data points.