The Effects of Social Information on Recommendation Trust and Moderating Effect of Product Involvement
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This study aims to identify which social information have significant influence on the improvement of recommendation trust and how these effects can be different according to the product involvement level. Based on the relevant literature reviews, this study posits four characteristics of recommendation trust, which are closeness, similarity, sincerity, and reputation, and established a research model for the relationship between social information and recommendation trust. And we found a moderating effect of product involvement on the relationship between social information and recommendation trust. 205 trust relationships(links) from 55 respondents of Google Docs. survey data have been collected and tested using multiple regression and hierarchical regression analysis. The results of our hypotheses testing are summarized as follows. Firstly, four social information characteristics of closeness, similarity, sincerity, and reputation have a significantly positive effect on recommendation trust. Secondly, a moderating effect of product involvement between recommendation trust and antecedents (e.g., closeness and reputation) of social information is significant. From the results, we provide theoretical and managerial implications, and suggestions for further research.
Abstract
This study aims to identify which social information have significant influence on the improvement of recommendation trust and how these effects can be different according to the product involvement level. Based on the relevant literature reviews, this study posits four characteristics of recommendation trust, which are closeness, similarity, sincerity, and reputation, and established a research model for the relationship between social information and recommendation trust. And we found a moderating effect of product involvement on the relationship between social information and recommendation trust. 205 trust relationships(links) from 55 respondents of Google Docs. survey data have been collected and tested using multiple regression and hierarchical regression analysis. The results of our hypotheses testing are summarized as follows. Firstly, four social information characteristics of closeness, similarity, sincerity, and reputation have a significantly positive effect on recommendation trust. Secondly, a moderating effect of product involvement between recommendation trust and antecedents (e.g., closeness and reputation) of social information is significant. From the results, we provide theoretical and managerial implications, and suggestions for further research.
참고문헌 (33)
- Arazy, O., "Improving Social Recommender Systems", Journal of IT Professional, 11(4), pp.31~37 (2009)
- Avesani, P., "Moleskiing : A Trust-Aware Decentralized Recommender System", Proceedings of the First Workshop on Friend of a Friend Social Networking and the Semantic Web (2004)
- Baron, R. M., "The Moderator-Mediator Variable Distinction in Social Psychological Research : Conceptual, Strategic and Statistical Considerations", Journal of Personality and Social Psychology, 51, pp.1173~1182 (1986)
- Bonhard, P., "Knowing me, knowing you-Using profiles and social networking to improve recommender systems", BT Technology Journal, 24(3), pp.84~98 (2006)
- Butler, J. K. Jr., "Toward Understanding and Measuring Conditions of Trust : Evolution of a Conditions of Trust Inventory", Journal of Management, 17(3), pp.643~663 (1991)
- Butler, J. K. Jr., "A Behavioral Decision Theory Approach to Modeling Dyadic Trust in Superiors and Subordinates", Psychological reports, 55(1), pp.19~28 (1984)
- Carrer-Neto, W., "Social Knowledge-based Recommender System : Application to the Movies Domain", Expert Systems with Applications, 39(12), pp.10990~11000 (2012)
- Constantinides, E., "Effects of Web Experience on Consumer Choice : A Multicultural Approach", Internet Research, 20(2), pp.188~209 (2010)
- Edelman, R., "Edelman Trust Barometer:Executive Summary" (2011), Edelman Co.
- Ferreira, A. G., "Product Involvement, Price Perceptions, and Brand Loyalty", Journal of Product & Brand Management, 24(4), pp.349~364 (2015)
- Gilly, M., "A Dyadic Study of Interpersonal Information Search", Journal of the Academy of Marketing Science, 26, pp.83~100 (1998)
- Golbeck, J., "Generating Predictive Movie Recommendations from Trust in Social Networks", Proceedings of the Fourth International Conference on Trust Management (2006)
- Granovetter, M. S., "The Strength of Weak Ties", American Journal of Sociology, 78(6), pp.1360~1380 (1973)
- Griffin, K., "The Contribution of Studies of Source Credibility to a Theory of Interpersonal Trust in the Communication Process", Psychological Bulletin, 68(2), pp.104~120 (1967)
- Gutierrez, S. S. M., "Product and Channel-Related Risk and Involvement in Online Contexts", Electronic Commerce Research and Applications, 9(3), pp.263~273 (2010)
- Hong, I. B., "Understanding the Consumer's Online Merchant Selection Process : The Roles of Product Involvement, Perceived Risk, and Trust Expectation", International Journal of Information Management, 35(3), pp.322~336 (2015)
- Iacobucci, D., "Toward an Encompassing Theory of Business Marketing Relationships(BMRS)and Interpersonal Commercial Relationships(ICRS) : An Empirical Generalization", Journal of Interactive Marketing, 13(3), pp.13~33 (1999)
- Kim, H. N., "Collaborative User Modeling with User-Generated Tags for Social Recommender Systems", Expert Systems with Applications, 38(7), pp.8488~8496 (2011)
- Kelley, H. H., "Analyzing Close Relationships", pp.20~67 (1983), W. H. Freeman and Company
- Larzelere, R. E., "The Dyadic Trust Scale: Toward Understanding Interpersonal Trust in Close Relationships", Journal of Marriage and the Family, pp.595~604 (1980)
- Lee, D., "Interpersonal Trust and Emotion as Antecedents of Cooperation : Evidence From Korea", Journal of Applied Social Psychology, 41(7), pp.1603~1631 (2011)
- Levin, Z, D., "The Strength of Weak Ties You Can Trust : The Mediating Role of Trust in Effective Knowledge Transfer", Management Science, 50(11), pp.1477~1490 (2004)
- Lewicki, R. J., "Trust in Relationships: A Model of Development and Decline, Conflict, Cooperation, and Justice" (1995), Jossey-Bass Publishers
- Li, Y. M., "TREPPS : A Trust-based Recommender System for Peer Production Services", Expert Systems with Applications, 36(2), pp.3263~3277 (2009)
- Mayer, R. C., "An Integrative Model of Organizational Trust", Academy of Management Review, 20(3), pp.709~734 (1995)
- Neto, W. L. M., "Insights on Social Recommender System", ACM Recommender Systems 2012International Workshop on Recommendation Utility Evaluation (2012)
- Okamoto, K., "Ranking of Closeness Centrality for Large-Scale Social Networks", Lecture Notes in Computer Science, 5059, pp.186~195 (2008)
- Resnick, P., "GroupLens : An Open Architecture for Collaborative Filtering of Netnews", Proceedings of ACM 1994 Conference on Computer Supported Cooperative Work, pp.175~186 (1994)
- Ricci, F., "Recommender Systems Handbook" (2011)
- Shardanand, U., "Social Information Filtering : Algorithms for Automating"Word of Mouth", Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp.210~217 (1995)
- Sinha, R. R., "Comparing Recommendations Made by Online Systems and Friends", DELOS Workshop: Personalisation and Recommender Systems in Digital Libraries (2001)
- Whitener, E. M., "Managers as Initiators of Trust : An Exchange Relationship Framework for Understanding Managerial Trustworthy Behavior", Academy of Management Review, 23(3), pp.513~530 (1998)
- Zheng, N., "A Recommender System based on Tag and Time Information for Social Tagging Systems", Expert Systems with Applications, 38(4), pp.4575~4587 (2011)