Abstract
In this paper, a three-stage recommender support was implied from a user study. The purpose of the user study was to understand how to best utilize different types of social information (e.g., product popularity, user reviews) for facilitating online consumers’ decision-making process in the e-commerce environment. Through both of in-depth tracking users’ objective behavior and qualitative interviewing their reflective thoughts, we have not only refined a traditional two-stage decision process into a more precise three-stage process, but also identified at each stage what information users are inclined to seek for. Based on the study’s results, suggestions were made to related recommender systems about their practical roles in the three-stage framework and how they can more effectively support users’ information needs.
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References
Aciar, S., Zhang, D., Simoff, S., Debenham, J.: Recommender system based on consumer product reviews. In: Proc. WI-IAT 2006, pp. 719–723 (2006)
Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734–749 (2005)
Amatriain, X., Lathia, N., Pujol, J.M., Kwak, H., Oliver, N.: The wisdom of the few: a collaborative filtering approach based on expert opinions from the web. In: Proc. SIGIR 2009, pp. 532–539 (2009)
Chen, L., Pu, P.: Evaluating critiquing-based recommender agents. In: Proc. AAAI 2006, pp. 157–162 (2006)
Engel, J.F., Blackwell, R.D., Miniard, P.W.: Consumer Behavior. Dryden Press, Orlando (1990)
Groh, G., Ehmig, C.: Recommendations in taste related domains: collaborative filtering vs. social filtering. In: Proc. GROUP 2007, pp. 127–136 (2007)
Guy, I., Chen, L., Zhou, M.X.: Workshop on social recommender systems. In: Proc. IUI 2010, pp. 433–434 (2010)
Häubl, G., Trifts, V.: Consumer decision making in online shopping environments: the effects of interactive decision aids. Marketing Science 19(1), 4–21 (2000)
Kim, Y.A., Srivastava, J.: Impact of social influence in e-commerce decision making. In: Proc. ICEC 2007, 293-302 (2007)
Leino, J., Räihä, K.: Case Amazon: ratings and reviews as part of recommendations. In: Proc. RecSys 2007, pp. 137–140. ACM Press, New York (2007)
Mizerski, R.: An attribution explanation of the disproportionate influence of unfavorable information. Journal of Consumer Research 9, 301–310 (1982)
Pang, B., Lee, L.: Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval l 2(1-2), 1–135 (2008)
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Chen, L. (2010). Towards Three-Stage Recommender Support for Online Consumers: Implications from a User Study. In: Chen, L., Triantafillou, P., Suel, T. (eds) Web Information Systems Engineering – WISE 2010. WISE 2010. Lecture Notes in Computer Science, vol 6488. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17616-6_33
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DOI: https://doi.org/10.1007/978-3-642-17616-6_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17615-9
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