• Title/Summary/Keyword: Hierarchical Confirmatory Factor Analysis

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The Effect of Social Network on Information Sharing in Franchise System (프랜차이즈시스템의 사회연결망 특성이 정보공유에 미치는 영향)

  • Yun, Han-Sung;Bae, Sang-Wook;Noh, Jung-Koo
    • Journal of Distribution Research
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    • v.16 no.2
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    • pp.95-118
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    • 2011

  • The purpose of this study is as follows. First, we investigate empirically the effects of social network properties such as social network density and centrality of a franchisee on its information sharing with various subjects such as the franchisor and other franchisees in the franchise system. Second, we examine exploratively if tie strength between a franchisee and its franchisor plays a moderating role on the relationship between social network properties and information sharing. The study model was established as shown in

    . We gathered 200 data from franchisees in Busan through a questionnaire survey and used 189 data for our purpose. To improve the quality of data, we selected respondents from the franchisees' owners or managers that had contacted often with their franchisor and other franchisees in the franchise system. Our data analysis began with reliability analysis, exploratory and confirmatory factor analysis, on the multi-item measures of social network density, social network centrality, tie strength, information sharing and control variables such as shared goals and ownership to assess the reliability and validity of those measures. The results were shown that the presented values satisfied the general criteria for reliability and validity. We tested our hypotheses using a hierarchical multiple regression analysis in four steps. Model 1 regressed the dependent variable(information sharing) only on control variables(shared goals, ownership). Model 2 added main effect variables(social network density, social network centrality) in Model 1. Model 3 added a moderating variable(tie strength) in Model 2. Finally, Model 4 added interaction terms between the main variables and the moderating variable in Model 3. We used a mean-centering method for the main variables and the moderating variable to minimize the multicollinearity problem due to the interaction terms in Model 4. Two important empirical findings emerge from this study. In other words, the effects of social network properties and tie strength on a franchisee's information sharing depend on subject types such as the franchisor and other franchisees in franchise system. First, social network centrality, tie strength, the interaction between social network density and tie strength and the interaction between social network centrality and tie strength all affect significantly a franchisee's information sharing with its franchisor. By the way, the interaction between social network centrality and tie strength has a negative effect on its information sharing while the interaction of social network density and tie strength has a positive effect on its information sharing. Second, both social network centrality affects significantly and directly a franchisee's information sharing with other franchisees in the franchise system. However, there does not exist the moderating role of tie strength in the second case. Finally, we suggest the implications of our findings and some avenues for future research.

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