Advances in Consumer Research Volume 6, 1979 Pages 133-138
FAMILY LIFE CYCLE AND LEISURE BEHAVIOR RESEARCH
E. Laird Landon, Jr., University of Houston
William B. Locander, University of Houston
The present research investigates the usefulness of Family Life Cycle (FLC) in the study of leisure/recreation behavior. The survey results presented show that FLC groupings capture much of the variance in recreation behavior. Implications are drawn for both public and private sector decision-makers interested in leisure behavior.
In recent years there has been a growing interest in recreation and leisure research by academics, executives, and public officials (Wells & Gubar, 1966; Omura and Talarzyk, 1975; Voss & Blackwell, 1975). Most of the research to date has focused on describing recreation behavior through large scale surveys. Many of the studies have been atheoretical in that they employ little behavioral theory in the research design.
The present article examines the Family Life Cycle (FLC) concept as a useful tool in understanding leisure and recreation behavior. FLC appears to have much potential for explaining leisure behavior because it matches needs with groups of peoples. That is, FLC offers a construct that is both multidimensional and dynamic. Its multidimensional nature is attributed to the fact that FLC is a composite of several important demographic variables. FLC is dynamic because it accounts for the changing family needs and structure over time. If FLC does capture differences in recreational needs, it would be an extremely useful variable for both recreation product companies and public recreation administrators to use in segmenting markets and predicting demand (Engel, Kollat, and Blackwell, 1978, p. 163-5).
The purpose of this paper is to examine recreation behavior from an FLC perspective. This research attempts to answer four questions:
1. Does FLC significantly relate to the frequency and kinds of leisure behavior?
2. Does FLC help explain a community's usage pattern for public facilities?
3. Can FLC be used to measure perceptions of how adequate are a community's facilities?
4. Will the FLC concept provide a means of helping both public and private sector decision makers analyze leisure markets?
The answers to the above questions might well reveal that researchers should devote more study to FLC as an important correlate of recreation and leisure behavior.
Some consumer researchers (Reynolds & Wells, 1977) have become interested in leisure research because of the important implications on an individual's use of time, amusement activities, and recreation equipment purchases. Wells & Gubar (1966) indirectly discussed the relationship between leisure/recreation variables and FLC. Family Life Cycle was reported to be better than age for predicting vacation travel and lodging out of the home city. FLC was correlated with ownership of many recreational objects like toys, sleds, bicycles, boats and trailers. Wells & Gubar quoted literature supporting the notion that for working class men their recreation orientation slowly subsides under the pressure of family obligations and does not return until most of the nest-building demands have been met. Thus, the study of FLC has examined some leisure pursuits, but there has been no work to date examining family life cycle as an exploratory variable relating group needs to recreation activities.
Interviews in 650 households in Pima County were conducted as part of a larger recreation study for the City of Tucson and Pima County recreation departments. The interviews averaged 45 minutes in length questioning respondents on leisure behavior away from home and about attitudes of existing and proposed facilities. The study was part of a program to develop a master recreation plan for the city and county.
The sample was a three stage probability sample. Fifty sampling units were allocated to each of 13 geographical strata, 10 blocks were selected from each stratum proportional to size, and 5 households were selected from each block in a systematic (interval) way.
Family Life Cycle
Table 1 shows the categories suggested by Wells & Gubar. As they indicate there is no consensus among researchers as to the definition of each category. However, in marketing the Wells & Gubar approach has been cited for the longest time. Engel, Kollat, & Blackwell (1978) reproduce the categories in their treatment of FLC.
Table 1 also presents the operational definitions for FLC used in the present study. Several deviations and clarifications should be noted:
1. Researchers have split the age variable at 35, 40, and 45. Forty was used in this study because it is closest to the median household age in the sample.
2. In stages 3 and 4, the young and married descriptions were not operationalized. One could be old and/ or single and still be in these stages. Having young children was felt to be more important than age or even marital status. For example, those who were divorced or who are over 40 with children could not be classified if age and marital status were included. The problem with operationalizing stages 3, 4, & 5 as originally described was that they included 10%, 10%, and 15% single people, respectively. To exclude these people from the child rearing stages was thought to be a misclassification. The higher incidence of divorce today was not a theoretical consideration when the original life cycle was described.
3. Stages 8 and 9 were combined because there were few people in each stage. The combined stages improved the appropriateness of Chi-Square tests. However, for leisure activities one might expect these groups to differ since retirement provides time for additional recreation.
4. Finally, age of children was inferred from a question asking if they were preschool, grade school, or high school age. Even though some ages misclassifications probably resulted, school and grade status are probably more predictive than age. For example, a five and a six year old both in the first grade are probably more alike than two six year olds, one in school and the other not yet in school.
FLC was cross tabulated with all demographic variables, recreation activity variables, and facility use and attitude variables. Chi-Square was computed using alpha equal to .05.
FLC was related to nearly all the demographic measures in this study. Of course, many of the relationships are self evident in that variables like occupation, marital status, number of members in household, number of children in different school grades, and age of household head are part of FLC. Other demographics were related to FLC because of their obvious relationship to the FLC defining variables: employment status of other household members, number of years lived in Pima County (related to age), and sex of respondent (married household heads are more likely to have a woman at home). Finally, some demographic variables relate to FLC for conceptual reasons. Occupation, accounting for retirement, was related to FLC. For example, stage 1 was 35% student compared with 4% in the total sample. Owning or renting was related to FLC in that 28% of stage 1 owned whereas 78% of the total sample did. Likewise, 17% of stage 6 (working over 40, married with no kids) had an advanced degree, whereas ~ 8% of the retired did. In this study, as in Wells & Gubar, income was found to be related to FLC. Income rises until stage 5; then it drops. FLC was related to ethnic background in that 36% of Anglo-Americans were in stages 6, 7, and 8, whereas only 22% of Mexican-Americans were in these stages. The extended families of Mexican-Americans clearly influence this relationship.
FLC is a quite robust measure for capturing the variance of the demographic variables. As a general measure of influence it is statistically useful and analytically meaningful. Only one variable, area type, was not related to FLC. Finally, it appears that FLC is distributed similarly in rural, urban, and suburban areas.
Frequency of Recreation
Table 2 presents the hours per week spent in recreation away from home by FLC. As might be expected, bachelors spend the greatest amount of time in recreation away from home. Likewise, over half the newly married couples without the responsibility of children spend more than 5 hours per week recreating. The frequency patterns of stages 3 and 4 are quite similar in that there is a slight drop in the greater than five hour per week categories. The most dramatic change in recreation frequency occurs between stages 4 and 5. Fifty-four percent of the full nest II stage recreate less than 2 hours per week away from home. This might be attributable to the fact that the youngest child at home is older than 14. Thus, the children are becoming responsible for their own recreation lessening the frequency of family type outings. This recreation frequency pattern appears to continue through stages 6, 7, and 8. In these stages, about 1/3 of respondents stated they did not recreate away from home. Overall, Table 2 shows definite patterns of recreation shifts over the family life cycle.
FLC DESCRIPTION & OPERATIONAL DEFINITIONS
PERCENT OF FLC STAGE SPENDING HOURS PER WEEK RECREATING AWAY FROM HOME
Kinds of Leisure
Table 3 shows the percentage participating in 18 different leisure behaviors for each stage in the family life cycle. All activities in Table 3 were significant at the .05 level. Two sports (golf and shuffle board) are not included because participation rate did not differ by FLC. For each stage, a profile of activity usage can be developed. For example, the bachelor stage was a heavier than average user of tennis, lake swimming, volleyball, horse riding, hiking, camping, running, and dancing. The bachelors were lighter than average in hunting and fishing. The newly married show less activity than stage 1, but have recreation profiles similar (except for hunting and fishing) to bachelors. The family life cycle stage 3 shows about average usage on all activities. This slow down of recreation behavior is in keeping with the general notion that the family concentrates on nest building activities in stage 3. This is shown for most of the activities with the possible exceptions of dancing and lake swimming. As one might expect, the respondents in stage 4 continued to report strong usage of family type activities (i.e., picnic and pool swimming) and those behaviors that can be done by subsets of the family (biking by children). Although FLC stage 5 showed a strong tendency to recreate less than stages 1 to 4, certain behaviors remain strong -- tennis, soccer (children), water skiing horseback riding, hiking, biking, and hunting. Although there is a tendency for most activities to be reduced through stages 6, 7, and 8, some behaviors remain relatively strong across the three groups -- swimming, picnic, hiking, camping, fishing, and dancing. The combined effect of examining Tables 2 and 3 shows that FLC does reveal patterns in both the frequency and types of recreation behavior favored in each stage of the life cycle.
Public Park Usage
The second research question addressed in this study referred to the usage pattern for public facilities. Table 4 shows the number of times per year the household used public parks. By far, the heaviest users of parks are bachelors and families with children between ages 6 and 14. Sixty-eight percent of the bachelors and 67% of full nest I (b) used a park 10 times or more per year while only 53% and 60% of the families in stages 2 and 3 reported that level of park usage. As can be seen from Table 4, the percentages for 10 or more park uses per year drops off dramatically after stage 5. Given that parks are designed to provide recreation with little need for travelling long distances, one might argue that since over 70% of stages 7 and 8 did not use a park more than 3 times a year, that the reduced general level of leisure activity is manifested by little park usage. Another explanation could be that the Parks Department of Pima County is not offering the activities that attract people from stages 7 and 8.
Adequacy of Facilities
When "don't know" responses were included in the analysis, all evaluative questions produced significant results. Since "don't knows" about various age group programs are related to FLC, they were deleted from the analysis. Thus, the evaluative results presented here are from respondents familiar with the activity.
Table 5 presents the results of a neighborhood availability question. It should be noted that those stages without children tend to rate the availability in neighborhoods as fair or poor with less frequency than the stages that have children to consider. Thus, perceptions of facility availability is related to the stage in the FLC. However, a similar question to the one shown in Table 5 asking about how "adequate" the facilities are in the area produced insignificant results.
When the questions were more specific, significant differences were noted for different programs. Table 6 summarizes the results of a program by program rating. The respondents were asked if the program was excellent, good, fair, or poor. Overall significance in these type analyses are secondary to examining percentages for different FLC groups. For example, the lack of significance for preteen programs is not as critical as the fact that 54% of the sample rated the program as "poor" and more than half of the respondents were from the most affected groups -- stages 3 and 4. Similarly, the significant Chi-Square for senior citizens programs is of secondary importance to the fact that nearly half of those in stages 6 to 8 rated these programs high, but 70% of the lower ratings came from those not directly using such activities.
PERCENT PARTICIPATING IN CERTAIN RECREATION ACTIVITIES BY FLC
NUMBER OF TIMES/YEAR HOUSEHOLD USED PARKS
Thus, the FLC concept helps to provide a measure of interpretability to program evaluations in that FLC stages serve as easily identifiable target groups in the community to whom certain recreation activities are supposed to be useful. The answer to the third and fourth research questions appears to be affirmative. The FLC concept offers a viable way to analyze perceptions and recreation behavior within a community.
Although some applications of life cycle have not been as fruitful as expected (Jain 1975), the present study showed that FLC is a promising independent variable for future leisure research. Municipal officials concerned not with personal income, but with the public's needs and usage patterns so as to evaluate and design different programs, should use FLC in demand and effectiveness analyses. FLC offers a construct that could provide a rich independent variable to analyze present and anticipated recreation needs within the community. Likewise, FLC offers a means of segmenting markets into target groups whose recreation needs and subsequent behaviors are relatively homogeneous.
RATINGS ON AVAILABILITY IN NEIGHBORHOOD BY FLC
RESULTS OF RATING OF DIFFERENT PROGRAMS BY FLC
James F. Engel, David T. Kollat, and Roger D. Blackwell, Consumer Behavior, (Hinsdale, Illinois: Dryden Press, 1978)
Subhash C. Jain, "Life Cycle Revisited: Applications in Consumer Research," In M. Schlinger (Ed.) Advances in Consumer Research, Volume 2, 1975, 39-49.
Glenn S. Omura and W. Wayne Talarzyk, "Relationships Between Consumers' Shopping and Leisure Activities and Their Attitudes Toward the Energy Crises: A Cross Sectional Study," In M. Schleinger (Ed.) Advances in Consumer Research, Volume 2, 1975, 803-815.
Fred D. Reynolds and William D. Wells, Consumer Behavior, (New York: McGraw-Hill, 1977)
Justin L. Voss and Roger D. Blackwell, "Markets for Leisure Time," In M. Schlinger (Ed.) Advances in Consumer Research, Volume 2, 1975, 837-845,
William D. Wells and George Gubar, "Life Cycle Concept in Marketing Research," Journal of Marketing Research, (1966) 355-63.