Author

  • Fereshteh Ghazizadeh Ehsaei

    • University Technology Malaysia (UTM), Johor, Malaysia
    • Malaysia
  • Ab. Razak Che Hussin

    • University Technology Malaysia (UTM), Johor, Malaysia
    • Malaysia

Abstract

In an online environment, the aim of reputation systems is to let parties rate each other and to help consumers in deciding whether to transact with a given party. In current reputation systems for e-commerce, users have to trust unreliable information sources and anonymous people. As a result, users are not only hesitant to trust online seller but also to reputation systems. Therefore, there is a need to improve current reputation systems by allowing users to make buying decision based on reliable source of information. This paper proposes a new approach of sharing knowledge and experience in reputation systems by utilizing social interactions. This study examines the potentials of integrating social relations information in reputation systems by proposing a model of acceptance of feedbacks in reputation systems.

Keywords

References

  • Arazy, O., kumar, N. & shapira, B. (2010). a theory of driven design framework for social recommendation systems. journal of the associaltion for information systems, 11(9).
  • Ba, S. & Pavlou, P. A. (2002). Evidence of the Effect of Trust Building Technology in Electronic Markets: Price Premiums and Buyer Behavior. MIS Quarterly, 26(3), 243-268.
  • Birnbaum, M. H. & Stegner, S. E. (1979). Source Credibility in Social Judgment: Bias, Expertise, and the Judge’s Point of View. Journal of Personality and Social Psychology, 37(48-74).
  • Bolton, G., Loebbecke, C. & Ockenfels, A. ( 2008). How Social Reputation Networks Interact with Competition in Anonymous Online Trading: An Experimental Study. CESifo Working Paper Series No. 2270. Available at SSRN : http://ssrn.com/abstract=1114755
  • Brown, J., Broderick, A. J. & Lee, N. (2007). Word of mouth communication within online communities: conceptualizing the online Social network. Journal Of Interactive Marketing, 21(3).
  • Brown, J. & Reingen, P. (1987). Social Ties and Word- of-Mouth Referral Behavior. Journal of Consumer Research in Consumer Behaviour, 14(350-62).
  • Bruyn, A. D. & Lilien, G. L. (2008). A multi-stage model of word-of-mouth influence through viral marketing. Intern. J. of Research in Marketing, 25, 151-163.
  • Buda, R. (2003). he Interactive Effect of Message Framing, Presentation Order, and Source Credibility on Recruitment Practices. International Journal of Management, 20(156-163).
  • Chang, E. J., Hussain , F. K. & Dillon, T. S. (2005). Fuzzy Nature of Trust and Dynamic Trust Modelling in Service Oriented Environments . Paper presented at the ACM, SWS’05, Fairfax.
  • Chang., E., Dillon., T. & Hussain, F. K. (2005). Trust and reputation for service -oriented environments: WILEY.
  • Cheung, M. Y., LUO, C., SIA, C. L. & Chen, H. (2007a). How do People Evaluate Electronic Word-Of-Mouth? Informational and Normative Based Determinants of Perceived Credibility of Online Consumer Recommendations in China. Paper presented at the PACIS 2007 Proceedings
  • Cheung, M. Y., Luo, C., Sia, C. L. & Chen, H. (2007b). How do people evaluate electronic Word-of-Mouth? Informational and normative based determinants of perceived credibility of online consumer recommendations in China.
  • Cho, J., Kwon, K. & Park, Y. (2009). Q-rater: A collaborative reputation system based on source credibility theory. Expert Systems with Applications, 36(2, Part 2), 3751-3760.
  • Cruz, C. C. P., Motta, C. L. R., Santoro, F. M. & Elia, M. (2009). Applying Reputation Mechanisms in Communities of Practice: A Case Study. Journal of Universal Computer Science, 15(9).
  • Dellarocas, C. (2003). The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms. Management Science, 49(10), 1407-1424.
  • Eagly, A. H. (1993). The Psychology of Attitudes. Fort Worth, TX: Harcourt Brace Jovanovich.
  • Frenzen, J. K. (1990). Purchasing behavior in embedded markets. 17 , 1(12).
  • Fuller, M., Serva, M. & Benamati, J. (2007). Seeing Is Believing: The Transitory Influence of Reputation Information on E-Commerce Trust and Decision Making. Decision Sciences, 38(4), 675-699.
  • Gilly, M. C., Graham, J. L., Wolfinbarger, M. F. & Yale, L. J. (1998). A dyadic study of interpersonal information search. Journal of the Academy of Marketing Science, 26(2), 83-100.
  • Granovetter, M. (1973). The strenght of weak ties. American journal of sociology, 78(6).
  • Granovetter, M. (1982). The Strength of Weak Ties: A Network Theory Revisited. Social Structure and Network Analysis, Beverly Hills, CA: Sage, 105-130.
  • Gregg, D. G. & Scott, J. E. (2006). The Role of Reputation Systems in Reducing On-Line Auction Fraud. International Journal of Electronic Commerce, 10(3), 95-120.
  • Gutowska, A. & Sloane, A. (2009). Evaluation Of Reputation Metric For The B2c E-Commerce Reputation System. Paper presented at the WEBIST 2009 - 5th International Conference on Web Information Systems and Technologies.
  • Gutowska, A. & Sloane, A. (2010). Modelling the B2C Marketplace: Evaluation of a Reputation Metric for e- Commerce. Paper presented at the WEBIST 2009
  • Hovland, C. & Weiss, W. (1951). The Influence of Source Credibility on Communication Effectiveness. Public Opinion Quarterly, 15(4), 635-650.
  • Huang, Q. R., Davison, Y. & Hefu, L. (2009). An Exploratory Study on Buyers’ Participation in Reputation Systems. Paper presented at the Pacific Asia Conference on Information Systems (PACIS).
  • Jøsang, A., Ismail, R. & Boyd, C. (2007). A survey of trust and reputation systems for online service provision. decision support systems, 43(2), 618-644.
  • Jøsang, A. & Pope, S. (2005). Semantic Constraints for Trust Transitivity. Paper presented at the Second AsiaPacific Conference on Conceptual Modelling (APCCM2005).
  • Josang, A., Roslan, I. & Boyd, C. (2007). A Survey of Trust and Reputation Systems for Online Service Provision. . Decision Support Systems, 43(2), 618-644.
  • Kim, D. j., Sivasailam, N. & Rao, H. R. (2004). information insurance in B2C websites for information goods/services. electronic markets, 14(4), 344-359.
  • Komiak, S. (2010). T he Effects of Perceived Information Quality and Perceived System Quality on Trust and Adoption of Online Reputation Systems . Paper presented at the AMCIS 2010 Proceedings.
  • Li, D., Browne, G. J. & Chau, P. Y. K. (2006). An Empirical Investigation of Web Site Use Using a CommitmentBased Model. Decision Sciences, 37(427- 444).
  • Lim, K. H., Sia, C. L., Lee, M. K. O. & Benbasat, I. (2006). How Do I Trust You Online, and If So, Will I Buy?: An Empirical Study of Two Trust Building Strategies. Journal of Management Information Systems, 23(2), 233-266.
  • Ling-Liu, M. M. (2012). Systematic analysis of centralized online reputation systems. Decision Support Systems.
  • Lu, Y., Zhao, L. & Wang, B. (2008). From virtual community members to C2C e-commerce buyers: Trust in virtual communities and its effect on consumers' purchase intention. Electronic Commerce Research and Applications, In Press, Corrected Proof.
  • Luca, A., Luca, C. & Cremonini, M. (2011). Modifying Trust Dynamics through Cooperation and Defection in Evolving Social Networks. In Proceedings of the 4th International Conference on Trust and Trustworthy Computing (TRUST 2011), 6740, 131-145,.
  • Maheswaran, M., Hon-Cheong, T. & Ghunaim, A. (2007). Towards a Gravity-Based Trust Model for Social Networking Systems . Paper presented at the Distributed Computing Systems Workshops, 2007. ICDCSW '07. 27th International Conference on.
  • Marsden, P. & Campbell, K. (1984). Measuring Tie Strength. Social Forces, 63(2), 482–501.
  • Mayer, D. & Schoorman, E. (1995). An Integrative Model of Organizational Trust. Academy of Management Review, 20(3), 709-734.
  • Mayer, R., Davis, J. & Schoorman, D. (1995). An Integrative Model of Organizational Trust. The Academy of Management Review, 20(3), 709-734.
  • McCroskey, L. L., McCroskey, J. C. & Richmond, V. P. (2006). Analysis and improvement of the measurement of interpersonal attraction and homophily. Communication Quarterly, 54(1-31).
  • McDonald, C. G. & Slawson-Jr., V. (2002). Reputation in an Internet Auction Market. Economic inquiry, 40(633650).
  • McPherson, M., Smith-Lovin, L. & Cook, J. M. (2001). Birds of a feather:Homophily in social networks. Annual Review of Sociology, 27, 415-444.
  • Money, R. B., Gilly, M. C. & Graham, J. L. (1998). Explorations of National Culture and Word-of Mouth Referral Behavior in the Purchase of Industrial Services in the United States and Japan. Journal of Marketing, 62, 76–87.
  • Perloff, R. M. (1993). The Dynamics of Persuasion. Lawrence, NJ: Erlbaum Associates.
  • Petter, S., Straub, D. & Rai, A. (2007). Specifying Formative Constructs In Information Systems Research1. MIS Quarterly, 31(4).
  • Resnick, P., Zeckhauser, R., Friedman, E. & Kuwabara, K. (2000). Reputation Systems: Facilitating Trust in Internet Interactions.
  • Rogers, E. (Ed.). (1995). Diffusion of Innovations (4th Ed).
  • Ruef, M., Aldrich, H. E. & Carter, N. M. (2003). The Structure of Founding Teams: Homophily, Strong Ties and Isolation Among U.S. Entrepreneurs. American Sociological Review, 68(195-222).
  • Sinha, R., Sinha, R. & Swearingen, K. (2001). Comparing Recommendations Made by Online Systems and Friend. Paper presented at the In Proceedings of the DELOS-NSF Workshop on Personalization and Recommender Systems in Digital Libraries
  • Smith, S. M. & Sivakumar, K. (2005). Online peer and editorial recommendations, trust, and choice in virtual markets. Journal Of Interactive Marketing, 19(3).
  • Subramani, M. R. & Rajagopalan, B. (2003). knowledge-sharing and influence in online social networks via viral marketing. communication of the ACM, 46(12), 300-307.
  • Sussman, S. W. & Siegal, W. S. (2003a). Informational Influence in Organizations: An Integrated Approach to Knowledge Adoption. Info. Sys. Research, 14(1), 47-65.
  • Sussman, S. W. & Siegal, W. S. (2003b). Informational Influence in Organizations: An Integrated Approach to Knowledge Adoption. Information Systems Research, 14(1), 47-65.
  • Ugur, K. & Jennifer, G. (2007). Sunny: a new algorithm for trust inference in social networks using probabilistic confidence models. Paper presented at the Proceedings of the 22nd national conference on Artificial intelligence, 2.
  • Vannoy, S. A., Nath, A. K. & Iyer, L. (2008). The Role of Trust in the Intention to Use Feedback from Reputation Systems . Paper presented at the AMCIS 2008 Proceedings.
  • Walker, J., Wasserman, S. & Wellman, B. (1994). Statistical Models for Social Support Networks. In Advances in Social Network Analysis (Eds.). Thousand Oaks, CA: Sage.
  • Wolfinbarger, M. F. & Gilly, M. C. (1993). The encoding and decoding of gift symbolism. Working paper : University of California at Irvine .
  • Young-Ae, K. & Jaideep, S. (2007). Impact of social influence in e-commerce decision making. Paper presented at the Proceedings of the ninth international conference on Electronic commerce.
  • Zhai, D. & Pan, H. (2008). A Social Network-Based Trust Model for E-Commerce . Paper presented at the Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on.
  • Zucker, L. G. (1986). Production of trust: Institutional sources of economic structure. Research in Organizational Behavior, 8(2).

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How to Cite

Ghazizadeh Ehsaei, F., & Che Hussin, A. R. (2012). Acceptance of Feedbacks in Reputation Systems: The Role of Online Social Interactions. Information Management and Business Review, 4(7), 391-401. https://doi.org/10.22610/imbr.v4i7.993

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Published

2012-07-15

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