AN ANALYSIS OF DEMOGRAPHIC, SOCIOECONOMIC AND ATTITUDINAL CHARACTERISTICS OF THE URBAN IN - HOME SHOPPER Thesis for the Degree of Ph. D. MICHIGAN STATE UNIVERSITY PETER LEE GILLETT 1969 Thumb I III III I III I II III III IIIII ' This is to certify that the thesis entitled AN ANALYSIS OF DEMOGRAPHIC, SOCIOECONOMIC AND ATTITUDINAL CHARACTERISTICS OF THE URBAN IN-HOME SHQPPER“ presented by Peter Lee Gillett has been accepted towards fulfillment of the requirements for ! @413;— degree in Jamel-A ng 0-169 MSU LIBRARIES RETURNING MATERIALS: Place in book drop to remove this checkout from your record. FINES wiII be charged if book is returned after the date stamped beIow. M ABSTRACT AN ANALYSIS OF DEMOGRAPHIC, SOCIOECONOMIC AND ATTITUDINAL CHARACTERISTICS OF THE URBAN IN-HOME SHOPPER By Peter Lee Gillett Despite the expansion Of suburban shopping centers, discount stores and self—service retailing, recent in-home buying gains have been most impressive in urban and sub- urban areas. Between 1955 and 1965, for example, general merchandise mail order sales approximately doubled, while total sales Of general merchandise grew at an estimated rate Of less than A per cent annually. The current retail- ing literature sees several trends encouraging urban in- home shopping: 1. ShOppers are more convenience-oriented than ever before. 2. With suburban growth, heavy traffic, inadequate parking and crowded stores are reducing the convenience Of suburban shopping. 3. In-home merchandisers are upgrading their facilities, merchandise and Shopping services. Peter Lee Gillett The research analyzed the relationships among selected demographic, socioeconomic and attitudinal characteristics of urban female Shoppers and their tele- phone and mail shopping for general merchandise. In-home buying was defined as: (l) telephone Shopping from retail stores; (2) Shopping from general merchandise catalogs by mail, phone or in person from catalog offices; and (3) buying by mail from specialty mail order firms. The research encompossed the following problem areas: 1. What is the nature and extent of in-home Shopping, from various in-home shopping sources? 2. IS the urban in—home shOpper "locked in" away from retail stores? 3. What socioeconomic and demographic characteristics discriminate in-home shoppers from women who do not buy at home? 4. Are in-home Shoppers especially convenience minded? Do in-home shOpperS express unique attitudes toward shopping convenience and the shOpping process that differentiate them from non-shoppers? Personal interviews with 210 female shoppers in Grand Rapids, Michigan provided the research data. Data were analyzed using several nonparametric bivariate tests of significance. Research findings indicated that: Peter Lee Gillett Most urban women had shopped at home during the preceding 11-month period, spending less than $60. Few shOppers are locked in because of their Job, age, preschool children at home, residential location or lack of transportation. Perhaps because of the easy access to shopping areas in Grand Rapids, locked-in shopping is only a minor contributor to in-home buying. In-home buying intensity is related to above average family income and education, but not to shopper age, family life cycle or family Size. Telephone and direct mail shoppers are above average in socioeconomic status, while catalog Shoppers do not differ from women who seldom or never buy at home. Negro shOppers did not differ significantly from white shoppers on in-home spending, although data suggested that Negro shOppers may spend less by direct mail. In—home shoppers do not view the shopping process as less important or enjoyable than do other women. But experienced in-home shOppers, who are also frequent store Shoppers, rate in-home Shopping more favorably over a wide range of convenience, service, merchandise and price factors than do other shoppers. Peter Lee Gillett 6. In-home buying is motivated by a wide range of factors: catalog shoppers buy most often be- cause of merchandise assortment and price, while phone shoppers stress Shopping convenience and impulse motives. Perceived risk of buying mer- chandise without personal inspection is a major deterrent to in-home buying. Many other shoppers avoid the experience of buying at home, particu- larly by phone, because it is unfamiliar. The research found differences between urban in-home shoppers and other buyers which have important implications for market segmentation and merchandising strategy. It is also suggested that the urban in-home market for general merchandise will continue its significant growth in the future. A projected rise in family incomes will be accom- panied by increased demands for shOpping conveniences, and technological innovations such as electronic ordering will make the in-home shopping task even more convenient. AN ANALYSIS OF DEMOGRAPHIC, SOCIOECONOMIC AND ATTITUDINAL CHARACTERISTICS OF THE URBAN IN—HOME SHOPPER By Peter Lee Gillett A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Marketing and Transportation Administration 1969 Copyright by PETER LEE GILLETT 1969 To Karen 11 ACKNOWLEDGMENTS The author wishes to express sincere appreciation for the guidance and financial support which made this work possible. The Chairman of the Committee which guided the research, Dr. Bernard J. LaLonde, contributed substantially to the work. Dr. LaLonde provided initial impetus for the research, and gave his time and encouragement freely throughout all stages of the work. His help is much appreciated. Appreciation is extended to Dr. Donald Bowersox and Dr. Jerome Herniter, the other members of the Committee, for their valuable contributions. The review of the pro- posal by Dr. Bowersox provided several useful changes in the sample design. Dr. Herniter's experience in the catalog merchandising area and his guidance in research design and analysis were particularly helpful. Financial support for the research effort was aided substantially by a research grant from the Department of Marketing and Transportation Administration. iii Productive conversations with several fellow graduate students and colleagues aided the completion of the work. I especially want to thank Dr. Richard A. Scott of the University of Arizona for willingly contributing his time and insights. iv TABLE DEDICATION . . . . ACKNOWLEDGMENTS . . LIST OF TABLES. . LIST OF FIGURES . . Chapter I. INTRODUCTION . Background of the Problem Scope of the Problem Statement of the Problem Hypotheses. Research Design and MethodolOgy Limitations of the Study Potential Contributions of the Research Organization OF CONTENTS 0 0 0 0 O 0 O 9 O 0 O O O O O O 0 II. THE CONVENIENCE-ORIENTED IN—HOME SHOPPER. Introduction Convenience- Orientation in In-Home Shopping Historical Development of In—Home Retailing ShOpping Convenience--Some Theoretical Considerations Shopping Convenience and In-Home Shopping--Some Empirical Evidence Environmental Factors in In-Home Shopping Socioeconomic and Demographic Characteristics of In-Home Shoppers Summary. . O O 0 0 D 0 Page ii iii viii xi 2O 2O 22 24 29 32 3A 37 59 Chapter III. RESEARCH DESIGN . . . . . . . . . Research Design Framework Field Work Procedures . Analysis of Data. . Summary. . . . . Definitions . . . IV. RESEARCH FINDINGS . . . . . . . . Introduction . . . . . . . In-Home Spending Profile . . . . The "Locked- In" Shopper and In-Home Purchasing Patterns. . The Influence of Selected Demographic and Socioeconomic Variables on In- Home Shopping. . . . The Relationship Between Selected Convenience Orientation Measures and In-Home Buying Intensity. . . The Influence of Income Class on In-Home Shopping. . . . . The Relationship Between Shopper Attitudes and In-Home Shopping . . Other Research Findings . . . . . Summary. . . . . . . . . . . O V. SUMMARY AND CONCLUSIONS . . . . . . APPENDICES Introduction . . . General Summary of the Study. Evaluation of the Hypotheses. Summary of Hypotheses . . . General Conclusions. . Implications of the Research Findings . . . . . . . . Suggested Areas for Further Research . O O O O O O O O O 0 O O O O O O O O 0 O O O 0 0 O O 0 APPENDIX A. Personal Interview Schedule, APPENDIX B. Interview Response Cards, and Telephone Interview Schedule . . Socioeconomic Characteristics and In-Home Spending Behavior of Respondents Interviewed by Telephone. . . . . . . . . vi Page 110 119 128 131 1A5 160 16“ 164 164 168 182 184 207 221 226 227 245 Chapter Page APPENDIX C. Map of Grand Rapids Census Tract Area 0 O O O O O O O O 0 0 2M9 BIBLIOGRAPHY. O O I O 0 O O O 0 O O O 251 vii Table 1. 10. 11. 12. 13. LIST OF TABLES The Growth of the General Merchandise Mail Diagram of the Interviewing Process . . . Total Dollars Spent In-Home . . . . . . Total Dollars Spent in Telephone, Catalog and Direct Mail Shopping . . . . . . In-Home Buying Intensity by Availability of Private Transportation During Major Shopping Hours . . . . . . . . . In-Home Buying Intensity by Travel Time from Home to Shopper's Favorite General Merchandise Store . . . . . . . . In—Home Buying Intensity by Accessibility of Public Bus Transportation. . . . . In-Home Buying Intensity by Family Life cyCle O O O O O D O O O O o 0 In-Home Buying Intensity--E1derly versus Other Shoppers . . . . . . . . . In-Home Buying Intensity by Shopper Employment Status . . . . . . . . In-Home Buying Intensity--Part-Time versus Full-Time Employment . . . . . . In-Home Buying Intensity by Annual Family Income . . . . . . . . . . . . In-Home Buying Intensity by Shopper Education Level . . . . . . . . . viii Page 83 97 98 101 103 105 106 108 109 110 111 113 Table Page lu. In-Home Buying Intensity by Family Size . . 11A 15. In-Home Buying Intensity by Race . . . . 116 16. Telephone Buying Intensity by Race. . . . 117 17. Catalog Buying Intensity by Race . . . . 117 18. Direct Mail Buying Intensity by Race . . . 118 19. In-Home Buying Intensity by Number of Telephones per Household . . . . . . 120 20. In—Home Buying Intensity by Number of Shelter Magazines in the Home . . . . 122 21. In-Home Buying Intensity by Number of Newspaper Subscriptions Received . . . 123 22. In—Home Buying Intensity by Number of Credit Cards . . . . . . . . . . 12A 23. In-Home Buying Intensity by Number of Charge Accounts . . . . . . . . . 126 2“. Choice of Telephone versus Catalog Buying by Annual Family Income Level . . . . 129 25. Direct Mail Shoppers versus Other Shoppers by Annual Family Income Level . . . . 130 26. In-Home Buying Intensity by Perceived Inconvenience of Selected Shopping Situations. . . . . . . . . . . 135 27. In-Home Buying Intensity by Attitude Differences Toward Shopping Convenience . 139 28. Comparison of Advantages of In-Store versus In-Home Shopping Source, by In-Home Buying Intensity . . . . . . 1A3 29. In-Home Shopper Type by Annual Family Income 0 O O O O O O O O O 0 O 1’47 30. In-Home Shopper Type by Shopper Age and Family Income Level. . . . . . . . 1A9 ix Table 31. 32. 33. 3A. 35. 36. 37. 38. 39. Page In-Home Shopper Type by Family Size . . . 150 In-Home Shopper Type by Education Level. . 151 In-Home ShOpper Type by Occupation of Household Head . . . . . . . . . 153 In-Home Shopper Type by Shopper Employment Status. 0 O 0 O o o o o o o o 15” In-Home Buying Intensity by Multiple Catalog Ownership . . .p . , , . , 15h In-Home Buying Intensity by Number of Specialty Catalogs. . . . . . . . 156 Extent of Use of Multiple Sources of In- Home Shopping, by Family Income Level . 158 Comparison of Reasons for Last Telephone Order and Last Catalog Order . . . . 159 Comparison of Total Purchases Against Estimated Annual General Merchandise Expenditures. . . . . . . . . . 185 Figure 1. LIST OF FIGURES In-Home Shopping Sources of Supply and Methods of In—Home Ordering . . . The In-Home Shopping Decision Environ- ment. . . . . . . . . . . Shopping Attitude Scale I. . . . . Shopping Attitude Scale II . . . . Shopping Attitude Scale III . . . . Map of Grand Rapids Census Tract Area. xi Page 64 71 133 137 141 250 CHAPTER I INTRODUCTION Background of the Problem The limited ability of any one firm to satisfy consumer demands requires that firms identify market segments and tailor their market Offerings to the potenti- ally most profitable segments. In a market of rapidly- increasing discretionary income and ever-changing consumer wants, however, identifying homogeneous groups of buyers is one of marketing management's most difficult tasks. The objective of the present research is to identify an important and growing market segment, the buyer who shops at home for a Significant portion of her purchases, the in-home ShOpper. Marketing research and the marketing literature have until recently paid relatively little attention to the in-home ShOpper. There is probably some justification for this apparent lack of interest: the in-home market as a percentage of total retail sales is quite small. For example, mail order retail sales, a substantial portion of the total in-home market, have never accounted for more than 1.3 per cent of total retail sales in any given year since 1929.1 Further, the in-home market in the United States has traditionally been the rural family, geographi- cally isolated from retail stores and dependent upon the general merchandise catalog for many shopping needs. With the population movement from a rural to an urban—suburban environment, the rural mail-order market has diminished in importance. But the national in—home market has not declined. In fact, examination of recent retail sales data shows that the in-home market has been growing faster than total retail sales. The major growth has been in the urban—suburban market, where telephone purchasing from retail stores and catalog firms has been steadily replacing mail ordering. Since the growth trend apparently reflects an increasing desire of urban and suburban families to shop at home, retailing efforts tailored to the in—home market would seem to hold considerable promise for future sales and profits. Several problems occur in trying to measure the Size and growth of the in—home market: First, there is little common agreement on what constitutes the "in-home market"; the term is not defined in the retailing literature nor in United States government or trade assoCiation publications. Second, lack of comprehensive data allows only rough esti- mates of the size and growth of the in-home market, and available data are generally understated. But an examination lE. Jerome McCarthy, Basic Marketing (revised ed.; Homewood, Illinois: Richard D. Irwin, InC., 1964), p. 499. of several sources of in-home shopping data reveals an increasingly important consumer market. One measure of the size and growth of in-home buying is presented in Table 1 below. The in-home market for general merchandise, the product category representing the bulk of total dollar sales to in-home Shoppers, is esti- mated by combining United States Department of Commerce data on retail mail-order sales by mail-order companies and mail order divisions with estimates of department store sales out-of-house.l The data show that, after rather 1The magnitude of the mail and telephone order market for general merchandise is understated in Table 1. Sales data for mail order retailing do not include mail orders received by retailers, principally some specialty and narrow line mail order houses not classified by the Census as mail order houses. The U. S. Bureau of the Census has defined mail order houses narrowly, excluding many retailers selling part of their volume by mail by Classifying them with other types of retail establishments. In addition, many mail order establishments are too small or transitory in nature to be included in any statistical compilation. To illustrate the differences in estimates of direct mail sales, Griffin states that there are reliable listings of organizations engaged in mail order selling triple or quadruple the numbers in the 1958 Census reports. (The 1958 Census of Business lists 2550 mail order establishments.) He cites a 1959 report by B. Klein and Company, New York City, claiming that the gross Sales of mail order firms in 1958 totaled approximately $3.5 billion, an increase of about 500 per cent in a little more than ten years; see Harold E. Griffin, Jr., Mail Order Retailing--Economic Consider- ations for Small Operators (University of Connecticut, 1963), pp. 13—15. The 1958 Census of Business, in con- trast, reported mail-order house sales of less than $2 billion. The 1963 Census lists 4,206 mail order houses with total annual sales of $2,378 million; see U. S., Department of Commerce, Bureau of the Census, Census of Business: 1963, Vol. I, Retail Trade—Summary Statistics, Table l: U. S.--l963 and 1958 (Washington, D. C.: U. S. Government Printing Office), pp. 1-6. TABLE l.-—The growth of the general merchandise mail order market: 1951-1967 (in millions of dollars). Mail Department Storeb . Year %g?§?;) Telephone Mail Order Total Total Sales Sales 1951 $1,308 $349 $249 $598 $1,905 1955 1,332 381 272 653 1,985 1960 1,860 509 364 873 2,733 1951 1,932 552 395 947 2,879 1962 2,028 554 396 950 2,978 1963 2,124 584 417 1,001 3,125 1965 2,340 652 466 1,118 3,458 1965 2,581 689* 499* 1,197* 3,778* 1966 2,691 747* 534* 1,281* 3,972* 1967 2,767 800* 571* 1,371* 4,138* a "Mail Order Sales of Department Store Merchandise by Mail Order Companies or Mail Order Divisions," Survey of Current Business, U. S. Department of Commerce. bMail order sales and telephone order sales based on estimates by National Retail Merchants Association, and Stuart U. Rich, Shopping Behavior of Department Store Customers (Cambridge: Harvard University, 1963). H Estimated by trend extension from Source b, 1960- 1964 data above. insignificant gains from the early and middle 1950's, general merchandise mail order sales approximately doubled in the ten years between 1955 and 1965. Mail order Sales have continued to increase, and it is certain that depart- ment store sales out-of-house, notably telephone sales, have also gained. This in-home market for general mer— chandise, probably exceeding four billion dollars in 1967, has grown faster than total retail sales during the last decade. Using similar data plus annual estimates of direct (door-to-door) sales, the Stanford Research Institute reports $7 billion annual in—home sales in 1963, or 9 per cent of total national general merchandise sales. Of the total, catalog sales Show a 6 per cent annual increase, an impressive trend when it is estimated that general merchan- dise sales have increased 3.5 per cent annually in the last decade. Stanford Research Institute predicts that in—home purchases of general merchandise will reach 10 to 11 per cent of general merchandise sales by 1975. Moreover, this is an increasingly urban market; an estimated 70 to 80 per cent of catalog Sales are now in the metropolitan market as compared with 50 per cent or less some fifteen years ago.1 lStanford’Research Institute, Industrial Economics Division, "In—Home Selling Report No. 225," (Menlo Park, California: Stanford Research Institute, October, 1964), pp. 2‘3, 5- Gains in advertising revenue also give some indication of growth in sales volume. Direct mail advertising volume is expanding; the $2.5 billion spent on direct mail adver- tising exceeds the amount spent on either TV or magazine advertising.1 Total expenditures for direct mail adver- tising increased 550 per cent from 1946 to 1964.2 Scope of the Problem The proposed study is a cross-section analysis of certain socioeconomic and attitudinal characteristics of urban shoppers that are believed to be related to in-home buying behavior. For purposes of the study, urban in-home buying will be confined to catalog and direct mail shopping, and buying by telephone from retail stores. The study will also be limited to general merchandise purchases, as de- fined below, and to specialty merchandise typically sold by direct mail houses. General merchandise, broadly descriptive of the majority of items sold through large mail-order catalogs,3 is chosen for analysis for two related reasons: first, the category represents the bulk of merchandise bought at home; second, being so inclusive, it is a category large l"Telepurchasing--Major Trend in Retailing?" Forbes, October 15, 1967, p. 62. 2Charles F. Higgins, "The Booming In-Home Market," The Reporter of Direct Mail Advertising, Summer, 1967, p. ”70 3See Chapter III, Definitions, p. 91- enough to be measurable within the research design limi— tations. Personal services and food items are major consumer expenditure categories specifically excluded from the study. In-home shopping is defined for purposes of the study as buying from samples, advertisements or catalogs. Merchandise is bought by description or from sample dis- plays, not from retail store Shelves. With the exception of catalog store or catalog counter ordering, described below, the complete shopping transaction can take place in the home. The study defines three methods of in—home shopping: (1) mailing orders to any retailer accepting mail orders, (2) ordering by telephone, (3) ordering in person at a catalog store or at the catalog counter of a retail store.1 While the latter method involves leaving the home to place the order, it nonetheless involves catalog ordering from sources other than retail store shelves. Specifically excluded from the study as methods of in-home shopping otherwise meeting the above definition are: (1) buying from direct (door-to-door) salespersons; (2) group in—home buying such as houseware "home parties"; and (3) ordering merchandise as premiums from trading stamp gift catalogs. Since the first two methods are seldom buyer-initiated and are not "long-distance" methods 1See Chapter III, Definitions, p. 90. of in-home buying, they are considered of minimal importance to the hypotheses in the research. Exchanging trading stamps for merchandise is not considered an alternative to in—store buying, for purposes of the study. The study classifies three major in-home shopping sources: (1) large general merchandise catalog firms, such as Sears, Montgomery Ward, and Spiegel, who regu- larly publish catalogs featuring wide varieties of general merchandise items; (2) direct-mail retailers, the smaller or more specialized firms, the bulk of whose business is by long-distance mail; and (3) retail stores offering shopping service via any of the in—home shOpping methods discussed above--usually telephone or mail order service. The large general—merchandise catalog firms offer the widest choice of in-home ordering methods. Their customers may order from catalogs via telephone or mail order or they may place orders in person at catalog stores or at catalog counters in retail stores. Merchandise information is obtained primarily through catalogs, usually two large catalogs per year supplemented by numerous sale catalogs, and through mail stuffers in billing statements. Direct mail firms rely on long-distance mailings for advertising, receiving and filling customer orders. Carefully screened and compiled customer lists are often used. Newspaper and magazine advertising are also heavily used, while radio and television advertising are limited and usually confined to the larger direct mail firms. Some retail stores, particularly the larger depart- ment stores, actively promote mail and telephone orders from their regular merchandise stocks. Newspapers are the advertising medium used most heavily in reaching in— home customers. Radio and television, special catalogs (particularly Christmas gift catalogs), and telephone calls to regular customers are other frequently-used methods of informing in-home shoppers and obtaining telephone and mail orders. In summary, types of in-home shopping to be measured are mail and telephone ordering from catalog firms, retail stores and direct mail firms, and in-person ordering from catalog counters and catalog stores. Specifically ex— cluded from the study are direct (door—to-door) sources of in-home buying, and group in-home buying such as house- ware "home parties." Statement of the Problem Among the many interrelated decisions a shopper makes are choosing how and where to search for merchandise. The urban Shopper has several broad alternatives. She can travel to stores and buy merchandise from retail Shelves. Or if she cannot or does not wish to travel to retail stores to shop in person, she may be able to delegate the shopping task to others, or cancel the 10 trip, or postpone it until more favorable circumstances for store shopping are present. She may also choose to avoid Shopping in retail stores and buy merchandise from her home. The research investigates whether people who shop by mail and telephone differ from other shoppers on a number of socioeconomic, demographic and attitudinal characteristics. A conceptual framework of in-home Shopping behavior will relate the intensity of use of mail and telephone ordering to the key behavioral vari- ables assumed to influence the shopping choice. The research thus has two related objectives. First, it attempts to describe an "in-home shopper" market seg- ment, those women who frequently choose in—home shopping sources and respond to newspaper and magazine advertise- ments and other persuasive messages from in-home shOpping sources. 'Second, through testing a number of related hypotheses within the research framework, the study attempts to explain the reasons why certain Shoppers tend to buy intensively at home. The following questions outline the scope of the research: 1. What is the pattern of in—home buying intensity among different types of urban Shoppers, and among the various methods and sources of in- home buying? 11 2. To what extent is the in—home ShOpper a "locked in" shopper?l 3. Are there distinctive socioeconomic character- istics which are related to preferences for different methods and sources of in—home shopping? 4. Do in-home shoppers express unique attitudes toward the shopping process that differentiate them from persons doing little or no in-home ShOpping? Are in—home ShOppers particularly convenience-minded? Hypotheses The following hypotheses to be tested in the study are grouped for convenience under five broad guiding assumptions. Their order of presentation does not neces- sarily represent a ranking of possible validity or importance. 1. Hypotheses concerning locked in shoppers A. Availability of private (family) automobiles during major shOpping hours is inversely related to in-home buying intensity. B. In—home buying intensity is positively related to perceived travel time from the home to the ShOpper's favorate general merchandise stores. 1See Chapter III, Definitions, p. 93. 12 In-home buying intensity is positively related to distance of Shopper's home from public bus transportation. Shoppers in the "young married with pre- school children" stage of family life cycle buy more at home than other ShOpperS. In-home buying intensity is higher in the "elderly, empty nest" stage of family life cycle than in earlier stages of family life cycle. Working women buy more at home than women not employed outside the home. Socioeconomic and demographic characteristics related to in-home buying intensity A. In-home buying intensity is positively related to amount of annual family income. In-home buying intensity is positively related to education level. In-home buying intensity is positively related to family size. Negro ShOppers buy less at home than white shoppers. Convenience orientation of ShOpper types Heavy in-home buyers are more convenience— oriented than other shoppers, according to the following measures of convenience orientation: l3 In—home buying intensity is positively related to number Of telephones per household. In-home buying intensity is positively related to number of shelter magazines in the home.1 In-home buying intensity is positively related to the number of newspaper sub- scriptions received. In-home buying intensity is positively related to the number of credit cards. In—home buying intensity is positively related to number of charge accounts reported by ShOpperS. In—home ShOppers in lower income classes tend to order from general merchandise catalogs, while higher-income ShOppers tend to order by telephone from department and specialty stores. Hypotheses concerning shopping attitudes A. Heavy in-home buyers perceive their shopping Situations as less convenient than do other shoppers. Heavy in-home buyers perceive selected ele- ments of the shopping process as less con- venient than do other shoppers. 1See Chapter III, Definitions, p. 93. 14 C. Heavy in-home buyers compare in-home Shopping more favorably with retail store Shopping, on selected convenience factors, than do other shoppers. Research Design and Methodology Personal interviews were used to collect data on shopping habits, socioeconomic and demographic character— istics and Shopping attitudes of 210 adult female ShOppers in Grand Rapids, Michigan. Using 1960 census data and personal observation to stratify the population on esti- mated average annual family income, house value and racial composition by city block, four subsample areas were chosen to represent upper, middle, and lower income white, and lower income Negro urban populations. Households were sequentially sampled from a random starting point in each subsample area until a predetermined quota of approximately fifty interviews per area were com- pleted. Interviews were taken during a four-week period in November and the first week of December, 1967. Average length of interviews varied from thirty minutes for house- wives who had not shopped at home during the past year to forty-five minutes for in-home shoppers. After editing and coding all completed questionnaires, survey data were transferred to punched cards for tabu- lation and statistical testing of the research hypotheses. 15 The research hypotheses were tested for statistical significance using several nonparametric tests depending upon the measurement level of the data and the data classifications by the research variables. The X2 test, the Kolmogorov-Smirnov two—sample test and the Kruskal- Wallis one-way analysis of variance tests were all used where appropriate. In addition, other data related to the research hypotheses were collected. Limitations of the Study The results of the study should be interpreted keep— ing the following research design and procedures limi- tations in mind: 1. The research design was confined to one metro- politan area, Grand Rapids, Michigan, during a single four-week time period, November and the first week of December, 1967. To the ex- tent that Grand Rapids is an atypical area or that the interview period does not represent typical shopping conditions, the research findings and conclusions cannot be generalized beyond the sample. 2. The study utilized a quota sampling method in which households were selected from four pre- determined sample areas. In addition, the skip interval used in the Negro subsample differed from that followed in the other three 16 areas. Hence, statistical estimation from sample values to the shopper population of Grand Rapids or any other metropolitan area is precluded. 3. The sample is not a complete cross-section of the general merchandise ShOppers in the metro— politan area: only eligible housewives or adult female heads were Chosen for interviews, other single females, all males, and members of insti— tutions such as college dormitories or Sorori- ties being specifically excluded from the sample. Potential Contributions of the Research In-home shoppers are assumed to be nonrandomly distri- buted among the urban shopper population; that is, in-home shopping decisions result from unique combinations of environmental and attitudinal Characteristics common to in—home ShOppers. The potential contribution of the pre- sent study, like previous research in this area of consumer behavior, is the identification of the in-home Shopper in terms of these relevant characteristics. A twofold purpose is served by this research: 1. Information and insights about the in-home shopping segment may benefit firms offering mail and telephone shopping services. For example, the effectiveness of promotional l7 efforts can be increased by tailoring messages to more precisely identified market segments. The efficiency of catalog distribution likewise depends heavily upon the sender's knowledge of those buyer characteristics closely linked with in-home shopping intensity. 2. New hypotheses and data contribute to the further development of a specific body of knowledge of the in-home market that in turn aids further research in a relatively neglected area of con- sumer behavior research. The in-home Shopper as a market segment has received relatively little attention in the marketing and retailing literature. Several empirical studies of the department store telephone shopper have contributed findings relevant 1 Of these studies, Rich's 1963 to the present research. findings offer the most comprehensive profile of the tele- phone shopper's socioeconomic characteristics, what she buys, how much she spends, and why she shops that way. Less is known about the catalog shopper who orders by phone or mail. At least, non—proprietary data is scarce; lStuart U. Rich, Shopping Behavior of Department Store Customers (Cambridge: Harvard University, 1963); Bell’TeIephone System, Executive Summary from A Study of Telephone Shepping in the Baltimore Area (Philadelphia, Pennsylvania: National Analysts, Inc., 1956); Bell Telephone System, Executive Summary, The Locked-In Shopper, 1963; Bell Telephone System, Executive Summary, 1 San Francisco Women Tell About Shopping in Department Stores, (no date given). 18 Rich found too little mail ordering among his urban samples to reach meaningful conclusions about mail order shoppers. There is some evidence that multiple catalog ownership is increasing in urban areas. It would be useful to explore this evidence further. In summary, the present research will investigate the urban in-home Shopper who utilizes multiple sources of merchandise information to shop by mail or telephone for a relatively important share of her general merchandise purchases. In addition, the choice of a medium-sized city offers potentially useful contrast to previous research; urban in-home shopping studies usually have been conducted in the nation's largest cities, where Shopping conditions and shopper demands may differ from those in smaller urban areas in ways significant for in-home shopping. Finally, the present study re-examines some previous research questions in order to update their findings in a more current market environment. Organization The remainder of the study consists of four chapters: Chapter II reviews the literature relevant to the research problem. Chapter III explains the research design and methodology used to collect and analyze the data. Re— search findings are discussed in Chapter IV, while Chapter V summarizes the findings, describes the in- home ShOpper as a market segment, and suggests potential 19 marketing applications of the findings and their impli— cations for further research. Following Chapter V, the data collection instrument and telephone interview results are presented in the Appendix section. CHAPTER II THE CONVENIENCE-ORIENTED IN-HOME SHOPPER Introduction The consumer behavior literature provided several propositions which guided the research in the selection of the variables reviewed in Chapter II. The propositions are stated as follows: 1. The shopper is a rational goal-seeker whose decision processes can be usefully conceptu- alized as involving three basic sets of inter— related factors: (a) Shopping environment conditions and shopper income and credit cir- cumstances which limit the shopping decision in terms of choice of outlet and type and amount of products, services and conveniences; (b) environmental situations and personal attri- butes which intervene to narrow the affordable choice of product, place, and services. Such variables might include family life style characteristics, distance from residence or place of work to retail stores, cost and availability of transportation and parking, 20 21 shopping hours available, amount and type of merchandise sought, shopping information possessed by or available to the shopper, and so on; (c) the particular set of shopping experiences, values, attitudes and opinions through which the shopper perceives the elements of (a) and (b) above.1 2. The shopping decision results from an attempt to minimize both the commodity costs and con- venience (shopping) costs as perceived by the decision-maker.2 3. In-home shopping is basically convenience shopping; in—home shoppers perceive convenience costs as an especially important element in the shopping decision. Since the research is concerned with investigating Specific hypotheses based largely on the third proposition, Chapter II reviews the literature on convenience shOpping, paying particular attention to variables assumed to be important in describing or explaining in-home shopping behavior. The first section explores the evidence concerning the influence of shopping convenience on Shopping decisions. 1See Chapter III, pp. 70-73 for a further discussion of the conceptual framework used in the research. 2See p. 31 of this chapter. 22 The second section briefly traces the interrelated influences of environment and the consumer's shopping demands on the development of modern in-home retailing from its rural origins. Section three examines in detail the literature pertaining to the research vari- ables and attitude factors. The final section summarizes research findings on the in-home ShOpper and her decision environment. Convenience—Orientation in 'InéHome'ShoppIng The consumer, without knowing it, is the agent of change in marketing processes and techniques. That consumer, often acting in the grip of social and economic changes, has caused retailers, whole- salers, and manufacturers to drastically change their products, their methods of selling as well as the sales environment itself.1 The present study likewise sees the develOpment of modern retailing, and the growth of in-home retailing in particular, as basically a response to the consumer's changing life style. In-home retailing is viewed as offering shopping services and conveniences increasingly demanded by urban consumers as their desire and ability to pay for them has risen. Understanding and predicting present and future change in retailing and market insti— tutions, then, requires a thorough knowledge of the 1Robert D. Entenberg, "Socioeconomic Change and Retail Management: Present and Future," in Managerial Marketing: Perspectives and Viewpoints, ed. by Eugene J. fiélley and William Lazer (Homewood, Illinois: Richard D. Irwin, Inc., 1967), p. 507. 23 consumer and the changing social and economic environment influencing his life style. But as with any ex post facto investigation of phenomena, difficulties arise in establishing causal relationships. One serious limitation is the inability to control or account for all intervening variables that may be involved in any given relationship. For example, the current patterns of retailing structures and functions result from many influencing factors; the particular state of retail competition and the actions of competitors, the cost of land and capital, zoning laws, historical patterns of retail distribution and commercial dominance all play a part in businessmen's decisions regarding the location and design of shopping centers. One recent empirical study concludes, for example, that heavy reliance on existing theories of consumer convenience demands to predict the location of a shopping center is presently less satis- factory than relying on a wide range of institutional considerations.l With these limitations in mind, the following section reviews the historical development of modern in—home retailing, taking the point of view that the provision of shopping convenience has been the factor central to the growth and change in in-home retailing institutions and methods. 1Donald L. Thompson, "Consumer Convenience and Retail Area Structure," Journal of Marketing Research, (February, 1967). p- 43. 24 Historical Development of "In—Home'Retailing Rural Origins of the Mail—OrderrMarket The historical development of modern in-home retail- ing in the United States can be explained as a continual response to technological innovation, industrialization and urbanization and their effects on consumer life styles and market demands in a competitive retail environment. To understand the place of in—home selling in retailing history, it is useful to begin with the consumer market in the 1870's, a period during which Montgomery Ward opened the first full-line mail-order house in 1872.1 First, it Should be pointed out that from the post-Civil War period on, the nation has witnessed the steady trans- formation from a rural, agrarian society into a predomi- nantly industrial and urban environment. In terms of population and buying power, the urban market has grown significantly, while proportionately the rural market has been steadily declining. Nonetheless, until about 1910 more than half the national population was still rural and farm income was rising steadily. Thus the rural market was large and growing during this period of significant lBoris Emmet and John Jeuck, Catalogues and Counters (Chicago: The University of Chicago Press, 1950), p. 19. The "full-line" mail-order house, like department stores, offers relatively complete lines of general merchandise. 25 industrial expansion, particularly in the western regions. Small-town retailers and country stores served most of the needs of the rural market. Although urban areas offered wider assortments of merchandise than rural or small town retailers could carry, farm families isolated by distance, slow transportation and long work— ing hours generally found urban shopping quite incon— venient. Mail order provided farm families convenient buying from wider assortments of general merchandise than many small town retailers could offer. There is general consensus in the retailing liter- ature as to the major factors contributing to the early growth of mail-order retailing: the spread of a national railroad network, the adoption of an inexpensive, rela- tively efficient postal system, the high literacy rate, the increased use of advertising, the inefficiencies of the local merchant, and rapid industrialization leading to a buyer's market were together all contributing to a favorable environment for mail-order retailing. The mail— Order business flourished in the late nineteenth century, and quickly became dominated by several giants in the field, notably Sears, Roebuck and Company, and Montgomery Ward. Sears' sales, for example, rose from $137,743 in 1891 to 1 over $60 million by 1910. By 1918 there were 2,500 lIbid., pp. 172-173. 26 mail-order houses in the United States; 850 of them had annual sales of over $100,000. In-Home Selling to the Urban Market But after the turn of the century urban migration and immigration were rapidly creating a predominantly urban market, and department stores came into direct competition with the mail-order houses as suppliers of Shopping convenience. The rapid growth in urban shopping and the consequent revolution in retailing was enhanced by two major advances in transportation and communications: the birth of the private automobile and the consequent growth in the public highway system, and the telephone. Both had a major impact on in-home retailing. The private transportation system made downtown stores accessible to urban and rural shoppers alike, while the telephone was a technological innovation that simply replaced mail—order as the most convenient way to shop at home. In order to compete in the urban market, some of the catalog firms responded by changing their merchandise lines to appeal to both the rural and urban shopper, inStalling telephone ordering facilities, and opening retail stores. Sears, beginning the trend away from complete reliance on 1Paul H. Nystrom, Economics of Retailing (New York: The Ronald Press, 1930), p. 185. 27 in-home sales, opened its first store on the outskirts of Dallas, Texas in 1910.1 In-Home Retailing Response to the Suburban Movement POpulation pressures on cities and the advent of the private automobile as the major source of transpor- tation led to a rapid growth of suburban areas, and retailing responded to the changes in market demands. The "explosion" of cities into their suburbs brought with it a multitude of related retailing changes, the most striking response being the still-continuing develop- ment of the planned shopping center. But the trend to decentralized retailing was neither smooth nor immediate. As McNair states, Stores have, in some instances belatedly, followed their customers, and decentralization of retailing facilities has been the order of the day; mail- order stores, specialty stores, and chains began it; and department stores, slow to join the pro- cession because of tradition and preconceived ideas, have in the postwar period swung heavily to sub- urban branch operations. At the same time it has been necessary to meet changed buying habits, since shopping is no longer a major diversion, but rather a task or chore to be performed as expeditiously as possible.2 _ Catalog selling continued to hold its small Share of the urban market, with telephone ordering steadily 1Ibid., p. 184. 2Malcolm McNair, "Significant Trends and Developments in Postwar Period," in Managerial Marketing: Perepectives and Viewpoints, ed. by William Lazer and Eugene J. Kelley (Homewood, Illinois: Richard D. Irwin, Inc., 1962), p. 489. 28 replacing mail—order. Beginning in the 1930's, and particu- larly during the post-World War II period, the mail-order firms, now miS-named as their suburban stores grew in number, adjusted their marketing strategies to capture the attention of the affluent middle-class urban and suburban markets, while retaining the still-important rural customer. Style and fashion merchandise were stressed in both catalogs and stores; merchandise lines were upgraded and tailored to urban tastes. In-Home Retailing in RecentIYears The last several years have witnessed a renewed growth in catalog sales to urban—oriented customers. Montgomery Ward, for example, has increased the number of its catalog stores, particularly in smaller towns and suburban areas where the firms have no retail stores, and catalog sales have become the fastest-growing part of Ward's business.1 The success of catalog sales might be linked to several market trends. First, the suburban shopping center, which responded to shoppers' convenience needs more fully than could the congested, increasingly-distant down- town areas, is today often faced with the same crowded conditions and inadequate service that have plagued much downtown shopping for decades. Thus in-home shopping may lHiggins, "The Booming In-Home Market," p. 47. 29 offer relatively more convenience today than in several decades. Second, much catalog sales effort has been directed toward non—urban areas, the smaller towns and fringe areas beyond the suburbs that for some time have been experiencing retail sales growth rates exceeding that of suburban areas.1 Direct mail sales have also thrived in recent years. The rising affluence of the consumer has created new markets for unique, specialized products and services in which marketing specialists like direct mail firms can profitably compete. In response, direct mail marketing has acquired new technology and methods of efficiently locating market segments, advertising to them, and filling mail orders. Shopping Convenience-ASome Theoretical ' Considerations Neoclassical economic theory holds that economic decisions are largely a function of utility and disutility considerations. Utility theory has been applied in examin- ing the role of convenience in Shopping decisions.2 For lEli P. Cox and Leo G. Erickson, Retail Decentrali- zation (East Lansing, Mich.: Bureau of Business and Economic Research, 1967), pp. 5-20. 2Leo Aspinwall, "The Characteristics of Goods and Parallel Systems Theories," in Managerial Marketing: Perspectives and Viewpoints," ed. by Eugene J. Kelley and William Lazer (Homewood, Illinois: Richard D. Irwin, Inc., 1967); Wesley Bender, "Consumer Purchase Costs-~Do Retailers Recognize Them," Journal of Retailing, 30 example, on a highly conceptual level, Aspinwall's red- orange-yellow Characteristics of retail goods were related both to their channels of supply and the amount of con- sumer research involved. Thompson suggests that one of the first applications of utility theory to marketing began with Parlin's convenience goods—-shopping goods classification scheme for retail merchandising.l From Parlin's original classification, Copeland2 added 3 Specialty goods, and Holton and Bucklinu have appraised XL (Spring, 1964), 1-8, 52; Richard N. Cardozo, "An Experimental Study of Consumer Effort, Expectation and Satisfaction " Journal of Marketing Research, II (August, 1965), 244-249; Anthony Downs, “A Theory of_Consumer Efficiency," Journal of Retailing, (Spring, 1961), 6-12; Eugene J. Kelley, "The Impoftance of Convenience in Con- sumer Purchasing," in Managerial Marketing: Perspectives and Viewpoints, ed. by Eugene J. Kelley and William Lazer (Homewood, Illinois: Richard D. Irwin, Inc., 1967), pp. 155—162; William J. Reilly, The Law of Retail Gravi- tation (New York: William J. Reilly Company, 1931); Thompsop "Consumer Convenience and Retail Area Structure," pp- 37- o lCharles Coolidge Parlin, "The Merchandising of Textiles," (1915), reprinted in Marketing in Progress: Patterns and Potentials, ed. by Hiram C. Barksdale (New York: Holt, Rinehart and Winston, Inc., 1964), pp. 297- 312. 2Melvin T. Copeland, Principles of Merchandising (Chicago: A. W. Shaw Co., 1925). 3Richard H. Holton, "The Distinction Between Con- venience Goods, Shopping Goods, and Specialty Goods," Journal of Marketipg, XXIII (July, 1948), pp.'53-56. “Louis P. Bucklin, "Retail Strategy and the Classi- fication of Consumer Goods," Journal of Marketing, XXVII (January, 1963), pp. 51-56. 31 and refined the classification further, Bucklin adding the concepts of convenience, shopping and specialty stores. Kelley believes that the consumer attempts to mini- mize both product costs and convenience costs in making shOpping decisions, and suggests that convenience costs are becoming more important as patronage determinants.l Reilly's law of retail gravitation resulted from some early attempts at quantifying convenience cost importance in retail trade area drawing power. It is interesting to note the importance attached to downtown Shopping inconvenience early in the days of the private automobile. Reilly stated in 1921: But in connection with the centralization of markets for style goods, a noticeable reaction has already begun. The use of the automobile has resulted in such congestion in the downtown section of our larger cities that the inconveniences in- volved have tended to repel rather than to attract retail trade.2 A Similar conclusion was reached by Frederick, who explained the rise in telephone shopping and predicted a suburban Shift in retailing from his observations of urban shopping congestion.3 1Kelley, "The Importance of Convenience in Consumer Purchasing," p. 155. 2William J. Reilly, Methods for the Study of Retail Relationships (Austin: University of Texas Press, 1929] reprihted 1959), p. 35. 3J. George Frederick, Selling By Telephone (New York: The Business Bourse, I928). 32 Utility theory notions of convenience costs have not always been upheld in empirical research on shopping behavior. Cardozo found, for example, that increased shopping effort led to increased satisfaction with the product, a finding that suggests the relevance of dissonance theory to the shopping decision problem.1 Shopping Convenience and In-Home Shopping-- Some Empirical'Evidence There is a general consensus in the business litera- ture that shopping convenience is the key factor behind the recent growth of in-home shopping. Recent articles have pictured the urban Shopper as impatient with the deteriorating level of convenience and service she en- counters even in suburban ShOpping.2 The modern shopper is depicted as being concerned with saving time, as a result of her increasing tendency to work or to be "locked in" at home. The business literature draws most of its conclusions about the convenience-minded urban ShOpper from research studies in two prominent areas of retailing, planned shopping centers and telephone selling. Jonassen's 1955 study of Shopper attitudes and be- havior with respect to downtown versus suburban shopping lCardozo, "An Experimental Study," p. 248. 2"Telepurchasing——Major Trend in Retailing?" Forbes, (October 15, 1967), pp. 56, 61-63; Higgins, "The Booming In-Home Market," pp. 47-50; Grey Matter, Vol. 38, No. 9, September, 1967. 33 found that downtown shopping was considered inconvenient in terms of parking, traffic and crowds; the popularity of suburban shopping was attributed largely to the rela- tive absence of shopping inconveniences.l Downtown stores, because of their wider assortment of high quality merchandise, drew shoppers in spite of shopping incon- veniences. Similar studies in other cities have agreed substantially with Jonassen's conclusions.2 Telephone Shopping studies also affirm the importance of added convenience in the decision to shop by telephone. In Rich's survey of department store shopping, over 90 per cent of a sample of New York and Cleveland telephone shoppers claimed convenience as the major attraction of telephone shopping.3 They listed crowds, boredom and fatigue, making arrangements and getting to the store, and difficulty in finding merchandise and getting waited on as major inconveniences of store shopping. Several telephone Shopping studies sponsored by Bell Telephone agreed substantially with Rich's findingsf‘l 1C. T. Jonassen, The Shoppinngenter Versus Downtown (Columbus, Ohio: Bureau of Business Research, The Ohio State University, 1955). 2For example, George Sternlieb, The Future of the Downtown Department Store (Cambridge, Mass.: Harvard University Press, 1962). 3Donald F. Cox and Stuart U. Rich, "Perceived Risk and Consumer Decision Making—-The Case of Telephone Shopping," Journal of Marketing Research, (November, 1964), p. 7. ’ “Bell Telephone System executive summaries from: A Study of Telephone Shopping in the Baltimore Area; 34 In the Baltimore study, one—third of the shoppers reported experiencing barriers to shopping in person; almost half of the shoppers claimed they postponed shopping trips be- cause of crowds or public transportation problems.1 Another Bell study found 36 per cent of a nationwide sample of department store and discount store ShOppers "locked in" on any average day, usually by transportation problems, illness in the family, bad weather, no baby- sitter, or outside employment demands on their shopping time.2 Environmental Factors in In-Home Shoppipg The product plays a significant role in the in-home Shopping decision. Some general merchandise items are almost never purchased by mail or phone. There is a definite hierarchy of "perceived risk"3 in buying certain products in lieu of personal inspection which appears to hold for the majority of shoppers.LI Most furniture, The Locked-In Shopper; 1101 San Francisco Women Tell About Shopping in Department Stores. 1A Study of Telephone Shopping in the Baltimore Area. 2The Locked-In Shopper. 3See p. 58 for a definition of perceived risk. uCox and Rich, "Perceived Risk and Consumer Decision Making--The Case of Telephone Shopping," p. 504. 35 women's wearing apparel, almost any items which are usually tried on or matched for style, color, size and fit are seldom bought by phone. Linens, Children's clothing, and small appliances are examples of products that shoppers consider much less risky to buy without personal inspection. There is some speculation in the literature that many products today involve less purchase risk as con- sumers are becoming more familiar with product attributes. Several marketing scholars have hypothesized that the continuous buyer's market and increasing consumer incomes are lessening the distinction between shopping goods and convenience goods. The result has been less comparison Shopping on product attributes and an increasing emphasis 1’2 In-home on buying at the most convenient place. shopping, a low convenience cost alternative, should consequently gain in pOpularity. Cox and Erickson cite several reasons why consumers are willing to forego pro- duct comparison. Mass production and marketing in a buyer's market result in greater standardization of higher-quality products that are nationally distributed and widely serviced; products thus differ from each other primarily in non-functional respects. Also, increased 1Cox and Erickson, Retail Decentralization, pp. 47-49. 2Kelley, "The Importance of ConvenienCe in Consumer Purchasing," p. 156. 36 national branding and intenSive advertising are making it easier for the shopper to comparison shop for price and brand without going from store to store. Protected from making bad product choices by the pressures of a buyer's market and by the tremendous amount of market information he obtains through advertising and other sources, the better-informed consumer is instead using his increasing purchasing power to save himself inconvenience in shopping.1 The importance of place, or location of retailing facilities and services in space and time in relation to the shopper, has been assumed in much of the previous discussion on in—home shopping as convenience shopping. The trend to convenience shopping for former shopping goods may evidence an increasing Shift in the importance of "place" in the Shopper's decision function. In-home shopping is an extreme example of the minimization of place costs; the Shopping search and transaction may take place entirely within the home. It appears that the more conveniently placed the retailing facilities, the less importance in—home shopping will have. Rich found that phone ordering was most 1Cox and Erickson, Retail Decentralization. 2For example, see Bernard J. LaLonde, "Differentials in Supermarket Drawing Power and Per Capita Sales by Store Complex and Store Size," (unpublished Ph.D. dissertation, Michigan State University, 1961). 37 popular in cities with the least suburban branch expansion. A problem in measuring retail location as a factor in con- venience shopping is that geographic distance measured in highway miles is but one element that the consumer must consider; parking and shopping time, both within and be- tween stores, are also important. It is suggested that a measure of portal-to-portal travel time, as a minimum, would provide a more meaningful estimate. Socioeconomic and Demographic Characteristics of‘In—Home'Shoppers The retailing literature has advanced a number of hypotheses and some empirical data relating shopping behavior to socioeconomic and demographic characteristics of shoppers and their families. The following section explores the research literature concerning the inter- relationships of in—home buying behavior to a number of key socioeconomic and demographic variables. From the research evidence, a number of hypotheses have been de- rived for testing in the present study. Age of Shopper Age of shopper appears to be related to in-home shopping behavior. Both the young adult shopper and the elderly shopper would seem to have special demands for 1Rich, Shopping Behavior of Department Store 92stomers, p.756. 1 38 shOpping convenience. Younger shoppers are new Shoppers, less closely tied to old ways of shopping and more willing to accept new products and shopping methods. The younger wife tends to have small children at home, restricting her shopping mobility. Young families, particularly those living in suburbia, may also be restricted in ShOpping mobility by a lack of private or public trans- portation. For the elderly shopper, advancing age pro- duces somewhat different shopping problems, but ones with similar results in restricted shopping mobility or de- creased desire to spend much time in Shopping. The elderly may have particularly strong demands for shopping convenience, since they often lack transportation for shopping or are unable to shop in person because of illness or other physical limitations. Further, shopping in stores, particularly self—service stores, often re- quires considerable walking, waiting in line, package carrying, as well as driving and parking, all of which may make the shopping trip a tiring, unpleasant task for older Shoppers. Changes in the age distribution patterns of the American population may be a contributing factor in the rise of in-home shopping. Both the young and the elderly have been growing disproportionately faster than the general population increase. Reversing an immediate postwar decline, the population of spending units in 39 which the head is under 25 is now increasing. The average age of the population is declining. At the same time, however, the proportion of spending units whose head is 65 years of age or older has been steadily increasing. Both trends accentuate the demand for in-home shopping. Family Life Cycle Family life cycle refers to the series of changes in the family status of the individual as he grows older. Marriage, birth of the first child, and the time when children grow up and leave the home all mark life cycle changes. The relationship Of these family status levels to important differences in purchasing behavior reflects changing life styles and consequent demands in consumption. Family life cycle, despite its relative newness in market- ing research, has proved to be a valuable concept in frequent use today. In an important article, Lansing and Kish illustrated the superiority of family life cycle over age in explaining changes in six economic characteristics.l Research involving life cycle suggests that certain Changes in the American family life cycle in the last several decades may favor in-home shopping: (1) Recent population trends in the United States have indicated a lowering of the age of first marriage 1John E. Lansing and Leslie Kish, "Family Life Cycle as an Independent Variable," in Marketing and the Behavioral Sciences, ed. by Perry J. Bliss (Boston: Allyn and Bacon, 1963), pp. 138-151. 40 and an acceleration of family formation; the proportion of young families is increasing. Young families, heavy con- sumers of general merchandise, particularly household durables, would seem to be particularly receptive to shopping at home. Younger people tend to be early adOpters of new shopping ideas. And if both husband and wife work, or if small children keep the wife at home, the restricted shopping time and mobility may increase the ShOpper's demands for convenience.1 (2) Data from surveys of American families through- out the 1950's and early 1960's shows a decline in the proportion of married units with no children at home. Katona, for example, reports a decline in the prOportions of single, widowed, divorced or separated persons under 45 years of age.2 Childless wives are often working wives, a segment assumed to have shOpping time restric- tions. (3) Spending units with three or more children have also increased significantly. Two— and three-person 1These assumptions are found in a number of recent articles and research studies on in-home buying. See, for example, Higgins, "The Booming In—Home Market"; Grey Matter, September, 1967; Stanford Research Institute, "In-Home Selling Report No. 225"; Bell Telephone Systems Executive Summary, The Locked-In Shopper. There is currently little empirical support for fhe assumptions, however. 2George Katona, Charles A. Lininger and Eva Mueller, 1963 Survey of Consumer Finances (Ann Arbor: University 0? Michigan, 1964), p. 5} 41 spending units have declined, while larger units, primarily spending units with three or more children, have gained in proportion.1 And younger wives with several children at home, an increasing prOportion of total households, may be particularly receptive to mail and telephone shopping. Shopping studies have revealed some differences in shopping attitudes and behavior by both age and family life cycle. Age and life cycle differences have been reported for downtown versus shOpping center patronage; Rich, for example, found that younger people patronized shopping centers more than older people.2 Rich found also that New York women under 40 with children living at home were three times as likely to be high phone users as were women under 40 without children (15 per cent versus 5 per cent).3 Similarly the Bell Telephone "Baltimore" study reported that younger women postpone shOpping trips more frequently than older women, usually because of crowds, public transportation problems, and small children to care for. 1Ibid., p. 4. 2Stuart U. Rich and Subhash C. Jain, "Social Class and Life Cycle as Predictors of Shopping Behavior," Journal of Marketing Research, V (February, 1968), p. 45. 3Cox and Rich, "Perceived Risk and Consumer Decision Making--The Case of Telephone Shopping," p. 495. 1; Study of Telephone Shopping in the Baltimore Area, p. 5. Bell Telephone System Executive Summary from A 42 Rich and Jain, exploring the usefulness of social class and life cycle variables as predictors of shopping behavior in today's environment, summarize some of their life cycle findings as follows: (1) Younger women shopped more often than older women, but presence of children did not make any signifi- cant difference within the two age groups. Stone and Form found shopping frequency mainly dependent on pre- sence of children in the family.1 Rich and Jain attempt to reconcile the differences by suggesting that tradi- tional distinctions among stages in the family life cycle may be blurring because of "recent changes in income, education, leisure time, movement to suburbia, and other factors."2 (2) Women under and over 40 with children put more stgess on quick shopping than women without children. In contrast, Stone and Form found that women in their forties felt most hurried, and women in their twenties less hurried. Thus, age determined the attitude toward the importance of shopping quickly in one study, but not in another.3 (3) Life cycle did not differentiate shoppers on attitude toward shopping as a pleasant activity, types of stores favored for each of eight types of merchandise, on 1Rich and Jain, "Social Class and Life Cycle as Predictors of Shopping Behavior," p. 45. 2Ibid., p. 48. 3Ibid., p. 45. 43 interest in fashion, or on perceived helpfulness of news- paper advertising in shopping decisions.1 In summary, while family life cycle seems a potenti- ally useful independent variable for discriminating in-home buying behavior, some difficulties have been experienced in applying the classification to explain shopping be- havior. Rich and Jain suggest that recent changes in factors such as income, education and leisure time have obscured traditional life cycle distinctions. The diffi- culty with life cycle, however, does not lie entirely in the dynamics of consumer change outmoding life cycle classifications. As Wells and Gubar point out, there are some measurement problems involved with life cycle as a research tool.2 Researchers do not agree in their cate- gorization of the life cycle, making verification of study results difficult. And the categories have often been inappropriately selected, merging different groups and hindering discriminant ability. Family Income There is some evidence that higher—income ShOppers are more likely to buy at home than lower-income shoppers. Telephone shopping studies universally report that lIbid., p. 44. 2William D. Wells and George Gubar, "Life Cycle Concept in Marketing Research," Journal of Marketing Research, III (November, 1966), p: 360. 44 higher-income shoppers order by phone more frequently than lower-income shoppers. Among catalog shoppers, family income differences are apparently less important. Rich found that income had little effect on mail orders. On the other hand, the most frequent mail shoppers were also high phone users,1 suggesting that users of multiple in- home shopping methods are higher-income shoppers. There are further indications that high-income shoppers are convenience—oriented. Higher-income women shoppers own more credit cards and have more charge accounts and charge purchases twice as frequently as lower-income shoppers.2 Higher-income women expect more salesclerk assistance, home delivery and other services when shopping in department stores, while lower income women are more concerned with bargains and lower prices.3 The complexity of defining "shopper convenience" is evi- dent in Rich's study; higher- and lower-income women disagreed on whether department stores or discount stores were easier places in which to shop, higher-income women Choosing department stores and lower—income women selecting lRich, Shopping Behavior of Department Store Cus- tomers, p. 79. 2Bell Telephone System Executive Summary, 1011 San Francisco Women Tell About Shopping in Department Stores. 3Rich, Shopping Behavior of Department Store Cus- tomers, pp. 88;89. 45 discount stores. The reasons for the differences are evi- dent in the factors selected as "conveniences." The lower-income women stressed self-service, bargains and sales, accessibility and parking facilities, while upper- income shoppers mentioned salesclerk services, quality and variety of merchandise, and other services such as delivery, phone orders and charge accounts most fre- quently.1 Assuming in-home shoppers are likely to be above- average in family income, it is apparent that growth in mail and telephone sales could be attributed partly to rapid changes in income distribution. United States Bureau of the Census data indicate, for example, that while United States families with annual money incomes of $10,000 or more represented only 10 per cent of total spending units in 1955, in 1960 this percentage had jumped to 17 per cent, and to 25 per cent in 1965. Median income has risen over the same decade from $5,223 to $6,882.2 For families with the wife in the paid labor force, median money income rose from $5,622 in 1955 to $8,597 by 1965.3 The rapidly-rising family income levels suggests that an 1Ibid., p. 118. 2U. S., Department of Commerce, Bureau of the Census, Current Population Reports, Series P—60, No. 51, reprinted in StatiStical Abstracts, 1967, Table 477, p. 336. 3Ibid., Table 478, p. 336. 46 increasing percentage of shoppers can afford shopping con- venience and services. Working¥Wives Many marketers are convinced that the recent growth in catalog shopping is partly the result of rapid increases in the number of women in the labor force over the past two decades. Working women, particularly working mothers, they argue, have fewer hours of discretionary time for shopping plus more discretionary income than non—working women.1 And higher-income, shopping convenience—oriented women appear most likely to shop in—home. The working wife is an important source of family income. Households with two or more working members are more affluent than households with one wage-earner, for all but the very highest levels of household income. And households with two or more working members are found with increasing frequency at progressively higher incomes up to $15,000 per year.2 United States Department of Labor statistics confirm the increases in working wives. Today nearly 40 per cent of all females 14 or over are in the labor force, compared with 27 per cent in 1940.3 The most striking rate of 1For example, see Higgins, "The Booming In-Home Market," p. 49 . 2Katona, et a1., 1963 Survey of Consumer Finances, p. 5. 3U. S., Department of Commerce, Bureau of the (Zensus, Statistical Abstracts of the United States, 1967, Table 324. 47 increase in employment has been among working mothers. More than one out of three mothers were in the labor force in March, 1966 as compared with less than one out of ten in 1940. Almost two of every five working mothers have children under six years of age, while more than three out of five have children from six to seventeen years 1 Other notable trends are the increases in Old only. younger working women, particularly the number of child- less wives, probably reflecting the declining birth rate during the younger childbearing years. Nonwhite mothers are more likely than white mothers to be working: 40 per cent of nonwhite mothers who had children under six years of age worked in 1966 compared with 24 per cent for white mothers.2 Empirical research on the in—home shopping behavior of working wives is neither comprehensive nor conclusive. Among ShOppers reporting in a Bell Telephone Study that they were "locked-in yesterday" and unable to shop in stores, only 15 per cent listed employment outside the home as the reason, although 31 per cent of the declared "ready-to-buy" proportion of the "locked—in" ShOppers were 3 employed. Since over 36 per cent of married women work, 1U. S. Department of Labor, Bureau of Labor Statis- tics, Leaflet 37, "Who Are the Working Mothers?", 1967. 2Ibid. 3Bell Telephone System, The Locked-In Shopper. 48 the results cannot be interpreted as suggesting that work- ing wives feel especially restricted in their shopping activities.l Rich reported that working women did not display a greater-than-average propensity to shop quickly,2 and that working women, as expected, shOpped less frequently during weekdays and more frequently during evenings and Saturday than women who did not work.3 Also, working women near stores spent more of their lunch hours and to—and-from work time shopping than did other working women. One-fifth of women working near stores shopped during their lunch hours; to-and-from work shopping was infrequent.)4 Rich did not indicate whether working women were frequent or infrequent telephone Shoppers. Leisure Time There is some consensus in the retailing literature on two points with regard to leisure time and its uses: First, discretionary time is assumed to be increasing among persons who work and shOp. Second, increases in 1Although no information was given on the charac- teristics of non-respondents or the proportion of working wives in the total sample, the large (10,000) mail sample yielded an 89 per cent return rate, indicating that a reasonably representative socioeconomic cross-section would be expected. 2Rich, Shopping Behavior of Department Store Cus- tomers, p. 74. 3Ibid., p. 72. uIbid. 49 discretionary time parallel increased discretionary pur- chasing power and discretionary mobility, and the simultaneous gains in all three have widened the choices of alternate uses of discretionary time that are more attractive than shopping.l One possible outcome is that consumers more able and willing to seek convenience and save time in shopping will look to in-home shopping. Both assumptions need to be examined more carefully. On the first point, the shorter work week, it should be noted that large segments of the wOrking population are experiencing lepp leisure time, as measured by the in— creasing length of the work week. The number of nonfarm wage and salary employees working more than forty-eight hours per week almost doubled from 1948 to 1965, increas- ing from 12.9 per cent to 19.7 per cent during this time period.2 At the same time, other occupational groups were shifting to shorter workweeks. On the balance, average weekly hours for full-time nonfarm work force were about the same in 1965 as in 1948.3 Part of the increase in leisure time may be attributed to more days 1John M. Rathmell, "Discretionary Time and Dis- cretionary Mobility," in Managerial Marketing: Per— epectives and Viewpoints, ed. by Eugene J. Kelley and William Lazer IHomewood, Illinois: Richard D. Irwin, Inc., 1967), p. 149. 2Peter Henle, "Leisure and the Long Workweek," Monthly Labor Review, (July, 1966), p, 721, 3Ibid. 50 off with pay as opposed to shorter work weeks. Women shoppers are of course not as likely to be either part of the labor force, nor as likely to work more than forty hours per week, so the leisure time trends are less likely to directly affect their personal shopping habits. Second, the use of leisure time for Shopping has not been empirically established one way or the other. Thompson suggests that two conflicting hypotheses are possible: the rising value of time and the increasing array of attractive uses or opportunity costs of time may decrease the amount of time people are willing to spend in shopping. On the other hand, increasing discretionary time, income and mobility will make store shOpping easier and faster, allowing consumers to spend even more time Shopping, if shopping is an increasingly enjoyable alter- native use of their time.1 The researcher is of course faced with the problem of determining to what extent and under what conditions shopping intrudes on leisure time or is considered a leisure time activity in itself. Race Marketing research has until recent years paid relatively little attention to racial differences in buying behavior. But today the Negro market in particular is being studied intensively by market research firms ¥ lThompson, "Consumer Convenience and Retail Area Structure," p. 39. 51 specializing in Negro buying behavior, by Negro media, by academicians, social workers, and so on. Yet Bauer finds that generalizations about Negro consumers are quite difficult since it is not yet clear just how the Negro buyer perceives his role; that is, whether or not Negroes actually take whites as their reference group. Early studies of the Negro market showed that Negroes saved more of their incomes than whites at comparable income levels.1 It has also been found that Negroes take shOpping more seriously, are more interested in shopping values, and are less concerned with "shopping pleasure" and more opposed to "spending the money" than whites with comparable incomes.2 The latter findings may suggest that Negroes use other Negroes as reference groups. On the other hand, the marketing literature has frequently reported the tendency for many Negroes to be heavy consumers of conspicuous status items, and heavily brand conscious. Bauer, Cunningham, and Wortzel, noting the extremely high rate of the Negro male's consumption of items such as prestige-brand Scotch whisky, termed as "strivers" those middle class Negroes who are anxious to 1Raymond A. Bauer, "Negro Consumer Behavior," in On Knowing the Consumer, ed. by Joseph W. Newman (New York: John Wiley & Sons, Inc., 1968), p. 161. 2Ibid., p. 162. 52 buy the "right" things.1 Bullock describes how the "self- rejection side of the Negro split self-image" leads rela- tively well-off Negroes to overconform to what they see as "white community norms."2 Bauer found that Negroes rated themselves lower than did comparable whites on the National Opinion Research Center scale.3 In conclusion, Bauer thinks that the Negro market is self—segmenting on the basis of whether or not the individual is striving for the white standard, and whether the Negro is brand conscious and especially responsive to new brands, or brand loyal. Research on Negro in-home buying is limited, and data on the Negro consumer are not complete or specific enough to warrant strong hypotheses. Rich's study found little difference between Negroes and low-income whites in department store and telephone spending or shopping frequency. Especially where symbolic or fashion products are involved, the brand-conscious Negro would be unlikely to buy from catalogs, since mail-order houses have working class images and typically sell private label merchandise. 1Raymond A. Bauer, M. Cunningham and L. H. Wortzel, "The Marketing Dilemma of Negroes," Journal of Marketing, XXIX (1965), p. 1-6. 2H. A. Bullock, "Consumer Motivations in Black and Whitz," Harvard Business Review, XXXIX (May-June, 1961), p.9. 3 Bauer, "Negro Consumer Behavior," p. 161. 53 On the other hand, telephone ordering from department stores might be acceptable. It must be remembered that as predominantly lower- income shoppers, Negroes face certain income, credit, Shopping information and shopping mobility constraints. Like low income whites, Negroes often shop relatively close to their homes, patronizing neighborhood stores. Negroes are particularly aware of subtle discrimination and punishments from shopping in higher—class stores, and may avoid shopping in stores where they encounter hostility.l For Negroes, in-home buying may be a less- threatening method of shopping than buying in stores. Evidence is inconclusive; Rich found no differences between Negro women and lower-income white women on enjoyment of shopping in stores. Negro women shoppers were found to be more highly fashionrconscious than whites. But no significant differences by race were reported for any other aspect of department store and telephone shopping behavior that could not be accounted for by income differences. Place of Residence Families living in urban fringe or suburban areas are assumed to experience more transportation diffi- culties than city dwellers, and generally are farther 1Bullock, "Consumer Motivations in Black and White," p. 113. 54 from Shopping stores in travel time as well as distance. To the extent that these assumptions are correct, sub- urban families would appear to have heavier shopping convenience demands and thus greater in—home buying potential than city dwellers. Empirical data offer some support for the notion that suburban residents are heavier-than-average in-home buyers, but the findings are by no means conclusive. Rich, for example, found that New York suburbanites used mail—order more often than city dwellers. No urban-suburban differences in mail ordering were reported, however, for Cleveland mail shoppers.l Frequent telephone users tended to live in suburbs.2 Yet another study reports that "relatively few" suburban and rural women shOp by phone, although nearly 40 per cent of shoppers living outside the city limits were "locked-in yesterday" and unable to shOp in stores.3 It is increasingly difficult to make meaningful statements about the in—home shopping habits of suburbanites versus city dwellers, Since the type of transportation system and the extent of decentralization in retail shopping lRich, Shopping Behavior of Department Store Cus- tomers, p. 79. 2Ibid., pp. 81—82. 3Bell Telephone System, Executive Summary, The jLocked-In Shopper. 55 facilities vary widely within any metropolitan area. For example, suburban telephone buying is thought to be in- versely related to the extent of retail decentralization, particularly toward suburban shopping centers.1 Geographic distance is today thought to be a less valid delineator of retail trading areas than is driving time. Most shopping center trading area studies, for example, are using driving time as a measure of trading area potential. ‘The changing nature of urban and sub— urban transportation systems and traffic patterns, particularly the growth of expressway systems, have made spatial distance a less meaningful factor. A recent study in the Toledo, Ohio metropolitan area found that the most significant driving time dimension for shopping center trade area analysis is fifteen minutes. Approximately 75 per cent of each of the five shopping centers' patrons were found to reside within fifteen minute driving dis- tance of the center. The effect of expressways on shopping patterns was not measured.2 In addition to the spatial dimension, the place of residence as an independent measure of shopping behavior 1Rich, Shopping Behavior of Department Store Cus- tomers, p. 57. 2James A. Brunner and John L. Mason, "The Influ- ence of Driving Time Upon Shopping Center Preference," .Iournal of Marketing, XXXII (April, 1968), pp. 57-61. ‘ 56 reflects important differences in life style, income, and convenient access to store shopping, among other factors. Attitudes "Attitudes" as used in the present research are regarded as predispositions to act in certain ways in certain situations. Attitudes toward in-home buying directly affect purchase decisions and these, in turn, directly affect attitudes through experience with the products bought at home and with the in-home process itself. To the extent that Shopper attitudes can pre- dict shopping behavior, researchers find it useful to measure attitudes toward particular shopping referents. Jonassen's 1955 study of downtown and suburban shoppers, for example, produced several attitude scales, success- fully tested for reliability and validity, which pre— dicted shopper type and shopping behavior. In particular, attitude scores indicated that, on the balance, downtown Shoppers thought the quality and selection of merchandise advantages outweighed the inconveniences of the downtown area. Suburban shoppers were less concerned with the downtown's service and assortment attributes. The shopping attitudes of different socioeconomic types correlated significantly with their actual shopping choices.l lJonassen, The Shopping Center Versus Downtown, p- 25. 57 Several of the telephone shopping studies previously cited measured attitudes of different shopper types toward various shopping processes and elements in the shopping environment. The store preferences noted in Rich's study agree in essence with previous findings concerning atti- tude differences among social Classes; lower-middle income groups preferred to shop in discount and mail-order stores, while upper-middle and upper-income classes pre- ferred departmentstores.l Nearly all shOppers, both frequent and infrequent phone shoppers, and regardless of social class, see shopping as an enjoyable activity, although the reasons for enjoying shopping differed some— what by social class. Attitudes concerning which shopping features were most convenient or inconvenient differed by income level. Higher-income shoppers attached more im- portance to store services and variety and quality of merchandise, while lower-income ShOppers saw self-service and "bargains" as more important than sales clerk assist- ance. Higher-income whites and Negro women express more interest in fashion than low-income whites. Rich found that higher social status women consider it most important to shop quickly, even though higher status women spend inore on an average shopping trip than other women. lRich, Shopping Behavior of Department Store Cus- ‘tomers, pp. 106-107. 58 An attitude dimension of increasing interest to market researchers is the consumer's View of the risk of the shopping situation. The concept, generally known as "perceived risk," is described as follows: 'Perceived risk' refers to the nature and amount of risk perceived by a consumer in contem- plating a particular purchase decision. . . . The amount of risk perceived by the consumer is a function of two general factors: the amount at stake in the purchase decision, and the indi— vidual's feeling of subjective certainty that she will 'win' or 'lose' all or some of the amount at stake. The amount at stake in a buy- ing situation is determined by the importance of the buying goals . . . and by the costs (economic, temporal, physical, and psychological) involved in attempting to achieve a particular set of buy- ing goals.1 The high perceived risk of telephone shopping may explain why the majority or urban shoppers in Rich's study did not shop by telephone, despite the value American women seem to place on convenience and the recognized convenience advantages of telephone shOpping. Cox and Rich hypothesize that "the additional elements of potential uncertainty which are present in telephone shopping create perceived risk which acts as a deterrent to phone Shopping."2 Compared with store shOppers, telephone shoppers have far fewer opportunities to re— duce uncertainty, being limited to past experience with 1Cox and Rich, "Perceived Risk and Consumer Decision Marking--The Case of Telephone Shopping," p. 489. 2Ibid., p. 487. 59 the firm, product or brand, or to newspaper advertising which may not picture the merchandise. Cox and Rich showed that shoppers closely agree on the degree of per- ceived risk associated with various types of merchandise ordered by phone. By knowing these attitude measures, the authors Claim, it is possible to predict with a high degree of confidence the frequency with which various items will be bought by phone.1 Perceived risk attitude measures would appear to have potential use in isolating in-home shopping of all types. There is little reason to assume that catalog ordering, for example, differs significantly from tele— phone shopping in perceived risk. Summary Changes in the retailing environment are basically reactions to changing consumer needs brought about by a complex set of interrelated economic and social forces. Any prediction of in—home retailing behavior, however, must also recognize and take into account the broad institutional factors influencing the particular develop- ment of retail facilities and methods. A broad overview of the historical development of in-home retailing suggests that the underlying theme has been the response of in—home sellers to consumer demands 11610., p. 499. 60 for shopping convenience. Increasing demand for in—home ShOpping seems to be the result of several related factors: (1) Although retail stores have responded to changing consumer demands through new forms of shopping, such as planned shopping centers, discount stores and self—service, retail stores are limited in their ability to provide maximum shopping convenience and services to all types of customers. In-home retailing, in its various forms, specializes in offering a low-convenience-cost alternative that appeals to many shoppers. On the other hand, the high perceived risk of buying by description necessarily limits the in-home market. (2) Intensive use of retail store facilities, especially in downtown areas but increasingly in suburban shopping areas, produces major shopping inconveniences. Crowded stores, traffic and parking problems become major deterrants to shoppers. In-home shopping is one way to avoid these shopping inconveniences. (3) It has been hypothesized that in our high-level, market-oriented economy, mass distribution of increasingly standardized, branded and advertised products have shifted the Shopper's attention away from in-store comparison shopping among product attributes and toward purchasing convenience considerations. If the hypothesis is correct, in-home shopping along with other low-convenience cost 61 methods of obtaining products should become increasingly attractive. (4) Most importantly, not all shopper types respond equally to in-home shopping alternatives. The consumer behavior literature suggests that certain measurable socio- economic and attitudinal characteristics may differentiate the in-home shopper from her store—shopping counterpart. From a preliminary examination of the literature, it may be useful to postulate two types of in-home shoppers: the "locked-in shopper" who buys at home of necessity, and the "convenience-oriented Shopper" for whom in-home shopping is only one alternative method of buying. Both types may share many socioeconomic and attitudinal charac— teristics, but the circumstances under which they shop at home may differ. The "locked-in Shopper" is assumed to be prevented from shopping in stores, usually for one or more of the following reasons: she works outside the home, and has little spare time for shopping; she has small children at home who demand much of her time; or she lacks trans- portation for shopping, or is otherwise unable to travel to the stores, even if she has spare time. The locked-in shopper, then, demands shopping convenience because of her unusually restricted time or mobility. Evidence that she actually shops at home is not substantial, however. The "convenience-oriented in—home shopper," is not necessarily locked in at home, and in fact is ordinarily 62 a frequent store shopper. Evidence from telephone shopping studies suggests that, in contrast to the woman who does not shop by telephone, the frequent telephone shopper is younger, more affluent, and a heavier user of charge accounts. She is a suburban dweller, and probably has several children. She finds shopping enjoyable, but is more concerned with shopping quickly. She is probably less tolerant of the major inconveniences of shopping in stores. The two classifications of in-home ShOppers may be inaccurate. The evidence for each socioeconomic and attitudinal difference among shopper types is not equally convincing. On some variables the research data is in- conclusive; on others, relationships are still hypothetical. Most empirical data on the variables that seem relevant to in-home shopping differences are limited to department store customers who shop by phone. Data on mail-order shoppers and on buyers who use more than one in-home shopping source are limited. The present research attempts to answer some of the questions concerning the behavioral characteristics of today's urban in-home shoppers. I. . ,f—q-t b CHAPTER III RESEARCH DESIGN Research Design Framework Chapter III presents the research design and method- ology followed in collecting data and analyzing the research hypotheses. In the first section, the variables presented in the research hypotheses in Chapter I and reviewed in detail in Chapter II are listed and incorporated within a descriptive diagram or model of the shopping decision en- vironment. The second section explains the sampling design and methodology and the third section explains the inter- viewing procedures followed in obtaining the data. The method of data analysis is described in the fourth section, followed by a final section defining basic concepts used in the research. 'Dependent'Variables Previous research data had suggested that different shopper types vary rather widely in their in—home shopping ‘behavior, both in terms of how much they shopped at home .from various sources, and in the methods used to complete ‘the shopping transactions.l And evidence discussed in the 1See Chapter II, pp. 43—46. 63 4. .DFI 64 first two chapters suggested further that shopping decisions correlated with measurable socioeconomic differ- ences among shoppers that could be usefully employed in market segmentation. Consequently in-home shopping in— tensity was chosen as the general dependent variable in the study. Sub-classification of in-home shopping behavior by various sources and methods of in-home shopping, as outlined in Chapter I and summarized below in Figure l, allowed shopping intensity to be measured more precisely. Sources of Supply Method of Ordering telephone mail large general merchandise mail-order (Catalog) firms in person (at catalog stores and catalog counters) "’_’__,..— telephone \\ mail local retail stores direct mail firms mail Figure l.-—In—home shopping sources of supply and Inethods of in-home ordering. 65 Obtaining data on in-home shopping intensity among the Shopper sample required that respondents recall their in-home shopping actions. Two operational measures of in-home shopping intensity were suggested as potentially meaningful and accurate dependent variables: (1) number of dollars spent on in-home purchases, and (2) number of in—home orders. Both variables were used in the research to collect data on in-home shopping behavior. Because of difficulties in obtaining accurate recall data on number of direct mail orders for the variety of product categories included in the study, frequency of direct mail ordering could not be measured. Thus the total number of in-home orders from all three sources could not be reliably computed and used as a dependent variable for hypothesis testing. All hypotheses thus were tested by aggregating dollars Spent by each in-home method into the dependent variable, total dollars spent in-home. Since the number of catalog and telephone orders were also measured, the relationship between frequency of in-home buying and dollars Spent at home were examined. As expected, correlation analysis revealed that the re- lationships were positive and fairly strong.1 Independent Variables The shopper deciding whether to shop at home or from a retail store acts within a particular environment as lPearson y (number of phone orders x dollars spent by phone) = .497; Pearson y (number of catalog orders x dollars spent by catalog) = .662. 66 perceived through her system of attitudes and values. The environment, attitudes and value system all interact to constrain and motivate her shopping behavior. The present research is concerned with identifying key in- dependent factors which influence decisions to buy from telephone, catalog and direct mail sources. In selecting potentially useful independent variables for hypothesis testing, several criteria were followed: 1. A strong relationship between the independent variables and in-home buying behavior was assumed, as suggested by previous research findings in shopping behavior. 2. Independent variables were operationally definable; that is, they met the measurement requirements of the research and agreed in general with other accepted definitions in consumer behavior research. Independent variables measured in the research are grouped into three categories, socioeconomic and demo- graphic, convenience orientation, and attitude variables. All are outlined below. Socioeconomic and demographic attributes and convenience orientation data were gathered from structured survey questions. Three attitude scales measured ShOpper attitude responses. Previous attitude research findings formed a basis for choosing the attitude measures. Several of the items used in the scales had 67 been tested for reliability and validity in Jonassen's study of downtown versus suburban shopping, while others were chosen for the present study with the objective of efficiently covering a wide range of relevant shopping phenomena on which shopper attitudes could conceivably differ. Shopping Attitude Scale I, a six-item scale measur- ing shopper attitudes concerning the difficulty of their situation for store Shopping, was designed to complement several demographic measures of "locked-in" shopping conditions.1 The "locked-in" factors are listed below. Shopping Attitude Scale II, a 16-item Likert scale, measured attitudes toward the shopping process.2 On several items respondents evaluated importance of the search process in shopping. Other items measured shopper attitudes toward shopping convenience and enjoyment, particularly shoppers' opinions of the inconveniences involved in store shopping. The third shopping attitude scale attempted to ineasure the extent of perceived differences among retail stores and in—home shopping sources in providing Shopping enjoyment, services and conveniences.3 To isolate 1See Chapter IV, Fig. 3, p. 133. 2See Chapter IV, Fig. 4, p. 137. 3See Chapter IV, Fig. 5, P. 141. 68 discriminating scale items, attitude scores on all three scales were tested for significance of difference among shoppers on the dependent variable, dollars spent at home. The following list of independent variables used in the research include brief descriptions where necessary: I. Socioeconomic and Demographic Variables A. Life style variables 1. \OCDNmUl-IZ'UUN family life cycle, as measured by a) marital status b) age of household head c) number of children at home d) ages of children age of shopper education of shopper occupation of household head employment status of shopper-—part- or full-time head of household——shopper, or her spouse race of shopper-—white or Negro family size mobility of family——how many times family has moved intercounty in the last five years. Other "locked-in shopper" variables 1. travel time (portal-to-portal) to favorite stores shopping mobility, as measured by a) availability of automobile transportation for shopping 69 b) shopper ability to drive automobile c) distance from home to nearest public (bus) transportation II. Convenience Orientation Variables 1. 2. 3. 4. 5. 6. 7. 8. number of mail-order catalogs in home number of specialty catalogs in home number of charge accounts in general merchan- dise stores number of credit cards owned by shOpper and spouse number of shelter magazines in home number of automobiles in family number of telephones in home number of newspaper subscriptions III. Attitude Variables A. Perceived shopping difficulties presented by: l. 5. hours available for shopping transportation situation distance to stores employment status children at home Shopping convenience attitudes concerning the following factors: 1. traffic problems when shopping parking difficulty when shopping parking costs crowds 70 store shopping enjoyment importance of spending time in shopping need to compare items in person before buying waiting for salesclerk assistance waiting in line to pay for merchandise carrying packages 0. Attitudes toward in—store versus in—home shopping sources on providing certain shopping conveniences and services and other factors, including: 1. 2. 3. 4. 5. 6. 7. 8. 9 10. 11. 12. delivery service return and exchange service selection of styles, sizes quality of merchandise low prices; value received for money sales merchandise guarantees merchandise information time convenience shopping enjoyment frequency of need to return merchandise overall shopping convenience The In-home Shopping Decision'Framework The following conceptual framework of the shopping decision environment, diagrammed in Figure 2, incorporates the variables into a research structure tentatively E l 7 woozpme wcfiaoocm new mooesow oEOCIcfi ammonnp wcfiooocm oEOCICH go zpfimcoDcH Hofi>m£mm wcfimaogm mmabmflpm> ucoocooma BOUGUIJUI Ol goedequt {In .DCOECOLH>CO :oflmfioop .ooo .ucmEmOwcm mcflqqocm oocoficm>coo mEfip mompcmnmsm cowpmenoucfi cofluooamw szHmSU OOHLQ ”mm £05m .mmmmpcm>pm mafiaoocm co mEozlcfi .m> OLODm coospon mmoconmmufio .opo .mmmm Ixomo wcfihgbmo .mOCHH psoxoozo .meOHOmOHmw Amcfiooonw Lou Sofiasosfiaoss osfiov wOLOpm Op mafia Ho>mnp mpEOCO cammmpu mcfixemo I ”mm £05m .mmpoOLQ mewaoocm mg» no mocmficm>coocfi mcficnmocoo mopsofiooa wcfiooonm mEOEICH oneln.m opsmflm null .onm .mcoflpaflnonnsm ocflmmwme .mmcozooHOB no poncsc mOpsm mo amass: monOOOm ombmco mnemo BHUCLO ”no aficmpoczo "an nonsmmOE .nLOuomm coflprCmHLCIoocwfico>coo Loaoozm mo own J TL. TL 3. m OHHnso pcm mum>flbo & ”Aufiafinmawm>m coflpmpnoomcmpp D. 3 u mmgoom EOLM m mafia mcfl>flgp ocw mocmpmfio n S u. oEo: mpflmpzo mxbos Lmqnocm oEo: pm COLUHHEO Hoocommbo ”mcflmmocm onoow OD mnmfinnmm woocmpm530LHo wcfipmpfimfioobm meanwfipm> ucmocmqmch mpocpme new moonsom wcfiooocm mEOCICH “ho hpfiHHDmHHm>< omfim AHHEmm Ampnmo pfipopo ocw mpcsooom mmnmcov pfipono Happen ”Mo zufiafipmafim>< Kq PSIJIPom oEoocfi zHHEmw Hmscc< neosoaocoo.wcfifioocm 72 explaining the shopping decision process as the inter- action of environment and its perception by the shopper. Similar conceptual models of consumer behavior have been expressed throughout the marketing literature. The 1935 article by Kornhauser and Lazarsfeld, for example, ". . . views the action of product choice as an inter- play between the "predispositions" of the consumer and the situation." The "situation" may consist of product attributes, store location, level of services offered and other market influences.l Jonassen summarized his model similarly: ". . . the consumer's market behavior is essentially a compromise adaption to attracting and repelling forces evaluated within the framework of his attitudes and values."2 The diagram utilized in the present study agreed substantially with the Katona view of the consumer decision process which proposes that it is meaningful to consider consumers as rational goal-seekers whose inarket decisions are constrained by enabling conditions and modified by precipitating circumstances and attitudes. Of the "enabling" factors, in—home shopping sources and 1Arthur Kornhauser and Paul F. Lazarsfeld, "The .Analysis of Consumer Actions," in Marketin 'Models, ed. txy Ralph L. Day (Scranton, Pennsylvania: International 'Textbook Company, 1964), p. 11. 2Jonassen, The Shopping Center Versus Downtown. 73 methods were considered as constant for the Grand Rapids environment, since all were available, although perhaps not equally accessible, to the entire shopper population. Field Work Procedures The Data Collection Instrument A structured nondisguised questionnaire was con- structed to guide the personal interviews. To minimize interview time and reduce errors in recording answers, closed-end questionnaire items and attitude scales were stressed. Extensive open-end responses were limited to several questions on in-home shopping behavior. For respondents who had not shopped at home, interviews took approximately a half-hour to complete; in-home shoppers answered several additional questions, increasing their interview time to about forty-five minutes. The question- naire is reproduced in Appendix A. The questionnaire and interviewing techniques were pretested in several homes prior to the initial interview period. As a result of the pretest findings, a number of questionnaire items were reorganized and simplified. Revision of the questions and changes in interviewing procedures, particularly the modification of answer cards to save interviewing time, resulted in a more concise, efficient and easily administered questionnaire. 74 Sample‘Design The Population The population from which the sample was drawn included all eligible adult female shoppers residing in selected 1960 Census tract areas of Grand Rapids, Michigan. Because of their relative ease of identification, however, housing units were defined for sampling purposes and then one eligible adult female shopper in each housing unit in the sample was interviewed. Grand Rapids was considered a representative urban shopping area for the following reasons: (1) As a United States Bureau of the Census "urbanized area" Grand Rapids was included within a Standard Metropolitan Statistical Area providing population characteristics for census tracts and city blocks. (2) It is a medium-sized city (206,000 peOple in the city, 387,000 in Kent County, 1965) offering a diversified shopping environment: down- town stores, suburban shopping centers, string street and neighborhood shopping areas were all available. The major mail-order firms were represented, and a variety of retail stores offered telephone and mail-ordering services. A modern expressway system allowed easy access to nearly all shopping areas, including the downtown. (3) With stable and diversified industry and employment, steady year-round retail sales and major population character- istics such as income, age and occupation closely 75 approximating Michigan and national averages, Grand Rapids ranks consistently among the nation's ten most popular test market areas, a good indication of repre- sentativeness.l (4) Grand Rapids, more than 100 miles from a larger metropolitan area, was quite free from the potentially biasing effects of retail influence from other large cities. 'The‘Sampling;Frame Several opposing objectives had to be satisfied in choosing a sample design. Given the exploratory nature of much of the research, the primary objective was to sample a wide range of shopper types intensively enough to be able to test the hypotheses at an acceptable level of precision. Obtaining proportionate representativeness of the Grand Rapids metropolitan area was considered a desirable but less important objective. Given the usual time and financial constraints of the study, it was de- cided to stratify the sample on key demographic and socioeconomic variables to obtain minimum quotas of important shopper types within limited, relatively contiguous geographic areas of the city. Three stratification criteria were established as guides for selecting the independent variables for stratifying the Grand Rapids population: (1) the 1The Grand Rapids Press, Grand Rapids Market, ‘gprrent Data, Grand Rapids, Michigan, 1967, p. l. Ill-Ill“ 76 independent variables should be strongly related to the dependent variable, in—home buying intensity; (2) popu- lation parameters of the independent variables should be known; and (3) the geographic concentration of the vari— ables in the population should be known. Annual family income, race, and residential location were chosen initially as meeting the strati- fication criteria and the sampling objectives. Family income was assumed to affect the intensity of in-home shopping as well as the choice of methods and sources of in-home shopping. Further, annual family income was 1 available from 1960 Census tract data, and average value of housing, a good estimate of family income, was avail- able for city blocks within the census tracts.2 The choice of race as a stratification criterion was con- sidered necessary, even though no strong relationship between race and in-home shopping behavior was known prior to the study, in order to efficiently sample and interview enough Negro shoppers to meet sample size requirements. Negro families in Grand Rapids, as in most northern cities, usually concentrate geographically 1U. S., Department of Commerce, Bureau of the Census, U. S. Census of Population and Housing; 1960, Final Report PHC (1)-55. Census Tracts. ‘Grand Rapids, Michi an (Washington, D.C.: U. S. Government Printing OTTice). 2U. S., Department of Commerce, Bureau of the Census, U. S. Census of Housing: 1960, Series HC (3)— 206, City Blocksi Grand Rapids, Michigan (Washington, D. C.: U. S. Government Printing Office). 77 near the downtown or central city area, and random sampling even in low income areas might have failed to cover enough Negro families to meet sampling requirements. Racial composition was also available from United States Census data. Both urban and suburban areas were originally con- sidered as independent variables for stratification pur- poses. Urban-suburban differences were considered important influences on in-home buying intensity, and population parameters and geographic concentration could be estimated from Census tract data. However, research limitations prevented sufficient sampling of both suburban areas and Negro shoppers to meet subsample minimums, so a decision was made to not select a suburban area subsample. Given the sampling objectives and the stratification criteria, a multistage quota sample design was chosen to stratify the Grand Rapids urban area on family income or house value and race. While the subsample areas were chosen on a judgment basis, precluding inferences on a probability basis to the pOpulation, probability sampling was done within each subsample area. Selection of Census Tracts and City Blocks Four geographic areas were chosen to represent the ‘urban population, one each for upper, middle and lower incomes, and one predominantly Negro area. From each 78 area, approximately fifty interviews were to be completed, for a total sample size of 200. In the first stage of the sampling process, all 1960 census tract areas in Grand Rapids were analyzed and ranked by average annual family incomes, and white-nonwhite proportions were noted. Using annual family income levels of $9,000 and above, $6,000 to $8,000, and below $5,000 as first estimates of higher, middle and lower incomes respectively, approximately three census tracts were selected for each income level. The three tracts with the highest prOportion of Negro residents were also chosen, excluding the downtown tract area because its high pro- portion of commercial and industrial areas would have made interviewing especially difficult. Census tract popu- lations often differ widely in their socioeconomic charac- teristics, so to assure further sample homogeneity within subsamples the researcher consulted city block census data for each selected tract. Since family income by City block was unavailable, average value of housing statistics were substituted as measures of economic status. Census tracts showing wide variation in family inCome per block were either eliminated in favor of more homogeneous tracts, or city block areas deviating markedly from tract aiverages were eliminated or if approximating the house 'values of adjoining tracts the blocks were included in ‘the»latter's sample area. Average house values of $20,000 79 and over, $10,000 to $16,000, and under $8,000 served as rough estimates of upper, middle and lower family incomes, respectively. Thus the four geographic areas finally chosen did not parallel exactly the 1960 census tract boundaries. Since the census data used to stratify the sample were seven years old, two further procedures helped update and verify the sample characteristics, spot checks of socioeconomic characteristics of several city streets in each area, using cross-classified telephone directory data On income, occupation, and house value, and personal observation in each of the areas. Finally, an interviewer with wide and current experience in the Grand Rapids area confirmed most of the observations. After final sample areas had been judged relatively homogeneous within their boundaries, representative of the family income averages and racial proportions required, and large enough to meet sample size requirements, de- tailed maps of several blocks each were constructed to aid the interviewers in selecting households for inter- viewing. Selection of Households and Respondents The sample quota was fifty completed interviews in each subsample, for a total sample size of 200. A 10 per cent oversample allowed for incomplete or ineligible 80 interviews. The final total of 210 useable interviews was distributed by subsample area as follows: higher income white = 50 middle income white = 50 lower income white = 51 lower income Negro = 59 Interviewers selected households systematically within each of the four sample areas by choosing a random starting point, avoiding corner house starts, and then following a skip interval of every fourth street address sequentially by city block until each area quota was filled. Substitutions of street addresses were allowed for refusals, non-existent or otherwise ineligible addresses (such as business addresses), for not-at-homes after callback attempt minimums had been met, and for ineligible respondents. The following criteria determined which households and respondents should be included in the sample: 1. In all selected households an eligible re- spondent must have shopped for general merchandise, by any shopping method, between January 1, 1967 and the time of the interview, in late November or early December, 1967; this requirement helped insure the validity of answers involving recall of shopping experi- ence and attitudes toward shopping. 81 2. Only housewives or female heads of households were eligible to be interviewed. While joint husband-wife shopping decisions are common where larger general merchandise items are involved, the high rate of general merchan- dise Shopping by women and the difficulty in finding husbands at home during normal inter- viewing hours resulted in selecting only women in the sample. In households of several adult females it is difficult to determine major purchase responsibility, so these households also were not interviewed. 3. Persons living in institutional residences such as college dormitories, sororities or nursing homes were not considered separate households and were not interviewed. 4. To avoid possible overrepresentation of apart- ment dwellers in large multiple-residence buildings, no more than four household addresses in a single apartment building were interviewed. The usual skip interval of every fourth address or apartment number was followed. Because information on the shopping behavior of 'working wives was especially important to the research, it was considered necessary to make vigorous attempts to :interview initial not-at-homes. Interviewers were 82 instructed to attempt on the first call to secure neigh- bor information on the not-at-homes. Then a minimum of two callback attempts were to be made on different hours and days to increase the Chances of finding working wives at home, before submitting the addresses to a list for telephone appointments. Finally, telephone numbers of the remaining not—at-homes were to be obtained from a cross—classified telephone directory, and three telephone appointment attempts made, also at random times. Substi- tutions could be made for the final list of not—at-homes by adding addresses to the sequential sample following the regular skip interval. The entire Sampling procedure is summarized in Table 2. Interviewer Selection and Training A staff of three female interviewers was hired and trained to conduct the personal interviews. All were residents of Grand Rapids, with extensive interview experience in the Grand Rapids area. One member of the staff, well-trained in interviewing supervision, was chosen to supervise the field interviewing. The author worked closely with the supervisor in pretesting the questionnaire. The supervisor was then given primary responsibility for instructing the other two interviewers in respondent selection techniques, interviewing and callback procedures. 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I I I I Imm w z m: o 2 mm mcoHpmHQEoo OEOOCHIOHUUHE NH a sH mN am 0 HH am nosonIooIooz HN oHossmcsm SN m Nm mNH m Nm NHH nooeooo< Hoooe N o o N o o N noHonHHocH m o H A o H o . annodom opHc: m om A...I..- IAm N NH ma N NH AN neoHooHaeoo oeoocHIsoanc mm A oH mm mm A mH moH moEocIuMIuoz "H oHaEmmnsm mon>noucH mon>L0ch m3OH>poucH m awe H zoo pmuaEmpp< xomnHHmo xomnHHmo xombHHmo DQEOHD< ococamee mflommm: HNCOmpom no xomnHHmo OOHAHUOZ ho Ucooom meHm 3OH>LODCH HocHa :oHoocHEEoe monsooo< ooHeroz toe oeHe so noosom HsHchH pm maumpm xomnfiamo umfiufinoz pouomflom wcfizofibnmch moeomlumIpoz Aav Hwy AAV .Hcv Hmv Hal Hmv HNV AHV .mmooopa wcuzofi>poucH on» uo EdawmuaII.~ mqm pcoocooooca 039 MO weapowoumo m mom OOHSQEOO AHHNQHwHHo oapmfiumum mp .Hooososmes nHmooo bsHHOOO Homo. on ocOOHHHemHn HHO A on OH.NV m nHHHozIHoxmsnmo 105 AOO HHHO HOV HHmO Homo Ammo HONV AOOH HOOH AOOH AOOH AOOH AOOH AOOH Hssoe mmI mml MMI wml mmi mmI Hal noso pen ONHH O N O O OH AH HH OHHIOOH O O NN mH AH OH HH OmIomH O O O NH O HH HN ONImHH AH O NN OH OH NH OH OHI HA AOO HAN Amm ANm AHm AHm AHN OH 30cm who: 2 m m H o o.coO so m DHmHOOHm ApHo CHV moan mam ummsmoz Op oocmpmfio m.GOHpmpHoamammp man OHHDSQ mo Apfiafinfimmmoom an zufimqmpcfi wcfimsn mEOCIcHII.A mqmge 106 into a family life cycle variable and categorized into four separate groups similar to the classification used in Stuart Rich's study of department store shoppers.l The four groups were women (a) under forty with pre- school children; (b) under forty without preschool chil- dren; (c) over forty without preschool Children; (d) forty or over with preschool children. A one-way analysis of variance found family life cycle groups did not differ significantly on in—home buying intensity, and the research hypothesis was re- jected. Table 8 data indicate that women under forty TABLE 8.--In-home buying intensity by family life cycle.av Stage in Family Life Cycle Dollars IHSHgme Under 40; No Under 40; Over 40; No Over 40; Preschool Preschool Preschool Preschool Children Children Children Children $0 25.9% 32.8% 30.3% 33.3% $1 -14 14.8 12.5 16.5 00.0 $15-29 307 17.2 703 3303 $30-59 14.8 10.9 17.4 00.0 $60-119 14.8 17.2 14.7 00.0 $120 & over 25.9 9.4 13.8 .33.3 Total 100.0% 100.0% 100.0% 100.0% (27) (64) (109) (6) aKruskal—Wallis H (5.068 at 3 df) significant at .167 (dollar totals ungrouped). y lRich, Shoppinngehavior of Department Store Cus— tomers, p. 62. 107 without preschool children may be most likely to spend above—average amounts at home, while younger women with— out preschool children do not differ from women over forty in shopping at home. Hypothesis l(E).--In-home buying intensity is greater in the "elderly, empty nest" stage of family life cycle than in earlier stages of family life cycle. It was hypothesized that elderly shoppers, because of their higher incidence of poor health or their un- willingness or inability to drive to shopping areas, carry packages or perform other shopping tasks, would be particularly receptive to in-home shopping alternatives. Shoppers Sixty years Old or older with no children at home were compared against all other shoppers on in-home buying intensity. A Kolmogorov-Smirnov two-sample test on the two groups yielded a significant difference on ungrouped buying data of approximately .40. Since the observed significance exceeded the .05 level, the hy- pothesis was not accepted. A closer examination of the data in Table 9 shows that about 30 per cent in either group bought nothing from in-home sources during the previous year. 108 TABLE 9.-—In-home buying intensity-—elderly versus other shoppers.a Dollars Spent Stage in Family Life Cycle In'Home All Other Elderly Shoppers $0 31.4% 30.2% $1 -14 22.9 12.8 $15-29 11.4 11.1 $30-59 14.3 14.5 $60—119 17.1 14.5 $120 and over 2.9 16.9 Total 100.0% 100.0% (35) (172) aKolmogorov-Smirnov D significant at less than .40. Hypothesis 1(F).--Working women buy more at home than women not employed outside the home. On the assumption that working women have fewer hours available for shopping than women who do not work, it was hypothesized that working women would shop at home more than nonworking women. Respondents grouped into two categories, employed outside the home, and not employed, were compared on total dollars spent at home. The two- sample test indicated a probability of .247 that in-home spending was higher for employed Shoppers. Since the observed difference was not significant at the .05 level, the research hypothesis was rejected. 109 TABLE 10.-—In-home buying intensity by shopper employment status.a Dollars Spent Employment Status of Shopper In-Home Employed Not Employed $0 30.4% 30.5% $1 -14 16.1 13.9 $15-29 1.8 14.6 $30-59 19.6 12.6 $60-119 14.3 15.2 $120 and over 17.9 13.3 Total 100.0% 100.0% (56) (151) aKolmogorov-Smirnov D Significant at .247 (dollar totals ungrouped). Employed Shoppers were separated into part-time and full-time workers and compared on in-home buying. The two groups were found to differ significantly in buying intensity, but in the opposite direction from that sug- gested by the fewer number of hours the full-time worker should have available for shOpping. Part—time working women spent significantly more dollars at home than full- time workers. The observed difference, shown in Table 11 below, was significant at .05. Family income level was found to be equivalent whether or not the shopper was employed. Since families in which the shopper works usually have two incomes, however, the finding suggests that the household head 110 TABLE 11.--In—home buying intensity: part-time versus full-time employment.a Dollars Spent Employment Status of Shopper In-Home Part-time Full-time $0 19.4% 44.0% $1 —14 12.9 24.0 $15—29 3.2 0.0 $30-59 25.8 12.0 $60-119 19.4 8.0 $120 and over 19.4 12.0 Total 100.0% 100.0% (31) (25> aKolmogorov-Smirnov D (7.05 at 2 df) significant at .05. in the "shopper employed" group earns less income than household heads in the single income group. Thus income of the household head is less strongly associated with in-home buying intensity than is total family income level. Total family incomes of shoppers employed part- time also did not differ significantly at the .05 level from family incomes of women employed full—time. The Influence of Selected Demogrephic and Socioeconomic Variables on In-Home ShOpping Hypothesis 2(A).--In-home buying intensity is positively related to amount of annual family income. 111 Based on earlier research studies which found strong relationships between family income level and the desire for shopping conveniences such as telephone shopping, it was hypothesized that higher-income shoppers would buy more at home than lower-income shoppers. Total dollars spent on in-home shopping were compared against family income class using the one-way analysis of variance. Table 12 shows in—home buying differences among the income classes were highly significant in the predicted TABLE l2.--In-home buying intensity by annual family income.a Annual Family Income Dollars Spent $0- $4 000- $7 000- $10 000— $15 000 In'Home $3,999 $61999 $91999 $141999 & oéer $0 35.7% 40.4% 29.3% 23.3% 14.3% $1 -14 32.1 24.6 8.6 2.3 3.3 $15-29 7.1 12.3 12.1 14.0 4.8 $30-59 3.6 7.0 22.4 27.9 0.0 $60-119 14.3 8.8 12.1 20.9 28.6 $120 & over 7.1 7.0 15.5 11.6 47.6 Total 100.0% 100.0% 100.0% 100.0% 100.0% (28) (57) (58) (43) (21) aKruskal—Wallis H (30.89 at 4 df) significant at less than 0.0001 (dollar totals ungrouped). direction, and the research hypothesis was not rejected. In-home shoppers apparently have larger annual family incomes than shoppers buying little or no general 112 merchandise at home. Shoppers in the $15,000 and over income level, for example, represented only 10 per cent of the total sample but accounted for one-third of the shoppers spending $120 or more at home. Twenty—two per cent of the shoppers in the three income categories below $10,000 spent $60 or more at home, while 47 per cent of shOppers in the two income categories above $10,000 spent $60 or more. The results of Hypothesis 2(A) apparently confirm earlier findings of similar studies. Hypothesis 2(B).—-In—home buying intensity is positively related to shopper education level. It was hypothesized that in-home buying increases with the Shopper's education level. To test the hy— pothesis, shoppers were first classified into seven categories according to the number of years of formal education completed. These seven categories were later regrouped into five to increase the sample cell size necessary for hypothesis testing. A one-way analysis of variance tested differences in in—home buying inten— sity among the five education levels. Buying differences were significant at .0018, and the hypothesis was not rejected. 113 TABLE 13.-—In-home buying intensity by shopper education level.a Years of Formal Educationb Dollars Spent Grade Some High Some College In-Home School High School College Grad. (to School Grad. (13- (16 or 6 Yrs) (7-11) (12 Yrs) 15 Yrs) More Yrs) $0 60.0% 34.7% 28.4% 25.0% 0.0% $1 -14 10.0 22.2 13.6 3.6 0.0 $15—29 10.0 12.5 9.1 10.7 22.2 $30-59 20.0 29.7 18.2 19.3 11.1 $60-119 0.0 12.5 15.9 28.6 0.0 $120 & more 0.0 8.3 14.8 17.7 66.7 Total 100.0% 100.0% 100.0% 100.0% 100.0% (10) (72) (88) (28) (9) aKruskal-Wallis H (20.99 at 6 df) significant at .0018 (dollar totals ungrouped). bH originally computed on seven education level categories. Hypothesis 2(C).-—In-home buying intensity is positively related to family size. The research explored the assumption that shoppers with large families would tend to be particularly inter- ested in shopping convenience, and would therefore buy more heavily from in-home sources than shOppers with smaller families. Shoppers were grouped into seven family size categories,1 and the groups were compared 1Categories include the husband and wife. Thus the single-unit category consists of adult female heads of household. 114 on in-home shopping intensity. As shown in Table 14 below, buying differences were significant at .143 in the pre- dicted direction, but above the .05 level of significance, and the hypothesis was rejected. TABLE 14.-—In-home buying intensity by family size.a Dollars Family Sizeb Spent ln-Home 1 2 3 4 5 6 7+ $0 46.7% 31.1% 23.1% 36.1% 23.8% 36.8% 25.0% $1 —14 20.0 20.0 11.5 11.1 14.3 21.1 4.2 $15—29 20.0 8.9 7.7 11.1 11.9 5.3 16.6 $30-59 6.7 15.6 23.1 8.3 14.3 10.5 20.8 $60-119 6.7 20.0 11.5 13.9 21.4 5.3 12.5 $120 or more 0.0 4.4 23.8 19.4 14.3 21.1 20.8 Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% (15) (45) (26) (36) (42) (19) (24) aKruskal-Wallis H (12.19 at 8 df) significant at .143 (dollar totals ungrouped). b gories. H originally computed on nine family size cate- Hypothesis 2(D).-—Negro shoppers buy less at home than white shoppers. It was hypothesized that Negro women shoppers buy less at home than white shoppers. Since family income level was assumed strongly related to in-home shopping intensity, the substantial Negro-white family income ciifferences were controlled by selecting a subsample of 115 white shOppers equivalent to the Negro sample on average annual family income. The "low income white" subsample proved to be almost identical to the Negro subsample on average income.1 In-home buying data for the two subsamples were grouped into‘six ordered categories, as shown in Table 15, and Negro-white buying differences were tested for significance with the Kolmogorov-Smirnov two-sample test. The test, which looks for areas of extreme difference between the two independent sample distributions, found observed differences significant in the predicted direction at less than .20, but above the necessary .05 level. Since the spending distribution data suggested that the sample means might differ, a t test was run on the ungrouped spending data. The observed t value of 1.33 was below the 1.645 level necessary for signifi— cance at .05, and the hypothesis was rejected. The magnitude of differences observed in Table 15 does suggest, however, that significant buying differences 1In evaluating the data several other points should be kept in mind. The two sample areas were geographically contiguous, suggesting that accessibility to stores, at least in terms of distance, was quite similar. Second, although upper-income Negro shoppers were not available .for comparison with upper-income whites, both of the sub- samples included middle as well as lower—income families, in.approximately equal proportions. For example, 41 I>er cent of the Negro shoppers reported family incomes OI'$7,000 and over, as did 43 per cent of the white sub— sample. Thus the two subsamples were comparable over Several family income classes. 116 TABLE 15.--In-home buying intensity by race.a b Dollars Spent Race In‘Home White Negro $0 32.0% 50.9%' $1 —14 28.0 14.0 $15-29 6.0 7.0 $30-59 10.0 12.3 $60-119 10.0 10.5 $120 and over 14.0 5.3 Total 100.0% 100.0% (50) (57) aKolmogorov—Smirnov D (3.80 at 2 df) significant at .20 (dollar totals grouped). bMean annual family income: whites, $4,105; Negroes, $4,020. by race might be found in the extreme ranges. For example, 32 per cent of low-income whites failed to buy at home during the preceding year, compared with 51 per cent of Negro shoppers in the sample. Negro-white differences in catalog, telephone and direct mail buying were also measured. As illustrated in Tables l6, l7 and 18 below, Negroes and whites did not differ significantly at the .05 level on any of the three in-home buying alternatives.l Apparently low income lSince respondents who bought from more than one shopping source are included in several tables, the sum of percentages in Tables l6, l7, and 18 exceeds the per- centage totals in Table 13. 117 TABLE l6.--Telephone buying intensity by race.a Dollars Spent Race In—Home White Negro $0 82.0% 86.2% $1 -14 6.0 3.5 $15-29 2.0 0.0 $30-59 2.0 8.6 $60-119 6.0 0.0 $120 and over 2.0 1.7 Total 100.0% 100.0% (50) (58) aKolmogorov-Smirnov D (4.27 at 2 df) significant at < .20 (dollars grouped). TABLE l7.—-Catalog buying intensity by race.a Dollars Spent Race In-Home White Negro $0 74.5% 74.6% $1 -14 5.9 5.1 $15-29 5.9 6.8 $30-59 5.9 3.4 $60-119 2.0 8.5 $120 and over 5.9 1.7 Total 100.0% 100.0% (51) (59) aKolmogorov-Smirnov D (1.92 at 2 df) significant at .40 (dollars grouped). 118 TABLE l8.--Direct mail buying intensity by race.a Dollars Spent Race In-Home White Negro $0 56.0% 77.2% $1 -14 16.0 8.8 $15—29 10.0 7.0 $30-59 6.0 7.0 $60-119 8.0 0.0 $120 and over 4.0 0.0 Total 100.0% 100.0%, (50) (57) aKolmogorov—Smirnov D (4.79 at 2 df) significant at .10 (dollars grouped). shoppers, white or Negro, seldom buy by catalog or tele- phone. Less than 20 per cent of either group bought by telephone during the preceding year while slightly more, 25 per cent in either race group, bought from a general merchandise catalog. But percentage differences between the two groups on direct mail spending suggest that direct mail shopping may be more popular among low income whites than Negroes. More than 40 per cent of the low income whites had ordered by direct mail, compared to 23 per cent of the Negro sample, a difference significant below .10.1 1The difference is significant at the .05 or .10 level depending upon whether or not a directional hy- pothesis is being tested. Since no directional hypothesis had been stated prior to testing the data, the more con- servative test was chosen, resulting in an observed X2 value significant at .10. But the observed differences seem large enough to warrant further examination. 119 The Relationship Between Selected Convenience Orientation Measures and In-Home Buying Intensity Previous research in retail shopping has suggested that convenience orientation is an important factor in explaining shOpping behavior. Telephone shopping, for example, appeals particularly to consumers who wish to avoid a shopping trip for only one or two items, or who cannot get out of the house to shop, or who often feel that shopping in stores is an unpleasant and time-consuming chore. Shopping studies have suggested further that the American consumer, particularly the more affluent shopper and her family, demand and can afford greater convenience in many aspects of everyday living. If the desire for convenience is an important motivator in decisions to buy at home, valid measures of family convenience orientation should effectively isolate the in-home buyer market seg- ment. Several hypotheses related different proxy measures of convenience orientation with in-home spending, and the results are presented in the following section. Hypothesis 3(A).--In-home buying intensity is positively related to number of telephones per household. Number of telephones per household was selected as one proxy measure of family convenience orientation. It was hypothesized that number of telephones in the home would be positively related to in-home buying intensity. 120 To test the hypothesis, shopper households grouped by number of telephones were tested for significant differ- ences in total dollars spent in-home. As shown in Table 19 below, the observed H value was significant at .0514. Since the relationship was very close to the .05 significance level, a product-moment correlation co- efficient was computed on the relationship, using un- grouped data. The coefficient of .276, tested against a Z distribution, was highly significant at less than .0005. Based on the Z test of significance, the research hypothesis was not rejected. TABLE l9.--In-home buying intensity by number of telephones per household.a b DOllars Spent Number of Telephones In-Home 0 1 2 3 $0 28.6% 26.6% 36.9% 18.8% $1 -14 42.9 21.9 10.7 3.1 $15—29 14.3 10.9 9.7 15.6 $30—59 0.0 14.1 16.5 12.5 $60-119 14.3 20.3 9.7 21.9 $120 and over 0.0 6.3 16.5 28.1 Total 100.0% 100.0% 100.0% 100.0% (7) (64) (103) (32) aKruskal-Wallis H (9.42 at 4 df) significant at .0514 (dollar totals ungrouped). bH originally computed on five categories of the independent variable. r = .276, significant at .0005. 121 The 15 per cent of families with three or more tele- phones were about twice as likely to spend $60 or more in—home than were households with two telephones or fewer. Families with two telephones are no more likely to buy at home than are one telephone households. Hypothesis 3(B).--In-home buying intensity is positively related to number of shelter magazines in the home. Women who read shelter magazines oriented toward home improvement, home furnishing and food preparation, and the "do-it-yourself“ reader were assumed to be especially concerned with shopping convenience because of their probable interest and involvement in time-consuming activities around the home. Accordingly, it_was hypothe- sized that the more shelter magazines the shopper received the more likely she would shop at home. To test the hypothesis, respondents grouped by number of shelter magazines regularly purchased or received by subscription were compared on in-home buying intensity. A Kruskal- Wallis test confirmed the research hypothesis at a signi— ficance level of .0003. Women who reported having one or more shelter magazines were nearly three times as likely to shop at home than women who did not regularly receive shelter magazines. Table 20 suggests, however, that while shelter magazine ownership is significantly re- lated to whether or not a shopper buys at home, within 122 the in—home buyer group the number of shelter magazines owned does not vary appreciably with in-home buying intensity. TABLE 20.-—In-home buying intensity by number of shelter magazines in the home.a b Dollars Spent Number of Shelter Magazines In-Home 3 or O l 2 More $0 46.3% 21.1% 14.8% 14.9% $1 -14 12.6 18.4 11.1 8.5 $15-29 11.6 13.1 11.2 17.0 $30-59 9.5 7.9 33.3 19.2 $60-119 12.6 21.1 14.8 14.9 $120 and over 7.4 18.4 14.8. 25.5 100.0% 100 0% 100 0% 100 0% (95) (38) (27) (47) aKruskal-Wallis H (29.09 at 8 df) significant at .0003 (dollar totals ungrouped). bH originally computed on nine categories of the independent variable. Hypothesis 3(C).--In-home buying intensity is positively related to the number of newspaper subscriptions received. It was hypothesized that heavy in-home buyers would subscribe to more newspapers than other shoppers. To test the hypothesis, shoppers grouped according to the number of local and out-of—town newspaper subscriptions received were tested for buying differences. As shown in Table 21 below, nearly 90 per cent of all shoppers in 123 the subsample subscribed to a newspaper. About 70 per cent of the shoppers subscribed to the one local newspaper, the Grand Rapids Press. The 17 per cent of the sample in the "two or more newspapers" category were all receiving at least one out-of—town newspaper. Significant buying differences were found among the shopper groups in the predicted direction at the .01 probability level, and the hypothesis was not rejected. Women subscribing to out-of-town newspapers as well as the local paper were especially likely to shop at home; two-thirds of this shopper group spent at least $30 at home, compared to only 23 per cent of the shoppers who did not subscribe to a newspaper. TABLE 21.—-In-home buying intensity by number of newspaper subscriptions received.a Dollars Spent Number of Newspapers In-Home 0 l 2 or More $0 50.0% 31.0% 20.6% $l-l4 11.5 17.0 6.0 $15-29 15.4 11.6 8.8 $30-59 3.9 15.7 17.6 $60-119 11.5 11.6 23.5 $120 and over 7.7 13.1 23.5 Total 100.0% 100.0% 100.0% (26) (147) (35) aKruskal—Wallis H significant at .01 (dollar totals ungrouped). 124 Hypothesis 3(D).—-ln-home buying intensity is positively related to number of credit cards owned by the family. It was hypothesized that the more credit cards a shopper and her family owned the more dollars the shopper would spend at home. To test the hypothesis, shoppers were grouped into four categories according to the number of credit cards owned and compared on in-home buying in— tensity. An analysis of variance yielded an observed H value significant at .006, and the research hypothesis was not rejected. TABLE 22.--In—home buying intensity by number of credit cards.a b Dollars Spent Number of Credit Cards In—Home 0 1 2—3 4 or more $0 36.4% 26.8% 24.3% 15.8% $1 —14 18.2 14.6 10.8 0.0 $15-29 12.7 9.8 10.8 5.3 $30-59 13.7 12.2 21.6 10.5 $60-119 10.0 26.8 13.5 21.0 $120 or more 9.1 9.8 18.9 47.3 Total 100.0% 100.0% 100.0% 100.0% (110) (41) (37) (19) aKruskal-Wallis H (21.5087 at 8 df) significant at .0059 (dollar totals ungrouped). bH originally computed on nine categories, 0-8 credit cards. 125 Table 22 data suggest that significant increases in buying intensity appear at the one credit card level. Shoppers owning two or more cards were nearly twice as likely to spend $30 or more at home than shoppers owning no credit cards. More than half of the total sample claimed to own no credit cards. Hypothesis 3(E).—-In-home buying intensity is positively related to number of charge accounts reported by shoppers. Charge accounts, like credit cards, offer definite shopping conveniences and enjoy widespread use among today's shoppers. Accordingly, it was hypothesized that shoppers owning several charge accounts would also buy more at home than shoppers who had few or no charge accounts. Shoppers grouped according to the reported number of charge accounts they held were compared on in- home buying intensity. Buying differences were found highly significant in the predicted direction, and the hypothesis was not rejected. Apparently shoppers with multiple charge accounts are much more likely to buy at home than other shoppers. V Table 23 data suggest that four charge accounts or more is the critical number in determining in—home buying differences. For example, only 10 per cent of shoppers with four or more charge accounts failed to buy at home, compared with 38 per cent of shoppers with 126 .mpczooom mwhmzo wno .mofihowopMO mafia co UmpSQEoo maamcfimfiho mp .Aooazomwcs manuou hmHHoov Hooo.o comp mmofi um meOHMHQme Ago w pm mmmw.mzv m maaamzlamxmsmxm Asav Ammo . goal Ammo game game Acme so.ooa ao.ooa so.ooa ao.ooa ao.ooa so.ooa so.ooa Hoooe m.mm 0.0: a.ma ‘ :.HH , s.m . :.m . 0.x oboe no omaa m.mm 0.0m m.sm :.HH H.HH m.mH o.m maanooa m.m o.oa a.mm a.mm H.HH a.ma o.w mmnoma 0.0 o.oH m.o m.aa H.HH H.m o.sH mmumaa m.m o.m m.o H.sa H.HH m.ma 0.3m ea: as R:.mm so.o am.o am.mm am.am am.mz uo.mm 0% +0 m a m m a o osomncH nmpcsooo< mwpmno mo ponezz pcoam mamaaom m.wpssooom owpmno mo hopes: up zpamcmpcfi wcflmsn oanIcHII.mm mqmHq Emequo m420 mm2 ”ow Lopcmo wcflqqocm m on so :30pczoo pow o» mE pom page nozm who oozm.ou oHomHHm>m mason >2 ”mH :30pczoo Lo popcoo mcfiaqozm mumsv loom cm on pom on oE Lou pmcp £05m ma COHBMSpHm m2 Amv HH< p< oaosope oz ADV oasoaccao Aaonmaam on oasoaacao Amv . pHSOHmeQ zHoEoprm Acoocfi ©o>fioohom an mpfimcoucfi wsfimsn mEonchII.mm mqm¢9 136 most shoppers eXperienced relatively little difficulty in getting out to stores when they wanted to shop. Hypothesis 5(B).--High-intensive in-home shoppers perceive selected elements of the shopping process as less convenient than do low-intensive in-home shoppers. Hypothesis 5(B) assumed that in-home shOppers would attach more importance to shopping convenience and less importance to shopping enjoyment than women who shopped very little at home. ShOpping Attitude Scale II, a 16- item Likert scale, was constructed to eXplore the hy- pothesis. None of the 16 attitude items had previously been tested for their discriminatory power in the in-home shopping situation, but several quite similar items had been validated in Jonassen's survey of shOpping con- venience-orientation among downtown and suburban shoppers. Shopping Scale II is reproduced from the questionnaire in Figure 4 below. Shoppers were divided at the $15 level into two in-home spending groups and tested using X2. While many shopping factors were rated as "difficult" by more than 50 per cent of all shoppers, on most items shoppers' responses did not differ by in-home buying intensity. Only Items 11 and 15 were significant at .05 in the predicted direction; the higher-spending group attached less importance to the necessity of seeing and comparing 137 - Response Item Practically EAtremely Slightly Ho Trouble -nposszble Difficult Diffizult Difficult At All (A) (h) (C) (D) E) 10. I H 1. When I drive to go shopping 1 find the traffic 3: ( ) ( ) ( l ( ) ( ) H _ . _ M, , , then i go shopp.ng by car, I it}: {rig a I;lEiCE? t;o g ar‘k 1.1: Qtrcngly Strongly Agree Agree Uniitiied Disaxree Disagree " \. -v‘ v»\ .4 (A) (n; (x) (c, (n) 4. As far as I'm concerned, the -ost of parking downtown matters very much. ( l I ) ( l ( ) ( ) ’) 5. Shopping in rhopplnr cezters, downtown, er in mt“.r stores is a pleasant change from everyday routine. ( ) ( ) f D ( l ( ) 6. When I go shopping in stores downtown or in :hopping centers, I fini the umuunt of walking is too mucn. ( l I i f ) ( ) ( ) 7. I :0 :.Cpp-n: 1r ‘ re 1:»1 1 here only uncn I Ci'HU lJUil 8. When I wwnt to go shopping for such things a: clothing and furniture, the time it takes me matters very much. ( ) ( l ( ) ( ) ( ) ' ,. . 0 .«n' . . isn't nece ”dry or .- “. 1 e . .‘ it zirn-cure ind A nt: in stares 11. Before buying things at home t .j or phone ormMN‘, I need to see and compare them. ( ) ( > ( l ( ) ( l 2. I find that waiting for assistance from a sales- clerk is very difficult and inconvenient ( ) ( ) ( l ( ) ( ) 13. I find that waiti _ to pay for something is very difficult and incon 14. I find that carrying packages while shopping is very difficult and inconvenient. ( ) ( ) ( ) ( l ( ) P. Am in No Way Hate Di like Affected Like Like Them Them Them by Them Them Very Much (A) w.) (c) (D) (E) 15. With regard to crowds when I shop, I can truly say u that I: ( ) ( ) ( ) ( ) ( ) 16. With regard to the hustle and bustle downtown and in shopping centers, I can truly say that I: ( ) ( ) ( ) ( ) ( ) Figure 4.-—Shopping Attitude Scale II. C 138 merchandise before ordering by phone or catalog, and liked shopping crowds less. One item revealed buying differences significant in the opposite direction from that predicted. Higher-spending buyers perceived less difficulty in parking downtown (Item 2). Item 6, amount of walking, was significant in the opposite direction below .10. None of the other 12 items, including shopping traffic problems, waiting in line to pay for merchandise, or getting salesclerk assistance discriminated shoppers on in-home buying below the .10 level of significance. Several items produced very little attitude difference. Almost all women felt that store shopping was a pleasant change from everyday routine, and few thought that they would buy furniture or home furnishings without prior inspection or would purchase clothing without first trying it on. V In summary, the attitude scale did not yield results which clearly indicate the nature of the relation— ship between in-home buying intensity and shoppers' atti- tudes concerning the importance or inconvenience of certain shopping factors. Hypothesis 5(C).--High—intensive in-home buyers compare in-home shopping more favorably with retail store shopping, on selected convenience factors, than do low-intensive in—home buyers. Results ping convenience . l) {10p ‘3 toward sampl t a - \_. \A x: f‘ differen= ) [9' K,. (D) 139 attitude onse by p {n- x ensity Shopper Re: 9. v in (R) q E 27.--In—home tuyin E Item ABL M .L J C s .3 v). (I, C) «,4 , r) 7 (\( rru 1d. «3 :J Oh we)" 1 A 1A} 31.1 at V0 .«L S 41+ a/ J '. 4.7 ,.r\ y 7‘ o I-.. .-J I l s O v 0 )) u.+ _ F) Wu 1 3v «xv 0.0 )) /\ n- J 5; ) ) u,+ 11. .:9 AU 1 Aflv Axv ,(\.I\ 11) l ‘ A ‘24.(3 ”(1.9 .1 ~\. $5—..'r -. . ¢\.._ 54‘ 1; o ') I24.) 0-14) ‘15 +) V 15 +) (3 (a ($0-l4) (‘ 7. 11 A)... l 11 _r:. C) A, V :4 i) A.W (111) 15 +) A (30—14) ( 10. P, 0‘4 3 ~. 0 , 1!. + R; 1 Axv A‘V (( \I/ .7; who .1. (\ (x .34 ,Cr9 230 [L C) L. 5;. [HO 7 aka 521 ($0—l4) ($15 +) 13. (111) r. ). All.U AU 1.0,. n‘ . 1‘). \J C) .. 0.21.4 rh/ rhu AJ/ «.4; 4-4 ($0-14) ($15 +) ( l4. )1 /01 (\( DEC 1.4 0 do an}. 60. n; r0 3:4 $0-l4) ($15 +) 15. .70 at sig. (26) (Ill) 10] dd flu U. n... 047 335 Ad 3 3|“ 81 F)“ “NH (80-14) ($15 +) 16. ion. st que the ible for v 1‘; P“ C ~pondents not el Other rec a 140 Hypothesis 5(C) explored the nature of the relation- ship between shOppers' opinions about store shopping versus in-home shopping advantages, and shOppers' actual in-home buying. More specifically, two related questions about shopper attitudes and buying behavior were explored by the hypothesis: 1. How do shoppers rate store shopping versus in-home shopping in providing certain shopping advantages? For example, which shopping method offers the lower prices, or is the least tiring? 2. To what extent are perceived differences in relative shopping advantages related to in—home buying differences? Shopping Attitude Scale III, constructed to test the research hypothesis, contained 14 statements on shopping convenience and enjoyment factors such as price, quality and selection of merchandise, guarantees and delivery service. From an answer card containing five response choices, subjects chose, for each different statement, either in—home shOpping or store shopping as having the advantage. A shOpper unwilling to choose be- tween store shopping and in-home shopping could also select either "no difference," "undecided" or "doesn't matter" to more accurately reflect her opinion.1 Shopping Attitude Scale III is reproduced below in Figure 5. 1Respondents were neither encouraged nor dis- couraged from choosing among the latter three answers. The "no difference" and "undecided" answers were assumed 141 .HHH mason oosoaoaa meaaoosmnu.m osswam A V A V A V A V A V we con wcAsAp nnmq .:H A V A V A V A V A V wcfiqaocm vomhohco who: .MA A V A V A V A V A V moses AE Low 63Am> mLoE poo .NA A V A V A V A V A V :mpmo mm omAUCBLOLoE shaman oh o>m£ u.:oc A .AA A V A V A V A V A V muwhzn E.A p353 psonm :oApsELoucH whoa mo>Ao .0A A V A V A V A V A V as sea mcwezncooloefiu whoa .o A V A V A V A V A V mwopcmpmsw mammnzmoov oLOE pom :mo A .m A V A V A V A V A V as con osoasos Icoo once nA mcwdao m .m A V A V A V A V A V sooaso sosoA scan A .o A V A V A V A V A V ooascocosoe ABHAmso Lennon BCAV cmo H .m A V A V A V A V A V mmAmm cfimwnmn Lopuon ecflu cmo A .2 A V A V A V A V A V noufln one moAmum no zuoflhm> hopmohw m pcwm cmo H .m A V A V A V A V A V nooom omcmcoxo one Cpspmp 0» we Lou Lowmmm .m A V A V A V A V A V ooa>son mpo>AAoo Loupoo pom cwo H .A AmV AQV AoV AmV A oLOBmICH no mowmpcm>om mo :omHLMQEooII.mm mqmo one ooo.oas s m o m NH OH ma ma AH mam.ma -ooo.sa use as «OH as am aoa am RNA ama mom.ow no Ham: Ham: Ham: ozonm poohfim woampmo ozonm pomhfio woampmo ocosm poohfim woampmo mmmao ao>o one on mmuos mmuom oeoocH masses 6&4 hmaaonm .Hm>mH oEoocH mafiemm one own hoaaonm mp mam» hoaaonm oEonchll.om mqm<9 150 .omsogm .mmmmonm moUSHoQHm wcaaaonm mEomIcH mo maze AoamV AomV AHoV AmsV mo.ooa mo.ooa uo.ooa mo.ooa Hopoe mquu NHwMI :.oH mqmmn osos no A m.m H.AH m.m m.m o 0.0m H.Hm m.am m.sm m N.AA H.Hm b.2m p.ma : a.ma «.ma m.m :.HH m m.am a.mH m.:a m.om m RH.A Rm.m no.3 mm.m H oaaemm Hams poopfia woamumo ozonnoaoe Hoooe mosam Aflasom .oufim mafiemm mp mam» mmamonm esonchll.Hm mqmoq cofipwosom wcfimaonm oEomIcH mo maze .Ho>oH cofipmosoo an camp hmgmonm mEozchll.mm mamnom .ofionomson opm>fihm m.wm m.mm m.Hm o.mH mo>Hpmhogo .coEmhom .coEmphmho m.oH 3.:H m.ma p.ma modem one HmOHhoHo 5.5A m.mm s.ma a.mm mfimfiofimmo .mhopmapoopo .mmowmcmz “a.mfi ms.oa ao.ma mm.ma Hmoasnoop .Hosoamooeosm madamm Hams pomhfim wOHMpmo mcosqofioe w a Hmpoe mofipo opmo coapm zooo maze hoaaonm mEomch .omos UHoaomson mo GOHpmazooo up camp nmamozn meonchll.mm mqmoq mEoonH zHHEem mo moopdom madfiufizz .Ho>ma mEoocH mafiemm an .mcfimmonw oEonch mo moohsom mHQHpHSE mo on: mo pseuNMIl.wm mqm ( n ) < c > c n > < a > AB. As far as I'm concerned, the cost of parking downtown matters very much. ( ) ( ) ( ) ( ) ( ) #9. Shopping in shopping centers, downtown, or in other stores is a pleasant change from.everyday routine. ( ) ( ) ( ) ( ) ( ) 50. When I go shopping in stores downtown or in shopping centers, I find the amount of walking is altogether too much. ( ) ( ) ( ) ( ) ( ) 51. I go shopping in stores around here only when I cannot avoid it. ( ) ( ) ( ) ( ) ( ) we»; ._ 52. When I want to go shopping for such things as clothing and furniture, the time it takes me matters very much. ( ) ( ) ( ) ( ) < ) 53. It really isn't necessary for me to look at furniture and home furnishi s in stores before buying them. ng ( ) ( ) ( ) ( ) 5h. It really isn't necessary for me to see and ‘ try on clothing before I buy it.( ) ( ) ( ) ( ) ( ) 55. Before buying things at home by catalog or phone order, I need to see and compare them. ( ) ( ) ( ) ( ) ( ) 56. I find that waiting for assistance from a salesclerk is very difficult and inconvenient. ( ) ( ) ( ) ( ) ( ) 57. I find that waiting in line to pay for something is very difficult and inconvenient. < > < ) < > ( ) ( > 58. I find that carrying packages while shopping is very difficult and inconvenient.( ) ( ) ( ) ( ) ( ) (CARD 5) Hate Dislike Am in no way Like Like them them them affected.by them. them. very much (A) (B) (C) (D) (E) 59. With regard to crowds when I shop, I can truly say that I: ( ) ( ) ( ) ( ) ( ) 6k). With regard to the hustle and bustle downtown and in shopping centers, I can truly say that I: ( ) ( ) ( ) ( ) ( ) -10- (CARD 6) For each of the next few statements I read, please tell me which you think has the advantage, shopping at home, or, shopping in stores. There are three other answer choices that may better describe your opinion. (REPEAT FOR EACH QUESTION) At In No Doesn't (A) home (B) store (0) d ff. (D) Unded. (E) gtteg 61. I can get better delivery service ( ) ( ) ( ) ( ) ( ) 62. Easier for me to return and exchange goods ( ) ( ) ( ) ( ) ( ) 63. I can find a greater variety of styles and sizes ( ) ( ) ( ) ( ) ( ) 6%. I can find better bargain sales ( ) ( ) ( ) ( ) ( ) 65. I can find better quality merchandise ( ) ( ) ( ) ( ) ( ) 66. I find lower prices ( ) ( ) ( ) ( ) ( ) 67. Shopping is more conven- ient for me ( ) ( ) ( ) ( ) ( ) 68. I can get more dependable guarantees ( ) ( ) ( ) ( ) ( ) 69. Less time-consuming for me ( ) ( ) ( ) ( ) ( ) 70. Gives more information about what I'm buying ( ) ( ) ( ) ( ) ( ) 71. I don't have to return merchandise as often ( ) ( ) ( ) ( ) ( ) 72. Get more value for my money ( ) ( ) ( ) ( ) ( ) 73. More enjoyable shopping ( ) ( ) ( ) ( ) ( ) 7h. Less tiring for me ( ) ( ) ( ) ( ) ( ) . Ht} 6. L0. L1. -2. . How many telephones are in your home? (CIRCLE) O l 2 3 (or more) Do you subscribe to a Grand Rapids area newspaper? YesU NOD Weekly ( ) Sunday ( ) Both ( Do you subscribe to any out-of-town newspapers? YesU NOE] Which ones? -11- (DEMOGRAHiIC AND SOCIOECONGIIC) Do you or other family members subscribe to any magazines, not including business or professional magazines? Yes No Which magazines? (LIST) Do you regularly purchase any other magazines? YesD NOD Which ones ? (LIST) __ Do you have a home freezer? YesD Not] Do you have a sewing machine in your home? YesD NOD Do you or anyone else in your family have any hotel, bank restaurant, gasoline or other credit cards? Yes No (mm) _— How many automobiles does the family have? (CIRCLE) o l 2 3 h (or (IF "0", GO TO Q. 12) more) Can you drive a car? YesD Not] Do you have use of a car during the day or evening? YesD NOD How many blocks is this residence from the nearest bus stop? (CIRCLE) o l 2 3 u 5 (or more) Don't know ( ) About what percent of the time do you use the bus to go shopping? .._._.._— (‘5) -12- We would like some general information about your family. 11?. Do you own or rent your home? Own ( ) Rent ( ) Other (Specify) (Single dwelling..______ Multi-unit__) 15. How long have you lived at this address? More thanSyrs. ( ) ltoSyrs. ( ) Less thanlyr. ( )(IFLESS) Where did you last move frml? (City (State) 16. What is your marital status? Married ( ) Single ( ) Divorced ( ) Widowed ( ) Sep. 17. (IF MARRIED) How long have you been married?_____years 18. Do you have any children living at home? YesU NOD (Go to Q. 19) (CIRCLE) (IF YES) How many children of preschool age? _ (under 5 years old?) 0 l 2 3 u 5 How may Children of grade school age? 0 l 2 3 h 5 How many of high school age? 0 l 2 3 h 5 How many over 18? O l 2 3 h 5 19. How many children 595 living at home? 0 l 2 3 I: 5 20. How many people, including yourself, live at this address? (NUMBER) 21. Please tell me the last grade you completed in school. ....____._.._. (Wife) (other than technical) _.__._____ (Husband) 22. Who is the Chief wage earner in this family? ‘ (Husband) ( ) (Wife) ( ) Other (specify) ( ) Van" ; .- 23. What is his (her) occupation at the present time? 21?. Are you employed outside the home? test") NoE] (Go to Q. 30) 25. Do you work more or less than ho hours per week YesD NOD Less than 100 ( ) More than he ) 26. Are you emplozgd more or less than 168 weeks a year? YeaD NOD Less than ( More than '08 ( ) 27. What are your usual working hours? Morning ( ) Afternoon ( ) Eve. ( ) Night ( ) Other (specify) - - 28. 29. 31. 32. Who do you work for? In what area of the city is your employer located? (CARD 7) Into which of the following brackets would you say your (combined) family in- come would fall? A a c D E___(est.)___(ref.)._._. How many in the family contribute to this income? (NUMBER) (CARD 8) Which of the following brackets best describes your age? ( )(Wife) (ref.) ( ) (Husband) (ref.) So that my office can check in case I've made any mistakes, what is your name? (NAME) (anmsss) (PHONE) (mm INTERVIEW COMEETED) 2A1 ‘Interview Response Cards CARD 1 What Respondent Would Do When Locked In At Home (A) Ask someone else to get what you want (B) Pick up what you want from a local neighborhood store (C) Telephone for what you want (D) Do without it (E) Postpone getting it until you can get out for a regular shopping trip (F) Order by mail CARD 2 Catalogs Currently in Home Sears Montgomery Ward Spiegel J. C. Penney Alden's Other CARD 3 Attitude Responses l—9 (A) Practically impossible (D) Slightly difficult (B) Extremely difficult (E) No trouble at all (C) Difficult 2A2 CARD A Attitude Responses 10-20 (A) Strongly agree (D) Disagree (B) Agree (E) Strongly disagree (C) Undecided CARD 5 Attitude Responses 21-22 (A) Hate them (D) Like them g (B) Dislike them (E) Like them very much h (C) Am in no way affected by them I CARD 6 Responses to Attitude Scale III (A) At home (D) Undecided (B) In store (E) Doesn't matter (C) No difference CARD 7 Family Income Levels (A) $0 to $3,999 (D) $10,000 to $1A.999 (B) $4,000 to $6,999 (E) Over $15,000 (0) $7,000 to $9,999 CARD 8 Shopper Age Categories (A) 20 to 29 (D) 50 to 59 (B) 30 to 39 (E) 60 to 69 (C) “O to A9 (F) Over 70 2A3 Telephone Interview Schedule Case No. Completed Name Date Address Phone 7f! Hello. My name is and I'm interviewing for a ( business research study at Michigan State University. We are conducting a telephone survey of housewives' shopping habits and I would like to talk with the housewife for a few minutes. Throughout the interview we'll be discussing only general merchandise, such as clothing, furniture and appliances . . . £23 food. * 1. How many times per month do you go to stores to shop for general merchandise, such as clothing, home furnishings, furniture and appliances, items you would find in department stores? Times per month 2. Which of this year's general merchandise catalogs do you have in your home? (READ) 2 Yes 0 Sears, Roebuck? Montgomery Ward? Spiegel? J. C. Penney? Alden's? lllll lllll Any others? How about supplementary catalog issues from these companies, like sale catalogs or Christmas catalogs? 3. Do you have any current gift or specialty catalogs in your home, such as Spencer's, Sunset House, etc.? Yes No Which ones? 10. ll. 12. l3. 2““ Have you purchased through any of the mail order catalogs since January 1st of this year? Yes No (IF YES) Approximately how much have you spent this year on catalog orders? $ Have you shopped by telephone from any department, clothing or other stores selling general merchan— dise, since January 1st? Yes No (IF YES) Approximately how much have you spent this year on these telephone orders? $ Can you drive a car? Yes No Do you have use of a car during the day or evening? Yes No What is your marital status? Married Single Divorced Widowed Separated (IF MARRIED) How long have you been married? Years Do you have any children living at home? Yes No (IF YES) How many children of preschool age? (Under 5 yrs.) 0 l 2 3 A 5 What is the occupation of the household head at the present time? Are you employed outside the home? Yes No (IF YES) Do you work 40 hours or moron or less than A0? 0 MO or more less than Is it a permanent Job, or one just for the holiday season? permanent holiday What is the age of the household head? Years Male Female (RESPONDENT) Estimated family income (letter) : n 4:; APPENDIX B SOCIOECONOMIC CHARACTERISTICS AND IN-HOME SPENDING BEHAVIOR OF RESPONDENTS INTERVIEWED BY TELEPHONE rt- V Socioeconomic Characteristics and In-Home '“Spendinngehavior‘ofiRespondents Interviewed by Telephone In order to obtain information on sample households in which the eligible female respondent could not be reached at home by personal contact, a brief telephone interview schedule was constructed and administered to a sample of eligible addresses. The sample represented households in which the eligible female respondent was not at home on the initial interview attempt and on the two followup attempts to secure personal interviews. The twenty telephone interviews yielded nineteen completed questionnaires from which the socioeconomic and in—home spending data are presented in summary tables below. Compared with the personal interview sample, shoppers interviewed by telephone were somewhat older, less likely to have preschool children, and more likely to be employed outside the home. Both samples were similar in catalog and telephone buying. 2A6 TABLE B.--Summary of socioeconomic characteristics and 2A7 in-home spending behavior of telephone sample versus total sample. Telephone Sample Total Sample n % % Estimated Family Income $0—3,999 2 10.5 13.3 A,000-6,999 5 26.3 27.1 7,000-9 999 5 26.3 28.6 10,000—1A,999 5 26.3 20.5 15,000 and over _g 10.5 10.5 Total 19 100.0 100.0 Employment Status of Respondent Not Employed 8 A2.l 73.0 Employed Full-time 5 26.3 12.0 Employed Part—time ._9 31.6 15.0 Total 19 100.0 100.0 Age of Household Head 20-29 1 503 21c“ 30-39 2 10.5 22.8 “0-49 5 26.3 2303 50-59 A 21.1 11.7 60-69 A 21.1 12.6 70 and over ._i 15.8 8.3 Total 19 100.0 100.1 Have Preschool Children at Home Yes 1 5.3 3A.0 No ‘18 9A.? 66.0 Total 19 100.0 100.0 gums.- .- TABLE B.-—Continued. 2A8 Telephone Sample Total Sample n % % Dollars Spent_by Catalog $0 13 68.4 71.0 1.1“ l 503 700 15-29 2 1005 700 30-59 1 5.3 6.0 60—119 1 5.3 7.0 120 and over _1 5.3 3.0 Total 19 100 0 101.0 Dollars Spent by_ Telephone $0 11 57.9 62.0 l-lA 3 15.8 6.0 15-29 1 503 700 30-59 0 0.0 13.0 60-119 3 15.8 7.0 120 and over _1 5.3 5.0 Total 19 100.0 100.0 Number of General Merchandise'Catalogs in Home 0 11 57.9 A7.A l 6 31.6 32.9 2 or more _2 10.5 19.7 Total 19 100.0 100.0 Number of Specialty Catalogs in Home 0 1A 73.7 62.1 1 2 10.5 22.6 2 or more _§_ 15.8 15.3 Total 19 100.0 100.0 “Wu. .-. APPENDIX C MAP OF GRAND RAPIDS CENSUS TRACT AREA, SHOWING RESIDENTIAL AREAS SAMPLED AND MAJOR SHOPPING LOCATIONS q weaves-9' I MAP OF GRAND RAPIDS CENSUS TRACT AREA census “ACTS! ? . qu CENSUS TRACKS SAMPLED: HioH Income: m Mu‘DDLE Incont: m Low INCOME: S_H_9PPING Aggsg‘. - 2 3 SCALE- Expness 353:1: -—--—.—. .O {H BIBLIOGRAPHY ’-w-v~iggrr BIBLIOGRAPHY Books Copeland, Melvin T. Principles of Merchandising. Chicago: A. w. Shaw Co., 1925. Cox, Eli P., and Erickson, Leo G. Retail Decentralization. East Lansing, Michigan: Bureau of Business and Economic Research, 1967. Emmet, Boris, and Jeuck, John. Catalogs and Counters. Chicago: The University of Chicago Press, 1950. Frederick, J. George. Selling by Telephone. New York: The Business Bourse, 19 8. Griffin, Harold E., Jr. Mail Order Retailing--Economic Considerations for Small Operators. University of Connectidfit, 1963. Jonassen, C. T. The Shopping Center Versus Downtown. 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Cambridge: ’Harvard University Press, 1962. Articles and Periodicals Aspinwall, Leo. "The Characteristics of Goods and Parallel Systems Theories." Managerial Marketing: Per- opectives and Viewpoints. Edited by Eugene J. Kelley and William Lazer. Homewood, Illinois: Richard D. Irwin, Inc., 1967. Bauer, Raymond A. "Negro Consumer Behavior." On Knowing the Consumer. Edited by Joseph W. Newman. New York: John Wiley & Sons, Inc., 1968. Bauer, Raymond A.; Cunningham, M.; and Wortzel, L. H. "The Marketing Dilemma of Negroes." Journal of Marketing, XXIX (1956), 1-6. Bender, Wesley. "Consumer Purchase Costs--Do Retailers Recognize Them." Journal of Retailing, XL (Spring, 196A), 1-8, 52. Brunner, James A., and Mason, John L. "The Influence of Driving Time Upon ShOpping Center Preference." Journal of Marketing, XXXII (April, 1968), 57—61. Bucklin, Louis P. "Retail Strategy and the Classifi— cation of Consumer Goods." Journal of Marketing, XXVII (January, 1963), 51-56. Bullock, H. A. 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"The Distinction Between Convenience Goods, Shopping Goods, and Specialty Goods." Journal of Marketing, XXIII (July, 1968), 53-56. Kelley, Eugene J. "The Importance of Convenience in Consumer Purchasing." Managerial Marketing: Perspectives and Viewpoints. Edited by Eugene J. Kelley and William Lazer. Homewood, Illinois: Richard D. Irwin, Inc., 1967. Kornhauser, Arthur and Lazarsfeld, Paul F. "The Analysis of Consumer Actions." Marketing_Models. Edited by Ralph L. Day. Scranton, Pa.: International Text- book Co., 1964. Lansing, John B., and Kish, Leslie. "Family Life Cycle as an Independent Variable." Marketing and the Behavioral Sciences. Edited by Perry J. Bliss. Boston: Allyn and Bacon, 1963. McNair, Malcolm. "Significant Trends and Developments in Postwar Period." Managerial Marketing: Perspectives and Viewpoints. Edited by William Lazer and Eugene J. Kelley. Homewood, Illinois: Richard D. Irwin, Inc., 1962. Parlin, Charles Coolidge. "The Merchandising of Textiles." (1915), reprinted in Marketing in Progress: Patterns and Potentials. Edited by Hiram C. Barksdale. New York: Holt, Rinehart and Winston, Inc., 196U. 3mg: 255 Rathmell, John M. "Discretionary Time and Discretionary Mobility." Managerial Marketing:‘ Perspectives and Viewpoints. Edited by Eugene J. Kelley and William Lazer. Homewood, Illinois: Richard D. Irwin, Inc., 1967. Rich, Stuart U., and Jain, Subhash C. "Social Class and Life Cycle as Predictors of Shopping Behavior." Journal of Marketinngesearch, V (February, 1968), iii-“9 o "Telepurchasing--Major Trend in Retailing?" Forbes, (October 15, 1967), 56, 61-3. Thompson, Donald L. "Consumer Convenience and Retail Area Structure." Journal of Marketing Research, (February, 1967), 37-45. Wells, William D., and Gubar, George. "Life Cycle Concept in Marketing Research." Journal of Marketing Re- search, III (November, 1966), 355-63. Published and Unpublished Reports Bell Telephone System. Executive Summary from A Study of Telephone Shopping in the Baltimore Area. Philadelphia, Pa.: National Analysts, Inc., 1956. Bell Telephone System. Executive Summary from The Locked- ‘In ShOpper, 1963. Bell Telephone System. Executive Summary from 1101 San Francisco Women Tell About Shopping in Department ‘ Stores. The Grand Rapids Press. Grand Rapids Market, Current Data. Grand Rapids, Michigan, 1967. Grey Matter. Vol° 38, No. 9, September, 1967. LaLonde, Bernard J. "Differentials in Supermarket Draw- ing Power and Per Capita Sales by Store Complex and Store Size." Unpublished Ph.D. dissertation, Michigan State University, 1961. Stanford Research Institute. Industrial Economics Division. "In-Home Selling Report No. 225." Menlo Park, California: Stanford Research Insti- tute, October, 1964. :fl-I-u 256 Public Documents Department of Commerce. Survey of Current Business. Washington: U. S. Government Printing Office, 1968. Department of Commerce. Bureau of the Census. 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