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Adolescents' influence in family purchase decisions: A socialization perspective
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Adolescents’ Influence in Family Purchase Decisions: A Socialization Perspective Ellen R. Foxman Patriya S. Tansuhaj Washington
State University
Karin M. Ekstrom University
of GBthenburg
Adolescents’ influence in family decision making was studied in the context of consumer socialization. The extent to which adolescents influence family decisions was found to be affected by family communication environment, adolescents’ personal resources, and perceived product knowledge and importance. Mothers, fathers, and adolescents were found to differ in their assessments of the amount of influence adolescents had, both in family choice of specific products and in the general family purchase decision process. Introduction Over 14 million American families have both parents working full-time (U.S. Census Bureau, 1987). The number of single-parent households also makes up an important proportion of families; it has been estimated that by 1990 only 69% of the children raised in the United States will be raised by both parents (Glick, 1984). The effect of these demographic changes on family decision-making roles has not been adequately examined. Although children’s participation in family decision making may have increased, we have little knowledge about the nature or amount of such an increase. The influence of the child in family purchase decision making therefore deserves further investigation. In previous family decision research, most studies have focused on parents alone or have demonstrated how children’s purchase decisions are influenced by parents through consumer learning (Douglas, 1983; Filiatrault and Ritchie, 1980; McNeal, 1987; Moschis and Churchill, 1977,1978; Tallman et al., 1983). Fewer studies have dealt with how children may influence family decisions (Atkin, 1978; Belch et al., 1985; Darley and Lim, 1986; Moschis and Mitchell, 1986; Roberts et al., 1981). Different family members’ perceptions of children’s purchase influence often have
Address correspondence State University, Pullman,
to Patriya S. Tansuhaj, WA 991664725.
Journal of Business Research 18, 159-172 (1989) 0 1989 Elsevier Science Publishing Co., Inc. 655 Avenue of the Americas, New York, NY 10010
College
of Business
and Economics,
Washington
0148-2%3/89/$3.50
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not been examined, and some studies that do seek parents’ views attempt to explain children’s influence primarily by examining differences among parents (Roberts et al., 1981). Finally, the relatively narrow range of products and influence occasions examined in past research perhaps may have led to understating children’s influence in family purchase decision making. We propose socialization as a theoretical perspective for explaining children’s roles in family purchases and thus increasing understanding of the family as a consumption unit. The family is viewed as a dynamic social group in which parents and children both teach and learn. Certain factors (e.g., communication environment, children’s earnings) shape the nature and content of communication within this social unit. By affecting what family members teach and learn, these factors affect children’s roles in family decision processes and outcomes. The nature and extent of influence within families in part shapes the socialization process. For example, Moschis (1987) explains that children’s influence on purchase decisions may help parents redefine their consumer roles to incorporate the child’s expectations, thereby resulting in resocialization to a modified consumer role. The purpose of the present study is to investigate adolescents’ roles in family purchasing using this socialization perspective. We examine the effect of several environmental socialization factors on two types of purchase influence: influence on outcomes and influence occurring during the decision process. We attempt to broaden understanding of family socialization and consumption relationships by including the child and both parents as respondents. Studies of family decision making have often found that respondents disagree in their ratings of different family members’ influence in purchase decisions (Belch et al., 1985; Davis, 1976; Davis and Rigaux, 1974). Because who reports children’s influence might be a factor in determining the amount and type of influence children are felt to have, all three family members’ ratings of influence are examined. In addition, we examine a range of products with different primary users and differing levels of involvement on the part of family members. Socialization
Factors
Affecting
Children’s
Influence
Socialization factors affecting children’s influence in family purchase decisions include family structure, the child’s individual characteristics, and the nature of the product being decided upon. Family Communication
Environment
McLeod and Chaffee (1972) developed a typology characterizing parent-child communication structure and consequent socialization as a combination of two communication patterns-socio-oriented and concept-oriented. In a socio-oriented communication environment, the child avoids controversy and does not argue, since he or she does not want to risk offending others. In a concept-oriented communication structure, the child is encouraged to develop his or her own ideas. Moschis (1985) and Moschis et al. (1984) empirically demonstrated a relationship between family communication patterns and how children are socialized. If socialization is considered a reciprocal process, family communication patterns are also expected to explain how parents are influenced by their children. This has
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161
been dealt with in a few studies, but only indirectly (Roberts et al., 1981). It is expected that a child in a socio-oriented family environment will be less likely to affect family purchase decisions or participate in the decision process than a child in a concept-oriented communication environment, i.e.: Hl:
Children in a concept-oriented family will: a. have greater influence relative to parents in family purchase decisions than children in a high socio-oriented family. b. have greater influence in the decision process than children in a sociooriented family.
Child’s Individual Characteristics Resource theory (Blood and Wolfe, 1960) asserts that the comparative resources of parents and children will determine who dominates in family decisions. Previous studies based on resource theory have examined spousal dominance and explained the husband’s dominance in family decisions on the basis of income and occupation, i.e., greater resources (Brinberg and Schwenk, 1985; Komarovsky, 1961; Schaninger and Allen, 1981). There is evidence that wives’ influence in family decisions has increased as more wives work outside the home and their financial resources increase relative to that of their husbands (Brinberg and Schwenk, 1985). Children’s personal resources should also affect their relative influence in family purchase decisions, with children who have greater resources having greater influence. Children’s resources may include their income contribution, employment status, grades, or perceptions of parental love and confidence. Churchill and Mosthis (1979) hypothesized that a first-born adolescent would interact more frequently with his or her parents regarding consumption matters. Their study found a positive but nonsignificant relationship between birth order and family communication. Examining financial resources, Moschis and Mitchell (1986) found empirical support for the idea that adolescents with outside incomes are more likely to purchase products independently. Children’s income, of course, is only one type of personal resource they might have; a more comprehensive measure of this construct might better support the following hypothesis: H2:
A child’s influence the child’s personal
in family decision resources.
making
will be positively
related
to
Product-related Factors Product importance and product knowledge are expected to affect children’s relative influence in family decisions. A person who is more involved with a product will be more active in the product decision process and have a greater effect on the decision outcome (Krishnamurthy, 1981). Consumer socialization studies have shown that parents’ influence on children varies depending on a child’s knowledge of the product and perceptions of product importance. Parents’ influence has been found to increase with high-risk products or products that the child knows little about (Moschis and Moore, 1979). Looking at family purchase influence from the child’s side, Roberts et al. (1981) reported that a greater number of children’s influence attempts was associated with
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a higher rate of product usage by the family. A reasonable explanation for this finding is that children more frequently attempt to influence decisions for products they consider to be important. We therefore state the following hypothesis: H3:
Research
A child will have greater influence in family decision purchase decisions: a. that he or she considers important. b. about which he or she has a high level of product
making
for product
knowledge.
Method
Sample The sample for the study consisted of 161 families with a father, mother, and their adolescent child in three northwestern towns. Adolescent children were chosen for the study because that age group was felt to be more appropriate for investigating children’s influence in family decisions from a socialization perspective. Infants and younger children clearly affect parental behavior and purchase decisions but are less suitable respondents for a variety of reasons: Younger children are not fully cognitively developed (Elkind, 1968; Mussen et al., 1969; Piaget, 1970) and have been demonstrated not to understand economic concepts (Strauss, 1952) and consumer skills related to information processing (Roedder, 1981; Wackman and Wartella, 1977). Middle-school and high-school officials in the area were contacted, and four schools agreed to participate in the survey. Questionnaires were delivered to the teachers to be administered in class. Each student was then requested to take two questionnaires home for his/her parents to complete independently. Students were asked to return questionnaires to school in one week. Of 525 students who filled out the “adolescent” version of the questionnaire, 161 brought back both parents’ surveys. The adolescent sample consisted of male and female middle-school and high-school students, with an average age of 15 and an age range of 11-18. They were from primarily middle-class families, with an average household income of between $30,000 and $40,000 annually. Most mothers were between 30 and 50 years old and had at least a high-school diploma (33%) or some college education (53%). Most fathers (60%) were between 40 and 49 years old; 25% were between 31 and 39 years old. Fathers were also relatively well educated, with 28% having completed high school and 70% having undergraduate or graduate degrees.
Dependent Measures Dependent variables in this study included two types of adolescent influence: product-choice influence and general influence in the family decision process. Most studies of children’s influence in the family focus on the degree to which children’s preferences match purchase outcomes in family decisions (i.e., the extent to which they dominate in family decisions). Decision influence is less often measured by constructs more closely related to socialization, such as purchase participation or extent of learning or knowledge acquisition (Roberts et al., 1981). The present study measured children’s influence in family decisions using both a product-choice
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measure and a more general measure of participation in the decision process. Adolescents and both parents were asked to rate children’s influence using both types of measure, yielding six separate measures of influence for each adolescent. The product-choice measure included 14 products, six for family use, six for the adolescent’s own use, and the remaining two for parental use. The product set included both high-involvement products (e.g., automobile, computer, dress clothes) and low-involvement products (e.g., toothpaste, groceries). Respondents were asked to rate relative influence using a l-5 scale, with 1 = a purchase decision made entirely by the adolescent, 2 = a decision in which the adolescent has more say than the parents, 3 = a decision in which parents and adolescent had equal influence, 4 = a decision in which the parents have more say, and 5 indicating a decision made entirely by the parents. It assumes an equal distance property of ordinal scales, recognizing that an ordinal interpretation may not be justified for all respondents. The Cronbach alpha reliability measure indicated high internal consistency, with alpha = 0.80 on adolescents’ responses, alpha = 0.84 on mothers’ responses, and alpha = 0.80 for fathers’ responses. For all except the last hypothesis (which examined knowledge and importance perceptions about particular products), a summary influence variable was created by taking the mean of the influence responses for the 14 products. The measure of general influence in family decision processes included six Likert scale items (1 = strongly agree, 5 = strongly disagree). These items were more communication and socialization oriented, e.g.: l
l
Adolescent
usually
Adolescent usually family use.
suggests
stores to shop.
goes shopping
with parents
when
looking
a product
for
The Cronbach 0.74, and 0.86 except the last mary variable items.
alpha reliability coefficients were satisfactory, with alphas of 0.70, for adolescent, mother, and father responses respectively. For all hypothesis (which focused on particular product decisions), a sumwas created by taking the mean of the responses to the individual
Independent
Measures
Family Communication Environment. Consumption-related family communications were measured using Moschis and Moore’s (1979) 12-item scale based on McLeod and Chaffee’s typology (1972), discussed above. Adolescents were asked to respond to the items using a scale in which 1 indicated very often and 5 indicated never. Responses were summed across the six items for each dimension. Following Moschis and Moore’s (1979) procedure, families were placed in one of the four family communication environment groups using median splits on the socio- and concept-dimension scores. Internal consistency and validity had been evaluated in previous studies (Moschis and Moore, 1979; Moschis et al., 1984). In the present study, alpha coefficients were 0.80 for the socio-dimension items and 0.62 for the concept-dimension items.
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Personal Resources. Several single-item measures were used to capture adolescents’ personal resources: birth order (i.e., firstborn child or not), only-child status, child’s employment, child’s income level, and self-reported school grades. We also developed a 4-item Likert scale to measure adolescents’ perceptions of parental support and confidence in the child’s abilities. It yielded a Cronbach alpha of 0.84 and includes the following items: l
I think my parents don’t have much faith in my abilities [reverse scaled].
. My parents are confident that I will do well in the future. l
l
My parents feel good about my accomplishments. I believe that my parents’ attitude about my ability is [l = very positive, 5 = very negative].
Children’s birth order and the presence or absence of siblings are represented as a single variable (Place) with three levels: first and only child, first child of several, or neither the first nor the only child. A similar strategy is employed with respect to child’s employment status and earnings. In this case, the variable (Earn) also has three levels: no income (not employed), low income (less than the median reported income for children), or high income (equal to or greater than the median reported income for children). School grades and perceptions of parental support are also categorized as either high or low based on median splits. Product-related Factors. The importance of products included in the study was measured using a 5-point scale ranging from “really important” to “really unimportant.” Adolescents’ knowledge of selected products (i.e., dress clothes, personal computers, and bicycles) was measured using Selnes and Gronhaug’s (1986) 4-item scale. This assesses subjective knowledge (by respondents’ ratings of the degree to which they know the relevant decision criteria), confidence (measured by asking how respondents thought their closest friend would evaluate their familiarity with the products), advice giving (by asking whether respondents had been asked for advice about the products), and self-evaluation (by asking about likelihood of success in purchasing the products). Alpha coefficients assessing the reliability of the product knowledge measure were 0.80 for bicycles, 0.81 for personal computers, and 0.78 for dress clothes.
Data Analyses
and Findings
Multivariate analysis of variance (MANOVA) was used to simultaneously examine the two influence variables and influence ratings from the three family members in testing the hypotheses. Analysis of variance (ANOVA) and Scheffe’s tests of means were used to uncover the location and nature of group differences identified by MANOVA. Means and standard deviations for all significant main effects and interactions are presented in Table 5. Family
Communication
Environment
According to the first hypothesis, children from concept-oriented families were expected to have greater influence in purchase decision making than children from
Adolescents’
Influence
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Table I. Effect
of Communication
Environment
on Children’s
Influence
in Family
Decision Making
df MANOVA Communication environment Respondent Communication environment x respondent ANOVAS 1. Product intluence Communication environment Respondent Communication environment x respondent 2. General influence Communication environment Respondent Communication environment x respondent
F
Probability
2,245 4,490 4,490
24.19 15.05” 0.54
0.01 0.01 0.71
5,246 1 2 2 5,246 1 2 2
20.25 39.56 30.37 0.49 5.06 23.55 0.12 0.49
0.01 0.01 0.01 0.62 0.01 0.01 0.89 0.62
“F value represents Wilks’ lambda for multivariate tests; it is the exact F calculated by the SAS program based on Rao (1973). providing an appropriate degree of freedom for p = 2.
socio-oriented families. Families that were high or low on both socio and concept communication dimensions were excluded, resulting in a comparison of 49 sociooriented families with 35 concept-oriented families. The analysis (summarized in Table 1) strongly supports the hypothesis (F = 24.79, p < 0.01). Communication environment has a significant effect on both product choice and genera1 influence (F = 39.56 and 23.55 respectively, both p < 0.01). Mean influence ratings were 3.77 (product choice influence) and 2.97 (general influence) for adolescents from concept-oriented families. For those from socio-oriented families, mean ratings were 3.46 and 2.58, respectively. Which family member reported children’s influence was also a significant main effect in the analysis (F = 15.05, p < 0.01). There was no significant interaction between communication environment and respondent. Influence ratings were found to vary by respondent only for the product choice influence measure (F = 30.37, p < 0.01). Respondent was not a significant source of variation for the genera1 influence measure (F = 0.12, p < 0.89). It is possible that differences by respondent are not detected by the genera1 influence measure because it evaluates influence in a process that occurs over time, and individuals may “average out” their feelings over many occasions in responding to each item. The product choice influence measure directs respondents to recall specific purchase occasions and thus appears to be more likely to uncover differences in influence perceptions. For the product choice influence measure, the mean influence ratings from mother and adolescents of adolescents’ decision influence were not significantly different (mean = 3.51 and 3.50, respectively). Fathers, however, perceived adolescents to have significantly less influence in product choice than did mothers and adolescents (mean = 3.91). This may possibly reflect traditional family role perceptions (i.e., fathers’ perceptions of themselves as family leader and having the greatest say in family decision situations).
Personal Resources Children’s influence in family purchase decisions was expected to be positively related to their personal resources. Our analysis, summarized in Table 2, generally
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Table 2. Effect of Personal Resource Factors on Children’s
Influence in Family
Decision
Making
MANOVAh Child’s income Respondent Place x child’s income Child’s income x school grades Child’s income x parent’s opinion of child ANOVAS 1. Product influence Child’s income School grades Respondent 2. Participatory influence School grades Parent’s opinion of child Child’s income x parent’s opinion of child
df
F
4,764 4.764 8,764 4.764 4.764
2.13 20.12 1.88 1.95 2.68
0.08 0.01 0.06 0.10 0.03
33,383 2
5.21 3.89 8.71 65.07 1.79 3.46 15.63 4.51
0.01 0.02 0.01 0.01 0.01 0.06 0.01 0.01
1 2 33,383 1 1 2
Probability
“Equivalent to Wilks’ lambda on multivariate tests. bOnly significant effects and interactions presented.
supports the second hypothesis. Only the child’s earning/employment status and respondent were significant as main effects (F = 2.13 and 20.12, respectively, p < 0.08 and O.Ol), but the other three personal resource variables were significant or marginally significant in interaction with the child’s income status. ANOVAs of the two influence variables, with all personal resource variables in one design, were significant overall (F = 5.27 and 1.79, respectively, both p < O.Ol), but which personal influence factors were significant depended on the influence variable being examined. Children’s grades were the only personal resource factor that was significant in both analyses, with children with high grades having more relative influence in choice of products than did children with low grades. Adolescents’ earning/employment status was significant for product choice influence only; as hypothesized, adolescents in the employed/high earnings condition had greater relative influence in product choice decisions than children who were not employed and had no earnings. Parents’ opinion of the child was significant for general influence only, with adolescents whose parents had a high opinion of their abilities having more influence in family purchase processes. Though children’s earning status was not significant by itself, there was a significant interaction between children’s earning status and parents’ opinion of the child (F = 4.51, p < 0.01). Plots of the means of these two variables indicated a generally ordinal interaction, i.e., high earning status and high parental opinion were both associated with greater influence by children in family decision processes. The effect of having different raters for the two influence variables was essentially the same for hypothesis 2 as it was for hypothesis 1: that responses came from different family members was not a significant source of variation for the general influence variable, but did significantly affect product choice influence ratings (F = 65.07, p < 0.01). Mothers’ and adolescents’ responses were found to be alike and differed from fathers’ responses. Fathers reported significantly less product choice influence by children relative to parents than did mothers and children.
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Table 3. Effect of Children’s Knowledge and Importance Influence in Purchase Decisions” Source’
Importance Product Importance x respondent Knowledge X respondent Product x respondent Explained Residual Total
df 1 4
Sum of Squares
Perceptions on Their Relative F
Significance
25.13
32.28
544.37
174.84
0.01 0.01
15.85
10.18
0.01
5.52 1059.87 1639.37 1833.14 3472.51
3.35 170.20 35.70
0.03 0.01 0.01
2
2 8 59 2355 2414
167
“Includes influence ratings by mothers, fathers, and children. *Nonsignificant main effects and interactions not reported.
Product-related Factors Regarding the third hypothesis, children were expected to have more influence in family purchase decisions for products they considered important and about which they were knowledgeable. Since the hypothesis focused specifically upon purchase decisions rather than the purchase process in general, only the product choice variable was examined, and ANOVA was used in testing this hypothesis. Our expectations were supported or contradicted depending on whose assessment of children’s influence was included in the analysis. The initial analysis of variance including the following factors: child’s importance ratings; child’s knowledge ratings; the five products for which there were knowledge ratings; and decision influence ratings for children from mothers, fathers, and children (see Table 3). This analysis was significant overall (F = 35.70, p < O.Ol), but the results were contrary to expectations. Children’s importance rating was a significant factor in determining child’s decision influence (F = 32.28, p < O.Ol), but children had less influence in decisions for products they rated important than for those they considered unimportant (mean = 3.28 for low importance products, 3.49 for high importance products). The significant interaction (F = 10.18, p < 0.01) between importance rating and influence rater suggested a possible explanation for the contrary findings. In this interaction, adolescents reported approximately the same influence on products of low and high importance; parents, however, rated children’s influence as much greater for products that children considered unimportant. This implied that parents’ assessment of children’s influence for the products included in the analysis differed considerably from children’s assessment of their own influence, and that the two parental influence ratings might be masking relationships among children’s importance, knowledge, and influence ratings. In order to check this possibility, a second analysis of variance was performed in which parental ratings of child influence were excluded. This analysis (presented in Table 4) was also significant overall (F = 40.50, p < 0.01) and generally supported our expectations. Children’s knowledge was a marginally significant factor in determining children’s influence and, while the difference between high and low knowledge condition means was not statistically significant, it was in the expected direction. That is, children reported more influence in decisions for products about which they had a high level of knowledge. Children’s influence also varied by
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Table 4. Effect of Children’s Knowledge and Importance Influence in Purchase Decisions” Source” Knowledge Product Importance Explained Residual
x product
Total
df
Sum of Squares
1 4 4 19 785
2.94 686.09 8.37 698.56 712.64
804
1411.20
Perceptions on Their Relative F 3.23 188.94 2.30 40.50
Significance 0.07 0.01 0.05 0.01
“Includes only children’s influence ratings. bNonsignificant main effects and interactions not reported.
product in a logical way: Adolescents tended to report more influence for products that were for their personal use (mean = 2.16 for dress clothes for themselves) and the least influence in decisions regarding the purchase of parents’ clothes (mean = 4.70). Importance ratings for the products were not significant as a main effect (F = 0.03, p < 0.87), but did have a marginally significant interaction with product type (F = 2.30, p < 0.06). Examination of influence means suggested that adolescents tended to report greater decision influence for those products that they considered important and that were primarily for their use (see Table 5). Summary
and
Suggestions
for Future
Research
In this study, we found that adolescents’ influence depended on who was assessing it: Adolescents and their mothers consistently reported greater influence than did fathers. Adolescents also were found to have more influence in a concept-oriented family communication environment. Some personal resource factors, especially grades, were related to increased influence by children in family purchase activities. Finally, children’s knowledge and importance perceptions for specific products also affected their influence in family purchase decisions. The present study suggests several interesting directions for future research. Concerning influence specifically, we view product choice and purchase in families as the end result of a series of tasks and family member interactions; influence relationships exist in and affect the results of all these tasks and interactions. Because of this relationship, measuring adolescents’ or other family members’ influence and participation in decision processes potentially can have considerable value in explaining why particular family members dominate or do not dominate in particular purchase decision situations. Looking at perceptions of children’s influence from the viewpoints of both parents and the child also promises to provide a deeper, more dimensional understanding of the role of children in family purchase influence relationships. Our analyses consistently revealed real differences in family members’ perceptions of adolescents’ decision influence. Future studies should investigate patterns of agreement or disagreement in complete families (not just triads) in order to understand these differences more fully. As the number of information sources in such studies increases, however, so does the need to develop special analytic approaches in order to understand the multiple influence relationships inherent in such data.
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Table 5. Influence
Means (Standard
Deviations)
for Significant Main Effects and
Interactions Hypothesis 1 Communication Product General
environment
choice influence” influenceb
Respondent Product
choice
influence
Socio
Concept
3.77 (0.46) 2.97 (0.67)
3.46 (0.40) 2.58 (0.54)
Mother
Father
3.51 (0.37)
3.91 (0.45)
Hypothesis 2 School grades Product choice influence General influence Child’s income Product choice influence Parent’s opinion of child
Produce Earnings (general
x
Product:
Low 3.63 (0.50) 2.72 (0.59)
Importance Respondent
x
3.58 (0.39)
all respondents’ influence ClothesClothesParents Child
High importance Low importance
4.04
(0.48)
3.01 (0.66) Child 3.47 (0.46)
3.77
High
Low
No
2.65 (0.64) 2.99 (0.73)
2.70 (0.57) 2.80 (0.56)
2.75 (0.59) 3.13 (0.67)
assessments PCFamily
(1.39)
(product
choice
PCChild
BicycleChild
High
2.51 (0.95) Low
3.49 (1.22)
3.29 (1.16)
3.56 (0.96)
3.82 (0.89)
influence
respondent
Father
3.74 (0.52) Low
Earnings
3.37 (1.24) choice
3.77 (0.52) 2.88 (0.68) No
High
Importance Product
3.62 (0.49) 2.77 (0.59)
Mother
choice influence parental opinion influence)
3-including
Low
Hieh
High opinion Low opinion Hypothesis
High
3.64 (0.49)
General influence Respondent
Child 3.50 (0.44)
influence) Mother
Father
Child
3.50 (1.15) 3.26 (1.11)
3.58 (1.11) 3.20 (1.11)
3.40 (1.38) 3.41 (1.25)
Researchers could benefit more from a broader, more representative sample that would permit more confident generalization of findings; the sample in the present study was skewed towards middle- and upper-middle-income families and more
educated parents, and this may have affected the analysis results. Further examination of the effect of parental product importance and knowledge ratings on their perceptions of child decision influence would also help clarify the relationship among the views of mother, father, and child. A final important area for future research involves the development of better measures of both decision influence and consumer socialization. Most previous family decision-making studies have focused on measuring specific decision outcomes, an approach that has so far has been relatively lacking in explanatory value. It may prove that some broader measure of influence, such as the general influence measure used here, will permit a broader understanding of family influence processes. Future research also needs to focus on the relationship between decision-
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Table 5. (continued) Knowledge x Respondent Respondent
(Product choice influence) Mother 3.42 (1.14) 3.36 (1.14)
High knowledge Low knowledge Product x Respondent Respondent
Child 3.35 (1.34) 3.48 (1.29)
(product choice influence) Mother 2.65 4.60 3.77 3.52 2.45
Clothes-parents Clothes--child PC-family PC--child Bicycle--child Hypothesis 3-including Knowledge
Father 3.46 (1.09) 3.36 (1.17) Father
(0.82) (0.64) (0.87) (0.91) (0.88)
2.77 4.55 3.77 3.49 2.52
(1.00) (0.64) (0.85) (0.90) (0.87)
Child 4.70 2.16 3.91 3.67 2.57
(0.58) (1.02) (0.94) (1.05) (1.08)
children’s infiuence assessments only High
Product choice influence ClothesParents Product: 4.70 (0.58)
ClothesChild 2.16 (1.02)
Low
3.55 (1.34) PCFamily 3.91 (0.94)
Importance x product (product choice infuence) Importance
3.48 (1.29) BicycleChild
3.67 (1.05)
2.57 (1.08)
High 4.67 3.88 3.52 2.30 2.15
Clothes-parents Clothes-child PC-family PC+hild Bicycle-child
PCChild
Low
(0.60) (0.96) (1.13) (0.99) (1.00)
4.81 3.97 3.75 2.69 2.18
(0.47) (0.93) (1.00) (1.11) (1.07)
“1 = decision made all by child. 2 = more say by child, 3 = equal say, 4 = more say by parents, 5 = decision made all by parents. ‘1 = strongly agree (that child has influence). 2 = agree. 3 = neither agree nor disagree. 4 = disagree. 5 = strongly disagree.
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of Marketing
of Parent-Child Interaction 42 (October 1978): 41-45.
in Supermarket
Decision-
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J BUSN RES 1989:18:159-172
Adolescents’ Influence in Family Purchase Decisions: A Socialization Perspective Ellen R. Foxman Patriya S. Tansuhaj Washington
State University
Karin M. Ekstrom University
of GBthenburg
Adolescents’ influence in family decision making was studied in the context of consumer socialization. The extent to which adolescents influence family decisions was found to be affected by family communication environment, adolescents’ personal resources, and perceived product knowledge and importance. Mothers, fathers, and adolescents were found to differ in their assessments of the amount of influence adolescents had, both in family choice of specific products and in the general family purchase decision process. Introduction Over 14 million American families have both parents working full-time (U.S. Census Bureau, 1987). The number of single-parent households also makes up an important proportion of families; it has been estimated that by 1990 only 69% of the children raised in the United States will be raised by both parents (Glick, 1984). The effect of these demographic changes on family decision-making roles has not been adequately examined. Although children’s participation in family decision making may have increased, we have little knowledge about the nature or amount of such an increase. The influence of the child in family purchase decision making therefore deserves further investigation. In previous family decision research, most studies have focused on parents alone or have demonstrated how children’s purchase decisions are influenced by parents through consumer learning (Douglas, 1983; Filiatrault and Ritchie, 1980; McNeal, 1987; Moschis and Churchill, 1977,1978; Tallman et al., 1983). Fewer studies have dealt with how children may influence family decisions (Atkin, 1978; Belch et al., 1985; Darley and Lim, 1986; Moschis and Mitchell, 1986; Roberts et al., 1981). Different family members’ perceptions of children’s purchase influence often have
Address correspondence State University, Pullman,
to Patriya S. Tansuhaj, WA 991664725.
Journal of Business Research 18, 159-172 (1989) 0 1989 Elsevier Science Publishing Co., Inc. 655 Avenue of the Americas, New York, NY 10010
College
of Business
and Economics,
Washington
0148-2%3/89/$3.50
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not been examined, and some studies that do seek parents’ views attempt to explain children’s influence primarily by examining differences among parents (Roberts et al., 1981). Finally, the relatively narrow range of products and influence occasions examined in past research perhaps may have led to understating children’s influence in family purchase decision making. We propose socialization as a theoretical perspective for explaining children’s roles in family purchases and thus increasing understanding of the family as a consumption unit. The family is viewed as a dynamic social group in which parents and children both teach and learn. Certain factors (e.g., communication environment, children’s earnings) shape the nature and content of communication within this social unit. By affecting what family members teach and learn, these factors affect children’s roles in family decision processes and outcomes. The nature and extent of influence within families in part shapes the socialization process. For example, Moschis (1987) explains that children’s influence on purchase decisions may help parents redefine their consumer roles to incorporate the child’s expectations, thereby resulting in resocialization to a modified consumer role. The purpose of the present study is to investigate adolescents’ roles in family purchasing using this socialization perspective. We examine the effect of several environmental socialization factors on two types of purchase influence: influence on outcomes and influence occurring during the decision process. We attempt to broaden understanding of family socialization and consumption relationships by including the child and both parents as respondents. Studies of family decision making have often found that respondents disagree in their ratings of different family members’ influence in purchase decisions (Belch et al., 1985; Davis, 1976; Davis and Rigaux, 1974). Because who reports children’s influence might be a factor in determining the amount and type of influence children are felt to have, all three family members’ ratings of influence are examined. In addition, we examine a range of products with different primary users and differing levels of involvement on the part of family members. Socialization
Factors
Affecting
Children’s
Influence
Socialization factors affecting children’s influence in family purchase decisions include family structure, the child’s individual characteristics, and the nature of the product being decided upon. Family Communication
Environment
McLeod and Chaffee (1972) developed a typology characterizing parent-child communication structure and consequent socialization as a combination of two communication patterns-socio-oriented and concept-oriented. In a socio-oriented communication environment, the child avoids controversy and does not argue, since he or she does not want to risk offending others. In a concept-oriented communication structure, the child is encouraged to develop his or her own ideas. Moschis (1985) and Moschis et al. (1984) empirically demonstrated a relationship between family communication patterns and how children are socialized. If socialization is considered a reciprocal process, family communication patterns are also expected to explain how parents are influenced by their children. This has
Adolescents’
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161
been dealt with in a few studies, but only indirectly (Roberts et al., 1981). It is expected that a child in a socio-oriented family environment will be less likely to affect family purchase decisions or participate in the decision process than a child in a concept-oriented communication environment, i.e.: Hl:
Children in a concept-oriented family will: a. have greater influence relative to parents in family purchase decisions than children in a high socio-oriented family. b. have greater influence in the decision process than children in a sociooriented family.
Child’s Individual Characteristics Resource theory (Blood and Wolfe, 1960) asserts that the comparative resources of parents and children will determine who dominates in family decisions. Previous studies based on resource theory have examined spousal dominance and explained the husband’s dominance in family decisions on the basis of income and occupation, i.e., greater resources (Brinberg and Schwenk, 1985; Komarovsky, 1961; Schaninger and Allen, 1981). There is evidence that wives’ influence in family decisions has increased as more wives work outside the home and their financial resources increase relative to that of their husbands (Brinberg and Schwenk, 1985). Children’s personal resources should also affect their relative influence in family purchase decisions, with children who have greater resources having greater influence. Children’s resources may include their income contribution, employment status, grades, or perceptions of parental love and confidence. Churchill and Mosthis (1979) hypothesized that a first-born adolescent would interact more frequently with his or her parents regarding consumption matters. Their study found a positive but nonsignificant relationship between birth order and family communication. Examining financial resources, Moschis and Mitchell (1986) found empirical support for the idea that adolescents with outside incomes are more likely to purchase products independently. Children’s income, of course, is only one type of personal resource they might have; a more comprehensive measure of this construct might better support the following hypothesis: H2:
A child’s influence the child’s personal
in family decision resources.
making
will be positively
related
to
Product-related Factors Product importance and product knowledge are expected to affect children’s relative influence in family decisions. A person who is more involved with a product will be more active in the product decision process and have a greater effect on the decision outcome (Krishnamurthy, 1981). Consumer socialization studies have shown that parents’ influence on children varies depending on a child’s knowledge of the product and perceptions of product importance. Parents’ influence has been found to increase with high-risk products or products that the child knows little about (Moschis and Moore, 1979). Looking at family purchase influence from the child’s side, Roberts et al. (1981) reported that a greater number of children’s influence attempts was associated with
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a higher rate of product usage by the family. A reasonable explanation for this finding is that children more frequently attempt to influence decisions for products they consider to be important. We therefore state the following hypothesis: H3:
Research
A child will have greater influence in family decision purchase decisions: a. that he or she considers important. b. about which he or she has a high level of product
making
for product
knowledge.
Method
Sample The sample for the study consisted of 161 families with a father, mother, and their adolescent child in three northwestern towns. Adolescent children were chosen for the study because that age group was felt to be more appropriate for investigating children’s influence in family decisions from a socialization perspective. Infants and younger children clearly affect parental behavior and purchase decisions but are less suitable respondents for a variety of reasons: Younger children are not fully cognitively developed (Elkind, 1968; Mussen et al., 1969; Piaget, 1970) and have been demonstrated not to understand economic concepts (Strauss, 1952) and consumer skills related to information processing (Roedder, 1981; Wackman and Wartella, 1977). Middle-school and high-school officials in the area were contacted, and four schools agreed to participate in the survey. Questionnaires were delivered to the teachers to be administered in class. Each student was then requested to take two questionnaires home for his/her parents to complete independently. Students were asked to return questionnaires to school in one week. Of 525 students who filled out the “adolescent” version of the questionnaire, 161 brought back both parents’ surveys. The adolescent sample consisted of male and female middle-school and high-school students, with an average age of 15 and an age range of 11-18. They were from primarily middle-class families, with an average household income of between $30,000 and $40,000 annually. Most mothers were between 30 and 50 years old and had at least a high-school diploma (33%) or some college education (53%). Most fathers (60%) were between 40 and 49 years old; 25% were between 31 and 39 years old. Fathers were also relatively well educated, with 28% having completed high school and 70% having undergraduate or graduate degrees.
Dependent Measures Dependent variables in this study included two types of adolescent influence: product-choice influence and general influence in the family decision process. Most studies of children’s influence in the family focus on the degree to which children’s preferences match purchase outcomes in family decisions (i.e., the extent to which they dominate in family decisions). Decision influence is less often measured by constructs more closely related to socialization, such as purchase participation or extent of learning or knowledge acquisition (Roberts et al., 1981). The present study measured children’s influence in family decisions using both a product-choice
Adolescents’
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Influence in Family Purchases
measure and a more general measure of participation in the decision process. Adolescents and both parents were asked to rate children’s influence using both types of measure, yielding six separate measures of influence for each adolescent. The product-choice measure included 14 products, six for family use, six for the adolescent’s own use, and the remaining two for parental use. The product set included both high-involvement products (e.g., automobile, computer, dress clothes) and low-involvement products (e.g., toothpaste, groceries). Respondents were asked to rate relative influence using a l-5 scale, with 1 = a purchase decision made entirely by the adolescent, 2 = a decision in which the adolescent has more say than the parents, 3 = a decision in which parents and adolescent had equal influence, 4 = a decision in which the parents have more say, and 5 indicating a decision made entirely by the parents. It assumes an equal distance property of ordinal scales, recognizing that an ordinal interpretation may not be justified for all respondents. The Cronbach alpha reliability measure indicated high internal consistency, with alpha = 0.80 on adolescents’ responses, alpha = 0.84 on mothers’ responses, and alpha = 0.80 for fathers’ responses. For all except the last hypothesis (which examined knowledge and importance perceptions about particular products), a summary influence variable was created by taking the mean of the influence responses for the 14 products. The measure of general influence in family decision processes included six Likert scale items (1 = strongly agree, 5 = strongly disagree). These items were more communication and socialization oriented, e.g.: l
l
Adolescent
usually
Adolescent usually family use.
suggests
stores to shop.
goes shopping
with parents
when
looking
a product
for
The Cronbach 0.74, and 0.86 except the last mary variable items.
alpha reliability coefficients were satisfactory, with alphas of 0.70, for adolescent, mother, and father responses respectively. For all hypothesis (which focused on particular product decisions), a sumwas created by taking the mean of the responses to the individual
Independent
Measures
Family Communication Environment. Consumption-related family communications were measured using Moschis and Moore’s (1979) 12-item scale based on McLeod and Chaffee’s typology (1972), discussed above. Adolescents were asked to respond to the items using a scale in which 1 indicated very often and 5 indicated never. Responses were summed across the six items for each dimension. Following Moschis and Moore’s (1979) procedure, families were placed in one of the four family communication environment groups using median splits on the socio- and concept-dimension scores. Internal consistency and validity had been evaluated in previous studies (Moschis and Moore, 1979; Moschis et al., 1984). In the present study, alpha coefficients were 0.80 for the socio-dimension items and 0.62 for the concept-dimension items.
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Personal Resources. Several single-item measures were used to capture adolescents’ personal resources: birth order (i.e., firstborn child or not), only-child status, child’s employment, child’s income level, and self-reported school grades. We also developed a 4-item Likert scale to measure adolescents’ perceptions of parental support and confidence in the child’s abilities. It yielded a Cronbach alpha of 0.84 and includes the following items: l
I think my parents don’t have much faith in my abilities [reverse scaled].
. My parents are confident that I will do well in the future. l
l
My parents feel good about my accomplishments. I believe that my parents’ attitude about my ability is [l = very positive, 5 = very negative].
Children’s birth order and the presence or absence of siblings are represented as a single variable (Place) with three levels: first and only child, first child of several, or neither the first nor the only child. A similar strategy is employed with respect to child’s employment status and earnings. In this case, the variable (Earn) also has three levels: no income (not employed), low income (less than the median reported income for children), or high income (equal to or greater than the median reported income for children). School grades and perceptions of parental support are also categorized as either high or low based on median splits. Product-related Factors. The importance of products included in the study was measured using a 5-point scale ranging from “really important” to “really unimportant.” Adolescents’ knowledge of selected products (i.e., dress clothes, personal computers, and bicycles) was measured using Selnes and Gronhaug’s (1986) 4-item scale. This assesses subjective knowledge (by respondents’ ratings of the degree to which they know the relevant decision criteria), confidence (measured by asking how respondents thought their closest friend would evaluate their familiarity with the products), advice giving (by asking whether respondents had been asked for advice about the products), and self-evaluation (by asking about likelihood of success in purchasing the products). Alpha coefficients assessing the reliability of the product knowledge measure were 0.80 for bicycles, 0.81 for personal computers, and 0.78 for dress clothes.
Data Analyses
and Findings
Multivariate analysis of variance (MANOVA) was used to simultaneously examine the two influence variables and influence ratings from the three family members in testing the hypotheses. Analysis of variance (ANOVA) and Scheffe’s tests of means were used to uncover the location and nature of group differences identified by MANOVA. Means and standard deviations for all significant main effects and interactions are presented in Table 5. Family
Communication
Environment
According to the first hypothesis, children from concept-oriented families were expected to have greater influence in purchase decision making than children from
Adolescents’
Influence
.I BUSN RES 19X9:18:159-172
in Family Purchases
Table I. Effect
of Communication
Environment
on Children’s
Influence
in Family
Decision Making
df MANOVA Communication environment Respondent Communication environment x respondent ANOVAS 1. Product intluence Communication environment Respondent Communication environment x respondent 2. General influence Communication environment Respondent Communication environment x respondent
F
Probability
2,245 4,490 4,490
24.19 15.05” 0.54
0.01 0.01 0.71
5,246 1 2 2 5,246 1 2 2
20.25 39.56 30.37 0.49 5.06 23.55 0.12 0.49
0.01 0.01 0.01 0.62 0.01 0.01 0.89 0.62
“F value represents Wilks’ lambda for multivariate tests; it is the exact F calculated by the SAS program based on Rao (1973). providing an appropriate degree of freedom for p = 2.
socio-oriented families. Families that were high or low on both socio and concept communication dimensions were excluded, resulting in a comparison of 49 sociooriented families with 35 concept-oriented families. The analysis (summarized in Table 1) strongly supports the hypothesis (F = 24.79, p < 0.01). Communication environment has a significant effect on both product choice and genera1 influence (F = 39.56 and 23.55 respectively, both p < 0.01). Mean influence ratings were 3.77 (product choice influence) and 2.97 (general influence) for adolescents from concept-oriented families. For those from socio-oriented families, mean ratings were 3.46 and 2.58, respectively. Which family member reported children’s influence was also a significant main effect in the analysis (F = 15.05, p < 0.01). There was no significant interaction between communication environment and respondent. Influence ratings were found to vary by respondent only for the product choice influence measure (F = 30.37, p < 0.01). Respondent was not a significant source of variation for the genera1 influence measure (F = 0.12, p < 0.89). It is possible that differences by respondent are not detected by the genera1 influence measure because it evaluates influence in a process that occurs over time, and individuals may “average out” their feelings over many occasions in responding to each item. The product choice influence measure directs respondents to recall specific purchase occasions and thus appears to be more likely to uncover differences in influence perceptions. For the product choice influence measure, the mean influence ratings from mother and adolescents of adolescents’ decision influence were not significantly different (mean = 3.51 and 3.50, respectively). Fathers, however, perceived adolescents to have significantly less influence in product choice than did mothers and adolescents (mean = 3.91). This may possibly reflect traditional family role perceptions (i.e., fathers’ perceptions of themselves as family leader and having the greatest say in family decision situations).
Personal Resources Children’s influence in family purchase decisions was expected to be positively related to their personal resources. Our analysis, summarized in Table 2, generally
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Table 2. Effect of Personal Resource Factors on Children’s
Influence in Family
Decision
Making
MANOVAh Child’s income Respondent Place x child’s income Child’s income x school grades Child’s income x parent’s opinion of child ANOVAS 1. Product influence Child’s income School grades Respondent 2. Participatory influence School grades Parent’s opinion of child Child’s income x parent’s opinion of child
df
F
4,764 4.764 8,764 4.764 4.764
2.13 20.12 1.88 1.95 2.68
0.08 0.01 0.06 0.10 0.03
33,383 2
5.21 3.89 8.71 65.07 1.79 3.46 15.63 4.51
0.01 0.02 0.01 0.01 0.01 0.06 0.01 0.01
1 2 33,383 1 1 2
Probability
“Equivalent to Wilks’ lambda on multivariate tests. bOnly significant effects and interactions presented.
supports the second hypothesis. Only the child’s earning/employment status and respondent were significant as main effects (F = 2.13 and 20.12, respectively, p < 0.08 and O.Ol), but the other three personal resource variables were significant or marginally significant in interaction with the child’s income status. ANOVAs of the two influence variables, with all personal resource variables in one design, were significant overall (F = 5.27 and 1.79, respectively, both p < O.Ol), but which personal influence factors were significant depended on the influence variable being examined. Children’s grades were the only personal resource factor that was significant in both analyses, with children with high grades having more relative influence in choice of products than did children with low grades. Adolescents’ earning/employment status was significant for product choice influence only; as hypothesized, adolescents in the employed/high earnings condition had greater relative influence in product choice decisions than children who were not employed and had no earnings. Parents’ opinion of the child was significant for general influence only, with adolescents whose parents had a high opinion of their abilities having more influence in family purchase processes. Though children’s earning status was not significant by itself, there was a significant interaction between children’s earning status and parents’ opinion of the child (F = 4.51, p < 0.01). Plots of the means of these two variables indicated a generally ordinal interaction, i.e., high earning status and high parental opinion were both associated with greater influence by children in family decision processes. The effect of having different raters for the two influence variables was essentially the same for hypothesis 2 as it was for hypothesis 1: that responses came from different family members was not a significant source of variation for the general influence variable, but did significantly affect product choice influence ratings (F = 65.07, p < 0.01). Mothers’ and adolescents’ responses were found to be alike and differed from fathers’ responses. Fathers reported significantly less product choice influence by children relative to parents than did mothers and children.
Adolescents’
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Table 3. Effect of Children’s Knowledge and Importance Influence in Purchase Decisions” Source’
Importance Product Importance x respondent Knowledge X respondent Product x respondent Explained Residual Total
df 1 4
Sum of Squares
Perceptions on Their Relative F
Significance
25.13
32.28
544.37
174.84
0.01 0.01
15.85
10.18
0.01
5.52 1059.87 1639.37 1833.14 3472.51
3.35 170.20 35.70
0.03 0.01 0.01
2
2 8 59 2355 2414
167
“Includes influence ratings by mothers, fathers, and children. *Nonsignificant main effects and interactions not reported.
Product-related Factors Regarding the third hypothesis, children were expected to have more influence in family purchase decisions for products they considered important and about which they were knowledgeable. Since the hypothesis focused specifically upon purchase decisions rather than the purchase process in general, only the product choice variable was examined, and ANOVA was used in testing this hypothesis. Our expectations were supported or contradicted depending on whose assessment of children’s influence was included in the analysis. The initial analysis of variance including the following factors: child’s importance ratings; child’s knowledge ratings; the five products for which there were knowledge ratings; and decision influence ratings for children from mothers, fathers, and children (see Table 3). This analysis was significant overall (F = 35.70, p < O.Ol), but the results were contrary to expectations. Children’s importance rating was a significant factor in determining child’s decision influence (F = 32.28, p < O.Ol), but children had less influence in decisions for products they rated important than for those they considered unimportant (mean = 3.28 for low importance products, 3.49 for high importance products). The significant interaction (F = 10.18, p < 0.01) between importance rating and influence rater suggested a possible explanation for the contrary findings. In this interaction, adolescents reported approximately the same influence on products of low and high importance; parents, however, rated children’s influence as much greater for products that children considered unimportant. This implied that parents’ assessment of children’s influence for the products included in the analysis differed considerably from children’s assessment of their own influence, and that the two parental influence ratings might be masking relationships among children’s importance, knowledge, and influence ratings. In order to check this possibility, a second analysis of variance was performed in which parental ratings of child influence were excluded. This analysis (presented in Table 4) was also significant overall (F = 40.50, p < 0.01) and generally supported our expectations. Children’s knowledge was a marginally significant factor in determining children’s influence and, while the difference between high and low knowledge condition means was not statistically significant, it was in the expected direction. That is, children reported more influence in decisions for products about which they had a high level of knowledge. Children’s influence also varied by
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E. R. Foxman et al.
Table 4. Effect of Children’s Knowledge and Importance Influence in Purchase Decisions” Source” Knowledge Product Importance Explained Residual
x product
Total
df
Sum of Squares
1 4 4 19 785
2.94 686.09 8.37 698.56 712.64
804
1411.20
Perceptions on Their Relative F 3.23 188.94 2.30 40.50
Significance 0.07 0.01 0.05 0.01
“Includes only children’s influence ratings. bNonsignificant main effects and interactions not reported.
product in a logical way: Adolescents tended to report more influence for products that were for their personal use (mean = 2.16 for dress clothes for themselves) and the least influence in decisions regarding the purchase of parents’ clothes (mean = 4.70). Importance ratings for the products were not significant as a main effect (F = 0.03, p < 0.87), but did have a marginally significant interaction with product type (F = 2.30, p < 0.06). Examination of influence means suggested that adolescents tended to report greater decision influence for those products that they considered important and that were primarily for their use (see Table 5). Summary
and
Suggestions
for Future
Research
In this study, we found that adolescents’ influence depended on who was assessing it: Adolescents and their mothers consistently reported greater influence than did fathers. Adolescents also were found to have more influence in a concept-oriented family communication environment. Some personal resource factors, especially grades, were related to increased influence by children in family purchase activities. Finally, children’s knowledge and importance perceptions for specific products also affected their influence in family purchase decisions. The present study suggests several interesting directions for future research. Concerning influence specifically, we view product choice and purchase in families as the end result of a series of tasks and family member interactions; influence relationships exist in and affect the results of all these tasks and interactions. Because of this relationship, measuring adolescents’ or other family members’ influence and participation in decision processes potentially can have considerable value in explaining why particular family members dominate or do not dominate in particular purchase decision situations. Looking at perceptions of children’s influence from the viewpoints of both parents and the child also promises to provide a deeper, more dimensional understanding of the role of children in family purchase influence relationships. Our analyses consistently revealed real differences in family members’ perceptions of adolescents’ decision influence. Future studies should investigate patterns of agreement or disagreement in complete families (not just triads) in order to understand these differences more fully. As the number of information sources in such studies increases, however, so does the need to develop special analytic approaches in order to understand the multiple influence relationships inherent in such data.
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Table 5. Influence
Means (Standard
Deviations)
for Significant Main Effects and
Interactions Hypothesis 1 Communication Product General
environment
choice influence” influenceb
Respondent Product
choice
influence
Socio
Concept
3.77 (0.46) 2.97 (0.67)
3.46 (0.40) 2.58 (0.54)
Mother
Father
3.51 (0.37)
3.91 (0.45)
Hypothesis 2 School grades Product choice influence General influence Child’s income Product choice influence Parent’s opinion of child
Produce Earnings (general
x
Product:
Low 3.63 (0.50) 2.72 (0.59)
Importance Respondent
x
3.58 (0.39)
all respondents’ influence ClothesClothesParents Child
High importance Low importance
4.04
(0.48)
3.01 (0.66) Child 3.47 (0.46)
3.77
High
Low
No
2.65 (0.64) 2.99 (0.73)
2.70 (0.57) 2.80 (0.56)
2.75 (0.59) 3.13 (0.67)
assessments PCFamily
(1.39)
(product
choice
PCChild
BicycleChild
High
2.51 (0.95) Low
3.49 (1.22)
3.29 (1.16)
3.56 (0.96)
3.82 (0.89)
influence
respondent
Father
3.74 (0.52) Low
Earnings
3.37 (1.24) choice
3.77 (0.52) 2.88 (0.68) No
High
Importance Product
3.62 (0.49) 2.77 (0.59)
Mother
choice influence parental opinion influence)
3-including
Low
Hieh
High opinion Low opinion Hypothesis
High
3.64 (0.49)
General influence Respondent
Child 3.50 (0.44)
influence) Mother
Father
Child
3.50 (1.15) 3.26 (1.11)
3.58 (1.11) 3.20 (1.11)
3.40 (1.38) 3.41 (1.25)
Researchers could benefit more from a broader, more representative sample that would permit more confident generalization of findings; the sample in the present study was skewed towards middle- and upper-middle-income families and more
educated parents, and this may have affected the analysis results. Further examination of the effect of parental product importance and knowledge ratings on their perceptions of child decision influence would also help clarify the relationship among the views of mother, father, and child. A final important area for future research involves the development of better measures of both decision influence and consumer socialization. Most previous family decision-making studies have focused on measuring specific decision outcomes, an approach that has so far has been relatively lacking in explanatory value. It may prove that some broader measure of influence, such as the general influence measure used here, will permit a broader understanding of family influence processes. Future research also needs to focus on the relationship between decision-
170
J BUSN RES
E. R. Foxman
1989:18:159-172
et al.
Table 5. (continued) Knowledge x Respondent Respondent
(Product choice influence) Mother 3.42 (1.14) 3.36 (1.14)
High knowledge Low knowledge Product x Respondent Respondent
Child 3.35 (1.34) 3.48 (1.29)
(product choice influence) Mother 2.65 4.60 3.77 3.52 2.45
Clothes-parents Clothes--child PC-family PC--child Bicycle--child Hypothesis 3-including Knowledge
Father 3.46 (1.09) 3.36 (1.17) Father
(0.82) (0.64) (0.87) (0.91) (0.88)
2.77 4.55 3.77 3.49 2.52
(1.00) (0.64) (0.85) (0.90) (0.87)
Child 4.70 2.16 3.91 3.67 2.57
(0.58) (1.02) (0.94) (1.05) (1.08)
children’s infiuence assessments only High
Product choice influence ClothesParents Product: 4.70 (0.58)
ClothesChild 2.16 (1.02)
Low
3.55 (1.34) PCFamily 3.91 (0.94)
Importance x product (product choice infuence) Importance
3.48 (1.29) BicycleChild
3.67 (1.05)
2.57 (1.08)
High 4.67 3.88 3.52 2.30 2.15
Clothes-parents Clothes-child PC-family PC+hild Bicycle-child
PCChild
Low
(0.60) (0.96) (1.13) (0.99) (1.00)
4.81 3.97 3.75 2.69 2.18
(0.47) (0.93) (1.00) (1.11) (1.07)
“1 = decision made all by child. 2 = more say by child, 3 = equal say, 4 = more say by parents, 5 = decision made all by parents. ‘1 = strongly agree (that child has influence). 2 = agree. 3 = neither agree nor disagree. 4 = disagree. 5 = strongly disagree.
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