Use of time as a determinant of family market behavior

Use of Time as a Determinant of Familv Market Behavior Lucy Chao Lee, Robert Ferber, University

ofIllinois-Urbana

An attempt is made to represent the concept of life style in terms of the use of time. The variables obtained are used to test their effectiveness, in conjunction with socioeconomic and attitudinal variables, for explaining certain types of consumer financial behavior, using data from two panels of young married couples, one of 130 couples in Decatur-Peoria, Illinois, and the other of 185 couples in Chicago. The results indicate that use-of-time variables are significant in helping to explain purchase of durables, ownership of credit cards, and amount of insurance.

The processes by which families make decisions and the factors that enter into these processes are numerous and varied. They include demographic and psychological characteristics, attitudes of the individual family members, and the nature of the relationships among these individuals. Many of these characteristics can be singled out and studied separately, for example, such variables as family composition, occupation and education of family head, and life cycle. Many other factors cannot be singled out because they are not easily measurable or are individually of minor importance. This latter type of factor includes the more amorphous concepts of goals, general attitudes toward life, and various other sociopsychological considerations involved in decision making. A review of the literature on life style suggests a highly intuitive concept, often either too narrow or too diffuse to permit application to broad types of problems. The marketing studies of the 1960s have taken a rather narrow view of life style because of their limited objectives. This is not to deny the usefulness of those studies for short-run managerially oriented problems such as those This paper is part of a larger the National Science Foundation, gratitude.

study made possible by Grant SOC7423458 for which the authors would like to express

from their

Address correspondence to: Lucy C. Lee, Survey Research Laboratory, Universityof Illinois-Urbana,414 David Kinley Hall, Urbana,Illinois 61801. JOURNAL OFBUSINESS 0 Elsevier North-Holland,

RESEARCH Inc., 1977

5 (March,

1977):

75-91

75

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Lucy Chao Lee and Robert

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concerning the “positioning of a product or a brand in a product class. “l Yet marketing scholars feel the necessity of broadening the concept of life style when faced with long-run problems of interest not only to business managers but also to “social” managers, that is, legislators and regulators [7]. The need is manifested in the recent volume [S] published by the American Marketing Association in which attempts are made to broaden life style in order to make it applicable to a variety of marketing problems including the development of advertising strategy, the creation of advertising campaigns, market segmentation, and even marketing strategy with regard to channels of distribution and industrial design. No single definition of life style seems adequate for all purposes, and different approaches to classification can yield very different results [7] _ Two studies seeking to classify automobile drivers by life style segments obtain very different conclusions (e.g., Ziff [ 10: 145-61 and Pernica [7:310]). Actually, stronger conceptualizations are also lacking in other disciplines, e.g., Glock and Nicosia [2] and Nicosia and Glock [ 61. Various aspects of life style are often implicitly embedded in the studies of consumer expenditure patterns and more explicitly in the studies of aspirations by George Katona and his colleagues at the University of Michigan. Reports on “quality of life,” social indicators, and use of leisure time have also tapped various dimensions of life styles that should be relevant to understanding industrialized society. Our point of departure is to view life style as an intuitive concept, fundamental and inherent to the consumer unit, be it individual or family. Essentially the concept refers to the manner in which a consumer unit patterns its way of living, given three broad groups of variables: socioeconomic characteristics, sociological structure, and financial resources. In addition to these constraints, life style will be affected by the goals and attitudes of a consumer unit. For our purposes, attitudes are relevant in the sense that certain components may provide valuable clues with regard to the spending and time-use plans of the consumer unit and of its likely future life style (including possible changes from the present life style). As in the case of ’ See, for example, the excellent article by Alpert and Gatty [ 11. A broader set of descriptors has been investigated by Wells and Tigert [9], but the “dependent” variables are still the purchase of any one product or brand.

Time as Determinant of Family Market Behavior

77

SCCIOEC’WNIC CHAR4CiERISTICS

FIGURE 1: Key Descriptor Variables of Life Style.

attitudes, the relevance of particular goals must depend on the type of problem studied. Thus, in some types of problems certain goals may have little or no relevance, while in other types differences in life styles will probably be reflected by variance in the goals of the consumer units. These three broad sets of variables are not independent but interact in various ways. The principal interactions are shown in Fig. 1. Roth goals and attitudes interact with resources in influencing life style, so that these broad groups of variables exert both direct and indirect effects. The life style of a particular consumer unit may be represented as a configuration of “values” in the multidimensional space represented by these three sets of variables.2 The variables depicted in Fig. 1 may have effects on consumer behavior other than those exerted through their influence on life style. Thus certain attitudes may affect behavior directly in addi2 One set of variables that clearly influences changes in life style from one period to another is purposely omitted here, namely, habits. For our purposes, these variables are not considered to be of a causative nature, especially for explaining consumer behavior. On the other hand, if the primary objective were prediction, habits would be a key variable if the necessary past information were available.

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tion to entering into the determination of life style; in some cases these attitude components may be identical, while in others they may vary. At times, while it may be possible in theory to bypass life style and combine all the individual components of attitudes, goals, and resources in influencing a particular type of behavior, it is probably meaningful to use the composite variable, life style, and also to consider separately other variables that may be components of these three descriptor variables. If the particular definition of life style selected has any influence on that type of behavior, its effect should be noticeable and significant in addition to that of any other variables considered. Highly relevant to this question is the point that life style concepts may be of two types. One category may be termed underlying, or general, values. Concepts of this type usually are involved in explaining many different types of consumer behavior in the marketplace. For example, a life style oriented toward or against the acquisition of material possessions should influence many different types of consumer behavior. As another example, if a family’s life style can be classified as career-oriented, pleasureoriented, or home-oriented, such a distinction should also influence many types of behavior. The second category of life styles is one that distinguishes a particular type of behavior. For example, whether a particular family likes to look after and putter around a house is a specific life style indicator that may be quite influential in any study of the likelihood of a homeowner remaining in that state or selling the house and becoming a tenant. No attempt is made to provide specific criteria for distinguishing between general and specific life styles. Actually, the value of such a distinction is not clear, since only one particular type of consumer behavior is usually studied, and the object will be to use life style in one or more forms to help explain that type of behavior. A much more meaningful problem is how to delineate particular life styles in an individual study and, in addition, how to translate them into operational variables. In this empirical study, we try to resolve this issue by considering use of time as a generalized indicator of life style and then determining how well it helps to explain acquisition of durable goods and three other measures of financial behavior-stock of financial assets, number of credit cards, and amount of insurance.3 3 For a broad review of the manner in which use of time studies of consumer behavior, see Jacoby et al. [ 31.

has been

dealt

with

in

Time as Determinant

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79

The significance of the life style variables will be tested not only alone but also in conjunction with the usual socioeconomic variables (see Appendix) for the explanation of consumer behavior. Method The data used in this study are from two panels of young married couples, one a cohort married in the summer of 1968 in the cities of Decatur and Peoria, Illinois, and the other a younger cohort, where the couples were married in the summer of 1972 in the Chicago area. In both panels the husband was 30 years of age or less at the time of marriage and the marriage was the first for the couples. The couples have been interviewed every 6 months since their marriage, and a great deal of information has been obtained on their demographic characteristics, occupational status, and purchase of various durables, among other subjects. This study is based on data as of 1974, which include the first nine waves of interviews of the Decatur-Peoria panel and the first three waves of the Chicago panel. The sample sizes for this analysis are 130 and 184, respectively, after elimination of incomplete observations. Use-of-Time Variables In addition to the background information obtained, weekly use of time was obtained separately from each member of the couple for the following activities: (1) housework, (2) shop for home needs, (3) job, (4) school, (5) travel to job or school, (6) TV or hi-fi use, (7) other home recreation, (8) spectator recreation outside home, (9) participant recreation outside home, ( 10) visit or entertain friends or relatives. The measures of life style are based on these data. The 10 use-of-time variables have been grouped into three categories. While sophisticated statistical techniques were tested, such as factor analysis [5], the results were actually no better than those obtained with this simple pooling approach. The following three life style categories were used: 1. Home hours-includes (1) housework and (2) shopping for home needs and clothing. While time spent on child care is an essential ingredient of home activity, unusually high figures on child care hours were reported by the parents in both panels. For example, 30% and 60% of the parents in the Decatur-Peoria panel and the Chicago panel, respectively, reported over 100 hours of child care per week. Therefore, to avoid clear duplication, child care hours were not combined

80

Lucy Chao Lee and Robert Ferber with home hours. Furthermore, since in each panel the correlation between child care hours and number of children is significant at the 0.01 level, the influence of children on family behavior can still be tested by using number of children as a demographic variable. 2. Career hours-includes (3) job, (4) school, and (5) travel to school or job. Some couples may go to night school more for recreation than for improving their careers. However, without information about their intentions, time for school is classified as part of career time. 3. Recreation hours-includes the other five categories, which represent outdoor and indoor spectator and participant recreation.

These three categories for both the husband and the wife constitute a set of six life style variables for exaplaining consumer behavior. Durable Good and Financial Behavior Variables Two types of dependent variables were used to measure durable goods acquisition of the families. One is a stock variable, the number of durables owned of a possible list of 13 in 1974, which corresponds to the third and ninth waves of the Decatur-Peoria panel and the Chicago panel, respectively. The other is a difference variable, which gives the net increase in durable stock since the first wave of interviews. The time span covered by this variable is 7 years for the Decatur-Peoria panel and 3 years for the Chicago panel. For each type of dependent variable, two variations were used, one including automobiles and the other excluding them. The financial variables are net total assets (gross financial assets less debts, including value of home and home mortgage), number of credit cards owned by the couple, and face value of life insurance (including term insurance). Patterns in the Use of Time The average number of hours per week spent in different activities by members of the two panels is shown in Table 1. Husbands in both panels spent approximately the same amount of time per week on career and home activities, although husbands in the Chicago panel reported spending more time on recreation activities than their counterparts in Decatur-Peoria. The principal differences, however, in the use of time are for the wives in the two panels. On the average, wives in the Chicago panel devoted nearly three times more hours per week to career

Time as Determinant of Family Market Behavior

81

Table 1: Use of Time Activity, Panel, and Member of Couple (Average Number of Hours per Week) Decatur-Peoria

Chicago

Husband

Wife

Both

Husband

Wife

Both

Home hours Housework Shop for home needs or clothing

10 8

32 27

42 35

9 5

20 15

29 20

2

5

7

4

5

9

Career hours Job School Travel to job or school

49 46 0 3

9 8 0 1

58’ 54 0 4

49 42 2 5

25 21 1 3

14 63 3 8

Recreation hours TV or hi-fi users Other home recreation Spectator recreation outside home Participant recreation outside home Visit or entertain friends or relatives

24 9 5

32 15 6

56 24 11

30 11 6

33 13 6

63 24 12

2

2

4

2

3

5

3

2

5

3

2

5

5 83

I 13

12

8 88

9

17

78

166

Activity

Total

156

activities than the Decatur-Peoria wives, but spent about one-third less time on home activities. This is only to be expected, however, in view of the 4-year average age difference between the two sets of wives; a much higher proportion of the Chicago wives were in the labor market while a much higher proportion of the DecaturPeoria wives had small children. Interestingly, the average number of hours devoted to recreation activities is almost identical for the two groups. Further insight into the differences in the use of time can be obtained by comparing the couples according to various key economic and demographic characteristics. Four such characteristics are used here: family income, husband’s occupation, number of children, and whether the wife is working. To bring out the differences more clearly, the focus in this series of tables is on the three major categories of activity.

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Lucy Chao Lee and Robert

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Table 2: Use of Time (Average Number of Hours per Week) by Category and Family Income (in Thousands of Dollars) Decatur-Peoria

Chicago

Under 13

13-19

20 or more

Total

Under 13

13-19

20 or more

Total

Home hours Husband Wife

10 37

10 32

10 25

10 32

11 23

8 18

6 18

9 20

Career hours Husband Wife

47 2

51 10

49 15

50 9

45 16

50 28

53 34

49 25

25 31

21 33

29 30

24 32

30 35

31 31

30 32

30 33

26.2%

54.6%

19.2%

100.0%

33.7%

48.9%

17.4%

100.0%

34

71

25

130

62

90

32

184

Activity

Recreation Husband Wife

hours

Percentage

of cases

Base

When comparisons are made by income level, different patterns in the use of time are apparent between the two panels. In Decatur-Peoria the hours spent by the husband in home activity or on career varies very little by income level, with a tendency for the number of hours on recreation to rise with income level (Table 2). In Chicago, however, the number of hours spent at home tends to decrease and the hours spent on career to increase with income level, while hours spent on recreation hardly change at all. In contrast, the time-use patterns of the wives are very similar in the two panels: as income level rises, hours spent in the home decrease, hours in career increase, and there is little change in hours spent on recreation. The income of the wife undoubtedly contributes to moving a family into a higher income bracket at the expense of time spent in the home. Actually, at the higher income levels, both husbands and wives spend less time in the home, this decrease being especially marked for the Chicago panel, among which only a minority had children.

Time as Determinant

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83

Table 3: Use of Time (Average Number of Hours per Week) by Category and Husband’s Occupation Decatur-Peoria Activity Home hours Husband Wife Career hours Husband Wife Recreation Husband Wife

hours

Percentage

of cases

Base a 01 = Professional occupations.

Chicago

ala

02

03

Total

01

02

03

Total

10 33

11 32

10 30

10 32

9 19

8 21

11 19

9 20

47 9

49 11

52 6

49 9

49 29

50 23

41 21

49 25

21 35

22 27

23 34

24 32

33 34

29 30

28 34

30 33

32.3%

31.2%

31.5%

100.0%

40.2%

38.1%

21.8%

100.0%

42

41

41

130

14

IO

40

194

and managerial;

02 = clerical,

sales, and craftsmen;

03 = laboring

Differences by occupation are much less pronounced than by income level (Table 3). Although one might expect that husbands in a professional or managerial occupation put in more hours on the job, the table does not support this hypothesis. However, “career hours” may refer to more than one job, and moonlighting was not infrequent among all occupation categories. Moonlighting would be less frequent among wives, and in their case the expected pattern seems to appear, the most hours per week on career activities being reported by women whose husbands are in professional and managerial work. Comparing use of time by number of children in the household we find, as expected, that hours in the home tend to increase with the number of children, especially for the wives (Table 4). Surprisingly, hours spent in the home do not increase with the number of children for Decatur-Peoria husbands. For this group the presence of children seems to stimulate them to spend more hours on their career, partly for economic reasons (and possibly for other reasons as well).

84

Lucy Chao Lee and Robert

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Table 4: Uses of Time (Average Number of Hours per Week) by Category and Number of Children Decatur-Peoria Activity

N=O

N=l

N>2

Chicago Total

N=O

Nzl

Total

Home hours Husband Wife

12 23

10 30

10 36

10 32

8 17

11 28

9 20

Career hours Husband Wife

45 22

50 9

50 5

50 9

48 31

51 8

49 25

28 26

26 31

21 29

24 32

30 31

30 37

30 33

13.8%

40%

46.2%

100.0%

72.8%

27.2%

100.0%

18

52

60

130

134

50

184

Recreation Husband Wife Percentage of cases Base

hours

The most pronounced effect of the presence of children is on the wives, who spend more hours in the home, fewer hours on a career, and more hours on recreation. Comparison of the use of time by whether the wife is working would be expected to yield similar results to those in Table 4, and this is evident from Table 5. The effect of a wife working on the pattern in her use of time is as expected.4 More surprising is the minor effect that a wife working seems to have on the use of time by the husband. The effect seems to be virtually nil. Effects of Use-of-Time Variables As a prelude to considering the effects of the use-of-time variables on the dependent variables, two decisions on the manner of using these time variables need to be reported. One decision relates to whether the data for the two panels should be combined or analyzed separately. While there are some similarities in the pattern on the use of time between the two panels, differences are almost as frequent as similarities. In 4 The fact that wives may spend time on careers when they are not working inconsistent because “career hours” also includes time spent going to school.

is not

Time as Determinant

of Family Market Behavior

85

Table 5 : Uses of Time (Average Number of Hours per Week) by Category and Wife Working or Not Chicago

Decatur-Peoria

Wife does not work

Total

8 17

10 24

9 20

50 9

49 37

49 1

49 25

23 34

24 32

30 32

31 34

30 33

37.7%

62.3%

100.0%

67.4%

32.6%

100.0%

49

81

130

124

60

Wife works

Wife does not work

Total

Home hours Husband Wife

11 25

10 36

10 32

Career hours Husband Wife

49 24

50 0

25 29

Activity

Recreation Husband Wife Percentages

Wife works

hours

of cases

Base

184

addition, since these two panels differed from each other both in environment and in age, separate analysis would seem to be more meaningful. Also, in this way the results obtained from the two panels can serve to a certain extent as a check on each other. The other decision relates to whether the life style variables for the husband and the wife should be kept separate or be combined into one set of figures for the couple as a unit. Combining husband and wife’s use of time has the practical advantage of putting the data on a family basis. However, the distinct patterns in the use of time between husband and wife would be lost by this method. The patterns are very distinct, and the relationship between husband’s and wife’s use of time is not close, as is evident from the following correlation coefficients: Activity Home hours Career hours Reacreation hours a Significant * Significant

at 0.10 level. at 0.01 level.

Decatur-Peoria -0.00 -0.01 0.26”

Chicago O.lY 0.05 0.26*

86

Lucy Chao Lee and Robert

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Thus, it seems best to keep the life style variables separate for husband and wife and to explore their individual effects on the dependent variables. Given these decisions, the effect of the life style variables on each of the dependent variables was tested by a multiple regression approach for each panel in the following steps: 1. The dependent variable was regressed on the set of six life style variables alone. 2. A separate regression of the dependent variable was run on the economic and demographic variables alone. 3. The lifestyle variables and socioeconomic variables in the prior two functions with t-ratios of 1 or more were combined into a final function, and a new set of parameters was estimated. The results of the last step are shown in Table 6 for durable goods and in Table 7 for financial variables. Only those variables that survived the elimination process are shown in these tables. Where no coefficient is shown for a variable in a particular function, the variable was not used in that instance. Table 6 shows that generally such socioeconomic variables as homeownership, family income, and initial stock of durables influence the variation in ownership of durable goods most heavily, whether this variable is expressed as a stock or as an increase over time. Home hours of the wife is the only life style variable that makes an appreciable contribution to the explanation of durables increase in the Decatur-Peoria panel, adding about three percentage points to the value of the coefficient of determination. The sign of the coefficient suggests that the wife’s time in the home and the purchase of durables acted as substitutes in the DecaturPeoria panel. This is not supported by the results for the Chicago panel; the two panels are especially different in this regard-the wives in Peoria-Decatur having small children much more frequently, not working, and spending much more time in the home. 5 5 This result would seem to which implies that if the wife would be larger than otherwise. tion among wife working, wife’s nonworking wives, the simple durables is negative and highly sponding coefficient is just about

conflict with the negative coefficient for wife working, is not working, the increase in the stock of durables The explanation would seem to lie in the intercorrelahome hours, and the dependent variable. Thus, among correlation between home hours and the increase in significant, whereas among working wives the correzero.

Time as Determinant

87

of Family Market Behavior

Table 6: Beta Coefficiems of Durable Goods, Decatur-Peoria (D-P) and Chicago (C) Durables Stock 1974 Including Auto Independent Variables Homeownership Wife works

Durables Increase Wave 1 to 1974

Excluding

Auto

Including Auto

D-P

D

D-P

C

D-P

C

0.25”

0.4ja

0.2ga

0.47”

0.23=

0.52a

-0.13

-0.13b

Family income1973

0.31=

0.10

Durables stockWave 1 (including auto)

0.33b

0.45b

Durables stockWave 1 (excluding auto)

-0.13

0.32=

-0.12

0.12

-0.17b

0.27=

-0.53”

o.2ga

0.43”

0.10

0.08

-0.13

0.09

Excluding D-P 0.26’= -0.16b

0.28=

Auto C 0.53a

-0.12

0.13

-0.03

-0.49”

-0.04

Life style variable Home hours (h) Home hours (w) Adjusted

R2

0.09

0.10

-0.18b

0.10

-0.18b

0.08

0.29a

0.46’

0.29’

0.44’=

0.44=

0.29’=

0.43a

0.30’

0.01

0.01

0.01

0.01

0.03”

0.01

0.03b

0.01

0.02

0.03b

0.02

0.03

0.10=

0.02

0.09O

0.01

Contribution of life style variable Additional bution

to

contri-

R2

Simple r2 ’ Significant b Significant

at 0.01 level. at 0.05 level.

The results for the financial variables, shown in Table 7, are somewhat more favorable for the life style variables. More life style variables survived the elimination process, and for five of the six functions shown the life style variable makes a significant contribution to the explanation of the variation in the dependent variable.

Lucy Chao Lee and Robert

88

Table 7: Beta Coefficients of Financial (D-P) and Chicago (C) Net Total Assets Independent

Variables

D-P

Homeownership

-0.16

Wife works

-0.07

Number

C

D-P

0.36“

0.20b

(h)

0.23b

income

Professional, clerical

in 1973

C

Decatur-Peoria

Amount of Insurance D-P

C

-0.11

-O.lSb -0.16

Age (h) Family

Number of Credit Cards

of children

Education

Variables,

Ferber

-0.03 0.18b

-0.21b

0.06

0.16b

o.20b

-0.03 0.07

0.04

-0.11

0.21 b

0.31=

0.25O

0.25a

0.19b

0.00

0.19b

0.18b

managerial,

Life style variables Home hours

(h)

Career hours

(h)

Career hours

(w)

Recreation Adjusted

hours

-0.08

Additional toR2

-0.20b

(w)

-0.17b 0.03

0.32=

0.26a

0.01

0.02b

0.06 a

0.01

0.04b

0.14O

0.15”

o.of

0.04”

o.09a

0.03 b

0.12=

0.08’=

0.02

of life style contribution

Simple r2 0 Significant b Significant

b

0.30n

R2

Contribution variable

-0.16

at 0.10 level. at 0.05 level.

Starting with the husband’s life style, the career hours of the husband is an important variable in explaining the amount of insurance owned by the Decature-Peoria couples, accounting for more than half of the total explained variance. In addition, home hours of the husband is v&y important in explaining credit card ownership, with a negative sign, which may suggest that the couple needs fewer credit cards the more the husband stays at home (and the less carousing he does).

Time as Determinant

of Family Market Behavior

89

Home hours of the husband is also a determinant of net total assets for both panels. Again, the sign of the coefficient is negative, which suggests that the more the husband stays at home, the less he is engaged in asset-generating activities. Turning to the wife’s life styles in the Chicago panel, note that career hours of the wife is important along with family income in explaining the number of credit cards owned, which suggests that the wife’s activity in the labor market is a major stimulus to the acquisition of credit cards by a couple. It is puzzling, however, to find that recreation hours of the wife, with a negative sign, is a significant determinant of the amount of insurance. Summary Admittedly the data used in this study on life style refer to a highly limited segment of the population, both geographically and with regard to life cycle. Nevertheless, based on these results and other studies we have seen,, .we must conclude that life style variables can supplement socioeconomic variables in explaining market behavior but are unlikelyto replace them. Any search for general,ized explanations of consumer behavior would seem to be most successful if it relies on the much maligned set of socioeconomic variables, that is, such variables as income, age, family size, education, and occupation. With relatively little modification, these variables are always influential in affecting all types of market behavior-~ Conceivably, life style variables based on such concepts as attitudes, interests, and use of time could be made to be equally significant in particular but not necessarily in all instances. Generalized measures oilife style are more likely to contribute to the explanation of a particular type of market behavior if they are more specific to that type of behavior. The use-of-time variables developed in this study as generalized measures of life style are a case in point for the explanation of specific types of consumer behavior in a multivariate context. For example, Tables 6 and 7 revealed that home hours of the wife influence the increase of durables, career hours of the wife influence the number of credit cards, and career hours of the husband influence the amount of insurance. These results also emphasize a truth that tends to be neglected by many people: the value of a particular variable can only be

Lucy Chao Lee and Robert

90

Ferber

ascertained in a multivariate framework. The widespread intercorrelation among behavior and attitudinal variables underlines the need for such an approach. Because of these relationships, much of the apparent effect of the life style variable is substantially reduced when the usual socioeconomic variables are taken into account. However, all things considered, the results discussed suggest that for practical marketing or economic purposes, the collection of either general or specific life style data may be worth the effort.

References 1.

Alpert, L., and Gatty, R., Product keting 33 (April, 1969): 65-69.

2.

Glock, C. Y., and Nicosia, F. M., The Consumer, in The UsersofSociology, Lazarsfeld, W. H. Sewell and H. L. Wilensky, eds., Basic Books, New York,

3.

Jacoby, Jacob, Szybillo, George J., and Berning, Carol Kohn, Time and Consumer Behavior: an Interdisciplinary Overview, J. Consumer Res. 2 (March, 1976): 320-339.

4.

Lazer, William, Marketing’s uary, 1969): 3-9.

5.

Lee, Lucy Chao, An Exploration of the Role of Family Life Style on Selected Behavior Variables, in Advances in Consumer Research, Vol. III, Beverlee B. Anderson, ed., Proceedings of the Sixth Annual Conference of the Association for Consumer Research, 1975. Association for Consumer Research, Cincinnati, Ohio, 1976.

6.

Nicosia, F. M., and Glock, C. Y., Marketing and Affluence: a Research Perspective, in Marketing in the New Science of Planning, R. L. King, ed., American Marketing Association, Chicago, Illinois, 1968.

I.

Pernica, Joseph, The Second Generation of Market Segmentation Studies: an Audit of Buying Motivations, in Life Style and Psychographics, W. D. Wells, ed., American Marketing Association, Chicago, 1974.

8.

Wells, W. D. (ed.), Life Style and Psychographics, ation, Chicago, 1974.

9.

Wells, W. D., Tigert, D. J., Activities, 11 (August, 1971): 27-35.

10.

Changing

Positioning

by Behavioral

Social Relationships,

Interests

Life Styles,

J. Marketing

American

and Opinions,

Marketing

J. Mar-

P. F. 1967.

33 (Jan-

Associ-

J. Advertising Res.

Ziff, Ruth, The Role of Psychographics in the Development of Advertising Strategy and Copy, in Life Style and Psychographics, W. D. Wells, ed., American Marketing Association, Chicago, 1974.

Time as Determinant Appendix:

of Family Market Behavior

List of Socioeconomic

Variable Homeownership Wife working Number of children Education (h)

Age (h) Family income in 1973

Occuptation (h) Professional and managerial Clerical and sales Craftsman Laborer Household worker

Variables and Their Codes Coding 1 = yes; 0 = no 1 = yes; 0 = no Actual number 1 = Some high school or less 2 = High school graduate 3 = Technical school or some college 4 = College graduate 5 = Some graduate school or more Actual years 3 = Under $5,000 6 = $5,000-$6,999 8 = $7,000-$8,999 10 = $9,000-$10,999 12 = $11,000-$12,999 14 = $13,000-$14,999 17 = $15,000-$19,999 22 = $20,000-$24,999 30 = $25,000 or more 1 = yes; 1 = yes; 1 = yes; 1 = yes; 1 = yes;

0 = no 0 = no 0 = no 0 = no 0 = no