INFORMATION TO USERS

This material was produced from a microfilm copy of the original document. While the most advanced technological means to photograph and reproduce this document have been used, the quality is heavily dependent upon the quality of the original submitted.

The following explanation of techniques is provided to help you understand markings or patterns which may appear on this reproduction.

1. The sign or "target" for pages apparently lacking from the document photographed is "Missing Page(s)". If it was possible to obtain the missing page(s) or section, they are spliced into the film along with adjacent pages. This may have necessitated cutting thru an image and duplicating adjacent pages to insure you complete continuity.

2. When an image on the film is obliterated with a large round black mark, it is an indication that the photographer suspected that the copy may have moved during exposure and thus cause a blurred image. You will find a good image of the page in the adjacent frame.

3. When a map, drawing or chart, etc., was part of the material being photographed the photographer followed a definite method in "sectioning" the material. It is customary to begin photoing at the upper left hand corner of a large sheet and to continue photoing from left to right in equal sections with a small overlap. If necessary, sectioning is continued again — beginning below the first row and continuing on until complete.

4. The majority of users indicate that the textual content is of greatest value, however, a somewhat higher quality reproduction could be made from "photographs" if essential to the understanding of the dissertation. Silver prints of "photographs" may be ordered at additional charge by writing the Order Department, giving the catalog number, title, author and specific pages you wish reproduced.

5. PLEASE NOTE: Some pages may have indistinct print. Filmed as received.

Xerox University Microfilms 300 North Zeeb Road Ann Arbor, Michigan 48106 HAWES, Douglass Kenneth, 1938- AN EXPLORATORY NATIONWIDE MAIL SURVEY OF MARRIED ADULT LEISURE-TIME BEHAVIOR PATTERNS AND THE SATISFACTIONS DERIVED FRCM LEISURE­ TIME PURSUITS.

The Ohio State University, Ph.D., 1974 Business Administration

I University Microfilms, A XEROX Company, Ann Arbor. Michigan

@ Copyright by

Douglass Kenneth Hawes

1974

THIS DISSERTATION HAS BEEN MICROFILMED EXACTLY AS RECEIVED. AN EXPLORATORY NATIONWIDE MAIL SURVEY OF MARRIED ADULT

LEISURE-TIME BEHAVIOR PATTERNS AND THE SATISFACTIONS

DERIVED FROM LEISURE-TIME PURSUITS

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

By

Douglass K. Hawes, B.E.E., M.B.A.

*****

The Ohio State University 1973

Reading Committee: Approved by Prof. Roger D. Blackwell Prof. W. Wayne Talarzyk Prof. W. Arthur Cullman

Adviser Faculty of Marketing ACKNOWLEDGEMENTS

The writer wishes to acknowledge the assistance received from numerous individuals in all phases of this study. Particular thanks go to Mr. Mark Ebersole and Mr. Timon Runyan of the OSII Instruction and Research Computer Center. Their speedy and knowledgeable programing efforts literally "saved the day" on several occasions.

Especial thanks also to Dr. Warren Phillips of the OSU Political

Science Department for his insightful and stimulating thoughts on factor analysis. Mr. Philip Hupfer and Mrs. Phyllis Kelderhouse at Market Factss Inc. in Chicago did a great job in administering and coding the survey questionnaire. Finally, the writer wishes to* express his deep and sincere gratitude to the selection committee of the Fred B. and Mabel Dean Hill Fellowship Fund for granting the funds to permit the conduct of this study. VITA

Douglass Kenneth Hawes

BORN: September 14, 1938—Melrose, Massachusetts

EDUCATION: (1 Warren High School, Warren, Rhode Island, 1952-1956 (2 Rensselaer Polytechnic Institute, Troy, New York, B.E.E. Degree, 1956-1960 (3 The Ohio State University, Columbus, Ohio M.B.A. Degree, 1962-1969 (4 The Ohio State University, Columbus, Ohio Ph.D. Degree, 1969-1974

WORK EXPERIENCE: (1 Field Engineer, Hazeltine Electronics Division, Hazel tine Corporation, 1960-1961 (2 Field Engineer, Airborne Instruments Labora­ tory, 1961-1963 (3 Senior Research Engineer, North American Rockwell Corporation, 1963-1969 (4 Administrative Staff Analyst, Ohio St*te University Research Foundation, 1969-1973 (5 Assistant Professor of Business Administra­ tion, University of Wyoming, 1974-

HONORS: (1 Fred and Mabel Dean Hill Fellowship Recipient (dissertation research support) (2 Fellow at 1972 AMA Doctoral Consortium

FIELDS OF STUDY

MBA Program: Marketing, Management, Adaptive Systems

Ph.D. Program: Major Field—General Marketing Minor Fields—Consumer Behavior, Quantitative Methods, Economics Additional Areas of Concentration: Sociology/ Social Psychology, Higher Education/ Teaching Techniques, Natural Resources/ Recreation.

i i i TABLE OF CONTENTS

Page

ACKNOWLEDGMENTS...... 1i

VITA...... ii 1

LIST OF TABLES ...... ix

LIST OF FIGURES...... x iii

Chapter

I. INTRODUCTION AND PROBLEM DESCRIPTION...... 1

Introduction to the Problem ...... 1 Definitions of Leisure and Leisure-Time ...... 2 General Outline of the Study ...... 4 General Limitations of the Study ...... 5 General Background ...... 6 Growth of Leisure-Time ...... 8 Growth of Leisure Market ...... 10 Coverage in Business Journals ...... 12 Justification for Research Emphasis ...... 14 Sociologists and Outdoor Recreationists...... 14 Business and Economics Scholars ...... 15 National Academy of Science ...... 17 U. S. Department of the I n t e r i o r ...... 19 Summary ...... 19 Potential Implications/Utility of the Results ...... 20 Utility to Private Enterprise ...... 20 Utility to Public Policy Makers and Planners .... 21

II. PROBLEM OPERATIONALIZATION...... 24

Definitions ...... 24 Research Questions ...... 26 Research Hypotheses ...... 28 Diagrammatic Models ...... 28

iv Table of Contents (Continued)

Chapter Page

III. RESUME OF RELATED RESEARCH...... 31

Conceptions of Leisure and Leisure-Time ...... 31 Hypotheses-Related Research ...... 32 Hypothesis H-> ...... 32 The Lynds ...... 32 Lundberg, et a l ...... 33 Edward L. Thorndike ...... 34 Robert Havighurst ...... 34 Recent D isse rta tio n s ...... 36 Summary ...... 37

Hypothesis Ho ...... 38 Charles Proctor ...... 38 Thomas Burton ...... 39 Bultena and Klessig ...... 39 Tatham and Dornoff ...... 40 O th e rs ...... 40 Summary ...... 41

Hypothesis H 3 ...... 42

Hypothesis H 4 ...... 43 Credit Usage ...... 44 Survey Research Center (Michigan) Studies ...... 45 Credit Cards ...... 45 Life-Style Differences in Use of Credit—Ross Goble. 47 Mathews and Slocum ...... 48 Joseph Plummer ...... 49 Summary ...... 50

Hypothesis H 5 ...... 50 Bass, Pessemier and Tigert ...... 51 Wells and Sheth...... 51 Summary ...... 51

Related Research...... 52 Conclusions ...... 53

IV. METHODOLOGY AND PRETESTING...... 54

Overall Research P l a n ...... 54 Research Design ...... 56 Null Hypotheses ...... 56 Research V a ria b le s ...... 58

v Table of Contents (Continued)

Chapter Page

Pretesting of AIO Statements ...... 60 AIO Pretest Results...... 62 Pretesting of "Satisfactions" Statements ...... 63 Satisfactions Statements Pretest Results ...... 64 Study Sample ...... 65 Sample L im itatio n s ...... 67 Sample Selection ...... 68 The Qi/isstionnaire ...... 72 Market Facts P retest...... 72 Market Facts Pretest Results ...... 73 Results—Demographic Distributions ...... 73 Results—AIO and Satisfactions Statements ...... 76 Results—Other...... 76 Final Survey Mailing ...... 77 General Analysis P l a n ...... 77 Data File Management ...... 79 General Methodological Approach ...... 80 S tatistical Measures Employed ...... 81 Correlation Coefficients ...... 81 Factor Analysis...... 85 Cluster Analysis ...... 89 Discriminant Analysis ...... 90 Data R eliability and V a lid ity ...... 91

V. ANALYSIS AND RESULTS...... 96

Survey Return Rate ...... 96 Analysis of Household Biographical Data ...... 97 Conclusion ...... 101 Analysis of Hypotheses ...... 101 Analysis of Hypothesis H-j ...... 102 Analysis Approach ...... 105 Analysis of Table 8 ...... 106 Analysis of Table 9 ...... 110 Analysis of Table 10 ...... 110 Analysis of Table 11 ...... 116 Summary ...... 118 Conclusion ...... 118 Analysis of Hypothesis H 2 ...... 121 Analysis Approach ...... 123 Analysis of Table 13 ...... 124 Analysis of Table 14 ...... 127 Analysis of Table 15 ...... 127 Analysis of Table 16 ...... 127 Analysis of Table 17 ...... 134

vi Table of Contents (Continued)

Chapter Page

Analysis of Table 18 ...... 137 Analysis of Table 1 9 ...... 142 Analysis of Table 20 ...... 148 Analysis of Table 21 ...... 148 Sum m ary ...... 155 Conclusions ...... 157 Analysis of Hypothesis H 3 ...... 159 Analysis Approach ...... 160 Analysis of Table 22...... 161 Analysis of Table 2 3 ...... 164 Sum m ary ...... 167 C onclusion ...... 167 Analysis of Hypothesis H 4 ...... 168 Analysis Approach ...... 169 Results of Cross-Tabulation Analysis ...... 170 Holders of Credit Cards ...... 170 Uses of Credit during1972 172 Uses of Credit in 1972versus Demographics . . . 173 Uses of Credit in 1972versus Magazines Read . . 174 Reasons for Considering Use ofLong-Term Credit . 175 Use of Credit in 1972 versus Reasons for Con­ sidering use of Long-Term Credit ...... 177 Analysis of Table 2 4 ...... 177 Analysis of Table 2 5 ...... 180 Analysis of Table 26 ...... 183 Analysis of Table 2 7 ...... 183 Analysis of Table 28 ...... 191 Analysis of Table 29 ...... 194 Analysis of Table 3 0 ...... 197 Analysis of Table 31 ...... 201 Summary ...... 206 Conclusions ...... 209 Analysis of Hypothesis H 5 ...... 211 Analysis Approach ...... 212 Results of Cross-TabulationAnalysis ...... 213 Cross-Tabulations of Favorite Pursuits versus Favorite Pursuits ...... 213 Cross-Tabulations of Favorite Pursuits versus Demographics ...... 214 Cross-Tabulations of Favorite Pursuits versus M a g a z in e s ...... 214 Cross-Tabulations of Magazinesversus Magazines . 215 Cross-Tabulations of Magazines versus Demo­ graphics ...... 216 Cross-Tabulations of Favorite Pursuits versus TV Program-Types ...... 218 Cross-Tabulations of TV Program-Types versus TV Program-Types ...... 218 v ii Table of Contents (Continued)

Chapter Page

Cross-Tabulations of TV Program-Types versus Demographics ...... 219 Analysis of Table 32 ...... 221 Analysis of Table 33 225 Analysis of Table 34 229 Analysis of Table 35 233 Analysis of Table 36 237 Summary ...... 240 Conclusions ...... 242 Additional Analyses ...... 244 Analysis Approach ...... 245 Analysis of Table 37 247 Analysis of Table 38 251 Analysis of Table 39 258 Summary ...... 267 Conclusions ...... 269 Chapter V Summary ...... 270

VI. SUMMARY AND IMPLICATIONS...... 271

Summary of the Study Objectives and Procedures .... 271 Major F in d in g s ...... 273 Hypothesis H-j ...... 274 Hypothesis H 2 ...... 276 Hypothesis H 3 ...... 279 Hypothesis H 4 ...... 281 Hypothesis H 5 ...... 283 Additional Analyses ...... 284 Implications of the Findings ...... 285 Study Limitations ...... 290 Data/Techniques ...... 290 Study D e s i g n ...... 291 Directions for Future Research ...... 292 Conclusion ...... 297

APPENDIX

A. Questionnaire ...... 298

B. Panel Member Basic Demographic/Biographical Data Card . 320

C. Testing for Rectangular or Peaked Distribution of Satisfactions Statements ...... 329

REFERENCES CITED ...... 332

v m LIST OF TABLES

Table Page

1. Number of Articles in Several Marketing and Business Journals Dealing Directly with Leisure or Recreation* Topics ...... 13

2. Original Havighurst "Satisfactions" Statements Eliminated in Pretesting...... 66

3. Comparison of Percentage Distribution of Selected 1000 Households Versus Distribution of U.S. Population Based on 1970-1971 U. S. Census Data ...... 70

4. Comparison of Initial Distribution of 100 Pretest Households with Returning and Non-Returning Households on Selected Demographic Variables ...... 74

5. Internal Consistency Reliability of Four Scales as Measured by Cronbach's Coefficient Alpha ...... 94

6 . Comparison of Initial Distribution of 1000 Households with Responding and Non-Responding Households on Several Selected Demographic Variables ...... 98

7. The 32 "Satisfactions" Statements ...... 103

8 . Satisfactions Statements with Peaked (Point) or Rec­ tangular Distribution of Responses—by Favorite Activity (Female Respondents) ...... 107

9. Frequencies of "Peaked" Response Distribution Across Satisfactions Statements (Female Respondents) ...... Ill

10. Satisfactions Statements with Peaked (Point) or Rectangu­ lar Distribution of Responses--by Favorite Activity (Male Respondents) ...... 112

11. Frequencies of "Peaked" Response Distribution Across Satisfactions Statements (Male Respondents) ...... 117

12. Summary of Satisfactions Statements with Non-Peaked Response Distribution--Female and Male Respondents. . . 119 ix List of Tables (Continued)

Table Page

13. Groups (Factors) of Related Leisure-Time Pursuits Engaged in During 1972 by Female Respondents ...... 125

14. Groups (Factors) of Related Leisure-Time Pursuits Engaged in During 1972 by Male Respondents ...... 128

15o The Most Popular Favorite Leisure-Time Pursuits ...... 130

16. Groups (Factors) of Related Leisure-Time Pursuits Selected as "Favorite" Pursuits by Female Respondents . . 132

17. Groups (Factors) of Related Leisure-Time Pursuits Selected as "Favorite" Pursuits by Male Respondents . . . 135

18. Groupings (Factors) of Related Satisfactions Statements Across all Activities in Each of the Three "Favorite" Categories (Female Respondents) ...... 138

19. Groupings (Factors) of Related Satisfactions Statements Across all Activities in Each of the Three "Favorite" Categories (Male Respondents) ...... 143

20. Groupings (Factors) of Satisfactions Statements for the Leisure-Time Pursuits "Attending Movies" and "Bowling" (Female Respondents) ...... 149

21. Groupings (Factors) of Satisfactions Statements for the Leisure-Time Pursuits "Listening to Music from Records, Tapes, Radio" and "Playing Golf" (Male Respondents) . . . 152

22. Similar Groups (Factors) of Satisfactions Derived from Participating in Different Leisure-Time Pursuits (Female Respondents) ...... 162

23. Similar Groups (Factors) of Satisfactions Derived from Participating in Different Leisure-Time Pursuits (Male Respondents) ...... 165

24. Descriptive Summary - Credit Cards Held and Uses of Credit (603 Female Respondents) ...... 178

25. Descriptive Summary - Credit Cards Held and Uses of Credit (512 Male Respondents) ...... 181

x List of Tables (Continued)

Table Page

26. Final Variables used in Factor Analysis of Selected Credit-Oriented, Religion, Life-Style and Demographic Variables...... 184

27. Groupings (Factors) of Related Selected Credit-Oriented, Religion, Life-Style and Demographic Variables Based Upon Female Holders of Credit Cards ...... 188

28. Groupings (Factors) of Related Selected Credit-Oriented, Religion, Life-Style and Demographic Variables Based Upon Female Non-Holders of Credit Cards ...... 192

29. Groupings (Factors) of Related Selected Credit-Oriented, Religion, Life-Style and Demographic Variables Based Upon Male Holders of Credit L-rds ...... 195

30. Groupings (Factors) of Related Selected Credit-Oriented, Religion, Life-Style and Demographic Variables Based Upon Male Non-Holders of Credit Cards ...... 198

31. Means of the 86 Variables Factor- Analyzed in Tables 27-30 ...... 202

32. Summary of Positive Correlations Greater than +0.40 Between the Most Popular Favorite Leisure-Time Pursuits and Magazines/TV Show-Types (Male and Female Respondents) 222

33. Groupings (Factors) of the Most Popular Favorite Leisure- Time Pursuits and Most Popular Magazines (Female Respon­ dents) ...... 226

34. Groupings (Factors) of the Most Popular Favorite Leisure- Time Pursuits and TV Show-Types (Female Respondents) . . 230

35. Groupings (Factors) of the Most Popular Favorite Leisure- Time Pursuits and Most Popular Magazines (Male Respondents)234

36. Groupings (Factors) of the Most Popular Favorite Leisure- Time Pursuits and TV Show-Types (Male Respondents) . . . 238

37. The Selected Variables Used in the Discriminant Analysis of Both Male and Female Participants in Each of Two Groups of Leisure-Time Pursuits ...... 248 List of Tables (Continued)

Table Page

38. Discriminant Analysis of Two Groups of Leisure-Time Pursuits Engaged in During 1972 by Female Respondents. . 252

39. Discriminant Analysis of Two Groups of Leisure-Time Pursuits Engaged in During 1972 by Male Respondents. . . 259

x ii LIST OF FIGURES

Figure Page 1. Generalized Black-box Model ofLeisure-Time B ehavior ...... 29

2. Hypothesized Relationships BetweenSeveral Key Types of Variables ...... 29

3. General Analysis P l a n ...... 78

xi i i CHAPTER I

INTRODUCTION AND PROBLEM DESCRIPTION

This research project represents an attempt, through an explora­ tory survey, to provide a richer understanding of some of the motiva­ tional forces affecting leisure-time behavior among married American adults.

Introduction to the Problem

Leisure-time related expenditures by the ultimate consumer are variously estimated to be between $80- and $150-bill ion dollars a year. A recent U. S. News and World Report article (April 17, 1972:

42-45) estimates the 1972 leisure spending level at $105 billion. Yet, based on published data, knowledge of leisure-time consumer behavior and related decision-processes is minimal. The potential economic and social consequences of inadequate knowledge about this area of human behavior are significant.

Research efforts in this area, traditionally, have been funda­ mentally broadly economic in character. What?, when?, where?, how much?, and how many?, have been the usual questions studied. The question "why?" has practically never been addressed. Little research emphasis has been given to obtaining a better understanding of the social, social-psycho!ogical, and other motivational forces which shape and sustain leisure-time consumption behavior. A better 2

understanding of these forces is important to the progressive, effective

management of both private and public sector organizations—particularly

in regard to recreational services to be provided to the many "publics."

While it may never be possible to fully answer the question of

why people participate in one leisure-time pursuit rather than another,

i t is toward this goal that this dissertation is directed.

Definitions of Leisure and Leisure-Time

Professor Max Kaplan (1971:19) identifies and describes six con­

ceptions of the nature of leisure. These are:

1) The humanistic model of leisure which sees it as an end in

its e lf , illu strated by the contemporary Chinese and the ancient Greeks.

2) The therapeutic model of leisure which sees i I as a means,

an instrument, a control.

3) The quantitative model of leisure which views i t as the

time left over when the work necessary for maintaining life is finished.

4) The institutional conception of leisure which seeks to

distinguish it from such behavior and value patterns as the religious, marital, educational, or political.

5) The epistemological conception of leisure which relates activities and meanings to the assumptive, analytic and aesthetic '■v views of the world.

6 ) The sociological conception of leisure which views it as a construct with such elements as an antithesis to the work of the participant, a perception of the activity as voluntary or free, a pleasant expectation and recollection, and covering a full range of possibilities. 3

Within these six categories there are numerous definitions by

almost as many writers as there are in the field. While the concept

of "leisure" as a frame of mind, a state of being or an attitude to­ ward a situation is aesthetically and intuitively pleasing, it poses

problems of operationalization. The quantitative model of leisure will, therefore, be assumed in this study.

This definition of leisure is anchored in the framework of

time. It follows that of Neumeyer and Neumeyer (1936:1), Voss (1967:

101), Linder (1970:1-27), Kraus (1971:257-260), and others. The

shorthand word "leisure," or the more correct phrase "leisure-time," will be used herein to mean a form of non-obligated, or discretionary time—that time remaining after the formal duties and practical necessities of contemporary life have been attended to. As Kraus

(1971:257) states,

This concept of leisure sees it as time which is free from work or from such work-related responsibilities as travel, study, or social involvement based on work. I t is also regarded as time not devoted to essential life-maintenance activities, such as sleep, eating or personal care. Its most important characteristic, therefore, is that it lacks a sense of obligation or compulsion.

It is recognized that this definition of leisure has several deficiencies, none the least of which is determining the absence, presence, or extent of obligation felt by the participant. This study circumscribes this difficulty by parenthetically identifying "leisure­ time" with "spare-time" and then permitting the respondent to set his own context. 4

It should also be pointed out that, in the current view, leisure is often equated with recreation, though recreation is more correctly recognized as a subset of leisure. The expression "play," is also conceptually distinct from recreation and is a subset of leisure (Nash,

1953:34, 82; Miller and Robinson, 1963:5-10; Kraus, 1971:253-266).

Recreation itself is commonly discussed in terms of outdoor recreation. Therefore, in the discussions to follow, comments regard­ ing "recreation" or "outdoor recreation" by various authors should be interpreted in the broader framework of "leisure-time activities," or, more appropriately, "discretionary-time activities."

Here too, a caveat should be inserted, however. Theoretically, leisure-time is viewed as a sub-set of discretionary-time. In prac­ tic e , they are frequently used synonymously.

General Outline of the Study

The purpose of this study is to attempt to group individuals, acting in a leisure-time context, into relatively homogeneous market segments amenable to appeals by contemporary promotional techniques utilizing existing media. The term "market segments" is used in the sense of groups of people with common leisure-time felt "needs."

The study is seen as primarily exploratory in nature, while at the same time sufficiently representative in sample structure to per­ mit potential utilization of the results in ( 1 ) developing more inten­ sive studies of specific subgroups, and ( 2 ) developing tentative marketing strategies for leisure-time goods and services. The study sample was limited to households with both a male and female head-of-household present, with a total household income greater than $400Q.0O annually, and located in the continental

United States. There was no attempt made a priori, to single out specific groups ( i.e ., the aged, or particular youth groups) within the population for exclusive attention.

Data were collected by a mail questionnaire from a sample of 1000 households around the country on a wide range of personal characteristics, leisure-time behavior, sought-after "satisfactions" from leisure-time pursuits, and expenditures of resources.^

Preferences for, and participation in, various leisure-time pursuits were then related to a large number of these personal char­ acteristics. Leisure-time related variables were subsequently clus­ tered, or grouped, through factor analysis and other techniques. The results are an indication of the relationships between preferred leisure time activities, the "satisfactions" or benefits derived therefrom, media preferences, and usage of credit for leisure-time goods and services. The results of this study are discussed in detail in Chapter V.

General Limitations of the Study

This study was consciously restricted in scope. It did not consider the meaning, nature or substance, or preferred ("correct") use of leisure in a philosophical sense.

^Refer to Chapter IV for a discussion of the sample selection procedure. 6

No consideration was given to the question of whether or not

the average work week is increasing or decreasing; whether individuals

have more or less "leisure” than in times past; or whether the four-

day work week is a trend or a fad. This research did not attempt to

prove or disprove an existing theory or model of leisure-time behavior,

as none have been found in the literature that are relevant or com­

prehensive enough for the marketplace problems discussed below.

General Background

Leisure is big business. U. S. News and Vlorld Report (April 17,

1972:42) estimates i t at a 105-billion-dollar business in 1972 and the fastest growing business in America . 2 The article states,

The money Americans are now spending on spare-time activ ities exceeds national-defense costs. It is more than the outlay for construction of new homes. It surpasses the total of corporate profits. It is far larger than the aggregate income of U. S. farmers. It tops the over-all value of this country's exports.

And estimates are that the dollar volume of leisure­ time expenditures will more than double during the decade of the '70s.

O £The estimated $105 billion figure, representing an increase of $22.4 billion since 1969, is broken down as follows:

1. Recreation-sports equipment andactiv ities — $50 billion 2. Vacations, recreation trips in U. S. — $40 billion 3. Travel abroad — $ 7.5 billion 4. Vacation land and lots — $ 5.5 billion 5. Second homes — $ 2 billion Dr. Max Kaplan, director of the Center for the Studies of

Leisure at the University of South Florida, states that the conventional

aggregation of leisure-time spending may significantly understate the

"true" picture. Dr. Kaplan (1970:6) adds several items to the U. S.

Department of Commerce l i s t under "leisure," "... such as 60 percent

of passenger car costs and maintenance which can be attributed to

'pleasure' trips, and comes to a total of $110 billion in 1969, or

perhaps triple the Commerce estimate." If this estimate were roughly

correct then, by the same ratio, the 1972 estimate or the "true" pic­

ture would be close to $139 billion.

An even higher estimate of the leisure market was made by the

Securities Research Division of Merrill Lynch, Pierce, Fenner and

Smith, Inc, (1968:4). In a 1968 report entitled Leisure: Investment

Opportunities in a $150-Bi11 ion Market, they state:

. . . The limits of the leisure market are difficult to define. It is made up of any number of small mar­ kets, some completely interdependent, some closely related, others totally unrelated. Available data are often incomplete, and statistics for one segment of the market are not necessarily comparable to those for another. A major drawback is separating goods and services purchased for leisure from those bought for regular consumption. An automobile, for example, is often necessary for work and subsistence. Yet, one observer has estimated that one-third to one-half of the purchase price and maintenance expenses for all cars on the road can be considered costs incurred in the use of free time. All things considered, we believe that the leisure market in all its aspects is rapidly approaching the $150-bill ion mark.

Merrill Lynch economists further predict a 7 percent compound annual rate of growth in disposable personal income during the 1970's.

Based on this growth rate, and the growth, between 1955 and 1968, of 8 consumer spending for recreation (as categorized) as a percent of dis­ cretionary personal income (from 5.5 to 6.3 percent); they predict that spending on leisure-related goods and services will reach 10 per­ cent of discretionary personal income by the late 1970's.^

Growth of Leisure-Time. The apparent growth of leisure time in this country has been well documented. The term "apparent" is used intentionally. Depending upon one's definition of leisure time and one's starting point, it can be shown both that there is more leisure time today than in times past, or that there is actually less time available for leisure pursuits in recent time than in the decades around the turn of the century (De Grazia:1964).

It is interesting to note two other contemporary viewpoints regarding the increase in leisure time. Joffre Dumazedier (1967:34) states that "leisure is a continuous product of technical progress," and "is itself a creation of our industrial system." He contrasts th is growth in leisure time attributable to industrial organization and automation with the holy days and other non-work days around

1700. Although these numbered around one hundred and sixty, to ta l, the activ ities of these particular days disqualify them, in Dumazedier's view, from the category of leisure.

%ote that a 7 percent annual increase implies a doubling in 10.2 years, while an (average) 5.9 percent annual increase implies a doubling in 12.2 years. 9

Staffan Linder (1970:22-24), in The Harried Leisure Class, takes the opposite view that increasing industrial and technical progress brings with it a growing leisure "time famine." The increasing claims upon a fixed quantity of time, that are con­ comitant with the growth of an affluent, consumption economy, act to decrease discretionary time. In his economic analysis, Linder, points out that the value, or yield, of the time available to consume a commodity increases with the volume of consumption goods at one's disposal.

In his overview a rtic le , Philip Schary (1971:51) supports Lin­ der's thesis of "the rising scarcity value of time in an affluent society." He brings out the oft-neglected fact that consumption is a process, "equivalent" to production, in which time is one of the scarce inputs and satisfactions one of the outputs. Depending on the size of the increments of leisure-time available to be combined with other resources, leisure-time consumption patterns may be quite d if­ ferent.

The impact of the three-day weekend has only ju st begun to be f e lt by leisure-related industries.^ Riva Poor (1970:14) and her associates were able to quickly locate, between May and October of

^The increasing acceptance by the various states of the new federal Monday-holiday law is proving to be a boon for short- and medium-distance travel-related industries (U. S. News and World Report, November 8 , 1971:64). 10 1970, some three dozen firms working a four-day week. In July of 1971,

she was quoted as having indicated th at, by her la te st count, some

367 companies had converted to a reduced-from-five- 8 -hour-days work

week (Business Week, July 17, 1971:33).

A national newsweekly, in its March 20, 1972 issue reports a

study by the American Management Association which estimates that 700

to 1000 firms, governmental agencies or organizations are trying the

four-day week (U. S. News and World Report, March 20, 1972:82).

Both the numbers of firms involved in changing th eir workweek

and the extent of their experience are inadequate to predict atrend

toward this change. It appears to be easier or more expedientfor

small firms (under 1000 employees) to make the s h ift, than forlarger

firms to make such a change.

"Flexi-time" (G leitzeit), or employee-determined sta rt and stop

times for the workday, is also increasing in its implementation (Lang-

holz, 1972; Hedges, 1973). This, too, permits more usable blocks of

leisure-time, suitable for different activities, than rigid 9 to 5

scheduling.

Growth of Leisure Market. There have been many recent refer­

ences in the popular press to the growing potential leisure market.

It is estimated that there will be 25 million households with an

annual income of $15,000 or more (in 1970 dollars—the assumed infla­

tion rate is not specified) by 1980 (U. S. News and World Report,

December 6 , 1971:28-29). By 1990, this figure is estimated to be

40 million families or 57 percent of all families (U. S. News and

World Report, February 14, 1972:42-43). One out of every four n

families is expected to earn more than $25,000 in 1990. These incomes, coupled with shorter work weeks and increasing percentages of dis­ cretionary personal income spent on leisure-time goods and services, are "certain" to provide an expanding market for leisure-related busi­ nesses. "Certain," that is, ceteris paribus.

One author (Eisenpreis, 1971:60) points out th at, "For every

1% increase in income 1948-1968, sporting goods expenditures rose 2%; radio, TV and foreign travel expenditures rose slightly more." He also goes on to remind businessmen that "Western U. S. families spend one-third more on recreation than the U. S. average, and population is moving westward."

Finally, the impact of the retiree and over-65 market, with its much greater discretionary time budget and its gradually increasing discretionary income, is becoming a major force in the marketplace for leisure-time goods and services. The over-65 market is estimated at $60-billion, compared with the so-called youth or under-30 market which is variously estimated at anywhere from $20- to $45-bi11 ion

(Business Week, November 20, 1971:52). This over-65 age group now constitutes 10 percent of the total population and is growing at 5 twice the rate of the under-65 group.

^In certain localized parts of the country—parts noted for their attraction of retirees—they comprise from 20 to almost 50 percent of the population (Business Week, November 20, 1971:57).

i 12

Coverage in Business Journals. In spite of the indications of

market opportunities alluded to above, research into demands for lei­

sure goods and services reported in the business-oriented scholarly

journals has been sparse indeed. It seems to be the case, as David

Riesman (1964:147) reflects, that "there has been some tendency to

regard leisure as not quite a serious topic." He further states,

(Riesman, 1964:108) "... in general when I discuss leisure, I often

encounter the attitude that the subject is not quite serious—and

certainly not a solid topic for research. We are still work-minded

in our views of what constitutes a proper subject for research ..."

Table 1 indicates the extent of publication of "leisure-related" articles in several of the more prominent business journals since 1960.

"Leisure"related" should be taken to include articles on the four-day work week as well as those concerned with an industry directly affected by leisure expenditures. This investigator depended, for the most part, on the title of the article in deciding whether or not it was possibly leisure-related. Those that met this c rite ria were scanned to verify their content before entering them into the inventory of Table 1.

It seems clear that writers in the scholarly business publica­ tions have given very little direct attention to the leisure market.

It should be noted, however, that the greatest percentage of leisure- oriented articles have been in marketing publications. It is also interesting to note that travel and tourism research and discussion has predominated in the leisure-related articles in these journals. 13

Table 1

Number of Articles in Several Marketing and Business Journals Dealing Directly with Leisure or Recreation Topics

Number of Leisure- Journal .Related Articles Since 1960

Journal of Marketing 2

Journal of Marketing Research 1

Journal of Advertising Research 1

Journal of Retailing 0

American Marketing Association "Proceedings" 10

Harvard Business Review 2

Business Horizons 3

Business Topics 0

Journal of Business 0 14

JUsti.fi.cation for Research Emphasis

Historically, most studies of leisure-time usage involved

primarily inventory or head-counting studies of participants in

various recreational pursuits. Numbers of participants were related

to various economic and demographic variables, to catchment areas, and to available facilities. Attempts were made to predict usage of particular fa c ilitie s based on demographic characteristics of

known users and the likely number of potential users within the

catchment area of the fa c ility .

There have been many researchers, business scholars, and seg­ ments of the public sector who have recently called for more research

in the socio-psychological theory of leisure-time activities. These

researchers have been primarily in the disciplines of sociology and outdoor recreation planning, while the business scholars have tended to be marketing academicians. The most vocal groups in the public sector have been the National Academy of Science and the Department of the Interior.

Sociologists and Outdoor Recreationists. Kenneth Roberts

(1970:3-5) points out that several studies have shown the futility of merely finding out what people do in their leisure-time without probing their motives. He calls for the development of theories relating leisure behavior to its social context and to other social institutions.

Two writers in the field of outdoor recreation have stated

(Clawson and Knetsch, 1966:293-298), 15

. . . Recreation simply has not been recognized by many professions as a respectable field for scientific inquiry . . .

The need for research may not have been so apparent in an earlier period when the competition for use of natural resources was less severe, and the problems of recreation use of resources were not so serious . . .

. . . it is one thing to observe instances of such regularity [in patterns of behavior among individuals] and have intuitive notions about them: it is quite another thing to relate the regularities to the impor­ tant determining factors and to have empirically deter­ mined estimates of the importance of each factor and of the relationships of one to another and to time related changes.

. . . Any research on this problem [how to increase . the attractiveness or capacity of a recreation area of facility] should consider the values and satisfac­ tions of the recreation experience.

While these statements are fairly general and applicable to the need for research in any consumer-oriented field, they were made in the context of outdoor leisure-time activities.

There have been numerous other sociologists and planners who have called for more research into the motivational underpinings of leisure-time consumer behavior: Molyneux (1970:61), Emmett (1970:73),

Taylor (1970:225), Burton (1970:264), Klausner (1971:134-136, 158-159),

LaPage (1971:186-192), Shafer and Moeller (1971:5-21), and Dumazedier

(1967:268-269) among others.

Business and Economics Scholars. Several writers and researchers in the business and economics disciplines have pointed out, or alluded to, the need for research of the nature discussed herein. Philip Kotler 16

(1972:82) discussed the shifts in the American cultural environment.

One of these is from "hard work" to the "easy life." He, following

Linder, points out some of the marketing significance of the increas­ ing shortage of time (and its corresponding increase in value). The leisure-time life is a hedonistic life, full of all the related accoutrements. The implied point here, is why certain accoutrements rather than others?

John Rathmell (1960:178-184), in an older article, called attention to the changing consumption patterns resulting from increases in discretionary purchasing power plus increases in dis­ cretionary time. These two factors combine to result in what Pro­ fessor Rathmell calls "discretionary mobility." He apparently attrib­ utes the increases in consumption of leisure-time goods and services to increases in discretionary time, more than to increases in discre­ tionary purchasing power per se.

Theodore Levitt (1969:305-316), in discussing what he considers to be "the illusory leisure market," espouses the belief that afflu­ ence, more than the increase in available leisure-time, is the engine behind the growing demand for leisure-time products and services.

These kinds of products and services have displaced more u tilitarian tangible goods as the nouveau items of "conspicuous consumption" and

"status symbols." Levitt (1969:312) poses a question directly rele­ vant to this research effort,

. . . Why, for example, do people spend i t [money] on skis, golf, sailboats, camping equipment, sports cars, do-it-yourself workshops, oil paintings, Puerto Rican vacations and trips to Europe? Why not more on better home furnishings, contributions to the church, or dinner parties at home? 17

Levitt's view is that these growth activities are possessed by a

highly individualistic, personal, nongroup character, and represent a revolt against the organized, structured quality of modern life. It

is quite interesting that this is the same view espoused by Thomas

Burton (1970:265) in writing about the future of recreation in

England. One indication of the growth in individualized outdoor

recreation, is the recent decision to limit wilderness/back country back-packers in both the Rocky Mountain National Park and in the Great

Smoky Mountains National Forest by a reservations-only, permit system— the first of such attempts at outright rationing of access to a tradi­ tionally "free" good (U. S. News and World Report, May 8 , 1972:40).

National Academy of Science. On June 2-8, 1968, the presti­ gious National Academy of Sciences (NAS, 1969) conducted a Study

Conference on Outdoor Recreation Research for the Bureau of Outdoor

Recreation of the U. S. Department of Interior. The report which resulted from this conference was published in late 1969, and con­ tains the conclusions and recommendations of the conferees in three areas: (1) the basic social and psychological dimensions and func­ tions of outdoor recreation, ( 2 ) the economics of demand and supply, and (3) the operation of recreation service systems.

The report (NAS, 1969:1-6) talks of the need for a multi­ dimensional approach to outdoor recreation in these terms.

In order to understand recreation better . . . we must recognize:

1 . the forces that drive it, springing from the behavior patterns of people who engage in it, the social and psychological needs they seek to satisfy, and the established and encouraged forms of consumption; 18

2 . the interactions that couple recreation with other social institutions and action systems;

3. the impact of recreation on the natural and human resources for which i t competes and that i t needs for its maintenance; and

4. the dynamics of recreation institutions.

Such a multidimensional approach to outdoor recreation can make a twofold contribution: ( 1 ) understanding will be accelerated by identifying the analogies with other, more extensively studied, social structures, and (2 ) investigation of outdoor recreation needs will be stimulated by insights gained from the study of other structural contexts.

The report makes twelve major recommendations for the direction

and emphasis of future research in this field. The highest priority

recommendations are for a systems research effort involving social

and behavioral scientists to broaden the understanding of recreation

as a social institution and to experiment on the social structures

serving outdoor recreation.

The second highest priority is placed upon a "coordinated pro­

gram of analyses, and measurement aimed at understanding the social

and psychological forces that shape and sustain outdoor recreation

programs." This research should be directed at

. . . analysis of satisfactions sought in recreation activities, diagnosis of dysfunctional behavior, the relation between activities and the value imputed to them as reflected in time and resources allocated, and the benefits to the external community.

In this second priority category, the report also calls for "vigorous research" involving economics and the behavioral sciences to develop better models for anticipating consumer behavior in outdoor recreation. 19

As is pointed out, "Important gains can come from investigations of

specific decision-making situations in which recreation is in competi­

tion with alternative uses of resources."

U. S. Department of the Interior. Two more recent reports out of the U. S. Department of the Interior reiterate the same message. In a series of ten forums on the subject of nationwide outdoor recreation planning conducted in various cities around the nation, one of the major research needs identified was that of conducting research into the socio-psychological recreation needs and desires of various units of society (Bureau of Outdoor Recreation, 1973:32). In the follow-on f ir s t draft of a Nationwide Outdoor Recreation Plan, the Bureau of

Outdoor Recreation (B.O.R.) (B.O.R., 1973:16-32) emphasizes that we need to know more about:

What motivates people to engage in certain outdoor recreation activities and why they go where they do when they do.

How people use the outdoor recreation portion of their total available leisure time.

Summary. A number of segments of our society have become increasingly concerned with the current lack of knowledge regarding the mativations, socio-psychological needs and desires, and consumption patterns of people acting in leisure-time situations. . This aspect of consumer behavior has not been adequately researched, in part, because competition for use of resources has only recently become severe. From a marketing standpoint, Dr. Levitt's quote is highly relevant. Just why do people prefer one or one set of leisure-time pursuits over another? Answers to this question could permit more effective market­ ing efforts in satisfying the leisure-time needs and desires of consumers. 20

Potential Implications/Uti1itv of the Results

"The basic reason for research on recreation is to provide a

sound basis for making policy and management decisions on the develop­

ment of recreational fa c ilitie s for future needs" (Clawson, 1959:287).

Utility to Private Enterprise. The primary reason for studying

consumers is in order to "develop more efficient use of marketing

resources and more effective solutions to marketing problems" (Engel,

Kollat, Blackwell, 1968:9),

By studying consumer behavior, therefore, businessmen are able

to make more accurate predictions concerning what products and ser­

vices consumers will buy and under what conditions they will buy them.

The uncertainties in adjusting marketing to the vagaries of consumer

(leisure-time) spending can thereby be reduced (Engel, Kollat, Black- well, 1968:11; Fisk, 1963:3).

More specifically, knowledge about the demand for specific

leisure-time goods and service, as related to various socioeconomic,

demographic, and other descriptive variables will permit more confi­

dence in the prediction of future demand for these goods and services as based upon trends in these variables, ceteris paribus. Sellers will be better able to determine production and marketing strategies

consistent with characteristics of marketing opportunities in var­

ious segments of the population.

To the extent that the demand for specific leisure-time goods and services is found to be correlated with some readily available index of growth or social change, some indication of likely future 21 demand can be established. To the extent that participation in one activity is found to be strongly correlated with participation in another, the possibility of substituting one for the other becomes a real option. This would increase the marketer's flexibility in seg­ menting the leisure-time market.

Product differentiation (by association with other selected leisure-time goods and services) would also be potentially enhanced by the ability to then package together several different, but related, leisure-time goods or services.

Utility to Public Policy Makers and Planners. Traditionally, marketing research projects have, for the most part, been only tangen- tia lly concerned with generating and/or providing data to governmental bodies as an aid in public policy formulation. Quite recently, however, the American Marketing Association (AMA) created a Public Policy Div­ ision. This Division has stated (Thorelli, 1972:2),

As an organization of professional people, the AMA is vitally interested in bringing the expertise of its members to bear on matters of public policy formulation . . .

In future (sic), the AMA will have to extend its atten­ tion to the marketing by public bodies of their own products, services, programs and policies . . .

This statement indicates the growing interest of marketing academi­ cians in becoming involved with marketing problems of the public sector.

Public policy makers are continually confronted with planning, resource allocation, and public funds investment problems in meeting 22 expanding needs for leisure-time. "Thus the question of how much to budget for production of leisure goods and services is part of the larger problem of mobilizing the nation's productive resources" (Fisk,

1963:1). The Department of Health, Education and Welfare's (HEW)

"Panel on Social Indicators" stated, "We have measures of the level and distribution of income, but no measures of the satisfaction that income brings" (U. S. Dept, of HEW, 1969:XIV). This statement is directly translatable into the leisure-time area.

Are some activities substitutes for others? Will people engage in activity Y if the facilities for activity X are not avail­ able and good facilities for Y are? Technology is bound to not only alter the mix of choices available to meet leisure-time demands, but also influence individual and social values of leisure. Molyneux

(1970:52) asks the key question, "Would fuller understanding of the motivations and satisfactions which attract people to different forms of recreation lead to possibilities of substitution within groupings of activities?"

The possibility of substitutability among activities leads to two benefits. One, obviously, is increased utilization of presently underutilized facilities and activities. The other is the "demarket­ ing" of presently overutilized resources. As an article by two recreational researchers (Shafer and Moeller, 1971:16) employed by the U. S. Forestry Service states: 23

. . . the major problem is not to forecast future increases in use, but rather to predict how certain management regulations and procedures can lim it, or even decrease recreation use-intensity.

This concept of substitutability between activities is one

"which will open a whole new dimension for the urban and regional planner faced with seemingly ever-increasing demands upon severely limited land and water resources" (Burton, 1971:349). "The functional equivalent of the mountain for the mountain climber may be needed—at a lower cost than access to mountain en tails—in the more congested city environment" (Klausner, 1971:162). CHAPTER II

PROBLEM OPERATIONALIZATION

While the previous chapter described the current needs in leisure-time and recreation research and highlighted several problem areas, this chapter focuses on the specific research questions selected for investigation in this dissertation. Chapter III con­ tains a discussion of the literature found relevant to each of the selected research questions.

It should be apparent from Chapter I that any study of lei­ sure-time behavior requires the somewhat arbitrary selection of particular questions to be investigated. There is not a single, monolythic research tradition which one can follow to its current frontier and then logically "take the next step." There are a great many unresolved researchable questions in many areas of leisure­ time behavior. It is a very eclectic area of human activity. Those questions which have been selected reflect personal interests as much as the desire to extend knowledge in this particular area.

Definitions

Several terms which are used throughout this dissertation are defined below:

24 25

1. Lei sure-time—Time perceived by the respondent as not obligated a priori to work, work-related activities, life-mainten- ance activities, routine family duties and responsibilities, and routine social and civic responsibilities.

2. Leisure-time pursuits—Those endeavors, either passive or active, which people undertake during their leisure-time. "Pursuit" is used rather than activity as it does not have the connotative restriction of "activeness."

3. Groups of participants'(people)—Aggregations of individuals defined by their leisure-time life style and pursuits. A verbal pro­ file of groups of individuals built up by relating an individual and his situational parameters to either favorite leisure-time pursuits or those pursuits participated in during 1972.

4. Satisfactions--The meanings or significance which leisure­ time pursuits hold for the respondent, as perceived by him. These can be viewed as the perceived psychological "outputs" or benefits from participating in a pursuit.

These meanings or benefits are embodied in a l i s t of statements (hereafter called "satisfactions statements") of, hope­ fully, unitary affective content. The respondent indicates the relevance of each satisfaction to him (as an output from participa­ tion in a favorite pursuit) through rating each statement on a five- point "importance" scale.

5. Credit--All forms of credit extensions granted to consumers for personal use. It includes charge accounts, credit cards, single 26 and multiple payment loans, installment sal e-credit, and other personal borrowing, such as on insurance policies or from rela­ tives.

Research Questions

The general literature reviews of Chapter I, and in particu­ lar the National Academy of Sciences report, implied or directly suggested a great number of researchable questions in the area of leisure-time behavior. Several of these have been selected on the basis of being particularly interesting and important to this researcher.

It is believed that an exploratory study of these questions can be useful in more clearly defining specific areas worthy of additional intensive study. It is also hoped that the results of this study will directly further the understanding of leisure-time behavior.

Two additional questions of more direct interest to marketers and planners are also included. These deal with the financing of leisure-time products and pursuits and the means by which suppliers might communicate their offerings to the using public.

The selected research questions are as follows:

1. Are there identifiable "satisfactions,” or perceived felt benefits, which people (participants) derive from leisure-time pur­ suits?

2. If there are identifiable "satisfactions," do these "sat­ isfactions" cluster or group together in some manner based upon particular leisure-time pursuits? 27

3. Do people typically engage in definable, fairly distinct, clusters of leisure-time pursuits to the exclusion of other pursuits?

If so, how strongly are the pursuits within a cluster related? Can these clusters be considered reachable, viable market segments?

4. Are clusters of pursuits and clusters of satisfactions related to some discernible extent?

5. To what extent is some form of credit used in the financ­ ing of leisure-time products and pursuits? To what extent is the use of credit in this context correlated with other demographic or psychographic variables? What is the range of attitudes toward the use of credit for leisure-time products and pursuits, and with what variables (if any) do these attitudes covary?

6 . Can specific clusters of leisure-time pursuits, and/or specific leisure-time life-styles be identified with distinct media preferences?

In summary, then the particular leisure-time content areas chosen for investigation in this dissertation are:

1) Leisure-time satisfactions

2) Clusters of leisure-time pursuits

3) The relationship of clusters of pursuits to clusters of

satisfactions

4) Use of credit for leisure-time products and pursuits

5) Leisure-time related media preferences 28

Research Hypotheses

These research questions can be restated, more formally, as testable "hypotheses." The term "hypotheses" is used rather loosely here, insofar as there is effectively no theory per se upon which to base formal hypotheses. There is, however, sufficient related empirical evidence to suggest that these "hypotheses" are both

(1 ) reasonable and ( 2 ) able to be made operational.

H-j: There are definable "satisfactions" which people derive from leisure-time pursuits.

H2 : Leisure-time pursuits and satisfactions can be clustered into distinct groups.

H3 : Specific clusters of leisure-time pursuits and satis­ factions are related to a significant degree.

H4 : There are significantly different patterns in the use of credit for leisure-time products and pursuits by different groups of people.

H5 : There are distinct media preference patterns associated with each distinct cluster of leisure-time pursuits.

Diagrammatic Models

There are several ways in which generalized leisure-time behavior can be depicted. In terms of the "black-box" model (Engel,

Kollat, Blackwell„ 1968: ) one can indicate the various generic forces acting upon the individual as shown in Figure 1.

Figure 1 shows that, considering leisure-time behavior to be a probabilistic (as opposed to deterministic) process, the indicated input variables, as constrained by physical, fiscal, individual and social/cultural forces, will lead to outputs which may be thought of in the terms shown. This is basically a very 29

PHYSICAL AND FISCAL CONSTRAINTS

LEISURE-TIME PREFERENCES- Feedback SKILLS- u t i l i t i e s /s k i l l s INFORMATION- P (l e i s u r e -t i m e b e h a v i o r ) SATISFACTIONS ACCOUTREMENTS- I RESIDUALS LEISURE-TIME'

INDIVIDUAL MOTIVATIONS AND

s o c i a l /c u l t u r a l FORCES Figure 1. Generalized Black-box Model of Leisure-Time Behavior.

0

S U I S A S F

E M R S

Figure 2. Hypothesized Relationships Between Several Key Types of Variables, 30

general model of "consumer behavior" which has been adapted to a

letstire-time behavior context.

Figure 2 depicts the hypothesized relationships between

people, leisure-time pursuits, satisfactions, and media preferences.

The directionality of the relationships shown is not tested in this

dissertation, but merely assumed.

This figure is meant to imply several situations. First,

people engage in leisure-time pursuits. Second, people also have

inner need-states for which they seek fulfillment or satisfactions.

It is hypothesized that people engage in particular leisure­ time pursuits in order to gain certain satisfactions, i.e. fulfill

certain inner need-states. In other words, the satisfaction of the need-state is the sought-after end, and the pursuit is a means to that end.

A relationship between leisure-time pursuits and satisfac­ tions would therefore seem reasonable.

It is also hypothesized that people use particular media both for direct satisfaction of inner need-states through vicarious

involvement, and also as a source of information about a particular pursuit. This information may concern participation requirements or opportunities, characteristics of the pursuit and its typical participant, or location/availability of the pursuit.

A relationship between particular media and particular pur­ suits would therefore seem reasonable, as would a relationship be­ tween satisfactions and particular media (although this is not in­ vestigated here). CHAPTER III

RESUME OF RELATED RESEARCH

Chapter I presented an overview of the state of knowledge and attendant concerns with regard to human leisure-time behavior. Chap­ ter II indicated the particular research questions, out of the many possibilities, which have been selected for investigation. This chapter, in turn, summarizes the reported research dealing with each of the five selected "hypotheses" or research questions.

Before reviewing the literature related to each "hypothesis," a brief discussion of various conceptions of leisure-time behavior will be presented.

Conceptions of Leisure and Leisure-Time

Because of the great diversity of available pursuits, outlets for expression, and intrinsically subjective nature of the pleasures derived, it is doubtful that there will ever be one single, all encompassing "theory of leisure-time behavior" (Lanfant, 1970). The term "leisure" itself is equally amorphous. Sebastian de Grazia

(1962) views i t as a state of being marked by freedom from every­ day necessity and devoted to contemplation and creativity. He points out in a later article (de Grazia, 1968), that in its purest sense leisure is distinct from free time and divorced from any

31 32

contradistinction with work. His is definitely a philosophical

approach based on the early Greeks' view of leisure.

Thorstein Veblen (1918) viewed leisure in a related manner, though more closely tied to the concept of social class structure

in a society. He saw it as a total way of life for the privileged class, and regarded them, in turn, as exploiters who lived off the to il of others. Undoubtedly this view has influenced the traditional deprecation of "leisure-living."

By extension then, lei sure-time is understood to be those blocks of time in which the individual feels free from (perceived) compulsory activ ities or duties, and can devote himself to pursuits of his own choosing and for their own intrinsic value to him. This closely parallels the definition of leisure-time given in Chapter II.

Joffre Dumazedier (1967), a French leisure scholar, sees leisure-time as having three major functions: ( 1 ) relaxation,

(2) entertainment, and (3) personal development. No longer is leisure-time a means to work-oriented end, but rather work has become the means of enjoying leisure-time. Leisure has achieved its own dynamic, in his view, in which the needs of the individual become determined by this new "social right."

Hypotheses-Related Research

H-|: There are definable "satisfactions" which people derive from leisure-time pursuits.

The Lynds. The classic study by the Lynds (1929), Middletown, contains a section on "Using Leisure." This research is primarily 33

a "how," "what," "with what," "with whom," "how much," and "how

many" type of study. There are, however, several references to the

perceived values of certain leisure-time pursuits as seen by some of

their respondents. It is more a case of reading-between-the-lines,

than an explicit statement of the derived satisfactions.

Luridberg, et a l . Another sociological study which appeared

about the same time came even closer to the specific allocation of

want-satisfying properties to various activities. Leisure: A Subur­

ban Study (Lundberg, et a l ., 1929) was probably the f ir s t full book

to result from a study dealing solely with the leisure and recrea­

tional behavior of suburban people. One of the authors' basic goals

(Ibid. , 365) was to "learn something of the nature of the satisfac­

tions man seeks from these (leisure-time) pursuits and the more

common behavior patterns which he has evolved to gratify his

cravings."

The authors, in a study of "good-time" patterns, identify

(1) the thrill of a new experience, ( 2 ) the suggestion of physical

danger, (3) the release from customary norms of conduct, (4) compe­

tition for prizes, (5) aroused dreams of future careers, ( 6 ) peer

group socialization, (7) intellectual challenge, ( 8 ) the satisfac­ tion of solitude, and (9) escape from unhappy family situations as constituent factors in pleasurable leisure experiences (Ibid. , 113-

116). Other related "satisfactions" or "elements of enjoyment" are also discussed. 34

The three authors, summarize their beliefs in a paragraph

which, seems to have gone relatively unnoticed for some twenty

years (Ib id ., 121).

Every person could undoubtedly give a half dozen widely different occasions which he could truly designate as enjoyable. It is interesting to note that in spite of this fact a study of even a comparatively small number of cases reveals such striking preponderance of certain patterns as is reflected in the above tabulation and illustrations. There is evidence also that, greatly as the details of each may vary between different ages and classes, they have a certain elemental similarity. The main patterns are present among practically all groups. People engage in them in response to certain common needs. It is probable safe to assume that relative to the capacities of each group, these activities yield essentially the same type of satisfactions.

Edward L. Thorndike. The historical concern with this aspect

of leisure-time can also be traced back to at least one of the early

psycho!ogists--Edward L. Thorndike (1937). In his study of how

people spend their time and what they spend i t for, he presents

a list of sixteen "wants" business girls supposedly gratified in

varying degrees by seven non-work activ ities. Such "wants" as

(1 ) mental activity, curiosity, and exploration, ( 2 ) manipulation

and construction, (3) companionship, (4) entertainment, (5) approval,

(6 ) mastery over others, (7) affection, and ( 8 ) concern with the welfare of others are among those recognized.

Robert Havighurst. The next major study to investigate lei­

sure-time satisfactions was that by Robert Havighurst and his asso­

ciates in 1952-1955 and as reported in several sources (Havighurst,

1957; Havighurst and Feigenbaum, 1959; Donald and Havighurst, 1959; 35

Havighurst, 1961). This investigation of leisure-time satisfactions was part of a larger study of adult (ages 40-70) "social life" or

"life-style" and social roles which Havighurst and his associates conducted in Kansas City. One of these social roles was that of a

"user of leisure time." A sample of 234 residents of Kansas City was used in this three year study.

In a nineteen item sub-set of the basic questionnaire, the researchers inquired (via interviewers) about spare time activities.

One of the questions was a twelve-item checklist of possible mean­ ings of leisure-time activ ities. This li s t of meanings was as follows:

1. I feel that I am being creative. 2. It gives me a chance to achieve something. 3. It gives me more standing with other people. 4. It makes the time pass. 5. It gives me new experiences: I feel I learn something from it. 6 . It makes me popular among other people. 7. It helps me financially. 8 . I feel I can respect myselffor doing these things. 9. I like i t because I like to do things that will be of benefit to society. 10. It is a welcome change from my work. 11. I like it because it brings me into contact with friends. 12. I like it just for the pleasure of doing it, that's all.

Havighurst and his associates were able to discern not only significant systematic relationships between these twelve meanings, but also between the meanings associated with eleven categories of specific leisure-time activities and, to a lesser degree, between meanings and social class and other personal variables (Donald and

Havighurst, 1959:358-360). They noted with some surprise the rela­ tions between content and meaning, as the categories of content used were "so broad that they might have been expected to submerge 36 some relationships. When such diverse activities are grouped together as watching a football game and playing golf, it is sur­ prising that a special pattern of meanings does emerge" (Donald and

Havighurst, 1959:359).

Recent P issertations. Several recent dissertations have addressed the problem of determining the outputs or benefits of leisure-time pursuits for the participant.

Royal Jackson (1971) examined the relationship of value orientations, leisure attitudes add leisure activity preferences within the framework of a dominant social group and a variant sub­ group. He defined nine "leisure settings" (after Havighurst's

"meanings" of leisure-time activities) which, in effect, described possible reasons for participating in the activity. Jackson, like

Havighurst, found that the greatest apathy and disinterest in lei­ sure occurred in the lower classes, but that there were differing patterns of interest in activities providing different outcomes across the two social classes and two ethnic groups tested.

Charles Johnson (1964), using college sophomores, related individual differences in leisure-time behavior to scores on the

Strong Vocational Interest Blank (SVIB). Through factor analysis and contingency table analysis, he was able to define systematically grouped leisure-time activities (12 factors based on 100 different activities), and to associate these with some occupational interests.

These interests plus the "natural" grouping of various activities, and peripherally collected personality characteristics, lead to the 37

conclusion that certain particular patterns of leisure-time activi­

ties were likely to be consonant with some underlying psychological

domain or need-state.

Hardeep Bhullar (1970) further developed some relationships

researched by Moss (1969; Moss and Lamphear, 1970) on recreational

activities as behavioral expressions of basic personality structure.

The underlying hypothesis here is that recreation is need-fulfilling

behavior and there is a definite inter-relationship extant between

motives or need-states, personality and recreation activities. The

Edwards Personal Preference Schedule (EPPS) was the instrument used

to measure personal "needs." Bhullar did find that dominant motives

or need-states (as defined by the EPPS) were related to outdoor

recreation activ ities though in different ways for males and females

and also between Blacks and Whites. Overlap of activities within

different clusters was also observed as it was by Charles Johnson

(1964).

Finally, Gray (1961), Farina (1965), and Lowrey (1969), all

found associations of varying strength (but typically fairly weak) between personality variables and participation in various leisure­ time activ ities. These personality tra its were taken (or measured) to be indicants of some psychological need-state which might be satisfied by leisure-time activities.

Summary. Although interest in the values or benefits derived from leisure-time pursuits goes back at least some forty-four years, there has been relatively little research on this topic until very :8

recently. Havighurst developed and extended Thorndike's "wants"

into a list of possible "meanings" of leisure-time pursuits. While

several recent dissertations have probed ( 1) reasons for participat­

ing in certain leisure-activities, or ( 2 ) the need-fulfilling quali­

ties of these activities, there apparently has not been an attempt

to extend Havighurst's work.

This study expands upon the l i s t of "meanings" of leisure­

time pursuits (herein called "satisfactions statements") developed

by Havighurst. Additional statements are developed and related to

"favorite" activities (as indicated by the respondent). It seems

reasonable to expect more than twelve possible meanings or satis­

factions as outputs from the wide-variety of possible leisure-time

pursuits. It is believed that this needs investigation in the inter­

ests of a better understanding of "why" people participate in various

leisure-time pursuits.

H2 : Leisure-time pursuits and "satisfactions" can be clustered into distinct groups.

This hypothesis states, in part, that, given that there are

such entities as identifiable "satisfactions" received from parti­

cipation in leisure-time activities (and given that the selected methodology is adequate to the task), these can be grouped.

Charles Proctor. The earliest attempt to cluster or statis­

tically group leisure-time activities was the study by Charles Proc­

tor (1962) for the 1960 National Recreation Survey. He predicted

that people were more likely to take part in several activities 39 within a single group of activities than to take part in activities which fell into different groups. He hypothesized four groups of activ ities aased on the fifteen specific activ ities measured.

These groups, were:

1. Backwoods recreation

2. Boat culture

3. Country club to picnic area recreation

4. Passive outdoor recreation

These hypothesized groups were found to hold true even though they .

"explained" only 50 percent of the variance based upon a principle- axis factor analysis. Furthermore* these four groups were found to hold up to varying degrees across both white males and females in four regions of the country.

Thomas Burton. Thomas Burton (1971), operating in Britain, has been able to replicate Proctor's basic findings of groups of similar activities. He utilized 71 different activities and developed four­ teen groups based upon a "cluster analysis," and eight groups based upon a factor analysis. Several different factor analyses were carried out, with the groups produced by the eight-factor analysis deemed the "most reasonable." Comparison of the cluster analysis groupings and those resulting from the factor analysis resulted in four relatively stable recreation groups.

Bultena and Klessig. On a more specific level, Bultena and

Klessig (1969), citing research done by others, developed five dimensions of camping that appear to be important to the satisfac­ tion which people derive from this activity. These components 40 include: type of resource base, style of camping, level of physi­ cal activity, pattern of social interaction, and the nature of the derived values.

Tatham and Dornoff. A study which, in some respects, paral­ lels this one is an attempt to segment the market for outdoor recreation. This study was done by two marketing scholars at the

University of Cincinnati (Tatham and Dornoff, 1971). It is p ri­ marily a methodological study using data collected by other re­ searchers. The authors utilize cluster analysis, and select a procedure utilizing the Mahalanobis D 2 distance measure in a hier­ archical clustering procedure.

Ten market segments are developed based on twenty leisure­ time activities and nine socioeconomic characteristics. L ittle interpretation of the meanings of the clusters is given, however.

As developed, they are only marginally operationally useful, as no data are included as to how to "reach" the different clusters.

Others. Finally, the studies by Havighurst (Donald and

Havighurst, 1959), Johnson (1964), Farina (1965), Moss and Lam- phear (1970), and Bhullar (1970) were all able to develop clusters or groups of statistically related leisure-time activities, albeit by using college students as subjects (except Havighurst and Farina who used non-student subjects). 41

Summary. The basic critique of all of these studies (with

the exception of Bhullar's dissertation) is that, individually, they do not go far enough.

Secondly, the research of Havighurst is based on a very

limited sample (234) in one city twenty years ago. This needs replication on a broader scale.

Third, the Proctor study is based on data that is twelve years old, while the Burton study was done in Britain. There is a need for a study approximating the depth of Burton's using cur­ rent United States data.

Fourth, the potential hazards in extrapolating results obtained using college students as subjects are well known.

Fifth, the ab ility to use the newer measures of life -sty le s or "psychographics" provides a potential opportunity to develop a much richer and more useful (to both marketers and public policy makers and planners) set of groupings of leisure-time users. This is in some degree substantiated by the unclear results of the

Tatham and Dornoff study which utilized only some basic socioeconomic variables as discriminators.

Based on these five points, there would appear to be a need to research the clustering or grouping of leisure-time pursuits fur­ ther using a broad range of pursuits as options.

There also would appear to be a need to investigate the ex­ tent to which meanings or satisfactions derived from participation in particular pursuits, or groups of pursuits, cluster or group 42 together. This apparently has not been done since the Havighurst study. Knowing whether a particular lei sure-time pursuit provides one or a group of benefits or satisfactions, and to whom, has poten­ tial utility in the planning and management of these pursuits and their associated facilities.

H3 ;. Specific clusters of leisure-time pursuits and satisfactions are related to a significant degree.

This hypothesis takes the various research emphases resulting in, and being further extended by, H-| and H 2 , and moves one step further by attempting to determine if groups of pursuits and groups of satisfactions are related.

No published studies were located which directly attempted to verify or reject this relationship using self-reported satis­ factions received from leisure-time pursuits. The very strong impression remaining after reviewing the studies cited above, is that this is a logical "next step" in attempting to understand why people choose one leisure-time pursuit over another.

As discussed above, both Moss and Lamphear (1970) and Bhullar

(1970) were successful in relating clusters of outdoor recreational activ ities to personal needs of the participants as measured by the

EPPS. Farina (1965) used a "Likes and Interests Test" and also found "... some association between personality scales as measured and free-time activity patterns. The association is not strong . . ."

Correlations were not strong in all cases, however.

1 43

This research does appear to indicate that there are clus- terable inner needs which are satisfied through participation in certain specific leisure-time activities. The question now becomes whether the more pragmatic and tangible, self-perceived and reported, indicants of satisfactions received used in this study can also be related to leisure-time pursuits. From a marketing standpoint, it is difficult to see the utility in knowing that participants in a given group of pursuits are high on succorance,* nuturance* and endur­ ance,* while another group is low on abasement* and intraception.*

H^: There are significantly different patterns in the use of credit for leisure-time products and pursuits by different groups of people.

A priori, there would seem to be at least two related under­ lying forces at work in determining attitudes toward leisure-time pursuits and their financing. Those people who still subscribe to the so-called Protestant Ethic will probably have difficulty in experiencing any significant amount of leisure-time activity without a sense of guilt (Gray, 1972:5-6). One might predict that these people, controlling for income and education, would be more likely to save their funds and purchase leisure-time goods and services, rather than use credit in one form or another. Not only does the

Protestant Ethic glorify work over leisure, but also ostensibly praises thrift over debt.

*Several of the EPPS categories found significant by Moss and Lamphear. At the other end of the continuum, people (again controlling for income and education) not as constrained by these more tradi­ tional values may experience a more leisure-centered life-style.

These people may also be more prone to using credit, when conven­ ient or "necessary," for "immediate" gratification of a leisure­ time desire.

One might therefore predict differences in patterns of financ­ ing leisure-time goods and services. Rather obviously, one would be limited in making inferences about the extent of influence of the "Protestant Ethic" to analysis of surrogate variables and patterns of relationships among them.

Credit Usage. Credit is widely regarded as an element in the re ta ile r's merchandising mix or strategy. Beckman and Davidson (1967

703) state that

. . . In general, however, the consumer is prompted to use credit by one or more of three sets of motives: convenience, a desire- for immediate improvement of his standard of living, and necessity.

They go on to point out (Beckman and Davidson, 1967:704) that the increasing use of consumer credit is, in part, due to,

. . . (1 ) growing acceptance of credit as an institu­ tion of modern society, as opposed to a puritanical aversion to indebtedness; ( 2 ) increasing levels of per-family income which has enhanced the demands for goods commonly sold on a credit basis and caused a larger proportion of the population to qualify as acceptable credit risks; and (3) a wider variety of credit or financing arrangements . . . 45

A number of authors agree with Beckman and Davidson on the contention that Puritanical attitudes or values toward credit are easing—but have not disappeared entirely, by any means. Chase

(1965:366) states th at, "Today [1965] only 1 American in 10 believes it morally wrong to go into debt."

Survey Research Center (Michigan) Studies. James Morgan (1968:

21-22) of the Survey Research Center of the University of Michigan reports a more discriminating attitude toward the use of installment credit. Interestingly, he reports that only 9 percent of the popula­ tion view credit as an acceptable means of financing a vacation. This figure has not changed during the period 1959-1967. In order of acceptability, vacation use of credit ranks seventh behind uses for medical expenses, education, car purchase, furniture, b ill paying and covering expenses when income is cut. Use of credit also seems to be a middle income phenomenon. According to Morgan (1968:21), high income people seem to use it "more rarely but for longer period commitments."

Credit Cards. The recent surge in the use of credit cards as an instrument of consumer credit dates from 1950. Prior to this time, cards had been issued by one firm for use in its establishments only. According to Mandell (1973:3),

In 1950 another dimension was added to the credit card when Frank X. McNamara decided that the credit card would be more useful if i t could be used at more than one place . . . Out of this plan grew the Diners Club credit card operation . . . Diners Club, the first so-called 'travel and entertainment card,' was later joined in the field by other such operations including American Express and Carte Blanche. 46

Banks entered the credit card market in 1951 when the Franklin National Bank of New York developed its credit card plan. By 1955, this number had grown to more than 100 banks with credit card plans.

Mandell (1972:4) goes on to state that, "In 1970, more than

seven billion dollars was charged on bank cards."

The most comprehensive recent study of credit card use in

general in the United States is that reported by Lewis Mandell (1972)

of the Institute of Social Research of the University of Michigan.

This report summarizes the data compiled from three nationwide

studies conducted in 1970 and 1971, involving the personal inter­

views of 3,880 heads of households.

Although this study is quite comprehensive, only passing men­

tion is made of the use of either bank or store credit cards for

recreation or travel items. Fully 30 percent of all families inter­

viewed used a bank card for travel-related purchases, but only 5

percent of all families used this type of card for recreation items

(Mandell, 1972:70). When broken down by income and age categories,

the "under $10,000" annual family income group and the "under 35"

age of head of household group accounted for the largest use of bank

cards for purchase of recreation items. The "$15,000 and over" and

the "age 55 and over" groups were the largest users of bank cards

for travel-related purchases.

With regard to store credit cards, only 8 percent of all families used these cards for the purchase of recreation items—the fourth ranking type of purchase (Mandell, 1972:4). The "under 35" 47

age of head of household group was again the most frequent users

of this type of card for the purchase of recreation items. The

"$10,000-14,999" income group, however, was the most frequent group

in this CuS? tv use store cards to buy recreation items.

'Li fe-Sty1e Pi fTerences in ’ Use’o f'Credi t—Ross Gobie. Several

stu'dies were found which suggest life-style differences in the utili­ zation of credit. Qoble (1970:368-376) explored the "life behavior profile" of two groups of consumers. One group was a high credit risk, low income group and the other was a group of university stu­ dents. The low income, less educated group was significantly d if­ ferent in their life behavior profile than the university students.

While many of the differences found could have been predicted a priori because of the nature of the two samples, several inter­ esting results stand out.

The sample of people "who have chronically failed to utilize their consumer credit effectively" indicated that they had appreci­ ably more difficulty budgeting their money properly, figuring out the full cost of an item bought on credit, and developing and carrying out fairly detailed long and short range plans.

These results might be interpreted as suggesting that it is a recognized inadequacy in comprehending the complexities of credit financing, coupled with difficulty in perceiving the future and planning accordingly, which may keep lower income, less educated people from using credit for leisure-time goods and services. This is only a very tenuous implication, as there are many cases of lower- income overuse of credit. 48

' Mathews' and SIocum. Mathews and Slocum (1969:71-78; 1970:

69-74) have published two somewhat confusing and conflicting accounts of the effects of social class on bank credit card usage. Using

Hollingshead's two-factor index of social position (combining occu­ pation and education), they found significant differences across social classes in the pattern of use of bank credit cards for either charge account or installment purchasing. The lower classes tended to use their credit cards for installment financing to a greater extent than upper classes. The authors interpreted this greater use by the upper classes of the charge account aspect of credit cards (paying the balance within the billing cycle) as a greater preference for convenience.

Interestingly enough, both installment users and convenience users showed about the same profile of attitudes towards goods con­ sidered chargeable. Goods and services which might be considered to be leisure-time related garnered a smaller percentage of favor­ able attitudes toward charging. Consumer durables, education, medi­ cal expenses, and gasoline were seen by both groups as eminently chargeable. With the exception of "vacations," the upper classes

(predominantly the "convenience" users) were somewhat more favor­ ably disposed to charging "luxury goods" or leisure-time goods.

Installment users were slightly more favorably disposed toward charging vacations.

Finally, the authors (Mathews and Slocum, 1969:78) conclude that, "installment credit card holders tend to seek out stores 49 honoring th eir cards," while "convenience users state that they do not seek stores accepting the bank charge plan." This state­ ment holds is of interest in this study to the extent that if a particular leisure-time pursuit caters to different social classes, purveyors of that pursuit and its accoutrements may or may not wish to accept bank credit cards and their attendant costs.

In a follow-up article, these same two authors reanalyze their data, and, holding social class constant, decide that income alone is a useful segmentation variable. It appears that "neither segmentation variable influences consumer attitudes more than the other" (Slocum and Mathews, 1970:73). Within the upper income categories, the authors state, social class does, however, appear to be a somewhat more valid segmentation variable. Again, the data appear to have several limitations.

Joseph Plummer. The la st study deemed to have a direct bearing on this hypothesis is one by Plummer (1971:35-41). He attempts to extend the findings of Mathews and Slocum along life­ style dimensions. Using AIO measures, he draws profiles of the male and the female bank charge card holders. Approximately 17 percent of his total sample of 1845 used bank cards. Ten percent used them less than three times per month, and seven percent used them more than three times. Unfortunately, the data presented only distinguishes between users and non-users without accounting for intensity of use.

The general conclusion is that users are modern rather than conservative, and have an active, upper-socioeconomic, upper-suburban, 50 convenience-oriented life-style with many interests outside the home. This result, to the extent that it is generalizable, would appear to imply that different patterns of credit usage may exist within differing life-styles and social-classes with regard to the purchase of leisure-time goods and services.

Summary. The question whether or not so-called traditional or Puritanical attitudes toward the use of credit for leisure-time oriented purposes remain, and to what extent, is s till not answered.

There would appear to be a need to replicate studies now five years old to determine how much of a shift in these attitudes has occurred in the intervening period. This seems particularly a propos in view of Mandell's very limited treatment of leisure-time oriented uses of credit cards. He also did not study the usage of long-term credit for leisure-time oriented purposes.

Finally, the use of AIO measures in distinguishing between users and non-users of credit, and between users of credit for one purpose (or type of purpose) and another, is still in its infancy and needs additional applications.

H^: There are distinct media preference patterns associated with each distinct cluster of leisure­ time pursuits.

No studies have been found which directly attempted to relate media preferences to leisure-time behavior patterns. Wells (1972) did discuss the characteristics of air travelers who read Playboy or National Geographic, but this was done in a very general manner and did not refer to any other media preferences. 51

In a more general sense, a number of researchers have related

media of one form or another to market segments. Factor analytic

and clustering techniques have been used to group magazine readers

into potentially useful market segments.

Bass, Pessemier arid Tigert. Bass, Pessemier and Tigert (1969)

found five distinct factors (through factor analysis) and three

distinct clusters (through another clustering technique) of magazine

and newspaper readers based on forty-four periodicals and a sample

of 344 housewives. They were also able to significantly discriminate

between at least two of the three clusters using four (of eight)

socioeconomic variables and four (of fourteen) AIO factor scores.

Wells and Sheth. Wells and Sheth (1971) report the results

of a similar study using th irty magazines and “a large sample of

adult males." They, too, used factor analysis techniques and, after

rotation, came up with ten fairly "clear" and interpretable factors.

It is interesting that two of their factors agreed (as far as they went) with two of the five factors found by Bass, et a l . (1969).

Since Wells and. Sheth used male-oriented magazines and Bass, et a l .,

used female-oriented periodicals, most of the two lists of periodi­

cals were different.

Summary. It does seem possible, therefore, to expect to be

ahJe to group respondents by preferences for "similar" media. It is also expected that media habit patterns can be related to leisure­ time behavior patterns. Quite obviously, the ability to identify specific media preferences with specific leisure-time pursuits is 52 critical i.f marketers are to reach and communicate with participants in these pursuits.

A glance at any fairly extensive newstand will reveal the proliferation of specialized leisure-time periodicals obviously catering to specific pursuits. L ittle is known, however, (based on published studies) about the appeal of mass circulation periodicals to participants in different leisure-time pursuits or groups of pursui ts .

This study attempts, therefore, to determine if groups of related leisure-time pursuits are also significantly related to var­ ious mass circulation magazines, and to the most prevalent television program-types.

Related Research

Subsequent to the in itiation of this research project, two other similar in-progress studies have been reported.

Professor Frank Sessions (1972) of Central Washington State

College has initiated a pilot survey on work, leisure, and recrea­ tion in that area of the state of Washington. As it turns out,

Professor Sessions asks many of the "same" questions contained in the present study.

The National Parks Branch of the Canadian Bureau of Indian and

Northern Affairs (Beaman, 1973) is in the midst of a very comprehensive study of Canadian outdoor recreation demand patterns. Although the available information is sketchy, the development of usable (for 53

planning purposes) packages of correlated activities through the use of factor analytic and clustering methods is one of the prime focal points of this effort.

Conclusions

The literatu re reviewed in connection with each of the five hypotheses is believed to support the thrusts of each of these hypo­ theses. While some information is known about each of the five areas, there is much more that is still to be learned. Marketers and public planners in the area of lei sure-time products and pursuits need to have a better understanding of why their markets behave as they do and how they can best communicate with these markets. There is also a need for a better understanding of the role of credit in the marketing process for these kinds of goods and services. CHAPTER IV

METHODOLOGY AND PRETESTING

This chapter discusses the mechanics of operationalizing the research questions outlined in Chapter II. A brief overall research plan or approach is fir s t presented, followed by a detailed research design. The research design first restates the research questions

(or "hypotheses") in the form of testable null hypotheses. It then defines the variables necessary to be measured to test each hypothe­ sis. Discussion of the pretesting effort leads to the final config­ uration of the questionnaire. Sample selection and the method of collecting the final data precede a brief discussion of the data analysis approach. A brief discussion of methodology and of questionnaire reliability and validity concludes this chapter.

Overall Research Plan

The basic research plan for this dissertation involved col­ lecting data on a fairly comprehensive group of leisure-time oriented variables from a representative cross-section of the American popula­ tion. The variables selected were dictated by the five hypotheses stated in the previous chapter.

The primary interest was to select specific variables, within the constraints of the hypotheses, which would result in data per­ mitting conclusions usable by private management or by public offi­ cials interested in leisure-time planning. 54 55

This study was designed to be the fir s t in an ongoing research program delving into many aspects of leisure-time behavior. In this

context, one objective of this project was to delineate areas worthy of further intensive study. As a result, a substantial amount of data were to be collected beyond those required for the evaluation of the five stated hypotheses.

Given the nature of the five hypotheses, and the goal of providing actionable information as an output, a fairly large nation­ ally representative sample of the American population was obtained.

A nationwide mail questionnaire survey method of data collection was selected as the most appropriate for this study.

Previous empirical studies have generally employed a local or regional sample. While this may be appropriate for accomplishing some objectives, the nature of leisure-time behavior, conditioned by climatic, available facility, and socio-cultural factors as it seems to be, argued for a sample which covers many different regions of the country and a wide range of social and economic strata.

A promising alternative, laboratory experimentation, was rejected at this stage of leisure-time behavior research. This method is believed to hold more promise for follow-up studies of limited areas of leisure-time behavior in which the controllable and uncontrollable variables are more clearly defined. Some work along this line has already been done, however, in determining visual preferences for scenery and beaches (Rabinowitz and Coughlin, 1970;

Shafer, Hamilton and Schmidt, 1969; Peterson and Neumann, 1969). 56

The. data collection instrument was pretested in three phases which are discussed in more detail in a later section of this chap­ ter.

Research Design

The particular research design selected, or "specified frame­ work for controlling the collection of data" (Boyd and Westfall,

1972:45), is primarily in the "exploratory research" category. As discussed in Chapter III, the basic thrust of the research involves the search for usable leisure-time product and pursuit market seg­ ments. Primary emphasis in this study, therefore, is on delineating potential bases for such segmentation, and locating variables poten­ tia lly useful in describing or reaching such segments as rnay be found.

Although the study is primarily exploratory, there is also an element of descriptive research involved. This aspect of the research attempts to determine life-style and demographic character­ istics of different leisure-time behavior patterns.

Null Hypotheses. The five hypotheses stated in Chapter II are now restated in a more directly testable "null hypotheses" form.

H-j There are no definable "satisfactions" which people

derive from leisure-time pursuits.

Hg Leisure-time pursuits and "satisfactions" cannot be

clustered into distinct groups.

H3 Specific clusters of leisure-time pursuits and satisfac­

tions are not related to any significant degree. 57

There are no significantly different patterns in the

use of credit for leisure-time products and pursuits

by different groups of people.

H5 There are no distinct media preference patterns associa­

ted with each distinct cluster of leisure-time pursuits.

The term "distinct" refers to the situation where a particular group

of variables relate more close!, to each other than to the other

variables in the analysis. In correlational situations, this will

be taken to mean a majority of intercorrelations within the group

of at least 0.30. In factor analytic situations, this will be taken

to mean groups of variables associated through loading on a common

factor at 0.400 or greater. The factor itself must account for

approximately 5 percent or more of the data variance.

The term "significant" will be interpreted judgmentally based

upon the results of the analysis. This is necessitated by the parti­

cular analytical methods to be employed in testing the hypotheses

(as stated). For example, there is no generally accepted te s t for

determining the number of factors or clusters which are statistical 1.y

significant.

It is believed that the costs of a Type I error (rejecting a

null hypothesis which is in fact true) are higher than those of a

Type II error (acceptinq a null hypothesis which is in fact false).

In the marketplace for leisure-time products and pursuits, taking

some action on the basis of erroneously rejecting one of these null hypotheses could potentially be more costly than taking no new

action because one of these null hypotheses was erroneously accepted. 58

Research Variables. The different hypotheses require data to be collected on the following variables. Variables are listed by hypothesis number with the understanding that if a latter hypothe­ sis requires a variable already needed by an earlier hypothesis, that variable will not be listed twice.The question number in parentheses refers to the questionnaire in Appendix A. H-j 1. Respondent's favorite leisure-time pursuits (three

pursuits selected from a list of fifty) (question 5a)J

2 . "Satisfactions" statements rated on a 1-5 very impor­

tant/not important scale (question 5b).

Hg 1. List of fifty popular leisure-time pursuits (question

4 ).

2. A categorical response as to whether or not the respon­

dent has participated in each of these pursuits in the

past (question 4A).

3. The number of times the respondent engaged in each

pursuit in 1972. A four level categorical scale is

used with different levels for each of three groups

of pursuits (question 4B).

• H3 (Same variables as those used for testing H-j.)

Hhese are listed in Table 7 of Chapter V, and discussed in the following sections on pretesting. 59

H4 1. Major credit cards held by the respondent (question

lb).

2. Usage rate of each card relative to a year ago

(question lb).

3. Respondent's rating, on a 5-point important/unimportant

scale, of each of a fourteen-item list of credit card

characteristics (question 1c).

4. A checklist (yes/no) of the purposes for which the

respondent has used credit during 1972. A list of

twenty-one purposes is given (question Id).

5. A categorical rating of the number of times during

1972 that the respondent used credit for each of the

twenty-one purposes listed (question le).

6 . A twenty-two item checklist of purposes for which the

respondent might consider the use of long-term (90

days or more) credit (question 2).

7. Respondent's agree/disagree rating of a series of

AI0 statements. Seven credit-oriented statements

are presented along with eighty other statements

(question 11).

8 . A set of demographic variables including:

a. Respondent’s age^ b. Respondent's religion (question 22) c. Respondent's education^

^These come from Market Facts household demographic data card —see Appendix B. 60

d. Total family income 2 e. Household size2 f. Occupation of husband^ g. Rural/urban location of household 2

Hg 1. A checklist (read regularly?) of ninety-two of the

most popular mass-circulation magazines (question 12).

2. Respondent's like/dislike rating of eighteen tele­

vision program-types (question 31).

3. Respondent's stated preference of which of nine

different sources of information about leisure-time

opportunities he typically utilizes (question 30).

4. Leisure-time pursuits as described under H2 .

Pretesting of AIQ Statements

After the particular variables to be used in the study had been violated, it was decided that two particular groups of variables

required pretesting in order to determine those which were discrimina­ ting in the context of the present study. These two groups were

the "satisfactions" statements and the Activity-Interest-Opinion

(AI0) statements.

Other studies had indicated that AI0 statements did provide valid discriminatory indices. The problem was that the available stock of 300 AIO statements from which to draw (Wells, 1971) was both too large to use in its entirety, and too lacking in leisure­ time oriented statements to be the sole source of statements.

It was decided to limit the group of AIO statements to not more than one-hundred. Wells' list of 300 AIO statements was screened 61 for those which seemed most appropriate to the present study. A number of new statements were developed dealing with lei sure-time interests and attitudes. Eventually, a total of one hundred and six statements were collected and formatted into a short questionnaire.

A further question to be resolved was whether to use a five or a seven point agree-disagree scale. Several previous AIO studies had used a seven point scale. A five point scale was preferred in this study in the interest of minimizing respondent fatigue given the amount of data to be collected. To test for differences between the two scales, one hundred questionnaires in each of the two scale formats were printed.

The two scales were as follows:

(5 point) SA AS U DS SD

(7 point) DD GD MD U MA GA DA

Respondents were to circle the response which best indicated their agreement or disagreement with the statement. The f irs t page of the questionnaire identified the scale categories as follows:

SA - Strongly Agree DD - Definitely Disagree

AS - Agree Somewhat GD - Generally Disagree

U - Undecided, no opinion MD - Moderately Disagree or the statement does not apply at all to me. U - Undecided, no opinion, or the statement does DS - Disagree Somewhat not apply at all to me

SD - Strongly Disagree MA - Moderately Agree

GA - Generally Agree

DA - Definitely Agree 62

It was assumed that the scales did not differ in other ways detri­

mental to this study (for example, the reversed agree/disagree order).

It was also assumed that both the two-point and three-point (on each

side of "U") versions spanned the same conceptual space. Eighty-

five copies of each of the two forms (identical except for the scale

length) were eventually distributed to various staff members of the

Ohio State University Research Foundation.

AIO Pretest Results. Fifty-seven of the five point scale

version were returned while 47 of the seven point version came back.

This difference is significant at the .10 (2-tailed) level (but

not at the .05 level) using a chi-square test. The five point scale produced an average of 10.23 "undecided" answers per respondent, while the seven point scale had 10.24 "undecided" responses per

respondent. Only three of the one hundred and six statements had means that were significantly different (at the .01 level using a

t-te st) between the two scales. Three other statements were signi­

ficantly different at the .05 level.

Seventeen of the statements were eliminated from further

use based upon one of the following criteria.

1. A statement showed six to eight (or more) correlations

of 0.35 or greater with other statements. Correlations

of 0.252 or greater are significant at the 1 percent

level for 102 degrees of freedom (sample size of 104).

2 . The frequency distribution of the responses to a statement

showed 20 percent or less of the responses on one side of 63

the neutral point ("U" on the scale) plus those in the "U"

category its e lf. In other words, on a seven point scale,

more than 80 percent of the responses fell in categories

1, 2, and 3 or 5, 6 , and 7. Using an 80/20 sp lit as a

cutoff criterion is frequently the decision rule used in

published studies, and is a fairly conservative rule.

The conclusions reached from this pretest were that (1) no appreciable amount of information would be lost by using a five- point scale rather than a seven point scale, and ( 2) the remaininq

AI0 statements appeared to have good discriminatory ability. These conclusions are tempered by the fact that this was a small, non-random sample.

Pretesting of "Satisfactions 11 Statements

The initial concern with the "satisfactions" statements included not only the need to develop a reduced subset of statements from all possible ones, but also whether or not subjects would be able to understand and discriminate between the various statements.

The writer intended to use the full twelve item set of statements developed by Havighurst (Donald and Havighurst, 1959:357, and page of Chapter II), plus a number of additional statements developed after thoroughly researching the literature on leisure-time activi­ ties. In many articles or texts, authors would state or imply that people derived such-and-such a benefit or meaning from a particular activity. In most cases, no research data were given to support the author's claim. It was decided to attempt to test these claims. 64

An initial list of forty-seven, seemingly independent "satis­ factions" (or "meanings") statements was compiled which included ten of the oriqinal twelve Havighurst statements. Two of these statements were not included because of insignificant correlations in the original study. A questionnaire was composed in which the respondent was asked to select two of his favorite lei sure-time activities and then rate each of the forty-seven satisfactions state­ ments in terms of its importance to him as a reason for engaging in the activity. Each statement was rated twice, once for each activity.

A seven point rating scale was used consisting of very-fairly- somewhat important/unimportant.

The sample used in this pretest was composed of sta ff and several graduate students of The Ohio State University. Approxi­ mately ninety questionnaires were given out to both men and women.

Forty-seven respondents returned questionnaires giving a total of ninety-four activity ratings. No distinction was made as to the sex of the respondent, nor were any other classificatory data collected.

Satisfactions Statements Pretest Results. Even though no attempt was made to separate the responses by sex, favorite activity, or other variables, a number of fairly clear-cut "global" clusters of satisfactions statements emerged. A factor analysis of the data produced 7 or 8 seemingly meaningful factors. An interval cluster analysis was also performed, and the "best" output resulted in 6 clusters. 65

These clusters of "global" satisfactions revealed that only

13.8 percent of the intercorrelations among the statements were

greater than 0.4, and only 4.8 percent above 0.5 with the highest

being 0.63. Clusters or factors can be developed on the basis of

low intercorrelations, but these statements were initially selected

on the basis of their (perceived) relative independence.

In addition, fifteen statements were eliminated from further

consideration based upon the same two criteria used for selecting

the final group of AI0 statements. In this case, all but one of the

statements that were dropped were discarded based upon a frequency

distribution skewed greater than 80/20. It is noteworthy that of

the ten original Havighurst statements included on the pretest, six were eliminated based on a skewed distribution-as indicated in

Table 2.

Study Sample

It was decided to utilize the Consumer Mail Panels (CMP) facility of Market Facts, Incorporated of Chicago, Illinois after consideration of several alternatives. Market Facts maintains a national sample of 45,000 households that have agreed to respond to mail questionnaires and product tests. Balanced samples of 1000 households have been constructed to parallel 1970 census data for the United States with respect to geographic divisions, and within each division by total annual household income, age of female head of household, and population density and degree of urbanization of residence location. A considerable amount of household member 66

Table 2

Original Havighurst "Satisfactions" Statements

Eliminated in Pretesting 3

Number of 0bservations=94

80 Percent or More of the Statement Sample Observation Responded That i t was------t o them

1. It gives me a chance to achieve something. Important

2. It gives me new experiences; I feel I learn something from it. Important

3. It helps me financially. Unimportant

4. I like i t because I like to do things that will be of benefit to society; I like being involved. Unimportant

5. It is a welcome change from my work and other daily routines. Important

6 . I like it just for the pleasure of doing i t , th at's a l l . Important

aThe full list of 12 statements used in the original Havighurst study is given on page in Chapter III of this dissertation. 67 characteristics data (demographics) is "on file" for each household.

Response rates are advertised to be typically 60 to 70 percent or better, even on long and complex questionnaires. This response rate is achieved, in part, by the use of gifts (incentives) as rewards for returning a filled-out questionnaire.

Sample Limitations. Several limiations were recognized, but were judged to be within acceptable "cost" limits. One limitation was that the CMP sample is a female-oriented sample, "while at the same time representing as closely as possible and practical a household sample" (Market Facts, 1973:3). This meant that (1) a lov/er response rate could be expected from the male head of the household than from the female "panel member," and ( 2) male and female responses would not be independent—necessitating a dichoto- mization of the data bank into male and female subsets.

A second limitation or concern was with the representative­ ness of the panel members as a sample of the U. S. population in general. Market Facts, in a communication with this writer, indica­ ted that although they do not advertise or suggest that the results of tests using their panel members be extrapolated to the U. S. on a whole, many users of their services do so, apparently successfully.

In a further communication, Market Facts (1973) stated,

The means by which Market Facts obtains its controlled mail panel members is by buying lis ts of names from various sources, randomly selecting names through the use of telephone books, by referrals from our current CMP members, and also through our field department. 68

There are no data available, to this w riter's knowledge, on the

actual deleterious effects, if any, from these practices. The pri­

mary concern here is if a bias does exist, is it one which is likely

to significantly distort the relationships found in this particular

study?

A third limitation of panel studies in general is that of

bias in the responses from panel members who are ( 1) trying to

look good, ( 2 ) trying to appear as an expert or someone different

from whom they really are, (3) are bored, annoyed, or fatigued

from answering questionnaires at frequent intervals. Market Facts

indicated to this writer that one questionnaire a week is not at all

unusual for many panel members. They also acknowledged that panel

members did tend to overreport in certain (unspecified) categories

of data.

The assumptions were made that (1) none of the above factors

would seriously bias the kinds of data to be sought in this study,

and (2 ) the panel members would be sufficiently representative of

non-panel members in their leisure-time interests to permit some

generalizations. It should be emphasized that these were assump­

tions, and not the result of empirical data.

Sample Selection. Budget considerations dictated that a

sample size of 1000 households could be used, with a separate but

identical questionnaire going to both the male and female head of

household. The 1000 households were to be a specially selected group composed of households drawn from other panels. Each selected

household was to ( 1) have a male head of household present, ( 2) have 69 a total annual household income in excess of $4000.00, and (3) other balancing characteristics as close to the U. S. Census figures as possible. Table 3 shows the composition of the final sample in rela­ tion to the Census characteristics.

Eliminating households with income less than $4000.00 was a judgment based on two considerations. One is that households with this level of income or less are probably only marginally able to consider commercial leisure-time activities in their plans. As such, they would comprise a very small market for firms interested in purveying leisure-time opportunities, even though this group does consist of 13 percent of the national population.

A second reason for eliminating this group is the historically lower response rate to mail questionnaires from low income groups.

It was fe lt that the loss in representativeness would be worth the potential gain in more responses from income groups more likely to be interested and active in leisure-time pursuits.

An unexpected byproduct of this income category deletion was the slight-to-moderate distortion of the percentages in all other balancing categories relative to the U. S. norm. Thi*s is^particular- ly true (and significant) in the case of the Age of Panel Member categories. The final sample is overrepresentative by some 11 per­ cent in the "Under 25 years" category and underrepresentative by an equal percentage in the "55 years and over" category. This is shown in Table 3. 70

Table 3

Comparison of Percentage Distribution of Selected 1000 Households

Versus Distribution of U.S. Population Based on

1970-1971 U.S. Census Data

Selected 1000 Total U.S. Household Sample Population

Geographic Division New England 5.9% 5.8%* Middle Atlantic 18.7 18.6 * East North Central 18.0 19.5 * West North Central 7.9 8.2 * South Atlantic 14.9 15.0 * East South Central 6.8 6.1 * West South Central 9.5 9.5 * Mountain 3.8 4.1 * Pacific 14.5 13.2 *

Total Annual Household Income Under $4000 0% 13.0% $4000 - $5999 11.9 11.1 $6000 - $7999 14.0 11.7 $8000 - $9999 15.5 12.3 $10,000 - $14,999 32.5 27.0 $15,000 and over 26.1 24.9

Population Density and Degree of Urbanization Rural (under 2500) 15.3% 17.2%* Urban (2500-49,999) 11.6 11.7 * SMA 50,000 - 499,999 - - Central City 9.1 8.8 * Urban 4.5 5.0 * Rural 3.3 4.3 * SMA 500,000 - 1,999,999 - - Central City 11.5 11.1 * Urban 12.9 11.8 * Rural " ' ~~ 3.7 3.0 * Table 3 (Continued)

Selected 1000 Total U.S. Household Sample Population

SMA 2,000,000 and over Central City 11.9 12.1 * Urban 14.3 13.4 * Rural 1.9 1.6 *

Age of Panel Member (Female Head of Household)^ Under 25 years 22.7% 11. 1% 25 - 34 years 26.2 19.9 35 - 44 years 15.9 18.7 45 - 54 years 15.0 19.3 55 years and over 20.2 31.0

*These percentages are based upon Sales Management Survey of Buying Power, July 10, 1972, Page B -l, Section B, et seq. , not U. S. Census Data. They represent recognized estimates of household distribution by geographic division and population distribution as of December 31, 1971. 72

The Questionnaire

Once the decision to use a mail questionnaire was made, the writer formulated some sixty-questions--most of which were multiple part. Through consultation with Market Facts personnel and faculty at Ohio State, this list was reduced to essentially forty-five ques­ tions. Market Facts requested the addition of "precoding" cate­ gories for each response. This researcher was assured that the presence of the precoding numerals had not in the past been observed to be a cause of bias in the responses.

It was decided to use a single version of the questionnaire for both the husband and the wife. Although there were a few excep­ tions, essentially all of the questions could logically be answered by either party.

Market Facts then composited, printed and bound the question­ naire into a booklet form, twenty pages in length. In order to accommodate all of the questions, the final printed type-size was reduced to eighty percent of normal elite type. Appendix A con­ tains a copy of the final version of the questionnaire, which differs only slightly from the pretest version.

Market Facts Pretest

This "pretest" questionnaire was thereupon mailed to a

"balanced" sample of 100 households around the country. The sample was balanced on those factors discussed above under Selection of the Sample. All income groups were included in this pretest. Each 73

household was preselected to insure that a male head was present.

Each household then received two identical questionnaires with appropriate instructions on filling them out.

It will be noted that there are no questions on the study questionnaire concerning respondent or household demographics. As noted above, this information is already on file for each panel household (updated as of January, 1973). Appendix B contains a summary of Market Facts' Code Book for their Panel Member Basic

Data Card. This summary indicates the specific demographic vari­ ables on which data are collected.

Market Facts Pretest Results. Tabulation of returns was terminated after six weeks, at which time sixty-four households had returned usable questionnaires.

1.-Results--Demographic Distributions. Table 4 shows the in itial frequency distribution of the one-hundred households across several demographic variables. It also shows the frequency distribu­ tion of both returning and non-returning households on these same variables.

It can be seen from this table that the distribution of returns and non-returns follows the pattern of the distribution of the initial sample fairly well. These figures do indicate some ten­ dency for the non-respondent households to be more rural than metro­ politan, lesser educated, older, and generally in the lower socio­ economic strata. This bias did not appear to be excessive. 74

Table 4

Comparison of Initial Distribution of 100 Pretest

Households with Returning and Non-Returning

Households on Selected

Demographic Variables

(Percentages)

Initial Non- SampleReturns (64) Returns (36)

Geographic Division* New England 5% 4.7% 5.5% Middle Atlantic 19 18.7 19.4 East North Central 19 20.3 16.6 West North Central 9 6.2 13.8 South Atlantic 14 14.0 13.8 East South Central 6 6.2 5.5 West South Central 10 11.0 8.3 Mountain 5 6.2 2.77 Pacific 13 12.5 13.8

Total Annual Household Income* Under $4000 6% 4.5% 8 .2% $4000 - $5999 9 9.4 8.2 $6000 - $7999 11 10.9 11.0 $8000 - $9999 12 14.1 8.3 $10,000 - $14,999 32 31.0 33.2 $15,000 and over 30 29.8 30.5

Population Density and Degree of Urbanization* Rural (under 2500) 20% 17.0% 25.0% Urban (2500 - 49,999) 17 20.3 19.4 SMA 50,000 - 499,999 -- - Central City 6 7.8 2.7 Urban 4 1.5 8.3 Rural 3 1.5 5.5 SMA 500,000 - 1,999,999 - - - Central City 10 9.4 19.4 Urban 10 12.5 5.5 Rural 5 3.0 8.3 75

Table 4 (Continued)

Initial Non- Sample Returns (64) Returns (3f

SMA 2,000,000 and over Central City 5 6 .2 2.7 Urban 18 18.7 16.6 Rural 2 1.5 2.7

Age of Panel Member* (Female Head of Household) Under 25 years 12% 14.0% 8.3% 25 - 34 years 21 17.0 27.7 35 - 44 years 24 22.0 27.7 45 - 54 years 19 26.5 5.5 55 years and over 24 20.3 30.5

Education of Panel Member Elementary or Grammar School only 6% 3.0% 11.0% Some High School 15 14.0 16.6 High School Graduate 42 46.9 33.3 Some College 25 28.0 19.4 College Graduate 9 7.8 11.0 Post-Graduate Degree 3 0 8.3

Occupation of Panel Member's Husband Professional 19% 23.4% 11 .0% Manager or Administrative 13 12.5 13.8 Clerical or Kindred 6 7.8 2.7 Sales Worker 7 7.8 5.5 Craftsman or Kindred 24 25.0 22.2 Operative 6 3.0 11.0 Laborers, except farm 2 3.0 0 Farmers, farm managers, farm laborers 2 1.5 2.7 Service Worker 6 7.8 2.7

*Market Facts Consumer Mail Panels (CMP) balancing variables. 76

2.-Results--AI0 and Satisfactions Statements. Based on

either multiple high intercorrelations or excessive skewed frequency

distribution of responses (greater than 80/20), as noted above under

AIQ Pretest Results, fourteen AIO statements were dropped. Twelve

new statements were added to bring the final questionnaire total to

eighty-seven.

Frequency distributions and intercorrelations were obtained

for the three different groups of "satisfactions" statements (ques­

tion 5). None of the statements showed a badly (greater than 80/20)

skewed distribution. As a resu lt, there were no changes made to the

list of "satisfactions" statements.

3.-Results--0ther. There were no questions which were skipped

altogether by any appreciable number of respondents. The list of

leisure-time pursuits was expanded by two in the final version--

"racing or rallying" and "square-dancing."

Finally, a difference of twelve percent was noted in the

return rate between households with lower panel member ID numbers

(below 90,000) and those households with higher ID numbers (over

100,000). Since newer panel members have the higher numbers, it

appeared as though some degree of ennui or annoyance had set in

among the "old hands" on the panel.

As a resu lt, Market Facts was requested to use only households with panel ID numbers greater than 100,000 on the final survey. It was hoped that this would maximize the number of usable returns. 77

Final Survey Mailing

Market Facts mailed out 2000 final questionnaires to a spe­

cially composited Consumer Mail Panel of 1000 households on May 11

and 14, 1973. These 1000 households all had husbands living at home,

had panel ID numbers greater than 100,000 and were distributed across

the four Market Facts balancing variables as indicated in Table 3.

Reminder post-cards were sent out to non-responding households

approximately two weeks after the initial mail-out. Six weeks were

allowed for the returns to come back from the respondents.

Market Facts processed the data through the transcription of

keypunched data onto magnetic tape. As part of their normal opera­

tion, they subjected the data to a fairly extensive editing and

consistency check procedure designed to ensure that the final data were as "clean" as possible.

General Analysis Plan

Figure 3 diagrammatically shows the general approach taken to

the data analysis, particularly the early phases. Upon receipt of

the survey data and household biographical (demographic) data from

Market Facts, these data were run through specially written data

conversion computer programs. The biographical data on the non­

respondents were separated out and frequency counts of the variables

made.

After the data had been "converted" and merged into households

as basic data records, the male and female data were separated into 78

Figure 3

General Analysis Plan I I Pull « Receive MF Receive Data Non- BIO Deck Tapes (2) - Store spare Respondents ♦ Add Conversion Add Conversion Freq. Program ______Program Count Perform Conversion + Do Sort- Merge I Separate Male-Female I To Review^. Dump Disk-Pack Record on for Files" " (2 Files) Backup Tape Sequence on Printer 1 Review Freq. Transfer Review for for __ Count ___ „ Data to ^ Variables Conversion of all Male-Female" with Low Program Variables Questionnaires Frequency Errors Counts 1 Compare Respondent and non-respondent BIO Data (Demos)

Begin Hypothesis Testing T H2 Hr H/4 (See Discussion of ♦ each Hypothesis) 79 two files and stored on disk. These files were then printed out and manually reviewed for proper sequencing.

A frequency count of essentially "all" variables was run and this was used to generate two "master" questionnaires (male and female) with the distribution of responses to each question indica­ ted on each questionnaire. These were used to facilitate the selec­ tion of variables for specific analyses. Finally, the respondent and non-respondent biographical or household demographic data were compared in search of any significant differences.

After this initial data file manipulation and analysis of the distribution of respondents along demographic lines, the analysis proceeded to the questionnaire data itself. Each of the five hypo­ theses were tested sequentially, as the analysis of at least the first three hypotheses each built upon the preceding one. These details are discussed in the sections of Chapter V dealing with each hypothesis.

Data File Management

In order to reduce the number of tab card columns used for originally recording the data, non-exclusive categorical data were multiple-punched. This meant that there might be up to twelve punches in one card column, and in turn necessitated that the data be written on magnetic tape in column-binary form. Since the available computer equipment (IBM) cannot process this form of coding, con­ version to binary-coded-decimal form was mandated.

Much of the household biographical data are essentially categorical in nature, but were recorded ("punched") as though they 80 were interval in nature. It was decided to expand these data by recording them in one-zero "dummy variable" format.

A number of biographical variables (age, for example) were segmented by Market Facts into only a few categories (five in the case of aqe). These categories were expanded into a more discriminating set (three years per category), through a recording of the original data.

The net result of these and several other related modifica­ tions to the original data resulted in the number of tab cards of data for each respondent increasing from an original thirteen to a final twenty-seven. The final data file then consisted of 30,105 cards of data--16,281 for the female file and 13,824 for the male file .

General Methodological Approach

The basic thrust of this dissertation is in the definition and description of related groups of variables. This emphasis sug­ gests the use of statistical clustering methods such as factor analysis or cluster analysis. Descriptively discriminating between groups suggests the use of multiple discriminant analysis.

More basic methods of analysis such as frequency distribu­ tions and cross-tabulations are used where appropriate. The SPSS-G and -H (Statistical Package for the Social Sciences) package of computer analysis routines, and the OSIRIS-II (Organized Set of

Integrated Routines for Investigation with Statistics) package of data processing programs are the primary tools of analysis. The

UCLA Biomed (BMD) package was used for the discriminant analyses. 81

S tatistical Measures Employed

Certain specific statistical measures and procedures were chosen over other alternatives. Those selected were based upon the nature of the data, both as designed into the questionnaire and as responded to by the CMP households, and in part on judgmental decisions.

The judgmental nature of some of these decisions should be noted. For all its long history, statistics is still a field in which leading scholars disagree on the "most appropriate" measure or technique to use in a specific situation. There is, apparently, no one, single "right way" to handle a particular set of data, even given one's objectives and the assumptions one is w illing to make about the underlying characteristics of the data sample and data universe.

Correlation Coefficients. The conventional Pearson product- moment correlation coefficient is not always the proper correlation coefficient to use (Rummel, 1970:297, 303). John B. Carroll (1945:

14) was one of the first to recognize this problem,

. . . The Pearsonian coefficient affords a means of estimating the efficiency of prediction of the score on one item from the score on another item. I f the primary concern is not with prediction, however, but with the factorial relation between two items, the Pearsonian coefficient does not given a correct indication of this relation because even where sets of items measure a single ability, the correlation coefficient varies widely as a function of the difficulties of the items.

In a later article (Carroll, 1961:349) he elaborates,

. . . No assumptions are necessary for the computation of a Pearsonian coefficient, but the interpretation of its meaning certainly depends upon the extent to which the data conform to an appropriate statistical model for 82

making this interpretation. As the actual data depart from a f i t to such a model, the limits of the correlation coefficient may contract, and the adjectival interpreta­ tions are less meaningful. The limiting case is provided when the two distributions are dichotomous and the points of dichotomy are asymmetrical between the two distributions, for here the Pearsonian coefficient (in this case, called the phi coefficient) does not, in general, range between plus and minus one, . . . But even when the distributions have more than two class intervals, the possible range of the correlation coefficient is constricted to the extent that the two marginal distributions are disparate, i.e., not of identical shape and skew.

This restriction of range of the product moment correlation coefficient can occur at either extremity of the range. If one of the distributions is skewed in a direction opposite to the other, the positive range of the coefficient will be restricted. If, on the other hand, both distributions are skewed in the same direction, the negative range will be restricted (Rummel, 1970:217).

While this problem can be of significance with interval and multichotomous data, i t is of particular concern with dichotomous or with pseudo-variate (dummy variable) data. To the extent that the distribution of scores between the "one" and the "zero" categories departs from fifty-fifty, the range of the phi coefficient is restricted, i.e,, does not extend from -1.00 to +1.00. This can produce artifactual factors if these proportions vary from variable to variable. Rummel (1970:217) for example, recommends omitting dichotomous variables split greater than 90-10 percent. Note that even in this case, the maximum value which phi can attain is 0.33

(Guilford, 1965:335).

The question then becomes which of the various correlation coefficients to use. Two options are the phi-over-phi-max and the tetradoric coefficients. The phi-over-phi-max coefficient is calculated by dividing

the phi for the two variables by its maximum range for their

data. The phi coefficient across variables with different splits

is thus made more comparable, and the possibility of an arti-

factual factor resulting from this variance is thereby removed.

There are at least two difficulties with the phi-over-phi-max

coefficient which limit its applicability. First, it makes the

assumption that the underlying correlation surface is a type of bivariate rectangular surface, which as Carroll (1961:363) states

is "just a bit improbable." Second, Carroll (1961:369-365) shows that this coefficient has an increasingly steep approach to 1.00 as the splits in the data become more disproportionate, "thus introducing a different source of noncomparable variance in place of that which i t eliminates" (Rummel, 1970:304). Both Carrol 1 (1961

364) and Guilford (1965:337) argue against using this coefficient.

Several authors suggest the use of the tetradoric coeffi­ cient for disproportionally s p lit dichotomous data, though there

is no concensus among methodologists on this question (Baggaley,

1964:30; Carroll, 1961:362, 364-367; McNemar, 1969:227; Rummel,

1970:304, 306). The primary advantage of the te tra d o ric is that

its range is not influenced by disproportionate splits in the data up to around a 90-10 sp lit (for dichotomous data), unless the sample size is quite large (McNemar, 1969:224). Guilford (1965:

330) suggests that "for dependable results" a sample size of 300 or more be utilized. 84

The limitations to the use of the tetradoric coefficient are the following:

1. Both variables are assumed to represent an underlying

continuous normal distribution even though they are

only recorded dichotomously.

2. The standard error of the tetradoric coefficient is

much greater than that for the product moment coefficient,

i.e. it is less reliable or less stable.

3. The tetracloric will give a value of -1.0 when there is

a zero in the cell representing a "one" on variable A

and a "one" on variable B. This is irrespective of the

number in the cell representing a "zero" on each variable.

These limitations are acceptable in this study, and so the tetracloric coefficient was used on data that are "primarily" dichotomous. ^ The product-moment coefficient is used on data that are "primarily" interval or multichotomous. Baggaley (1964:30) points out the rarity of empirical distributions that closely approxi­ mate a point rather than a normal distribution. Obviously, sex is a point-distributed variable, but "most variables in the behavioral sciences . . . tend to give unimodel distributions."

o The final resulting sample sizes of 512 males and 603 females is believed to be sufficiently far above the recommended N of 300 to give adequately reliable and stable coefficients. 85

The phenomenon of -1.0 correlations is acceptable given the nature of the data. This characteristic does create other problems in both factor analysis and cluster analysis, however, as is dis­ cussed later.

Finally, a sample of fifty dichotomous variables was processed

through the OSIRIS CORREL program which produces essentially

“all" of the possible correlation coefficients for dichotomous data. The product moment and phi coefficient values were identi­ cal as expected. The phi-over-phi-max coefficient and the tetra­ cloric produced essentially the same pattern of correlations, although the magnitude of the tetracloric was typically higher.

Signs did not d iffer, nor did the presence of "ones" in the matrix.

Factor Analysis. There are two primary types of factor analysis, principal components (also called component analysis or principal axes analysis) and principal factors (also called common factor or classical factor analysis).4 Principal compon­ ents analysis is basically a geometric rotational procedure designed to reproduce the dimensions of the space defining the total vari­ ance of a set of variables. There is no assumption that a

^Rummel (1970:113-132) describes several other lesser-used factor analysis models. These are image factor analysis, cannoni- cal factor analysis, and alpha factor analysis. 86 variable's variance is in fact composed of separable common and unique variances. This is the assumption underlying principal factor analysis which then searches out the dimensions of the space of the common parts of the variables. Principal factor analysis is a statistical procedure including an error term in the algorithm and also usually involves axis rotation in the interest of inter- pretability (Aaker, 1971:205-211; Green and Tull, 1970:402-427;

Harman, 1967; Rummel, 1970).

There are also two types of rotation of the dimensions or axes, orthogonal and oblique, with the former being a limiting case of the latter. Within these two categories, a number of specific methods have been developed. Some of these are Varimax, quartimax, equimax, target, oblimax, oblimin, and other lesser used techniques (Rummel, 1970:390-396). Each has its particular objectives.

For a number of reasons and after trying and comparing several approaches, principal components analysis, followed by

Varimax rotation, was selected as the particular factor analytic technique to be used in this study. R-type factor analysis, which gen­ erates factors that are combinations of variables taken across cases (subjects) on the same occasion is the analysis model foil owed.^

^There are also other models—0-, P-, Q-, S-, and T-type factor analyses. See Rummel (1970:181-202). 87

One reason for this selection is the necessity of making

assumptions about the general structure of the variables

which is required by principal factors analysis. A preferred

method is one which gives "factors" or groups which are

exact mathematical transformations of the original variables.

Principal components is such a method and one which will indicate whether or not there are a smaller number of "components," or

underlying dimensions (linear combinations of the actual variables) which can account for most of the variance in the data. It is

these dimensions which are believed amenable to marketing a c tiv itie s,

rather than the hypothetical constructs or "factors" implied through principal factor analysis.

Green and Tull (1970:422-424) also advocate the use of principal components analysis rather than principal factor analysis. As they point out, it is a "reproducible procedure for accounting for the common variance in a set of associated variables."

Another argument in favor of principal components is the fact that using i t avoids the so-called "communality problem"

(Harmon, 1967:68-92). This issue has concerned methodologists for many years and revolves around what value should be placed

in the diagonal of the correlation matrix. A "one" in the diagonal implies that the total variance in the variable, considered as a whole, is to be "explained." A value less than one (the "commun­ al ity") implies that one has some prior information (or can make a "guess") about the division of the total variance into "common" and "unique" parts. Communalities are typically estimated by one of several methods (Harmon, 1967:83-90).

One of the more common methods of estimating the in itial communalities is by means of the squared multiple correlations

(SMC) of one variable with all the others in the data matrix.

This method apparently cannot be employed, however, when there are off diagonal values of +1.00 in the correlation matrix.6

The tetradoric correlation coefficient not infrequently reaches a value of +1.00, and therefore the use of this coefficient pre­ cludes the calculation of SMC's in certain situations.

A final reason behind the selection of the princi­ pal components technique is twofold. Based on experimenting with several different sets of variables from this study, it was determined that both principal components and principal factors gave essentially the same resulting groupings of variables.

Rummel (1970:112) points out that this is not uncommon if the variables have low uniquenesses. Given that the two techniques produce similar results, ceteris paribus, principal components is to be preferred because i t requires much less computer time.

^This statement is based on the w riter's experience with the SPSS factor analysis routine, and may reflect idiosyncratic properties of this routine. 89

Orthogonal rotation was selected over oblique rotation, because, in all cases where a comparison between the two methods was made, the end results were very similar. The inter-factor correlations, in the case of oblique rotation, were always less than 0.2 and in most cases less than 0.1. A number of different groups of factors were subjected to both types of rotation, and this pattern appeared quite general.

The other reason for preferring orthogonal rotation is that interpretation of the factors is made easier by their mathematical independence. The Varimax procedure was selected because it is the most widely used and tends to avoid the creation of a "general factor" on which all variables load highly. Harmon (1967:294) states that the Varimax rotation procedure "not only does a better job of approximating the classical simple-structure principles, but it also tends to lead to factorially invarient solutions."

Cluster Analysis. Cluster analysis is another mathematical grouping technique. There are several varieties of this generic method. They all basically work on a matrix of proximities directly.

This matrix is typically a correlation matrix, although it does not have to be.

Two of the approaches to clustering are (1) hierarchical and

(2) threshold or key-cluster.^ While both of these types are avail­ able as part of the OSIRIS package, it was decided that neither was appropriate here for the following reasons.

^See for example Sneath and Sokol (1973) and Tryon and Bailey (1970). 90

The basic concept underlying hierarchical clustering is that

of a taxonomy of related groupings. This conceptual model did not

appear to fit this particular study.

Threshold or key-cluster methods, as implemented in OSIRIS, were rejected because of the lack of definitive clustering algorithm.

The size (and, essentially, composition) of the resulting clusters

is effectively determined by researcher manipulation of clustering

parameters.

Discriminant Analysis. This technique determines those

variables which are associated with the probability of an individ­

ual's falling into one of several predetermined categories. The process finds different linear, additive combinations of the variables, such that each combination discriminates maximally between two or more categories of observations (respondents). The coeffi­ cients of each variable in the resulting discriminant function (if standardized) yield information on the relative importance of each variable in the discrimination process.

The discriminant function can be interpreted, based on the variables included, in a descriptive manner similar to factor analysis. In this study, therefore, the variables indicate the behavioral, demographic or attitudinal orientation of the predeter­ mined categories of respondents depending on the variables selected for a particular analysis.

There does not appear to be an absolute, objective evaluative criteria for ascertaining whether the results of a discriminant 91 analysis are acceptable or efficient. Both the prior probabilities

(classification by "chance") and the costs of m isclassification must be considered (Morrison, 1971:130-140).

In this study, the group sizes (number of respondents) will be essentially equated. This makes the prior probability of correct classification equal to 0.5 or fifty percent correctly classified by chance alone. The costs of misclassification are unknown, but assumed to be relatively high (Type I error costs greater than

Type II).

The decision was made to use that discriminant function with the fewest variables which resulted in approximately seventy per­ cent of the total number of respondents involved being correctly classified. The upper limit on variables was set at one-quarter of those available.

The particular analysis program used in this study (BMD 07M) is a stepwise routine, wherein variables are added to the function one at a time and the function's classificatory ability at each step printed out. This facilitates determining the most efficient function based on the above criteria.

Data Reliability and Validity

The concepts of reliability and validity are discussed in detail in many texts.® Briefly, the reliability of a test or

®See for example Baggaley (1964:60-90), Cronbach (1970:156- 179), Guilford (1965:438-506), Rozeboom (1966 :187-209 , 375-425), and Selltiz, Jahoda, Deutsch and Cook (1959:154-186). 92 questionnaire is a measure of the consistency (either internal or over time) with which the test distinguishes among testees. The validity of a test is a measure of its adequacy in testing what it is supposed to test. There are both several different types of each of these two concepts, and several different approaches to assessing each one.

Two of the four kinds of validity--concurrent and predictive—

(Baggaley, 1964:66-69) cannot be ascertained at this time either for the whole questionnaire used in this study or even for component parts. The passage of time and further data are required.

Content validity is not measurable statistically, but is based upon the subjective judgment of the researcher about how completely he thinks the scales and questions used represent all possible positions on the particular (attitudinal) domain under consideration. Construct validity can be partially inferred based upon a comparison of the results with those- of other similar studies.

On this basis, it appears that the content validity of most of the topical areas on the questionnaire is "good." Those areas of attitudes toward work versus leisure, personal self-concept, and concern with household financing are not as thoroughly covered as the others on the questionnaire.

Reliability, in terms of temporal sta b ility or consistency, also cannot be assessed at this time. The internal consistency of the instrument itself in total is meaningless, given, the degree of heterogeneity of the questionnaire. However, the internal 93 consistency of certain specific groups of ostensibly homogeneous te st items can be calculated by the use of Cronbach's coefficient alpha (Cronbach, 1951:297, 334; 1970:160-162; Rozeboom, 1966:

411-415). One approximation formula for computing this is (Roze­ boom, 1966:412):

n Homx 1 + (n-1) Homx

where ctx = coefficient alpha for the set x of n variables (test items)

n = number of te st items

Homx = rX£ or the arithetic mean correlation among aft pairs of different variables in the sex x, i . e . the homogeneitv of the set.

Thisformula becomes exact when all the items in the set have equal variance.

While the results of this study are discussed in detail in the next chapter, it seems appropriate here, as a point of methodological interest, to examine the internal consistency of several groups of test items. Table 5 shows the value of coefficient alpha for the four sets of items (AI0 statements-question

11) which were in itia lly believed to be the most likely groups to display homogeneity.

This table clearly points out that, with the exception of the attitude toward religion scale, the actual internal consistency of these scales is not very high at all. One text (Crano and Brewer,

1973:231) suggests that coefficient alpha should be in the 0.80 or Table 5

Internal Consistency Reliability of Four Scales as Measured by Cronbach's Coefficient Alpha

No. of Avg. inter-item i terns correlation Aloha Value Scale in Scale male female male female

Attitude toward Religion9 7 .272 .230 .724 .676

Attitude toward Credit*3 7 .021 .034 .131 .198

Attitude toward Work0 14 .046 .024 .403 .257

Attitude toward Leisure^ 8 ...... • .038 • .050 .241 .296 aAI0 statements number1, 10, 26, 30, 42, 74, 85. bAI0 statements number2, 12, 37, 57, 65, 72, 75. cAI0 statements number4, 5, 16, 33, 48, 61, 62, 66, 76, 78, 79, 83, 86, 87. dAI0 statements number8, 18, 27, 31, 36, 38, 46, 73.

AI0 statement numbers refer to the sequence in the list of 87 statements in question 11. 95 above range to adequately satisfy the criterion of internal consis­ tency. It should be kept in mind, however, that this criterion is based on attempting to measure a single attitudinal disposition or dimension by one scale composed of several parts (variables, te sts,

AIO statements, etc.).

Evidently these groups of statements about credit, work, and leisure are tapping several dimensions of each of these four scales or phenomena. Apparently, the attitude one holds toward religion, at least as measured by these seven statements, is more monovalent or unitary.

This analysis of reliability indicates several points.

First, although the groups of credit, work and leisure statements were carefully selected in an attempt to collect a group of related statements, they in fact are measuring multiple dimensions of each of these phenomena or constructs. Second, each of the statements in these three groups will have to be considered a separate (though probably not independent) variable in this study.

Third, this implies the need to carefully research these phenomena or constructs so as to determine ju st what dimensions of each are salient in what circumstances and for what groups of people. CHAPTER V

ANALYSIS AND RESULTS

Chapter IV discussed methodological matters, the pretesting

effort, and the other related activities and decisions which preceded

the final mailing to the one-thousand households.

This chapter now focuses on the analysis of the results of

this survey. This survey return rate is noted, followed by an

analysis of the household biographical data. The analysis of the

five hypotheses, or, as pointed out earlier, more correctly "research questions," concludes this chapter.

Survey Return Rate

A total of 610 of the 1000 households returned usable ques­ tionnaires. Not all households returned both questionnaires with the result that there were 603 usable female and 512 usable male questionnaires. There were twenty-three additional female and ninety-six additional male questionnaires which were returned incompletely filled out. While these could have been used as sources of data on specific questions that were answered, or could have had the missing data filled in with the mean value of each response, it was decided to delete all of these partial returns from subsequent analyses.

96 97

The gross return rate on this survey then was approximately

63 percent while the net usable returns totaled 61 percent. It should be noted that this represents a 7 percent drop in the

usable return rate from the 100-household pretest. This is a t t r i ­ buted mainly to the time of year when the final survey was mailed out. Mid-May through mid-June is a period of improving weather,

the termination of some secondary school sessions and the beginning of the summer vacation season. It was originally intended that the final survey be distributed during April, but various delays pre­ vented this.

Analysis of Household Biographical Data

Table 6 gives a comparison of the in itia l distribution of the

1000 households with both responding and non-responding households on several demographic variables.

It is evident from this table that the distribution of respon­ dents follows the initial distribution on these variables quite well.

In no case does the distribution on a single category differ by more than 3.4 percent between these two samples. Even on the other demo­ graphic variables (see Appendix B), the largest difference on any category between the initial sample the respondent group is 3.7 percent. It seems fair to say, then, that to the extent that the

initial sample of 1000 households reflected U. S. population para­ meters, the sample of respondents do also. 98

Table 6

Comparison of Initial Distribution of 1000 Households with Responding and Non-Responding Households on Several Selected Demographic Variables (Figures represent percentage in Each Category)

Initial Non- Sample Respondents Respondents (1000) (610) (390)

Geographic Division* New England 5.9% 7.1% 4.1% Middle Atlantic 18.7 19.7 17.2 East North Central 18.0 14.9a 2 2 .8a West North Central 7.9 8 .2 7.4 South Atlantic 14.9 14.9 14.9 East South Central 6 .8 6.7 6.9 West South Central 9.5 9.3 9.7 Mountain 3.8 4.3 3.1 Paci fi c 14.5 14.9 13.9

Total Annual Household Income* Under $4000 0 .0% 0 .0% 0 .0% $4000 - $5999 11.9 13.1 10.0 $6000 - $7999 14.0 14.6 13.1 $8000 - $9999 15.5 14.1 17.7 $10,000 - $14,999 32.5 33.3 31.3 $15,000 and over 26.1 24.9 28.0

Population Density and Degree of Urbanization* Rural (under 2500) 15.3% 15.3% 15.4% Urban (2500 - 49,999) 11.6 12.1 10.8 SMA 50,000 - 499,999 --- Central City 9.1 10.0 7.7 Urban 4.5 4.6 4.4 Rural 3.3 3.1 3.6 SMA 500,000 - 1,999,999 -- _ Central City 11.5 9.7b 14.4b Urban 12.9 13.8 11.5 Rural 3.7 3.9 3.3 SMA 2,000,000 and over -- Central City 11.9 12.0 11.8 Urban 14.3 13.4 15.6 Rural 1.9 2.1 1.5 99 Table 6 (Continued)

Initial Non- Sample Respondents Respondents (1000) (610) (390)

Age of Panel Member (Female Head of Household)* Under 25 years 22.7% 2 0 .8% 25.6% 25 - 34 years 26.2 23.0a 31.3a 35 - 44 years 15.9 15.6U 16.4l 45 - 54 years 15.0 17. lb 11.8b 55 years and over 20.2 23.6C 14.9C

Education of Panel Member Elementary or Grammar School only 3.8% 3.0% 5.1% Some High School 16.8 17.2 16.2 High School Graduate 43.0 44.3 41.0 Some College 25.4 24.3 27.2 College Graduate 8.4 9.2 7.2 Post Graduate Degree 1.9 1.6 2.3

Occupation of Panel Member's Husband Professional 13.4% 12.0% 15.6% Managerial or Administrative 12.9 13.0 12.8 Clerical or Kindred 5.4 6.1 4.4 Sales Worker 7.1 7.2 6.9 Craftsman or Kindred 20.4 20.2 20.8 Operative 13.3 13.3 13.3 Laborers, except farm 2.5 2 .0 3.3 Farmers, farm managers, farm laborers 2.1 2.1 2.1 Service worker 8 .8 9.2 8.2

*~CMP Balancing Variables

Notes aZ-test of difference in population proportions significant at .01 < p<; .001.

bZ-test of difference in population proportions (respondents versus non-respondents) significant at ,05< p<[ .02.

cZ-test of difference in population proportions significant at .001 p. 100

The non-respondents also do not appear to skewed excessively with regard to some demographic variables or category of variable.

There are, however, three categories where the non-respondents

differ noticeably from the in itial sample. The East North Central

category is overrepresented by 4.8 percent, the (female) "25-34 years" of age category is overrepresented by 5.1 percent and the (female)

"55 years and over" category is underrepresented by 5.3 percent.

The respondents and non-respondents as groups differ from each other somewhat more dramatically. Table 6 indicates that on five variable categories the differences are statistically significant at the 5 percent level, based on a Z-test for proportions. A chi-square test for difference gives the same results. None of the other dif­ ferences on these variables reach this level of significance.

It is interesting to note that on the "age of panel member" variable, the respondent group is overrepresented significantly in the "45 and over" age brackets, while the non-respondents are over­ represented significantly in the 25-44 age bracket. This is also the situation with the "age of husband" variable and for that rea­ son, it is not shown on Table 6. Evidently, the older panel members had more time and/or willingness to complete this questionnaire; while the younger panel members did not.

Non-respondents also tended to be heavier in the $8000-10,000 and $15,000 and over income categories, although this difference was not significant. The marginally educated and the very well educated panel members also tended to have more non-respondents among them.

This is also seen in the slightly greater percentage of non-respondents 101

in the "professional" category of husband's occupation. The only

unclear difference appears in the significantly greater number of

non-respondents in the East North Central geographic division.

Conclusion. The only differences between the respondents and

non-respondents which may have a real bearing on the results are on

the two age variables. The impact of the fewer younger respondents

and greater number of older respondents may be to overemphasize

those variables in the study which are age-sensitive to the extremes

of the age range. The fact that the distribution of ages in the

respondent group differs little (less than 3.5 percent in the worst

case) from the composition of the original sample means that the

generalizability of age-sensitive results to similar samples should not be greatly impaired.

Analysis of Hypotheses

The following sections discuss each of the five study hypo­ theses in turn. Various elements of data appropriate to the testing of each hypothesis are selected from the questionnaire and analyzed by frequency distribution of responses, cross-tabulation, correlations, principal components factor analysis, and/or discriminant analysis depending on the situation.

Two points should be recognized. First, this dissertation is part of a continuing research program in leisure-time behavior.

Those elements of data not included in the testing of these hypo­ theses will be analyzed in later phases of the program. 102

Second, the five hypotheses are more appropriately considered

"research questions" phrased "Are there . . . ?" As such, they

are not amenable to rigorous, purely objective tests of acceptance

or rejection based upon statistical significance.

Analysis of Hypothesis H]

Hypothesis H-j, in null form, stated

There are no definable "satisfactions" which people derive from leisure-time pursuits.

The testable implication of this hypothesis is that if (1) there are no definable "satisfactions" or (2) the statements purporting to define "satisfactions," in fact, do not, the distribution of responses

to the statements should follow one of two forms. If the subjects

respond to a particular statement randomly, the distribution of responses should be approximately rectangular, i.e., approximately an equal number of responses in each of the five scale categories.

' On the other hand, i f subjects are indifferent about the con­ tent of the statement, or "don't know" or feel that it does not apply to them or to the pursuit, the distribution of responses should approximate a point (or "peaked") distribution centered on the median category of three on the five-point important-not impor­ tant scale.

The data to test this hypothesis come from question number 5 of the questionnaire in Appendix A. These satisfactions statements

are also listed in Table 7. 103

Table 7

The 32 “Satisfactions" Statements

1. I feel that I am being creative.*

2. It gives me a chance to meet new people.

3. I t gives me a chance to learn about new things.

4. I like it because it brings me into contact with friends.*

5. It provides me with a mental challenge; a problem to solve.

6 . It brings me peace of mind.

7. It gives me a chance to experiment my style of living.

8 . It provides me with an escape from home or family pressures.

9. It gives me a chance to develop a sk ill.

10. It brings our family closer together; it helps achieve stronger family ties.

11. It gives me a feeling of independence and self-reliance.

12. I t gives me a chance to be alone with my thoughts.

13. I like it because it is an old familiar activity one with which I have had lots of experience.

14. I like it because there is adventure and excitement in it.

15. It provides an educational experience for my children.

16. I like it because I have a feeling of mastery of the activity.

17. It gives me a chance to get the most out of life while I can still enjoy it.

18. It provides interesting experiences which I can tell my friends about afterwards.

19. I t gives me a chance to compete with others.

20. I like it because of the uncertainty involved; alot of different unexpected things can happen. 104

Table 7 (Continued)

21. It helps to keep me healthy and should prolong my life.

22. I like it because I like to do things that will be of benefit to society or the conmunity.*

23. It helps me to understand myself better.

24. I t provides me with a physical challenge, or a chance for intense physical activity.

25. I like it because it brings happy memories to mind after the occasion has passed.

26. It gives me an opportunity to seek out and enjoy the wonders of nature.

27. I like it because it gives me a feeling of complete control over the outcome of the activ ity —what happens is s tric tly up to me.

28. I feel I can respect myself for doing thes** things,*

29. It gives me an opportunity to see and do new and different things.

30. I t gives me a chance to be alone in a quiet, peaceful spot.

31. It brings me recognition from other people.

32. I like it because it helps me in my work.

*This statement appeared in original Havighurst list. See page 105

Analysis Approach. The analysis approach used here was to look at the skew and kurtosis of the frequency distribution of each of the thirty-two satisfactions statements for each of the "most popular" "favorite activities." The details of this procedure are given in Appendix C. The "most popular" "favorite activities" are listed in Table 15.

Two measures of the degree of peakedness were employed in the analysis. First, a conservative measure, based on more than

50 percent of the respondents rating the particular statement on scale value "3" was used. This established the set of statements which the (simple) majority of subjects were indifferent about or felt did not apply to them relative to a particular activity. A second measure based upon non-significant skew and significant kurtosis established that sub-set of statements which were

"extremely" peaked in their distribution of responses. Table 8

(female respondents) and Table 10 (male respondents) show which of the thirty-two statements (by number) had a peaked or a rectangular response distribution.

Tables 8 and 10 also indicate which statements had a response distribution for a particular activity which did not differ statis­ tically from a rectangular distribution. Apparently, these state­ ments, relative to that particular activity, were engendering a

"random" distribution of responses, or else were sufficiently neutral in their meaning to cause as many respondents to respond positively as negatively. 106

Tables 9 (females) and 11 (males) indicate, for each of the thirty-two statements, the total number of times that the response distribution was peaked on the scale value of "3" under each of the two measures.

Analysis of Table 8. Table 8 shows that the activities

"Listen to music," "Attending movies," "Attend concerts or plays,"

"Write letters, do crosswords," "Read a book for pleasure" and

"Visit with friends, partying" all engendered an "indifferent or does not apply" response on half or more of the statements. "Visit with friends, partying" also had the most statements with a,statis­ tically peaked response--eleven statements. "Collecting, etc.,"

"Attending movies," and "Read a book for pleasure" each generated four or more statistically peaked responses. "Collecting, etc." also generated the greatest number of rectangular response distri­ butions—five.

All of these particular activities may be considered to be broad in their appeal and multifaceted in their benefits to the participant. If one examines the statements rated "3" by a majority for each of these activities, it is apparent that the activity is not one which might be expected to yield that particular benefit or satisfaction to the respondent. For example, "being creative,"

"physical challenge" or "keep healthy" are not satisfactions, benefits or reasons why people might be expected to engage in the activities listed above as having half or more of the statements rated "3." The "does not apply" category would seem to fit these statements relative to these particular activities. Table 8

Satisfactions Statements with Peaked (Point) or Rectangular Distribution of Responses—by Favorite Activity (Female Respondents)

statements rated ‘'3" Statements with Statements with by more than 50% of Statistically "Peaked" S tatistically "Rectangular" Activity3 N Ssb the N Ss (# of subjects i>° Distribution Distribution Statement No. Total (P£.05)d...... (p> .05)e

Attending 44 1, 2, 5, 7, 9, 11, 12, 20 1, 11, 16, 24 None Movies 13, 16, 19, 21, 22, 23, 24, 26, 27, 28, 30, 31, 32

Bingo, 76 1, 7, 11, 12, 15, 21, 13 15 None Bridge, 22, 23, 24, 26, 29, etc. 30, 32

Bowling 65 1, 3, 7, 12, 15, 22, 11 None 31 23, 26, 29, 30, 32

Church- 43 1, 7, 9, 11, 12, 16, 14 16:,'26, 30 None Related 19, 20, 21, 24, 26, 27, 30, 32

Collecting 29 7, 10, 15, 21, 22, 23, 10 15, 21, 22, 23, 26 2, 4, 8, 16, 31 etc. 24, 26, 30, 32

Gardening 6 2, 4, 15, 22, 32 6 None None

Concerts, 44 1, 5, 7, 9, 11, 12, 15, 18 26 None Plays 16, 19, 21, 22, 23, 24, o 26, 27, 28, 30, 32 Table 8 (Continued)

Statements rated "3" Statements with Statements with by more than 50% of S tatistically "Peaked" S tatistically "Rectangular" Activitya N Ssb the N Ss (# of subject!f)e Distribution Distribution Statement No. Total (b> .05)d (p> .05)e

Camp by 64 1, 5, 19, 22, 32 5 None None Trailer

Fish, Hunt 51 1, 7, 15, 22, 23, 32 6 None 16, 19, 20

Horseback 35 7, 22, 23, 32 4 None 3, 10, 19 Riding

Picnicking 61 1, 5, 9, 11, 16, 19, n 22 2 22, 24, 27, 31, 32

Swimming 69 1, 3, 5, 7, 15, 18, 12 7, 22, 23 19 20, 22, 23, 26, 29, 32

Creative 255 2, 10, 14, 15, 20, 21, 10 10, 15, 22 None Crafts 22, 24, 26, 32

Drive for 51 1, 5, 7, 9, 16, 19, 13 5, 22 None Pleasure 21, 22, 23, 24, 28, 31, 32

Listen to 54 1, 2, 4, 5, 9, 10, 11, 21 26 None Music 14, 15, 16, 18, 19, 20 9 21, 22, 24, 26, 27, 28 9 29, 31

Play with 46 11, 12, 19, 30, 32 5 None None ^ Children o CO Table 8 (Continued)

Statements rated ''3" Statements with Statements with by more than 50% o f S tatistically "Peaked" S tatistically "Rectangular" Activitya N Ss the N Ss (# of subjects)0 Distribution Distribution Statement No. Total (p£.05)(nv nsld...... (P2i.05)e ______

Read Book 153 1, 2, 4, 7, 9, 10, 11, 17 7, 10, 22, 27 None 15, 19, 20, 21, 22, 24, 26, 27, 29, 31

Read Bible 33 2, 4, 9, 11, 16, 19, 12 None None 20, 21, 24, 27, 29, 31

Visit 92 1:, 5, 9, 11, 12, 13, 16 1, 9, 12, 15j 16, 21, None Friends 1.5, 16, 19, 21, 22, 24 22, 24, 26, 27, 32 26, 27, 30, 32

■Write 34 2, 7, 10, 11, 14, 15, 18 7, 15, 24 None Letters, 18, 19, 20, 21, 22, Cross­ 23, 24, 25, 26, 27, words 29, 32

Notes: ^Paraphrased favorite activity. See Table 15 for a more complete description. “Number of subjects (respondents) who selected this pursuit as one of their three favorite leisure­ time pursuits. c"Statements" refer to the 32 satisfactions statements listed in Table 7. The scale value of "3" represents the "Indifferent or don't know (or the statement does not apply)" category. dStatements were accepted as being statistically "peaked" if the skewness was not significant at the .05 level, and the kurtosis was^significant at the .05 level or greater. Statements were accepted as being statistically "rectangular" in their distribution if the chi- square value was not significant at the .05 level (chi-square less than or equal to 9.5 for four -• degrees of freedom). § 110

The statistically peaked statements associated with "Collect­

ing, etc." also appear to be statements to which the respondent might be expected to feel indifferent or feel that they "do not apply."

The five statements engendering essentially a rectangular distribu­ tion vis a vis "Collecting, etc." apparently are satisfactions or benefits which are important to some people, but not to others.

Statement 19 ("Gives me a chance to compete") is the only one which engendered a rectangular distribution of responses across several activities.

Analysis of Table 9. Table 9 indicates that statements 15,

22 and 26 from a statistical significance standpoint, are the weak­ est in terms of meaning or applicability to the female respondents across the particular activities selected as favorites. It may be inferred that "it's a benefit to society," "enjoy the wonders of nature," and "it's educational for the children" are not major rea­ sons behind (or satisfactions derived from) the activities selected as favorites by this sample.

Statements 1, 7, 11, 15, 19, 21, 22, 23, 24, 26, and 32, on the other hand, are questionable in their meaning or applicability

(relative to these particular favorite activities) on the basis of more than half of the respondents giving the statement a rating of

"3" on more than half the activities.

Analysis of Table 10. Table 10 indicates that the activities

"Visit bar or club," "Attending movies," "Bingo, bridge or similar card games," and "Visit with friends, partying" all brought forth Ill

Table 9

Frequencies of "Peaked" Response Distribution Across Satisfactions Statements (Female Respondents)

Satisfactions No. of Times Response No. of Times Response Statement Distribution was Distribution was Number3 "Peaked"*3 ...... Significantly "Peaked" (p £ :0 5 )e

1 13 2 2 7 0 3 2 0 4 4 0 5 8 1 6 0 0 7 12 3 8 0 0 9 9 1 10 5 2 11 11 1 12 7 1 13 2 0 14 3 0 15 12 4 16 8 3 17 0 0 18 3 0 19 12 0 20 7 0 21 12 2 22 17 6 23 11 2 24 13 3 25 1 0 26 12 5 27 9 2 28 4 0 29 7 0 30 8 1 31...... 6...... 0 ...... ' 32...... 17...... 1 ...... Notes: 3Per Table 7. ^Number of times 50% or more of the respondents rated the statement as "3", out of a maximum of 20 possible times. cNumber of times 50% or more of the respondents rated the statement as "3" and skewness of the distribution was not significant at .05 level while kurtosis was significant at .05 level. Table 10

Satisfactions Statements with Peaked (Point) or Rectangular Distribution of Responses—by Favorite Activity (Male Respondents)

Statements rated *‘3" Statements with Statements with by more than 50% of S tatistically "Peaked" S tatistically "Rectangular" Activitya N Ssb the N Ss (# of subjects)0 Distribution Distribution Statement No. Total ' (p£.05)d (p> .05)e

Attending 33 1, 5, 7, 9, 11, 12, 18 19, 27, 31 18 Movies 16, 19, 21 , 22, 23, 24, 26, 27, 28, 30, 31, 32

Attend 53 7, 15, 16, 22, 23, 10 None None sporting 24, 26, 27, 30, 31 events

Auto Mods, 28 2, 10, 15, 17, 21, 11 10, 15, 22, 26, 29 None Tune-ups 22, 23, 25, 26, 29, 30

Playing 45 10, 15, 22, 26, 30, 32 6 22, 30 None ball, etc.

Bingo, 35 1, 3, 7, 11, 12, 15, 16 3, 15 9 bridge, 21, 22, 23, 24, 26, etc. 28, 29, 30, 31, 32

Bowling 49 7, 15, 22, 23, 26, 29, 8 22 None 30, 32

Fix up 41 4, 15, 19, 21, 22, 26, 7 26 None z L house, etc, 30 ro Table 10 (Continued)

Statements rated “3'1 Statements with Statements with by more than 50% of S tatistically "Peaked" S tatistically "Rectangular Activitya N Ssb the N Ss (# of subjects)0 Distribution Distribution Statement No. Total (p>.05)d (p> .05)e

Gardening, 70 2, 4, 14, 15, 22, 23, 8 None None etc. 29, 32

Pool, 33 1, 7, 10, 11, 15, 21, 12 15, 30 None Billiards, 23, 26, 28, 29, 30, 32 etc.

Camp by 50 5, 22, 23, 32 4 22 20 * tra ile r,e t * •

Camp by 30 22, 32 2 None 8 tent

Fishing, 190 1, 22, 32 3 None None Hunting

Golf 44 1, 10, 15, 22, 29, 30, 7 None 13, 25 32

Picnicking 32 5, 7, 9, 16, 19, 22, 8 None 2, 8, 14 23, 32

Power 40 22, 32 2 None 5, 19, 31 boating

Swimming 49 1, 7, 22, 23, 32 5 None None

Drive for 49 1, 5, 9, 19, 21, 22, 12 None None ; Pleasure 23, 24, 27, 28, 31, 32 c Table 10 (Continued)

Statements rated "3" Statements witli Statements with by more than 50% of' S tatistically "Peaked" Statistically "Rectangular" Activity3 N Ssb the N Ss (# of subjects)0' Distribution Distribution Statement No. Total (p> .05)d ...... (p£.05)e

Listening 60 2, 4, 5, 7, 9, 11, 12 None None to Music, 14, 15, 16, 18, 19, etc. 20, 21, 22, 23, 24, 26, 27, 29, 31, 32

Photography 28 7, 21, 22, 23, 24, 7 23 6, 19 28, 32

Play with 26 1, 7, 9, 11, 12, 16, 10 11, 16 3, 18, 21, 23, 29 children 22, 27, 30, 32

Read a book 46 1, 2, 4, 9, 10, 11, 12 None 18, 32 for pleas­ : 16, 19, 21, 22, 24, ure : 27

Visit bar 28 1, 5, 7, 9, 10, 15, 20 1, 5, 15, 22, 24, 26, 12 or club 16, 19, 20, 21, 22, 27, 30, 32 23, 24, 26, 27, 28, ; 29, 30, 31 , 32

Visit with 49 1, 5, 9, 11, 12, 13, 16 5, 9, 11, 15, 16, 22, . 8 friends 15, 16, 19, 21, 24, 24, 26, 27, 30 ; 26, 27, 28, 30, 32-

Wood­ 50 2, 4, 15, 19, 20, 21, 10 26 8 working, 22, 23, 26, 32 Metal­ working,

C w v « Table 10 (Continued)

Notes:

Paraphrased favorite activity. See Table 15 for a more complete description.

^Number of subjects (respondents) who selected this pursuit as one of their three favorite leisure-time pursuits.

c"Statements" refer to the 32 satisfactions statements listed in Table 7. The scale value of "3" represents the "Indifferent or don't know (or the statement does not apply)" category.

Statements were accepted as being statistically "peaked" if the skewness was not significant at the .05 level, and the kurtosiS was significant at the .05 level or greater.

Statements were accepted as being statistically "rectangular" in their distribution if the chi- square value was not significant at the .05 level (chi-square less than or equal to 9.5 for four degrees of freedom). 116 an "indifferent or does not apply" response from half or more of the statements. As in the case of the female respondents, these activities are broad and multifaceted in their nature. It is inter­ esting to note that "Visit bar or club" and "Visit with friends, partying" also had an unusually large number of statistically peaked statements--nine or more.

"Playing with children" apparently is an activity which gener­ ates some satisfactions or benefits which are important to some and unimportant to others. It is interesting that learning or doing new things as a result of playing with children falls in this category, as does the chance for the respondent to "understand himself better."

Statement 8 ("provides me with an escape from home or family pressures") is the only one which engendered a rectangular distribu­ tion of responses across several activities. The implication is that subjects were responding in an essentially random manner.

Analysis of Table 11. Table 11 shows that statements 15, 22,

26, and 30, from a statistical significance standpoint, are the weakest in terms of meaning or applicability to the male respon­ dents across the particular activities here selected as favorites.

These are the same statements (except 30) as indicated in Table 9 as statistically peaked.

Statements 1 , 7, 15, 21 , 22, 23, 26, 30, and 32 are question­ able in their meaning or applicability (relative to these particular activities) on the conservative basis of more than half of the respondents rating them as "3" on more than half of the activities. 117 Table n

Frequencies of "Peaked" Response Distribution Across Satisfactions Statements (Male Respondents)

No. of Times Response Satisfactions No. of Times Response Distribution was Statement Distribution was ...... Significantly "Peaked Number* ‘ "Peaked"^ (p > .0 5 )c 11

Notes: |*Per Table 7. “Number of times 50% or more of the respondents rated the statement as "3", out of a maximum of 24 possible times. cNumber of times 50% or more of the respondents rated the statement as "3" and skewness of the distribution was not significant at .05 level while kurtosis was significant at .05 level. 118

Summary. The following statements were rated as "3" by more than half of both the male and female respondents, and therefore apparently have a restricted applicability relative to the activities selected as favorites (as listed in Table 15):

1 - i t gives me a chance to be creative

7 - it gives me a chance to experiment with ny style of living

15 - it. provides an educational experience for nry children

21 - it helps me to keep healthy and should prolong n\y life

22-1 like i t because I like to do things that will be of benefit to society

23 - i t helps me to understand n\yself better

26 - it gives me an opportunity to seek out and enjoy the wonders of nature

32 - I like i t because i t helps me in ny work

Table 12 lists those statements which were not rated as "3" by more than 50 percent of the respondents across 50 percent or more of the activities selected as favorites.

With the possible exception of the two satisfactions state­ ments "... like to do things that will be of benefit to society" and . . helps me in rny work," the statements given in the questionnaire do appear to have meaning, albeit activity—specific meaning, to the respondents. These two statements are the least meaningful to the respondents, vis a vis the activ ities which they selected as favorites in this study.

Conclusion. The implication is that the remaining satis­ factions statements do seem to have meaning to the respondents 119

Table 12

Summary of Satisfactions Statements with Nori-Peaked Response Distribution—Female and Male Respondents^

' ' Female Respondents

It gives me a chance to meet new people. I t gives me a chance to learn about new things. I like it because it brings me into contact with friends. It provides me with a mental challenge; a problem to solve. It brings me peace of mind. It provides me with an escape from home or family pressures. It gives me a chance to develop a sk ill. It brings our family closer together; it helps achieve stronger family ties. It gives me a chance to be alone with my thoughts. I like it because it is an old familiar activity; one with which I have had lots of experience. I like it because there is adventure and excitement in it. I like it because I have afeeling of mastery of the activity. It gives me a chance to get the most out of life while I can still enjoy it. It provides interesting experiences which I can tell my friends about afterwards. I like it because of the uncertainty involved; a lot of different unexpected things can happen. I like it because it brings happy memories to mind after the occasion has passed. I like i t because it gives me a feeling of complete control over the outcome of the activity—what happens is s tric tly up to me. I feel I can respect myself for doing these things. It gives me an opportunity to see and do new and different things. It gives me a chance to be alone in a quiet, peaceful spot. It brings me recognition from other people.

Male Respondents

I t gives me a chance to meet new people. It gives me a chance to learn about new things. I like it because it brings me into contact with friends. It provides me with a mental challenge; a problem to solve. It brings me peace of mind. It provides me with an escape from home or family pressures. It gives me a chance to develop a sk ill. It brings our family closer together; it helps achieve stronger family tie s. I t gives me a feeling of independence and self-reliance. 120 Table 12 (Continued)

I t gives me a chance to be alone with my thoughts. I like it because it is an old familiar activity; one with which I have had lots of experience. I like it because there is adventure and excitement in it. I like it because I have a feeling of mastery of the activity. It gives me a chance to get the most out of life while I can still enjoy it. It provides interesting experiences which I can tell my friends about afterwards. It gives me a chance to compete with others. I like it because of the uncertainty involved; a lot of different unexpected things can happen. It provides me with a physical challenge, or a chance for intense physical activity. I like it because it brings happy memories to mind after the occasion has passed. I like i t because i t gives me a feeling of complete control over the outcome of the activ ity —what happens is s tric tly up to me. I feel I can respect myself for doing these things. It gives me an opportunity to see and do new and different things. It brings me recognition from other people.

Notes

a"Non-peaked" refers to not being rated as "3" by more than 50 % of the respondents on 50% or more of the activities selected as favorites. 121 relative to specific leisure-time pursuits or activities. To the extent that the statements actually reflect satisfactions or benefits derived from participating in the activity, different activities engen­ der different groups of satisfactions which are rated as "important" by respondents, and different groups which are rated as "unimportant."

Hypothesis H-j, as stated, is therefore tentatively rejected based on the results of this particular study. There do appear to be definable satisfactions, recognizable as such, which people derive from lei sure-time activities.

Analysis of Hypothesis H 2

Hypothesis H 2 » in null form, stated

Leisure-time pursuits and "satisfactions1' cannot be clustered into distinct groups.

There are three ways in which the first half of this hypo­ thesis (clustering of pursuits) could have been tested, given the content and structure of the questionnaire. Two approaches were selected out of these three. The f ir s t approach groups all of the fifty leisure-time pursuits based upon whether or not a subject had engaged in the activity during 1972. These data come from question 4B.

The second approach groups the most popular favorite leisure­ time pursuits as indicated by the subjects in their response to question 5A. The third alternative, grouping those activities which respondents had participated in at least once in their lives (question

4A) was believed to be too "gross" a categorization for this parti­ cular situation. 122

I t was fe lt that the f ir s t approach would give a relatively

broad clustering of a greater number pursuits since most people

probably would have participated in a fairly wide range of pursuits

during the period of a calendar year. The second approach was

believed to be useful in discriminating much more finely those few

pursuits which "go together" based on their being liked enough to

be considered favorite pursuits.

The second half of this hypothesis, i.e. the clustering or

grouping of satisfactions, was also approached in two ways. The

f ir s t approach grouped satisfactions statements across all the

activities selected as favorites. It was believed that this would

show any groupings of satisfactions which "go together" irrespective

of the means by which they are attained. These would be underlying,

basic relationships which would indicate relatively all-pervasive

"bundles of benefits or satisfactions" which are sought through a

range of leisure-time pursuits.

The second approach to this half of the hypothesis was to look

at individual pursuits and the possible groupings of satisfactions which they brought forth. In the interests of brevity, rather than presenting the groupings of satisfactions statements for all twenty

(female) or twenty-four (male) favorite pursuits, two pursuits from each group of respondents are presented for discussion. The selection of the pursuits was based on the number of relatively distinct groups of satisfactions which the factor analysis brought forth. Activities 123 were selected which had several distinct groupings of satisfactions each accounting for more than 5 percent of the total variance.

Tables 13 (female) and 14 (male) present the groupings of pursuits engaged in during 1972. Tables 16 (female) and 17 (male) present the groupings of favorite leisure-time pursuits. Table 15 lists all the leisure-time pursuits selected as "favorites" by five percent or more of the respondents. Tables 18 (female) and 19 (male) present the groupings of satisfactions statements across all activi­ ties in each of the three categories of "favoriteness"--most favorite

(MFA), second most favorite (SFA), and third most favorite (TFA).

Tables 20 (female) and 21 (male) present the groupings of s a tis ­ factions statements for each of two selected pursuits for each sex.

Analysis Approach. The analytical approach used here was principal components factor analysis followed by Varimax rotation to simple structure. Groups were determined from the factoring process on the basis of pursuits or satisfactions statements which loaded at least 0.40 on the particular rotated factor and were at least three in number per rotated factor. That is, rotated factors with only one or two variables loading 0.40 or greater on them were excluded.

Factors were extracted from the data as long as the Varimax rotated factors accounted for at least ("approximately," in some cases) 5 percent of the variance in the data, and had at least three variables loading 0.40 or greater on them.

The factor analysis of the favorite pursuits was performed upon a tetracloric correlation matrix, as participation in the 124 favorite pursuit was scored 1 (yes) or 0 (no). The factor analysis of the pursuits engaged in during 1972 was performed on a "Pearson r" correlation matrix as participation here was scored on a three point scale. The factor analysis of the satisfactions statements was also performed on a "Pearson r" correlation matrix, as the statements here were rated on a 1—5 important/not important scale.

No attempt will be made to name the extracted factors as the purpose here is not to determine a single underlying dimension which can be labeled, but rather to determine if leisure-time pursuits and satisfactions can be clustered into distinct groups. The distinctive­ ness of the groups is tested by selecting only pursuits and satis­ factions which load heavily (0.40 or greater) on a factor. This achieves a "core" grouping, with minimal extraneous loadinyj, by a particular variable on other factors.

Analysis of Table 13. Table 13 shows that the leisure-time pursuits or activities engaged in by the female respondents during

1972 can be clustered into groups with at least "face validity."

These groups also account, individually, for a fairly significant proportion of the variance in the data. Together, they account for

51.2 percent of the variance.

Group 1 appears to be an active, group-sports oriented cluster, while group 2 is more individualistic in orientation. Group 4 seems to be active, people-oriented, while group 5 again seems more individualistic and passive in orientation. Groups 6 through 9 are definitely outdoor-oriented, but variously more active or more pas­ sive in orientation. Group 3's orientation is unclear. 125

Table 13

Groups (Factors) of Related Leisure-Time Pursuits Engaged in During 1972 by Female Respondents3

1. (7:2%)b 5 ; (5:5%) Tennis (.780)c Bingo, bridge or similar card Bicycling (.653) games (.584) Bowling (.518) Attending sporting events as Playing basketball, football, as spectator (.558) baseball, softball, volleyball, Collecting coins, stamps, bottles, handball (.498) etc. (.539) Chess, Checkers, Backgammon (.438) Swimming (.401)

2 . (6.8%) 6: (5:4%) Reading the Bible (.714) Camping by Tent (.817) Gardening, Lawn Care, Land­ Attending Concerts or Plays (.552) scaping (.648) Camping by tra ile r, camper, or Exercising, Jogging, Visiting motor home (.409) Health Spa (.497) Church-Related Activities (.434) 7. (5.0%) Horseback Riding (.427) Ice skating, Roller skating (.672) Canoeing, Rowing, Rafting (.605) 3. (6.0%) Driving around for pleasure or Volunteer, Community, School, sightseeing (.511) Youth Group, or Charitable Playing basketball, football, Organization Work (.718) baseball, softball, volleyball, Woodworking, Metalworking, handball (.403) Furniture Refinishing, Home Workshop Projects (.713) 8. (4.7%) Not Horseback Riding (.535) Hiking, Backpacking, Nature Study (.754) 4. (6.0%) Walking for Pleasure (.515) Square-Dancing or other organized Canoeing, Rowing, Rafting (.481) dances (.703) Visiting a bar or club (.651) 9. (4.6%) Photography, Taking pictures (.604) Power boating, water skiing, scuba Playing piano, organ or other diving (.739) musical instrument for pleasure Fishing or Hunting (.696) (.502) Camping by tra ile r, camper, or motor home (.518) 126

Table 13 (Continued)

Notes:

aNumber of respondents indicating that they had engaged in a particular activity during 1972 varied from 63 to 507.

^Percentage of variance in the data accounted for by the total Varimax rotated factor.

cNumber in parentheses after leisure-time pursuit is the loading of that pursuit on that factor. 127

Analysis of Table 14. Table 14 indicates a set of results sim ilar to Table 13. There are fewer groups and they are larger in their content of related pursuits. Again, these groups individ­ ually account for a fairly significant amount of variance and together account for 42 percent of the total variance.

Group 1 appears to be an active, traditional-concept-of-a-male orientation, while group 2 seems to be creative, passive, and perhaps, delicate in orientation. Group 3 appears to be an upper socioeconomic scale orientation, while group 4 may be lower socioeconomic scale and people-oriented. Group 5 seems individualistic and outdoor while group 6 seems more passive and around-tne-house in orientation.

Analysis of Table 15. Table 15 lis ts the twenty leisure-time pursuits selected as favorites by at least 5 percent of the female sample, and the twenty-four pursuits selected by at least 5 percent of the male sample. It should be noted that in most cases, a given pursuit was selected as a favorite by only 11 percent or less of the sample. This small sub-sample size tends to re strict both the analy­ sis and any potential generalizations regarding a particular leisure­ time pursuit as a favorite pursuit.

Analysis of Table 16. Table 16 shows the groupings of leisure­ time pursuits rated as favorites by the female respondents. As anticipated, the factor loadings are higher in general than the groupings of pursuits engaged in during 1972, thereby indicating more tightly knit groupings or clusters of related pursuits. The percentage of variance explained by each factor is also higher, also inferring relatively tight and homogeneous groupings. It is 128 Table 14

Groups (Factors) of Related Leisure-Time Pursuits Engaged.-in During 1972 by Male Respondents3

1. (10.7%)b Attending sporting events as a spectator (.682) Playing basketball, football, baseball, etc. (.627) Automobile modification or tune-ups (.607) Swimming. (.598) Chess, checkers, backgammon (.590) Bingo, bridge or similar card games (.522) Bowling (.515) Pool, billiards or table-tennis (.446) Fishing or hunting (.401)

2 . (8.2%) Playing the piano, organ or other musical instrument for pleasure (.657) Reading a book for pleasure (.654) Creative crafts or handicrafts (.563) Walking for pleasure (.530) Playing with children (.525) Woodworking, metalworking, furniture refinishing, home workshop pro­ jects (.516) Golf (.455) Listening to music from records, tape or radio (.453) Photography, taking pictures (.421)

3. (6.4%) Hiking, backpacking, nature study (.687) Attending concerts or plays (.662) Volunteer, community, school, youth group, or charitable organization work (.607) Golf (.603) Job-related reading or study (.496) Power boating, water skiing, scuba diving (.463)

4. (6.0%) Square-dancing or other organized dances (.758) Horseback riding (.730) Visiting a bar or club (.566) Ice skating, roller skating (.452) Bicycling (.444) Table 14 (Continued)

5. (5.7%) Canoeing, rowing, rafting (.819) Writing le tte rs, doing crossword puzzles (.626) Camping by tent (.560)

6. (4:7%) Fixing up the house, remodeling, making repairs (.744) Gardening, lawn care, landscaping (.606) Collecting coins, stamps, bottles, etc. (.470)

Notes:

aNumber of respondents indicating that they had engaged in a particular activity during 1972 varied from 78 to 378.

^Percentage of variance in the data accounted for by the total Varimax rotated factor.

cNumber in parentheses after leisure-time pursuit is the loading of that pursuit on that factor. 130

Table 15

The Most Popular Favorite Leisure-Time Pursuits9

No.(%) of Female No.(%) of Male Respondents Selecting Respondents Leisure-Time Pursuit(Activity)P it as a "Favorite" Selecting it as ...... • - a ' "Favorite"

50-Attending concerts or plays 44 (7.3%) (c) 51-Camping by tra ile r , camper or motor home 64 (10.8%) 51 (10.0%) 52-Camping by tent (c) 30 (5.9%) 54-Fishing or hunting 51 (8.8%) 192 (37.5%) 55-Golf (c) 44 (8.6%) 57-Horseback riding 35 (5.8%) (c) 59-Picnieking 61 (10.3%) 32 (6.3%) 60-Power boating, water skiing, scuba diving (c) 40 (7.8%) 64-Swimming 70 (11.6%) 49 (9.6%) 30-Attending movies 44 (7.5%) 34 (6.6%) 31-Attending sporting events (c) 54 (10.5%) 32-Automobile modifications, tune-ups* etc. (c) 28 (5.5%) 33-Playing basketball, football, baseball, etc. (c) 45 (8.8%) 35-Bingo, bridge or similar card games 76 (12.8%) 35 (6.8%) 36-Bowling 65 (10.8%) 49 (9.6%) 38-Church-related activities 43 (7.3%) (c) 39-Collecting coins, stamps, bottles, etc. 31 (5.1%) (c) 40-Fixing up the house, remodeling (c) 42 (8.2%) 41-Gardening, lawn care, landscaping 65 (10.9%) 71 (13.9%) 42-Pool, billiards, table tennis (c) 34 (6.6%) 70-Creative crafts or handicrafts 255 (42.6%) ( 0 71-Driving around for pleasure 51 (8.6%) 49 (9.6%) 74-Listening to music from records, tapes, radio 54 (9.0%) 60 (11.7%) 75-Photography (c) 28 (5.5%) 77-Playing with children 46 (7.6%) 26 (5.1%) 78-Reading a book for pleasure 153 (25.5%) 47 (9.2%) 79-Reading the Bible 33 (5.5%) (c) 80-Visiting a bar or club (c) 28 (5.5%) 81-Visiting with friends, partying 92 (15.6%) 49 (9.6%) 83-Woodworking, metalworking, furniture refinishing, home workshop projects (c) 50 (9.8%) 84-Writing le tte rs , doing cross­ word puzzles 34 (5.8%) (c) Table 15 (Continued)

Notes:

aThose pursuits selected by at least 5 percent of the sample as one of their three favorite activities in question 59.of the question- nai re .

^Arranged in the same order as they appear on pages 5-7 of the questionnaire.

cNot selected as a favorite by at least 5 percent of the sample. Table 16

Groups (.Factors) of Related Leisure-Time Pursuits Selected as "Favorite" Pursuits by Female Respondentsa

1. (16.2%)b Fishing or hunting (.995)° Attending concerts or plays (.938) Not writing letters or doing crossword puzzles (.576) Picnicking (.534) Not church-related activities (.504)

2. (15.9%) Not writing letters or doing cross word puzzles (.995) Reading Bible (.934) Church-related activities (.887)

3. (15.1%) Not driving around for pleasure or sightseeing (.995) Attending movies (.862) Attending concerts or plays (.654) Not playing with children (.448)

4. (13.0%) Not playing with children (.995) Collecting coins, stamps, bottles, etc. (.878) Not swimming (.507) Bowling (.423) Camping by tra ile r, camper or motor home (.414)

5. (12.2%) Not horseback riding (.995) Collecting coins, stamps, bottles, etc. (.518) Church-related activities (.448)

6. (12.0%) Listening to music from records, tapes, radio (.923) Not swimming (.778) Not camping by tra ile r, camper, or motor home (.621)

7. (11.2%) Gardening, lawn care, landscaping (.995) Not visiting with friends, partying (.626) Collecting coins, stamps, bottles, etc. (.479) 133 Table (Continued)

Notes:

aNumber of respondents indicating that the particular leisure-time pursuit was a "favorite" varied from 31 to 255.

^Percentage of variance in the data accounted for by the total Varimax rotated factor. Inflated somewhat due to "imaginary variance" resulting from negative eigenvalues (Rumniel, 1970:260).

cNumber in parentheses after leisure-time pursuit is the loading of that pursuit on that factor. 134 interesting that not participating in certain pursuits is as much a criterion of membership in certain groups as participation in other pursuits.

The total variance accounted for by these factors amounts to some 96 percent of the total variance, although this is inflated somewhat due to the negative eigenvalues that were associated with several of the last few factors to be extracted.^

Group 1, because of the interest in concerts and plays, appears to be an "upscale" (socioeconomically) group, while group 2 is apparently religiously oriented.2 Group 3 appears to have a performing arts orientation, while groups 4 and 5 seem to be more quiet or less vigorous in their orientation. Group. 6 represents an interest in recorded music. Group 7 may be an "around-the-house" oriented group.

Analysis of Table 17. Table 17 reflects the similar groupings of favorites of the male respondents. Here again, both the individual factor loadings and the variance accounted for by each factor are higher in general than for the case of activities engaged in during 1972. Not participating in various pursuits is parti­ cularly important in group meirbership with the males.

*The exact amount of inflation is unknown. Those factors (6) with negative eigenvalues accounted for 26 percent of the total real plus imaginary variance.

2This description of Group 1 is based upon the demographic characteristics of those respondents engaging in fishing/hunting and in attending concerts or plays as brought out in prior cross­ tabulation analysis. Table 17

Groups (Factors) of Related Leisure-Time Pursuits Selected as "Favorite11 Pursuits by Male Respondents^

1. (16.5%)b Not visiting with friends, partying (,947)c Picnicking (.926) Not listening to music from records, tapes or radio (.790). Fishing/Hunting (.547) Not reading a book.for pleasure (.444) Not driving around for pleasure or sightseeing (.431) ' Not visiting a bar or club (.427) Swimming (.405)

2. (13.2%) Visiting a bar or club (.946) Not reading a book for pleasure (.905) Not engaging in photography or taking pictures (.875)

3. (13.1%) Not playing with children (.995) Golf (.888) Attending movies (.695) Camping by tra ile r, camper or motor home (.412)

4. (12.9%) Gardening, lawn care, landscaping (.995) Bingo, bridge or similar card games (.739) Not playing basketball, football, baseball, etc. (.658) Not camping by ten t (.606) Not engaging in automobile modification or tune-ups (.436)

5. (12.5%) Not swimming (.902) Not engaging in automobile modifications or tune-up (.852) Attending sporting events as a spectator (.679) Not engaging in power boating, water skiing, scuba diving (.453) Picnicking (.427)

6. (12.4%) Fixing up the house, remodeling, making repairs (.995) Woodworking, metalworking, furniture refinishing, home workshop pro­ jects (.668) Not picnicking (.661) Not attending movies (.517) 136

Table 17 (Continued)

7. (12.0%) Not camping by tra ile r, camper, motor home (.995) Not engaging in power boating, water skiing, scuba diving (.781) Bowling (.645) Bingo, bridge or similar card games (.427)

Notes:

aNumber of respondents indicating that the particular leisure-time pursuit was a "favorite" varied from 26 to 192.

^Percentage of variance in the data accounted for by the total Varimax rotated factor. Inflated somewhat due to "imaginary variance" resulting from negative eigenvalues (Rummel, 1970:260).

cNumber in parentheses after leisure-time pursuit is the loading of that pursuit on that factor. 137

The total variance accounted for by these factors amounts

to some 93 percent of the total. Here again, this is inflated

somewhat.^

Group 1 seems to be an outdoors, small-group or individual

oriented group, while group 2 may be an indoor, small-group oriented

cluster. Groups 3, 4, and 5 seem to have a less-vigorous kind of

activity orientation, both indoors and outdoors. Group 6 appears to have a "handyman" kind of orientation, while group 7 seems

similar to group 4 in being a small-group, less active kind of

cluster.

Analysis of Table 18. Table 18 presents the groupings of

satisfactions statements across all pursuits or activities in each

of the three permissible categories— MFA, SFA, and TFA. These groups both individually and collectively account for a significant portion of the total variance. All the groups together account for

53 percent (MFA category), 46 percent (SFA category) and 51 percent

(TFA category) of their respective total variance, even though the average loading of the pursuits on the factors is not exceptionally high. Among the first five groups of the MFA pursuits, there is only one statement which loads into more than one group—"stronger family tie s." This implies relatively independent groups of a l l - pervasive satisfactions statements.

^The exact amount of inflation is unknown. Those factors (8) with negative eigenvalues accounted for 26 percent of the total real plus imaginary variance. 138

Table 18

Groupings (Factors) of Related Satisfactions Statements Across all A ctivities in Each of the Three "Favorite" Categories (Female Respondents)5

' Most FaVorite ActiVi ties (MFA)

' 1i (9;5%)b 2 - meet new people0 (.653)d 3 - learn new things (.621) 4 - contact with friends (.603) 29 - do new things (.589) 25 - happy memories (.533) 10 - stronger family ties (.517) 17 - get most out of life (.486)

2. (9.1%) 9 - develop a skill (.791) 1 - being creative (.721) 16 - feeling of mastery (.606) 5 - mental challenge (.563) 11 - feeling of independence (.535) 27 - feeling of control (.400)

3. (8.3%) 24 - physical challenge (.520) 21 - keep healthy (.758) 26 - enjoy wonders of nature (.612) 10 - stronger family ties (.463)

4. (8.0%) 30 - alone in quiet spot (.797) 12 - alone with thoughts (.743) 6 - peace of mind (.548) 139

Table 18 (Continued)

5. (6.6%) 20 - uncertainty involved (.660) 18 - interesting experiences (.626) 19 - chance to compete (.610) 14 - adventure and excitement (.524) 31 - recognition from others (.426)

6; (6:1%) 22 - benefit to society (.727) 32 - helps in my work (.705) 23 - understand myself better (.503) 15 - educational for children (.417) 31 - recognition from others (.400)

7. (5.2%) 28 - can respect myself(.749) 27 - feeling of control (.566) 17 - get most out of life (.413)

Second Most Favorite Activ itie s ' (SFA)

1. (10.5%) 9 - develop a skill (.701) 1 - being creative (.674) 5 - mental challenge (.634) 11 - feeling of independence (.558) 16 - feeling of mastery (.550) 28 - can respect myself (.536) 27 - feeling of control (.505) 7 - style of living (.447)

2. (9.8%) 25 - happy memories (.733) 29 - do new things (.688) 17 - get most out of life (.659) 18 - interesting experiences (.632) 14 - adventure and excitement (.513) 28 - can respect myself (.467) 10 - stronger family ties (.428) 140 Table 18 (Continued)

3. (6.5%) 24 - physical challenge (.807) 21 - keep healthy (.726) 26 - enjoy wonders of nature (.499)

4; (6.4%) 12 - alone with thoughts (.732) 30 - alone in quiet spot (.686) 6 - peace of mind (.646) 8 - escape from pressures (.564)

'5: (6:4%) 19 - chance to compete (.744) 31 - recognition from others (.603) 20 - uncertainty involved (.557) 32 - helps in my work (.418) 18 - interesting experiences (.401)

6 . (6 . 1%) 32 - helps in my work (.654) 22 - benefit to society (.650) 15 - educational experience for children (.565) 23 - understand myself better (.533)

Third Most Favorite Activities (TFA)

1. (9.6%) 9- develop a skill (.746) 1- being creative (.698) 5- mental challenge (.645) 11- feeling of independence (.571) 16- feeling of mastery (.542) 27- feeling of control (.540)

' 2: (9.0%) 17- get most out of life (.705) 25- happy memories (.596) 18- interesting experiences (.594) 13- old familiar activity (.561) 28- can respect myself (.517) 14- adventure and excitement (.480) 6- peace of mind (.400) 141

Table 18 (Continued)

3; (7.2%) 4 - contact with friends (.802) 2 - meet new people (.745) 3 - learn new things (.421) 14 - adventure and excitement (.410)

4: (7;o%) 30 - alone in quiet spot (.783) 12 - alone with thoughts (.771) 8 - escape from pressures (.621) 6 - peace of mind (.551)

5: (6.9%) 24 - physical challenge (.742) 21 - keep healthy (.712) 26 - enjoy v/onders of nature (.683)

6. (6.7%) 32 - helps in my work (.736) 22 - benefit to society (.699) 23 - understand myself better (.494) 31 - recognition from others (.428)

7. (5.0%) 19 - chance to compete (.785) 20 - uncertainty involved (.488) 31 - recognition from others (.455)

Notes:

aNumber of respondents answering these questions varied from 580 to 589.

^Percentage of variance in the data accounted for by the total Varimax rotated factor.

cParaphrased» numbered satisfaction statement from Table 7.

dLoading of that statement on the factor. 142

Group 1 of the MFA category appears to stress "newness" and relating to people. Group 2 appears to stress mental activity and psychological independence, control and mastery. Group 3 has an active, physical, "body" orientation; while group 4 is more contem­ plative and passive. Group 5 seems to imply a seeking of the unknown, of overcoming challenges. Group 6 may be an introspection-through- extraversion orientation, or as termed in clinical psychology, the

"messiah complex." Group 7 implies a concern with self-respect.

Group 1 of the SFA category is similar to group 2 of the MFA group. Group 2 appears to have a "mental imagery," along with a searching for new images, type of orientation. Groups 3, 4, 5, and

6 are basically the same as groups 3, 4, 5, and 6 (respectively) of the MFA groups.

Groups 1 and 2 of the TFA category are sim ilar to groups 1 and

2 of the SFA groups, with the exception that "old familiar activity" appears for the f ir s t time in any group. Group 3 seems to have a

"newness" orientation in a small-group context. Groups 4, 5, 6 and 7 and basically the same as groups 3, 4, 5, 6 of the SFA groupings, albeit rearranged.

Analysis of Table 19. Table 19 presents the same kind of data as Table 18, except for the male respondents. All the groups together in each of the three categories account for the following percent­ age of the total variance in the data: MFA category—53 percent;

SFA category--50 percent; TFA category—53 percent. The groups of statements, at least under the MFA category, are not as distinct 143

Table 19

Groupings (Factors) of Related Satisfactions Statements Across all Activities in Each of the Three "Favorite" Categories (Male Respondents)a

Most Favorite Activities (MFA)

i;(9 .3 % )b 24 - physical challenge0 (.712)d 21 - keep healthy (.698) 9 - develop a skill (.664) 16 - feeling of mastery (.625) 19 - chance to compete (.490) 27 - feeling of control (.482) 11 - feeling of independence (.403)

2. (911%) 32 - helps in my work (.697) 31 - recognition from others (.639) 1 - being creative (.600) 22 - benefit to society (.589) 23 - understand myself better (.535) 5 - mental challenge (.511) 3 - learn new things (.435)

3. (8.2%) 30 - alone in quiet spot (.784) 12 - alone with thoughts (.770) 26 - enjoy wonders of nature (.512) 6 - peace of mind (.474) 11 - feeling of independence (.454) 29 - do new things (.414) 7 - style of living (.411)

4. (8.2%) 25 - happy memories (.655) 13 - old familar activity (.655) 17 - get most out of life (.548) 28 - can respect myself (.543) 18 - interesting experiences (.456) 6 - peace of mind (.455) 27 - feeling of control (.451) 144 Table 19 (Continued)

5; (618%) 20 - uncertainty involved (.680) 14 - adventure and excitement (.577) 19 - chance to compete (.565) 18 - interesting experiences (.504) 29 - do new things (.428)

6. (5:9%) 10 - stronger family ties (.671) 15 - educational for children (.661) 22 - benefit to society (.490) 23 - understand myself better (.421) 26 - enjoy wonders of nature (.405)

7: (5:7%) 2 - meet new people (.765) 4 - contact with friends (.754) 3 - learn new things (.530)

Second Most Favorite A ctiv ities' (SFA)

1.(11.0%) 27 - feeling of control (.698) 16 - feeling of mastery (.694) 11 - feeling of independence (.651) 28 - can respect myself (.618) 9 - develop a skill (.513) 5 - mental challenge (.443) 21 - keep healthy (.440) 13 - old familiar activity (.439) 24 - physical challenge (.400)

2. (9.4%) 19 - chance to compete (.742) 20 - uncertainty involved (.640) 4 - contact with friends (.615) 2 - meet new people (.602) 18 - interesting experiences (.517) 14 - adventure and excitement (.514) 31 - recognition from others (.473) 24 - physical challenge (.418) 145

Table 19 (Continued)

" 3: (9 .3 % ) 10 - stronger family ties (.739) 25 - happy memories (.651) 17 - get most out of life (.639) 29 - do new things (.527) 15 - educational for children (.488) 14 - adventure and excitement (.476) 26 - enjoy wonders of nature (.418)

4. (7.9%) 32 - helps in my work (.787) 22 - benefit to society (.754) 23 - understand myself better (.576) 31 - recognition from others (.419)

5: (7.1%) 30 - alone in quiet spot (.850) 12 - alone with thoughts (.708) 26 - enjoy wonders of nature (.612) 29 - do new things (.400)

6. (5.0%) 3 - learn new things (.686) 1 - being creative (.598) 5 - mental challenge (.478)

Third Most Favorite Activities (TFA)

1. (12.8 %) 9 - develop a skill (.748) 27 - feeling of control (.743) 16 - feeling of mastery (.695) 19 - chance to compete (.645) 24 - physical challenge (.584) 11 - feeling of independence (.563) 31 - recognition from others (.511) 20 - uncertainty involved (.456) 5 - mental challenge (.442) 28 - can respect myself (.441) 21 - keep healthy (.428) 14 - adventure and excitement (.405) 146

Table 19 (Continued)

' 2 ; (8 :7%) 29 - do new things (.724) 25 - happy memories (.614) 26 - enjoy wonders of nature (.588) 14 - adventure and excitement (.538) 18 - interesting experiences (.529) 20 - uncertainty involved (.483) 17 - get most out of life (.407)

' 3: (8:1%) 22 - benefit to society (.751) 32 - helps in my work (.603) 23 - understand myself better (.597) 15 - educational for children (.518) 21 - keep healthy (.479) 10 - stronger family ties (.400)

~4: (6.4%) 4 - contact with friends (.782) 2 - meet new people (.768) 18 - interesting experiences (.426) 19 - chance to compete (.416)

5. (6.3%) 12 - alone with thoughts (.729) 30 - alone in quiet spot (.701) 8 - escape from pressures (.538) 7 - style of living (.440)

6. (5.9%) 6 - peace of mind (.675) 17 - get most out of life (.544) 13 - old familiar activity (.518) 10 - stronger family ties (.492) 28 - can respect myself (.414)

7: (5.0%) 3 - learn new things (.627) 5 - mental challenge (.619) 1 - being creative (.610)

Notes: ^Number of respondents answering these questions varied from 489 to 502. “Percentage of variance in the data accounted for by the total Varimax rotated factor. “Paraphrased, numbered satisfaction statement from Table 7. Loading of that statement on the factor. 147

as with the female sample. Within the f ir s t five groups, six sta te ­ ments appear in more than one group. This implies less independent bundles or clusters of satisfactions.

Group 1 of the MFA category has an implication of active, physical, competence seeking. Group 2 seems to represent a desire for recognition through "good works," as well as seeking an under­ standing of se lf—perhaps the "messiah complex" again. Group 3 implies contemplative introspection, possibly outdoors. Group 4 may have a nostalgia orientation along with "living life to the fullest."

Group 5 appears to represent a seeking of the unknown and the over­ coming of challenges. Group 6 may represent a family orientation, while group 7 is interaction-with-people oriented.

Groups 1 and 2 of the SFA category are both similar to group 1 of the MFA category, except that this group 1 has more of a "self"

(inner-directed) orientation, while group 2 has more of an "others"

(other-directed) orientation. Group 3 seems to be a combination of family orientation plus a seeking of mental imagery upon which to dwell at a later time. Groups 4 and 5 are similar to groups 2 and 3 of the MFA category. Group 6 has a mental activity orientation to i t .

Group 1 of the TFA category appears to be a combination of groups 1 and 2 of the SFA category. Group 2 seems to be the mental imagery orientation again, while group 3 seems to be the introspec- tion-through-extraversion orientation again. Group 4 is similar to group 7 of the MFA; groups 5 and 6 are similar to groups 3 of MFA and 5 of SFA. Group 7 is the same as group 6 of the SFA category. 148

' Analysis of Table 20. Table 20 presents for the females, the different bundles or groups of satisfactions derived from par­ ticipation in each of two specific pursuits. The factors (groups) listed account for 63 percent of the variance for "Attend movies," and 52 percent for "Bowling." It is interesting to note that the f ir s t group of satisfactions under each pursuit is that group of benefits or satisfactions which are not "reasons why" people par­ ticipate in the pursuit.

The breadth of impact and content of movies is brought home in groups 2 through 7 of the satisfactions derived from attending movies. Mental imagery, adventure and excitement, a learning exper­ ience, an old familiar pattern, self understanding and reflection, and escape from daily pressures are all basic components of differ­ ent bundles of satisfactions derived from attending movies.

Bowling also provides many different bundles of satisfactions to participants. Group 2 of the satisfactions under this pursuit probably represents most people's view of the sport of bowling.

Other bundles or groups of satisfactions involve being with friends; having interesting experiences; understanding one's skills or lack of them; a friendly, familiar activity; and recognition from others are all basic components of different bundles of satisfactions derived from bowling.

Analysis of Table 21. Table 21 is similar to Table 20, except it is for male participation in "listening to music" and

"playing golf." The four factors (groups) extracted for "listening to music" accounted for 54 percent of the variance, while the five 149

Table 20

Groupings (Factors) of Satisfactions Statements for the Leisure-Time Pursuits "Attending Movies" and "Bowling" (Female Respondents)5

"Attending Movies"

' '1: ‘ C243g)b . 21 - keep healthyc(-.903)« 31 - recognition from others (-.888) 22 - benefit to society (-.886) 32 - helps me in my work (-.855) 24 - physical challenge (-.811) 19 - chance to complete (-.697) 26 - enjoy wonders of nature (-.667) 16 - feeling of mastery (-.653) 20 - uncertainty involved (-.525) 9 - develop a skill (-.483) 14 - adventure and excitement (-.482) 8 - escape from pressures (.461) 23 - understand myself better (-.454)

2. (7.8%) 25 - happy memories (.876) 17 - get most out of life (.760) 16 - feeling of mastery (-.463) 14 - adventure and excitement (.455) 18 - interesting experiences (.414)

•31 (712%) 29 - do new things (.767) 13 - old familiar activity (.669) 28 - can respect myself (.664) 18 - interesting experiences (.474)

•4 ; (7 :0%) 11 '- feeling of independence (.768) 9 - develop a skill (.571) 7 - style of living (.520) 20 - uncertainty involved (.474) 14 - adventure and excitement (.444) 150

Table 20 (Continued)

5; (5.9%) 6 - peace of mind (.786) 30 - alone in quiet spot (.728) 23 - understand myself better (.473)

6: (5 :7%) 1 - being creative (-.898) 8 - escape from pressures (.577) 10 - stronger family ties (-.465)

7 ; (5:3%) 3 - learn new things (.857) 23 - understand myself better (.429) 8 - escape from pressures (.400)

"Bowling11

1. Cll .8%) 29 - do new things (-.803) 26 - enjoy wonders of nature (-.761) 30 - alone in quiet spot (-.713) 12 - alone with thoughts (-.648) 3 - learn new things (-.634) 15 - educational for children (-.559) 5 - mental challenge (-.434)

2. (9.0%) 19 - chance to compete (.739) 24 - physical challenge (.727) 5 - mental challenge (.572) 14 - adventure and excitement (.548) 20 - uncertainty involved (.531) 9 - develop a skill (.511)

' 3; (617%) 2 - meet new people (.856) 4 - contact with friends (.819) 21 - keep healthy (.485)

' 4: (6:5%) 18 - interesting experiences (.853) 15 - educational for children (.574) 21 - keep healthy (.470) 20 - uncertainty involved (.400) Table 20 (Continued)

5. (6:2%) 23 - understand myself better (.684) 9 - develop a skill (.560) 7 - style of living (.530) 17 - get most out of life (-.514) 11 - feeling of independence (.489) 1 - being creative (.444)

6 ; (5 .9%) 13 - old familiar activity (.732) 6 - peace of mind (.699) 14 - adventure and excitement (.416)

7. (5:7%) 31 - recognition from others (.769) 32 - helps in my work (.611) 20 - uncertainty involved (.432)

Notes: a65 respondents selected "Bowling" as a favorite activity. 44 respondents selected "Attending Movies" as a favorite activ ^Percentage of variance in the data accounted for by the total Varimax rotated factor. cParaphrased, numbered satisfaction statement from Table 7. ^Loading of that satisfaction statement on the factor. 152

Table 21

Groupings. (.Factors) of Satisfactions Statements for the Leisure-Time Pursuits "Listening to Music from Records, Tapes, Radio" and "Playing Golf" (Male Respondents)3

' ' "Listening to Music"

1; (20.6%)b . 31 - recognition from others0 (-.874) 24 - physical challenge (-.805) 26 - enjoy wonders of nature (-.799) 22 - benefit to society (-.791) 19 - chance to compete (-.779) 16 - feeling of mastery (-.748) 20 - uncertainty involved (-.748) 9 - develop a skill (-.684) 21 - keep healthy (-.488) 29 - do new things (-.479) 11 - feeling of independence (-.462) 10 - stronger family ties (-.432) 2 - meet new people (-.403)

2. (15:1%) 18 - interesting experiences (.860) 17 - get most out of life (.849) 27 - feeling of control (.776) 25 - happy memories (.663) 3 - learn new things (.648) 7 - style of living (.627) 28 - can respect myself (.568) 10 - stronger family ties (.553) 29 - do new things (.421)

3. (9.8%) 5 - mental challenge (.844) 4 - contact with friends (.812) 2 - meet new people (.673) 11 - feeling of independence (.542) 1 - being creative (.522) 9 - develop a skill (.502) 153

Table 21 (Continued)

4. (816%) 30 - alone in quiet spot (.878) 8 - escape from pressures (.812) 12 - alone with thoughts (.806) 6 - peace of mind (.465)

"Playing Golf"

l; (20.5%) 14 - adventure and excitement (.823) 16 - feeling of mastery (.821) 21 - keep healthy (.812) 24 - physical challenge (.812) 17 - get most out of life (.810) 20 - uncertainty involved (.789) 27 - feeling of control (.748) 19 - chance to compete (.732) 9 - develop a skill (.720) 5 - mental challenge (.460) 18 - interesting experiences (.455) 4 - contact with friends (.409)

2. (14.1%) 22 - benefit to society (.869) 32 - helps in my work (.818) 7 - style of living (.795) 15 - educational for children (.774) 3 - learn new things (.737) 1 - being creative (.548) 29 - do new things (.446) 23 - understand myself better (.420)

3. (6;5%) 13 - old familiar activity (.830) 29 - do new things (.635) 26 - enjoy wonders of nature (.617) 18 - interesting-experiences (.423)

4: (6.2% ) 28 - can respect myself (.872) 11 - feeling of independence (.586) 23 - understand myself better (.489) 154 Table 21 (Continued)

5; (5.5%) 5 - mental challenge (.736) 12 - alone with thoughts (.692) 18 - interesting experiences (-.390)

Notes:

a60 respondents selected "Listen to Music from Records, Tapes or Radio" as a favorite activity. 44 respondents selected "Playing Golf" as a favorite activity.

^Percentage of variance in the data accounted for by the total Varimax rotated factor.

cParaphrased, number satisfactions statement from Table 7.

^Loading of that satisfaction statement on the factor. 155 factors (groups) extracted for "golf" accounted for 53 percent of the variance.

Group 1 represents those satisfactions not derived from

"listening to music." Groups 2 and 3 under "listening to music" are not clearly interpretable. Group 2 seems to focus on control of an experiential environment. There is also a mental imagery component involved. Group 3 may represent "serious" listening in the company of others—perhaps those respondents who vicariously "direct" the orchestra. Group 4 seems to have a relaxing, unwinding, introspec­ tive, solitudinous, orientation.

The f ir s t group of satisfactions under "playing golf" (like the second group under "bowling" for women) seems to represent those s a tis­ factions which might most readily come to mind as possible benefits or outcomes of "playing golf." The second group, in to ta l, is less clear. There is an "other-directed" element involved as well as a mental-involvement orientation. Group 3 combines doing new things in a familiar, safe, outdoor situation or context. Group 4 has a self-respect plus introspection connotation, while group 5 seems to be the individual, "loner" serious golfer.

Summary. Groups of leisure-time pursuits engaged in during

1972 were found. Several of the groups were independent, while several had one or more pursuits common to more than one group.

Female respondents had more groups of pursuits with overlapping activities than did the male respondents. 156

Groups of favorite leisure-time pursuits were also found. These

groups tended (1) to be smaller, (2) to have higher loadings, and (3)

to account for a greater proportion of the total variance than did the

groups of pursuits engaged in during 1972. These groups also included

numerous pursuits in which not participating was a condition for

membership in the group. These "not-participating" pursuits imply a

bipolar factor in which the two groups are systematically antithetical.

The male respondents had a greater number of "not participation"

pursuits in th eir groups of pursuits than did the female respondents.

These groups also included several cases where one pursuit was a mem­

ber of more than one group. "Collecting coins, bottles, stamps, etc."

appeared in three groups for the female respondents. "Picnicking"

and "Bingo, bridge and similar card games" were the only two pursuits

appearing in more than one group (in a do_participate sense) for the

male respondents.

Two types of groupings of satisfaction statements were found.

Pervasive "universal" groups which cut across all the activities

selected as favorites, and also pursuit or activity-specific groups.

The same kinds of groupings of satisfactions came out of each

of the three categories of "favoriteness," with only minor variations.

"Being creative," "developing a skill" and "a mental challenge" were the three leading components of the primary factors or

groups of satisfactions for the females. "Physical Challenge,"

"keeping healthy," "developing a skill" and feelings of "mastery,"

"control" and "independence" were the leading components of the 157 primary factors or groups of satisfactions for the males. As in the case of the groupings of pursuits, there were several situations in which the same satisfactions statement appeared in more than one group.

The activity-specific groups of satisfactions tended to be more distinct with fewer cases of the same satisfactions appearing in more than one group. "Interesting experiences" and "uncertainty involved" in the case of "attending movies" and "bowling," respec­ tively, tended to be ubiquitous satisfactions to the females. For the males, "listening to music" did not have any overlapping satis­ factions, while "playing golf" engendered one general group of satis­ factions plus several others in which "mental challenge," "interesting experiences," "do new things" and "understand myself better" appeared in more than one group.

Conclusions. Leisure-time pursuits and the satisfactions derived from them can be clustered in groups, albeit with varying degrees of distinctiveness. Apparently, some pursuits and satis­ factions are more pervasive, multifaceted, or non-polar in their appeal than others and thereby link or overlap with more than one otherwise d istinct group.

Favorite leisure-time pursuits seem to group into bipolar groups in which the "not participate" pursuits form one apparently homogeneous group (on the basis of face validity), while the "do participate" pursuits form what appears to be a sub-group with a different orientation. 158

Groupings of satisfactions statements across all activities or pursuits selected as favorites seem to be pervasive irrespective of whether the pursuit is a MFA, SFA, or TFA one, with minor excep­ tions. This implies that there are bundles of satisfactions which people seek through diverse pursuits, and, therefore, that substitute pursuits may be suitable in the absence of a preferred or traditional pursuit.

In the case of three of the four pursuits selected to discuss pursuit-specific groups of satisfactions, the largest group of satisfactions comprised those which are not reasons for p artic i­ pating in the pursuit. This implies that there is a very distinct and significant set of satisfactions which are not associated with these pursuits, and therefore a person seeking these satisfactions could not be expected to engage in that particular pursuit.

The fact that each of the four pursuits engendered several fairly distinct groups of satisfactions, rather than one general group, implies that the pursuit is multifaceted in its appeal — providing different benefits or satisfactions to different people and/or different "distinct" groups of benefits to the same person.

Hypothesis H 2 , as stated, is therefore tentatively rejected based on the results of this particular study. It should be noted, however, that the groups that were defined were not all equally and/or completely distinct. 159

Analysis of Hypothesis H 3

Hypothesis H3, in null form, stated

Specific clusters of leisure-time pursuits and satisfactions are not related to any significant degree.

It was originally intended that cannonical correlation be used

to determine the degree of relationship between clusters or groups

of pursuits and groups of satisfactions statements. The survey data

as received, however, did not permit this approach. The number of

respondents selecting any particular pursuit as a favorite in any one

of the three categories of "favoriteness," MFA, SFA, or TFA, were

too few to permit meaningful clusters or groupings within one of

these three categories. Since the satisfactions statements only

relate to each of the three categories individually, the study is

limited to equating groups of pursuits and of satisfactions within

a single category.

Those groups of favorite activ ities which did come out of

the analysis, and which are shown in Tables 16 and 17, are also not "clean" groups. Not being "clean" means that the groups are not all composed of variables (pursuits) with positive loadings on the particular factor of which the group is a subset. The nega­ tive loadings of certain pursuits implies "not participating" but says nothing about what is done instead. The pursuits loading positively in each group are only one, two or three in number.

Correlating "groups" of two pursuits with groups of satisfactions statements is not overly meaningful. 160

It is theoretically possible to take the required data from the questionnaire and regenerate new composite variables. The amount of combinatorial programming seemingly required is beyond the scope of this dissertation.

The basic thrust of this hypothesis is to see if related groups of pursuits provide related (or the same) groups of s a tis ­ factions or benefits to the participant. Given this objective, it was decided to search out a group of pursuits which were "highly" intercorrelated.3 The specific groups of satisfactions statements engendered by participation in each member of the group would then be listed side-by-side and visually compared for similarity. Should sim ilar or identical groups of satisfactions statements be found as

"outputs" of more than one pursuit, it could then be inferred that all those pursuits with this particular group of statements asso­ ciated with them provide "the same" benefits or satisfactions to the participants. Of course, each of the pursuits in the group may also provide unique and distinctive bundles or groups of s a tis ­ factions in addition to those in common with other pursuits.

Analysis Approach. The combined favorite pursuits (selected by 5 percent or more of the sample) were correlated using the

^A "Statistically significant" (at the .001 level) correlation coefficient, for a sample size of, say, 500 is only 0.15. Both the male and female sample sizes exceeded 500. While this level of correlation may be statistically significant, it may not be "managerially useful" in any reliable way. 161 tetracloric correlation coefficient The correlation matrix was then examined and the group of pursuits with the highest inter­ correlations determined. The responses to the satisfactions state­ ments for each pursuit in the group were then factor analyzed

(principal components/Varimax rotation). The resulting factors or groups of satisfactions statements were then compared for sim ilarity among groups across pursuits. Tables 22 (female) and 23 (male) present the results of this analysis.

Analysis of Table 22. Table 22 presents the results of the analysis of the most highly intercorrelated favorite pursuits of the female respondents. "Attending concerts or plays," "Fishing or

Hunting," and "Picnicking" were the three pursuits which inter­ correlated the highest. At that, the correlation between "concerts/ plays" and "fishing/hunting" is only .210. This group of pursuits also happens to be the most important group, in terms of explained variance, derived through factor analysis and shown in Table 16.

Only two "general" factors or groups of satisfactions evolved out of the factor analysis of the statements for fishing/hunting.

Each of these two groups had essentially all statements loading on it at a level of .35 or greater. Interpretation of these two groups is unclear. Because of this lack of distinct groupings, this pursuit could not be compared with the other two.

^"Combined" means that the three categories of MFA, SFA and TFA were combined (through programming) into one category of "favorite pursuits." 162

Table 22

Similar Groups (Factors)of Satisfactions Derived from Participating in Different Leisure-Time Pursuits (Female Respondents)

A. Correlation Matrixa

‘ Concerts ' Fish/Hunt Picnicking Concerts (NSs =44) 1.0 Fish/Hunt (NS§ = 51) .210 1.0 Picnicking (NSs =61) .340 .442 1.0

Similar Groupings (Factors) of Satisfaction Statements - Picnicking vs. Concerts0

Picnickinq Concerts (26.8%)d (23.8%) £

:1 - being creative0 -.704e -.746 7 - style of living -.507 -.424 9 - develop a skill -.822 -.741 11 - feeling of independence -.509 -.803 12 - alone with thoughts -.632 -.401 16 - feeling of mastery -.700 -.622 19 - chance to compete -.830 -.880 20 - uncertainty involved -.522 -.562 24 - physical challenge -.509 -.528 26 - enjoy wonders of nature • -.401 -.749 31 - recognition from others -.848 -.877 32 - helps in my work -.755 -.771

g j (17:7%) (11.4%) 3 - learn new things .448 .612 14 - adventure and excitement .451 .654 18 - interesting experiences .552 .840 20 - uncertainty involved .526 .471 25 - happy memories .461 .688 29 - do new things .639 .816

h . (5:5%) (5:5%) 2 - meet new people .664 .850 4 - contact with friends .491 .585 17 - get most out of life .311 .480 163

Table 22 (Continued)

Notes:

aThese three pursuits intercorrelated the highest of all the 20 pur­ suits selected as favorites by at least 5 percent of the female sample of 603 respondents. NSs is the number of respondents who selected the f M S full 2NKH& Tilted TSergl!fium as 11sted parap*irase<* b"Fishing and Hunting1' could not be compared with "Attending Concerts or Plays" or "Picnicking" because only two factors of satisfaction - statements were found with eigenvalues greater than one. These two factors had essentially all 32 statements loading .35 or higher on both of them.

Paraphrased, numbered satisfactions statement from Table 7.

^Percentage of variance in the data accounted for by the total Varimax rotated factor.

eLoading of that satisfaction statement on the factor.

^There were other statements loading greater than .40 on this factor that were not common to the factor across both pursuits. "Picnicking" and "Attending concerts or plays" do appear to provide similar and, in one case, identical bundles or groups of satisfactions to the participants. Group 3 is an identical group of satisfactions for each pursuit, with no other loadings of sig­ nificance on it. Groups 1 and 2 indicate that there are also other similar, although not identical, bundles of satisfactions provided by the two pursuits. These groups represent sub-sets of related satisfactions from larger groups loading 0.400 or greater on the factor.

The first group represents those satisfactions which are not relevant reasons for participating in either of the two pursuits.

This kind of grouping implies that tbe pursuit-irrelevant satisfac- tions are as important, if not more so, than the pursuit-relevant satisfactions in groups 2 and 3.

Group 2 implies a desire for newness, novelty, mental stimu­ lation and imagery production. Group 3 has an interrelating-with- people orientation.

Analysis of Table 23. Table 23 presents the most highly intercorrelating group of favorite pursuits for the male respon­ dents. "Listen to music from records, tapes, radio," "Photography, taking pictures," and "Reading a book for pleasure" were the three most closely related pursuits. Here again, however, one of the correlations is only .252. This group of pursuits does not show up as a "positive" factor or group on Table 17, but is included within the f ir s t two groups in a "not participate" condition. 165

Table 23

Similar Groups (Factors) of Satisfactions Derived from Participating in Different Leisure-Time Pursuits (Male Respondents)

A. Correlation Matrix9 Read Listen to Music Photography Book Listen to Music (NSs = 60) 1.0 - - Photography (NSs = 28) .374 1.0 - Read Book (NSs =46) .252 .315 1.0

Similar Groupings (Factors) of Satisfaction Statements ; Between These Three Pursuits: Photography, Read Listen to Music Take Pictures Book 11 «e » (15.1%)c (14.2%) (10.3%) 17 - get most out of life0 .849 .604 .782 18 - interesting experiences .860 .850 .814 25 - happy memories .663 .563 .267 27 - feeling of control .776 .463 .542 28 - can respect myself .568 .643 .018 29 - do new things .421 .564 .409

(9.0%) h . (8.6%) (7.4%) 6 - peace of mind .465 .450 .844 8 - escape from pressures .812 .886 .208 12 - alone with thoughts .806 .885 .174 13 - old familiar activity .182 .170 .781 30 - alone in quiet spot .878 .718 .818

Notes:

aThese three pursuits intercorrelated the highest of all the 24 pursuits selected as favorites by at least 5 percent of the male sample of 512 respondents. NSs is the number of respondents who selected the pursuit as a "favorite" one. The pursuits are paraphrased from Table 15. Paraphrased, numbered satisfactions statement from Table 7. Percentage of variance in the data accounted for by the total Varimax rotated factor. ^Loading of that satisfactions statement on the factor. eThere were other statements loading greater than .40 on this factor that were not common to the factor across all 3 pursuits. 166

Contrary to Table 22, there is no "pursuit-irrelevant" group­ ing of satisfactions statements here. All three of these pursuits have a cerebral orientation and the two groups of satisfactions reflect this.

Group 1 has more of an active involvement (albeit perhaps vicariously) in the pursuit orientation than does group 2. Group 1 is also a sub-set of a larger group of satisfactions loading 0.400 or greater on each factor. It is interesting to note that the relative importance of "happy memories" and "can respect myself" as satisfactions derived from reading a book for pleasure are not nearly as great as for the other two pursuits. This is partially reflected in the lower correlation between "Book" and "Music."

Group 2 has an introspective, individualistic, reflective and perhaps nostalgic orientation. It is also a distinct grouping with no other satisfactions loading significantly upon it. It should be noted, however, that the group is not preserved intact across all three pursuits. "Old familiar activity" is not an important satis­ faction resulting from "listening to music" or "photography"—in relation to this particular group of otherwise related satisfactions.

On the other hand, "escape from pressures" and "alone with thoughts" are not strongly related to the other satisfactions with regard to

"reading a book for pleasure." These two satisfactions do load heavily, individually, on two other factors or groups. In addition,

78 percent of the respondents selecting "read a book" as a favorite activity said that "alone with thoughts" was an important satisfac­ tion to them. Fifty-nine percent said the same about "alone with thoughts." 167

Summary. Two groups of these pursuits each were found, based on having the highest intercorrelations of any of the pursuits selected as favorites by the respondents. Essentially identical or very similar groups of satisfactions were found to be significant (in terms of explained variance) outputs to participants in each of the member pursuits in each group. Several of the groups of satisfactions were, in fact, subsets of larger groups loading 0.400 or greater on the factor. There were also several groupings of satisfactions which were specific to each of the pursuits in each group.

Conclusion. Based on the very limited number of pursuits investigated, there does seem to be a tendency for related pursuits to provide similar, or in some cases, identical bundles or clusters of satisfactions to the participant. Certain groups of related satisfactions may contain both a sub-group of satisfactions common to several pursuits and a unique sub-group peculiar to a specific pursuit. The parallel between the communality and uniqueness com­ ponents of the variance of a measured variable may be noted.

Hypothesis H 3 , as stated, is therefore tentatively rejected based upon the results of this particular study, and the analysis which has been permissible given the characteristics of the data.

A cautionary note is inserted to the effect that (1) the number of respondents selecting a particular pursuit as a favorite is small enough that generalization is risky, and ( 2 ) the intercorrelations are fairly low (in the range of 0.2 to 0.4) though sta tistic a lly significant for the sample size. 168

Analysis of Hypothesis H 4

Hypothesis H^, in null form, stated

There are no significantly different patterns in the use of credit for leisure-time products and pursuits by different groups of people.

The basic thrust of this hypothesis is to inquire whether both general views toward credit and specific usage of credit for various

leisure-time products and pursuits vary across identifiable groups of people. These groups are defined on the basis of answering re­ sponse patterns to questions dealing with attitudes toward credit and credit usage, and to questions concerning religion, life-style and to certain selected demographic questions.

The data used in this analysis come from questions 1,2, 11, and 22 of the questionnaire (see Appendix A), and from the Market

Facts household demographic data (see Appendix B). Table 26 lists the eighty-six variables used in this section. These particular variables evolved as the group used in the final analysis, after extensive early review of the data had indicated that other vari­ ables ( 1 ) did not account for an appreciable amount of variance in the data, (2) had highly skewed response distributions, or (3) en­ gendered a very low response rate.

As in the case of the preceding hypotheses, the degree or extent of patterning in the data does not lend itself to statis­ tical tests of significance. Rather, the results of the various analyses are reviewed visually for predominant relationships. 169 Tables 24 (female) and 25 (male) are a descriptive summary of the

responses to the primary credit questions. Table 26 lis ts the final

variables used in the factor analysis of credit-oriented and related

variables. Tables 27 (female) and 29 (male) present the results of

the factor analysis of the responses of holders of credit cards.

Tables 28 (female) and 30 (male) present the results of the factor

analysis of the responses of non-holders of credit cards. Table 31

presents the means of the variables listed in Table 26.

Analysis Approach. The analysis approach used involved fre­

quency counts, cross-tabulations, and principal components/Varimax

rotation factor analysis. The frequency counts and cross-tabulations

provide descriptive information and some indication of relationships between pairs of variables. The factor analysis, and the cross-tabs

provide indication of levels of patterning in the data.

Given the large number of variables which were related to credit

usage and attitudes, the use of cross-tabulation is an appropriate method for discovering specific patterning among particular sub­

groups of variables. These sub-groups include credit cards held, magazines read, demographics, acceptable uses of credit, and leisure­

time pursuits engaged in during 1972.- Factor analysis, with its

limitations on the number of variables which can be included in one

computer run, is more appropriately used in searching out macro­

groupings, or patterning across several sub-groups of variables.

The significance level of the degree of association between the

two variables for all the 2 x 2 cross-tabulations was computed by the more accurate Fisher's exact test, rather than by the chi-square 170

test. Chi-square was used for all tables larger than 2 x 2 (where

Fisher's test is not appropriate). The same criteria for terminating

a factor analysis was used here as under hypothesis Hg*

Both holders and non-holders of credit cards were analyzed

separately for both sexes. Holders and non-holders were separated

on the basis of their response to question 1A., "Do you have any

credit cards?" The remainder of question 1 was not applicable to

non-holders of credit cards, and so these variables were not included

in the analysis of this group of respondents.

Results of Cross-Tabulation Analysis. While several thousand

cross-tabulations were analyzed in this part of the study, only those

pairs of variables which had a chi-square value which was signifi­

cant at the .005 level or greater are included in the following six-

part descriptive discussion. This does not imply that in specific situations, cross-tabulations with somewhat less significant chi- squares might not be "managerially significant."

The variables cross-tabulated for this hypothesis are those indicated in Table 26. The leisure-time pursuits engaged in during

1972 as listed in question 4.B., plus the magazines read by the

respondents as listed in question 12 of the questionnaire (see

Appendix A) are also included.

1.-Holders of Credit Cards. Male credit card holders in general

(in comparison with non-holders) tended to engage in job-related reading, golf, and readina a book for pleasure during 1972. They also tended to read Time, and not to read Sport magazine. Female credit card holders in general tended to attend concerts or plays, 171 play golf, and visit a bar or club during 1972. They also tended to read National Geographic, Time, and not to read Modern Romances or

True Story magazines.

With regard to specific credit cards held, male BankAmericard holders tended to be educated at the college level or higher and be in either a non-supervisory or a top executive position within their company. They tended to attend concerts or plays and play golf.

Female holders were more prevalent in the upper income and age cate­ gories and had husbands in the same job positions as noted above.

They tended to play tennis and golf during 1972.

Male Master Charge card holders showed the same demographic pat- term as BankAmericard holders and, in addition, tended to be in higher incone categories. They tended to attend concerts or plays, go ice or ro ller skating, fix up the house/remodel and engage in job-related reading during 1972. They tended to read Business Week, Playboy, and

Time.

Female holders tended to have younger husbands in higher execu­ tive positions in their company, and to be in the higher total house­ hold income categories. They tended to play golf during 1972 and read

American Home and 1001/Decorating Ideas.

Male gasoline company credit card holders also showed the same pattern of higher education, higher position in company and higher total household income, and in addition were high on the occupation scale (professionals, managers, administrators). They tended to attend concerts or plays, play golf and tennis, attend sporting events, engage in volunteer work, job-related reading, and for-pleasure book 172

reading. They tended to read Business Week, Changing Times. Parade,

Time and U. S. News and World Report. Female holders matched the male holders on demographics and in addition were in the middle-age

categories. They tended to attend concerts or plays, engage in job-related reading, and visit a bar or club during 1972. They

tended to read Sunset and Woman's Day and not to read Modern Romances

and True Story magazines.

Neither male nor female holders of Sear's, Penney's, or Ward's

credit cards had significant demographic cross-tabs. Male holders of one or more of these cards tended to engage in job related read­ ing, photography and playing with children during 1972. Female holders of these cards tended to play golf, collect "things," engage in gardening/lawn care and visit a bar or club during 1372. They tended to read Sunset and not to read True Story magazine.

Female holders of "other department store" credit cards tended to be better educated (college level or higher) and have a higher total household income. Male holders did not have significant demographic cross-tabs. Female holders tended to v isit a bar or club during 1972, read Glamour and Time and not read True Story magazine. Male holders tended to attend concerts or plays, play golf, engage in job-related reading during 1972, and read Business

Week, Time and U. S. News and World Report.

2.-Uses of Credit during 1972. Males who used credit for outdoor clothing also tended to use it for drugs/etc., sporting equipment, TV/radio/stereo equipment, garden/lawn care supplies and photographic equipment and for non-business dining; but not for 173

leisure-time airline travel or hotel/motel/lodge reservations, or

gas/oil/parts for the car on a vacation. The same held for males who used credit for drugs/etc., sporting equipment and for TV/radio/ stereo equipment.

Males who used credit for garden/lawn care supplies or for photographic supplies, however, also tended to use it for leisure-time airline travel and hotel/motel/lodge reservations, and for gas/oil/ parts for the car on a vacation and for non-business dining. Those who tended to use credit for leisure-time airline travel or vacation hotel/motel/lodge reservations, or for gas/oil/parts for the car on a vacation also tended to use i t for the other two uses in this group.

Essentially the same pattern prevailed among the females, in that using credit for outdoor clothing, drugs/etc., sporting equip­ ment, TV/radio/stereo equipment, garden/lawn care supplies, and for photographic equipment/supplies all tended to be strongly related, and related to non-business dining to a slightly lesser extent.

Using credit for garden/lawn care supplies, photographic equipment/ supplies, leisure-time airline travel, gas/oil/parts for the car while on a vacation, staying in a hotel/motel/lodge while on a vaca­ tion and for non-business dining also all tended to be strongly related. There thus appear to be two overlapping groups of related

(equally acceptable) uses of credit during 1972.

3.-Uses of Credit in 1972 versus Demographics. Examining the two groups of uses of credit discussed above under 2 .-, i t was found that respondents (both sexes) who utilized credit for basically non­ leisure time purposes (Group I) tended to be (1) younger, (2) better 174 educated and (3) had smaller families. Respondents (both sexes) who used credit for leisure-time airline travel, hotel/motel/lodge while on vacation and for gas/oil/parts for car while on a vacation tended to be ( 1 ) better educated, (2 ) upscale on total household income, and (3) the male tended to be an executive at his place of employment.

4.-Use of Credit in 1972 versus Magazines Read. Examining the two groups of uses of credit discussed above under 2 .-, the following significant relationships were found among the male respondents:

Group I

1. Used credit for outdoor clothing and tended to read

Business Week and Esquire.

2. Used credit for sporting equipment and tended to read

Field and Stream, Outdoor L ife, Parade, PIa.ybo.y and

Sports Illustrated.

Group II

1. Used credit for lei sure-time airline travel and tended

to read Time.

2. Used credit for gas/oil/parts for car while on a vaca­

tion and tended to read Changing Times, National Geo­

graphic, Newsweek, Parade, Time, and U. S. News and

World Report.

3. Used credit for hotel, motel, lodge while on a vacation

and tended to read Newsweek, Time, and U.S. News and

World Report. 175

The following significant relationships were found among the female respondents:

Group I

1. Used credit for outdoor clothing and tended to read

1001/Decoratihq Ideas and Glamour.

2. Used credit for TV/radio/stereo equipment and tended

to read 1001/Decoratihq Ideas and Glamour.

Group II

1. Used credit for leisure-time airline travel and tended

to read Better Homes and Gardens, Ladies Home Journal,

National Geographies, Time and U.S. News and World

Report.

2. Used credit for gas/oil/parts for car on a vacation

and tended to read Consumer's Reports, Family C ircle,

Ladies Home Journal, National Geographies, and Woman1s

M- 3. Used credit for hotel, motel, or lodge while on a vaca­

tion and tended to read Family Circle, National Geogra-

phics, Newsweek, Southern Living, and Woman's Day.

5.-Reasons for Considering Use of Long-Term Credit. The cross­ tabulations of the male data indicated basically that if the respon­ dent would consider using credit for one of the reasons listed, he would consider all the reasons acceptable. The only discernable departure from this pattern was the fact that using long-term credit to take a vacation trip was related significantly to only six other 176 reasons which was the smallest group of interrelationships among all

the reasons. These six other reasons were: buy home furnishings, pay piled up bills, cover expenses when income cut, have optional surgery, pay legal b ills and buy second home.

It should be noted, however, that the following reasons were not included in the cross-tab analysis because of very low frequency counts: buy/stocks or bonds, furs or jewelry, expensive sporting equipment, or swimming pool, stay at a resort, and take a honeymoon trip. "Buy a car" was also not included because of a very high frequency count. Four of these reasons are leisure-time oriented.

The females in general were much more conservative in what they felt were (statistically significant) acceptable reasons for using long-term credit. In terms of a data matrix of significant relationships between all pairs of reasons, the males had thirty-two empty (non-significant at .005 level) cells, while the females had fifty-one such cells.

In their case, the females showed a significant relationship between using credit to take a vacation trip and only two other rea­ sons: buy home furnishings and pay piled up b ills. The females were also not very prone to using long-term credit to help a rela­ tive (significant relationships with only two other reasons) or to buy a second or vacation home (significant relationships with only

3 other reasons: buy land or property, buy house or trailer, and go into business for myself). 177

' 6 i,-Use of C r e d i t i n ! 972' versus' Reasons for Corisidering Use of Long-Term Credit. There were very few significant cross-tabs for either the males or females when these two sets of variables were related. Two relationships were highly significant, however, for both the males and females.

1. Respondents who used credit for leisure-time airlin e

travel during 1972 also would consider using long-term

credit to take a vacation trip.

2. Respondents who used credit to buy sporting equipment

during 1972 would also consider using long-term credit

to buy a recreational vehicle, camping trailer, or boat.

Other significant relationships among the males included: used credit forTV/radio/stereo equipment/would considerlong­ term credit to buy home furnishings; and used credit fordrugs,etc./ would consider long-term credit to pay medical b ills. The remain­ ing few significant relationships were less meaningful.

Analysis of Table 24. Table 24 presents for the female respondents a series of summary frequency counts and percentages.

Holders of Sear's, Penney's and/or Ward's credit cards are not only the most numerous but also the most likely to also have a BankAmeri­ card, Master Charge, and gasoline company card or cards. The tradi­ tional Travel and Entertainment (T & E) cards are not held by very many of the respondents. More respondents hold Master Charge cards than BankAmericard.

Use of credit for outdoor clothing and for gas, oil, etc. for car while on a vacation were the two most popular uses of credit 178

Table 24

Descriptive Summary - Credit Cards Held and Uses of Credit 9 (603 Female Respondents)

Percent of Percent of Number

A. Have credit card(s) 485 80% 100% Do not have any credit cards 117 20 0

B. Have: Sear's, Penney's, Ward's card 341 56.6 70.3 Gasoline Co. card 313 52.0 64.5 Other Dept, store card 296 49.1 61.0 Master Charge (MC) 175 29.0 36.1 Bank Americard (BAC) 149 24.7 30.7 American Express card (Amex) 28 4.6 5.8 Airline travel card (ATC) 16 2.7 3.3 Auto Rental card 9 1.5 1.9 Diner's Club 7 1.1 1.4 Carte Blanche 3 .5 .6

C. Number (and percent).holding both of the two indicated cards:b Sear's, Other Amex BAC MC Gas Co. ATC etc. Deot. St. Amex 28 12 15 23 2 17 18 BAC 43% 149 67* 106* 7 104* 94* MC 54% 45% 175 124* 8 129* 119* Gas Co. 82% 71% 71% 313 15* 225* 192* ATC 7% 5% 5% 5% 16 9 9 Sear's, etc. 61% 70% 74% 72% 5F% 341 205* Other Dept. 64% 63% 68 % 61% 56% ~ W % o 296 *Significant at . 001 level or greater (chi-square test) D. Number using credit for each of the following purposes during 1972:

Percent of Percent of Number Total Sariipl e Card Hoi ders Outdoor Clothing 283 47.0% 58.4% Gas, oil, etc. for car while on a vacation 258 42.8 53.2 Drugs, cosmetics 144 23.9 29.7 Stay at hotel, motel, lodge on a vacation 115 19.1 23.7 TV, radio, stereo , tape equip. 114 18.9 23.5 Garden, lawn care supplies 101 16.7 20.8 179 Table 24 (Continued)

D. (.Continued) Percent of Percent of Number ' Total Sample Card Holders

Eating in a restaurant on a vacati on 90 14.9 18.6 Personal vacation or leisure-time airline travel 84 13.9 17.3 Photographic equipment 77 12.8 15.9 Sporting equipment 67 11.1 13.8 Cash Advances 61 10.1 12.6 Indoor Table Games 58 9.6 12.0 Other hobby equipment 51 8.5 10.5

E. Reasons for which respondents would consider use of long-term credit (more than 90 days): Percent of Percent of ' Number Total Sample Card Holders

Buy a car 446 74.0% 92.0% Buy land or property 398 66.0 82.1 Buy house or tra ile r 352 58.4 72.6 Pay medical expenses 310 51.4 63.? Put children thru college or tech. school 289 47.9 59.6 Buy home furnishings 282 46.8 58.1 Have optional surgery/dental work 260 43.1 53.6 Go into business for myself 217 36.0 44.7 Pay legal bills or settlement 179 29.7 36.9 Pay piled up bills 167 27.7 34.4 Pay for personal education 162 26.9 33.4 Buy a rec. vehicle, trailer, boat 150 24.9 30.9 Help a relative who needs money 115 19.1 23.7 Buy a second or vacation home 107 17.7 22.1 Cover expenses when income cut 99 16,4 20.4 Take a vacation trip 62 10.3 12.8 Buy swimming pool 61 10.1 12.6 Take honeymoon trip 23 3.8 4.7 Buy stocks or bonds 20 3.3 4.1 Stay at a resort 20 3.3 4.1 Buy expensive sporting equipment 15 2.5 3.1 Buy furs or jewelry 7 1.2 1.4 Notes: a "User of credit during 1972" . with fewer than 15 responses are not listed. ^Number of respondents holding both cards is given above the main diagonal; percentage holding both is given below. 180

during 19.72. Almost twice as many respondents used credit for

these two purposes as for the third most popular purpose.

Only 25 percent of the respondents would consider

using long-term credit for the "most acceptable" leisure-time

oriented purpose--buy a recreational vehicle, trailer or boat. All

other leisure-time oriented purposes are acceptable to even fewer

respondents.

Analysis of Table 25. Table 25 presents the same variables

as Table 24 tabulated for the male respondents. Approximately the

same ranking of credit cards holds for the males or for the females.

The only switch is in the f ir s t and second position, in that more

of the males have a gasoline company card than have a Sear's,

Penney's and/or Ward's card.

While "other department store card" is third in popularity for both sexes, 20 percent fewer of the males carry them than do the females. ,

As with the females, approximately 6 percent more of the respondents have Master Charge cards than BankAmericards. Since these cards are typically issued one (with copies) to a family, the consistency of this percentage is not surprising.

The proportion of males holding an American Express card and

BankAmericard, Master Charge, gasoline company and/or airline travel cards is sta tis tic a lly significant. This might imply that an Ameri­ can Express card alone is not deemed sufficient. 181

Table 25

Descriptive Summary - Credit Cards Held and Uses of Credit 3 (512 Male Respondents)

Percent of Percent of Number Total'Sample Card Holders

A. Have credit card(s) 409 79.9% 100% Do not have any credit cards 103 20.1 0

B. Have: Gasoline Co. card 287 56.1 70.2 Sear's, Penney's, Ward's cards 275 53.7 67.2 Other Dept. Store card 196 38.3 40.4 Master Charge (MC) 156 30.5 38.1 Bank Americard (BAC) 132 25.8 32.3 American Express card (Amex) 38 7.4 9.3 Airline travel card (ATC) 25 4.9 6.1 Auto rental card 17 3.3 4.2 Diner's Club 9 1.8 2 .2 Carte Blanche 7 1.4 1.7

C. Number (and percent) holding both of the two indicated cards :b Other Amex BAC MC Gas Co. ATC Sear's etc. DeDt.St. 22 BAC 50% 132 58* 97* 14* 84* 66* MC 61% ~ m 156 116* 13 108* 90* Gas Co. 95% 72% ~ m 287 21 192* 143* ATC 26% 11% 8% 7% 25 12 17 Sear's, etc. 58% 64% 69% 67% m 275 138* Other Dep.St. 58% 50% 58% 50% 68% “50% 196 ♦Significant at .001 level or greater (chi-square test) D. Number using credit for each of the following purposes during 1972:

Percent of Percent of ‘Number Total Sample Card Holders

Gas, oil, etc. for car while on a vacation 245 47.9% 60.0% Outdoor Clothing 179 35.0 43.8 Stay at hotel, motel, lodge on a vacation 103 20.1 25.2 TV, radio, stereo, tape equip. 97 18.9 23.7 Garden, lawn care supplies 92 18.0 22.5 Eating in a restaurant on a vacation 85 16.6 2 0 .8 Table 25 (Continued) 182

D. (Continued)

Percent of Percent of Number ' Total Sample Card Holders

Personal vacation or leisure-time airline travel 80 15.6 20.0 Sporting equipment 77 15.0 18.8 Drugs* cosmetics 73 14.3 17.8 Cash advances 70 13.7 17.1 Photographic equipment 51 10.0 12.5 Other hobby equipment 46 9.0 11.2 Indoor Table games 37 7.2 9.0 Bicycling equipment 23 4.5 5.6

E. Reasons for which respondents would consider use of long-term credit (more than 90 days):

Percent of Percent o- ' Number Total Sample Card Hoi del

Buy a car 400 78.1% 97.8% Buy land or property 368 71.9 90.0 Buy house or tra ile r 332 64.8 81.2 Pay medical expenses 289 55.5 69.4 Go into business for myself 217 47.9 59.9 Buy home furnishings 243 47.5 59.4 Put children thru college or tech. school 236 46.1 57.7 Have optional surgery/dental work 200 39.0 48.9 Pay legal bills or settlement 189 36.9 46.2 Pay for personal education 157 30.7 38.4 Buy a rec. vehicle, trailer, boat 150 29.3 36.7 Pay piled up bills 147 28.7 35.9 Buy a second or vacation home 111 21.7 27.1 Cover expenses v/hen income cut 107 20.9 26.2 Help a relative who needs money 99 19.3 24.2 Buy swimming pool 55 10.7 13.4 Take a vacation trip 40 7.8 9.8 Buy expensive sporting equipment 38 7.4 9.3 Buy stocks or bonds 30 5.9 7.3 Take honeymoon trip 24 4.7 5.9 Stay at a resort 21 4.1 5.1 Buy furs or jewelry 7 T.4 1.7 Notes:

a"Uses of credit during 1972" with fewer than 17 responses are not listed. ^Number of respondents holding both cards is given above the main diagonal; percentage holding both is given below. 183

There are also more statistically significant pairs of cards held by the males than with the females. This might imply that males carry more credit cards than do females.

Seven of the first eight purposes for which credit was used during 1972 are the same for the males and females. The difference is that almost twice as many females used credit for drugs, cos­ metics, sundries, etc. than did the males. Also, as in the case of credit cards held, gasoline cards and purchases on credit are at the top of the l i s t for males and second on the l i s t for females.

Only 29 percent of the males would consider using long­ term credit to buy a recreational vehicle, trailer, or boat, which is also their "most acceptable" leisure-time oriented purpose for which they might use this form of credit.

Analysis of Table 26. Table 26 lists the final eighty-six variables used in the succeeding factor analysis of credit-oriented and related variables. This list represents a selection of those variables deemed relevant and with "sufficient" responses (usually

5 percent or more) to permit useful analysis. Tables 27--30 present the results of the factor analysis of the variables in Table 26 for both holders and non-holders of credit cards.

Analysis of Table 27. Table 27 shows the groupings of related variables by female holders of credit cards. The three factors

(groups) together account for only 17 percent of the total variance in the data. There were no other factors which individually accounted for 5 percent or more of the variance. 184

Table 26

Final Variablesibles used in Factor Analysis of Selected Credit-Oriented,Credi Religi on, Life-Styl-and-:Demographic Variables

Variable - Note — Variable No.

Total Household Income Scale ($4K—15K and up) (a) 1 Have credit cards - yes/no (b) 2 Have American Express Card (b) 3 Have BankAmericard (b) 4 Have Master Charge (b) 5 Have Gasoline Co. card (b) 6 Have Sear's, Penney's, Ward's card (bj 7 Have other department store card (b) 8

Credit Card Characteristic: (c) Safer than carrying cash 9 They may be lost or stolen 10 More convenient than checks 11 I may buy more than necessary 12 Can buy now without the cash 13 The interest charges are high 14 The receipts help keep track of spending 15 They contribute to inflation 16 Useful in emergencies 17 Get fewer b ills each month 18 Its hard to tell what is spent 19 Good when travelling 20 Computer mistakes lead to falsified bills 21 Quick credit identification when needed 22

AIO Statements: (d) Organized religion should try to deal with social problems. 23 Credit cards make it too easy to buy things I may not really need. 24 Religion is more important to me today than it was five years ago. 25 Using credit when you buy something is bad practice. 26 I will probably not have more money to spend next year than I have now. 27 When i t comes to my recreation, time is a more important factor to me than money. 28 I sometimes feel the presence of God. 29 Five years from now, our family income will probably be a lot higher than it is now. 30 Religion is less of an influence on society today than it was five years ago. 31 185 Table 26 (Continued)

Variable ...... vNote.. .Variable No.

I usually charge everything that I can on a trip or vacation. 32 It is important for me to seek God's will when I make major decisions. 33 It is more important to live graciously, than to save up a lot of money for the future. 34 In a job, security is more important than money. 35 When i t comes to my recreation, money is a more important factor to me than time. 36 People should avoid expensive or luxurious products. 37 When I get my credit card bill, I usually pay it in fu ll. 38 Our family income is high enough to satisfy nearly all our important desires. 39 A "travel-now-pay-later" vacation iswrong. 40 No matter how fast our income goes up we never seem to get ahead. 41 I buy many things with a credit card or chargecard. 42 I try hard to carry my religion over intoall my other dealings in life. 43 If i t wasn't for the convenience aspect of credit, I wouldn't use it. 44 Most people spend too much time working, and not enough time enjoying life . 45 I get paid what I am worth. 46 Our family is too heavily in debt today. 47 A person should share his religious beliefs with others. 48

Used credit in 1972 for: (e) Outdoor clothing, etc. 49 Drugs, cosmetics, sundrys 50 Sporting equipment 51 TV, radio, stereo equipment 52 Garden or lawn care supplied 53 Photographic equipment 54 Personal vacation airline travel 55 Gas, oil, parts for car on avacation 56 Hotel, motel, lodge while on avacation 57 Eating in restaurants while on avacation 58 186

Table 26 (Continued)

Variable...... Note Variable No.

Would consider using long-term credit to: (f) Pay medical expenses 59 Buy home furnishings 60 Pay piled up bills 61 Buy stocks or bonds 62 Buy land or property 63 Buy a house or tra ile r 64 Take a vacation trip 65 Pay for an education for myself 66 Cover expenses when my income has been cut 67 Have optional surgery/dental work done 68 Put children through college 69 Pay legal bills or settlement 70 Buy expensive sporting equipment 71 Go into business for myself 72 Help relative who needs money 73 Buy a second or vacation home 74 Buy recreational vehicle 75 Buy swimming pool 76 Religious Affiliation scale (g) 77 Education level of female ■(h) 78 Education level of male (h) 79 Position of male within company (h) 80 Occupation of male (h) 81 Employment status of female !h! 82 Household size h) 83 Age of male (h) 84 Population density and degree of urbanization (h) 85 Age of female (h) 86

Notes:

aTotal Household Income scaled as follows: $4000-4999 1 5000-5999 2 6000-6999 3 70Q0-7999 4 8000-8999 5 9000-9999 6 10,000-11,999 7 12,000-14,999 8 15,000 or more 9 Table 26 (Continued)

Notes:

cFrom question 1c.

eFrom question le.

^From question 2 .

^From question 2 2 , scaled as follows: Other Protestantdenominations 1 Catholics 2 Baptists or Disciples 3 Methodists 4 Presbyterians orLutherans 5 Episcopalians 6 Jewish 7 Unitarians 8 Other 9 None 0

^From Market Facts biographical data card - see Appendix B. 188

Table 27

Groupings (factors) of Related Selected Credit-Oriented, Religion, Life-Style and Demographic Variables Based Upon Female Holders of Credit Cards3

i ; (6;2%)b Occupation of male—scaled from professional (1) to service worker (9) (-.537)c Would consider using long-term credit to buy land or property (.528) Would consider using long-term credit to buy a house or trailer (.506) Position of male within company-scaled from owner (1) to hourly (7) (-.502) Would consider using long-term credit to send children to college (.494) Education level of male—scaled from little (1) to post-grad (7) (.468) Age of female—scaled from "under 25" ( 1) to "55 and over" (5) (-.456) Education level of female—scaled from little (1) to post-grad (7) (.456) Would consider using long-term credit to pay for an education for myself (.454) I will probably have more money to spend next year than I have now (.450) Would consider using long-term credit to go into business for myself (.442) Total household income—scaled from $4-5K (1) to $15K and up (9) (.439) Would consider using long-term credit to buy a second or vacation home (.438) Age of male—scaled from "under 25" ( 1) to "55 and over" (5) (-.425) Five years from now our family income will probably be a lot higher than it is now (.415) People should not avoid expensive or luxurious products (.400) Would consider using long-term credit to buy a recreational vehicle (.395)

2. (5.8%) I buy many things with a credit card or charge card (.676) I usually charge everything that I can on a trip or vacation (.572) Used credit for eating in a restaurant while on a vacation or for other non-business dining in 1972 (.548) Used credit for staying in a hotel, motel, or lodge while on a vacation in 1972 (.533) Used credit for purchasing outdoor clothing, etc. in 1972 (.496) Used credit for purchasing drugs, cosmetics, sundrys in 1972 (.494) Used credit for purchasing garden or lawn care supplies, etc. in 1972 (.456) Used credit for purchasing photographic equipment, parts, supplies in 1972 (.412) Used credit for personal vacation or leisure-time airline travel in 1972 (.407) Used credit for gas, oil, parts for car while on a vacation in 1972 (.406) Have "other department store" credit cards (.390) Have BankAmericard (.390) 189 Table 27 (Continued)

3; (5.3%) When I get my credit card bill I do not usually pay it in full(.580) Our family is too heavily in debt today (.564) Would consider using long-term credit to pay piled up bills (.554) No matter how fast our income goes up, we never seem to get ahead (.552) Age of female—scaled from "under 25" ( 1) to "55 and over" (5) (-.508) Age of male—scaled from "under 25" ( 1) to "55 and over" ( 5 ) (-.491) Our family income is not high enough to satisfy nearly all ourneeds (.473) Would consider using long-term credit to buy home furnishings (.471) The fact that one can "buy now without the cash" is important to me (.459) Credit cards make it too easy to buy things I may not really need (.410) Would consider using long-term credit to cover expenses when my income has been cut (.395)

Notes:

aThere were 485 female respondents who indicated they had one or more credit cards.

^Percentage of the variance in the data accounted for by the total Varimax rotated factor.

cLoading of that variable on the factor. 190

Group 1 appears to have a higher male occupational level/ position within company, younger, better educated, and higher total household income orientation. Respondents falling into this group consider the use of long-term credit to finance either the purchase of tangible assets or an education to be acceptable. They appear optimistic about their future income levels, and are not adverse to expensive or luxurious products. The use of long-term credit to finance the purchase of a recreational vehicle, trailer or boat is only marginally acceptable.

Group 2 seems to be the heavy users of credit, particularly through the medium of credit cards. They do not appear to be ad­ verse to using credit for lei sure-time related purposes based upon their usage of credit during 1972. They tend to be more likely to have a BankAmericard and other department store" credit card. Inter­ estingly, having a Master Charge card only loaded 0.35 on this fac­ tor, although that was the highest loading on any factor for that variable. No demographic variable loaded higher than 0.25 on this factor, and only one loaded at that level--the rest were less than

0.13.

Group 3 appears to be a younger group who are deeply concerned about their financial situation. They seem to be overextended relative to their liquid assets and perhaps are overly prone to using credit unwisely or unnecessarily. They may be caught in a

"vicious circle" wherein much of their income goes toward paying credit card bills, leaving them with insufficient cash and thereby encouraging additional usage of credit. This group may also tend 191

to be in an occupational situation where there is a danger of an

income cut, perhaps due to layoffs or strikes.

Analysis Of Table 28. Table 28 presents the results of the

groupings of the variables by female non-holders of credit cards.

These four groups together account for 25 percent of the variance in the data.

Group 1 appears to be an older group without prospects for a significantly higher income in the future. They tend to be adverse toward the use of credit in general and toward a travel-now-pay-

later- vacation in particular. They would not consider using long­ term credit to buy a house or tra ile r—possibly because either they already have one or because they do not wish to incur significant debt on a limited income.

Group 2 appears to be similar to group 3 of the female holders of credit cards. They are concerned about their financial situa­ tion, perhaps are overcommitted financially, and, at least relative to recreation, value the monetary costs involved more highly than the time costs. Household size seems somewhat larger, implying one or two or more children. There are no other demographic variables which reach significant loadings on this factor (about 0.40 or greater), however, "position of male within company loads at -.370, which tends to imply a middle level executive position.

Group 3 is a cluster of all but one of the religious-oriented

AIO statements. There were no other variables which came close to significant loadings on this factor except the "religious affiliation scale" which loaded at 0.33 implying a slightly upscale orientation. 192

Table 28

Groupings (Factors) of Related Selected Credit-Oriented, Religion, Life-Style and Demographic Variables Based Upon Female Non-Holders of Credit Cards3

i : (7:4%)b Age of male—scaled from "under 25" ( 1) to "55 and over" (5) (.869)c Age of female—scaled from "under 25" (1) to "55 and over" (5) (.822) Five years from now our family income will probably not be a lot higher than it is now (.633) Using credit when you buy something is bad practice (.575) Would not consider using long-term credit to buy a house or trailer (.549) I will probably not have more money to spend next year than I have now (.502) A "travel-now-pay-later" vacation is wrong (.411)

2 ; (6:1%) No matter how fast our income goes up, we never seem to get ahead (.672) Our family is too heavily in debt today (.627) When it comes to my recreation, money is a more important factor to me than time (.557) Our family income is not high enough to satisfy nearly all our important desires (.532) People should avoid expensive or luxurious products (.524) Household size—scaled from 2 members to 8 members (.457) Would consider using long-term credit to pay piled up bills (.412)

3. (5.9%) I try hard to carry my religion over into my other dealings in life(.778) It is important for me to seek God's will when I make major decisions (.762) A person should share his religious beliefs with others (.701) I sometimes feel the presence of God (.680) Religion is more important to me today than it was five years ago (.620)

4. (5.5%) Would consider using long-term credit to have optional surgery or dental work done (.628) Would consider using long-term credit to pay medical expenses (.565) Would consider using long-term credit to pay legal bills or a settle­ ment (.552) Would consider using long-term credit to help a relative who needs money (.490) Would consider using long-term credit to pay for an education for myself (.486) Would consider using long-term credit to put my children through college or technical school (.452) Would consider using long-term credit to pay piled up bills (.432) Table 28 (Continued)

Notes:

aThere were 117 female respondents who indicated they did not have credit cards.

^Percentage of the variance in the data accounted for by the total Varimax rotated factor.

cLoading of that variable on the factor. 194

The point of interest here is that these variables are much more closely related to each other than they are to any of the credit- oriented or related variables used in this analysis. The implica­ tion appears to be that respondents can divorce their feelings toward these statements from their feelings toward the other variables used.

It may be noted that the same variables form a factor or group for the female holders of credit cards, but the factor only accounted for 4 percent of the variance.

Group 4 represents a cluster of uses of long-term credit more highly related to each other than to any other variables used in the analysis. There were no demographic variables that loaded above 0.260 on this factor and only one above 0.190. The closest variable to significance was the AIO statement "I get paid what I am worth" loading at .370. This group of uses of long-term credit might be viewed as "traditionally acceptable" uses. There are no leisure-time oriented uses included in the group, and none of this category of uses loaded higher than 0.100 on this factor.

Analysis of Table 29. Table 29 presents the results of the groupings of the variables male holders of credit cards. These four factors account for 24 percent of the variance in the data.

Group 1 appears to represent a younger group who are optimistic about the long-term growth of their total household income. They would consider long-term credit to finance an education either for themselves or for their children, and to purchase a home and home furnishings. This group also seems to be concerned about their present financial situation, income vis a vis expenses. None of 195

Table 29

Groupings (Factors) of Related Selected Credit-Oriented, Religion, Life-Style and Demographic Variables Based Upon Hale Holders of Credit Cards3

1 . (7.7%)^ Age of male—scaled from "under 25"'(1) to "55 and over" (5) (-.694)c Age of female—scaled from "under 25" (1) to "55 and over" (5) ( - . 686 ) Five years from now our family income will probably be a lot higher than it is now (.552) Would consider using long-term credit to put my children through college or technical school (.513) Our family is too heavily in debt today (.510) Would consider using long-term credit to buy home furnishings (.510) Would consider using long-term credit to pay for an education or special training for myself (.506) When I get my credit card bill, I do not usually pay it in full (.504) Would consider using long-term credit to pay piled up bills (.446) Would consider using long-term credit to have optional surgery or dental work done (.433) Would consider using long-term credit to buy a house or trailer (.424) Would consider using long-term credit to pay legal bills or a settle­ ment (.400)

2 . (6 . 1%) Education level of male—scaled from l i t t l e (1) to post-grad (5) (.623) Total household income—scaled from "$4-4.9K" (1) to "$15K and over" (9) (.554) Used credit in 1972 to eat in a restaurant while on a vacation or for other non-business driving (.541) Used credit in 1972 for gas, oil, parts for car while on a vacation (.523) Used credit in 1972 for staying in a hotel, motel, lodge while on a vacation (.518) Education level of female—scaled from little (1) to post-grad (5) (.477) Used credit in 1972 for personal vacation or leisure-time airline travel (.450) Position of male in company—scaled from "owner" (1) to "hourly" worker (7) (-.436) I usually charge everything that I can on a trip or vacation (.432) Occupation of male—scaled from "professional" (1) to "service worker" (9) (-.419) Credit cards do not make it too easy to buy things I may not really need (.391) 196 Table 29 (Continued)

3 .(5 ;6%) It is important to respondent that credit card receipts help keep track of spending (.652) It is important to respondent that credit cards are safer than carrying cash (.642) It is important to respondent that credit cards are more convenient than checks (.612) It is important to respondent that credit cards mean getting fewer bills each month (.600) It is important to respondent that credit cards are good when travell­ ing (.532) It is important to respondent that credit cards provide quick credit identification (.508) I buy many things with a credit card or charge card (.499) It is important to respondent that credit cards permit buying now with­ out the cash (.442) It is important to respondent that credit cards are useful in emergen­ cies (.430)

4. (4.7%) Respondent has "other department store card" (.576) It is not important to respondent that credit cards contribute to infla­ tion (.524) Respondent has "Master Charge" card (.520) It is not important to respondent that with credit cards it's hard to te ll what is spent (.502) Respondent has "Sear's, Penney's, or Wards'" card (.495) It is not important to respondent that interest charges are high with credit cards (.492) It is not important to respondent that computer mistakes lead to falsified credit card bills (.463) Respondent has "BankAmericard" card (.438) Respondent has "American Express" card (.437) It is not important to respondent that credit cards may be lost or stolen (.400)

Notes:

aThere were 4Q9 male respondents who indicated they had one or more credit cards.

^Percentage of the variance in the data accounted for by the total Varimax rotated factor.

cLoading of that variable on the factor. 197

the leisure-time oriented uses of long-term credit load significantly

(.400 or greater) on this factor, but do load .300 or greater.

Group 2 appears to represent that group who did use credit for

leisure-time oriented products and pursuits during 1972, and tend

to use credit heavily on a vacation. They seem to be better educated,

have an "upscale" total household income, and be in a higher occupa­

tional level/position at their place of employment.

Group 3 represents a clustering of all the advantages or

positive characteristics of credit cards as presented in question

1c. None of the disadvantages or negative characteristics load

significantly on this factor. Apparently, the respondent who tends

to use credit cards extensively feels that all of these benefits or

advantages are important to him. The implication here, however,

as in the case of the religious-oriented AIO statements, is that

these characteristics form a conceptual cluster by themselves quite

unrelated to most of the other variables used in this analysis.

Group 4 appears to represent that group of respondents who

have several different credit cards. They do not seem to recognize,

or be concerned with, the possible disadvantages or negative char­

acteristics of credit cards. There were no demographic variables

loading greater than .12 on this factor.

Analysis of Table 30. Table 30 presents the results of the

groupings of the variables by male non-holders of credit cards.

These six factors or groups account for 36 percent of the variance in the data. 198

Table 30

Groupings (Factors) of Related Selected Credit-Oriented, Religion, L ife-S tyle and Demographic Variables Based Upon Male Non-Holders of Credit Cards9

1; (7.o%)b Age of female—scaled from "under 25" (1) to "55 and over" (5) (-.824)° Age of male—scaled from "under 25" (1) to "55 and over" (5) (-.800) Would consider using long-term credit tobuy a house or trailer (.640) Five years from now, our family income will probably be a lot higher than it is now (.424) Religious affiliation scale (see note (g), Table 26) (.418) Would consider using long-term credit to buy a recreational vehicle (.414) Would not consider using long-term credit to pay medical expenses (.405) Would consider using long-term credit to buy home furnishings (.404) Would consider using long-term credit to go into business for myself (.390) I will probably have more money to spend next year than I have now(.370) Using credit when you buy something is not a bad practice (.360)

2 . (6.6%) I try hard to carry religion over into all my other dealings in life (.815) Religion is more important to me today than it was five years age (.750) A. person should share his religious beliefs with others (.711) It is important for me to seek God's will when I make major decisions(.683) I sometimes feel the presence of God (.574) Organized religion should try to deal with social problems (.527) Credit cards make it too easy to buy things I may not really need (.380)

3. (6.5%) Would consider using long-term credit to pay legal bills or a settle­ ment (.630) Would consider using long-term credit to pay for an education for myself (.625) Would consider using long-term credit to buy expensive sporting equip­ ment (.543) Would consider using long-term credit to pay medical expenses (.506) Would consider using long-term credit to buy a second or vacation home (.479) Would consider using long-term credit to put my children through college (.468) Would consider using long-term credit to go into business for myself (.464) Would consider using long-term credit to help a relative who needs money (.457) Would consider using long-term credit to pay piled up bills (.450) 199 Table 30 (Continued)

4. (6.0%) Our family income is not high enough to satisfy nearly all our impor­ tant desires (.656) Our family is too heavily in debt today (.628) No matter how fast our income goes up, we never seem to get ahead (.595) When it comes to my recreation, time is not a more important factor to me than money (.501) When it comes to my recreation, money is a more important factor to me than time (.482) I do not get paid what I am worth (.462) If it wasn't for the convenience aspect of credit, I wouldn't use it (.428) Household size—scaled from 2 to 8 (.390) I usually charge everything I can on a trip or vacation (.340) Education level of male—scaled from l i t t l e (1) to post-grad (5) (-.320) Would consider using long-term credit to pay piled up bills (.320)

5: (5:0%) Position of male in company—scaled from owner (1) to hourly worker (7) (.642) Occupation of male—scaled from professional (1) to service worker (9) (.618) Education level of female—scaled from little (1) to post-grad (5) (-.526) I buy many things with a credit card or charge card (.447)

6. (4.9%) Population density/degree of urbanization—scaled rural to SMSA of 2M and over (.673) People should not avoid expensive or luxurious products (.560) A "travel-now-pay-later" vacation is not wrong (.466) Would consider using long-term credit to take a vacation trip (.454) Would consider using long-term credit to pay for optional surgery or dental work (.404) It is more important to live graciously than to save up a lot of money for the future (.367) Credit cards do not make it too easy to buy things I may not really need (..355) Education level of female—scaled from little (1) to post-grad (5) (.343)

Notes: aThere were 103 male respondents who indicated they did not have any credit cards.

^Percentage of the variance in the data accounted for by the total Varimax rotated factor.

cLoading of that variable on the factor. 200

Group 1 appears to represent a fairly young segment of the

respondents who are optimistic about the future growth of their

income. They also tend to be upscale on the religious affiliation

scale. They consider the use of long-term credit to buy a house,

home furnishings, or to start a business to be acceptable. They also

tend to be upscale on the religious affiliation scale. They consider

the use of long-term credit to buy a house, home furnishings, or

to start a business to be acceptable. They also would consider the

use of long-term credit to buy a recreational vehicle, trailer or

boat. With the exception of "house or tra ile r," however, most of

the variable's loadings on the factor are marginal in their signi­

ficance. This may imply a marginally coherent or definable group.

Group 2 is the religious-attitude statement group as dis­

cussed under the female non-holders. All six of the religious-

oriented AIO statements are included in this group. No demographic

variable loading approached 0.400. The closest other variable to

significance is the AIO statement that "credit cards make it too

easy to buy things I may not really need" (.380). This tends to

imply that males who agree with the religious AIO statements believe

credit cards to be a "temptation."

Group 3 is very similar to group 4 of the female non-holders, with the addition of two acceptable leisure-time oriented uses of

long-term credit-expensive sporting equipment and a second or

vacation home. Again, no demographic variables come close to load­

ing significantly on this factor. 201

Group 4 is very similar to group 2 of the female non-holders.

This is the "high-concern-over-money-matters" group. Males in this group tend to be somewhat less educated. They also tend to value the convenience aspect of credit and perhaps tend to charge exces­ sively, particularly on trips.

Group 5 appears to represent a lesser educated (education level of male loaded -.370), non-supervisory, lower occupational level group of males who tend to buy many things with a credit card.

This is particularly interesting since all of the group of respon­ dents are supposed to be non-holders of credit cards. Perhaps they are using their wives' cards, or perhaps they did not fill out the questionnaire properly.

Group 6 may approximate an upper-middle class "jet set." They appear to live in more highly urbanized areas, and consider gracious or luxurious living to be acceptable. They also do not appear to feel that the use of credit for vacation trips or discretionary surgery/dental work is improper. Apparently, they also feel they can control their impulse purchasing with credit cards.

Analysis of Table 31. Table 31 presents the arithmetic means of the eighty-six variables listed in Table 26. In all cases where there are statistically significant differences in the means (at the .005 level or greater) between holders of credit cards and non­ holders, the differences are significant for both males and females.

The differences in means were tested by means of a t- te s t (Dixon and Massey, 1969:116). 202

Table 31

Means of the 86 Variables Factor Analyzed in Tables 27—30

Variable ...... Female...... Male Number Holders Non-Holders Holders Non-Holders (Table 26) 27) (Table 28) (Table 29) (Table 30)(Table

1 6.52 5.15* 6.46 5.15* 2 3 2.35 4 .60 1.96 5 .72 2.01 6 1.22 1.94 7 1.28 1.87 8 1.04 1.71 9 3.89 3.90 10 4.00 3.90 11 3.59 3.64 12 2.99 2.72 13 3.65 3.45 14 3.86 3.86 15 3.55 3.59 16 3.11 3.06 17 4.65 4.65 18 3.25 3.17 19 3.00 2.91 20 4.31 4.41 21 3.31 3.21 22 4.31 4.17 23 3.53 3.53 3.46 3.27 24 3.52 4.25* 3.55 4.42* 25 3.27 3.33 3.05 3.13 26 2.98 3.61* 2.94 3.62* 27 3.52 3.69 3.45 3.69 28 3.36 3.28 3.42 3.31 29 4.13 4.35 3.68 3.67 30 3.17 3.27 3.40 3.24 31 3.12 3.35 3.37 3.22 32 1.87 1.36* 2.00 1.25* 33 3.80 3.99 3.29 3.32 34 3.07 2.94 3.01 2.96 35 3.43 3.42 3.46 3.75 36 2.60 2.69 2.66 2.96 37 2.86 3.13 3.01 3.26 38 3.92 3.19* 4.07 3.15* 39 3.47 3.30 3.45 3.21 40 3.68 4.09 3.72 4.17 203

Table 31 (Continued)

Variable Female Male Number ...... Holders ...... • -Non"Holders •• Holders Non-Holders (Table 26) (Table 27) (Table 28) (Table 29) (Table 30)

41 3.08 3.19 3.12 3.23 42 2.55 1.52* 2.55 1.44* 43 3.68 3.62 3.09 3.13 44 3.72 3.11* 3.63 3.15* 45 3.76 3.67 46 2.81 2.69 2.71 2.66 47 2.14 2.18 2.22 1.92 48 3.29 3.46 3.16 3.17 49 .58 .44 50 .30 .18 51/ .14 .19 52 .24 .24 53 .21 .23 54 .16 .13 55 .17 .20 56 .53 .60 57 .24 .25 58 .19 .21 59 .51 .52 .56 .55 60 .50 .35 .51 .35 61 .26 .33 .27 .39 62 .07 .03 63 .66 .68 .70 .78 64 .58 .62 .65 .63 65 .12 .04 .09 .03 66 .28 .21 .31 .27 67 .18 .11 .20 .23 68 .44 .40 .40 .34 69 .47 .50 .46 .46 70 .30 .30 .38 .32 71 .08 .04 72 .36 .34 .48 .49 73 .20 .14 .20 .17 74 .21 .06 .24 .12 75 .26 .20 -.31 .21 76 .12 .05 77 3.45 3.20 3.45 2.79* 78 4.35 3.78* 4.32 3.82* 79 4.44 3.66* 4.42 3.68* 204 Table 31 (Continued)

Variable Female Male Number ...... Holders • Non-Holders Holders Non-Holders (Table 26) (Table 27) (Table 28) (Table 29) (Table 30)

80 6.34 6.56 6.21 7.06* 81 4.67 5.38* 4.55 6.08* 82 4.04 4.50 83 3.08 3.10 3.09 3.00 84 3.28 2.91 3.25 2.97 85 4.36 4.00 86 3.05 2.68 3.03 2.76

*Difference between means of holders and non-holders is significant at the .005 level. 205

Based on this test* respondent holders and non-holders differed in the following ways:

1. Holders have higher total household incomes (by about

$1000) than non-holders.

2. Holders are less likely to agree that credit cards make

it too easy to buy things they may not really need, than

non-holders.

3. Holders are more likely to disagree that using credit

when you buy something is bad practice, than non-holders.

4. Holders are less likely to disagree with the statement,

"I usually charge everything that I can on a trip or

vacation," than non-holders.

5. Holders are more likely to agree that when they get their

credit card bill, they usually pay it in full, than non­

holders.

6. Holders are less likely to disagree with the statement,

"I buy many things with a credit card or charge card,"

7. Holders are more likely than non-holders to agree that if

it wasn't for the convenience aspect of credit, they

wouldn't use it.

8. Holders tend to be higher on the religious affiliatio n

scale than non-holders (more "liberal").

9. Holders tend to be better educated (at least through high

school), come from a household where the husband is salaried

rather than hourly-paid, and where the husband is in one of

the traditional "white-collar" occupation, in comparison

with non-holders. 206

Summary. The cross-tabulation analysis indicated that credit

card holders in general tended to engage in traditionally "upscale"

(upper-middle class and above) leisure-time activities such as attend­

ing concerts and plays, playing golf and tennis, job-related reading or study, and for-pleasure book reading. They also tended to be better educated, have a "white-collar" job (or have a husband with such a job), have an "upscale" total household income. There was some tendency for BankAmericard holders to be older and have a some­ what lower total household income than Master Charge holders.

Female holders of "other department store credit cards" tended

to be better educated and have higher total household incomes than

female holders of Sear's, Penney's or Ward's credit cards. The

results for male holders were inconclusive.

There appeared to be two patterns of use of credit during 1972.

One pattern included all the (significant) leisure-time oriented uses, and the other pattern included none of these uses. The latter pattern seemed to stress traditional "utilitarian" uses of credit.

The only apparent demographic differences between these two groups was that the leisure-time oriented use group tended to be more up­ scale on total household income, and the male tended to be an executive at his place of employment.

Finally, the leisure-time oriented use group, in comparison to the "utilitarian" group, tended to read one or more of the three major newsweeklies, Changing Times, Consumer's Reports, National

Geographies, Family C ircle, Woman's Day, Better Homes and Gardens, and Ladies Home Journal. 207

It was noted that, basically, if the respondent would con­ sider the use of long-term credit for one purpose, he or she would consider it for all purposes listed, with the exception of "taking a vacation trip." In general, females were less willing than males to consider using long-term credit for any of the purposes listed.

Only two major relationships were found between uses of credit during 1972 and acceptable uses of long-term credit. Leisure-time airline travel in 1972 was related to using long-term credit for a vacation trip . Using credit to buy sporting equipment in 1972 was associated with using long-term credit to buy a recreational vehicle, tra ile r or boat. This la tte r usage of long-term credit was the most acceptable leisure-time oriented use of long-term credit to either sex, and, at that, acceptable to less than 30 percent of the respondents.

It was found that approximately 6 percent more of the respon­ dents hold Master Charge cards than BankAmericard. Males who have an American Express card tend to have several other cards as well.

Both males and females indicated that use of credit for the pur­ chase of outdoor clothing and for gas/oil/parts for the car while on a vacation were the two most prevalent uses of credit during 1972.

The groupings of credit-oriented and related variables found through factor analysis, for both holders and non-holders of credit cards of each sex, accounted for only 36 percent of the variance in the best case (male non-holders). Both male holders and non-holders had a greater proportion of their total data variance 208 accounted for by the extracted factors than did the females. Only those factors accounting for approximately 5 percent of the variance apiece were extracted.

Female holders fell into three groups, based on the analysis,

(1) a younger, income-optimistic, more educated, higher occupational level group who would use long-term credit for purchase of tangible assets or an education, (2) a heavy-user, leisure-time use oriented group, and (3) a younger, financially insecure group concerned about their level of indebtedness.

Female non-holders fell into four groups, based on the analysis,

(1) an older group, pessimistic about their future income increases who feel using credit is. a bad practice, (2) a financially insecure group concerned about their level of family indebtedness, (3) a non­ credit related "strongly" religious group, and (4) a group who would consider the use of long-term credit for "practical," purposes, b ill paying or for an education as acceptable.

Male holders fell into four groups, based on the analysis,

(1) a younger, income-optimistic group concerned about family debt who would use long-term credit to pay bills, develop tangible assets or pay for an education, (2) a higher income, better educated, higher occupational level/position in company group who used credit for leisure-time oriented uses in 1972, (3) a group of heavy users of credit cards who only "see" the advantages of cards and feel that all of them (as listed) are important to them, and (4) a group of multiple card holders who do not feel that the negative aspects of cards (as listed) are important to them. Male non-holders fell into six groups, based on the analysis,

0 ) a younger, income-optimistic group interested in using long­ term credit for asset development who tend to be more liberal in their religious beliefs, (2) a "strongly" religious oriented group who feel credit cards are a "temptation," (3) a group who would con­ sider using long-term credit for a variety of "traditionally accep­ table" purposes (pay b ills , get an education, develop assets), (4) a somewhat lesser educated, larger family, financially insecure group concerned about their level of family indebtedness, (5) a heavy user,

"blue-collar" group, and (6) an urban, better educated, gracious living group not adverse to using long-term credit for financing a vacation.

Finally, holders and non-holders of credit cards were found to differ on several variables based on the mean response to the variable. Holders tended to have a higher income, be better edu­ cated, be more religiously lib eral, come from a household where the male is a salaried, "white collar" worker, and feel more favorably disposed toward credit cards and their use. Holders also value the convenience aspect of credit cards.

Conclusions. There do appear to be different patterns in the use of, and feelings toward, credit for leisure-time products and pursuits by different groups of people. In general, in comparison with non-holders of credit cards, holders tend to be younger, better educated, higher income, and possibly more liberal in their religious views. They tend to read what might commonly be labeled as the "upscale" (socioeconomic scale) magazines and engage in

"upscale" leisure-time pursuits. 210

Other conclusions can be enumerated as follows:

1. Actual acceptable uses of credit for leisure-time

oriented products and pursuits, however, were not

nearly as numerous as uses for "serious" purposes.

2. The two most common bank-affiliated cards appear to

have slightly different segments of the card holding

market.

3. There is a substantial segment of the respondents who

are concerned about family finances and indebtedness

irrespective of whether credit cards are held or not.

4. The religious-oriented AIO statements, in general, do

not relate to the credit-oriented variables; nor do •

the credit card characteristics statements of question

1c relate to very many other variables outside this

group. To a lesser extent, the potential purposes

for using long-term credit also tend to cluster

more closely to each other than to other variables.

5. These three sets of variables (religious AIO's, credit

card characteristics, and user of long-term credit)

do not appear to be overly discriminative, based on the

analyses conducted.

Hypothesis H^, as stated, is therefore tentatively rejected based on the results of this particular study. Both the (statisti­ cal) significance level selected in the cross-tabulation analysis, and the level of loadings on the factors represent "significant" differences. 211

Analysis of Hypothesis H 5

Hypothesis Hg, in null form, stated:

There are no distinct media preference patterns associated with each distinct cluster of leisure- time pursuits.

The underlying question of this hypothesis is whether or not

groups of respondents prefer television program-types or read

magazines which are related to their leisure-time pursuits. Stating

the question in another manner, "Are there specific groups or

clusters of media which are related to certain other specific

groups of leisure-time pursuits?"

Two levels of "interest" in particular leisure-time pursuits

are utilized in this analysis; ( 1 ) those pursuits engaged in during

1972, and (2) those pursuits which the respondent indicates are his

or her favorites.

The data analyzed here come from questions 4.B., 5.a., 12, and

31 of the questionnaire (in Appendix A). Only those magazines read

by at least twenty-four females or twenty-one male respondents were

used.

Table 32 lists all the most-popular favorite leisure-time

pursuits for both sexes which had correlations with either maga­

zines or television program-types of greater than +0.40. Again,

"most popular" refers to those leisure-time pursuits listed as favo­

rites by at least 5 percent of the sample. A number of these

pursuits did not show any correlation greater than +0.40 with any

of the media listed in the questionnaire. 212

Tables 33 (females) and 35 (males) present the groupings of most popular favorite leisure-time pursuits and the most popular magazines resulting from a factor analysis of these variables.

Tables 34 (females) and 36 (males) present the groupings of most popular favorite leisure-time pursuits and all eighteen television program-types listed in question 31.

Analysis Approach. The analysis approach followed here invol­ ved two steps. The first was to cross-tabulate favorite activities with themselves, with selected demographic variables (per Table 26), with magazines, and with television program-types. Magazines and television program-types were also cross-tabulated with themselves.

These cross-tabulations,as in H^, provided some indication of patterning within specific sub-groups of variables. This, in turn, provides a descriptive framework valuable in interpreting subsequent factor analysis.

The second step involved correlating the most favorite leisure­ time pursuits with both magazines and television program-types.

These correlation matrices were then factor-analyzed (principal components/Varimax rotation) to determine i f there were any rela­ tively strong groupings or patternings of pursuits and media together, i.e., if they were strongly related in multi-dimensional conceptual space. The same criteria for terminating a factor analysis was followed here as in earlier hypotheses testing. 213

Results of Cross-Tabulation Analysis. While many thousands of cross-tabulations were reviewed, only those with a chi-square value significant at the .005 level or greater will be included in the following discussion. It should not be inferred from this that, in specific situations, cross-tabs with somewhat less significant chi-squares might not be "managerially significant." It was felt, however, that, for discussion purposes, the more significant chi- squares are more reliable indicators of "statistical dependence"

(lack of sta tistic a l independence) among the two variables.

1.-Cross-Tabulations of Favorite Pursuits versus Favorite

Pursuits. Among the females, it was found that picnicking was associated with fishing and hunting, and inversely associated with creative crafts and reading a book for pleasure. Creative crafts and attending movies were also inversely associated. Reading the

Bible and church-related activities Were associated. In general, including some of the less-significant cross-tabs, it was found that creative crafts was inversely associated with outdoor pursuits.

Among the males, it was found that fishing/hunting was associated with both forms of camping and inversely associated with golf, driving for pleasure, listening to music, reading a book for pleasure, and visiting with friends/partying. Gardening/!avm care was associated with fixing up the house and inversely associated with playing basketball/football/baseball/etc. Fishing/hunting seemed to be the most distinguishing pursuit here, as creative crafts was for the females. 214

'' 2.-Cross-Tabul ations of Favorite Pursuits' versus Demographics.

The only significant (.005 level) associations among the female respondents were that concerts/plays and reading a book for pleasure were both associated with higher education and total household in­ come levels. Reading a book for pleasure was also associated with higher age level and higher occupational positions of the husband.

Horseback riding and attending movies were both associated with younger age groups.

The male respondents' data showed that fishing/hunting was associated with a less urban geographical location, and a lower occupational level. Auto modification/tune-ups was also associated with lower occupational levels. Golf, on the other hand, was asso­ ciated with higher occupational levels. Not surprisingly, playing basketball/football/baseball, etc. was associated with the younger age groups, while bingo/bridge and similar card games, and gardening/ lawn care was associated with the older age brackets.

3.-Cross-Tabulations of Favorite Pursuits versus Magazines.

The data from the females indicated that gardening/lawn care and reading Organic Gardening and Farming were associated. Creative crafts was associated with reading McCall's Needlework and Crafts,

Woman's Day and Workbasket. Reading House Beautiful and listening to music from records/tapes/radio were associated, as were reading a book for pleasure and reading Good Housekeeping and Newsweek. An interesting relationship (at better than the .0010 level) was found between reading the Bible as a favorite leisure-time pursuit and reading True Stor.v magazine. 215

Among the males, preferring fishing/hunting as a leisure­

time activity was associated with reading American Rifleman, Field

and Stream, Outdoor Life, Sports Afield, and not reading Time.

Golfing and reading Golf Digest and Sports Illustrated were asso­

ciated. Performing auto modifications/tune-ups appeared to go along with reading Car and Driver, Hot Rod Magazine, Machanix Illustrated and Motor Trend. Finally, the following two pairs of relationships were statistically significant at better than the .001 level, (1) driving for pleasure and reading Family Circle and (2) playing with children and reading Parade.

4 .-Cross-Tabulations of Magazines versus Magazines. There were

1764 cross-tabs of magazines for the female respondents, and 1296 for the male respondents. Of these, there were over 150 associations significant at the .005 level for the females and over 100 for the males. Readership of essentially each magazine was apparently associated with readership of many other magazines on the l i s t . In actuality, the significant cross-tabs in many situations resulted from non-readership of magazine A being associated with non-readership of magazine B. These particular cross-tabs then turned out to be sig­ nificant because of the overwhelming number of cases in the (0, 0) cell combined with the few cases in the (1, 1) cell, resulting in a total value of that diagonal far exceeding the value of the other (0, 1)-

(1, 0) diagonal. The reliability of these cross-tabulations is therefore questioned. 216

‘ ' 5:-^Cross-Tabu!atioris of Maqazities' versus ‘Demoqrarihics. The four demographic variables most frequently associated with female magazine readership were, (1) education, (2) age, (3) total house­ hold income, and (4) population density/degree of urbanization. The following are the associations with the greatest (statistical) likelihood of occurrence:

1. Ladies Home Journal with higher levels of education and

total household income.

2. Modern Romances with lower total household income and

degree of urbanization (more likely to be in smaller city

or town).

3. National Geographic with higher levels of age and total

household income.

4. Parent's Magazine with one or two children in the family

and younger age levels.

5. Playboy with older age levels.

6. Reader's Digest with older age level.

7. Time with higher levels of education, male occupation,

total household income and degree of urbanization.

8. True Story with lower levels of education, total household

income and degree of urbanization.

9* TV Guide with the 25-44 age bracket.

10. U.S. News and World Report with higher levels of education.

11. Workbasket with lower levels of education.

I t may be noted that Newsweek showed the same pattern of associations as Tims but at a lower level of statistic a l significance. 217

The male respondents showed fewer associations at the level of significance chosen for this discussion (.005). The pattern of associations was also different in that very few magazines, in contrast with the females, showed an association with total house­ hold income. There were also a few more significant associations between magazines and male occupation and male position in company.

The following are the associations with the greatest statis­ tical likelihood of occurrence among the male respondents.

1. Better Homes and Gardens with older age brackets.

2. Business Week with higher occupational levels.

3. Playboy with lower age levels and an employed female

head of household.

4. Reader's Digest with older age brackets and smaller house­

hold sizes.

5. Time with higher levels of education, male occupation,

male position in company, and total household income.

6i U. S: News and World Report with higher levels of education,

male position in company, and a tendency toward higher age

brackets (although this association did not reach even the

.01 level).

It may be noted that Newsweek did not have any association reaching the discussion level, but did show lesser associations with higher education, age and occupation levels. 218

6.-Cross-Tabulations of Favorite Pursuits versus TV Program-

Type s:. There were not very many significant associations between favorite pursuits and TV program-types for either the females or the males. The females showed associations between attending con­ certs or plays and watching plays or concerts on television, and between fishing/hunting and watching sports on television. Religious television programs were associated with church-related activities and reading the Bible. Finally, reading a book for pleasure was significantly associated with watching plays on television.

Among the males, watching plays on television was associated with reading a book for pleasure arid inversely associated with fishing/hunting. Playing pool, billiards, table tennis and watching

"horror" movies were associated, as were listening to music from records/tapes/radio and watching concerts on television.

7.-Cross-Tabulations of TV Program-T.ypes versus TV Program-

T.ypes. As in the case of the magazines, there were a great many significant associations between TV program types. In this case, however, the (1, 1) cell (watch both types) was the most populated rather than the (0, 0) cell (watch neither type). The implication may be that of a lack of discrimination on the part of many viewers, at least in comparison with magazines.

The least discriminating program-types among the males were

(1) "variety" shows which had significant associations with comedies, musicals, sports, quiz shows, plays, and talk-shows, and (2) "edu­ cational" programs which had significant associations with musicals, religious programs, plays, concerts, regular news programs, 219 and documentaries.. Several interesting smaller groups were noted, for instance religious programs were associated with both educational programs and romance stories, and inversely associated with "horror" movies. Real life dramas were associated with plays and documen­ taries. Westerns, detective shows, and mystery/suspense shows were all associated, but only mystery/suspense shows were associated with any other type--"horror" movies.

The female respondents showed both slightly different patterns and distinctly larger groups of associations. The two least dis­ criminating program-types among the females were (1) Plays, which associated with musicals, variety shows, concerts, talk-shows, dramas, news programs, documentaries and educational programs, (2) musicals which associated with comedy, religious, variety, plays, concerts, news programs, documentaries and educational shows. At the other extreme, "horror" movies only showed associations with detective and mystery/suspense shows. Mystery/suspense shows had an inverse association with religious programs. Religious programs were asso­ ciated with westerns, musicals, quiz shows, concerts and educational programs.

8 .-Cross-Tabulations of TV Proqram-Types versus Demographics.

Only age, education and, to a lesser extent, male occupation were involved in the significant (.005 level or greater) cross-tabs of program-types versus demographics for the male respondents. Wes­ terns were associated with lower levels of education, while concerts and documentaries were associated with higher levels of education. 220.

Documentaries also were associated with higher levels of occupation.

All of the remaining significant associations were with older age brackets, and these were with (1) musicals, (2) religious programs,

(3) plays, (4) "horror" movies, (5) news programs, (6) documentaries,

(7) mystery/suspense shows, and (8) educational programs.

The significant cross-tabs of the female respondents' data were more varied. The following are the associations with the greatest statistical likelihood of occurrence among the females:

1. Detective shows with younger age groups.

2. Musicals with higher positions of male within company,

total household income and age levels.

3. Religious programs with lower levels of education arid

older age brackets.

4. Sports with higher positions of male within company.

5. Plays with higher male occupational levels and older age

brackets.

6. "Horror" movies and mystery/suspense shows with younger

age brackets.

7. Concerts with higher male occupational and company posi­

tion levels, and older age brackets.

8. Both regular news programs and documentaries with older

age brackets; documentaries also with higher education

levels.

9. Romance or love stories with younger age brackets. 221

Analysis of Table 32. Table 32 presents the correlations between favorite leisure-time pursuits and (1) magazines, and (2) television program-types that exceeded +0.40. These correlations are tetradoric correlations; therefore, an exact test of statis­ tical significance is not possible. This discussion will be limited since these relationships agree in many cases with the results of the cross-tabulations.

In most cases, there is "face validity" in the relation­ ships listed. Sporting-oriented magazines are correlated with sporting activities, for example, as are craft-oriented magazines with crafts, religious television programs with church-related activities, and so on.

Several interesting, perhaps less "obvious" relationships, are those of U. S. News and World Report with writing letters/doing crosswords, which in turn is correlated with several "romance" magazines. It may be that this double activity is including two different sets of respondents.

Among the male data correlations, two groups of correlations are particularly interesting. One is that correlation between

Penthouse and Golf Digest and attending movies. It may be that more than one type of movie-goer is included in this group. The second relationship is that between Esquire, Car and Driver and the pursuit playing pool, billiards, table tennis. The factor here may be whether one engages in this pursuit at home or in a public establish­ ment. 222

Table 32

Summary of Positive Correlation Greater than +0.40 Between the Most Popular Favorite Leisure-Time Pursuits and Magazines/TV Show-Typesa (Male and Female Respondents)

Female Respondents

Leisure-Time Correlated Greater than Pursuit*3 +0;40 with . I .c

Attend Concerts, Plays (44)^ ' Changing Times (41)e ' Weight Watchers Maqazine (25) Plays (337)e Concerts (237)

Fishing or Hunting (51) Sports (241)

Horseback Riding (35) ’ Field and Stream (28) Hairdo and Beauty (23) ' Sports Illustrated (19)

Swimming (70) Sports Illustrated (19)

Attend Movies (44) Mystery/Suspense Shows (449)

Bingo, Bridge, other similar card games(76) Sports Illustrated (19)

Church-related activities (43) Religious Programs (261)

Gardening, lawn care, etc. (65) Organic Gardening and Farming (24)

Creative crafts (255) McCall's Needlework and Crafts (80)

Listen to music from records, tapes, Glamour (41) radio (54) ' House Beautiful (48)

Read Bible (33) Religious Programs (261)

Visit with friends, partying (92) Holiday (21) Parade (33)

Write letters, do crosswords (34) Hairdo and Beauty (23) Modern Romances (33) True Story (44) H• S. News arid World Report (27) 223

Table 32 (Continued)

Male Respondents

Leisure-Time Correlated Greater than Pursuit______+0;40 w ith '; . .

Camping by tra ile r (51) Westerns (402)

Camping by tent (30) ' Outdoor Life (48) Sports Afield (48)

Fishing or Hunting (192) Arcerican Rifleman (36) Fie! d and' Stream"" (99) ' ' Outdoor Life (48) ' Sports Afield (48)

Golf (44) Golf Digest (18) Sports Illustrated (62) Sports (404)

Picnicking (32) Variety Shows (302)

Attend movies (34) Golf Digest (18) 'Penthouse (33)

Attend sporting events (54) Sports II1 us trated (62) Sports (404)

Auto modifications, tune-ups (28) Car and Driver (30) Hot Rod Magazine (35) Mechanix Illustrated (71) Motor Tre~nd (33) Popular Mechanics (94)

Play basketball, football, baseball, Sports Illustrated (62) etc. (45) Comedy Shows (407) Sports (404) Mystery/Suspense shows (379)

Bingo, bridge, other similar Lady's Home Journal (27) card games (35) ' McCall's Magazine (21)

Fix up house, remodeling, etc. (42) Detective shows (426)

Gardening, lawn care, etc. (71) ' Lady1s'HOme'Journal (27) ' Organic Gardening and Farming (21) 224 Table 32 (Continued)

Leisure-Time Correlated Greater than Pursuit •HK40 with

Pool, billiards, table tennis (34) Car and Driver (30) Esquire (24) Detective shows (426) Horror movies (204)

Drive for pleasure (49) Family Circle (39) Good Housekeeping (26) Regular Nev/s Programs (410)

Listen to music from records, tapes, radio Concerts (131) radio (60) Play with children (26) Parade (21)

Read a book for pleasure (47) Good Housekeeping (26) Lady's Home Journal (27) ’ McCall's Magazine- (21) ' Time (91) Plays (175) Regular News Programs (410)

Visit bar or club (28) Mystery/Suspense shows(379)

Visit with friends, partying (49) Parade (21)

Notes:

aThose magazines from question 12 which were read by at least 24 females or by at least 21 males were included in the correlation matrix. All 18 TV show-types were included.

Paraphrased favorite leisure-time pursuit. Refer to Table 15 and pages 5-7 of the questionnaire for detailed "description." Those favor­ ite pursuits (ppr table 15) not listed here did not have any media cor­ relations greater than 0.40.

cMagazines are underlined, TV show-types are not.

Plumber in parentheses is the number of respondents identifying the pur­ suit as a favorite one, or, in the case of the magazines, the number reading regularly the magazine.

eThe number in parentheses is the number of respondents who indicated they "liked" that particular type of television program. 225

Analysis of Table 33. Table 33 presents the results of the

factor analysis of the most favorite leisure-time pursuits and "most popular" magazines of the female respondents.5 The pursuits are

underlined in this table. It can be seen that, with the exception of the first group of essentially all magazines, pursuits and maga­ zines do tend to cluster together—albeit in bipolar groupings.

These groups (factors) individually account for a fairly sig­ nificant amount (6 percent or more) of the variance in the data.

Collectively, they account for 80 percent of the variance in the data.

Group 1 represents a group of magazines not associated with respondents who indicated that playing with children was a favorite activity. Most of these magazines appear to be in what is sometimes called the "home and shelter" category. There may also be a ten­ dency for these magazines to have an "upscale" orientation, socio­ economically. This is substantiated by the cross-tabulations in those cases where the cross-tabs were "significant" (as defined).

Group 2 seems to represent a bipolar group with religious interests and around-the-home interests at one pole, and more cosmo­ polite interests at the other extreme. The underlying dimension here ( if there is a single dimension) may be socioeconomic (possibly a combination of education and income) in nature.

Group 3 appears to represent a beauty/romance conscious group a t one end of the continuum, and perhaps a conservative, church- oriented group at the other. The underlying dimension here is unclear.

5"Most popular" refers to being read regularly by twenty-four or more respondents. Table 33

Groupings (Factors) of the Most Popular Favorite Leisure-Time Pursuits and Most Popular Magazines9 (Female Respondents)

i; (15.1%)b House and Garden (.842)c Flower and Garden Magazine (.838) House Beautiful (.836) Holiday (.776) Better Homes and Gardens (.726) American Home (.685) Consumer's Reports (.588) Forbes (.564) Organic Gardening and Farming (.554) Cosmopolitan (.545) National Geographic (.531) 1001/Decorating Ideas (.528) Good Houskeeeping (.519) Lady's Home Journal (.510) Woman's Day (.483) Hairdo and Beauty (.478) Family Circle (.476) McCall's Magazine (.449) Lady's Circle (.433) Play with Children (-.431)

2. (9.9%) Read Bible (.846) Church-related activities (.734) Gardening, fawn-care (.645) Organic Gardening and Farming (.419) The Workbasket (.411) Camping by tra ile r (.380) ' Read a book for pleasure (-.420) Changing Times (-.422) Newsweek (-.431) Glamour (-.458) Cosmopolitan (-.508) Holiday (-.518) ...... ' Wrlte 1etterS , do crosswords (-.566) ' Attend concerts and plays (-.638) Playboy (-.639) Sports Illustrated (-.630) Table 33 (Continued) 227

3 . (9 .7 % )

Hairdo and Beauty (.885) True Story (.875) Modern Romances (.848) Parent's Magazine (.670) ...... Write L etters, Do Crosswords (.638) TV Guide (,488)- Horseback Riding (.413) Church-Related Activities (-.462) Read Bible (-.469) Changing Times (-.689)

' 4: (8:9%) Sports Illustrated (.838) Horseback Riding (.786) Swimming (.714) Glamour (.438) Write 1e tte r s „ do crosswords (-.565) Holiday (-.606) 'Col 1ecting Coins, etc. (-.995)

’ 5: (8:4%) Fishing or hunting (.995) Picnicking (.850) Organic Gardening and Farming (.719) Attend movies (-.434) Church-related activities (-.560) Hairdo and Beauty (-.560) Seventeen (-.874)

6 . (7.8%) Play with children (.738) Listen to music (7554) Glamour (.520)” Read Bible (.424) Swimming T- .409) Sunset (-.817) Parade (-.995)

7. (7 2%) Play with children (.673) Driving around foT pleasure (.580) McCall' s Needlework (.547) Creative Crafts (.521) Simplicity Fashion Magazine (.476) Family Circle (.437) Popular Mechanics (.433) Attend movies ( - . 666)...... Attend concerts and plays (-.690) 228 Table 33 (Continued)

8 ; (7;i%) Weight Watchers Magazine (.995) Play with children (.484) Sports Illustrated (-.538) U. S. News and World Report (-.539) Popular Mechanics (-.563) Field and Stream (-.873)

■ 9; (6:3%) Sunset Magazine (.607) U. S. News and World Report (.434) 'V isit'w ith friends (.391) Organic gardening and farming (-.458) Gardening> lawn card (-.495) Southern Living (-.995)

Notes:

aThe 20 pursuits which at least 5 percent of the respondents listed as a "favorite" were used. The 42 magazines which had a readership of at least 24'respondents were used. Leisure-time pursuits are underlined) magazines are not.

^Percentage of the variance in the data accounted for by the total Varimax rotated factor.

cLoading of the variable on the factor. A negative loading implies that respondents do not read that magazine or do not consider that pursuit a "favorite" one i f they do_read the other magazines loading on the factor and do engage in the other pursuits loading on the factor. Factors were derived from a tetradoric correlation matrix. 229

Group 4 may have an (moderately) active/passive orientation in the two sub-groups evident. It may also be an indoor-older/ outdoor-younger orientation.

Group 5 seems to have an indoor-younger/outdoor-older orien­ tation. Both these orientations of group 4 and group 5 are supported by those cross-tabs which reached significance.

Group 6 may also have an indoor/outdoor orientation, perhaps again combined with a younger/older grouping. The cross-tabs indicated that G1amour was read more by younger women and Sunset more by the older respondents.

Group 7 seems to be a passive/home-centered crafts versus passive/outside-the-home orientation. There may also be a manual - dexterity pleasure versus cerebral or mental-challenge orientation here.

Group 8 may be an outdoor-active versus indoor-active orien­ tation. Since it is composed of primarily magazines, there may also be an underlying search for knowledge dimension.

Finally, group 9 appears to have a group-centered versus individual-centered orientation. This might be described as "other- directed" versus "inner-directed" in David Reisman's terms

(Reisman, 1961).

Analysis of Table 34. Table 34 presents the results of the groupings of favorite leisure-time pursuits and television program

(or show)-types for the females. All the groupings (factors) together account for 67 percent of the variance in the data; 230

Table 34

Groupings (Factors) of the Most Popular Favorite Lei sure-Ti line Pursui ts and TV Show-Typesa (Female Respondents)

,; i;(n:4%) Plays (.747)° Documentaries (.730) Concerts (.705) Attend Concerts and Plays (.678) Educational Programs (.613) Regular News Programs (.595) Musicals (.557) Talk-Shows and Interviews (.528)

' ' 2. (9:9%) Horseback Riding (.692) Mystery/Suspense Shows (.642) Attend Concerts arid ^ PI ays (.593) Horror Movies (.517) Religious Programs (-.534) Read Bible (-.673) Church-Related Activities (-.995)

3; (8 .6%) Driving Around for pleasure (.882) Fishing or hunting (.591) Play with children (.576) Attend concerts and plays (-.473) Attend movies (-.949)

4. (8.1%) Fishing or hunting (.871) Attend concerts or plays (.674) Picnicking (.641) Camping b,y tra ile r (.413) Attend Movies (-7478) Listen to Music (-.481)

...... -5. (7.9%) PI ay yi/i th Ch i 1 dren (.740) Swimming (.529) Horseback Riding (.477) Bowling (-.466) Col1ecting Coins, etc. (-.995) Table 34 (Continued)

6 . (7:4%) Detective shows (.614) Quiz/Panel shows (.581) Comedy Shows (.569) Romance or Love Stories (.549) Variety Shows (.526) Mystery or Suspense Shows (.411) Real Life Dramas (.409) Westerns (.403)

7; (7;3%) Gardening, lawn care (.761) Read Bible (.445)~ Church-related activities (.360) Writing 1 ette rs , doing crosswords (-.995)

81 ( 6 .8 %) Read Bible (.718) Listen to music from records, tapes, radio (.672) Bingo, bridge and similar card games (.380) Gardening, lawn care (-.500) Swimming (-.819)

Notes:

aThe 20 pursuits which at least 5 percent of the respondents listed as a "favorite" were used. All 18 TV show-types (from question 31) were used. Leisure-time pursuits are under!ined, TV show-types are not.

^Percentage of the variance in the data accounted for by the total Varimax rotated factor.

cLoading of the variable on the factor. A negative loading implies that respondents do not like that TV show-type or do not consider that pursuit a "favorite" one if they jto like the other TV show*- types loading on the factor and do engage in the other pursuits loading on the factor. Factors were derived from a tetradoric correlation matrix. 232

In summary:

1. Group 1 appears to have an "upscale" orientation,

socioeconomically. This is borne out by the cross­

tabulations.

2. Group 2 seems to be religious interests versus non­

interest in religious oriented activities.

3. Group 3 appears to be an indoor/outdoor orientation.

4. Group 4 appears to have more of a socioeconomic scaling

underlying it, rather than just indoor versus outdoor.

5. Group 5 again seems to have an indoor-passive versus

outdoor-active orientation.

It is interesting to note that groups 3 through 5 (and also groups 7 and 8 , yet to be discussed) do not contain any TV program- types. This implies that the pursuits, as grouped, are not strongly related to preferred television program-types. Whether this implies a relative lack of interest in television programming among people strongly interested in these pursuits is open to speculation.

Group 6 may represent the heavy television viewer whose favo­ rite leisure-time activity may, in fact, be watching TV. None of the listed leisure-time pursuits are apparently close (in multidimensional conceptual space) to this group of television program-types.

Groups 7 and 8 seem to represent relatively small clusters of pursuits in which reading the Bible is contrasted with several other pursuits. It is interesting that reading the Bible and gardening/lawn care are related in one group and contrasted in the other. This would imply that gardening/lawn care is perhaps a 233 favorite pursuit for different types of people, i.e. is multi-­ faceted in the bundles of satisfactions it brings to the participants.

Analysis of Table 35. This table, for the males, represents the same type of groupings as Table 33 for the females. All of the groups (factors) together account for 87 percent of the variance in the data. "Most popular" magazines for the males refers to those read by at least twenty-one respondents.

Group 1 seems to be a bipolar group, with the (rugged) out- doorsman at one end and the (perhaps) more sedate, indoor oriented male at the other end.

Group 2 appears to have a socioeconomic bipolarity to it.

Those magazines which tend to be read by "upscale" respondents are contrasted with pursuits and magazines which tend to be read by respondents "downscale" socioeconomically (education, occupational level, total household income). The cross-tabulations which reach significance (as defined) tend to bear this out.

Group 3 seems to contrast those males interested in tradi­ tionally female-oriented magazines with those who perhaps are less interested in magazines in general.

Group 4 seems to contrast those "upscale," perhaps more cosmpolite males with males interested in pursuits involving manual dexteri ty .

Group 5 appears to represent a younger, perhaps "pin-up" oriented, active sports group with an older, more sedate, passive pursuit group of male. 234

Table 35

Groupings (Factors) of the Most Popular Favorite Leisure-Time Pursuits and Most Popular Magazines3 (M aleRespondents)

1. (14.6%)b Outdoor Life (.993)c Sports Afield (.948) American Rifleman (.939) Field and Stream (.795) Sport (.754) Motor Trend (.665) True (.634) Popular Mechanics (.601) Argosy (.588) Mechanix Illustrated (.581) Popular Science Monthly (.539) Fishing or Hunting (.484) Sports Illustrated (.432) Camping by Tent (.428) Golf (-.400') Play with Children (-.572) The Workbasket (-.763)

2. (12.7%) U. S. News and World Report (.849) Changing Times (.739) Business Week (.710) Time (.650) Newsweek (.647) Consumer's Reports(.620) National Geographic (.594) Reader's Digest (.551) Better Homes and Gardens (.528) Pool» billiards, table tennis (-.408) Visit bar or club (-.435) Hot Rod Magazine (-.506) Auto Modif•ications, tune-ups (-.516) The Workbasket (-.847) 235

Table 35 (Continued)

3. ( IK 8 %) Good Housekeeping (.995) Lady's Home Journal (.995) Family Circle (.805) McCall's Magazine (.795) Better Homes and Gardens (.587) American Legion (.514) Driving for pleasure (.435) ’ 'Picnicking (».490) Pool, billiards, table tennis (-.615) ' Play with children (-.743)

4: (11:5%) Golf Digest (.995) Golf (.955) Esquire..(.585) Swimming..(.,47.3) ...... Bingo, bridge, similar card games (.451) sports ,il Justr.ated..(..408) Fix up .house,./.remodelling (-.445) • • Campi ng. by. . te n t . (.*•. ..541.) ...... Auto modifications, tune-uos (-.593) ^Iay with children (-.597) Organic Gardening and Farming (-.749)

5. (10.7%) Penthouse (.928) Car and Driver (.820) Hot Rod Magazine (.732) Playboy (.631) Motor Trend (.548) Playing basketball, football, baseball, etc. (.527) Esquire (.474) Gardening, lawn care (-.431) The Workbasket (-.653) ’ Bingo, bridge, and other similar card games (-.995) \ 236 Table 35 (Continued)

...... 6 . (9.1%) Picnicking (.912) Popular Science Monthly (.591) Camping by tra ile r (.489) Good Housekeeping (.456) Power boatirig, water skiing (.427) Fishing or Hunting (.400) Sport (".513) ...... ' Listen' to rhus 1 c from records, ‘ tapes; radio (-.604) Visit with friends, partying (-.849) Visit bar or club (-.896)

...... 7 . - ( 8 :6%) Auto modification, tune-ups (.771) Hot Rod Magazine (.594) Play with children (.565) Car and Driver (.507) McCall's Magazine (.468) Visit bar or club (.452) Pool, billiards, table^tennis (.400) Camping by tent (-.651) “Photography, taking pictures (-.995)

8 . (7.6%) Parade (.943) Argosy (.610) Swimming (.610) True (.510) Auto modification, tune-ups (-.478) Attend sporting events (-.904)

Notes: aThe 24 pursuits which at least 5 percent of the respondents listed as a "favorite" were used. The 36 magazines which had a "readership" of at least 21 respondents were used. Leisure-time pursuits are underlined, magazines are not.

^Percentage of the variance in the data accounted for by the total Varimax rotated factor.

cLoading of the variable on the factor. A negative loading implies that respondents do not read that magazine or do not consider that pursuit a "favorite" one if they cto read the other magazines loading on the factor and do engage in the other pursuits loading on the factor. Factors were derived from a tetradoric correlation matrix. 237

Group 6 may have an underlying orientation of interest in the outdoors and things mechanical versus an indoor, individual--or group—centered set of in terests.

Group 7 seems to contrast an interest in automobiles with roughing i t in the outdoors and photography. This may include scenic/wildlife photography.

The orientation of group 8 is unclear. Overall, there is an interest in physical activity.

Analysis of Table 36. This table, for the males, indicates the same kinds of groupings as Table 34 for the females. All groups

(factors) together account for 56 percent of the variance in the data.

Group 1 appears to contrast the heavy TV viewer with those males who, perhaps, are less interested in television in general, or who only are interested in i t in a "background" context.

Group 2 seems to be an active/outdoor versus passive/indoor orientation. Westerns and detective shows are frequently outdoors oriented.

Group 3 would seem to represent a younger versus older orien­ tation (an age "dimension"). This is substantiated by the cross­ tabulations.

Group 4 appears to have an "upscale" versus "downscale" socioeconomic orientation to it. This partially borne out by the cross-tabulations.

Group 5 seems to have an outdoor, physical involvement versus an indoor, more vicarious involvement type of orientation. Table 36

Groupings (Factors) of the Most Popular Favorite Lei sure-Time Pursui ts and TV Show-Typesa (Maie Respondents)

1. <12.9%)b

Regular nefos programs (.678)c Plays (.665) Educational Programs (.657) Documentaries (.649) Musicals (.629) Variety shows (.605) Talk-shows or interviews (.584) Concerts (.506) Real-life dramas (.473) Sports programs (.473) Religious programs (.464) Comedy shows (.456) Quiz or panel shows (.445) Romance or love stories (.433) Visit bar or club (-.320) Camping.by tent (-.350) Pool, bi 1 l'iards, tab!e tennis (-.519)

2. (10.3%) Picnicking (.995) Fishing or Hunting (.490) Camping by tra ile 7 (.457) Swimming (.360) Westerns (.340) Detective shows (.320) Drive for pleasure (-.404) Read a book for pleasure (-.449) ^ is it a bar 'or club (-.485) Visit with friends (-.806) Listen to music from records, tape,~radio (-.817)

...... 3; :.(8.8iS).- ...... Play basketball, football, baseball> etc. (.947) Mystery or suspense shows (..513) Horror movies (.476) ...... ' ‘ .Pool ,., b illiard s, ..table tennis (.402) Bingo, bridge or similar card games (-.755) ' Gardening, lawn care (-.864] 239

Table 36 (Continued)

...... -4, (8,4%) ' Photography taking- pictures (.883) Read a-book for pleasure (7815) Spdrt$~programs (-.370) Visit bar or club (-.950)

...... 5. (8.1%) Camping .by tent (.995) Power boating, water skiing, scuba diVing (.518) Detective shows (-.360) ' Attend movies (r-,621) Pool, billiards, table tennis (-.837)

...... ■.■6...(7.5%)...... fix up the house, remodel1ing (.995) Woodwork!ng, metalworking, ' e tc . (.481) Gardening, lawn care (.38(7) Detective shows (.380) Westerns (.320) ' Attend movies (-.594) Picnicking (-.616)

Notes:

aThe 24 pursuits which at least 5 percent of the respondents listed as a "favorite" were used. All 18 TV show-types (from question 31) were used. Leisure-time pursuits are underlined, TV show-types are not.

^Percentage of the variance in the data accounted for by the total Varimax rotated factor.

cLoading of the variable on the factor. A negative loading implies that the respondents do not like that TV show-type or do not con­ sider that pursuit a "favorite" one if they do^ like the other TV show-types loading on the factor and do engage in the other pursuits loading on the factor. Factors were derived from a tetradoric correlation matrix. 240

Finally, group 6 would appear to have an around-the-home, manual dexterity, and direct involvement orientation, contrasted with a more passive, observer-of-the-scene focus.

Summary. Cross-tabulating favorite pursuits, magazines, TV program types and demographics showed both a number of strong asso­ ciations and a larger group of essentially no associations at all.

Religious oriented interests and activities were uniformly associated. This has held true in several analyses in this study.

Outdoor pursuits were separated from indoor pursuits, and

"rugged” outdoor pursuits (fishing/hunting/camping) from more docile or refined outdoor pursuits (golf, tennis). Pursuits involving man­ ual dexterity were generally distinguished from pursuits with a more cerebral, intellectual, mental-challenge orientation.

With regard to demographics, very active pursuits were typi­ cally associated with younger age groups and vice versa with more passive pursuits. Attending concerts or plays, reading a book for pleasure and playing golf were typically "upscale" pursuits soio- economically.

Magazines tended to associate with those pursuits with which one might expect association. Few associations seemed unusual.

One interesting association was between reading the Bible as a favo­ rite pursuit and reading the so-called "romance" magazines.

The cross-tabulations of magazines versus magazines were basically misleading due to the larger number of respondents reading neither of the two magazines involved.This would seem to be a func­ tion of the cross-tabulation algorithm involved. 241

Relating magazines to demographic again tended to result in

associations which might be expected based on general observations

and knowledge. There did not appear to be a clear-cut distinction

between the readership of the three major newsweeklies; except

insofar as Newsweek readership was apparently so diffused through­

out the demographic spectrum sampled that none of its associations with

these variables reached the .005 level of significance.

There were few associations of meaningful significance between

television program types and favorite pursuits. On the other hand,

there were many statistically significant associations among tele­

vision program-types. This leads to the implication of a general

lack of discrimination on the part of many of the respondents with

regard to th eir viewing patterns.

Documentaries, concerts and plays tended to be associated with higher education levels, while westerns were associated with lower educa­ tion levels. Age seemed to be the most discriminating variable for both males and females in defining their viewing preferences.

The factor analysis of the coirbined sets of variables—pur­ suits/magazine and pursuits/television program-types—resulted in a number of bipolar factors or groups. While it might be conceptually possible to label a single underlying dimension for these groups, this was not done because there is no evidence thus far that there is a single underlying dimension. Much of such interpretation of the groups as was attempted was supported, at least in part, by the earlier, descriptive cross-tabulations. 242

In many cases, the groups which evolved seem to have one or

more (in combination) of the following underlying orientations:

1. indoor-outdoor

2 . active—passive

3. younger—older (participants)

4. manual—mental

5. “roughness"—"refinement"

6 . individual—small group

7. socioeconomically "upscale" —"downscale"

8 . vicarious involvement--actual involvement

Both the factor analysis of pursuits/magazines and pursuits/

television showed significant groups (in terms of variance accounted

for) of only magazines or only television program-types. This could

be interpreted as that group of respondents whose favorite leisure­

time pursuit is either reading magazines or watching television. This

could also be interpreted as merely that those variables are more

closely related to each other, irrespective of any interest in

particular leisure-time pursuits.

Conclusions. A number of different orientations can be dis­

tinguished with regard to combinations of leisure-time pursuits,

magazines read regularly, and preferred television program-types.

These are noted above.

The results of the various analyses showed very few surprises

in terms of the relationships deemed significant. Those relationships which might be expected based on "common knowledge" and experiences

did in fact appear. 243

Demographic variables, particularly socioeconomic variables

and age, do seem to be a good basis for segmenting certain kinds of

pursuits and pursuit/media patterns. This was brought out particu­

larly in the cross-tabulations.

Because of low frequency counts, cross-tabulating magazines

versus magazines did not appear beneficial here. Non-readership was much more likely to be associated with non-readership than

readership with readership.

There is apparently a tendency for television viewers to be

relatively non-discriminating in th eir viewinq habits. This has

the implication that, in general, this media might not be an effi­

cient one to use in reaching participants in particular groups of

leisure-time pursuits. There may be some useful exceptions to this, however.

Hypothesis H 5 , as stated, is therefore tentatively rejected, based upon the results of this particular study. A conditional note is added that magazine preference patterns are more likely to be associated with leisure-time pursuit preference patterns than are television program-type preference patterns. 244

Additional Analyses

In addition to the preceding analyses specifically directed toward the various hypotheses, it was decided to continue the search for distinguishing characteristics between participants in various groups of pursuits by a different approach. This decision resulted from review of the results of the analysis thus far.

It becomes evident that the nature of the groupings of pur­ su its, media, and satisfactions was such that using cannonical correla­ tion to relate various groups would probably not result in meaningful comparisons and differentiations. On the other hand, multiple dis­ criminant analysis might profitably be applied to one group at a time

(versus "all others"), or to two or three distinguishable groups, to find those variables which best differentiated between the groups.

While differentiating between groups is not the same as relating them, this approach was believed to be a promising one in terms of making best use of the existing data to determine those variables which efficiently segment a particular dependent variable.

The objectives here, then, are several. They are:

1. Can discriminant analysis define distinguishing character­ istics of participants in different clusters of leisure-time pursuits?

2. Can discriminant analysis distinguish between these clusters in an efficient manner, i.e . correctly classify at least seventy percent of the members of each group with less than one- quarter of the available variables? 245

3. Given 1. and 2 ., do AIO statements, magazines, or demo­

graphic variables do a "better" job of discriminating between groups?

"Better" means that they are included in the "final" discriminant

function (at the 70 percent classification point).

4. Are the final discriminating variables the same as those

indicated by earlier analyses using other methods?

The variables selected for this analysis consisted of twenty- one leisure-time oriented AIO statements, ten demographic variables,

and a total of eighteen magazines. These are listed in Table 37.

Television program-types were not included because, as pointed out in the last section, they did not appear to differentiate particularly well between leisure-time pursuits. The reasons for this are not clear, and should be investigated further, as, intuitively, one might hypothesize that they would discriminate.

A total of forty variables (out of the 1100 variables on which data was collected) were used in each discriminant analysis for both females and males, the results of which are presented in Tables 38 and 39 respectively. This was the largest convenient number which could be utilized in a single analysis, given the computer routines in use. This analysis is essentially demonstrative in nature, and indicative of possibly fruitful future directions in analysis of this data. The results should not, therefore, in any sense be considered to be final or optimal.

Analysis Approach. Two groups of five lei sure-time pursuits

(engaged in during 1972) each were selected based on the highest intercorrelations among all the pursuits for a particular sex. In 246

both the male and female situations, these were the only two groups

of this size with "high" intercorrelations. "High" here refers to

0.30 or higher. There were particular intercorrelations within

each group which did not reach this level, but sixty percent or

more of the individual correlations in each group were 0.30 or greater.

Through computer programming, respondents were assigned to

one or the other of these two groups i f they engaged in at least

three (or more) of the five pursuits during 1972. If they did not

engage in any of the pursuits in either of the two categories, they

were placed in a third pseudo "control" group. Finally, all those

respondents who logically did not fall in any of these three groups

were placed in a fourth group consisting of those who participated in

zero, one, or two of the five pursuits during 1972.

Those independent variables that were selected were included

for one or more of several reasons. Magazines were selected which

had the highest likelihood of being associated with individual

pursuits in each group of pursuits defined (based on cross-tabula­

tions), and which did not have a high likelihood of association with

the pursuits in the other group. Demographic variables were included which had shown some discriminating power in other analyses.

Essentially all of the directly leisure-time oriented AIO

statements were included. Those that were not had a highly skewed

distribution of responses. Other AIO statements were included if 247 it was believed that they might be discriminating in the particular situation under analysis.

It is recognized that an upward bias can occur in the classi­ fication matrix when the same cases are classified as were used to calculate the discriminant function (Morrison, in Aaker, 1971:130)J

This is believed to be a minor problem here, given the demonstrative nature of this discussion.

Finally, two other points should be noted. First, pursuits engaged in during 1972 were used rather than favorite leisure-time pursuits because of the much smaller frequencies associated with favorite pursuits. Second, cross-tabulation analysis indicated that, as in the case of favorite pursuits, television program-types did not show many significant associations with pursuits engaged in during

1972. Therefore, these variables were not included in the analysis.

Analysis of Table 37. Table 37 lists all the variables used in the several discriminant analyses. It indicates which variables were used for the female analyses and for the male analyses.

It may be noted that, with the exception of Changing Times,

Reader's Digest, and Time, different groups of magazines were used for each sex.

Hhe classification matrix was generated through the use of the BMD-07M stepwise discriminant analysis routine. See General Methodoloqical Approach in Chapter IV. 248

Table 37

The Selected Variables Used in the Discriminant Analysis of Both Male and Female Participants in Each of Two Groups of Leisure-Time Pursuits

...... Used in ...... : Male Female Variable...... • Group Group

AIO Statements (Question 11)a

1. I express my talents better in my leisure-time activities than in my job. X X 2. We do not often go out to dinner or the theatre together. XX 3. Our family travels together quite a lot. X X 4. Television is our primary source of entertainment. X X 5. On a vacation, I ju st want to rest and relax. X X 6 . When I play a game or sport, my technique is more important than winning or losing. X X 7. I prefer to participate in individual sports more than team sports. X X 8 . When i t comes to recreation, time is a more important factor to me than money. X X 9. Leisure means actively participating in various sports and games. X X 10. Whenever possible, I prefer to participate in sporting activities, rather than just watch them. X X 11. I would not work i f I did not have to. X X 12. When I go camping, I enjoy roughing it. X X 13. I have enough leisure time. X X 14. I do a lo t of repair work on my car. X X 15. It is more important to live graciously, than to save up a lot of money for the future. X X 16. I enjoy getting all hot and sweaty vigorously playing a sport. X X 17. Basically, I'm satisfied with my present leisure time activities. X X 18. I do not like to go to club or organization meetings. X X 19. Our family income is high enough to satisfy nearly all our important desires X X 20. I would rather work alone than in a group. X X 21. I would rather spend a quiet evening at home than go out to a party. X X 249 Table 37 (Continued)

Used in Male Female Variable Group Group

Magazines (Question 12)b

22. Better Homes and Gardens (87)c X 23. Changing Times (44, 41) XX 24. Consumer's Reports (50) X 25. Field and Stream (99) X 26. Flower and Garden (29) X 27. Hairdo and Beauty (23) X 28. Holiday (21) X 29. Ladies Home Journal (222) X 30. Modern Romances (33) X 31. Motor Trend (33) X 32. Outdoor Life (48) X 33. Parent's Magazine (63) X 34. Reader's Digers (196, 296) XX 35. Sports Afield (48) X 36. Sports Illustrated (62) X 37. Sunset (24) X 38. Time (91, 78) X X 39. True Story (44) X

Demographies (Questions 22 and M.F. demographic data) d

40. Religious Affiliation Scale XX 41. Education level of female X 42. Education level of male X 43. Position of male within company XX 44. Occupation of male X X 45. Household size X X 46. Total household income XX 47. Age of male X 48. Age of female X 49. Population density and degree of urbanization XX Total Used 40 40

Notes:

Number of respondents answering these statements varied some­ what, but generally were in the range: 494 £ 5 (males) or 585 +. 6 (females.

^The particular magazines selected for use in either the male or the female discriminant analyses were those that were the most significantly associated (.001 level or greater) with the 250 Table 37 (Continued)

Notes, (Continued)

pursuits in one or the other (but not both) of the two groups of pursuits. This relationship was based on cross-tabulating the pursuits against the magazines.

cThe figure in parentheses represents the number of respondents indicating that they read the magazine regularly. Where two figures appear, the first refers to the males, the second to the females.

^Essentially all of the respondents (603 females and 512 males) responded to each of the demographic variables. 251

Analysis of Table 38. This table presents the results of

the discriminant analyses on the female respondents.

The two groups of pursuits are derived from the correlation

matrix of all pursuits engaged in during 1972 plus the third pseudo

"control" group as discussed under Analysis Approach.

A cross-tabulation analysis of the pursuits in each group

revealed the following associations, significant at the .005 level or greater:

1. Ice/ro ller skating and reading Hairdo and Beauty were associated, as were exercising/jogging and reading Good Housekeeping, and playing basketball, etc. and not reading Reader's Digest.

2. Camping by trailer was associated with lower levels of education. Camping by tent and swimming were both associated with lower age brackets, and tent camping also with a lower degree of urbanization. Hiking, backpacking, nature study was associated with working females.

In group 2 all the pursuits were associated with lower age brackets, except chess/checkers which did not show any significant associations. In addition, skating was associated with a lower occupational position of the husband in his company.

3. Each of the ten pursuits showed fairly high likelihood

(.005 or greater) associations with many (4-12) other pursuits.

This implies that from a bare statistical significance standpoint

(given a sample size of 603), these pursuits do not form very "tight" clusters. 252

Table 38

Discriminant Analysis, of Two Groups of Leisure-Time Pursuits Engaged in During 1972 by Female Respondents?

A. The two groups of pursuits plus a "control" group:b

Group 1 (36 respondents)(Label: Outdoor, "natural" setting! 51 - Camping by tra ile r, camper, or motor home 52 - Camping by tent 53 - Canoeing, rowing, rafting 56 - Hiking, backpacking, nature study 64 - Swimming

Group 2 (199 respondents)(Label: Outdoor, "man-made" setting) 58 - Ice skating, roller skating 33 - Playing basketball, football,baseball, softball,- volley­ ball, handball 34 - Bicycling 37 - Chess, checkers, backgammon 72 - Exercising, jogging, visiting a health spa

Group 3 (86 respondents)c Respondents who did not engage inany of the 10 pursuits of Groups 1 and 2 during 1972.

B. Results of a 40-variable discriminant analyses:0*

1. Group 1 (36 respondents) Vs. Group 3 (41 respondents)

Classification Matrixe Number of cases classified into group—

Original Groups :Group 1 Group 3 Group 1 27 (75%) 9 Total correctly Group 3 3 ______;______38 (93%) classified = 65 or

Variables used to classify cases: 1. I express my talents better in my leisure-time than in my job (AIO statement). 2. Age of female—scaled from "under 25 ( 1) to "55 and over" (5).

Function* Variable ' Group 1 Group 3 1. 1.7896 1.2340 2. 1,7170 3.3462 Constant -5.2482 -9.31441 *F = 30,62 for 2 and 74 d.f.--significant at the .05 level. 253 Table 38 CContinued)

2. Group 2 (86 respondents) vs. GrOUp 3 (86 respondents)

Classification Matrixe Number of cases classified into group—

Original Group: Group 2- ' ...... Group 3 Group 2 70 -(81%) ...... 16 Total correctly Group 3 10 ...... 76 (88 %) classified = 146 or 85%. Variables used to classify cases: 1. On a vacation, I just want to rest and relax (AIO state­ ment). 2. Household size—scaled from 2 to 8 3. Age of female—scaled from "under 25" (1) to "55 and over" (5)

Function* Variable Group 2 Group 3 1. 1.6720 2.0740 2. 3.0544 2.2202 3. 3.2441 4.9943 Constant -10.5282 -16.5056

*F = 82.77 for 2 and 169 d.f.--significant at the .025 level.

3. Group 1 (36 respondent^ vs. GrOUP 2 (39 respondents)

Classification Matrixe Number of cases classified into group—

Original Group: Group 1 ______Group 2 Group 1 27 (75%) 9 Total correctly Group 2 8 31 (79%) classified = 58 or 77%.

Variables used to classify cases: 1. Our family travels together quite a lot (AIO statement). 2. I have enough leisure-time (AIO statement) 3. Our family income is high enough to satisfy nearly all our important desires (AIO statement). 4. Respondent reads Hairdo and Beauty. 5. Occupation of male—scaled from professional (1) to service worker (9). 254 Table 38 (Continued)

Function* Variable ; Group l Group 2 1. ‘ 1.3892 1.0792 2 . 0.2959 0.8464 3. 1.9786 1.5717 4. 3.6366 6.4085 5. 0.7934 1.2072 Constant -7.7522 -7.9604

*F = 4.8799 for 5 and 69 d.f.—significant at the .05 level.

4. Group 1 (36 respondents) vs. Group 2 (39 respondents! vs. Group 3 (41 respondents)

Classification Matrixe Number of cases classified into group—

Original Group: Group 1 Group 2 Group 3 Group 1 19 (53%) 9 8 Total correctly Group 2 9 27 (69%) 3 classified = 82 Group 3 2 ...... 3 ...... 36 (88 %) or 71%.

Variables used to classify cases:

1. When I go camping I enjoy roughing i t (AIO statement) 2. I have enough leisure-time (AIO statement). 3. Respondent reads Hairdo and Beauty 4. Education level of female—scaled from little (1) to post-grad (7). 5. Age of fem ale-scaled from "under 25" (1) to "55 and over" (5).

Function* Variable Group 1 Group 2 Group 3 1. 2.6158 2.1947 2.0076 2 . -0.0046 0.3925 0.2955 3. 0.9600 4.7758 0.2383 4. 3.4103 3.5015 2.7167 5. 2.9317 2.4777 4.1718 Constant -14.0297 -13.0273 -15.4691

*F = 11.1165 for 10 and 218 d .f .—significant at the .0001 level. 255 Table 38 (Continued)

Notes:

aGroups 1 and 2 are composed of those pursuits intercorrelating the highest in the correlation matrix of all activities engaged in during 1972. The correlation matrices are:

Group 1

51 52 53 56...... 64 ‘ N 51 1.0 - - - - 143 52 .329 1.0 - 127 53 .503 .339 1.0 86 56 .131 .111 .441 1.0 116 64 .224 .328 .156 .353 1.0

broup l

.3 4 .... 58 ' 33 • ' 37 72 N 58 1.0 - -- - 1 179 33 .498 1.0 -- - 187 34 .363 .456 1.0 - - 261 VI W ( .285 .587 .361 1.0 - 220 72 .082 .382 .210 .437 l.C 232

^Respondents were assigned to either Group 1 or Group 2 if they engaged in at least 3 (any 3) of the five pursuits in the group during 1972.

cThere were 282 respondents who fell into "Group 0" which was the residual group.

dA portion of Group 2 and of Group 3 was used when comparing against Group 1. A portion of Group 2 was used when comparing against Group 3.

eIt is recognized that the percentage of cases classified cor­ rectly is probably inflated since the same cases were used in both deriving the classification function and in the classifi­ cation process itself. The cut-off point in the stepwise discriminant analysis procedure (BMD07M routine) was selected as the fewest variables which resulted in approximately 70 percent of the total number of cases being correctly classified. 256

Four different discriminant analyses were performed on these

three groups. The fourth "residual" group was not used. The four

analyses were:

1. Group 1 versus Group 3

2. Group 2 versus Group 3

3. Grop 1 versus Group 2

4. Group 1 versus Group 2 versus Group 3

The first analysis resulted in a classification function, statistically significant at the .05 level, composed of only two independent variables which correctly classified 75 percent of the respondents in group 1 and 93 percent of those in group 3.® A total of 84 percent of all the respondents in the analysis were correctly classified.

The coefficients of the resulting function indicate that age of female is the more important in distinguishing group 1 from group

3, which is in accord with the cross-tabulation analysis. It should be recalled that Group 3 consists of those respondents who did not engage in any of the pursuits in either of the two groups during 1972.

There issome tendency for respondents who believe they express themselves better in their leisure time to engage in the pursuits in group 1 than not to engage in any of these ten pursuits.

®Since the two groups are intentionally quite similar in size, a "chance model" of 50 percent correctly classified by chance alone can be assumed in all these analyses. 257

The second analysis resulted in a classification function, significant at the .Q25 level, composed of three variables which correctly classified 81 percent of the members of group 2 and 88 percent of the members of group 3. This resulted in a total of

85 percent correct classifications. Again, age of female is the more important variable. This is supported by the cross-tabulation analysis, as is the indication that a smaller household size is more likely to be associated with group 2 than with group 3. Respon­ dents in group 2 are also less likely to want to rest and relax on a vacation.

The third analysis resulted in a classification function, significant at the .05 level, composed of five variables which correctly classified 75 percent of group 1 and 79 percent of group 2 members. A total of 77 percent were correctly classified. Since both groups tend to be composed of respondents in lower age brac­ kets, age is no longer a discriminating variable.

Cross-tabulations indicated some likelihood that either form of camping is associated with higher male occupational levels.

This is also implied by this classification function. This function also implies that group 2 members are more likely to read Hairdo and Beauty than those in group 1. This is also borne out by the cross-tabs. The implication that the group 1 members are more likely than those in group 2 to travel together as a family "quite a lot” also appears reasonable given the nature of the pursuits in group 1 .

Finally, the fourth analysis indicates that discriminating 258

between all three groups simultaneously is less reliable than, be­

tween two at a time. The function developed here, even though it

is significant at the .0001 level, composed of five variables

only correctly classifies 53 percent of group 1, 69 percent of

group 2, and 88 percent of group 3. Seventy-one percent of all

the group members are correctly classified.

The implication here is that group 1 and group 2 members are

more alike, and different from group 3, than they are differ­

ent from each other. Readership of Hairdo and Beauty is the most

important variable in discriminating between groups 2 and 1 or 3.

As indicated by the cross-tabs, respondents in both groups 1 and

2 tend to be slightly downscale on level of education, and dis­

tinctly downscale on age of female. This is also implied here by

the function coefficients for education and age.

Analysis of Table 39. This table presents the results of the several discriminant analyses performed on male respondent data.

Here too, the two groups of pursuits are derived from the correla­

tion matrix of those pursuits engaged in during 1972.

A cross-tabulation analysis of the pursuits in each group revealed the following associations at the .005 level or greater:

1. Attending concerts or plays, reading Changing Times, and not reading Workbasket were associated. Camping by tent, reading

Field and Stream, Hot Rod and not reading U. S. News and World

Report were associated, as were canoeing/rowing/rafting and not 259

Table 39

Discriminant Analysis of Two Groups of Leisure-Time Pursuits Engaged in During 1972 by Male Respondents3

A. The two groups of pursuits plus a "control" group:b

Group 1 (34 respondents) (Label: Outdoor, "natural" setting) 50 - Attend concerts or plays 52 - Camping by tent 53 - Canoeing, rowing, rafting 54 - Fishing or hunting 56 - Hiking, backpacking, nature study

Group 2 (231 respondents)(Label: Outdoor, "man-made" setting) 31 - Attend sporting events (as a spectator) 32 - Automobile modification, tune-ups 33 - Playing basketball, football, baseball, softball, volleyball, handball 34 - Bicycling 37 - Chess, Checkers, backgammon

Group 3 (34 respondents)c Respondents who did not engagein any of the 10 pursuits of Groups 1 and 2 during 1972.

B. Results of a 40-variable discriminant analysis

1. Group 1 (34 respondents) vs. GroUp 3 (34 respondents) Classification Matrixe Number of cases classified into group—

Original Group: Group 1 ______Group 2 Group 1 27 (79%) 7 Total correctly cl as Group 2 8 26 (76%) sified = 53 or 78%.

Variables used to classify cases: 1. When I go camping, I enjoy roughing i t (AIO statement). 2. I have enough leisure-time (AIO statement). 3. Education level of m ale-scaled from l i t t l e (1) to post­ grad (7).

Function* Variable Group 1 Group 2 1 . 2.1746 1.4483 2 . 0.5231 1.0297 3. 2.7837 1.7190 Constant -9.1401 -5.2891

*F = 13.3660 for 1 and 64 d .f .—significant at the .025 level. 260 Table 39 (Continued)

2. Group 2 (38 respondents) vs. Group'S (34 respondents) Classification Matrixe Number-of cases-classified into group— Original Group: Group 2 ...... Group 3 Group 1 30- (79%) 8 -- Total correctly clas- Group 2 7 ' 27 (79%) sified = 57 or 79%.

Variables used to classify cases: 1. Our family travels together quite a lot (AIO statement). 2. Age of male—scaled from "under 25" (1) to "55 and over" (5) 3. Total houshold income—scaled from "$4K-4,999" (1) to "$15K and over" (9)

Function* Variable Group 2 GrPup 3 1. 1.5197“ 0.9336 2. 1.5159 2.5870 3. 1.5597 0.9191 Constant -8.5749 -8.3044

*F = 15.3427 for 3 and 68 d.f .—significant at the .025 level.

3. Group 1 (34 respondents) vs. Group 2 (38 respondents) Classification Matrixe Number of cases classified in group— Original Group: Group 1 Group 2 Group 1 25 (74%) 9 Total correctly cl assi- Group 2 10 28 (74%) fied = 53 or 74%.

Variables used to classify cases: 1. I would not work i f I did not have to (AIO statement). 2. I do a lot of repair work on my car (AIO statement). 3. Respondent reads Consumer's Reports 4. Respondent reads Field and Stream 5. Respondent reads Sports Afield 6 . Respondent reads Sports Illustrated 7. Household size—scaled from 2 to 8 8 . Total household income—scaled from "$4K-4,999" ( 1) to "$15K and over" (9). 261 Table 39 (Continued)

...... Function* Variable ' Group 1 Group 2 1. 1.1192 0.7507 2 . 0.6948 1.3266 3. 0.8749 t0.7077 4. 0.7874 -0.5347 5. -2.3700 -0.1447 6 . 0.0751 1.8488 7. 1.8282 2.2477 8 . 1.4543 1.6937 Constant -6.7016 -9.3122

*F = 3.1711 for 8 and 63 d.f.—significant at the .05 level.

4. Group 1 (34 respondents) vs. Group 2 (38 respondents) vs. Group 3 (34 respondents) Classification Matrixe Number of cases classified into group— Original Group: Group!'Group 2 Group 3 Group 1 21 (62%) 7 6 Total correct- Group 2 12 23(61%) .3 ly classified Group 3 3 ...... 3 28 (82%) « 72 or 68 %.

Variables used to classify cases: 1. Our family travels together quite a lot (AI0 statement). 2. On a vacation, I just want to rest and relax (AI0 state­ ment). 3. I would not work i f I did not have to (AI0 statement). 4. When I go camping, I enjoy roughing i t (AI0 statement). 5. I have enough leisure-time (AI0 statement). 6 . I do a lot of repair work on my car (AI0 statement). 7. Respondent reads Sports Afield. 8 . Education level of male—scaled from l i t t l e (1) to post­ grad (7). 9. Age of male—scaled from "under 25" (1) to "55 and over" (5). 10. Total household income—scaled from "$4K-4999" ( 1) to "$15K and over" (9). 262 Table 39 (Continued)

...... ' Function* Variable ' Group 1 GroCip 2 Group 3 U 1.1340 1.1877 0.4722 2 . 1.3731 1.5745 1.8664 3. 1.4496 1.2725 1.7818 4. 2.5302 2.3371 1.9975 5. -0.1902 -0.1145 0.1864 6 . 1.4674 2.0479 1.3875 7. 0.8540 2.8274 0.0418 8 . 3.4241 3.3951 2.7071 9. 3.3264 3.2377 3.8442 10. 0.9638 1.2359 0.7481 Constant -24.9091 -27.2287 -23.5558

*F = 4.6383 for 20 and 188 d.f .—significant at the .0005 level.

Notes:

aGroups 1 and 2 are composed of those pursuits intercorrelating the highest in the correlation matrix of all activities engaged in during 1972. The correlation matrices are:

Group 1

50 52 53 54 56 N 50 1.0 - --- 190 52 .449 1.0 - - - 131 53 .121 .623 1.0 - - 113 54 .238 .200 .300 1.0 - 301 56 .385 .470 .409 .449 1.0 112

Group 2

31 32 33 34 ’ 37 N 31 1.0 - --- 332 32 .455 1.0 - -- 227 33 .486 .406 1.0 -- 232 34 .338 .328 .280 1.0 - 199 37 .429 .458 .475 .481 1.0 204

^Respondents were assigned to either Group 1 or Group 2 if they engaged in at least 3 (any 3) of the five pursuits in the group during 1972.

cThere were 213 respondents who fell into "Group 0," which was the residual group. 263

Table 39 (Continued)

Notes (Continued)

portion of Group 2 was used when comparing against Groups 1 and 3.

eIt is recognized that the percentage of cases correctly classi­ fied is probably inflated since the same cases were used in both determining the classification function and in the classi­ fication process itself. The cut-off point in the stepwise discriminant analysis procedure (BMD07M routine) was selected as the fewest variables which resulted in approximately 70 percent of the total number of cases being correctly classified. 264

reading Time. Those engaging in fishing or hunting during 1972 were likely to read Sports Afield, Field and Stream, and Outdoor

life and not to read'Consumer1s Reports. Hikers, backpackers and

nature studies were likely to read Playboy and TV Guide.

In addition, members of group 2 were likely to have the

following associations: attending sporting even’s and reading Hot

Rod, Motor Trend and TV Guide; auto mods, and not reading Time;

playing "ball" and'not reading Better Homes and Gardens, Ladies

Home Journal, McCalls or Reader's Digest and reading Playboy.

Finally, those engaging in chess/checkers/backgammon were likely to read Sports Illustrated and not read Better'Homes'and Gardens.

2. All of the pursuits in group 1 and playing "ball" and bicycling were associated with younger male age brackets. Attend­ ing sporting events and auto mods, were associated with younger female age brackets. The cross-tabs against male age did not reach significance on these two pursuits. Attending concerts and plays and chess/checkers/backgammon were both associated with higher total household income categories, while camping by tent and hiking/ backpacking were associated with a lower (male) occupational posi­ tion in his company (supervisor or non-supervisory or hourly).

Both camping by tent and fishing/hunting were associated with lower levels of education, while canoeing/rowing/rafting were associated with middle levels of education (high school grad, some college). Camping by tent and fishing/hunting were also both associated with lower degrees of urbanization, while bicycling and hiking/backpacking were associated with higher degrees of urbanization of the respondent's place of residence. 265

Playing "ball" was associated with both "managers/admini­

strators" and "operatives" as two different levels of male occupa­

tion. This implies that perhaps certain types of "ball" are played by different occupational levels.

3. As in the case of the female respondents, each of these ten pursuits showed fairly high likelihood associations with from

six to eighteen other pursuits. The implication again is that from a statistical significance standpoint (and a sample size of 512), these pursuits do not form very "tight" clusters.

Four different discriminant analyses were performed on these three groups. The fourth "residual" group was not used. The four analyses were:

1. Group 1 versus Group 3

2. Group 2 versus Group 3

3. Group 1 versus Group 2

4. Group 1 versus Group 2 versus Group 3

The first analysis resulted in a classification function, statistically significant at the .025 level, composed of three independent variables which correctly classified 79 percent of the respondents in group 1 and 70 percent of those in group 3. This resulted in a total of 78 percent correctly classified. The coef­ ficients of the resulting function indicate that male education level is the most important variable in distinguishing between groups 1 and 3. This is borne out by the cross-tabs, in which participants in group 1 are likely to be lower on the educational level scale. Members of group 1 also enjoy roughing i t when they 266

go camping. This seems reasonable,, given the nature of the pur­

suits in group 1.

The second analysis resulted in a classification function,

significant at the .025 level, composed of three variables, and

which correctly classified 79 percent of both group 2 and group 3.

Age of male is the most important variable here and this too is

supported by the cross-tabulations in which participation is the

pursuits in group 2 is likely to be associated with the lower age

categories (under 35 years of age).

The total household income of participants in chess/checkers

backgammon tends to be the higher categories according to the cross­

tabs. This may account for this variable appearing in this func­

tion. Finally, there is apparently some tendency for members of

group 2 to travel together as a family "quite a lot."

The third analysis resulted in a function, significant at

the .05 level, which correctly classified 74 percent of both

groups 1 and 2. It requires eight variables to reach this level

of correct classifications, however. Based on both the results

of the cross-tabulations add the function coefficients, it appears

that members of group 1 are not particularly interested in their work and, as a group, show some tendency to read Consumer's Reports,

Field arid Stream, and Sports Afield. Group 2 members show a ten­ dency to do a lot of repair work on their car, read Sports Illus­ tra te d , and have at least one child. Total household income does not seem to be a particularly good discriminating variable here. 2 6 7 The fourth analysis resulted in a function, significant at

the .Q0Q5 level, which correctly classified only 62 percent of

group 1, 61 percent of group 2 and 82 percent of group 3, for an

average of 68 percent correctly classified. It required ten vari­

ables to reach even this level of correct classification. The same

situation exists here as did with the female respondents, in that

the sim ilarity between groups 1 and 2 and their mutual difference from group 3 makes discrimination between all three simultaneously

less reliable.

Reading Sports Afield seems to be the most discriminating variable in distinguishing between membership in group 2 and either group 1 or 3. Apparently both group 1 and group 3 members are rela­ tively likely to read this magazine. Both group 1 and group 2 members, in comparison with group 3 members, feel that th eir family travels together "quite a lot." Doing a lot of repair work on his car again seems to distinguish group 2 males from group 1 or 3 males.

The other variables do not seem, individually, to be particularly distinctive.

Summary. Four different discriminant analyses were run for both the males and the females. Participation in either of two groups of pursuits was compared with not participating in any of the pursuits in either group.

The f ir s t group of pursuits for both the males and females was an outdoor-oriented, camping/backwoods, water-trip group.

Participants tended to be younger, somewhat lower in attained education level, feel they express their talents better in their 268 leisure-time than at their job, enjoy roughinq it in the woods and fields, and tend to wish for more leisure-time.

The second group had three pursuits in common with both sexes—playing "ball," bicycling, and playing chess/checkers/back­ gammon. The females in addition tended to skate or exercise, while the males attended sporting events or worked on their car. This group tended also to be younger, have somewhat larger families, travel together a lot as a family, and not particularly want to rest and relax on a vacation.

When groups 1 and 2 were compared with each other, reader­ ship of several magazines become discriminating variables. Males in the first group tended to read the outdoor-oriented hunting/ fishing magazines, while those in the second group tended to read

Sports Illustrated. Females in the second group tended to read

Hairdo and Beauty. Both males and females in the first group tended to feel they did not have enough leisure-time. It also took more variables to discriminate between groups 1 and 2 together than between groups 1 and 3 or 2 and 3.

Finally, when the attempt was made to discriminate between all these groups simultaneously, the results were not as satis­ factory, in terms of percent correctly classified, and i t took more variables to reach a given level of correct classifications.

This was a reflection of the similarity of some of the characteris­ tics of participants in both groups 1 and 2 in contrast to those in group 3. 269

Conclusions. The results of these analyses can now be

related to the original objectives (in the order stated):

1. Discriminant analysis can define distinguishing char­

acteristics of participants in different clusters of leisure-time

pursuits—particularly in comparison with non-participants in any

of the pursuits in the cluster.

2. Discriminant analysis does appear to be able to efficiently

discriminate between membership in a particular cluster of pursuits

and membership in a cluster based upon non-participation in any of

the selected pursuits.

3. Demographic, AIO and magazine readership variables all seem to do about an equally good job of discriminating between groups of pursuits (at least with the groups used here). It depends on the kind of comparisons being made, which variables are the more

important. Of the three types, however, demographic variables and

AIO statements appear to be the more powerful in discriminating between participation and non-participation.

4. The variables in the resulting discriminant functions and their coefficients imply the same relationships found in cross-tabulation analysis and the principal components factor analysis. Comparisons with the factor analysis results are ten­ uous, however, due to ( 1) the limited number of discriminant analy­ ses performed, and ( 2 ) the lack of absolute uniqueness in the factors resulting from a particular group of variables used, fac­ tors rotated, and method of rotation. 270

Chapter V Summary. This chapter has presented the results of the analysis of the data relative to each of the five hypotheses.

Each hypothesis was supported, to a greater or lesser degree, given the nature of the data, the particular analysis methods employed, and the phrasing of the particular hypothesis. Certainly, there is room for additional analysis on this extensive data bank. This analysis will be conducted as part of an ongoing program in the study of leisure-time behavior by both this writer and his colleagues.

Chapter VI summarizes the salient findings of this study and indicates how they relate to the results of similar studies. Such implications as can reasonably be drawn from the findings are also discussed. CHAPTER VI

SUMMARY AND IMPLICATIONS

Chapter IV discussed the study methodology and the pretesting which preceded the major survey. Chapter V then related the results of the survey to the major research questions, or hypotheses, around which the study was designed. This chapter summarizes the salient findings in relation to the original study objectives. Possible implications of the findings and some suggested directions for future research are also discussed.

Summary of the Study Objectives and Procedures

The basic study objectives, as suggested in the research questions of Chapter II, and subsequently formalized into research hypotheses, consisted essentially of the search for market segments for ( 1) leisure-time pursuits, (2) uses of credit as a means of payment for leisure-time products and pursuits, and (3) uses of television and magazines as related to a person's interest in particular leisure-time pursuits. The distinguishing character­ istic s of these segments were also sought.

The "pursuits" segments were defined in terms of clusters or groups of related leisure-time pursuits providing one or more related clusters of "satisfactions" or benefits to the participant. Reacha­ b ility of the segments was investigated by searching for clusters or groups of media, specifically magazines and television program- 271 272 types, which were related to these groups of leisure-time pursui t s .

The "uses of credit" segments were defined in terms of two basic groups of respondents—holders and non-holders of credit cards. Within these two general groups, a combination of cross­ tabulation analysis and factor analysis evolved groupings or clusters of the eighty-six selected credit-oriented variables. There were five subgroups of credit-oriented variables among the eighty-six;

(1) possession of specific credit cards

(2) attitude toward certain characteristics of credit

cards

(3) specific uses of credit during 1972

(4) acceptable uses of long-term credit

(5) general attitude or opinion about credit.

Cross-tabulation analysis helped define distinguishing character­ istic s of market segments based on these five subgroups individually, while factor analysis was used to develop segments across all five subgroups together plus a group of demographic variables.

The primary research questions asked, therefore, were

1. Are there identifiable "satisfactions" or perceived

benefits which people derived from lei sure-time pursuits?

2. Do leisure-time pursuits and satisfactions (if they exist),

tend to be related in relatively homogeneous clusters (groups)? 273

3. Are clusters of leisure-time pursuits related to clusters

of satisfactions?

4. Are there differing attitudes toward, and uses of, credit

for the financing of leisure-time products and pursuits

by different groups of people?

5. Are there differing patterns of (mass) magazine reader­

ship and television viewing preferences associated with

different clusters of leisure-time pursuits?

The research approach involved first the determination of whether or not leisure-time "satisfactions," as embodied in a list of "satisfactions" statements, were meaningful to the respondents.

Next, leisure-time pursuits and satisfactions were factor analyzed to see i f reliable, meaningful clusters emerged. A comparison of the resulting clusters of pursuits and satisfactions was then made.

Attitudes toward use of credit, and actual use during 1972, for leisure-time oriented products and pursuits were determined through a combination of cross-tabulation analyses, correlations, and factor analysis. The relationship of magazine readership and television program-type preferences to leisure-time pursuits was determined in the same manner.

Major Findings

This study resulted in a nuntier of salient findings. The fact that the study respondents were over-represented (relative to both non-respondents and the initial sample distribution) in the

45-and-over age groups and under-represented in the 25-34 age 274

group, should be borne in mind in considering these findings (see

Table 6 ).

It was initially believed, based on the literature search,

that (1) leisure-time pursuits would group together in relatively

tight clusters, and ( 2) particular pursuits, or groups of related

pursuits, provide essentially the same "satisfactions"'to all

participants. In other words, most people who participated in one

particular pursuit also tended to participate in the same related

pursuits, thus leading to "high" intercorrelations among these

pursuits and "low" correlations with pursuits outside the group. The

same statement could be made about factor loadings.

This study indicated that there is much more variability in

both the participation in leisure-time pursuits and in the "satis­

faction" derived than the literature would seem to imply. This finding is based on ( 1) the small number of pursuits selected as

favorites by 5 percent or more of the sample, (2) the relatively

low intercorrelations between pursuits found throughout the study,

(2) the low (typically less than 10 percent) amount of variance in

the data explained by the derived factors, and (4) the bipolar

factors of "favorite" pursuits.

Hypothesis H-j. People seemingly can relate th eir participa­

tion in various leisure-time pursuits to at least some of the intan­

gible benefits or "satisfactions" felt by them as a result of

participating. 275

These "satisfactions" may be considered to be some of the

"reasons why" people participate in particular leisure-time pursuits.

Out of the thirty-two "satisfaction" statements, twenty-one of them appeared to be meaningful to the female respondents in relation to all those pursuits selected as favorites. Twenty-three of these statements appeared meaningful to the males.

Individuals apparently can relate their participation in outdoor, active, group-oriented pursuits more readily to derived

"satisfactions," than they can to participation in indoor, passive, primarily individual pursuits. The latter type of pursuit engendered an "indifferent or does not apply" response on half or more of the

"satisfactions" statements by half or more of the respondents. This would imply that people who participate in this latter type of pursuit do so for reasons (to gain "satisfactions") which are ( 1) subconscious, ( 2) perceived to be socially unacceptable in some sense, (3) not included in the list provided, or (4) few in number compared with outdoor, active, group-oriented pursuits.

It is also interesting to note that, among the males, the pursuits "visiting a bar or club" and "visiting with friends" engendered this same extent of "indifferent" response as more obviously individual activities such as "read a book," "attend movies," and "listen to music." This may indicate a tendency for males to be more susceptible to the "alone in a crowd" syndrome than females. 276

Finally, only two of the original twelve Havighurst

list of "meanings" of leisure-time pursuits (see page

appeared in the l i s t of "satisfactions" statements with non-peaked

response distribution (Table 12). This would tend to place in question the reliability of Havighurst’s findings of relationships between his "meanings" and his categories of leisure-time activities.

The published results of his studies in this area do not give

sufficient detail on the conduct and other specifics of his inter­

views, however, to permit more than the questioning of his results.

Hypothesis H 2 . Leisure-time pursuits do cluster together in interpretable groups (factors) which individually account for approximately 5-16 percent of the variance in the data. Both pursuits "engaged in during 1972" and "favorite" pursuits were found to cluster, with the "favorite" pursuits generating groups accounting for 11-16 percent of the variance. Both indoor and outdoor pursuits were typically included in a single cluster.

These "favorite" groups were seemingly bipolar in nature and included some groups (factors) with negative eigenvalues. They should therefore be interpreted cautiously pending further study.

The phenomena of clustering of leisure-time pursuits supports the earlier findings of Proctor (1962), Burton (1971), and others discussed in Chapter III. While the specific pursuits (or categories of pursuits) differed somewhat between the Proctor study and this one, two of Proctor's clusters (named "backwoods recreation" and "boat culture") were essentially duplicated in this study. 277

Some sim ilarity between the clusters or groups developed by

Burton and those in this study was also noted. This was particu­ larly true in the general sense of active, physical pursuits versus more "sedate” (though not entirely "passive") pursuits—both in the outdoors. Here again, specific pursuits differed somewhat in the two studies.

The groups or clusters that evolved were not unique, however.

Both clusters of pursuits "engaged in during 1972" and clusters of

"favorite" pursuits contained several overlapping pursuits, or pursuits which fell into more than one cluster. There were many more cases of overlapping pursuits among the clusters of "favorite" pursuits than among those "engaged in during 1972," however. This would appear to be a reflection of ( 1) the bipolar nature of the

"favorite" pursuit clusters, ( 2) the small size of the sub-sample selecting any particular pursuit or a "favorite," and (3) the broad scope of "favorite" activ ities.

An interesting finding was the difference between the distinct indoor orientation of the females coupled with a slight overall outdoor orientation of the males. There were thirteen indoor- oriented pursuits selected as favorites by the females, to only eight outdoor-oriented onesJ The males, on the other hand, selected thirteen indoor-oriented pursuits (not the same set as the females) and fifteen outdoor-oriented ones as favorites. The three

■Some pursuits were rated as either indoor or outdoor. 278 most favorite pursuits among the females, in order, and with the percentage selecting it as a favorite indicated, were ( 1) creative crafts or handicrafts (43%), (2) reading a book for pleasure (26%), and (3) visiting with friends/partying (16%). The three most favorite for the males were (1) fishing or hunting (38%), (2) gardening, lawn-care, landscaping (14%), and (3) listening to music from records, tapes, radio ( 12%).

These data, and Table 15 in general, indicate two interesting situations. F irst, females appear to have a narrower range of favorite activ ities than males. Second, females and males appear to have diverse favorites which in some cases may be incompatible in terms of simultaneous performance. The implications for family harmony or discord are interesting to contemplate, particularly in light of the rising divorce rate and, in some cases, increasing leisure-time (either annually or over a life time).

Perceived "satisfactions" do group together, both across many pursuits and also in relation to a single pursuit. This finding is significant because it indicates that individuals seek out a group of related leisure-time satisfactions through a variety of means. Here again the differences between the clusters of satis­ factions for males and females is interesting. The most significant clusters (in terms of explained variance) for the males and females are noticeably different in content, as reference to Tables 18 and 19 will show. Furthermore, while the most significant clusters for the most-, second-, and third-most-favorite activities for the males are 279 essentially identical in content, the females appear to make a distinction in the benefits they seek from their most favorite activity versus those from their second- and third-most-favorite acti vi ti es.

The women appear to seek people-contact, novelty (newness), memories, and stronger family relationships f ir s t, and personal s k ill, creativity, mastery, challenge and independence only secondarily.

The men, on the other hand tend to seek challenge, mastery, control, recognition, and independence from all three of th eir favorite activities.

The clustering of "satisfactions" statements or benefits from participating in a particular pursuit indicates that a particular pursuit typically provides somewhat different "bundles" of satis­ factions to participants. That is, a participant may do so for one or more of several groups of related benefits, or different parti­ cipants may gain different benefits from the same pursuit. This is in contradistinction to the idea that a pursuit is monolithic in its "satisfactions" or benefits provided to participants.

These groups or bundles of satisfactions tend not to be unique, in that some satisfactions are found in more than one group.

This may imply that what appears to be a single discrete "satis­ faction" is, in reality, a multidimensional concept.

Hypothesis H 3. Different, related pursuits do appear to provide common groups or bundles of "satisfactions." As discussed above, a single pursuit is likely to provide several different 280 bundles of satisfactions to participants. One or more of these bundles may be totally or partially in common with other pursuits.

The finding of groups of satisfactions statements with nega­ tive factor loadings for a particular pursuit implies that these are not satisfactions derived from participating in the pursuit. Given the content of these groups (clearly not relevant to the pursuit), the implication is that these statements fall in a group in multi­ dimensional space far removed from the other groups of statements.

Certain pursuits appear to perform a "linking-pin" function in connecting two or more groups of (internally) "strongly" related pursuits. This is brought out in Table 22 (picnicing is the linking pursuit) and Table 23 (photography is the linking pursuit). This finding is even more evident in an analysis of the complete intercorrelation matrix of "favorite" pursuits or pursuits "engaged in during 1972." These linking pursuits would appear to provide bundles of satisfactions which are different enough to satisfy different groups of participants. For example, attending concerts is a typically upper-middle class (and above) pursuit, while

(conventional) fishing and hunting seems to cater more to lower middle class (blue-collar) individuals and below. Picnicing on the other hand is an activity which can be enjoyed by essentially all groups. The wide scope of activ ities subsumed under "fishing and hunting" probably accounts for the correlation between it and

"attending concerts/plays." 281

Hypothesis H^. The results of this study indicate that there is still a significant degree of reluctance on the part of many people to use either credit cards or "long-term" credit for leisure­ time oriented products and pursuits. This is particularly true in the case of "long-term" credit where the most popular leisure-time oriented use of this form of credit (to finance a recreational vehicle) was acceptable to only a maximum of 30 percent of the respondents.

Fully 80 percent of the respondents held at least one credit card, with gasoline company cards and Sear's/Penney's/Ward's cards being the most popular. Card holders in general tended to be better educated, more affluent and hold higher-level jobs. They also, according to the analysis, tended to be older, though this may be a reflection of the age distribution of the respondents.

The tendency was to use credit for many purposes if it was used at a ll. This is also reflected in the parallel tendency to hold several credit cards i f any were held. Respondents who f e lt that the use of long-term credit was acceptable for one purpose similarly felt it was acceptable for a wide range of purposes— except "taking a vacation trip."

Two definable sets of uses of credit during 1972 appeared.

One of these was "acquisition of tangible property" and "utili­ tarian" oriented. It did not include any leisure-time travel uses.

These respondents tended to be younger, earlier in the family life cycle and somewhat less affluent. The second set did include all 282

given leisure-time travel uses, plus using credit for photography and gardening/lawn care supplies, and excluded uses in the first set. The orientation here seemed to be one of a seeking for new horizons and a broadening of ones interests and ideas. These respondents tended to be better educated, more affluent and (by implication) older.

Non-business dining appeared to bridge these two sets of uses of credit in that it was acceptable to both groups. Many people who do not use credit for other purposes also find this use acceptable. This may be indicative of a desire for fashionable current consumption without the need for carrying large sums of cash. Also,

"eating out" may be considered by many to be in the "grey area" between a leisure-time activity and a convenience sometimes bordering on a necessity.

Credit card holders in general tend to be good potential customers for an automobile, land or property, a house or trailer and home furnishings. This is no doubt in part a reflection of their relative affluence vis S vis non-holders of cards.

Non-holders of credit cards tend to be less well educated, less affluent, more religiously conservative, and older. Non­ holders also are more homogeneous as reflected in the greater amount of data variance (relative to holders) accounted for in the factor analyses of these respondents. This is in part also a reflection of th eir smaller absolute numbers. Interestingly, there were groups of both holders and non-holders who evidenced a strong concern over their family's financial situation. No doubt the effects of 283 inflation and uncertainty about the economic future affects both groups.

Hypothesis H 5 . The popular understanding that there are distinct differences in the readership of various magazines was supported in this study. Of those general variables cross-tabula­ ted against magazines, demographics seemed to be good discriminators.

Association of magazines and favorite leisure-time pursuits were generally of the nature one would expect based upon experience and thoughtful reasoning. Inconclusive results were found when magazines were cross-tabulated with magazines because of the relatively small number of respondents reading any one magazine.

Among the major newsweeklies, Time and U. S. News and World

Report were both associated with higher levels of education and male's position within his company, while readership of Newsweek was more diffused throughout the population with only some tendency toward socioeconomically "upscale" readers. Interestingly, Bible readers, who tended to be older and less affluent, also were readers of the "romance" magazines. The sim ilarities between these two media in the eyes of these respondents can only be speculated upon.

The popular belief that there is a substantial segment of the television viewing public who is not particularly discriminating in th eir viewing preferences was also corroborated. There were a great many significant associations between all of the television program types listed . Demographics, again, showed good discrminatory power in identifying viewers of particular types of programs. 284

Association of favorite leisure-time pursuits and television program types were generally self-evident--either through a direct relationship or through an intervening common demographic variable.

An interesting finding that parallels current practice was that

"attending movies" as a favorite pursuit was associated with preference for niystery/suspense television programs. Certainly, many of today's movie films have a iriystery/suspense/danger/violence theme.

The results of the factor analysis of favorite pursuits and magazines/television program types indicated that magazines discriminate better than television program types in distinguishing between groups of related pursuits. This was indicated both by the greater amount of variance accounted for by the magazines/pursuits factors, and also by the greater number of "mixed" (as opposed to monalithic or single variable-type) factors in this analysis. Most of these factors were bipolar, however, implying an underlying unifying dimension which could only be hypothesized at this stage of the research.

Additional Analyses. It appears possible to distinguish participants in one group of leisure-time pursuits from those in another group through discriminant analysis. Given the efficiency of the few demonstrative analyses attempted, it would seem that this analytical approach may be the most fruitful in terms of distinguish­ ing between participants and non-participants in one or a group of pursuits. 285

Demographic variables, again, along with AIO statements and magazines showed good discriminatory power in differentiating between (1) participants/non-participants and (2) participants in different groups of leisure-time pursuits. There are two draw­ backs to the use of this analytical technique in this study. They are (1) the tendency toward small sample sizes when "membership" in a group is defined in terms of participating in at least half the pur­ suits in the group during 1972, and (2) the tendency toward low (.30 and below) correlation between participation in different pursuits coupled with widely varying N's (number of subjects participating)— sometimes exceeding a 2:1 ratio between pursuits being correlated.

Implications of the Findings

The degree of variability evidenced in the data from this study in regard to both participation in leisure-time pursuits and derived satisfaction has several implications. First, it significantly complicates planning by both the private and the public sectors. It will not be easy for either sector to develop economically viable packages of related pursuits designed to divert users from existing overcrowded facilities and activities. Parti­ cipants in one pursuit do not seem overwhelmingly to also favor one or two other pursuits.

On the positive side, the variability in satisfactions derived from a particular pursuit permits managers and developers to tailor existing facilities,programs and specific activities to serve a wide range of needs. Armed with the knowledge about the overall types of 286 satisfactions sought by males and females across all their "favorite" pursuits, management can develop and stress these particular benefits or satisfactions. New or additional pursuits can be added to existing recreational complexes which are known to provide these

"universally" sought satisfactions.

Also, through further research,groups of leisure-time pursuits which provide highly similar satisfactions can be defined and subsequently implemented. Combining concerts and picnics (as is presently done) is appropriate, as is installing music listening facilities in libraries and book stores, for example, It might even be appropriate to combine photography, books and music in one retail enterprise.

It appears that people can recognize at least some of the satisfactions which they seek out in their leisure-time pursuits, at least in active, other-directed pursuits. Suppliers, therefore, should ascertain the type, level and degree of satisfactions sought by th eir customers from their particular fa c ilitie s , programs, and activities.

Depending on the sizes of the various market segments involved, it may be possible to accentuate various types of satis­ faction sought by different segments without negating the benefits received by other segments. This is assuming that there are many small segments involved and, consequently, that i t would not be cost-effective to concentrate on one or a few. If on the other hand, the majority of a facility's patrons seek a fairly homogeneous set 287

of satisfactions, and these are not being entirely fulfilled, then

concentration on providing these satisfactions is warranted.

Similarly, if it appears that a net economic gain can be achieved

by focusing on one presently small, but expandable, segment

then this should be investigated.

The indoor orientation of females and the outdoor orienta­

tion of males poses problems in developing family-oriented

recreational complexes. Fortunately, the narrower range of favorite

activities of females makes the task somewhat easier. The fact that

clusters of related pursuits typically contained both indoor and

outdoor pursuits may also fa c ilita te moving males indoors and females

outdoors.

The opportunity to play golf, for example, at different levels

of involvement (degree of mental and physical challenge), and under

different environmental conditions (extent of social contact, varia­

bility of experiences, indoor and outdoor) should be provided.

Similarly, bowling should be made available under a wide range of

circumstances (extent of challenge invoked, chance for socialization,

novel situations, chance for skill improvement, and easy-going

relaxation).

Since bowling establishments and to some extent golf

fa c ilitie s are already promoting a fairly wide range of situations

under which a person might participate, the results of this study

are supportive of current practice. The key implication here is that management has a "new" dimension along which to research and segment 288 their patrons and, in light of which, to evaluate their operations, image and degree of customer satisfaction.

Purveyors of credit cards and long-term credit seem to be faced with three broad market segments based essentially on age.

A younger (probably mid-thirties and below) segment is oriented toward using credit for "nest-building” products and services.

This group seems u tilita ria n in their orientation toward the use of credit, and at this point in their lives do not consider it appro­ priate for leisure-time travel and expensive products. Since their general attitude toward credit seems favorable, this does not mean that they would not consider using credit for leisure-time goods and services at a later point in life. It appears to be a matter of priorities.

A second older segment (probably la te -th irtie s and above) does use credit cards for lei sure-time travel and related needs. This segment has probably completed their essential "nest building" and can turn to vacation travel, recreational vehicles, and refurnishing their homes.

It should be noted however that usinq long-term credit for leisure-time products and services is still frowned upon by some 70 percent of the respondents. Purveyors of those kinds of leisure­ time products and services which are costly enough to warrant long­ term financing have an uphill battle facing them in reducing this reluctance. Probably stressing the "investment" and "mental growth" aspects of the product or service would be more appropriate than the

"fun" aspects. 289

Similarly loan companies are the same situation in attempting

to broaden their markets to include leisure-time oriented uses.

A sim ilar investment/growth approach may be fru itfu l.

Finally, there is a third segment, comprised of both younger

and older respondents who are adverse to the use of credit cards, but not necessarily long-term credit. These respondents tend to be lesser educated and less affluent. By implication, they need credit counseling and one way in which BankAmericard (BAC) might

gain them as customers would be to provide such counseling and budgeting services. Since concern with family finances also is prevalent among credit card holders, this service could benefit existing BAC and, correspondingly, Master Charge customers.

As a means of gaining potential customers, purveyors of automobiles, real estate, mobile homes, and home furnishings might acquire mailing lists from the bank and travel/entertainment cards.

Card holders in general were very amenable to the use of long-term credit to finance these types of products. Perhaps a joint venture between one of the purveyors and a loan company or bank could be developed.

Use of television as a media to communicate with particular leisure-time market segments does not seem to be as effective a means as the use of magazines. The exceptions to this are in the cases of

(1 ) general sports enthusiasts and ( 2 ) concert-and-play-goers and music lovers. Participants in these pursuits may be reached through television sports programming and through televised concerts and pi ays. 290

The present proliferation of specialized magazines designed to reach specific segments of the leisure-time market seems to be appropriate. One interesting relationship that should prove viable is the use of the "romance" magazines to promote Bibles, syndicated religious programs, and religious products of various types.

Finally, one of the most pervasively discriminating sets of variables in this study was the group of demographic variables.

This implies that this readily available type of variable may be at least as effective, if not more so, as the more exotic attitudinal and psychological variables. This is not meant to negate the utility of, for example, psychographics in providing a "richer" description of market segments. I t does appear, however, that the standard demographic variables of age, income, occupation, education, family size, and position of male within company (many of which are interrelated as a so-called "social class" construct) are useful bases for defining leisure-time market segments.

Study Limitations

Recognized lim itations to this study fall into two categories:

( 1 ) those resulting from the nature of the data as collected and the analysis techniques utilized, and ( 2 ) those caused by the design of the study itself.

Data/Techniques. Limitations in the first category include unknown generalization biases in the Market Facts sample vis $ vis the American population as a whole. The extent to which the leisure- 291 time behavior and preferences of Market Facts panel menbers in general and, more specifically, these particular respondents reflect those of non-panel members is unknown.

The low response rate on some of the variables not only limits generalizability, but also may effect the operation and results of certain of the analytical techniques--particularly correlations and subsequent operations performed on the correlation matrix. Missing data, although controlled for in this study where possible, may also bias correlation.

Finally, the full impact of the use of the tetradoric correlation coefficient is not clear, nor is the impact of mixing dichotomous and interval-scaled variables in different proportions in a single "Pearson-r" or tetracloric correlation matrix. There is no consensus in the literature regarding the application of the tetracloric correlation coefficient.

Study Design. Limitations in this category include the in ability to detect temporal shifts in behavior or attitudes—a characteristic of all single-point, cross-sectional surveys. The effect on the respondent's selection of favorite pursuits, for example, of the time of year when the survey was conducted is unknown.

Although care was taken in the design and layout of the questionnaire, there may be order bias or misinterpretations still remaining. The true thrust of the questionnaire is probably soon evident to the respondent and may cause an upward bias in the number of leisure-time oriented options selected in latter parts of the questionnaire. 292

The broad scope of the sample utilized may have caused more variability in the data than can be reliably partial led out. This may be one reason for the relatively low strength of most of the relationships.

Certainly, the entire domain of meanings or "satisfactions" to the participant in a leisure-time pursuit was not sampled. The list of satisfactions statements needs to be further developed. The same caveat applies to the AIO statements.

Finally, the coirbining of several leisure-time pursuits under one label, in the interests of brevity and reduced respondent fatigue, limited the clarity and interpretation of the resulting clusters of pursuits. Some of the listed pursuits, themselves, represented mini-clusters of (a priori) related pursuits.

Directions for Future Research

While many avenues for additional data collection became evident in the analysis of this study's data, a number of oppor­ tunities remain for further analysis of the existing data file.

Many of the variables discussed in the dissertation need to be looked at from different perspectives and in different groupings.

More specifically, essentially no partitioning of the data set was done prior to any analysis. Groups of respondents, based on their answers to certain questions, need to be selected out for intensive analysis. Several examples based mainly on variables already included in some analysis might be: 293

1. Minority groups

2. Specific religious affiliations

3. "Heavy" versus "light" participants in a particular

pursuit (in terms of frequency of participation).

4. Participants in a particular pursuit versus non-participants

in that pursuit.

5. New participants in a particular pursuit versus those who

have been participating for 10 years or more.

6 . Respondents who have never engaged in a particular pursuit,

but would like to versus those who do not care to.

7. Respondents who indicate that a particular pursuit is a

favorite one versus those who merely participate in i t .

8 . Respondents who agree with a particular AIO statement

or group of statements versus those who disagree.

9. Readers of a particular magazine or viewers of a particular

TV program-type versus "others."

10. Participants in a particular leisure-time pursuit in one

region of the country versus those in another part of the

country. Ditto for city versus suburban versus rural

dwellers; or other demographic variables.

11. BankAmericard holders versus Master Charge holders.

12. Users of credit cards for leisure-time travel versus users

of credit cards for purely "utilitarian" purposes.

13. Credit card holders versus non-holders in terms of their

leisure-time interests and range of pursuits engaged in. 294

In addition to partitioning the data set, an analysis of the conditional relations operating within a sub-set of the data and of the conjoint influences prevailing needs to be conducted. This general procedure has come to be known as elaboration, and is crucial in a thorough analysis of survey data (Rosenberg, 1968:x i-x ii)-

The technique of using factor scores in cross-tabulations or as the dependent variable in a discriminant analysis should be inves­ tigated further. This would be one way of providing a more descrip­ tive picture of the respondents loading heavily on that factor. Also, the use of cannonical correlation to relate groups of pursuits and satisfactions or media should not be entirely ruled out.

The time actually spent in various leisure-time pursuits in relation to money spent, and In relation to proposed use of

(hypothetical) extra-time (too hours per day or 3 day weekend), needs to be investigated. These data, although collected, were not included in any of the present analyses.

An analysis of why people reduced or stopped their p artic i­ pation in various leisure-time pursuits during the last five years also remains to be done. The results of this may indicate whether

"environmental" factors are crucial to participation or whether novelty and the search for new challenge are more controlling.

Finally, the whole area of attitudes toward work versus attitudes toward lei sure-time has not yet been investigated althouqh data on this topic were collected as part of this survey. There is a considerable research tradition in sociology on this topic, but nothing of recent vintage. 295

With regard to future studies, more emphasis needs to be placed on collecting data on larger samples of participants in particular leisure-time pursuits. One of the drawbacks to the present study was the low frequency of participation in certain pursuits, and more specifically the low frequency with which respondents rated a particular pursuit as a favorite.

Future studies would therefore be more likely to make a significant contribution to understanding leisure-time behavior by focusing on specific segments of the population. It would probably be beneficial to focus on specific age, education, racial, or occupational groups in terms of the differing patterns of "satis­ factions" received by these groups from a particular leisure-time pursuit. The whole topic of why people participate in particular leisure-time pursuits needs much more investigation before viable demand and supply forecasts can be made.

Several specific areas in need of further study are:

1. Are individualistic, basically passive, typically indoor

leisure-time pursuits qualitatively different in their

appeal than group-oriented, active outdoor pursuits?

2. If leisure-time pursuits are presented to respondents in

macro-detail rather than in collectivities as done in this

study, do the resulting groupings change, become stronger,

or become even more diffuse?

3. How much of a strain on interfamily relations is

a result of the indoor-outdoor differences in 296

female versus male preferences and the result of different

emphases in satisfactions sought?

4. Are there other types of satisfactions sought which were

not included in this study and which are important to

significant sized segments of the population?

5. What are the unique characteristics of "linking-pin"

pursuits, or pursuits which appear in two or more

otherwise diverse clusters of pursuits?

Attention also needs to be directed toward the development of causal models of leisure-time behavior. The direction of rela­ tionships needs to be identified as well as the conditional or environ­ mental factors. Some work is underway in this area at the University of Waterloo, Ontario in relating the psychological needs and social rate of the recreationist to the prevailing social institutions

(Burton, 1971:298).

Finally, much more needs to be done in the area of use of media in relation to leisure-time pursuits. It is understood from conversations with the Bureau of Outdoor Recreation, that they are particularly interested in the whole communication process between suppliers and users of (in their case) outdoor recreational resources.

It is not clear to them how people become aware of alternative recreational resources, both in terms of actual activities and their physical location. They desire much more information on the level of awareness in various segments of the population regarding extent leisure­ time opportunities. This would certainly seem to be an appropriate area for marketing academicians to investigate. 297

Conclusion

This dissertation has investigated several aspects of leisure­ time behavior. A primary focus has been on attempting to define reachable, practical, market segments of participants in related leisure-time pursuits. A number of findings of interest have re­ sulted, although not the number of clear-cut, highly significant, original findings originally hoped for. I t has, however, been a beginning in an area relatively untouched by marketing academicians.

I t has also given encouragement to the practical u tility of the concept of "satisfactions" received from participating in leisure­ time pursuits. A great deal more work is needed in this area, however. APPENDIX A

QUESTIONNAIRE

298 APPENDIX A

QUESTIONNAIRE

General Interpretive Notes

The copy of the questionnaire presented here is the copy sent to the male head-of-household. The female head-of-household copy was identical except for ( 1 ) being printed on pink paper (male copy on white paper), and (2) the introductory block read "This question­ naire is to be completed by my panel member."

Frequency counts are listed on the questionnaire, for both the female and male respondents, for most of those questions directly analyzed in the dissertation. Questions la., lb., 1c., Id., le.,

2., 4.A., 4.B.I., 11., 12., 22., and 31. have their frequency counts listed. Question 5., although it formed a major basis for hypotheses

H2 and H3, does notlend itself to the listing of frequency counts.

A fewspecific comments on each question for which frequency counts are recorded:

1. Question la.: "Yes" responses are listed first; "No" responses second.

2. Question lb.: Female responses precede the card name and box under "Using i t . . ; male responses are shown after name or box.

3. Question lc.: Female responses are listed to the le ft of each box; male responses (in the same sequence) are listed to the right of the number (5) box.

299 300

4. Question I d .: Female responses precede "purpose;" male responses are listed to the left of the YES box.

5. Question le .: Female responses to the left of each box; male responses to the right and slightly superscripted.

6 . Question 2.: Female responses to the left of the item name; male responses to the right.

7. Question 4.A.: Female responses to the left of the box; male responses to the right.

8 . Question 4.B.1: Both responses listed to the left of the box; female responses pre­ cede the slash-mark, male responses follow.

9. Question 11.: Female responses are shown immediately to the le ft of the box; male responses to the right.

10. Question 12.: Female responses precede the journal name; male responses follow the name.

11. Question 22.: Female responses precede the denomina­ tion; male responses follow the box.

12. Question 31.: Female responses are shown imnediately to the le ft of the box; male responses to the right. 301

CONSUMER MAIL PANELS 323 SOUTH FRANKLIN STREET ■ CHICAGO. ILLINOIS 60606

(3-D1421-2

THIS QUESTIONNAIRE IS TO BE COMPLETED BY THE MALE HEAD OF YOUR HOUSEHOLD FBmtlE FEmaic A s r 4 0 ^ ■ / II 7 ioj la. Do you have any credit cards? Yes n No n — ■(SKIP TO QUESTION 2) (13)

lb. Please indicate which of the following credit cards7 you now have, and for each credit card you now have, whether you find that overall it is being used "m o re ," " le s s ," or "about the same" as it was a year ago.

I now have these Using It. . ^^£edit_cajnk^^_ More Less Same ("X” all that apply) (1) U) (3) A fltf . (14-15) F A) F F Z 8 American Express ...... jy L ]l V - n '7 7 f ] 1 >3 f) /fc (lb) 7 7 0 Cl BankAmericard ...... •/J2[7]2 “ 3fan9<» (17) I A ') o n > 3 Carte Blanche ...... 7 (7)3 - 3 H J (18) 7 Diner's Club ...... *1 (7]4 * 3 P3 3 n ? (19) I 7 S - Master Charge ...... c3"<,[7]5 * *iz ri37 ;?0 n?? ( 2 0 ) Gasoline company credit card . . . .7T7r~lf> - •f‘?(71s'f’ 9 ! [ ] b ' / liS O o-e ( 21) °l Automobile rental card ...... /7 tl]7 * ? .D 2 * n i Airline travel card ...... 23" Cl® " P.D 3 ^ □ 7 ( » □ ' * (23) 3 4 ) Sears. Penney's or Ward's credit card ...... 274*[~]9 ■ /«2(Hr2 ,yo(^!/3 7 (241 2 7 6 Other department store credit card./It.“^0 ■ *.7.-/7 / /07772 /-mlT* (25) z s - Other 2 j i 1- 1 - ■t .- t 7 0.7 /5 n // (2b) (Please Specify)

lc. How im portant or unim portant to you are the following characteristics of credit cards? Please "X" one box for each characteristic that best indicates how important that characteristic is o, e to you.

("X" one box for each characteristic) Credit Card Characteristic FEFIBIE (4) (5) Safer than carrying cash ...... • • Z ° 3 0 [7] G7I7] 31(7! (27) They may be lost or stolen ...... 206(7) (67[_J 5"3[7J *-7(7] /,?y (20 More convenient than checks ...... / 63(7] 173X1 66(7) 4 3 0 & /'7&/3I/6A (29) I may buy m ore than necessary ...... io ) [7] foy(7) 77(7) -3^(7] 12°(7] ?j't'l/i'iZ (30) Can buy now without the c a s h ...... )7*) [7] 4 3 0 . ^ ^ - O 6 7 [I](/7/(2v/‘y')/ 36/ 7,i (31) The interest charges are high ...... 22o [ ] u 3 ~ 0 f>9[7! 3k C 3 ? (7]' '-'W t ?/<■'’/- t 7 (32) The receipts help keep track of spending...... /fa° O l ^ l l ] £ 4 0 72(71 *>S'n/^'-/»,'f/s (33) They contribute to in f la tio n ...... 7S" {3] p/[]22f?[7] 27(7] ^’4*(7]7v62/yTU/gj-/p£' (34) Useful in emergencies ...... 370(7) 4 1 |_j 7 [7] A [7] 3~0^,ef7i/i}’/3 / 7 (351 Get fewer bills each month ...... 132. (7) 79 [_] f'-tT! ^ ° \ 0 ^ (3b) It's hard to tell what is spent ...... 8$" (7) 2*6 7} 7fc‘2[—] S 8 0 8“) I 7" is’S/h? /44 jit i (37) Good when traveling ...... 3 C I 8 0 /Ob [_] 2 4 [_] 75(7] Z & O t'*"! j

Page 2 (3-D142)

Id* For which of the following purposes have you used credit cards or aome other form of credit during 1972* ("X" ALL THAT APPLY)

le« For each purpose you "X'ed", tell me about how often you used any form of credit (credit cards, tlme-payment plans, loans, mortgage, etc.) for that purpose during 1972*

Did You Use Number of Times Credit Used Credit For For This Purpose in 1Q72 This Purpose 1-2 5- o 7-12 More l.i^n D u rin ^ ^ 9 7 ^ Times Tmies 12 Timus

FEM ALE ^ m a 7 § (41 £ m L . a F M p A'l fcl Cash advances...... [_J 7 © L jl' 4 3 0 ^ lO Q 2 II 3 D 3 ' O D 4 i (43) ZPS Outdoor clothing, shoes, boots, gloves, etc...... r~)^79f~~|2 —^ 6 ci r j ^ b .12 Q 2 7' 4 7 0 4 ZZ (44) Drugs, cosmetics, sundrys ...... Q 7JQ 3 ► 3o A b U 2^ 3 > D 3 'i i z n * Zu (45) 0, ; v □□□ - <0 7 Sporting equipment for individual use. . . . □ 77[H4 D 2 ^ ' (46) Boating equipment, parts or service . . . /£Q5 3 I Q 3 * 0 (47) 0

32, Bicycling equipment, parts or service. . . □ -■> '8 '* * (48) □□□ Z D 2 a O D 3 '

Television, radio, stereo or tape equipment, parts or service...... Q *170?" I 7 □ 2 H 2 D3r 0 (49) i 0 \ Carden or lawn care supplies, equipment or service Q 92QS " ■5-JQl” 3 k d 2 * ‘l O 3' S D 4 ? (50) S'S Indoor table games (cards, boxed games, p u ssies) ...... * □ 37Q9* ^ □ 1^' 3 □ 3 “ o n *0 (51)

Z 3 Pool table, ping-pong table, car racing sets, trains, or other large self- n 0 contained indoor games Q I3f~l0 — ► 2 r n i Z (~~l2 O D 3 0 Q 4 (52) 7 7 Photographic equipment, supplies or service (not for business use). * .* ,* * •□ 57QR /

Personal vacation or leisure-time ^ * i airline travel...... • SDQZ —►S'^Ql Z o \ ^ l H Q 3 (55) 2 .S 8 Gasoline, oil, parts and service for your.. q ^

Stayins at a hotel, motel, or lodec while 72, l4? on a vaction ...... □ I03D5—►46(Dl‘H 3<\ D 2 //□ 3 s n * " (58) Admission to a sporting event that you were partlcioatinc in feolf. tennis, bowling, skiing, skating, e tc .). 3-D6-*-3 □ * z n z * 0 0 3 ' 0 o * 1 (59) Eatinz in a restaurant while on a vacation r-. -/S' or other non-business dinine • * ...... , □ t i n t —* -z i D i rt 2 1 0 2 / r n 3 ' 3 i ‘) D * - ‘> (60)

Admission to professional or semi-pro sporting events or races ...... □ ^DB—► J'DI4 1 02* <5 0 3 ° o n 4° (51) Admission to shows, movies, concerts, plays, night clubs, casinos ...... □ /6Q9—► * □1*’ 1 1 □ i* o n* ° (52) Other Icisurc-time related use: . □ /S’DO— ► S □ I s’ 3CJ27 z n * 1 O 0 4 ' (53) (Please Specify) 303

(3-D142) Page 3

2. For which of the following reasons would you consider borrowing money, taking out a loan, or using some form of long-torni credit / 1 am defining "long-term credit'1 as credit for more than 90 days (3 months)* Please ''X'1 all that apply. FEMMJ! FEMMC Atat-C 3*0 Pay medical expenses* ...... • • [ 3 1 <64) 360 I lave optional or corrective surgery or ■4^6 Buy a car ...... dental work ...... <65) 232. Buy home furnishings • * . f *3 2J9Put my children through college or technical school* . . . . * ...... / 7^Pay lbgal bills or a settlement . . . . I fj3

1 6 / Pay piled up b ills ...... *^^04 2 o Buy stocksor b o n d s ...... **\ 0 5 «_ e* *. . 2 / r— „ . . 7 rh/. Z o Stay at a r e s o r t ...... r / . ! “»1 4 7 Buy furs or tc w c lr y ...... / • ® _ tJ ' 9 / 5^ Buy expensive spurting equipment (costing over $150) ...... 2/7G° itito business for m yseif ...... ^ t>

3*}? Buy land or properly...... Q 7 3S2L Buy a house or trailer...... OB 6 2. Take a vacation t r i p ...... 0 9 1/jTlIelp a relative who needs money . . . ^ □ 7 - — - - • /©7Buy a second or vacation home .... 2 B Take a honeymoon tr ip ...... [P9

i 6 Z Pay for an education or special 6-78 training for myself. /S7 • □ 0 /jTOBuy a recreational vehicle, camping Open) Cover cxpensos when my income tra ile r, or boat /SO r . 7‘^IT80 has been c u t ...... (”]R Buy swimming pool ......

3. Over the last year, approximately what percent of vour total household income was spent on Cd. 2 the following categories of household expenses. You do not need to do a lot of calculating* Dupl. but please give each category careful thought In order to get reasonably accurate percentages. 1-8

of Total Household Income

Food (at homo and away from hom e) ...... •. "*■ (9-10)

^lothlng (for all members of the household) (1 1- 12)

Shelter (rent, mortgage payments, utilities, property taxes, repairs, furniture, etc.). . . • r» (13-14)

Transportation (automobile payments, operation and insurance, public transportation) . "!■ (15-lt*)

^avln£8j-iInv££im£I!i£j»££!i-L!!5i££2n£<5 (bank accounts, stocks, bonds, property, all forms of insurance) "li (17-18)

Entertainm ent. Recreation, Travel and Vacations ■ • • < 19-20)

Gifts, Contributions, and Donations* *...... (21-22)

All other expenses ...... (23-24)

(25-2». Total Must Equal 100 ft Open) P a g e 4 (3-D 142)

4. Now, I would like to talk about what activities you like to do in your leisure-tim e or "spare-time" as many people call it. On the next 3 pages is a list of some of the more popular leisure-tim e activities grouped into 3 categories — I, II, and III. For each activity please answer the following questions by checking the proper box.

A. Please "X" the one box which best describes your participation in each activity. That is, please indicate whether. . .

• you have never engaged in the activity and do not care to, or • you have never engaged in the activity, but would like to someday, or • you have engaged in the activity in the past -

B. For each activity you have engaged in the past please indicate. . . 1. The approximate number of times you actually engaged in the activity during 1 9 7 2 . (Note that the^ate£ories_ar£ different for Grou£s 1^ 1^ and III. ) ~ ——~ —

2. Whether you usually -- not necessarily always - participate in the activity with (1) your family, (2) your friends outside your family, or (3) alone.

3. Approximately how long you have been participating in the activity.

(Please disregard for now the two digit code number in front of each activity. You will be using this in a later question. )

oCO 4S» GROUP I B. Participation in Activities {Answer eacii of the following questions for each ("X" One Box for Each Activity} activity you engaged in during 1972) Number of Times Have Been 1. Engaged in 1972 2« Usually Do Wit'i •. Partiiipatini* for: Have Never Have Never Have ("X" One Box) r^^OncHnx^ Engaged Engaged Engaged In This In This In This Activity, Activity, Activity Do Not Would In The ACTIVITY Ca re To Like To Past CODE (U ( 2 ) (3) (2) 13) (4) (I) (2) (3) M ) (2) (31 FFmtZ *(*£ ffimrne * u f female uxte r~1 50 Attending concerts or plays C P *4 7*10*1 3C.1 □27^W64Af30»vJ,i35-ftnn2V/C] 45 □ □ □ 9 ( '7.1 51 Camping by trailer, camper or motor home ...... j ? y □ / « 2 Z Z O W /S&D28^»J0<) fJ<^/D2#0«y>*C!46 □ □ □ lO □ r ; □28 2S% 1—1 52 Camping by tent »«...•* M30W 2/ 2^ 2 9 ——^ 7 l//o l D»lliiOf>kdQM lSO 47 n □ □ a n I □ 29 53 Canoeing, rowing, rafting ??*$ n m /5 3 D 3 0 —' v / i z U p A O '/'O ’/-*□ 48 □ □ □ 12 n □ □30 54 Fishing or hunting ...... Q 72 47QJ) 331 □31^£»,77/76Q»/fO*^n2yAC]49 □ □ □ 13 n □31 3 ST 55 Golf ...... □237 / ° * O l? i o7T7\n □ w/ S i O ^ i 3fc 7[U3t ^^►/2j//4n7‘/v O ‘J/'9C93A/[n52 L_j □ □ H ' r i I" □34 ISI r 1 58 Ice skating, roller skating 01*11 ■?*> O* 0312 7ojja//n0ff 3 □ □ f~i 17 LI □35 59 Picnicking ... * ...... n □ « - I£ G^l >-r rQ 3 ,'t!2e ^?/-f6 □2 / ^ / O j'/ « 0 » / / C 5 4 □ n □ 18 □ □ □36 60 Power boating, water skiing 2fc6 scuba diving ...... 6 22 rC3- 1 □ n □ lO n □ □37 i / r 61 Sailing ...... □ 2fci l9 4 0 > s > 7 7dj3t 73" ^ / 1o/3-JQ 2'/’ ‘ □ >/? □-*/“) C56 r r r -20 □ □ □38 3 3 f 62 Snov-mobiling ...... □ 260 t?C 0 9 r?D3‘. He.V/7 n*/'2C!57 n r . r '2l n □39 3 S Z 63 Snow skiing ...... □ 2‘W / J"C Qy/J 6 1 D » * 2 D58 □ n □ 22 D □ rao I- 1 64 Swimming 1 4 0 7 S' Jt> 0 3° -95-/G4 1^67A3n*'/f'03^ry^.l59 n n □ 27 □ n»i 65 Tennis ...... □ »,-o zoi 0»2 n □ □ 24 n n □42 6t» Square-dancing or other organized dances ...... Z i i 23*) G 8*\ r j ' t Z>'5Ql3 □ □ □ 24 □ □ □43

1—n 67 Other 1 2 l - l I O i 5-2G44ii. □ "«<2 □ n □ 2*. n □ ^ 4 4 (45- (Please Specify) (63-74 Open) 7'tuD.SO 78 793)) run Cd. 4 Open) c h . 3 Dupl. 1-8 Dopl. 1-8 (3-D142) Page 5 CO0 01 (3-D142) GROUP II P age 6

Participation in Activities (Answer each of the following questions for each {nX” One Box for Each Activity) activity you engaged in during 1972) Number of Times Have Been i» Engaged in 1972 _2^ Usually Do With 3. Participating Fort Have Never Have Never Have ("X” One Box) ("X" One Box) ("X" One Box) Engaged Engaged Engaged In This In This In This Activity, Activity, Activity Do Not Would In The ACTIVITY Care To Like To ^ ^ a s t _ CODE (1) (2) (3) fl) (2) .(3) (4) ID (2) (3) o i (2) (3) Ftmuc n*t£ F______E * v /**Ate 30 Attending movies ...... , , . .2 2 .0 2 4 / 0 2 . □ 9 2 5 S7J □ i □ □ « G □ □ 57 31 Attending sporting events (as a spectator) ...... ^ o S J f r 42 024 ^ tg io 2 6 □ □ □ 92 □ D □ 58 32 Automobile modifications, tune-ups, etc ...... 3-T041 s-i □ 112±i^s-y2i D ^„a% jn 6/v n 27 □ □ □ 43 D □ □ 59 33 Playing basketball* football baseball, softball, volleyball handball . . * ...... £3 70/22. 34 0*4 i/2Q i2 3- ^ ! a,/ ' " C i^ /4 2 i y s i n 1‘/f7 n 2« □ n □ 44 □ □ □ 60 34 Bicycling . * ...... ^ ^ O ^ 1 7 2 0 4 1 3 t,(,U I3 j G % Q Z 9 □ □ □ 4=3 n □ □ <>1 35 Bingo, bridge, or sim ilar card games; "boxed” or board games ^ such as Monopoly, Scrabble, etc. I ?□< 2- « 7 nu 3£±*>izon,% n ,y ,p % p 30 p n P 4„ □ □ □ <■2 36 Bowling ...... Q /2/ -9&D27 4/rn 13 7r,.n 31 n p r u 7 □ p □ 63 37 Chess, checkers, backgammon. ,22/0/76 i z n z ° s i z o u , 32 n □ P 4B p n □ 64 38 Church-related activities ...... 7 0 /0 /6 ° ^ □ 1 7 Q‘% n% fD"’A r 33 n n n 4n p P □ 65 39 Collecting coins, stamps, bottles shells, nic-nacs, antiques, etc. 2£Tl \2.bo s-3 □ « 2i□22 38 □ n P P 7 0 44 Racing or rallying (car or bike) 4 ? / ;?2° J?G?2- 3iG2 3 □«/«□ */?□*/«□ 39 □ □ □ G 71 45 Other 2 ZGZ. /cJG24^^‘’/7 □«>/£□ ^G^cG 90 □ G □ □ G 72 (please specify) 79f0R~60 Cd. 4 Dupl. 1 - "• ow 03 GROUP in A. I B. Participation in Activities (Answer each of the following questions for eaeh^ ("X" One Box for Each Activity) >_actWlt^_£oujmga£edtainijdu^n£-J_272J—. Number of Times Have Been _U Engaged in 1972 Usually Do With Participating For! Have Never Have Never Have ("X" One Box! ("X" One Box) ("X" One Box) Engaged Engaged Engaged / In This In This In This / Activity, Activity, Activity Do Not Would In The ACTIVITY Care To Like To Past I CODE (1) / (2) . <3) (1) fS»MIB Ir e 'w e WILE, 70 Creative crafts or handicrafts /fe n /iiE AV>i/r such as painting* drawing. fEi*4l£/M iG sculpturing, sewing, knitting embroidery, candle making.etc.£^(~l?27 3 < > \y » S~40 □ 9— +.Zih-C,Ol74>j3lty,iGl*‘//E }25 □ □ □ 41 □ □ □ 57 71 Driving around for pleasure or sights ceing 3 3 0 4 3 2 1 U 3 «;Q iol£Lr/9 0*% p% pr**ipu □ □ □ 42 □ □ □ 58 72 Exercising, jogging, visiting a nc. Q J i'ihealth spa , 1 1 ? Q J i'ihealth 2 b 4 □ 11 -~ + 2< Jzb0?aJ 2 j0 slh s,0 7s/>l □ 2 7 □ • □ □ « □ □ □ 59 73 Job-related reading or study . . ??r Q/7> r 7 Q ? 9 24 S O 1 2 i 2 8 □ □ □ 44 □ □ □ 60 74 Listening to music from records... tapes, FM or AM radio • • • . . . 0 4 1 <£> OM r c s o 1 3 i / i □ □ □ 45 □ □ □ 61 75 Photography, taking pictures 7^0/(<» 4 6 C P ? 46) □ u£2**/n □'W/JP^AQ-%,P30 □ □ □ 46 □ □ □ 62 76 Flaying the piano, organ or other musical instrument for pleasure/760272 H ZoQ /tJ ?4 7 □ 15 □ ^ x O ^ h O V s , □ 31 □ □ □ 47 □ □ □ 63 77 Playing with children ...... >?□' ?fc □«> ,?4j □ 19^4.3./),- or^-c^xyhio-i 5 n □ □ 51 □ □ □ 67 81 Visiting with friends, partying . . i* D ifc S’ D 7 2olSi./i-//2 □ ^ aD % 0 ,M 3 6 □ □ □ 52 □ □ □68 82 Walking for pleasure ...... S' s-| 0 4 0 4 ^ n 2 i 2 w «nyunr’yanw an □ □ □ 53 □ □ □69 83 Woodworking, metalworking. furniture refinishing, home workshop projects ...... 4?' Q /2 Z ' .d iD 2 4 QC./1 Q /J / .n io □ □ □ 56 □ □ □ 72 (Please Specify) 79'6T?B0 Cd. 6 Dupl. 1-8 (3-D142) Page 7 oCO 308

P ag e 8 (3-D142I

5a* Different people participate in their favorite leisurc-time activities for many different reasons* We are interested in how important some of these different reasons are to you and your parti­ cipation in your favorite leisure-time activities*

Please refer back to question 4 (the three lists of leisure-timc activities). You will notice that ieach activity has a two digit code number in front of it. Please select your favorite 3 activities from Question 4 (any of the 3 lists) and write those activities1 code number and name of the lines below* 11

Write In Code Numbc Write in Activity Name

Most favorite activity .***.< ( 9-10)

Second most favorite activity 11- 12)

Third most favorite activity* (13.-14)

5b. Now, please copy these 3 code numbers over again onto the three lines on the top of the next page marked "most favorite activity", "second most favorite activity" and "third most favorite activity"

^ Then, please ratejeach of the following statements (on Page 9) on how important it is to you as a reason for participating in each of the 3 activities* Please rate each of the statements on a scale of 1 to 5 as follows:

SCALE

1 — Very important to me

2 — Somewhat important to me

3 — Indifferent or don’t know (or the statement does not apply)

4 — Somewhat unimportant to me

5 — Not important at all to me

*86 *67 #48 Moat Favorite Second Most Third Most Example Activity Favorite Activity Favorite Activity

It gives me a chance to be creative 1 •> 4 I like the excitement involved 3 5 2

CONTINUE ON NEXT PACE. . . . (3-D 142 P age 9

Write in Your Activity Numbers Here „ (MUST BE THE SAME AS ON PAGE 8 RateEaclw^^foi^^^Actlvitie 1-5 Most Favorite Second Most Third Most for Each Characteristic: A ctivity F.vortt. Activity Favorite Activity

I feel that I am beinp creative ...... 15 ______9 41 It gives nit* a chance to meet m*w people ...... ' If. 10 42 It gives me a ihanci* to learn about new things* « < ’ 17 11 ! « I like it because it brings me into contact with friends...... 18 12 . 44 It provides mu with a mental challenge; a problem to solve ...... 19 ______13 45 It brings me peace of mind ...... !20 ______14 ; 4b It gives me a chance to experiment my style

of liv in g ...... 21 ______15 . 47 It provides me with an escape from home or family pressures ...... 22 ______36 . 4s

It gives me a chance to develop a sk ill ...... 23 ______17 .48 It brings our family closer together; it helps achieve stronger family ties ...... • • . . 24 — — 18 .50 It gives me a feeling of independence and

self- reliance...... , 25 ______19 51 It giveB me a chance to be alone with my thoughts • « ...... * ...... 20 . 26 . 52 I like it because it is an old familiar activity one with which I have had lots of experience • • . 27 21 . 53 1 like it bucause there is adventure and 22 excitement in i t ...... 28 . 54 It provides an educational experience for my c h ild ren ...... 2

6. Over a period of time, people sometimes drop one leisure-time activity and pick up another - lor many different reasons. They may also reduce their participation in some activities without completely dropping them.

In the last b years, have you (1) completely dropped or stopped doing, or (2) have you reduced your participation in any leisure-time activities which you used to do on a regular basiB?

a. completely dropped or stopped . . Yes Ol No P)2 (9 ) b. reduced your participation ...... Yes C l No LJ2 (10) ^ (II you answered "no" to both of these, please skip to question 7)

.... if you answered "yes11 to either or both of these questions, please refer back to question 4 (the list of leisure-time activities) and write in the code numbers (the two digit mmibieiMnfTont>jsf>>each-actiWit£i!_o£itlios(e_activitLes which you have stopped or reduced your participation on the lines below.

"X" the proper box to indicate whether you have MstoppcdM or just "reduced*1 your participation in it. Then , please select one or more of the "reasons why" from the list below (you may select up to 5 reasons for eacn activity) below and write in the number of the reason (or reasons) on the line beside the activity. You may select up to 5 reasons for each activity. Stopped Reduced Activity Code Number Participating Participation Reasons why you did - sec lis (Write in from Q ues­ tion 4) (11-12) □ 1 □ 2 21 26 (13-14) □ 1 □ 2 22 28 29 (15-16) □ 1 □ 2 23 30 31 (17-18) □ l □ 2 24 32 33 (19-20) □ l □ 2 25 34 35

Reasons Why You May Have Stopped Or Reduced Your Participation

Number Numbe r 01 - The area or facilities closed down 09 • People 1 used to do the activity with 02 - Just lost interest have moved away or lost interest 03 - Became too crowded 10 • My general physical condition prevents me from doing the activity now 04 - The weather has been unfavorable 11 - My present family situation makes it 05 - Have new, different interests difficult to engage in the activity and activities Oh - Moved away from the area or 12 - Became too expensive facilities; it's too far to travel 13 - The need for me activity went away 14 - Don't have enough lime anymore 07 - Took up other activities which prevent m e from doing both 15 - Became too tiring or exhausting 08 - Had an accident which prevents me from engaging in the activity

16 - Other (please specify) 311

P age 11

7. There are 168 hours in the week (7 days of 24 hours). During the average week, approximately, how many of these h airs do you spend in each of the following activities? If you do not spend any hours in an activity, write in "0".

Sleeping, napping ...... hours a week 36-37 Ealing meals {breakfast, lunch, dinner) ...... hours a week 38-39 hours a week 40-41 Working at your job (include all paid employment) . . . hours a week 42-43 Commuting to and from w o rk ...... hours a week 44-45 Other work-related activity (meetings, reading, study, "homework") ...... hours a week 46-47 Housework, necessary home maintenance and lawn care ...... hours a week 48-49 Shopping ...... hours a week 50-51 Playing with or helping your children ...... hours a week 52-53 Reading newspapers and magazine* ...... hours a week 54-55 Watching television ...... hours a week 56-57 5R-59 Hobbies, games, crafts, etc...... hours a week Visiting with friends or relatives ...... hours a week 60-61 Participating in sports or athletics ...... hours a week 62-63 Attending sporting events as a spectator ...... hours a week 64-t>5 Entertainment outside the home (other than sporting i.6-<»7 events) ...... hours a week Other Maior Activities hours a week t.8-69 (Please Specify)

8 . What would you do with an extra 2 hours in your day? What would you do with a 3-day weekend every week? Please ’PC" one or more boxes below or write-in an activity if it does not appear on the list. I would do these I would do these things with an things with a 3- extra 2 hours day weekend

(70-71) (72-73) Rest, relax, loaf, sleep ...... □ i □ l Read, study ...... □ 2 □ 2 Walk, window shop ...... □ 3 □ 3 Work "overtime" at my job or occupation ■ . □4 □4 Do repair work on the house ...... • • □ 3 □ 9 Catch up on household chores, projects . . . □ «. Spend time with family, play with children . □ 7 □ 7 Watch television ...... □ h □ « Listen to music, records, tapes ...... □ 9 □ 9 7 ^ oTh]ho Spend time on outdoor hobbies ...... • • □o □ o Cd, 9 Dup. I -8 □ r □ w 9-10 Opon Socialize, visit friends ...... □ -1 □ -1

►(MORE ACTIVITIES LISTED ON THE NEXT PAGE) 312

P ag e 12 (3-D142) I would do these I would do these Question 8 (Continued) thlng(1 wilh an things with a 3- extra 2 hours in day weekend (14-15 Open)

Go to ballgames, other sporting activities ...... d} 1 □ l ,l6) Go to art gallery, museum * ...... I □2 Engage in some form of individual athletic activity or physical exercise ...... 0 3 Visit relatives ...»...... 0*1 □ 4 Spend time on indoor hobbies ...... O 5 □ 5 Spend time shopping ...... O ^ Do gardening, landscaping ...... O " □ 7 Moonlight, take second job ...... 0 8 □ « Spend time on “creative" activities ...... 0 9 □9 Go camping, hiking, backpacking ...... O o □0 Take weekend trips, visit places I've always wanted to see * « . CjR n Spend time on personal business and errands ...... O l (12) □ l 117) Go back to school, learn a trade or just learn something new ...... 0 2 □2 Become more active in school boards or, PTA ...... 0 3 □ 3 Engage in more political party activities ...... 0*1 □ 4 Work in service, community or charitable organisations ...... 0 5 □ 5 Join a social club ...... 0 6 □6 Attend movies, theater, concerts ...... O ? □ 7 Engage in church-related activities . . . OB □« Work on car, motorcycle, other powered vehicles ...... 0 9 □9 Join some kind of athletic team ...... O o □O Go fishing or hunting ...... O r □ R Become m ore active in youth groups (Scouts, Big Brother, etc.) ...... O l (13) □ l (18 ) Other O □ (please specify) ______o □ □ □

9. Assume that you were given 1 more long weekend (3-day weekend) free of all job-related duties, in the middle of each of the four seasons. That is, you had 1 more 3-day weekend free in the Winter, the Spring, the Summer, and the Fall. What would you be likely to do on each of these four long weekends? (WRITE IN, PLEASE TRY TO BE AS SPECIFIC AS POSSIBLE) a) On a 3-day weekend in the Winter^ I would probably

b) On a 3-day weekend in the Spring. I would probably^

c) On a 3-day weekend In the Summer. I would probably.

d) On a 3-day weekend in the Fall. I would probably

3TT 3 1 3

(3-D 142) P ag e 13

11. For each of the following statements, please in­ One Box For Each Statement dicate the extent to which you personally agree or disagree with that statement. "X" the box that best describes your feelings about the state­ ment. If a statement docs not apply at all to you, "X" the box under "undecided or no opinion".

, (21 (41 £ L / £ £L F n Organized religion should try to deal with social problems . • 214P/76 6 4 0 *3* FED+f 4 IU T 6 Credit cards make it too easy to buy things I may not really n ecl Q ltt /79CW47 47 (140 7 3 0 ” I often work on a do-it-yourself project in my home ...... | \i7? zo/ri/s-i 4 in 5"4 3 5 ^ 4 3 M y work does not involve many deadlines, pressures, and d em an d s...... ( 176 W O 3* /2 Q 7 7 l3 9 U i i r (34)

I express my talents better in my leisure-time activities than In my j o b ...... '.4 ^ 0 * 4 H»U PI / 6* L J 4 4 24G

Television is our primary source of entertainment ...... 0*7° I to O'sT 33029 / 37093 (39) Religion is more important to me today than it was five years a g o ...... ^ Lj/d* t i t e r s ’ P 7093 nbOf° | ‘fyC 'K ’i (40) On a vacation, 1 just want to rest and relax ...... (£6 I 4 /0 * 4 (41) Using credit when you buy something is a bad p rac tic e ...... /^3"0*** tSJQtof 6303"' /F4 0'36j 97026 (42)

When I play a game or a sport, my technique is more Important than winning or losing ...... r~lf°9 20S-O13 /4/Q 92 ■wa*^ /90^7 (43) A cabin by a quiet lake is a great place to spend the summer . ?J4 f l i t r I t 40*49 <'047 64DTS.! 42023 (44) 1 will probably not have more money to spend next year than 1 have now ...... [ J ltl « T 3 4 7 3>7076( ?on73 (45) I admire a successful businessman more than 1 admire a successful artist ...... 7.9 ( 1/7? 4 2 0 % / K O ,j4 )2

1 hate to lose at anything ...... 7 $ 0**4 126 Pdf 72 O 67 173 H '° c M /-0 7 6 (47) People express their real self in their lesure-tlme activities. 19$ 0 9 2 247O203 /34 0

In the past ten years, we have lived in at least 3 different cltlel^ I 760 8 (260(4 | (90*3 4 2 rG iT 6 (51) If people would work harder and complain less, this would be a better country ...... ??* Q 2 * (790*31 j S"4Qif 4 9 0 2 2 30 0 18 (52) Improving the welfare of people is more important than I preserving wilderness ...... V l~W ssoQiztt /16 0 9 1 / 3"3D /flt 3 4 0 9 4 (53) I prefer to participate in individual sports more than team s p o r t s ...... ^ Q 7 1 7070*4' 3 i O « (54)

i i When it comes to my recreation, time is a more important factor to me than money...... W* I |J*4 l72Q Frj 94073 n 4 09C 6 l O « (3b) I sometimes feel the presence of God ...... 0/1*0 I 7 3 0 3 7 ! ? l n > 'P 73“ 022 2 6 0 4 6 (56) Leisure means actively participating in various sports and gan&} I 142 44044 ;/o7 0 *°* f/2 .0 '3 1 1 /74DIZ6 (57) Five years from now, our family income will probably be a lot higher than it is now ...... /7JO*«i 116094 7 4 0 ^ **3DP4 (58) (59-78 Open) 79(515180 314

Page 14 (3-D 14Z)

"X" One Box For Each Statement

C d. 10 Question 11 (Continued)

Whenever possible, 1 prefer to participate in sporting activities, rather than just watch them ...... ^ [" 1 )2 1 I6°0<3? JiO*4 ' i i s n w 7 4 6 0 So ( 9) Religion is less of an influence on society today than it was five y e a rs a g o ...... 7 ° 0 9 2 < ? 7 0 < 4 7 /7 9 Q /2 9 < 2 3 0 6 6 7 2 0 4 9 (10) 1 tend to spend most of my leisure time indoors ...... I 133~ 2 0 7 0 /0 7 3 7 0 3 3 ) 7 2 0 / 5 4 3 6 0 / 5 4 (11) I like excitem ent ...... <.^2 0 < 4 ? 2 4 6 0 /2 5 7 2 0 3 V 7 / 0 6 ? 2 5 0 2 7 (12)

I would not work if I did not have to ...... 0 * 7 6 ■ M O M /2 0 Q 5 -0 < < 0 0 /0 7 / J 5 0 / 3 F (13) When 1 go camping, I enjoy roughing it. . . . I~1 !»9 < 3 3 0 /5 1 /2 o 0 S * ) 1 7 0 6 3 / 6 4 0 75- (14) I am or have been an officer of a society or club ...... 3 4 6 0 / J 9 J 7 0 7 3 3 ) 0 6 4 2 7 0 2 5 /? 2 0 < ? 4 (1 5 ) We have as good a chance to enjoy life as we should ...... 2 4 3 0 /6 7 2 » 2 0 /f lP 3 - 9 0 5-/ 6 7 0 77 2 7 0 2 3 - (16)

I usually charge everything that I can on a trip or vacation . . . ?^f~133 * 3 0 4 2 3 9 0 2 7 < < 4 0 9 6 360 0 2 ? 6 (17) 1 have enough lelsure-tim e ...... ^ 5 0 6 1 7 3 * 0 6 7 5 - 0 0 3 7 < 6 6 0 / 5 / 7 5 J 0 / 6 5 (1 8 ) On my vacation, I like to experience the uncertainty of not knowing what I will encounter from day to day ...... ? 6 1 16*) Z 2 /0 /7 O 7 ) 0 7 / < 2 4 0 /2 5 SI 0 ? 9 (19) I do a lot of repair work on my c a r ...... 6 0 ) 1 1 2 i 0 / / r < 3 7 0 2 * 4 3 0 3 2 3 3 3 0 1 4 3 (20)

1 frequently engage in some form of active recreation after working hours . . / * 0 73 1 2 3 0 1 2 3 1 2 0 0 5 7 /3 o0 / » 7 < 7 5 0 / 2 3 (21) It is important for me to seek God’s will when I make major decisions. . . 0«? < * 4 0 /0 4 0 2 0 ) 3 7 * 0 0 * 7 4 0 0 6 ? (22) It is more important to live graciously, than to save up a lot of money for the future ...... 0 ? ° ) B 0 l 1 f 7 9 0 S - * < 7 4 0 )4 1 f? O 0 7 2 (23) 1 enjoy getting all hot and sweaty vigorously playing a sport . . /5 " 0 79 7 1 0 < 3 4 9 7 0 6 6 < 4 y 0 /e > ' 2 3 5 0 9«) (24)

One of the real joys of life is m astery of a really difficult t a s k ...... i ...... 2.« * 0 Z /Z 2 7 2 0 ) 7 6 76 0 * 5 - 4 9 0 z < < 5 0 2 0 (25) Basically, I’m satisfied with my present lelsure-tim e activities^?2 0<<7 2 6 / 0 1 9 ) 9 3 0 3 9 7 /^ 0 1 0 2 4 3 0 3 6 (26) I watch television more than I should ...... ^ <6 J0I-9O 4 9 0 9 6 <36 0 0 4 < 2 4 0 ?2 (27) In a job, security is more important than m oney ...... <.°90/// 2 t f 0 / f o )<9 0 7 3 7 0 5 0 ? ) 4 0 0 3 ? (28)

1 like to spend my vacations in or near a big city ...... f~lZo r o 0 9 * 7 2 0 4 ? 7 7 3 0 /3 6 2 3 0 0 2 3 4 (29) If I have a choice, 1 prefer to be alone rather than with people . M I I*2 < 2 / 0 ) 2 ? ^ 3 0 5 - ? 2 0 5 0 7 3 5 < 6 2 0 ) 0 9 (30) Idleness breeds troublo ...... 2.O70 I 7 3 < 6 9 0 /3 1 S 6 0 3 Z ) S6 0 5 Y 4 4 0 2 ? (31) When it comes to my recreation, money is a more important factor to me than tim e. ^ 0 5 "0 0 6 0 9 6 9 ? 0 ? P < 9 9 0 )6 4 131 0 ^ 6 (32)

I do not like to go to club or organization meetings...... 'I 0 0 ) 2 9 < * > 0 /2 / 77 0 * 7 / 4 9 0 / / 5 < 0 * 0 6 1 (3 3 ) People should avoid expensive or luxurious products £9 n t9 7 3 6 0 ) 3 3 7 3 3 0 9 9 7?/ 0< 2 < 7 3 0 6 0 (34) Being independent and self-sufficient is important to m e ...... V /f~ \2 3 ? 23/ 0 / i r 5 2 0 3 4 4 5 0 ) 7 /o 0 4 (35) On my vacations, I like to get away from mechanization and automation ...... 0 )4 1 '’70/g/ 93-061 < < < 0 7 3 3 - / 0 2 4 (3 6 ) J3-D142) Page 15

"X" One Box For Each Statement

Question 11 (Continued} _ (1) (2) (3) (4) (5) -£. £_ f ± £_ A1 £ M £_ A1 When 1 gel my credit card hill, 1 usually pay it in full ...... ?7* Q255 1(2.077 f f o n ^ o 4s-nz

I feel very little real involvement in my w ork ...... Hfce0t>2 1Z i s ? n s 4 izpntzfc 22102/1 (41) I would like to see the work week cut to four d a y s ...... /T1 ClAPf io f n n s )3l 0 7 2 12 ~ 1/2 /o 2 0 73 ( 42) On a vacation, it is better to drive on side roads than on superhighways ...... itin iH 1 Z ^ [Jlf6 7 u 1 1 2 ^ 1 7 i n n IIS- (43) I like to surve or eat unusual dinners...... }11 zzrn/ey j r j n n /e /0 /i-7 4 7 ^ / e Z (44)

A "travel-now-pay-latcr" vacation is wrong ...... [""1202 H in n i 3 2 1 ’7' 9S- <~s? 44 0 3 7 (451 I often take work home at night ...... |~|31 J Ti"7 7c z « jn n r (4n) The beat sports are very competitive ...... 0 M o t2 in i3 S I 3 7 ^ 1 1 /2 tr ’72 y e n 40 (47) My major hobby is my family ...... ^ 3 ” 0 /73 /K.ri/i-y 5 - 1 ^ 6 7 I 7 r ~'24 (48)

No matter how fast our income goes up. we never seem to get ahead...... 0 W izdnwy l a n . n j 74063 (49) I admire rugged individualism ...... /5 P 0 /7 7 zzan /?/ I S l f j I I r / n j f 22.02/ (50) 1 would like to take a lesson in my favorite outdoor sport . . . ] D.*~\ \l61 Hffj/07 7( D 7 9 toi 0 7S (51) 1 buy many things with a credit card or charge card ...... *.**I \41 («90Vo 3 7 0 1 1 /410«>2 2l7CZot (52)

My leiaure-tlme tends to be boring ...... ?? 0 7 2 s s - n to 4iT?3P / * 7 n / « 2*10234 (53) I try hard to carry my religion over into all my other dealings in life ...... 0 /°2 U 6 0 9 7 <77 0/27 t t m r r ? r_,? r <54) If It wasn't for the convenience aspect of credit. 1 wouldn't use i t ...... f1/2 0 U P 2 e f 0 ; 71 n r n r s - 771-16q 4 2 ^ 4 3 (55) Most people spend too much time working, and not enough time enjoying life ...... 0/73" t i n t / 13 0 " J7H 2I (56)

I like danger ...... ,...... ? 0 3 1 4 b n w n n 7 b f 03 0 //o 7770/6*" (57) I get paid what 1 am w orth ...... & 7 0 4 1 1 1 r \ m » ? r n r i 707^110 /4?-T I 2- (58) I would rather work alone than In a group ...... (3 7 0 1 K /4 f 0 M 7 1 7 n w w n w lyntz. (591 I would rather spend a quiet evening at home than go out to a p a r t y ...... W 0M P i T j n w i r r~,J7 H 7f-’//0 740 If (60)

Vacations should be planned for the children ...... I V (7~1 V9 u r n m i z ngi iii 1 ' t p n j r (61) I like io go and watch sporting events ...... AV 0 (^ 2 2 3 /0 /f/ 73" r_l47 11 - T l J2 (62) A person should get more satisfaction from his work than from his leisure-time activities...... [7] 72 n/n/jfcws'yr-iqr 1T71 “1 /,*! 7 r » n f i (t>3) Our family is too heavily in debt today ...... 0 ^ 1 b r t U a - n u ;27r i /2/ 2pir'2ir (u4)

A person should share his religious bolicfs with others ...... I V 0 1 k 1 4 1 0 117 Mo 0M»* H D61 77 0 J O (65) If I could start all over again, I would still go into my present kind of w o r k ...... - Q 74 /J70/O6 / 7 j n 6 i 41067 t r n 7 i " („„) I can usually manage to find at least half an hour of free-time . . (other than lunchtimc) during my daily working hours .... 0/3 b !/rt[7i/Ty /0f>nva r i ’ ^ 2 fcfr'92. (67) 79015)80 Cd. 11 Dupl. 1-8 P a g e 16 (3 -D M 2)

12. Below is a list of some of the more popular magazines. Please look over the whole list and place an X in the box beside each magazine that you subscribe to or read regularly — whether at home, at work, or elsewhere. By "read regularly" I mean spend at least 16-20 minutes with almost every issue. Since some magazine titles are very similar to others, please be sure you arc "X'ing" the correct title. /I AIB FBrtALC SIME fg>vne /HAtg (9) (16) 04 A.D. ( 1021 Holiday 10 O ff Penthouse 3 3 20/S”American Girl, The I 2010 Hot Rod Magazine 3 ? dTj2Z Photoplay ■>*" 30/;2 American Home, The 15 30J2 House and Garden/5 06*) Playboy |43 “0/1 American Legion Mapazinejl 4045 House Beautiful C 4G2*f Popular Meehanirs 44 5| 1/6 Am erican Rifleman 3 €• 5 0 0 Ideal Fan I Popular Science Monthly ?.7 6 0 Argosy A I

7f~|277Bettcr Homes and G ardens57 C0O Ideal Woman 2 0 4 Psychology Today ^ Business Week JO 70/3 Ingenue 2 TG^^Rvader's Digest (46 “O'? Car and DrivcriJO 8 0 5 4 Lady 1 s Circle 4 BO^*- Redbnok Magazine 14 0013 Catholic Dipest 5" rQ u l Lady,s Home .Tournal/?7 Clff Saturday Evening Post iCIH/ Chanpinp Times, The 4 4 00(2.Saturday Review f 2 Kiplinper Magazine

( 10)

(HO 102 Columbia S 1_;2 Lion Magazine. The^J Y~'Z Scholastic Magazine O 2 0 ) Complete Woman O Lutheran, The 6 2 :5* Scouting Magazine 304 4 Consumer's Reports i~» 3i 1/6 Mademoiselle 2. 1 '2.0 Seventeen O 405”fa Cosmopolitan S’ 4l~’,2l9McCall,s Magazine 2 I 4 O Signature I 50r-J 1001 /Decorating Ideas 13 So McCall's Needlework 5~'5TO SitnpUcUy Fashion Magazine | 0 4 Ebony 4 ft Crafts 8

706 Elks Magazine 13 *G(2 Mechanix Illustrated 77 (O-SfcSouthern Living (5~ R0(fc Esquire 2 A TOM Mode rn Maturityff t _H Sport 71 3 90Zf2Family Circle .17 CJ53 Modern Romances 6 HTj(0Sport8 A field 4 ? 005”TFamily Health 17 C l2 i Modern Screen 2. ‘G](^ Sports Illustrated C»£ R 0 ir Family Weekly 3 Of. 13 Motor Trend 33 0O2-J Sunset Magazine 13 (11) (14) (17) 1025 Field and Stream 44 iCW My Romance Z If ]# Time 4 i 2024 Flower and Garden Magazine/S' 2f~]/f National Enquirer (0 •if l-T* Today's Education .3 304 Forbes If 3(3^iNational Geographic /PJ 3G(b True ?l 407 Girl Scout Leader I 40 ( National Scene I 4T1441) True Story Magazine 4 5 0 4 I Glamour 3 Nation's Business f JT 5i~l?2CTV Guidet*t3

(G)6© N ewsweck TV Radio M irror 7 O 2 Coif Digest 18 '02*1 Organic Gardening 7G27H.S. News and World Report 44 702J2Good Housekeeping Z t> and Farming 2f O * V. F. W. Magazine I t 80(2 Gourmet 4 f02( Outdoor Life^ff 9Gl2y*Weight Watchers Magazine.? 9022. Grit 10 9(3)33 Parade 2 1 nn?J7Wotnan's Day/4 0023 Hairdo h Beauty 2 Magazine llT )93 Workhasket. The 7 0 Better Family Living 3

13a. If you w ere given a check for $1,000, tax-free, how would you spend it'* If you would spend it on more than one thing indicate about how much you would spend on each.

13b. Some people would like to work more hours a week if they could be paid for it. Others would prefer to work fewer hours per week even if they earned less. How do you feel about this’’

Work more H)1 Work less G2 Work as much as I do now G3 317

(3- 0 1 4 2 ) P age 17

14i For each of the recreational items listed below, please indicate whether you presently own, would like to own, or would not care to own, the item, (22 Open)

Presently Would Like Would Not Care Not Sure or j "X" One Box For Eacli Item Own To Own To Own Have No Opinion

Recreational hom esite ...... □ ! □ 2 □ 3 □ 4 (23) Motor home* ...... □ 2 □ 3 □ 4 (24) Pistol...... □ 2 □ 3 □ 4 (25) Private campsite ...... □ » □ 2 □ 3 □ 4 (26) Truck camper * ...... □ » □ 2 □ 3 □ 4 (27)

Vacation cottage or cabin . • • ...... □ ! 0 2 □ 3 □ 4 (28) Pool table or ping-pong table . • ...... □ ! □ 2 □ 3 □ 4 (29) Camping trailer...... □» □2 □3 □ 4 (30) Swimming pool ...... Cll □ 2 □ 3 □ 4 (31) A ll-terrain vehicle (ATV) . . . . : ...... □ » □ 2 □ 3 □ 4 (32)

Canoe or rowboat ...... □ » □ 2 □ 3 □ 4 (33) Power b o a t ...... □ » □ 2 □ 3 □ 4 (34) Piano, organ or other fairly expensive m usical instrument ...... n i □ 2 □ 3 □ 4 (35) Mobile home ...... □ » □ 2 □ 3 □ 4 (36) Fishing gear (costing over $50)...... □ » □ 2 □ 3 □ 4 (37)

T rail bike ...... □ ! □ 2 □ 3 □ 4 (38) Motorcycle (street bike) ...... □> □ 2 □ 3 □ 4 (39) Houseboat ...... □ « □ 2 □ 3 □ 4 (40) S ailb o at ...... □ « □ 2 □ 3 □ 4 (41) Bicycle ...... □ » □ 2 □ 3 □ 4 (42)

Snowmobile ...... □ » □ 2 □ 3 □ 4 (43) Citizen-Band radio ...... □> □ 2 □ 3 □ 4 (44) Amateur radio equipment. . » • * ...... O l □ 2 □ 3 □ 4 (45) Movie Camera ...... □ 2 □ 3 □ 4 (46) Travel trailer ...... □ » □ 2 □ 3 □ 4 (47)

Rifle/shotgun ...... □ 2 □ 3 □ 4 (48) Hi-fi or stereo equipment (costing over $ 1 5 0 )...... □ ! □ 2 □ 3 □ 4 (49) Golfing equipment (costing over $150) • • 0 1 □ 2 □ 3 □ 4 (50) Bowling equipment (costing over $50). • . 01 □ 2 □ 3 □ 4 (51) Snow skiing equipment (costing over $200) 0 1 □ 2 □ 3 □ 4 (52) Tent camping or backpacking equipment. 01 □ 2 □ 3 □ 4 (53)

Other recreational item □« □2 □ 3 a * (54) (Please Specify)

15, Are you presently employed - cither full-time, part-tim e or both? ("X" ONE BOX)

Yes Ql No QZ—► (SKIP TO QUESTION 22) (55)

16. How many hours a week, on the average, do you work at your prim ary paid job?

Less than 20 hours per week • .[Hi 35-39 hours per week . . * . Q5 20-24 hours per week ...... 0 2 40-44 hours per week . • • .0 6 (56) 25-29 hours per week • • . 0 3 45-49 hours per week • • • « Tl7 30-34 hours per week ...... 04 50 hours or more a week « • | IB 318

P ag e 1 B (3-D142)

17a. Do you have a second part-time or full-time paid job? Yes, L[ J J l ~ i ^ r No D z -► (SKIP TO QU. 18) (57)

17b. How many hours a week, on the average, do you work at this second paid job? ("X" ONE BOX) 1-4 hours per week ...... O l 20-24 hours per week *• . . (~“l5 5-9 hours per week. . • * .0 2 25-29 hours per week . • . . 0 6 10-14 hours per week . • .0 3 30-34 hours per week .• . .0 7 (58) 15-19 hours per week . • . | 14 35 hours or more a week . • 0 8

18. In general, how do you feel about your job? ("X" ONE BOX IN EACH BOW) Ve ry Somewhat Somewhat Ve ry Satisfied Satisfied Neutral Dissatisfied Dissatisfied Type of w o rk ...... D i □ 2 □ 3 □ 4 □ 5 (59) Pay or s a l a r y ...... D i □ 2 □ 3 □ 4 □ 5 (60) Working conditions ...... O i □ 2 □ 3 □ 4 □ 5 (61) Employer or firm ...... Ql □2 □ 3 □ 4 □ 5 (62) The job as a whole ,.« ...... c ii □ 2 □ 3 □ 4 □ 5 (63)

19. If you were looking for a job today, which of the following things on this list would you most prefer or want most in the job; and which would you least prefer? Please rank the items from 1 (most preferred) to 6 (least preferred). Rank from I (most preferred) to An Occupation or Job in Which: 6 (least preferred) Income is steady ...... (64) Income is high ...... _ (65)

There’s Httle risk of being fired or unemployed ...... ______( 66) Working hours are short; lots of free time...... (67)

Chances for advancement are good ...... ( 6 8) The work is important - gives a feeling of accomplishment or satisfaction ...... (69)

20. As near as you can tell, at what age do you think you will RETIRE from your job (your pri­ mary or main job if you have more than one job)? ("X" ONE BOX) Under 45 years of age. • . Q l 60-64 years of age ...... Q? 45-49 years of age .... . QZ 65-69 years of age ...... Q 6 (70) 50-54 years of age . • • • *03 70 or more years of age . »I 17 55-59 years of a g e ...... Q4 I am already retired ...... 0 8 7

Please indicate how many work days of vacation you took in each month of 1972. Do not Cd. 12 include Saturdays, Sundays, or legal holidays in your count for each month. Dup. 1-8

Mdays in J a n ., 1972 ( 9-10) ^days In May, 1972 (17-18) _days in S ept., 1972 (25-26)

_days In F e b ., 1972 (11-12) _days in June, 1972 (19-20) _days in Oct., 1972 (27-28)

—days in M a r., 1972 (13-14) —days in July, 1972 (21-22) _days in Nov., 1972 (29-30)

.days in A p r ., 1972 (15-16) _days In A ug., 1972 (23-24) _days in D ec., 1972 (31-32) 319

(3-D 142) P ag e 19 22. ^ With which one of the m ajor rej^giona or denominations do you primarily identify? i c ? Methodists .... 0 1 9 2 /coBaptists or D isciples ...... 0 7 78" t r i C a th o lic s . i~~l2 l‘u 61 O ther P ro te sta n t 95" Presbyterians or denominations 08 f 3 Lutherans. . . [~~l371 (Please Specify) 33 17 J e w is h...... f~ l4 14 2 r o t h e r ______0 9 t S ~Episcopalians . . 059 (Please Specify) 6 Unitarians. 0 6 7 i r N o n e DO 31

23. How frequently do you attend religious services? Nearly every week . • □ I A few times a year .03 About once a month. . 02 Rarely or never. . . .1 14 34

24. Are you active in any social, civic, school, church, charitable, business, professional or youth groups ? By "active", I mean regularly attend meetings and participate in activities of the group. 0 l^ r No 02—►(SKIP TO QU. 26) 35 25. Approximately how many hours a month on the average do you spend in all these activities combined? 1-3 hours .01 7-10 hours. .03 16-20 hours. .05 ?.l-24 hours ...... 0 7 36 4-6 hours .0 2 11-15 hours .04 21-25 hours, .0 6 More than 30 hours f~~l8

26. How long have you lived in the town or city in which you are now living ?

Less than 1 year . Ol 5-6 years . .04 More than 1-2 y e a r s ...... 02 7-8 years . . 05 10 years . O? 37 3-4 y e a r s ...... 03 9-10 years. .[36

27a. How many times have you moved more than-50 miles away in the last 10 years? None. . .I~11 — -r O n c e ...... 02 Four times . . . I IS (SKIP TO 4 * Tw ice .... 03 Five or more 38 QUESTION 28) Three timea 04 times ...... 0 6

27b. Have you moved nTore_than_50_miles_awai£ from a previous residence in the last 3^ years? Yes O l—^ No 02—►{SKIP TO QU. 28) 39

27c. If yes, how far did you move? 51-75 miles. . .01 201-500 miles ...... 0 4 76-100 miles. .02 501-1, 000 miles ...... 0 5 40 101-200 miles .03 More than 1, 000 miles ’. | 16

28. Do you consider yourself to be a member of a minority group? YcsOL^e No02—►(SKIP TO QU. 29) 41 Which one ? Afro-American . . . . Ol Spanish-Surnamed-American . . . .( 13 Oriental-American. . 02 Other 04 I

320

Page (3-D142)

29. Which of the following do you expect to give you the most satisfaction in your life? ("X* ONE BOX IN EACH COLUMN.) Most Next Most Third Most Satisfaction Satisfaction Satisfaction Your career or occupation ...... □ l (46) O l <47) □ l (48) Family relationships.'...... □ 2 □ 2 □ 2 Leisure-time activities ...... □ 3 □ 3 □ 3 Religious beliefs or activities ...... □ 4 □ 4 □ 4 Participation as a citizen in the affairs of your com m u n ity ...... □ 5 □ 5 Participation in activities directed toward national or international b e tte r m e n t...... □ 6

30. Which of the following sources of information do you typically use when you want infor­ mation about leisure-time opportunities and activities that you might want to partici­ pate in if you knew more about them? (PLEASE "X" ALL THAT APPLY) Radio ...... D l Friends or relatives. . .04 Books ...... O? Television. . .02 Newspapers ...... 0 5 Formal class or (49) demonstration . . 0 8 Magazines. . .0 3 Watching someone do it. Q6 O ther:______(Please Specify)

Generatly speaking, what kinds of television programs (or television movies) do you like or dislike ? Please "X" one box for each type of program.

Like Like Neither like Dislike Dislike very much somewhat nor dislike somewhat very much (1) (2) (3) (4) (5) W e s te r n ...... 1°? □242- 2 io 0/6c /2702S* M O Z 6 .52 0 2 3 (50) Comedy Shows ...... ? K ° 1 12a6 23-} O 2 o | 7t> Q & 4 2/>0-2<- i z o * 1* (51) Detective .how s ...... Q 2li 322 0 2i f

M u s ic a l...... ? 1 7 0 7 9 /TVO/07 ?/>0>22 7/ O/c-o J o O 97 (53) Religion, programs .... Q5"-*" / « □ « / * ^ 0 ' 7<* S-o 0 7 9 9 2 0 " 2 (54) S p o rts ...... ? 7 a - * /J ^ O /2 3 12103"2 //t-O 2' / c s O ' l (55)

Variety shows ...... '?? f~l4r 26.6. 0 Zn4 HI o / 2 o ‘ to Ot<> 2 y O ) 1 (56) Quiz shows or panel shows.* 7.) |~|7j 226 0/>*9 VoQ/22 3-2 - l i O 6 * (57) P la y s ...... J*?UH > 770/22 >26 O ' 2 *? C i ' 0 ' l’2 I S 'O ,c',‘ (58)

"Horror" movies ...... 1 1?2- 7 T O l £ i S 3 O S i /o2 0 ^ 2 3 6 0 /7 2 (59) Concerts ...... ffi* 1 14o / ^ O 9) /3 2 0 //2 to*) □ «/“) H i- O / t r (60) Talk - shows or interviews !'?■ f~|74 24 7 0 /« 7 >e«7 □//& 7 / 0 7 6 5 2 0 / 2 (61)

Real-life d ram a...... 0 ^ 4 ■2 23*0 H6 /«* 0113 5-I 0 7 4 4 4 0 72 (62) Regular news programs . M"? f 1-4/ 2 /fO /6 7 72 0 7 2 a i Q / J to O II (63) Documentaries or special news programs ...... 0 2 /6 2o l-Q /6 7 0 67 43- 02 2 . 25 * 0 2 4 (64)

Mystery or suspense shows‘'.-,.<^O ^ t' 3-7 Qk7 4 2 Q W 4C O 27 (65) Educational programs . . ■ f i ' 1 197 2 ffO > 9 2 />**□« 4 2 6 I 162 2 2 0-70 ?0 / 6 c 4 > "0 '/2 23- O “ -<> (67) h m * FiMJia m m f Av)t£ FFM*r * * } £ femAte 7*QJ2;H(

Thank you very much. If you have any further comments about any questions, or any comments of anv kind about this questionnaire, please feel free to say whatever you'd like <>n the hack of my letter. APPENDIX B

PANEL MEMBER BASIC DEMOGRAPHIC/BIOGRAPHICAL

DATA CARD

321 APPENDIX B

PANEL MEMBER BASIC DEMOGRAPHIC/BIOGRAPHICAL

DATA CARD

Card Column Number Code Item

3-8 Six digit number Panel Member Number

9-10 The area in Brackets indicates Geographic Division.

State Code 11 Connecticut 12 Maine 13 Massachusetts NEW ENGLAND 14 New Hampshire 15 Rhode Island 16 Vermont

21 New Jersey 22 New York MIDDLE ATLANTIC 23 Pennsylvania

31 Illinois 32 Indiana 33 Michigan EAST NORTH CENTRAL 34 Ohio 35 Wisconsin

41 Iowa 42 Kansas 43 Minnesota 44 Missouri WEST NORTH CENTRAL 45 Nebraska 46 North Dakota 47 South Dakota

322 323

Card Column Number Code Item

State Code (Continued) 51 Delaware 52 D istrict of Columbia 53 Florida 54 Georgia SOUTH ATLANTIC 55 Maryland 56 North Carolina 57 South Carolina 58 Virginia 59 . West Virginia

62 Alabama 63 Kentucky 64 Mississippi EAST SOUTH CENTRAL 65 Tennessee

71 Arkansas 72 Louisiana 73 Oklahoma WEST SOUTH CENTRAL 74 Texas

81 Arizona 82 Colorado 83 Idaho 84 Montana MOUNTAIN 85 Nevada 86 New Mexico 87 Utah 88 Wyoming

91 California 92 Oregon PACIFIC 93 Washington

11-15 3 digit code County Code

11-16 3 digit code Standard Metropolitan Statistical Area Code

17 Type of Dwelling Unit 1 Apartment 2 One-family home 3 . Duplex (two-family home) 4 Mobile home (House tra ile r) 5 Other R(&) Not specified 324

Card Column Number Code Item

18 'Ownership of Residence 1 Own 2 Rent 3 Other R(&) Not specified

19 Farm Residence 1 Live on a farm 2 Do not live on a farm R(&) Not specified

20 ' EdUcation Level of Female 1 Did not attend school 2 Went to elementary or grammar school 3 Went to high school or trade school for less than four years 4 Graduated from high school 5 Went to college but did not graduate 6 Graduated from college 7 Have post-graduate degree R(&) Not specified

21 Educati on Level of Husband 1 Did not attend school 2 Went to elementary or grammar school 3 Went to high school or trade school for less than four years 4 Graduated from high school 5 Went to college but did not graduate 6 Graduated from college 7 Have post-graduate degree R(&) Not specified No husband

22 Position of Husband Within Company/ Salaried 1 Owner 2 President 3 Executive 4 Middle Management 5 Supervisor 6 * Non Supervisory

7 Hourly R(&) Not specified No husband/Husband not employed/ Husband employed part-time 325

Card Column ...... Number Code Item

23 Department Husband VJbrks In 1 Advertising 2 Accounting/finance 3 Data processing 4 Engineering 5 Purchasing 6 Manufacturing/production 7 Marketing 8 Sales 9 Maintenance 0 None of these R(&) Not specified No husband/Husband not employed/ Husband employed part-time

24 ' Employment Status of Husband 1 Works for someone else full-time or is temporarily unemployed 2 Self-employed 3 Works for someone else part-timeonly 4 Is not employed (retired) 5 Is not employed (student, disabled, etc.) 7 No husband in household R(&) Not specified

25 OccupatiOn of Husband 1 Professional Workers 2 Managers & Administrators, except farm 3 Clerical & Kindred workers 4 Sales Workers 5 Craftsmen & Kindred workers 6 Operatives, except transport 7 Transport equipment operatives 8 Laborers, except farm 9 Farmers, farm managers, farm laborers & farm foreman 0 Service workers, except privatehouse­ hold X Private household workers R(&) Not specified No husband/Husband not employed/ Husband employed part-time 326 Card Column ...... Number Code ' Item

26 Employment Status of Female 1 Works for someone else full-time or is temporarily unemployed 2 Self-employed 3 Works for someone else part-time only 4 Is not employed (retired) 5 Is not employed (student, disabled, etc.) 6 Full-time homemaker R(&) Not specified

27 " Household Size 1 Uni 2 Two 3 ...... Three 4 Four 5 Five 6 Six 7 Seven 8 Eight or more

28-30 Age of Female (Codes for Month and Year Born)

28 Month of Birth (Female) 1 January 2 February 3 March 4 April 5 May 6 June 7 July 8 August 9 September 0 October X November R(&) December

29-30 Year Of Birth (Female) (LAST TWO DIGITS OF YEAR CODED)

31-33 Age Of Husband 1 Under 25 years of age 2 25 to 34 years of age 3 35 to 44 years of age 4 45 to 54 years of age 5 55 years of age and over 327

Card Column Number Code Item

32-33 ' Year of Birth (Husband) (LAST TWO DIGITS OF YEAR CODED)

34 & 35-36 Age, Sex arid Year of Bi rth of Other Household Member

37 & 38-39 ' Age, Sex arid Year Of Birth of Other Household Member

40 & 41-42 Age, Sex and Year of Birth of Other Household Member

43 & 44-45 ' Age, Sex arid Year of Birth of Other ' Household Member

46 & 47-48 Age, Sex and Year of Birth of Other Household Member

49 & 50-51 Age, Sex and Year of Birth of Other Household Member

Cols. 34, 37, 40, 43, 46 and 4 9 - Combination Age and Sex Code:

Code Code Age Male Female 0-4 ) 7 5-9 2 8 10-12 3 9 13-16 4 0 17-19 5 X(+) 20 and over 6 R(S)

Cols. 35-36, 38-39, 41-42, 44-45, 47-48, 50-51 are last two digits of year of birth of other household members.

52 ’ 'Number'o f'AutOmobi1es Owned 1 One automobile owned 2 Two or more automobiles owned R(&) Not specified 328

Card Column Number Code Item

54 Marital Status 1 Married 2 Wi dowed 3 Divorced 4 Separated 5 Single RC&) Not specified

55 ' Total Household Irii 3 $4,000 to $4,999 4 $5,000 to $5,999 5 $6,000 to $6,999 6 $7,000 to $7,999 7 $8,000 to $8,999 8 $9,000 to $9,999 9 $10,000 to $11,999 0 $12,000 to $14,999 X $15,000 to $24,999 R(&) $25,000 or more

55 ' Population Density arid Degree of Urban­ ization 1 Rural (farm andnon-farm/outside city limits or live in town of population under 2500) 2 Urban (population 2500 - 49,999)

Standard Metropolitan Area (Population 50,000 - 499,999) 3 Central city 4 Urban 5 Rural

Standard Metropolitan Area (500,000 - 1 ,999,999)' 6 Central city 7 Urban 8 Rural

’'Standard Metropolitan Area (2,000,000 and Over) 9 Central city 0 Urban X Rural Card Column Number Code Item

57 Age of Panel Member 1 Under 25 years of age 2 25 to 34 years of age 3 35 to 44 years of age 4 45 to 54 years of age 5 55 years of age and over

79-80 99 . Card Number APPENDIX C

TESTING FOR RECTANGULAR OR PEAKED DISTRIBUTION

OF SATISFACTIONS STATEMENTS

330 APPENDIX C

TESTING FOR RECTANGULAR OR PEAKED DISTRIBUTION

OF SATISFACTIONS STATEMENTS

Rectanqularity

Rectangularity can be determined by a chi-square goodness-of- fit testJ Given a five-point Likert scale, the theoretical distribu­ tion would be one-fifth of the subjects in each cell. For four degrees of freedom, a chi-square of 9.5 or greater would indicate a significant

(at the 5 percent level) departure from a rectangular distribution.

Peaked Distribution

One measure of whether the distribution of responses approxi­ mates a peaked or point distribution centered on the median value of the scale, is the kurtosis of the distribution. Kurtosis is a mea­ sure of the "peakedness" of a normal (curve) distribution, and, as such, its value only represents departure from normality. The ideal distribution of responses on these satisfactions statements should approximate a bimodal curve with some peaking on either side of the median scale valuel In other words, most subjects should have some feeling about the statement, that it either is or is not important to them.

Hhe formula for chi-square is X 2 = ^ o ”fT ^2 where f„ is P f 7 the observed frequency in a cell (scale category) and fy is the theoretical frequency in that cell. The degree of freedom is one less than the number of scale categories. 331 332 This kind of a distribution is approximated by a platik u rtie, or flatter-than-norroal, curve. Platikurtosis is in turn indicated by a kurtosis value of less than three (the value for a perfect nor­ mal curve). Snedecor and Cochran (1967:552) present tables for te s t­

ing the significance of skew and kurtosis as departures from a normal curve.

Unfortunately, a high degree of skewness can also cause a high value of kurtosis. Therefore, one needs to look for combinations of low (non-significant) skewness coupled with high kurtosis as an indi­ cation of a statistically peaked distribution centered on the median scale value of three.

The thirty-two satisfactions statements were aggregated across each of the most popular "favorite activities" for the males and the females. "Most popular" was defined as those activities which were selected as favorites by at least five percent of the sample. This necessitated special combinatorial programming such that if a respon­ dent selected a particular activity as either his most favorite, second most favorite or third most favorite, the vector of satisfac­ tion statements for that activity was summed with all other satis­ factions vectors for the same activity.

This procedure resulted in a summing of the responses of that subset of subjects who had selected activity X as one of their three favorites. Twenty activities met the "most popular" criterion for the females and twenty-four activities met the test for the male sample. REFERENCES CITED REFERENCES CITED

Aaker, David A. Multivariate Analysis in Marketing: Theory and Application*! Belmont, California: Wadsworth Publishing Com- pany, Inc., 1971.

"Affluence Spreading Over U.S. - Findings of a New Study." U. S. News and World Report, December 6 , 1971, pp. 28-29.

"America of 1990, The." U. S. News and World Report, February 14, 1972, pp. 42-43.

Baggaley, Andrew R. Intermediate Correlational Methods. New York: John Wiley and Sons, Inc., 1964.

Bass, F. M.; Pessemier, E. A.; and Tigert, D. J. "A Taxonomy of Magazine Readership Applied to Problems in Marketing Strategy and Media Selection." The Journal of Business XLII, 3 (July, . 1969), 337-363. _ _

Beaman, Jay. Private Correspondence, 1973. See also "CORD andCORD- related Reports, Papers, Notes and Data" available from National and Historic Parks Branch, Department of Indian Affairs and Northern Development, Ottawa, Canada, Spring 1973.

Beckman, Theodore N., and Davidson, William R. Marketing. Eighth edition. New York: The Ronald Press Company, 1967.

Bhullar, Hardeep S. "Personality and Outdoor Recreation: A Study of Outdoor Recreation as Need-Fulfilling Behavior in Blacks and Whites." Unpublished Doctoral Dissertation, University of Georgia, 1970. (Dissertation Abstracts XXI, Vol. 11, 6363-B)

Boyd, Harper W., J r ., and Westfall, Ralph. Marketing Research. Homewood, Illinois: Richard D. Irwin, Inc., 1972.

Bultena, Gordon L., and Klessig, Lowell L. "Satisfaction in Camping: A Conceptualization and Guide to Social Research." Journal of Leisure Research III, 1 (Autumn, 1969), 348-354.

334 335

Burch, William R. "The Social Circles of Leisure: Competing Explana­ tions." Journal of Lei sure Research I, 2 (Spring, 1969), 125-147.

Burdge, Rabel J. "The Development of a Leisure-Orientation Scale." Unpublished Master's Thesis, The Ohio State University, 1961.

Bureau of Outdoor Recreation, U. S. Department of the Interior. 10 Public Forums on Nationwide Outdoor Recreation Planning. Washington, D.C.: U. S. Government Printing Office, 1973.

______. Outdoor America - A Plan for Providing Recreation Opportuni­ ties to the Nation. Washington, D.C.: U. S. Government Printing Office, 16 February 1973.

Burton, Thomas L .,(ed.). Recreation Research and Planning: A Sym­ posium. London: George Allen and Unwin, Ltd., 1970.

. Experiments in Recreation Research. London: George Allen and Unwin, L td., 1971.

Carlson, R. E.; Deppe, T. R.; and MacLean, J. R. Recreation in American Life. Second Edition. Belmont, California: Wads­ worth Publishing Company, Inc., 1972.

Carroll, John B. "The Effect of D ifficulty and Chance Success on Correlations Between Items or Between Tests." Psvchometrika X (No. 1, March, 1945), 1-19.

. "The Nature of the Data, or Howto Choose aCorrelation Coefficient." Psvchometrika XXVI (No. 4, December, 1961), 347-372.

Chase, Stuart. "American Values: A Generation of Chanqe." Public Opinion Quarterly XXIX, 3 (Fall, 1965), 357-367.

Clarke, Alfred C. "The Use of Leisure and Its Relation to Levels of Occupational Prestige." American Sociological Review XXI, 3 (June, 1956), 301-307.

Clawson, Marion. "Statistical Data Available for Economic Research on Certain Types of Recreation." Journal of the American Statis­ tical Association LIV, 285 (March, 1959), 281-309.

Clawson, Marion, and Knetsch, Jack L. Economics of Outdoor Recreation. Baltimore, Maryland: The Johns Hopkins Press, 1966.

Cronbach, Lee J. Essentials of Psychological Testing. Third Edition. New York: Harper and Row, Publishers, 1970. 336

DeGrazia, Sebastian. Of Time, Work and Leisure. Garden City, N.Y.: Anchor Books, 1964.

. "The Problems and Promise of Leisure" in William R. Ewald, Jr. (ed.) Environment and Policy; The Next Fifty Years. Bloomington, Indiana: Indiana University Press, 1968, pp. 112-133.

Donald, Marjorie N., and Havighurst, Robert J. "The Meanings of Leisure." Social Forces XXXVII, 4 (May, 1959), 355-360.

Doolittle, Warren T., and Getty, R. E. (eds.). Recreation Symposium Proceedings. Upper Darby, Pennsylvania: Northeastern Forest Experiment Station, 1971.

Dumazedier, Joffre. Toward a Society of Lei sure. New York: The Free Press, 1967.

Eisenpreis, Alfred. "The Goods for Leisure and Recreation." The Conference Board Record VIII, 7 (July, 1971), 58-61.

E llis, M. J. Why People Play. Englewood C liffs, New Jersey: Prentice-Hall, Inc., 1973.

Emmett, Isabel. "Sociological Research in Recreation" in Thomas L. Burton (ed.), Recreation Research and Planning: A Symposium. London: George Allen and Unwin, Ltd., 1970, p. 73.

Engel, James F.; Kollat, David T.; and Blackwell, Roger D. Consumer Behavior. New York: Holt, Rinehart and Winston, Inc., 1968.

Farina, Alfred J. 0. "A Study of the Relationship Between Personality Factors and Patterns of Free-Time Behavior." Unpublished Doctoral Dissertation, Washington University, 1965. (Disser­ tation Abstracts XXVI, Vol. 8 , 4795)

Ferris, Abbott L. (ed.). National Recreation Survey. Study Report 19. Washington, D.C.: Outdoor Recreation Resources Review Commis­ sion, 1962.

Fisk, George. "Toward a Theory of Leisure Spending Behavior." Journal of Marketing XXIV 2 (October, 1959), 51-57.

. Leisure Spending Behavior. Philadelphia: University of Pennsylvania Press, 1963.

Goble, Ross L. "New Psychometric Measurements for Consumer Credit Behavior" in Philip R. McDonald (ed.), Marketing Involvement in Society and the Economy. Chicago: American Marketing Association, 1959 Fall Conference Proceedings, Series No. 30, 1970, pp. 368-376. 337

"Going to a Park? Your V isit May be Rationed Now." U. S. News and World Report, May 8 , 1972, p. 40.

Gray, David. E. "Identification of User-Groups in Forest Recreation and Determination of the Characteristics of Such Groups." Unpublished Doctoral Dissertation, University of Southern California, 1961. (Dissertation Abstracts XXII, Vol. 9, 3258)

. "This Alien Thing Called Leisure" in Richard W. Harris and David E. Gray (eds.), Leisure-Society-Politics. Davis, Cali­ fornia: University of California, Department of Environmental Horticulture, Proceedings of Park and Recreation Administrators Institute, 1972, pp. 5-5.

Green, Paul E., and Tull, Donald S. Research for Marketing Decisions. Second Edition. Englewood Cliffs, New Jersey: Prentice-Hall, Inc., 1970.

Guilford, J. P. Fundamental S tatistics in Psychology and Education. Fourth Edition'. New York: McGraw-Hit1 Book Company, 1965.

Harmon, Harry H. Modern Factor Analysis. Second Edition, revised. Chicago: The University of Chicago Press, 1967.

Havighurst, Robert J. "Nature and Values of Meaningful Free-Time Activity" in Robert W. Kleemier (ed.), Aging and Leisure. New York: Oxford University Press, 1961, pp. 309-344.

. "The Social Competence of Middle-Aged People." Genetic Psychology Monographs LVI (1957), 297-375.

____ , and Feigenbaum, Kenneth. "Leisure and Life-Style." The Ameri­ can Journal of Sociology LXIV, 4 (January, 1959), 396-404.

Hedges, Janice Neipert. "New Patterns for Working Time." Monthly Labor Review, XCVI (No. 2, February, 1973), 3-8.

Hormachea, Marion N., and Hormachea, Carroll R. Recreation in Modern Society. Boston, Mass.: Holbrook Press, Inc., 1972. ^

Jackson, Royal G. "A Bicultural Study of Value Orientations, Leisure Attitudes and Activity Preferences." Unpublished Doctoral Dissertation, University of New Mexico, 1971. (Dissertation Abstracts XXI, Vol. 12, 6422-A) 338

Johnson, Charles E. "An Exploratory Study of Individual Patterns of Leisure-Time A ctivities." Unpublished Doctoral Dissertation, University of Minnesota, 1964. (Dissertation Abstracts XXV, Vol. 8 , 4798)

Kaplan, Max. Leisure in America: A Social Inquiry. New York: John Wiley and Sons, Inc., 1960.

. "Leisure: Issues for American Business." Paper read at the Seminar: The Economics of Leisure, at the National Associa­ tion of Business Economists, University of Denver, October 26, 1970.

. "A Life of Leisure." Industrial Desiqn XVIII, 4 (Mav, 1971), 18-19.

Klausner, Samuel Z. On Man in His Environment. San Francisco: Jossey- Bass, Inc., 1971.

Kleemier, Robert W. (ed.). Aging and Leisure. New York: Oxford University Press, 1961.

Kotler, Philip. Marketing Management: Analysis, Planning and Control. Second Edition. Englewood Cliffs, New Jersey: Prentice-Hall, Inc., 1972.

Kraus, Richard. Recreation and Leisure in Modern Society. New York: Appleton-Century-Crofts, 1971.

Lane, Sylvia. "Sub-Marginal Credit Risks: The Comparative Profiles and Their Implications." The Journal of Consumer Affairs V, . 1 (Summer, 1971), 24-40.

Lanfant, M. F. "Une Theorie du Loisir Est-Elle Possible? L'Envers de la Question." Society and Leisure I (No. 4, 1970), 21-28.

Langholz, Berno. "Variable Working Hours in Germany." Journal of Systems Management, XXIII (No. 8 , August, 1972), 30-33.

LaPage, Wilber F. "Cultural 'Fogweed 1 and Outdoor Recreation Research" in W. T. Doolittle and R. E. Getty (eds.), Recreation Symposium Proceedings. Upper Darby, Pennsylvania: Northeastern Forest Experiment Station, 1971, pp. 186-192.

Larrabee, Eric, and Meyersohn, Rolf (eds.). Mass Leisure. Glencoe, Illinois: The Free Press, 1958. 339

"Latest on Four-Day Week." U. S. News and World Report, March 20, 1972, p. 82.

"Leisure Boom: Biggest Ever and S till Growing." U. S. News and World Report, April 17, 1972, pp. 42-45.

Levitt, Theodore. "The New Markets--Think Before You Leap." Harvard Business Review LXVII, 3 (May/J-ane, 1969), 53-67.

. The Marketing Mode. New York: McGraw-Hill Book Company, Inc., 1969.

Linder, Staffan B. The Harried Leisure Class. New York: Columbia University Press, 1970.

Lowrey, George A., Jr. "A Multivariate Analysis of the Relationship Between Selected Leisure Behavior Variables and Personal Values." Unpublished Doctoral Dissertation, University of Illin o is, 1969. (Dissertation Abstracts XXX, Vol. 7, 2867-A)

Lucas, Robert C. "The Status of Recreation Research Related to Users." Proceedings of the Society of American Foresters Meeting. Boston, Massachusetts: 1964, 127-130.

Lundberg, George A.; Komarovsky, Mirra; and Mclnerny, Mary Alice. Leisure: A Suburban Study. New York: Agathon Press, Inc., 1969.

Lynch, Merrill, Pierce, Fenner, and Smith, Inc. Leisure: Investment Opportunities in a $150-Bill ion Market. New York: Merrill Lynch, Pierce, Fenner and Smith, Inc., October, 1968.

Lynd, Robert S., and Lynd, Helen Merrell. Middletown. New York: Harcourt, Brace and World, Inc., 1929.

Mandell, Lewis. Credit Card Use in the United States. Ann Arbor, Michigan: Institute for Soda! Research, University of Michigan, 1972.

Market Facts, Inc. Consumer Mail Panels Data Book. Chicago, Illin o is: Market Facts, Inc., 1973.

. Private Communication, 1973.

Mathews, H. Lee, and Slocum, John W. Jr. "Social Class and Commercial Bank Credit Card Usage." Journal of Marketing XXXIII, 1 (January, 1969), 71-78. 340

Maw, Ray. "Construction of a Leisure Model." Ekistics #184 (March, 1971), 230-238.

McDonald, Philip R. (ed.). Marketing Involvement in Society and the Economy. Chicago: American Marketing Association, 1969 Fall Conference Proceedings, Series No. 30, 1970.

McNemar, Quinn. Psychological S ta tistic s. Fourth Edition. New York: John Wiley and Sons, Inc., 1969.

Mercer, David. "The Role of Perception in the Recreation Experience: A Review and Discussion." Journal of Leisure Research III, 4 (1971), 261-276.

Meyersohn, Rolf. "The Sociology of Leisure in the United States: Introduction and Bibliography, 1945-1965." Journal of Leisure Research I, 1 (Winter, 1969), 53-68.

M iller, Norman P., and Robinson, Duane M. The Leisure Age. Belmont, California: Wadsworth Publishing Company, Inc., 1963.

Molyneux, D. D. "A Framework for Recreation Research" in Thomas L. Burton (ed.), Recreation Research and Planning: A Symposium. London: George Allen and Unwin, Ltd., 1970, p. 61.

Morgan, James N. "Family Use of Credit." Journal of Home Economics LX, 1 (January, 1968), 21-22.

Morrison, Donald G. "On the Interpretation of Discriminant Analysis" in David A. Aaker, Multivariate ' .

Moss, William T., and Lamphear, Stephen C. "Substitutability of Recreational Activities in Meeting Stated Needs and Driver of the V isitor." Environmental Education 1 (No. 4, Summer, 1970), 129-131.

; Shackelford, Lois; and Stokes, G. L. "Recreation and Person­ ality." Journal of Forestry, LXVII (No. 3, March, 1969), 182- 184.

Mueller, Eva, and Gurin, Gerald. Participation in Outdoor Recreation: Factors Affecting Demand Among American Adults. Study Report 20. Washington, D. C.: Outdoor Recreation Resources Review Commis­ sion, 1962. 341

Nash, Jay B. Phi 1 osbph.y of Recreati or> and Lei sure. St. Louis: The C. V. Mosby Company, 1953.

National Academy of Sciences. A Program for Outdoor Recreati on Research. Washington, D.C.: National Academy of Sciences, 1969.

Neulinger, John, and Breit, Miranda. "Attitude Dimensions of Leisure." Journal of Leisure Research I, 3 (Summer, 1969), 255-261.

. "Attitude Dimensions of Leisure: A Replication Study." Journal of Leisure Research III , 2 (Spring, 1971), 108-115.

Neumeyer, Martin H., and Neumeyer, Esther S. Leisure and Recreation. New York: A. S. Barnes and Company, 1936.

Peterson, George L., and Neumann, Edward S. "Modeling and Predicting Human Response to the Visual Recreation Environment." Journal of Leisure Research I, 3 (Summer, 1969), 219-237.

Plummer, Joseph T. "Life-Style Patterns and Commercial Bank Credit Card Usage." Journal of Marketing XXXV, 2 (April, 1971), 35-41.

Poor, Riva. 4 Days, 40 Hours. Cambridge, Massachusetts: Bursk and Poor Publishing, 1970.

"Power of the Aging in the Market Place, The." Business Week, November 20, 1971, pp. 52-58.

Proctor, Charles H. "Dependence of Recreation Participation on Back­ ground Characteristics of Sample Persons in the September 1960 National Recreation Survey" in Abbott L. Ferriss (ed.), National Recreation Survey. Washington, D.C.: Outdoor Recreation Resources Review Commission, Study Report 19, 1962, pp. 77-94.

Rabinowitz, Carla B., and Coughlin, Robert E. Analysis of Landscape Characteristics Relevant to Preference. RSRI Discussion Paper Series No. 38. Philadelphia, Pennsylvania: Regional Science Research In stitute, March, 1970.

Rathmell, John M. "The Profit Potential in Customer Leisure and Mobility." Journal of Retailinq XXXV, 4 (Winter, 1959-1960). 178-184, 213“

Reid, Leslie M., and Barlowe, Raleigh. The Quality of Outdoor Recrea­ tion As Evidenced by User Satisfaction. Study Report 5. Wash­ ington, D.C.: Outdoor Recreation Resources Review Commission, 1962. 342

Rengert, Arlene C. "Factors Related to Vacation Behavior." Unpub­ lished Master's Thesis, The Ohio State University, 1970.

Riesman, David. Individualism Reconsidered. New York: The Free Press, 1954.

' The Lonely Crowd. New Haven, Connecticut: Yale University Press, 1961.

. Abundance For What? And Other Essays. Garden City, New York: Doubleday and Company, In c ., 1964.

Roberts, Kenneth. Leisure. London: Longman Group, Ltd., 1970.

Rozeboom, William W. Foundations of the Theory of Prediction. Homewood, Illin o is: The Dorsey Press, 1966.

Rummel, R. J. Applied Factor Analysis. Evanston, Illinois: North­ western University Press, 1970.

Schary, Philip B. "Consumption and the Problem of Time." Journal of Marketing XXXV, 2 (April, 1971), 50-55.

Selltiz, Claire; Jahoda, Marie; Deutsch, Morton; and Cook, Stuart W. Research Methods in Social Relations. New York: Holt, Rine­ hart, and Winston, 1959.

Sessions, Frank Q. Private Correspondence, 1972.

Shafer, Elwood L.; Hamilton, John E. Jr.; and Schmidt, Elizabeth A. "Natural Landscape Preferences: A Predictive Model." Journal of Leisure Research I, 1 (Winter, 1969), 1-20.

» and Moeller, George H. "Predicting Quantitative and Qualita­ tive Values of Outdoor Recreation Participation" in W. T. Doo­ little and R. E. Getty (eds.), Recreation Symposium Proceedings. Upper Darby, Pennsylvania: Northeastern Forest Experiment Station, 1971, pp. 5-21.

Slocum, John W., J r ., and Mathews, H. Lee. "Social Class and Income as Indicators of Consumer Credit Behavior." Journal of Marketing XXXIV. 2 (April, 1970), 69-74.

Smigel, Erwin 0. (ed.). Work and Leisure. New Haven, Connecticut: College and University Press, 1963. 343

Smith, Steve. An Exegesis of Outdoor Recreation Research. Special Research Report. College Station, Texas: Department of Recreation and Parks, Texas A & M University, July, 1971.

Sneath, Peter H. A., and Sokal, Robert R. Numerical Taxonomy. San Francisco: W. H. Freeman and Company, 1973.

Tatham, Ronald L., and Dornoff, Ronald J. "Market Segmentation for Outdoor Recreation." Journal of Leisure Research I I I . 1 (Winter, 1971), 5-16.

Taylor, G. Brooke. "Quality in Recreation" in Thomas L. Burton (ed.)s Recreation Research and Planning: A Symposium. London: George Allen and Unwin, Ltd., 1970, p. 225.

Thorelli, Hans B. "The Public Interest and the AMA: A Policy State­ ment." Chicago: American Marketing Association, Public Policy and Issues Division, January, 1972.

Thorndike, Edward L. "How We Spend Our Time and What we Spend i t For." Scientific Monthly LXIV, 5 (May, 1937), 464-469.

Thornton, Robert L. "Tourism—West From Europe." Business Horizons XII, 5 (October, 1969), 27-34.

"Three-Day Weekends Boost Business." U.S. News and World Report, November 8 , 1971, p. 64.

Tryon, Robert C., and Bailey, Daniel E. Cluster Analysis. New York: McGraw-Hill Book Co., Inc., 1970.

Veblen, Thorstein. The Theory of the Leisure Class. 1918.

Voss, Justin. "The Definition of Leisure." Journal of Economic Issues I, 1 and 2 (June, 1967), 91-106.

U. S. Department of Health, Education, and Welfare. Toward a Social Report. Washington, D. C.: U. S. Department of Health, Educa­ tion, and Welfare, 1969.

Wells, William D., and Sheth, Jagdish N. "Factor Analysis in Market­ ing Research" in David A. Aaker (ed.), M ultivariate Analysis in Marketing: Theory and Application. Belmont, California: Wadsworth Publishing Company, Inc., 1971, pp. 212-227. 344

Wells, William D., and Tigert, Douglas J. "Activities, Interests, and Opinions." Journal of Advertising Research XI (No. 4, August, 1971).

. "AIO Item Library." Unpublished Paper, Graduate School of Business, University of Chicago, August, 1971.

. "Life-Styles in Selecting Media for Travel Advertising." Unpublished Paper presented at 1972 Conference of the Travel Research Association, Quebec, P.Q., Canada, August 15, 1972.

. "Seven Questions About Life-style and Psychographics." Unpub­ lished Paper presented at 55th International Marketing Congress, American Marketing Association, April, 1972.

White, R. Clyde. "Social Class Differences in the Uses of Leisure." The American Journal of Sociology LXI, 2 (September, 1955), 145-150.

Wildland Research Center. Wilderness and Recreation--A Report on Resources, Values and Problems. Study Report 3. Washington, D.C.: Outdoor Recreation Resources Review Commission, 1962.

i

\