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"1 ul , {\l v .U‘ I )I....\F (.1 III?! :v . ll: 76!»... \,..I:...V\ .L. ;.. large»; _, ‘ ‘ .A hgmgefi ., mass ZOCO This is to certify that the dissertation entitled Family Decision-Making's Influence on Recreation Choices of Female Children presented by Joan E . Williams has been accepted towards fulfillment of the requirements for Ph - D - degree in .EaLlLFRecxeation and Tourism Resources Md 1&9, [ Major professor MS U is an Affirmative Action/Equal Opportunity Institution 0- 12771 LIBRARY Michigan State University PLACE IN RETURN Box to remove this checkout from your record. TO AVOID FINES return on or before date due. MAY BE RECALLED with earlier due date if requested. DATE DUE DATE DUE DATE DUE sag, 1 1‘: m2 MAR armor is 8/01 chlRC/DatoDuepGS—pJS _—._ FAMILY DECISION-MAKING’S INFLUENCE ON RECREATION CHOICES OF FEMALE CHILDREN BY Joan E. Williams A DISSERTATION Submitted to Michigan State University In partial fulfillment of the requirements For the degree of DOCTOR OF PHILOSOPHY Department of Park, Recreation, and Tourism Resources 2000 ABSTRACT FAMILY DECISION-MAKING'S INFLUENCE ON RECREATION CHOICES OF FEMALE CHILDREN By Joan E. Williams The purposes of this study were: 1) to determine how much influence a female child has on decisions related to her organized recreation participation and 2) to assess how much influence other household members, extended family members outside of the household and others have on recreation decisions related to that child. Subjects for this study were members of the Michigan Capital Girl Scout Council. A questionnaire was developed and mailed to a random sample of 600 parent(s)/guardian(s) of registered scouts. The parent/guardian most involved in the decision process about recreation activities in which a female child participated was asked to fill out the survey. Overall, the response rate was 53.58%. Questions in the survey focused on the three stages of the decision process: problem recognition, information gathering, and final decision. Information was obtained about who was involved in decision process and to what degree. Moreover, information was gathered about how important selected criteria were in the decision process involving children’s participation in organized recreation activities. Three categories of organized recreation activities were assessed. They were organized team sports, individual sport or other activity, and summer camp. Mothers were found to be the most influential information gatherers for children across all three categories of activities. Mothers and children were joint decision-makers in the final decision across all three categories of activities. Multiple regression was used to determine the relative influence of selected variables on the amount of influence children have on the information gathering and final decision stages. Independent variables included in the regression model were age, birth order, who initiated the idea, how much information was gathered by children, motivation, children’s income and social class. Who initiated the idea and age were significant in explaining part of the variance of children’s influence in five of six regression equations. Copyright by JOAN ELAINE WILLIAMS 2000 To my nephews Matthew Ryan McMahon and Christopher David McMahon Your strength and courage will always amaze me. ACKNOWLEDGMENTS I am indebted to many people who encouraged and supported me in my pursuit of a doctoral degree. First, I would like to thank my family and friends for the love and support they showed me along the way, especially during the “stretch run”. I never would have made it without their help. I am very grateful to Dr. Joseph Fridgen, my advisor, for his guidance and encouragement along the way. Thanks for believing in me. I am very appreciative of the time my other committee members, Dr. Donald Holecek, Dr. Rex LaMore, and Dr. Gail Vander Stoep put into this study. Their different perspectives were invaluable. Finally, I would like to thank Dianne, Chris, and Dr. Mayle for continuing to remind me that there would be light at the end of the tunnel after the dissertation was done. vi TABLE OF CONTENTS LIST OF TABLES .................................... LIST OF FIGURES ................................... CHAPTER I INTRODUCTION ..................................... Purpose................................. ..... Theoretical Framework ........................ Objectives of the Study ...................... Hypotheses to be Tested ...................... Discussion of Key Variables .................. Limitations .................................. CHAPTER II LITERATURE REVIEW ................................. Family Decision-Making ...................... Dyadic Decision-Making ................. Triadic Decision-Making ................ Consumer Socialization ....................... Social Development ..................... Social Perspective Taking .......... Impression Formation .............. Stages of Consumer Socialization ............ CHAPTER III METHODS .......................................... Sample ....................................... Response Rate ............................... Instrumentation ............................. Cover Letter ............................ Questionnaire Items .................... CHAPTER IV RESULTS .......................................... Hypothesis One .............................. Hypothesis Two ............................... Hypothesis Three ............................. Hypothesis Four ............................. Hypothesis Five .............................. Regression Analysis ......................... Organized Sports ....................... Information Gathered by Children Final Decision ..................... Individual Sports or Other Activities .. Information Gathered by Children. Final Decision ..................... Summer Camp ............................ vii Page ix xiii c3\J\JUI¢.AIA 13 14 16 22 23 23 24 25 29 29 33 33 35 36 38 41 47 52 58 65 69 72 72 77 81 81 85 89 Information Gathered by Children... Final Decision ..................... Importance of Selected Criteria .............. CHAPTER V CONCLUSIONS AND IMPLICATIONS ...................... Limitations .................................. Conclusions ................................. Family Members Influence ............... Age of Child ............................ Single-Parent/Guardian Households Versus Dual-Parent Households .......... Influence of Children at Different Stages in the Decision Process .......... Children's Income ...................... Consumer Socialization ................. Importance of Selected Criteria ........ Implications ................................ Further Research ............................ REFERENCES ....................................... APPENDIX Appendix A ................................... Cover Letter and questionnaire .......... viii 89 93 104 110 110 111 111 112 113 113 114 115 115 116 117 121 133 134 Table 2.1 A Model of Consumer Socialization ........... 3.1 Age Groups Used in Previous Research ......... 3.2 Types of Data Gathered with the Questionnaire ............................... 4.1 Descriptive Statistics of Respondents and Households ................................... 4.2 Influence of Mothers versus Others on the Information Gathering Stage for Organized Sports ...................................... 4.3 Influence of Mothers versus Others on the Final Decision Stage for Organized Sports 4.4 Influence of Mothers versus Others on the Information Gathering Stage for Individual Sports or Other Activity .................... 4.5 Influence of Mothers versus Others on the Final Decision Stage for Individual Sports or Other Activity ........................... 4.6 Influence of Mothers versus Others on the ‘ ' Information Gathering Stage for Summer Camp.. 4.7 Influence of Mothers versus Others on the Final Decision Stage for Summer Camp ......... 4.8 Children’s Influence on the Information Gathering Stage of the Decision Process for Organized Sports ............................ 4.9 Children's Influence on the Final Decision LIST OF TABLES Stage of the Decision Process for Organized Sports ....................................... ix Page 27 3O 37 39 42 43 44 45 46 47 49 49 .10 .11 .12 .13 .14 .15 .16 ..17 .18 .19 .20 Children’s Influence on the Information Gathering Stage of the Decision Process for Individual Sports or Other Activity ......... Children’s Influence on the Final Decision Stage of the Decision Process for Individual Sports or Other Activity ..................... Influence of Children, Based on Parental Relationship, on the Information Gathering Stage for Organized Sports ................... Influence of Children, Based on Parental Relationship, on the Final Decision Stage for Organized Sports ......................... Influence of Children, Based on Parental Relationship, on the Information Gathering Stage for Individual Sports or Other Activity ..................................... Influence of Children, Based on Parental Relationship, on the Final Decision Stage for Individual Sports or Other Activity ...... Influence of Children, Based on Parental Relationship, on the Information Gathering Stage for Summer Camp ........................ Influence of Children, Based on Parental Relationship, on the Final Decision Stage for Summer Camp .............................. Differences in Influence of Children Between the Information Gathering and Final Decision Stages for Organized Sports .................. Differences in Influence of Children Between the Information Gathering and Final Decision Stages for Individual Sports or Other Activity ..................................... Differences in Influence of Children Between the Information Gathering and Final Decision Stages for Summer Camp ....................... 50 51 53 54 55 56 57 58 60 62 64 \L .21 .22 .23 .24 .25 .26 .27 .28 .29 .30 Children’s Income and its Relationship to Children’s Influence on the Information Gathering and Final Decision Stages for Organized Sports ............................. Children’s Income and its Relationship to Children’s Influence on the Information Gathering and Final Decision Stages for Individual Sports or Other Activity .......... Children's Income and its Relationship to Children's Influence on the Information Gathering and Final Decision Stages for Summer Camp .................................. Zero—Order Correlation Matrix of Independent Variables with Information Gathered by Children for Organized Sports ................ Regression Analysis for Children’s Influence on the Information Gathering Stage of Organized Sports ............................. Zero-Order Correlation Matrix of Independent Variables with Final Decision made by Children for Organized Sports ................ Regression Analysis for Children’s Influence on the Final Decision Stage of Organized Sports ....................................... Zero-Order Correlation Matrix of Independent Variables with Information Gathered by Children for Individual Sports or Other Activity ..................................... Regression Analysis for Children’s Influence on Information Gathering Stage for Individual Sports or Other Activity ..................... Zero-Order Correlation Matrix of Independent Variables with Final Decision made by Children for Individual Sports or Other Activity ..................................... xi 66 67 68 73 76 78 80 82 84 86 If‘ .31 .32 .33 .34 .35 .36 .37 .38 .39 .40 .41 Regression Analysis for Children’s Influence on the Final Decision Stage for Individual Sports or Other Activity ..................... Zero-Order Correlation Matrix of Independent Variables with Information Gathered by Children for Summer Camp ..................... Regression Analysis for Children’s Influence on Information Gathering for Summer Camp ..... Zero-Order Correlation Matrix of Independent Variables with Final Decision made by Children for Summer Camp ..................... Regression Analysis for Children’s Influence on the Final Decision Stage for Summer Camp ......................................... Summary of Zero-Order Correlation Matrixes for all Regression Models .................... Summary of Beta Weights for all Regression Models ...................................... How Important Selected Criteria are in Making Decisions Regarding Organized Recreation Participation of a Child .................... How Important Selected Criteria are in Preventing or Discouraging Participation of a Child in Organized Recreation Activities... How Important Selected Criteria are in Encouraging Participation of a Child in Organized Recreation Activities .............. Length of Entire Decision Process for Each Activity ..................................... xii 88 90 92 94 96 98 101 105 107 108 109 Chapter I INTRODUCTION Participation by children in organized recreation H activities, especially organized sports, has risen dramatically over the last few decades (Kleiber & Roberts, 1983). This may be due, in part, to the surge of new opportunities afforded to children during their leisure time. Competition for children as consumers continues to grow in the marketplace. McNeal (1998) reported that children ranging from 4 to 12 years of age spend over $24 billion in direct spending and influence another $188 billion in family household purchases. Thus, the spending power of children is significant. Furthermore, according to Rossiter (1979), over 20 percent of the nation’s consumers are children. Berey and Pollay (1968) stated that “There are at least three main reasons why studying the role of a child in the market is warranted: (1) the child market is rapidly growing; (2) obviously children influence the family’s decision making; and, (3) adult consumer behavior is the direct antecedent of child consumer behavior” (p. 70). 1 2 Little research has been completed on children's participation in recreation activities. In addition, there are few studies that focus on family members’ influence, constraints, and family decision—making related to recreation activity participation by children (Howard & Madrigal, 1990). Thus, there is a need to gather information to develop a better understanding of decision-making processes families use to determine in which recreation activities their children participate. This study provides insight into the effects of family structure on perceived influence by a parent/guardian in the decision process. Age of a child has not been widely used in recreation studies that have focused on decision-making regarding children’s participation in recreation activities. Additional social structural variables used in this study include: 0 the financial resources of the child, which is used to determine a child’s consumption autonomy; 0 family structure (relationship status of parents and birth order of the child); 0 socioeconomic status (total household income and highest level of education achieved by parent/guardian). 3 Information gathered from parents/guardians related to family decision-making provides valuable data about whom, when and how decisions are made related to recreation participation for a female child in the household. Additionally, data were collected on how families gather recreation opportunity information for their children. The sources of information families use to make recreation choices for daughters were determined, and the most useful sources of information used in the final decision were found. Few studies have been undertaken in the area of recreation and family decision—making. This study provides an application and extension of results presented in the consumer behavior literature with regard to children's involvement in family decision-making. It is important to study family structure in—depth because of the changing nature of households. The time of dual-parent households where only the father works outside of the home are in the distant past. According to Dornbusch, Carlsmith, Bushwell, Ritter, Leiderman, Hastorf and Gross (1985), "Half of all children under 18 will experience a parental divorce or separation, spending some time in a single-parent household" (p. 326). Moreover, in 1997, 19.8 million children under the age of 18 lived in single-parent households, accounting for 27.9% of all 4 children under 18 at that time (U.S. Bureau of the Census, 1998). Purpose The purpose of this study is first, to determine how much influence a female child has on decisions related to her own organized recreation participation and secondarily, how much influence other household members, extended family members and others have on recreation decisions related to that child. Theoretical Framework The theoretical framework used in this study is grounded in consumer behavior literature. Specifically, it draws upon consumer socialization theories. Consumer socialization is defined as "the process by which young people develop consumer-related skills, knowledge, and attitudes" (Moschis & Churchill, 1978, p. 599). Consumer socialization research is most often based upon two models of human learning, the social learning model and the cognitive development model. Moschis, Moore and Smith (1983) state that: "Studies using the social learning approach attempt to explain socialization as a function of the environmental influences impinging on the person. Learning is assumed to be taking place “1 5 during the individual's interaction with socialization agents in various social or structural settings" (p. 314)m"The recent conceptual model of consumer socialization includes five types of variables derived from general socialization theory: socialization agents, learning processes, social structural variables, age or life cycle and content of learning”. (p. 314) The model developed by Moschis and Churchill (1978) is reproduced as Figure 1.1. Objectives of the Study 1. To determine to what degree parents/guardians, children, and other family members exert influence on the family decision-making process related to organized recreation activity choices. To determine if the perceived level of a daughter's influence on organized recreation activity purchases vary according to family structural characteristics. To determine if age of daughter has an effect on a parent's/guardian's perception of her influence on a family's decision to allow her to participate in organized recreation activities. To determine the criteria families use in making organized recreation purchase decisions. .oom .mH .cuummmmm unnumxumz wo amcusow .mflmxamcm HMUHuHQEm ocm HMUHumuoonu a .cofiumNflHmfloom umESmcoo .Amhmav .<.w ..uh Haanousno a .m.w ~manomoz "mousom .coflumNHHMHoom mossmcoo mo Hmoos c .H.H musoflm cofiuflmOQ wao>o mafia no 60¢ coauomHOHCH Hmfluom I mmauumaoum usmEmouomcflmm u A amacummq A, ocHamUOZ I umdflnm:0Humamu A umcumoauucmo¢ moanmflum> Hmnsuosuum Hmfloom W®EOUQSO mmmmmOOHm COflHMNHNMflDOW WHCQUQUOHCQ Hypotheses to be tested 1. Mothers in dual-parent households will be perceived to have the most influence on decisions related to organized recreation activities in which their children participate. As the age of the child increases, the degree of perceived influence by a parent/guardian of the child on each stage of the decision process will increase. Degrees of child influence are perceived differently by single-parent/guardian families versus dual-parent families, with single-parents/guardians assigning more influence to children than parents in dual-parent families. A child’s influence will vary between the information gathering and final decision stages of the decision- making process. The degree of a child's influence on the family decision—making process is positively related to a child's financial resources. Discussion of Key Variables The variables discussed below were deemed critical to the study: 1. Social structural variables—A review of the literature has shown that these variables can play a significant role in the perceived influence children and adolescents have on family decision-making. Family structure has not been studied in-depth in recreation decision-making studies. This study provides an opportunity to investigate the role parent’s education, total household income, marital status, and birth order of the children play in family decision-making. Age of the child—Age of child has been found to be a significant factor in the cognitive development and consumer socialization of children. Influence of persons living outside the household—It has not been established what role extended family members and others outside the child’s immediate household have on family decisions regarding recreation choices for children. For this study, it was deemed important to look at all relevant family members whether they live in the household or not. Socialization agents-Socialization agents are described as any person or organization that is involved in the development of social interaction skills. They have influence on a person because of their frequency of contact, and control over rewards and punishments of the individual (Moschis & Churchill, 1983). The socialization agents whose influence will be determined 9 in this study are the following: (1) parent(s) and/or guardian; (2) other family members; (3) peers; (4) sponsoring agencies; and, (5) schools. 5. Types of organized recreation activities studied—It is hypothesized that the decision process will vary for different types of recreation activities (organized sports, individual sport/other activity and summer camp). This study is unique because of its use of several social structural variables. Most published studies on family decision—making have either ignored family structure variables altogether or analyzed the effects of only a few variables, specifically family size or birth order. According to Swanson (1978), these variables are studied most often because of the “assumption that the first born child, especially in large families, is more likely than others to have a differentiated status as agents”(p. 896). Additionally, this study provides a more detailed look at the effects of other household members and extended family members on family decisions. Parents/guardians were asked to quantify not only how influential they and their children were in each stage of the decision process, but were also asked about other children and adults in the household, and 10 aunts/uncles and grandparents not living in the household. The three stages of family decision-making used in this study are problem recognition, information gathering, and final decision. Previous studies have examined adult children’s (Sorce, Loomis, & Tyler, 1989) and adolescents’ (Baranowski, 1978; Peters, 1985) influence on their parents’ decision-making. Limitations While it is accepted as a limitation of this study, this research includes the perceptions of one parent's/guardian's beliefs on the level of influence different members of the household and extended family have on recreation purchase decisions. According to Stipp (1988), “Children are difficult to study. They are undependable reporters of their behavior, have poor recall and don’t understand abstract questions”(p. 27). Mann, Harmoni, and Power (1989) state that “Young adolescents are unable to create options, identify a wide range of risks and benefits, foresee the consequences of alternatives and gauge the credibility of information from sources with vested interests” (p. 265). Additionally, Ward (1979) found that the younger the children, the greater the concern of the reliability and validity of the data, especially data based 11 on verbal responses. Nevertheless, Bokemeier and Monroe (1983) believe that assessing family decision-making using a single family member’s perceptions may produce unreliable results with questionable validity. Chapter II LITERATURE REVIEW In 1989, the Roper Organization completed a survey for USA Weekend on consumer decision-making in American families. It found that leisure time is an area in which the majority of children have some influence on family decision-making. According to this study, about 75% of children between the ages of 7 and 17 help to decide what the family does for recreation. Decision-making occurs when an individual makes a selection among a group of alternatives in an effort to improve his/her quality of life (Paolocci, Hall, & Axinn, 1977; Rice & Tucker, 1986). According to Ajzen and Fishbein (1980), in general, people are quite rational in their decision-making, they make systematic use of the information available to them, and they consider the implications of actions before they make a final decision. Decision-making can be analyzed through a variety of methods. In this study, decision—making is examined through analysis of the process used to reach a decision where family members are both part of the decision making process, and impacted by the decision made. 12 13 Family Decision-Making According to Engel, Blackwell, and Miniard (1990), family consumption decisions involve at least five definable roles. The husband, wife, children, or other members of a household may assume these roles. Both multiple roles and multiple actors are normal. 1” Gatekeeper. Initiator of family thinking about buying products and the gathering of information to aid the decision. 2. Influencer. Individual whose opinions are sought concerning criteria the family should use in purchases and which products or brands most likely fit those evaluative criteria. Zl.Decider. The person with the financial authority and/or power to choose how the family’s money will be spent and the products or brands that will be chosen. 4. Buyer. The person who acts as purchasing agent: who visits the store, calls the supplier, writes the check, brings the product into the home, and so on. 5.User. The person or persons who use the product”. (p. 174) In addition, Kenkel (1961) acknowledged that in order to complete research on family decision-making, the following assumptions are made. “The individuals:(1) know the relative amount of influence they have, (2) are willing to admit it to themselves and others; and (3) are able to recall with accuracy how influence was distributed in some past decision—making session” (p. 174). Perceived relative 14 influence is a family member's perceptions of the degree to which an individual has engaged in activities that contribute to the decision-making process relative to the contributions of others in the household (Beatty & Talpade, 1994). Dyadic Decision-Making The majority of studies of family decision-making have focused on the husband—wife dyad. Hempel (1974) describes four family role structures for dyadic decision-making. First, husband—dominant decisions occur when the husband dominates the decision stage or process. Second, wife- dominant decisions occur when the wife dominates the decision stage or process. Third, syncratic or joint decisions occur when decisions are made jointly and the dominance is balanced. And, fourth, autonomic or separate decisions occur when decisions are made independently and dominance is balanced. Davis and Rigaux (1974), in their study of Belgian households for 25 economic decisions, found that the role of the husband or wife in the decision process depended on what the decision was related to. In addition, they found that who makes the final decision is a function of the husbands’ and wives’ perceived influence. They declared that the message to marketers is clear; marketers must understand who 15 is the dominant decision-maker for the product they are trying to sell. They held that the message marketers’ design must be directed at the person(s) involved in the decision—making process for purchasing the product. Fitiatrault and Ritchie (1980) found in their study on household decision-making that the influence in the household decisions was a function of the presence of children in the household and the income of the husband. Moreover, Ford, LaTour, and Henthorne (1995) found in their study of 24 product categories that who dominated the decision depends on the stage of the decision process. Nichols and Snepenger (1988), in their study of family vacationers to Alaska, found that in most families joint decision-making was most prevalent. They suggested that marketers’ promotional efforts should appeal to both spouses. Also, they found significant child involvement in the decision process when families were deciding where to go on vacation. Spiro (1983) completed a study on different influence strategies husbands and wives use to resolve disagreements concerning purchase decisions. She established that traditional family ideology, income, gender, age of the youngest child, education, wife’s employment and wife's income were significant determinants in household decisions 16 and how spouses resolve disagreements concerning purchase decisions. Furthermore, Corfman and Lehmann (1987) found that outcomes of preceding joint decisions made the strongest contribution to relative influence on current decisions. Triadic Decision-Making A smaller number of studies have dealt with the influence children and adolescents exert on family decisions. Most of these studies have dealt with adolescents' and children’s influence on the family purchase of durable goods (e.g., automobiles, washing machines, stereo equipment), choice of vacation destinations, and household goods (e.g., cereal, snack foods, toothpaste). Beatty and Talpade (1994) found that adolescents had greater influence for products purchased for their own use. Moreover, they found that as children’s income increased, their perceived influence on the decision process increased. Belch, Belch, and Ceresino (1985) determined the relative influence of fathers, mothers, and teenage children in the family decision-making process. They analyzed family members’ influence for six product categories. They were the purchase of a television, an automobile, a vacation, household appliances, household furniture, and breakfast cereal. They found that for five of the six product 17 categories, children’s greatest influence occurs in the initiation stage, and were lower in the information gathering and final decision stages. The product category that was dominated by children was the purchase of breakfast cereal. Similarly, Berey and Pollay (1968) and Atkin (1978) found the dominance of children in the purchase of breakfast cereal. Roberts, Wortzel, and Berkeley (1981) used secondary data to determine how mothers’ attitudes affect the amount of influence their children have on the family decision-making process. They found that mothers’ perceptions are inversely related to their attitudes toward financial matters, nutrition and whether they were liberal or conservative. Shim, Snyder, and Gehrt (1995), in their study of when children become “clothes conscious”, found that parental socialization variables were significantly related to children’s social-structural and development variables (a child’s age, birth order and parent’s marital status) regarding when children become involved in the purchasing of clothing. Additionally, they found that parents spent more time educating their first-born children regarding the value of money than later-borns. This finding supported Moschis’ (1987) statement that first-born children acquire better consumer skills than later-born children. 18 Ward and Wackman (1972), in their study on how much children attempt to influence purchase decisions, found that children’s purchase attempts differ depending on the type of product. However, as children get older, mothers increasingly yield to their children. Ward and Wackman stated that mothers’ yielding was probably a reflection of their perceived increased competence of older children in making judgments about purchase decisions. Many of the studies presented are criticized for not asking children directly the influence they believe they had on family decisions (Foxman, Tansuhaj, & Ekstrom, 1989). However, studies in which adolescents were asked about their influence on family decisions tended to rate it higher than their parents did (Beatty & Talpade, 1994; Foxman, et al., 1989). As an example, Darley and Lim (1986) completed a study on family leisure time activities. In their study, they measured the influence of children as described by parents on three family leisure activities (family-type movies, family outings, and participant sports). They found older children had more perceived influence on decisions related to family leisure activities than younger children. According to Howard and Madrigal (1990), mothers played a significant role in a child's introduction to formal or institutionalized recreation. Moreover, they state that 19 children made decisions independently only to a modest degree. They attributed mothers' dominance in decisions related to their children’s recreation activities to the fact that they are, for the most part, the primary caregiver. Even though mothers may have had the most influential role in decisions related to their children’s organized recreation participation, valuable data would have been lost if information regarding the influence of children, other family members, and non-family members in the decision-making process were not gathered. For example, Liprie (1993) found in her study on adolescent participation in family decision-making that "early adolescents are eager to influence family decisions and that they are able to perform specific roles such as information gatherer and participate in the discussion" (p. 251). Furthermore, previous research has shown a positive relationship between age of child and level of involvement in family decisions (Brown & Mann, 1988; Brown & Mann, 1989; Darley & Lim, 1986; Jenkins, 1979; Shim et al, 1995). Jenkins (1979) found that children were highly influential for products that the family used jointly, especially in decisions related to family vacations. In addition, for products in which the child is directly involved in consumption, the child is expected to 20 have at least some influence on the family decision-making process (Beatty & Talpade, 1994; Belch, Belch, & Ceresino, 1985; Foxman & Tansuhaj, 1988; Foxman, et al., 1989; Nelson, 1978). Nelson (1978) found that children were involved in the decision process as to where and when to eat out. Nevertheless, parents reserved the right to make the final decision and to decide how much was spent. Foxman and Tansuhaj (1988) found significant positive correlations between adolescents’ and parents’ perceived influence in choosing four of six products used by them (e.g., records, personal computers, bicycles, and magazine subscriptions). Thus, it is important that the effects of children in family decision-making are explicitly acknowledged. Lackman and Lanasa (1993) stated that “Because most families include children and because children have been shown to possess an integral and growing role within the family decision-making process, the exclusion of children from analysis of this process will likely produce findings of questionable validity” (p.90). Moreover, it is essential to consider the effects of different family structures on family decision-making. It was estimated that in the early 1990's 15% of all households had a single-parent structure (Hawkins, Best, & Coney, 1992). By 1997, this estimate grew to 29% (U.S. Bureau of 21 the Census, 1998). Dornbusch et a1. (1985) found that adolescents in single—parent families were more involved in decisions concerning themselves than adolescents in dual— parent families. Jacobs, Bennett, and Flanagan (1993) found that adolescents in single-parent families were given more purchase autonomy than were adolescents in dual-parent families. Foxman et a1. (1989) determined that in families in which both parents work, parents allowed or encouraged their child’s increased participation in family decision- making. Brown and Mann (1989) found that the highest level of participation by adolescents occurred in households where both parents worked. The influence various family members have on different types of consumer decisions is dependent on the product type and the relevant stage of the decision process (e.g., need recognition, search for information, and final decision) (Ford, et al., 1995; Swinyard & Sim, 1987; Sybillo & Sosanie, 1977; Ward & Wackman, 1972). Swinyard and Sim (1987) found that children’s influence varied across products, children's participation was more involved for products they use, and children were found to independently make decisions to a modest degree. 22 Consumer Socialization Research on children’s consumer behavior dates back to the 19505 with the publication of an article on brand loyalty (Guest, 1955). In the 19605, research on children’s consumer behavior expanded to include children’s understanding of marketing (McNeal, 1964) and their influence on parental decision-making (Berey and Pollay, 1968). In the 19705, research on children as consumers became widespread and gained legitimacy in marketing research (John, 1999; Moore-Shay & Wilkie, 1988). Ward (1974) argued vigorously for studying children and their socialization in the consumer role. Moreover, Moschis and Moore (1979) believed that it is important to use consumer socialization in order to study the effects of children on family decision-making because of the cognitive and behavioral patterns of decision—making. There is considerable evidence that parents are the most significant agents in young children’s consumer socialization (Hayes, Burts, Dukes, & Cloud, 1993). In fact, Grossbart, Carlson and Walsh (1991) suggested that children learn their purchasing and consumption behavior from their parents through consumer socialization. According to Ward, Wackman, and Wartella (1977), parents influence their children’s consumer socialization by 23 allowing their children to observe and initiate their behaviors, interacting with their children in consumption, and providing opportunities for consumption by their children. Consumer socialization takes place during the cognitive and social stages of children’s development. The most well known framework for characterizing basic cognitive abilities is Piaget’s theory of cognitive development. He proposed four main stages of cognitive development. They were:(1) sensorimotor (birth to two years): (2) preoperational (two to seven years); (3) concrete operational (seven to eleven years); and (4) formal operational (eleven through adulthood)(Ginsberg & Opper, 1988). Moschis and Moore (1979) cited many studies in which the social learning model was used to study the consumer socialization of children. The study of social development includes a wide variety of topics. However, to explain consumer socialization, the areas of social perspective taking and impression formation are the most relevant (John, 1999). Social Development Social Perspective Taking Selman (1980) addressed social perspective taking by describing how children’s abilities to understand different 24 perspectives progress through a series of stages. They are: OEgocentric Stage-(ages 3-6)—children are unaware of an perspective other than their own; OSocial information role taking stage-(ages 6-8)-children become aware that others may have different opinions or motives, but believe that this is due to having different information rather than a different perspective on the situation; OSelf-reflective role taking stage-(ages 8-10)- children not only understand that others may have different opinions or motives, even if they have the same information, but can consider another person’s point of View; OMutual role taking—(ages 10-12)- children develop the ability to consider another person’s viewpoint at the same time as one’s own. There is a great deal of persuasion and negotiating going on during this stage that requires dual consideration of both parties’ perspective; OSocial and conventional system role taking-(ages 12-15 and older)-features an additional development, the ability to understand another person’s perspective as it relates to the social group to which he (other person) belongs or the social system in which he (other person) operates. (John, 1999, p. 185) Impression Formation Impression formation undergoes a similar transformation to social perspective taking as children learn to make social comparisons on a more sophisticated level. Bareboim (1981) provided a description of the developmental sequence that takes place from 6 to 12 years of age. 25 OBehavioral Comparison Phase-(ages 6-8)-children do incorporate comparisons as a basis of their impressions, but the comparisons are based on concrete attributes or behaviors (e.g., “Hunter eats faster than Peyton”); 0P5ychological Constructs Phase-(ages 8-10)-impressions are based on psychological or abstract attributes but do not include comparisons to others (e.g., Katy is friendly”); 0Psychological Comparisons Phase—(11 or 12 years of age and older)-comparisons based on psychological or abstract attributes emerge which feature more adult like impressions of people (e.g., “Mike is more outgoing than Samantha”). (p. 141-142) Stages of Consumer Socialization Consumer socialization occurs through cognitive and social development as a series of stages as a child matures through childhood. John (1999) proposed that consumer socialization should be considered as a developmental process that proceeds through a series of stages as children mature into adulthood. She said that by “Integrating the stage theories of cognitive and social development, a clear picture emerges of the changes that take place as children become socialized into their roles as consumers” (p. 186). John (1999) developed a three—stage model of consumer socialization. The stages are the perceptual stage (3-7 years), the analytical stage (7-11 years), and the reflective stage (ll—16 years). The perceptual stage is characterized by a general orientation toward the immediate 26 and readily observable perceptual features in the marketplace. The analytical stage is characterized by children exhibiting more thoughtfulness in their choices, considering many attributes in making a choice and employing a decision strategy that seems to make sense given the environment. In the reflective stage, children are more reflective in their way of thinking and reasoning. They become more focused on the social meanings and underpinnings of the consumer marketplace (see Table 2.1). John described the limitations of her proposed model. They included: (1) the age ranges for each stage are approximations based on the general tendencies of children in that age group; (2) important developments in consumer socialization do not emerge in a vacuum, but take place in a social context including family, peers, mass media, and marketing institutions; and, (3) mass media and advertising provide information about consumption and the value of material goods. (pp. 187-188) The use of consumer socialization in determining the role individual family members have in the decision process has increased over the past twenty years. Early work by Ward and Wackman (1972) provides the backbone of this research. Consumer socialization was used to determine children’s roles in family decision-making as seen in the work by Grossbart, Carlson, and Walsh (1991), Moschis (1987) and Darley and Lim (1986). 7 2 ucmucoo Hmwoom ca Amuwsuo + czov Am>fluoodmuwa c3ov mw>fluomdmuma Hmso mm>fluoodmuoa Hmso vaupcmoomm o>fluoodmuom A=cm£u [Mflsv ucmocflucoo A:cmLuIMH:V acmGCHucoo maQEflm Hmcoflmcoeflpfluasz mcoflmcmeflp mHoE no 039 Hmcowmcmefinflca >uflmedEoo mmusumow ocfl>aumocs mwuspmow OCH>HHmccs mousummw \Hmcofluocsm \Hmcofluocsm Hmsudwouom msoom uomuum3¢ uomuumbfi mumuocou coflumucmfluo ”mmusuosnum mmomazocx lmumms GH-HHV Amumms HH->V Amumms bums mmmum o>fluooammm woman Hmofluzamc¢ ommum Hmsudooumm moflumflumuomumcu mommum coflummfiamfloom umEswcoo H.N manna 28 .mmH .om .noumommm Hoesmcou mo HmCHDOH .noumwmou mo mumm> m>flu u>ucmzu um xooH w>fluoodmouuou < "cmuoaflno no cofiumNflHmHUOm umEsmcoo .Ammmflv .m.o .cnon ”mousom axoucoo Hmfloom mm>fluomdmuma ammo mw>fluomdmumm Hmso ofluucmoomm m>fluommmumm UonHm>mU >aasm mumumpoz mcflmumEm >ufl>fludmp< mmflomumuum mo mmflooumuum mo mwflomumuum mo wuHODHmdmu meQEou muflouuoaou ompcmdxm ouflouumdwu omuHEHA mmusnfluuum madfluasz mmusnfluuum muoE no 039 mousnfluuum oaocflm >uflxwameoo mmusummm ucm>mamm mousymwm ucm>mamm mmusummu ucmflamm mmusummm mcfl>auoocs mmusummw mcfl>aumocs mmusummw \Hmcofluocsm \Hmcoflpocsm Hmsummoumm msoom oaomomuum Hsmunosonh ucmflbmaxm :oflumucmfluo "mmflmmumupm monogamcfl ocm mcflmeucoflmflooo lmumms masfific lmumms HH->v lmumms films woman m>fiuowammm mamum Hmoflu>amc¢ mmmum Hmsudmoumm moflumflumuomumno Aomzcflucoov H.N magma Chapter III METHODS Sample Subjects for this study were obtained from a list of registered members of the Michigan Capital Girl Scout Council (MCGSC) for the 1995-96 fiscal year. The purpose of using this sampling frame was threefold. First, it controlled for gender by using only female subjects. However, it did not eliminate gender bias because families may have different standards for males and females. Previous research has shown that it appears that female adolescents are more involved in consumptive decisions than their male counterparts (Moschis & Mitchell, 1986; Ward, 1974). Second, it was a convenient method to find a known population of organized recreation activity users. However, it is recognized that members of a specific organization are not necessarily representative of the general population. Third, it is difficult to obtain research access to children, and this was an accessible group. A questionnaire was developed and mailed first class to a stratified random sample of parent(s)/guardian(s) of registered scouts. In order to determine if a child's age had a significant impact on the degree of her influence, it 29 30 was essential to gather information from children of several different age groups. The population of the MSCGS included 4,984 scouts. Of that number, 573 scouts did not have their age listed. These scouts were eliminated from the list. Thus, the number of usable names was 4,411. To develop the parameters by which to group scouts by age, 14 previous studies on family decision-making involving children were analyzed. A child's specific age was not used in the sampling procedure for any of these studies. However, in four of the studies, Atkin (1978), Darley and Lim (1986), Nelson (1978) and Ward and Wackman (1972), ages were grouped for analysis (see Table 3.1). Table 3.1 Age Groups Used in Previous Research Author(s) Year Age Groups Atkin 1978 3-5, 6-8, 9-12 years Darley & Lim 1976 0—5, 6-12, 13-17 years Nelson 1978 under 5 years, over 6 years Ward & Wackman 1972 5—7, 8—10, 11-12 years 31 These groupings were not very helpful in making the decision for relevant age group categories for this study. Thus, the decision was made to group according to psychosocial development theory (Newman & Newman, 1995). Psychosocial development theory groups children into the following age ranges: 0 early school age (4 to 6) 0 :middle school age (6 to 12) 0 early adolescence (12 to 18) Due to the limited number of scouts in the 16-18 years old age range, they were eliminated from the sampling frame. The groupings in psychosocial development theory were modified in order to make the groups mutually exclusive. The three groups were: Group One (4-to-6 years old); Group Two (7-to—11 years old); and, Group Three (12-to-15 years old). A pretest was completed in May 1996. Parents of scouts from one Brownie troop and one Junior troop were asked to complete the survey and provide comments on its clarity and length. Adjustments were made to the questionnaire based on feedback from those parents. There were 200 surveys sent to randomly selected members in each stratum. The scouts used in the pretest were eliminated from the master list. Surveys were mailed on June 3, 1996. A follow-up postcard was sent on June 10, 32 1996. The postcard was sent to the entire sample. It thanked those who had already returned the survey and encouraged those who had not to do so at their earliest convenience. A second mailing was sent on June 24, 1996. In addition, students trained in telephone interviewing called those who had not yet responded to encourage them to send back the questionnaire. Interviewers read from a predetermined script so that all non—respondents heard the same thing. Two attempts were made to contact non- responding members of the sample. Incentives were used in attempt to increase response rate. Members of the sample were reminded that if they sent back a completed questionnaire within two weeks of the initial mailing (postmarked by June 19, 1996), their daughters' names would be placed in a drawing. The suggestion was made that parents might view a savings bond as a more "child driven" reason to respond than cash. Therefore, in lieu of $50 cash first prize, a $100 U.S. Savings Bond was awarded. Second prize was $25 off a week's stay at Camp Deer Trails, the MCGSC resident camp located near Houghton Lake, MI. Several smaller prizes, such as hats and tee shirts with the "Camp Deer Trails" emblem on them, were also awarded. 33 Response Rate A total of 600 surveys were mailed. Of that number, 14 were undeliverable. The first and second mailings resulted in 233 and 81 returned surveys, respectively, for a total of 314. Returned surveys were compared to the master list to ensure the age of the daughter was correct, based on her age as of March 31, 1996. In cases for which age was incorrect, it was changed to match the master list. Overall, the response rate was 53.58%. Group response rates were as follows: Group One, 46.42% (91/196); Group Two, 58.97% (115/195); and, Group Three, 55.10%, (108/196). There were no responses from families with a four—year-old scout. Instrumentation The questionnaire focused on items related to family, friends’ and others’ (e.g., coaches) involvement in different stages of the decision process for participation in three categories of organized recreation activities. Categories of activities chosen were organized team sports, individual sports or other activities, and summer camp. The decision-making process has been described in the literature in several ways. The most common approach, and the approach that was used in this research, was to subdivide purchase decisions into three distinct stages: 34 problem recognition; information search; and, final decision (Davis & Rigaux, 1974; Ford, et al., 1995; Hempel, 1974; Howard & Madrigal, 1990; Nelson, 1978; Szybillo & Sosanie, 1977). Respondents were asked who initiated the idea, and what percentage of the information gathered and final decision could be attributed to which household members, extended family members, and others. Influence of persons on the two latter stages was measured using the constant-sum method. The constant-sum method is defined as “a scaling method in which a subject divides a set of points between two standards so that the ratio between the assigned points corresponds to the subjective ratio” (Koschnick, 1996, p. 74). The constant-sum method has been used previously in family decision-making research (Corfman, 1991; Filiatrault & Ritchie, 1980; Howard & Madrigal, 1990; Jenkins, 1979; Qualls, 1987; Szybillo, Sosanie & Tenenbein, 1979; Woodside & Carr, 1988). According to Howard and Madrigal (1990), support for its application is based on three arguments. l. The constant sum format is better adapted to measuring the complete notion of joint decision—making for which monadic or categorical ratings (i.e., Likert—type scale of influence dominance) are too unwieldy. 2. _ The constant sum method avoids interpretive problems resulting from the use of adjectives in Likert and semantic differential scales. 35 3. The measurement has properties of interval data (p. 250). Additionally, respondents were asked how important selected criteria were in the decision process regarding recreation participation by a child. Respondents were asked to select the top three criteria their families use in these decisions and the top three criteria that prevent or encourage participation by their children in organized recreation activities. The list of criteria used was the same criteria used in a 1994 study of Girl Scout participation in summer camp for the MCGSC (Williams, La Lopa & Holecek, 1994). The criteria were developed from information gathered in several focus groups of parents of active scouts. The information obtained focused on why families did or did not send their daughters to Girl Scout camp. Cover letter A cover letter was sent as part of the questionnaire. It appeared on the first page of the questionnaire. Items included in the cover letter were as follows: 0 who was conducting the study (MCGSC and MSU); 0 who should complete the questionnaire and for which child; 0 importance of returning the survey; 36 0 how to return the survey; 0 that the results were confidential; 0 described how a participant’s child was eligible to win a $100 U.S. Saving Bond; and 0 that participation in the study was voluntary. Potential participants were told that by completing and returning the questionnaire they had given consent to be part of the study. Moreover, they were reminded that they did not have to answer all of the questions. However, they were encouraged to answer all of the questions. Questionnaire Items Items in the questionnaire covered the following areas: demographics, decision-making; motivation for participation; and, criteria for participation of a child in any organized recreation activity (see Table 3.2) 37 Table 3.2 Types of Data Gathered within the Questionnaire Demographics Household make-up Gender Race - Age range-household members Age of child Birth order Other children in household Level of education of parent Full-time wage earners Part-time wage Total household income Child’s income Decision-making Type of activities: Organized team sports Individual sport/other activity Summer camp Initiation of idea: Specific person Information gathered Final decision Length of decision time frame Sources of information used How influential were sources Most influential sources Motivation for participation Child Parent Parent and child Criteria forgparticipation by children in recreation activities Age of child Cost of activity Child’s interest in activity Child’s need for activity Flexibility times/dates of activity Educational value of activity Friend(s) participation in activity Health and safety of child Information from sponsoring agency Length of time of activity Location of activity Number of recreation activities in which child participates Development of leadership skills Organization sponsoring activity Parental time commitment Previous participation by child Previous participation by parent Top three criteria families use to determine recreation choices for children Top three criteria that prevent or discourage participation in activities by children Top three criteria that encourage participation in activities by children Chapter IV RESULTS The purpose of this study was to determine how much influence a female child has on decisions related to her own organized recreation participation and, secondarily, how much influence other household members, extended family members and others have on recreation decisions related to that child. Ninety-eight percent of the scouts live in a household with their biological mother while 85.9% also have their biological father present. Caucasians account for 93.1% of respondents. In addition, 89.7% of all respondents are married. The average household size is 4.42 persons with a range from two to ten. Children in the sample ranged from age five to 15, with an average age of 9.29 years. The parent or guardian most familiar with the child’s recreation activities was asked to complete the survey. A mother or stepmother returned 92.9% of all responses (see Table 4.1). 38 39 Table 4.1 Descriptive Statistics of Respondents and Households Category N Percent Respondents' Sex 310 Female 288 92.9 Male 22 7.1 Respondents’ Race 306 Caucasian/White 285 93.1 Hispanic/Latino 8 2.6 Asian 6 2.0 African American/Black 2 0.7 American Indian 2 0.7 Multiracial 1 0.3 Other 2 0.7 Respondents’ Marital Status 312 Married 280 89.7 Divorced 17 5.4 Single, never married 8 2.6 In a non-marital permanent relationship 5 1.6 Separated 1 0.3 Widowed 1 0.3 Family Structure (in household) 314 Dual—parent 256 81.5 One parent & one step-parent 28 8.9 One parent or legal guardian 25 8.0 One parent & extended family members 5 1.6 No. persons in household 312 Two 8 2.6 Three 34 10.9 Four 144 46.2 Five 90 28.8 Six 25 8.0 Seven 6 1.9 Eight 3 1.0 Nine 1 0.3 Ten 1 0.3 40 Table 4.1 Continued Category N Percent Respondents' highest level of education attained 310 Less than high school 3 1.0 High school 48 15.5 Some college, technical or associates degree 129 41.6 Bachelor’s degree 57 18.4 Some graduate level coursework 23 7.4 Graduate or professional degree(s) 50 16.1 Full-time wage earners in household 310 Zero 7 2.3 One 141 45.5 Two or more 162 52.2 Part-time wage earners in household 307 Zero 203 66.1 One 89 29.0 Two or more 15 4.9 Total household income 281 Less than $10,000 4 1.4 $10,000-$19,999 13 4.6 320,000-529,999 25 8.9 $30,000-$39,999 39 13.9 340,000-549,999 39 13.9 $50,000-$59,999 40 14.2 $60,000-$69,999 31 11.0 $70,000 or more 90 32.0 Analyses were completed to determine differences in family decision-making regarding different types of organized recreation activities. Thus, comparisons across 41 categories were made. By using this approach, it was assumed that respondents could recall correctly who was involved in past decision-making and would be able to report it in this research (Davis & Rigaux, 1974). Hypothesis One Hypothesis one states that mothers in dual-parent households will be perceived to have the most influence on decisions related to organized recreation activities in which their children participate. Dual-parent households are used in this analysis because in single-parent households whichever parent is present would most likely have inflated her or his level of influence. The issue of single-parent/guardian households versus dual-parent households is addressed in hypothesis three. For the purpose of this study, influence is defined as the percentage each group is involved in the information gathering and final decision stages of the decision process. “Daughters” will be referred to as “children” from this point forward. To test hypothesis one, a series of one— sample t-tests are performed. The confidence intervals of mothers at the .05 level of significance are tested against the confidence intervals of fathers, children, and other persons living in the household. Analyses are completed for 42 each activity for the information gathering and final decision stages of the decision process. As seen in Table 4.2, statistically significant differences were found between mothers and all others. Mothers are the most influential information gatherers for children’s participation in organized sports. Mothers gather 55.33% of the information, followed by children ‘1‘- _ (24.81%), fathers (16.64%), and others (8.33%). Table 4.2 Influence of Mothers versus Others on the Information Gathering Stage for Organized Sports (N=157) Household 95% Confidence Level Members Mean(%) SD Lower Upper Mothers 55.33 39.49 49.54 61.12 Fathers 16.64 28.31 12.26 21.02 Children 24.81 34.79 19.77 29.84 Others 8.33 23.53 4.94 11.73 In the final decision stage for organized sports, children are found to be significantly different at p<.05 .Level from all others in the household. In Table 4.3, one can see that children are the most influential on the final «decision to participate in organized sports. Children are 43 allocated 44.53% of the final decision, followed by mothers (30.79%), fathers (19.41%) and others (5.73%). Table 4.3 Influence of Mothers versus Others on the Final Decision Stage for Organized Sports (N=153) Household 95% Confidence Level Members Mean(%) SD Lower Upper Mothers 30.79 27.44 26.41 35.17 Fathers 19.41 20.75 16.09 22.72 Children 44.53 35.18 38.87 50.19 Others 5.73 16.41 3.10 8.35 In the information gathering stage for individual sports or other activities, mothers play a significantly different role than fathers, children and others at the p<.05 level. As seen in Table 4.4, on average, mothers gather 77.76% of the information, followed by children at 11.06%, fathers at 6.33%, and other household members at 4.98%, respectively. 44 Table 4.4 Influence of Mothers Versus Others on the Information Gathering Stage for Individual Sports or Other Activity (N=177) Household 95% Confidence Level Members Mean(%) SD Lower Upper Mothers 77.76 31.14 73.14 82.38 Fathers 6.33 18.24 3.62 9.03 Children 11.06 21.79 7.81 14.31 Others 4.98 16.91 2.48 7.49 Significant differences are found between mothers, fathers, and other household members on the final decision stage for participation by children in individual sports or other activities at the p<.05 level (see Table 4.5): However, mothers are not significantly different from children at the p<.05 level. The amount of the final decision attributed to mothers is 41.41% followed closely by children (39.23%). Fathers (15.78%) and others (4.36%) are not very involved in the final decision for this activity. 45 Table 4.5 Influence of Mothers Versus Others on the Final Decision Stage for Individual Sports or Other Activity (N=180) Household 95% Confidence Level Members Mean SD Lower Upper Mothers 41.41 29.28 37.10 45.72 Fathers 15.78 20.06 12.83 18.73 Children 39.23 34.75 34.14 44.33 Others 4.36 13.42 2.38 6.33 There are significant differences between mothers and all others in the amount of information gathered for summer camp participation by children. As can be seen in Table 4.6, mothers gather 63.10% of the information, followed by children (16.40%), others (13.19%), and fathers (6.63%). Others, on average, gather more information than fathers do. In this study, the others are, for the most part, older sisters. 46 Table 4.6 Influence of Mothers Versus Others on the Information Gathering Stage for Summer Camp (N=122) Household 95% Confidence Level Members Mean SD Lower Upper Mothers 63.10 39.49 56.05 70.15 Fathers 6.63 19.84 3.09 10.18 Children 16.40 29.36 11.14 21.66 Others 13.19 29.23 7.97 18.40 As can be seen in Table 4.7, mothers’ influence on the final decision stage for summer camp is not different from children at p<.05 level of significance. However, mothers and children are significantly different from fathers and other household members at p<.05 level. Mothers made 43.74% of the final decision, followed by children (34.49%), fathers (17.94%), and others (5.36%). 47 Table 4.7 Influence of Mothers Versus Other Household Members on the Final Decision Stage for Summer Camp (N=118) Household 95% Confidence Level Members Mean SD Lower Upper Mothers 43.74 27.53 38.72 48.76 Fathers 17.94 20.73 14.18 21.70 Children 34.49 30.94 28.77 40.20 Others 5.36 15.13 2.61 8.81 Overall, across all three categories of activities, mothers dominate the information gathering stage. Fathers play a limited role in this stage of the decision process. This may be due to the fact that mothers are, for the most part, the primary caregivers in the household. However, when the final decision is made about children’s participation in the three recreation activities, children become joint decision-makers with their mothers. Hypothesis Two The second hypothesis developed for this study was that as the age of the child goes up, the degree of perceived influence on each stage of the decision process increases. 48 Hypothesis two is tested using Analysis of Variance (ANOVA) to compare the means of each age group of children across the information gathering and final decision stages of the decision process. Bonferroni confidence interval post hoc tests are performed to determine if there are significant differences between age groups. There were only 14 children in the age group of 5—to-6-years old who had participated in summer camp; thus, there were no analyses completed for summer camp participation by this age group because of validity concerns. However, statistically significant differences are found across both decision stages for organized sports and individual sports or other activities. Group Three (12-to—15-years olds) are statistically different from Groups One (5-to-6-years old) and Two (7-to- 11-years old) in gathering information about their own participation in organized sports (F=21.110, p<.05) (see Table 4.8). Group Three is responsible for gathering 41.80% of the information for their own participation in organized sports, followed by Group Two (13.07%) and Group One (8.10%). Table 4.8 49 Children’s Influence on the Information Gathering Stage of the Decision Process for Organized Sports Age Groups N Mean(%) Sum of Squares DF 2F Value 5-6 29 8.10 Between Groups 41964.83 2 7-11 76 13.07 Within Groups 181898.20 183 12-15 81 41.80* Total 223863.03 185 21.110 Note. *p<.05 Overall, children’s influence is substantial in the final decision stage for their own participation in organized sports. Nonetheless, children in Group Three are statistically different than the other two groups at the p<.05 level with an F=6.755 (see Table 4.9). Group Three are associated with, on average, 52.09% of Children in the final decision as compared to children in Group One at 38.11% and children in Group Two at 34.22%. Table 4.9 Children’s Influence on the Final Decision Stage of the Decision Process for Organized Sports Age Groups N Mean(%) Sum.of Squares DF E'Value 5-6 27 38.11 Between Groups 16236.46 2 7-11 74 34.22 Within Groups 215123.60 179 12-15 81 52.09* Total 231360.07 181 6.755 Note. *p<.05 50 For individual sports or other activities, Group Three is significantly different from Groups One and Two (F=30.634, p<.05) (see Table 4.10). Members of Group Three gather 26.61% of the information for their own participation in an individual sport or other activity, as compared to less than 1% collected by Group One and 5.39% collected by Group Two. Table 4.10 Children’s Influence on the Information Gathering Stage of the Decision Process for Individual Sport or Other Activity Age _ Groups N Mean(%) Sum of Squares DF F Value 5-6 50 0.70 Between Groups 24882.47 2 7-11 82 5.39 Within Groups 80818.59 199 12-15 70 26.61* Total 105701.07 201 30.634 Note. *p<.05 51 Once again, children’s influence on the final decision stage is greater than on the information gathering stage. Older children, those in Group Three, are different than children in Groups One and Two at p<.05 level and with a F=4.734 (see Table 4.11). Children in Group Three have 48.78% of the final decision attributed to them, followed by children in Group One (35.24%), and children in Group Two (33.20%). Table 4.11 Children’s Influence on the Final Decision Stage of the Decision Process for Individual Sports or Other Activity Age Groups re Mean(%) Sum of Squares DF F Value 5-6 49 35.24 Between Groups 10678.71 2 7-11 84 33.20 Within Groups 231237.21 205 12-15 75 48.78* Total 241915.92 207 4.734 Note. *p<.05 Children ages 12-to-15-years—old gather more information than children who are in the 5-to—6-years-old age group and children in the 7-to-1l—years—old age group for both organized sports and individual sports or other activities. Children who are 5 or 6 years old most likely do not know where to gather information, and quite possibly, 52 are unable to read the information that was gathered. Older children (12-to—15-years old) were found to be statistically different from younger children (under 12 years old) in the amount of influence in making the final decision. This finding reaffirms what has been found in previous research. That is, as the age of children increases, they become more involved in the decision process for products that they will consume. Participating in an organized recreation activity is synonymous with consuming a product. Hyppthesis Three The third hypothesis developed for this study was that degrees of child influence are perceived differently by single-parent/guardian families versus dual-parent families, with single-parents/guardians assigning more influence to children than parents in dual-parent families. Hypothesis three is tested using independent sample t- tests. The information gathering and final decision stages are analyzed for children by single-parent/guardian versus dual-parent households. As can be seen in Table 4.12, children living in single-parent/guardian households do not gather significantly more information, at the .05 level of significance, than children living in dual-parent households for their own participation in organized sports (t=.608, p=.559). Children in single-parent/guardian households 53 gathered 32.78% of the information related to their own participation in organized sports while children in dual- parent households gathered 24.31% of the information. Table 4.12 Influence of Children, Based on Parental Relationship, on the Information Gathering Stage for Organized Sports Parental Sig. Relationship N Mean(%) SD t (2-tailed) Single-Parent/ Guardian 9 32.78 41.01 Dual-Parent 176 24.31 34.60 .608 .559 Children living in single-parent/guardian households do not have significantly more influence on the final decision for their own participation in organized sports than children living in dual-parent households (t=.839, p=.421) (see Table 4.13). Children in single—parent/guardian households are responsible for 54.03% of the final decision and children in dual-parent households are responsible for 42.64% of the final decision. 54 Table 4.13 Influence of Children, Based on Parental Relationship, on the Final Decision Stage for Organized Sports Parental Sig. Relationship N Mean(%) SD t (2-tailed) Single-Parent/ Guardian 10 54.03 43.08 Dual-Parent 170 42.64 35.26 .839 .421 Children in single-parent/guardian households are not significantly different from children living in dual-parent households in the amount of information they gather for their own participation in individual sports or other activities (p=.978, p=.347) (see Table 4.14). Children in single-parent/guardian households collect 20.38% of the information while children in dual-parent households collect 10.43% of the information. Table 4.14 Influence of Children, Based on Parental Relationship, on the Information Gathering Stage for Individual Sport or Other Activity Parental Sig. Relationship N Mean(%) SD t (2-tailed) Single-Parent/ Guardian 13 20.38 36.31 Dual—Parent 187 10.43 20.82 .978 .347 Children in single—parent/guardian households are quite similar to children in dual-parent households regarding the percentage of the final decision that is attributed to them for their own participation in individual sports or other activities. As seen in Table 4.15, children in single- parent/guardian households have 40.64% of the final decision attributed to them which is nearly the same as the 38.99% of the final decision attributed to children in dual-parent households (p=.162, p=.874). 56 Table 4.15 Influence of Children, Based on Parental Relationship, on the Final Stage for Individual Sport or Other Activity Parental Sig. Relationship N Mean( ) SD t (2-tailed) o\° Single-Parent/ Guardian 14 40.64 37.18 Dual-Parent 192 38.99 33.93 .162 .874 Children in dual-parent households gather more information regarding their own participation in summer camp than do children in single-parent/guardian households. The p value was -2.442 and it was significant at p<.05 (see Table 4.16). Children in dual-parent households gather, on average, 16.89% of the information compared to the 5.38% children in single-parent/guardian households gather. 57 Table 4.16 Influence of Children, Based on Parental Relationship, on the Information Gathering Stage for Summer Camp Parental Sig. Relationship N Mean(%) SD t (2—tailed) Single-Parent/ Guardian 13 5.38 14.50 Dual-Parent 130 16.89 28.85 -2.422 .024 Parental relationship does not make a significant difference in terms of the percentage of the final decision for summer camp attributed to children (p=—1.556, p=.147) (see Table 4.17). Children in single-parent/guardian households have 22% of the final decision assigned to them versus children in dual-parent households having 34.97% of the final decision assigned to them. 58 Table 4.17 Influence of Children, Based on Parental Relationship, on the Final Decision Stage for Summer Camp Family ' Sig. Structure N Mean( ) SD t (2-tailed) o\° Single-Parent/ Guardian 10 22.00 24.86 Dual-Parent 121 34.97 30.47 —1.556 .147 Except for the percentage of information gathered for summer camp, parental relationship does not seem to play a significant role in the influence children have on the information gathering or the final decision stages for the three organized recreation activities. This may have been due, in part, to the small percentage of single- parent/guardian households in the sample. Thus, not allowing for enough variation in the sample. Furthermore, these data should be interpreted judiciously because of the small number of cases that included single—parent/guardian households. Hypothesis Four The fourth hypothesis developed for this study was that a child’s influence varies between the information gathering 59 and final decision stages of the decision-making process. Hypothesis four is tested using paired sample t—tests. The paired-sample t-test procedure tests the null-hypothesis that differences in means of two related variables is 0 (Norusis, 1997). By using a paired—sample t—test, only those cases for which data are entered in both the information gathering stage and final decision stage for each activity are used. Thus, in cases where the questionnaire was not completely filled out, the data were dropped from the analysis. In this analysis, differences in the means between the amount of information gathered by children and the amount of the final decision attributed to them are tested. As seen in Table 4.18, a significant difference is found between the percentage of information gathered by children regarding their participation in organized sports and the percentage of the final decision attributed to them. The mean difference between the two stages is -18.54, with :g=-5.839 and p=.000. Children are more influential on the final decision stage (43.57%) than on the information gathering stage (25.02%) for their own participation in organized sports (see Table 4.18). 60 mm.mm hm.mv coflmflomo Hmcam mm.vm mo.mm ocflumnumo coflumEuowcH ooo. mmm.m| Hw.mv vm.mau muuoam pmNflcmmuo .95 8. am :8: am $28: 3839a mmocmumwwflo Umuamm Aomanzv muuomm omwflcmmuo now mommum coflmflooo Hmcflm pcm mCAHocumw coflumEHOMCH opp comzumm coupafico mo mocmSchH cfl mmocmumeHo mH.v manme 61 There is a significant difference between children’s influence on the information gathering and final decision stages for individual sports or other activity at the p=.000 level. The mean differences between the two stages is -25.77 with a p value=—9.446. Children gather, on average, 11.75% of the information for their own participation in organized sports and have 37.53% of the final decision attributed to them (see Table 4.19). 62 am.mm mm.am coflmsomo Hmcflu mH.mm m>.HH mcfluocumw coflumEuowcH ooo. www.mu oo.mm as.mm- suw>fluo< Harpo\uH0Qm Hmsnfl>flncH .oflm 8 mm 2mm: om lwvcmmz spfl>fluo< moocmuoLMHQ pouflmm Avanzv moflufl>fipo¢ nonpo no muuomm Hmspfl>flocH now mommum conHomo Hmcflm Ucm mcflumnumw coflumEuowcH mcu comzumm coupaflzo wo.oocmsamcH CH mmocmummwflo mH.v mHQmB 63 Children have significantly more influence on the final decision that the information gathering stage for their own participation in summer camp as can be seen in Table 4.20. The mean difference between the two stages is -16.82 with a p value=-5.345 at the p=.000 level. Children have 33.53% of the final decision attributed to them as compared to 16.71% of the information gathered. 64 mm.mm mm.mm :oflmflomo Hmcflm s>.mm H5.GH ocflumrumo cofiumEHOGcH ooo. mam.m- mH.Gm mm.GH- dsmo “messm .85m 6 am :mmz om lwvcmmz sufl>fluo¢ mmocmumwMHo Umuflmm Ammauzv mamo umEEDm now mommum coflmflomo Hmcflm Ucm mcflumcumo coflumE50mcH gnu comzpwm coupaflno Mo mucosamcH CA mmocwummwflo om.v manma 65 Overall, these findings reaffirm what has been found in previous research. Children’s influence during the information gathering stage is lower than their influence during the final decision stage. This is due, in part, to the fact that mothers as primary caregivers gather more information regarding their children’s participation in organized recreation activities (Howard & Madrigal, 1990). Moreover, previous studies have found that children are more involved in the final decision stage for products that they consume (Beatty & Talpade, 1994; Foxman & Tansuhaj, 1998). Hypothesis Five The fifth hypothesis developed for this study was that a child’s influence in the family decision—making process is positively related to a child’s financial resources. Financial resources are defined as those monies that children have that they can spend more or less as they choose. Such resources include allowances, gifts of money, money earned doing odd jobs and childcare, etc. Pearson zero-order correlations are computed to describe the strength of the relationships between children’s income across the information gathering and final decision stages for each activity. In the social sciences, a correlation between two variables, holding all other intervening variables constant, 66 is considered strong when it is above .25 (Agresti & Finley, 1997). There is a strong correlation between information gathered by children and the percentage of the final decision attributed to them (p=.261, p<.001) (see Table 4.21). In addition, there is a significant correlation between information gathered by children and children's income (p=.237, p<.01). There is a positive, but insignificant, correlation between the percentage of the final decision attributed to children and children’s income (£=.089). Table 4.21 Children’s Income and its Relationshipgto Children’s Influence on the Information Gathering and Final Decision Stages for Organized Sports (N=169) Variables X1 X2 X3 )fi Information Gathering Xinnal Decision .261** )@ Child’s Income .237* .089 Note: **p<.001; *p<.01; DF=167. Listwise deletions were used in computing the zero-order correlations. Children’s income is highly correlated with the percentage of information gathered for their own 67 participation in individual sports or other activities. The correlation has a p=.234, which is significant at p<.001 level (see Table 4.22). Moreover, there is a positive, but insignificant, relationship between children’s influence on the information gathering and final decision stages for individual sports or other activities (£=.129). Additionally, there is a negative, but not significant, relationship between the percentage of the final decision attributed to children and children’s income (£=-.005). Table 4.22 Children’s Income and its Relationship to Children’s Influence on the Information Gathering and Final Decision Stages for Individual Sport or Other Activity (N=183) Variables X1 X2 X3 )fi Information Gathering Xzfflnal Decision .129 )5 Child’s Income .234* -.055 Note: *p<.001; DF=181. Listwise deletions were used in computing the zero-order correlations. There is a positive, and significant, relationship between the percentage of information gathered by children for summer camp and children’s income (£=.271, p<.01) (see 68 Table 4.23). Also, there is a positive and significant, relationship between the information gathered by children and the percentage of the final decision attributed to them (£=.209, p<.05). There is a negative, but insignificant relationship between children’s income and the percentage of the final decision attributed to them (£=-.004). Table 4.23 Children’s Income and its Relationship to Children’s Influence on the Information Gathering and Final Decision Stages for Summer Camp (N=121) Variables X1 X2 X3 )fi Information Gathering )9 Final Decision .209* )Q Child’s Income .271** -.004 Note: **p<.01; *p<.05; DF=119. Listwise deletions were used in computing the zero-order correlations. For all three activities, there are significant correlations between the amount of information gathered by children and their personal income. However, there are no significant differences between children's income and their involvement in the final decision. This result did not 69 follow what had been found in previous studies by Beatty and Talpade (1994), Foxman et a1. (1989) and Moschis and Mitchell (1986). Regression Analysis Multiple regression is used to determine the impact of several variables on the amount of influence children have on the information gathering and final decision stages for each activity. To use multiple regression, the following assumptions must be met: (1) linearity of the phenomenon measured; (2) constant variance of the error terms; (3) independence of the error terms; and, (4) normality of the error term distribution (Hair, Anderson, Tatham, & Black, 1998). Variables in the multiple regression models are age, birth order, who initiated the idea, how much information is gathered by children, motivation, children’s income and social class. Social class is measured using either total household income or education level of parents depending on the activity. The basic multiple regression equation is as follows: Y=O(+B1X1+82X2+. . .+Bka 70 In this study, the dependent and independent variables include the following: Y dependent variable(s) Y¢= Information Gathered by Children Y§= Final Decision Attributed to Children Xg= independent variables Xv: Initiated Idea Xz= Motivation X3: Age )h= Birth Order )gg=Parent’s Education X5b= Household Income Xg= Child's Income XT= Information Gathered by Children Age is used to determine the child's cognitive development. It was hypothesized that older children would have greater influence in their own organized recreation activity participation than younger children. Brown and Mann (1989) and Darley and Lim (1986) found a positive relationship between age of adolescents and level of involvement in family decisions. Birth order is used because previous research has shown that first-borns are more involved in family decision-making than later-borns. This is due, in part, to the fact that first-borns and parents engage in interactions that are more continuous and intense than those with later—borns (Baranowski, 1978). Foxman et a1. (1989) and Moschis and Mitchell (1986) found that a child’s income has a positive relationship to products purchased by adolescents. 71 In consumer socialization of children, there are agent-learner relationships (refer to Figure 1.1). These relationships are measured by determining who initiated the idea, what percentage of information gathered was attributed to children and motivation. Initiation of idea is measured using a dummy variable (0,1) where “1” represented a child initiating the idea and “0” represented someone else initiating the idea. How much information that was gathered by a child is measured by the percentage assigned to a child in the information gathering stage. Motivation is used because the criterion “level of interest” has a mean of 3.88 on a 4.0 scale when parents/guardians were asked how important a list of criteria are in their decision to allow their children to participate in any organized recreation activity. Motivation is measured using an index. In the questionnaire, three questions were related to motivation for each activity. They were: 1” My daughter participated in this activity because she wanted to. 12.My daughter participated in this activity because I wanted her to. 13.My daughter participated in this activity because we both wanted her to. The questions are rank ordered in order of how motivated the child is in participating in the activity. A 72 child participating in an activity because “she wanted to” is assigned a “3”, followed by “we both want her to” is and “I wanted her to” is assigned a “1”. assigned a “2”, Euespondents were asked to state if they agreed with, were or disagreed with each statement. Agreed is neutral, and disagree is asasigned a “1”, neutral is assigned a “0”, assigned a “-1”. Thus, creating an index from -6 to 6 Wileareas -6 means the respondent disagreed with all three Sizéatements and 6 means the respondent agreed with all three 3 t atements . Organized Sports Information Gathered by Children The first step in completing each multiple regression In<>~’l'—‘ “cmpcmama mmo. mmo.u «4mmm. Hoe.) mmH. mEoocH m.pafizo ex 80.. So. mac. 9: .. 838:3 m Lcmumm 3x mNH.| mmo.| mbo. umouo nuuflm .x bwo.u «*me. mom mx mmo. :ofium>fluoz Nx mmcH owumfluflcH 1x mmwnmwwm> Hobowpmum ox mx vx mx Nx Hx moanmwum> muouoflpmum manomw oomflcmmuo now couoaficu >3 poumnumo coflumEHOMCH cufiz mmabmfium> ucopcommocH mo xflupmz coflumHmuuoo umpuoloumm E .V $35 74 Regression analysis is completed to test the independent variables’ influence on the percentage of information gathered by children for organized sports. By using The errter-method is used to complete the analyses. all variables in the block are entered into the tliis method, A linear regression model that has a ec1uation as a group. :sixgnificant F value shows that there is a linear .realationship between the dependent variable and the ixurdependent variables. In addition, a variable with a beta weight that has a significant 3 statistic associated with it iruciicates that the coefficient for the variable is not zero (IQ<3rusis, 1997). Thus, the independent variable does eXplain some of the variance in the dependent variable. The collinearity tolerance level is presented in each It tests to see how much each independent variable table. 5153 explained by other independent variables. Tolerance is tildes amount of variability of the selected independent ‘réiqtiable not explained by the other independent variables (Iiiair, et al., 1998). Thus, high tolerance values denote In this study, a tolerance value of J‘CDVV multicollinearity. "77(3 is considered acceptable which is consistent with the ac—‘-<:eptable level for the social sciences. From this point forward beta weights will be presented (p<.001) and initiation of kDS’ lasing B. Age has a B of .311 75 idea has a B of .302 (p<.001), indicating that age and initiation of idea have positive and significant impacts on amount of information gathered by children. Child’s income, __B—= - O90, motivation, B=.088 and birth order, B=.042, have positive, but insignificant impacts on the information gathered by children. Parent’s education, B=-.013, has a negative, but very weak and insignificant impact on information gathered by children for organized sports. These independent variables .have a linear relationship (_F_=10.586, p<.001). The adjusted R’- indicates the preportion of the variance of the dependent variable accounted for by the independent variables (Pedhazur, 1982) . Just over 27% of the variance in information gathered by children is explained by the independent variables (see Table 4.25). In spite of this, that leaves 73% of the Variance to be explained by other factors (see Table 4.25) . Table 4.25 76 Regression Analysis for Children’s Influence on the In formation Gathering Stage of Organized Sports (N=154) Beta Significance Collinearity Variables Weight T Value of Tabled T Tolerance X1 Initiated Idea .302 3.950 .000 .810 X2 Motivation .088 1.265 .208 .970 X3 Age .311 3.927 .000 .753 X4 Birth Order .042 .603 .603 .956 Xsa Parent’s Education -.013 -.013 -.183 .950 X6 Child’s Income .090 1.226 .222 .880 \ R=. 548; R2- .3300,- Adjusted R2=.272; F=10.586; p<.001 77 Final Decision The zero-order correlation matrix of independent variables with the percentage of the final decision assigned to children for organized sports is presented in Table 4.26. The variables found to be most correlated with the percentage of the final decision assigned to children for Organized sports are age (p=.306, p<.001), information gathered (_r=.263, p<.001), and initiation of idea (£=.255, B< - 01) . Variables with insignificant positive correlations on the percentage of the final decision assigned to children are child's income (p=.073) and parent’s education (£=.040) . Variables that have insignificant negative correlations with the percentage of the final decision assigned to children are birth order (_r_=-.132) and motivation (£=-.012). 78 .mcoflumamuuoo poouonoumu on» OCMDDQEOO Ca poms mum: mcoflumamo mmflzumflq .mmaumo “Ho.vm+ “Hoo.vmee .muoz .emwm. mac. Ovo. mmH.| weemom. mHo.u emmm. coflmflowo Hmcflm » mwnmflum> acmbchoQ ..mmm. mmo.u moo. weemmv. Nmo. «emmv. omumcumw coflumEHOHCH hx nmo. mmo.n 444mmm. moo.: mmH. oEoocH m.oafico ex bmo. mao.| moo. emmH.: coflumospm m.ucmumm.xx mHH.I voo.n mmo. umpuo :uuflm .x moo.) eemmm. mod mx who. aceum>eeoz Nx mmnH emumepHcH Hx mmwnmflum> Hobowbmwm Fx ex mx ex mx Nx Hx mmabmfium> muouoflowum manomm pmmflcmmuo no“ cmuoaflco momE cofimfiomo Hmcflm cuflz mmabmflum> ucmocmmoocH mo xfluumz :oflumamuuou uoUuOuoumN mm.v magma 79 Regression analysis is completed to test the independent variables’ influence on the percentage of the final decision assigned to children for organized sports. Age has a B of .188 (p<.05), indicating that age has a positive and significant impact on percentage of the final decision assigned to children. Initiation of idea, B=.159, information gathered, B=.128, and parent’s education, §= - 073, have positive, but statistically insignificant impacts on the percentage of the final decision assigned to Children. Birth order, B=—.120, child’s income, B=—.054, and mOtivation, B=—.045, had negative and insignificant impacts determining the percentage of the final decision assigned to Children. The B value is 3.353 and is significant at the B< - 01 level, thus indicating a linear relationship between the independent variables. Eleven percent of the variance in the percentage of the final decision assigned to children is explained by the independent variables. That leaves 89% of the variance to be explained by other factors (see Table 4 - 27) . ”Cable 4.27 80 Re gression Analysis for Children's Influence on the Final De Cision Stage of Organized Sports (N=154) Beta Significance Collinearity Va riables Weight T Value of Tabled T Tolerance X1 Initiated Idea .159 1.768 .079 .736 X2 Motivation -.045 -.569 .570 .964 X3 Age .188 2.000 .047 .672 X4 Birth Order -.120 -1.523 .130 .957 Xsa Parent’s Education .073 .917 .361 .948 X6 Child’s Income -.054 -.658 .512 .873 X7 Information Gathered .128 1.382 .169 .696 \ R=.369; R2 =.136; Adjusted R2=.106; F=3.535; B<-Ol 81 Individual Sports or Other Activities Information Gathered by Children The zero-order correlation matrix of independent ucmbchoQ 3.0. 3.0.: *mmfi. woof mao. wEoocH mepaflno ex mvof mma. mHo. oHo. coflumosom mLcmumm 2x moo... oHo. hao. nopuo nuuflm ex *«mom.| «Mam. wofi mx moo.- aceum>euoz ex mmoH omumfluHcH Hx moanmwumS Hobowpmum ex ox ex ex Nx _x moaomflum> muouoflomum mmflue>eno< Macao no mBHOQm Hmsne>encH How cmeeaero No pmuocumw coflumEuomcH LUHB moaomflnm> ucmocmmmch mo xfluumz coflumawuuou Mongolouom mm.v magma 83 Regression analysis is completed to test the influence of independent variables' influence on the percentage of Lnformation gathered by children for individual sports or other activities. Age has a B of .388 (p<.001), initiation CD f idea has a B of .287 (p<.001), and child’s income has a B of .212 (p=.001) indicating that age, initiation of idea, and child’s income have positive and significant impacts on explaining the amount information gathered by children. Motivation B=.099 and birth order B=.070, have positive but iixr155;ignificant impacts on the information gathered by ch i ldren. Parent’s education has a negative (B=-.199) and Significant impact (p<.01) on the explaining the amount of information gathered by children. The model has an B value of 14.820, which is significant at the p<.001 level, thus indicating a relationship between the independent variables. Tlflirty—three percent of the variance in information gathered by children for individual sports or other activities is explained by the set of independent variables. Nevertheless, that leaves 67% of the variance to be explained by other factors (see Table 4.29). Tab 1e 4.29 84 Re gression Analysis for Children's Influence on Information Gathering Stage for Individual Sport or Other Activity ( N =‘167) Beta Significance Collinearity Va riables Weight T Value of Tabled T Tolerance X1 Initiated Idea 287 4.421 .000 .952 X: Motivation .099 1.497 .136 .913 X3 Age .388 5.606 .000 .834 X4 Birth Order .070 1.104 .271 .991 Xsa Parent's Education -.199 -3.103 .002 .974 Xe Child's Income .212 3.266 .001 .951 \ RF=- 596; R2=.356; Adjusted R2= . 332; F=14.820; p<.001 85 Final Decision The zero-order correlation matrix of independent xy’eslwz:iables with the percentage of the final decision assigned 1:.<:> children for individual sports or other activities is 1;>:I:’eesented in Table 4.30. The only variable that is ss.jL.§gnificantly correlated with the percentage of the final <:1<:>ssitive correlations with the percentage of the final cieeczision assigned to children. Child’s income (£=-.068) and t>i.3:th order (£=-.009) have insignificant negative C:c>2:relations with the percentage of the final decision assigned to children. 86 .mcoflumamuuoo Hotpoiouon on» ocquQEoo CH poms mum: mCOAumaoo mmaZumfiA .oeeumo “Hoo.vm.. .muoz bra. moo.) who. moo.) ova. moo. emmm. cofimflomo Hmcflm » mqnmflum> unmpchmQ whom. mNH.n mno. *mmv. mvo.l +>mm. owumcumw coflumEHOMCH ex Hmo. mac.) *oom. moo.) oHo. oEoocH m.oaflzu ex mmo.) mmfi. «00. Geo. sceumusom m.ucmume.sx vaO.) Hoo. ooo. uwouo cuuflm .x .mmm.u .mmfi. mo< mx mHH.n copum>euoz Nx mmoH vmumeeecH Hx mmwQMflum> MOobwUmum ex ex ex ex ex Nx Hx moanmflum> mHOuUHUmHm sue>eeom uwcpo\u60dm Hmzoe>fincH How emanaflno we oomE coflmflooo Hmcflm cue: mmfibmflum> ucmocmmmocH mo xfluumz coflumaouuoo umUHOIOHoN om.v mapms 87 Regression analysis is completed to test the 1 ndependent variables’ influence on the percentage of the f inal decision assigned to children for individual sports or o t her activities . As can be seen in Table 4.31, initiation O f idea has a B of .212 (p<.05), indicating that initiation O f idea has a positive and significant impact on percentage 0 f the final decision assigned to children. Motivation, §= -149, age, B=.113, information gathering, B=.106, and pa rent’s education, B=.081, have positive, but insignificant impacts on the percentage of the final decision assigned to Children. Child’s income, B=-.130, and birth order, B=-.023 have negative and insignificant impacts on the percentage of the final decision assigned to children. This model has a B Value of 2.890, which is significant at the p<.01 level, thus indicating a relationship between the independent Variables. Nevertheless, only 7.6% of the variance in the percentage of the final decision assigned to children is explained by the independent variables. That leaves nearly 93% of the variance to be explained by other factors. Table 4.31 88 Regression Analysis for Children's Influence on the Final Decision Stage of Individual Sport or Other Activity (N=163) Beta Significance Collinearity Variables Weight T Value of Tabled T Tolerance X1 Initiated Idea 212 2.573 .011 .849 )9 Motivation 149 1.847 .067 .886 )9 Age 113 1.240 .217 .689 >O Birth Order -.023 -.300 .764 .981 X5,a Parent’ 5 Education .081 1.030 .304 .918 X6 Child’s Income -.130 -1.627 .106 .893 .X7 Information Gathered .106 1.114 .267 .638 R=.341; R2=.116; Adjusted R2=.076; F=2.890; p<.01 89 Summer Camp Information Gathered by Children The zero-order correlation matrix of independent variables with information gathered by children for summer camp is presented in Table 4.32. The variables most correlated with information gathered by children for summer camp are initiation of idea (B=.335, p<.001), age (B=.264, p<.01), and household income (£=-236r p<.05). Birth order (£=.174) and child’s income(£=.139) have insignificant positive correlations. Motivation (£=—.042) has an insignificant negative correlation. 90 Monmououmn onu mcfluSQEoo CH poms mum: mcofluwaoo mmazumflq .mcofiumaouuoo .Owfiflhfl umO.Vm+ uHO.Vm4* “HOO.VN**# .OUOZ mmH. womm. era. tevom. moH.l «eemmm. Uwuonumu cofiumEu0mcH Aexv > menmwum> ucmpchmQ mea. . mmH.| osfi. hNO.) med. wEoocH m.paflnu ex oma. nmo. omfi.| mmo. mEoocH paonmmsoznsx mmo.) boa.) oma. umouo nuuflm ex m3... 323mm. 654 mx ova.) cofium>fiuoz ex mmoH owumfluacH Ax mmHQmfiHm> scuowbmum ex 0x 9x mx Nx Hx mmabmflum> muouoflowum mEmO umEESm no“ cmuoaflno >3 pmumnumw coflumEHOMCH Luflz moanmflum> ucmpcmmwocH mo xfluumz coflumHmuuou umpuoloumm Nm.v OHQMB 91 Regression analysis is completed to test the independent variables’ influence on the percentage of information gathered by children for summer camp. Initiation of idea had the only significant B of .248 (p<.05), as can be seen in Table 4.33. All of the other variables have a positive, but insignificant impact on the percentage of information gathered by children. Household income has a B of .185 (p=.071), age has a B of .180 (p=.084), birth order has a B of .130 (p=.200), child’s income has a B of .058 (p=.565), and motivation has a B of .017 (p=.863). The independent variables have a relationship (B=3.654, p<.01) and explain 14.8% of the variance of information gathered by children regarding participation in summer camp. Table 4.33 92 Regression Analysis for Children’s Influence on the Information Gathering Stage for Summer Camp (N=92) Beta Significance Collinearity Variable Weight T Value of Tabled T Tolerance X1 Initiated Idea .248 2.395 .019 .864 )9 Motivation .017 .173 .863 .918 X3.Age .180 1.750 .084 .876 DC Birth Order .130 1.291 .200 .915 XSb Household Income .185 1.830 .071 .907 X6 Child’s Income .058 .578 .565 .906 =.451; R2=.203; Adjusted R2=.l48; F=3.654; p<.01 93 Final Decision The zero-order correlation matrix of independent scraariables with the percentage of the final decision assigned to children for summer camp is presented in Table 4.34. Motivation (_i:=.321, p<.05), household income (B=.268, E<'05)' and age (£=-219r p<.01) are significantly and positively correlated with the percentage of the final decision assigned to children for summer camp. Information gathering (_r:=.165), birth order (£=.156), and initiation of idea £=.155) have insignificant and positive correlations with the percentage of the final decision assigned to children. Child's income (£=-.026) has an insignificant negative correlation with the percentage of the final decision assigned to children. 94 umUHOIouoN .mcoflumamuuoo ocu ocflusdeoo :H com:.ouwz mcofluoaoo omfizumdg .mmaumo “mo.vme “HovmI Hoo.v.mtte .wuoz mofi. omo.n eoom. omH. +mfim. eeflmm. mmH. coflmflooo Hmcflm w manmwum> “cocchoQ mmfi. emmm. mmH. etmom. aoH.| teemhm. omumsumw :oflumEuOMCH hx moa. mma.) oofi. mHo.) mvH. oEoocH m.oaflco ex omo. oHo. o>H.| moo. oEoocH oaonwmsomnsx mmo.| moo.) HNH. umouo nuuflm ex voH.I «ttmvm. mo< mx 5:.) 833302 Nx mooH omumfluflcH ix mownmflum> Hoboflomum hx ex 2x .x mx Nx flx 833:5 muouoflooum mg HmEESm now coamflooo Hoses cues moanmflum> unmocmmmocH wo xfluumz coflumamuuoo umUHOIOHmN vm.v manme 95 Regression analysis is completed to test the independent variables’ influence on the percentage of the ff:i.rial decision assigned to children for summer camp. I‘1<:>1:lsehold income has a B of .223 (p<.05) indicating that 1"1<:>1_1sehold income has a positive and significant impact on €32>t151aining the percentage of the final decision assigned to Cllitildren (see Table 4.35). Age, B=.176, birth order, Eia= .110, initiation of idea, B=.042, and information Széithering, B=.018, have positive, but statistically Iirisignificant impacts on the percentage of the final decision assigned to children. Motivation, B=—.240, p<.05, has a negative and ESignificant impact on the percentage of the final decision assigned to children. Child’s income, B=-.086, has a negative and insignificant impact on the percentage of the final decision assigned to children. The B value is 2.785 and is significant at the p<.05 level, indicating a relationship between the independent variables. Thirteen percent of the variance in percentage of the final decision assigned to children is explained by the independent variables. That leaves 87% of the variance to be explained by other factors. 'Table 4.35 96 Ikegression Analysis for Children’s Influence on Final [Decision Stage of Summer Camp (N=83) Beta Significance Collinearity \fariable Weight T Value of Tabled T Tolerance X1 Initiated Idea .042 .360 .720 .763 )(2 Motivation -.240 -2.259 .027 .926 )<3 Age .176 1.553 .125 .819 )(4 Birth Order .110 1.034 .304 .918 X5,J Household InCome .223 2.048 .044 .883 X6 Child, 5 Income —.086 -.795 .429 .905 X7 Information Gathered .018 .152 .880 .769 R=.452; R2=u204; Adjusted RL=.131; F=2.785; p<.05 97 Zero-order correlations for each regression model are presented in Table 4.36. Multicollinearity is not a problem in any of the correlation matrixes. Therefore, the variables in each model are independent of each other. There are six regression models. They are identified as follows: Ry—Children’s influence on the information gathering stage for organized sports. Rg—Children’s influence on the final decision stage for organized sports. Ry-Children’s influence on the information gathering stage for individual sports or other activities. Ry—Children’s influence on the final decision stage for individual sports or other activities. Rg-Children’s influence on the information gathering stage for summer camp. Rg—Children’s influence on the final decision stage for summer camp. Who initiated the idea is significantly correlated with the dependent variable for five of six regression models. This variable was coded as a dummy variable. Thus, if <:hildren initiated the idea of participating in the :recreation activity, they are more involved in the decision Earocess. This reaffirms what is found in the previous Estudies in that children are more involved in the decision Earocess for products that they consume. 98 .coflumsqo coflmmouowu mcu ca poms uoc we manoeum> mcp mums: mmomaa :fl umoddm Anommnmmo .mo.vmt .muoz moH. 1): sea. I): emom. (I) owumcumo coflumEuOMCH Fx omo. mmH. moo.) tosm. mno. eamm. oEoocH m.oafl£o ex toom. tomm. I): :n: In) In) mEoocH oaonwmsomewx a): nun who. omH.| ovo. mvo.| coflumosom mtucoumm.ax oma. «ea. moo.) boo. NmH.| oHo. Hmono :uuflm ex emam. evom. oeH. «mmv. toom. *va. woe mx *Hmm. ooH.) moo. avo.n NHO.) Hoo. coflum>fluoz ex mmH. emmm. emmm. *Nom. «mmm. *mvv. mmoH omumfiuHcH Hx em nm em mm mm am mmHQMflum> QEmU HoEESm sue>euo¢ uwtuo \BHOQm Hmsee>endH manomm oomflcmmuo mambo: coflmmomme Ham now mmxfluumz coflumHmuuoo umouotoumm mo >HmEESm om.v mHQMB 99 Also, age is significantly correlated with the dependent variable in five of six regression models. Previous research has found a strong link between age of children and their level of involvement in the decision process in that as children get older they are more involved in the decision process. The amount of information gathered does not play a significant role in the percentage of the final decision attributed to children for any of the activities. The information gathering and final decision stages appear to be independent of each other. This finding does not follow the logic of the decision-making process in that the expectation is that the three stages of the decision process are interrelated. Moreover, age is highly correlated in the information gathering stage for all three activities and the final decision for two of three activities. However, the <:orrelations are reduced for the final decision stage. TFhus, age appears to lose its effectiveness in the final (decision stage. Additionally, it was hypothesized that children’s i.ncome would be highly correlated with the percentage of the 100 final decision attributed to them. In this study, children’s income has a very weak correlation, whether positive or negative, across the three activities. This may have been due, in part, to the young age of the sample. The average age of children in this study is 9.29 years. All six regression models are significant at the .05 level. However, the variables in the models explain more of the percentage of information gathered by children than the percentage of the final decision attributed to children. This finding was different from what was expected (see Table 4.37). 101 cfl ummddm Asommnmmo .sufi>wuom comm How momum ocflumnumo c0wum8uowcfl .coflumsgm c0ammmuowu mcu Ca poms uoc ma manmfium> may mums: moumad .xuw>auom comm How woman cofimflomo Hmcflm mnu new mamooE wum em cam .Jm.~m mcofimmmuomm map you maooos mum am cam..3wtsm mCOammmuomm “mo.vme .muoz :2. $3. $3. $2. $2. .NR. mm 8333 mac. )1) Goa. In: mma. (In nmumnumo coeumEHOMcH ex e8.) mmo. 02.- N8. $0.- 26. 6585 PBEo .x tmmm. mma. III III In) In: oEoocH oaocmmsomnsx nu- I): Hmo. Toma.) meo. mac.) aceumosnm m.ucmumd.xx OHH. omH. mmo.- oso. omH.u Nee. uwnuo tuuflm .x one. omH. mHH. emmm. .mmfi. THHm. mod mx «ovm.u bao. ova. moo. mvo.u moo. coflum>fiuoz Nx Nee. mew. INHN. whom. mmfi. mom. mmnH odomeuHcH 2x em mm .m mm mm 2m mmHannm> mEmU hwEESm sue>euo< umteo \uuomm HmsneswncH muuomm UmNHcmmuO maoooz mcoflmmmummm Ham How mucmwmz mumm mo mumfifism hm.v maflme 102 The expectation was that if the consumer socialization rncodel was used that the percentage of influence of the child corn the final decision stage of the decision process would be kbeetter explained. Using the consumer socialization model, ‘Jiariables in the study included peer influence, influence of :Ekamily members outside of the household and influence of coachs/instructors . However, respondents assigned minimal iJnfluence to members in each of these groups. It appears tzhat recreation decision-making for children is not parallel ‘to decision-making related to goods consumed by children. Thus a modification of the consumer socialization model was made (see Figure 4.1). 103 .c0flumuflamfioom umESmcoo mo Hmoos omwufloos a .H.v magmas soapflmOQ maoso coauowumucfl Hmfloom I done so mad mmHQmHHm> amusuuzuum HmHOOm meuHmQOHQ HCMWOOHOMCAOm I ocflcummq A) cflamooz I "maflzmcoflumHmu umcummasucmmd mmEooozo mommoooum COwBQNHwaoom mocmbmomuca 104 Importance of Selected Criteria Respondents are asked to rate how important a list of 3.“? selected criteria are to them in making decisions zreagarding their children’s participation in any recreation aa<:tivities. A four-point scale with 1 being “not important” aarid 4 being “very important” is used. Health and safety of aa child received the highest mean rating (3.93), followed by lxevel of interest of child (3.88), and information provided k>3rsponsor (3.41). Previous participation in the activity k3)’a parent has the lowest mean rating, 2.18 (see Table 4 .38). 105 Table 4.38 How Important Selected Criteria are in Makinngecisions Regarding Organized Recreation Participation of a Child Criterion N Mean SD Rank Health/safety of child 312 3.93 .28 1 Child’s interest in activity 311 3.88 .34 2 Information provided by organization 311 3.41 .76 3 Flexibility time/dates of activity 310 3.30 .77 4 Age of child 311 3.23 .89 5 Location where activity takes place 312 3.16 .81 6 Sponsor of activity 311 3.11 .90 7 Educational value of activity 312 3.04 .77 8 Length of time of activity 312 3.00 .82 9 Opportunity to develop leadership skills 312 2.98 .88 10 Cost of activity 312 2.97 .84 11 Number of activities in which child participates 310 2.94 .97 12 Parental time commitment 311 2.92 .86 13 Child’s independence 309 2.75 .93 14 Friend(s) participating in activity 312 2.36 .89 T-15 Previous participation in activity 311 2.36 1.00 T-15 Previous parental participation in activity 307 2.18 1.07 17 Scale: l=”not important”; 2="somewhat important”; 3="moderately important”; 4=”very important”. Moreover, respondents are asked to list the top three criteria, using the list that was presented in Table 4.39, that prevent or discourage their daughters’ participation in organized recreation activities. The data were coded to give them a total point value and then were ranked in order of importance. 106 Total points were calculated using the following formula: TP = [(X1*3) + (X2*2) + (X3)] Total Points = [(total number of respondents that gave a criterion a number one ranking * 3) + (total number of respondents that gave a criterion a number two ranking * 2) + (total number of respondents that gave a criterion a number three ranking). For example, for the criterion AGE, 12 ranked the criterion #1, 6 ranked the criterion #2, and 10 ranked the criterion #3. 58=[(12*3)+(6*2)+(10)] I The top three criteria that prevent or discourage participation in any recreation activities by children are cost of activity (290 points), child’s interest in activity (211 points), and flexibility of times/dates of activity (200 points). Child’s independence ranks last with 2 points(see Table 4.39). 107 Table 4.39 How Important Selected Criteria are in Preventing or Discouraging Participation of a Child in Organized Recreation Activities Total Criterion N Points Rank Cost of activity 137 290 1 Child’s interest in activity 96 211 2 Flexibility time/dates of activity 143 200 3 Location where activity takes place 94 178 4 Health/safety of child 63 137 5 Parental time commitment 47 90 6 Length of time of activity 37 68 7 Number of activities in which child participates 36 63 8 Age of child 28 58 9 Sponsor of activity 28 52 10 Information provided by organization 25 50 11 Previous participation in activity 17 39 12 Previous parental participation in activity 14 25 13 Friend(s) participating in activity 14 22 14 Educational value of activity ' 5 8 15 Opportunity to develop leadership skills 2 5 16 Child’s independence 1 2 17 Furthermore, respondents are asked to list the top three criteria that encourage participation of their children in organized recreation activities. The same formula, as stated above, is used to determine total points for each criterion. The top three criteria are child's interest in activity (229 points), educational value of activity (162 points), and flexibility of times/dates of 108 activity (118 points). Number of activities in which a child participates at one time and previous participation of parent in activity tied for last with six points each (see Table 4.40). Table 4.40 How Important Selected Criteria are in Encouraging Participation of a Child in Organized Recreation Activities Total Criterion N Points Rank Child’s interest in activity 199 229 1 Educational value of activity 88 162 2 Flexibility time/dates of activity 64 118 3 Opportunity to develop leadership skills 50 92 4 Friend(s) participating in activity 14 83 5 Health/safety of child 54 78 6 Cost of activity 60 76 7 Location where activity takes place 39 71 8 Sponsor of activity 36 70 9 Age of child 18 41 T-10 Child’s independence 21 41 T-10 Information provided by organization 19 36 12 Previous participation in activity 18 30 13 Parental time commitment 16 23 14 Length of time of activity 8 18 15 Number of activities in which child participates 5 6 T-16 Previous parental participation in activity 3 6 T-16 It was postulated that the length of time of the entire decision process (initiation, information gathering, and final decision) would be longer for summer camp versus organized sports and individual sport or other activities. 109 Respondents were given the following categories in which to state the length of the entire decision process: (1) less than two weeks; (2) two to four weeks; (3) more than four weeks. One-sample t-tests are used to complete the analysis. The decision process is significantly different at the p<.001 for all three activities. As expected the length of the decision process is longest for summer camp (see Table 4.41). Table 4.41 Length of Entire Decision Process for Each Activity Activity N Mean SD Organized Sports 191 1.16* .45 Individual Sport or Other Activity 201 1.39* .68 Summer Camp 149 1.63* .73 Note. *p<.001 Chapter V CONCLUSIONS AND IMPLICATIONS Limitations There are limitations associated with any study, including this one. The limitations discussed below are those considered most important in this study. They are: 0 Parent/guardian that completes the survey may have different perceptions of influence than the parent/guardian who did not complete the survey. 0 Parent/guardian’s perception of influence on decision stages may be different than the child’s perception of influence. 0 Results of the survey cannot be generalized to all girls ranging in age from five to 15 because a convenience sample was used in the study. First, it would have been beneficial to have both parents fill out the survey independently so tests could have been performed to see if influence as stated by each parent is statistically different. However, due to time and budgetary constraints, this was not possible. Since parents/guardians most involved in their children's organized recreation activities were asked to fill out the survey, hopefully information obtained from one parent/guardian was reflective of both parents in a dual— 110 g Pv nu. .hu Aye 111 Second, since this study dealt with triadic decision- making between mothers, fathers, and children, the outcomes of the study would have had more strength if all three groups completed a questionnaire. The decision not to include children in the survey process was based on two conditions. First, budget constraints limited the scope of the study and, second given the young age of some of the children in the study, they may not have been able to articulate how much influence they had in the decision process. Third, results of this study cannot be generalized to the general population of 5-to-15-years-old girls, but it does shed some light on what role children have in the family decision process for organized recreation activities to the extent that responding parents’/guardians’ perceptions are reasonably accurate. Conclusions Family Members Influence Mothers were found to be the most influential during the information gathering stage for all three activities. It was not surprising that mothers gathered most of the information because in most households they are considered the primary caregiver. Also, in the cover letter parents and guardians were asked to have the person most involved 112 with their children’s recreation activities fill out the survey. In addition, Howard and Madrigal (1990) found in their study of recreation participation by children that mothers were most influential in the information gathering stage. Moreover, they found that fathers had limited involvement in the entire decision process and that children were only meaningfully involved in the final decision. For the most part, these conclusions were supported by the results of this study. Age of Child It was hypothesized that older children have more influence of the decision process than do younger children. Previous research has shown that there is a positive relationship between age of a child and level of involvement in family decisions (Howard & Madrigal, 1990; Brown & Mann, 1989, 1988; Darley & Lim, 1986; Jenkins, 1979). Children in the oldest age group were found to be much more involved in both the information gathering and final decision stages. They were statistically different than the two younger groups at the p<.001 level. Thus, these data reaffirm what has been found in previous studies. 113 Single-Parent/Guardian Households versus Dual—Parent Households It was hypothesized that children from single- parent/guardian households would be perceived as having more influence on the entire decision process than children from dual-parent households have. Dornbusch et a1. (1985) found V WT that adolescents in single—parent families were more involved in decisions concerning themselves than adolescents in dual—parent households. In this study, statistically significant differences were found between children in single-parent/guardian versus dual—parent households only for the amount of information gathered by children for summer camp. In this case, children in dual-parent households gathered more information. There are three possibilities as to why there is only one significant difference. First, the sample size was small. Second, in this sample, 91% of children reside in dual-parent households as compared to 72% nationwide (U.S. Bureau of Census, 1998). Consequently, the sample was homogeneous and did not allow for much variation between the variables. Third, older adolescents 16-to-18-year olds were not a part of this study because of the low participation rate of this group in Girl Scouts. Had this age group been part of the study, there most likely would have been a 114 different pattern of influence in the final decision stage. Influence of Children at Different Stages in the Decision Process As stated previously, mothers are the primary caregiver in the majority of households and have been shown to gather statistically significant more information than fathers and (En children. Moreover, prior research has shown that children have shared in the final decision with their mothers (Beatty L et al., 1994; Belch et al.,1985; Foxman et al., 1989, 1988; Jacobs et al., 1993). In this study, children were found to be significantly more involved in the final decision stage for organized sports at the p<.001 level than they were in the information gathering stage. Also, they were significantly more involved in the final decision stage for summer camp at the p<.01 level than they were in the information gathering stage. Thus, the results of this study reaffirm what has been found in earlier family decision-making research. However, is using consumer socialization theory the expectation was that children would be much more active in the information gathering stage than results from this study indicate. Children’s Income The only difference found in this study that related to 115 <:hildren’s income was that children with personal incomes of 53500 or more collected significantly more information for (organized sports (p<.05) than children with personal incomes loelow $500. Had older adolescents been part of the survey, additional differences related to children’s income would likely have surfaced. Foxman et a1. (1988) and Moschis and Mitchell (1986) found older adolescents’ financial resources positively linked to their role in family decision-making. Consumer Socialization The analysis of the data suggests a modification to the consumer socialization model is necessary. It is assumed that path analysis would be the best method of analysis to use to measure children’s influence on the information gathering and final decision stages of the decision process. However, this did not hold true. The amount of influence peers and others (e.g., coaches, instructors, sponsors of activity) have and the motivation for participation in the activity are not directly related to the social structural variables and the age of the child. Thus, regression is the best analytical tool to use. Importance of Selected Criteria The results of this study indicate that health and .safety of a child, a child's interest in an activity, and :flexibility of times and dates an activity is offered are 116 t:he major concerns parents/guardians have with allowing a <:hild to participate in any organized recreation activity. Implications Mothers gather the majority of information regarding their children’s participation in organized recreation activities. Therefore, advertising for organized recreation activities should be aimed at mothers. It should focus on the safety of an activity (e.g., swimming—certified lifeguards on duty), how much supervision will be on hand, and safety of the location in which activity will take place (e.g., YMCA). Moreover, the ads should state the benefits to a child in participating in an activity. Items to emphasize in the ads should include some of the following list: social relationships that will be developed if the child participates, educational value of an activity, and other skills a child will learn as a result of participating in the activity (e.g., independence, responsibility, cooperation with others). In addition, because mothers and children are joint