Journal of the Korean Operations Research and Management Science Society (한국경영과학회지)

The Korean Operations Research and Management Science Society (한국경영과학회)
권호 표지

Effects of Product Recommendations on Customer Behavior in e-Commerce : An Empirical Analysis of Online Bookstore Clickstream Data

클릭스트림 데이터를 활용한 전자상거래에서 상품추천이 고객 행동에 미치는 영향 분석

  • Published : 2008.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

Studies of recommender systems have focused on improving their performance in terms of error rates between the actual and predicted preference values. Also, many studies have been conducted to investigate the relationships between customer information processing and the characteristics of recommender systems via surveys and web-based experiments. However, the actual impact of recommendation on product pages for customer browsing behavior and decision-making in the commercial environment has not, to the best of our knowledge, been investigated with actual clickstream data. The principal objective of this research is to assess the effects of product recommendation on customer behavior in e-Commerce, using actual clickstream data. For this purpose, we utilized an online bookstore's clickstream data prior to and after the web site renovation of the store. We compared the recommendation effects on customer behavior with the data. From these comparisons, we determined that the relevant recommendations in product pages have positive relationships with the acquisition of customer attention and elaboration. Additionally, the placing of recommended items in shopping cart is positively related to suggesting the relevant recommendations. However, the frequencies at which the recommended items were purchased did not differ prior to and after the renovation of the site.

Keywords

References

  1. Adomavicius, G. and A. Tuzhilin, "Personalization technologies：a process-oriented perspective," Communication of the ACM, Vol.48, No.10(2005), pp.83-90.
  2. Ansari, A., S. Essegaier, and R. Kohli, "Internet Recommendation Systems," Journal of Marketing Research, Vol.37, No.3 (2000), pp.363-375. https://doi.org/10.1509/jmkr.37.3.363.18779
  3. Awad, N.F., J.L. Jones, and J. Zhang, "Does Search Matter? Using Online Clickstream Data to Examine the Relationship Between Online Search and Purchase Behavior," Proceedings of Twenty-Seventh International Conference on Information Systems, Milwaukee, 2006, pp.915-926.
  4. Awad, N.F. and M.S. Krishan, "The Personalization Privacy Paradox：An Empirical Evaluation of Information Transparancy and The Willingness to be Profiled Online for Personalization," MIS Quarterly, Vol. 30, No.1(2006), pp.13-28. https://doi.org/10.2307/25148715
  5. Balabanovic, M. and Y. Shoham, "Fab： Content-based, Collaborative recommendation," Communication of the ACM, Vol. 40, No.3(1997), pp.66-72.
  6. Bodapati, A.V., "Recommendation Systems with Purchase Data," Journal of Marketing Research, Vol.14(2008), pp.77-93.
  7. Breese, J.S., D. Heckerman, and C. Kadie, "Empirical Analysis of Predictive Algorithms for Collaborative Filtering," Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, USA, 1998.
  8. Bucklin, R.E., J.M. Lattin, A. Ansari, S. Gupta, D. Bell, E. Coupley, J.D.C. Little, C. Mela, A. Montgomery, and J. Steckel, "Choice and the Internet：From Clickstream to Research Stream," Marketing Letters, Vol.13, No.3(2002), pp.245-258. https://doi.org/10.1023/A:1020231107662
  9. Cho, Y.B., Y.H. Cho, and S.H. Kim, "Mining changes in customer buying behavior for collaborative recommendations," Expert Systems with Applications, Vol.28, No.2(2005), pp.359-369. https://doi.org/10.1016/j.eswa.2004.10.015
  10. Claypool, M., A. Gokhale, T. Miranda, P. Murnikov, D. Netes, and M. Sartin, Combining Content-Based and Collaborative Filters in an Online Newspaper, Worcester Polytechnic Institute, 1999.
  11. Danaher, P.J., G.W. Mullarkey, and S. Essegaier, "Factors affecting Web site visit duration：A cross-domain analysis," Journal Of Marketing Research, Vol.43, No. 2(2006), pp.182-194. https://doi.org/10.1509/jmkr.43.2.182
  12. Herlocker, J.L., J.A. Konstan, L.G. Terveen, and J.T. Riedl, "Evaluating collaborative filtering recommender systems," ACM Transactions on Information Systems, Vol.22, No.1(2004), pp.5-53. https://doi.org/10.1145/963770.963772
  13. Ho, S.Y. and S.H. Kwok, "The Attraction of Personalized Service for Users in Mobile Commerce：An Empirical Study," ACM SIGecom Exchanges, Vol.3, No.4(2003), pp. 10-18. https://doi.org/10.1145/844351.844354
  14. Kim, B.M., Q. Li, C.S. Park, S.G. Kim, and J.Y. Kim, "A new approach for combining content-based and collaborative filters," Journal of Intelligent Information Systems, Vol.27, No.1(2006), pp.79-91. https://doi.org/10.1007/s10844-006-8771-2
  15. Kim, C.Y., J.K. Lee, Y.H. Cho, and D.H. Kim, "Viscors：A Visual-Content Recommender for the Mobile Web," IEEE Intelligent Systems, Vol.19, No.6(2004), pp.32 -39.
  16. Kim, J.K., Y.H. Cho, W.J. Kim, J.R. Kim, and J.H. Suh, "A personalized recommendation procedure for Internet shopping support," Electronic Commerce Research and Applications, Vol.1, No.3-4(2002), pp. 301-313. https://doi.org/10.1016/S1567-4223(02)00022-4
  17. Kim, J.W., B.H. Lee, M.J. Shaw, H.L. Chang, and M. Nelson, "Application of decision- tree induction techniques to personalized advertisements on Internet storefronts," International Journal of Electronic Commerce, Vol.5, No.3(2001), pp.45-62. https://doi.org/10.1080/10864415.2001.11044215
  18. Konstan, J.A., B.N. Miller, D. Maltz, J. L. Herlocker, L.R. Gordon, and J. Riedl, "GroupLens：Applying collaborative filtering to USENET news," Communication of the ACM, Vol.40, No.3(1997), pp.77-87. https://doi.org/10.1145/245108.245126
  19. Kumar, N. and I. Benbasat, "The Influence of Recommendations and Consumer Reviews on Evaluations of Websites," Information Systems Research, Vol.17, No.4 (2006), pp.425-439. https://doi.org/10.1287/isre.1060.0107
  20. Lee, J., M. Podlaseck, E. Schonberg, and R. Hoch, "Visualization and Analysis of Clickstream Data of Online Stores for Understanding Web Merchandising," Data Mining and Knowledge Discovery, Vol.5 (2001), pp.59-84. https://doi.org/10.1023/A:1009843912662
  21. Liang, T.-P., H.-J. Lai, and Y.-C. Ku, "Personalized Content Recommendation and User Satisfaction：Theoretical Synthesis and Empirical Findings," Journal of Management Information Systems, Vol.23, No. 3(2007), pp.45-70. https://doi.org/10.2753/MIS0742-1222230303
  22. Linden, G., B. Smith, and J. York, "Amazon. com Recommendations：Item-to-item Collaborative Filtering," IEEE Internet Computing, Vol.7, No.3(2003), pp.76-80. https://doi.org/10.1109/MIC.2003.1167344
  23. Mobasher, B., H. Dai, T. Luo, and M. Nakagawa, "Effective Personalization Based on Association Rule Discovery from Web Usage Data," Proceedings of WIDM 2001, Atlanta, GA, USA, 2001, pp.9-15.
  24. Mobasher, B., H. Dai, T. Luo, and M. Nakagawa, "Improving the Effectiveness of Collaborative Filtering on Anonymous Web Usage Data," Proceedings of Workshop Intelligent Techniques for Web Personalization, IJCAI-2001, Seattle Washington, 2001, pp.53-60.
  25. Moe, W.W., "Buying, Searching, or Browsing： Differentiating Between Online Shoppers Using In-Store Navigational Clickstream," Journal of Consumer Psychology, Vol.13, No.1-2(2003), pp.29-39. https://doi.org/10.1207/S15327663JCP13-1&2_03
  26. Moe, W.W. and P.S. Fader, "Capturing Evolving Visit Behavior in Clickstream Data," Journal of Interactive Marketing, Vol.18, No.1(2004), pp.5-19.
  27. Moe, W.W. and P.S. Fader, "Dynamic Conversion Behavior at E-Commerce Sites," Management Science, Vol.50, No.3(2004), pp.326-335. https://doi.org/10.1287/mnsc.1040.0153
  28. Montgomery, A.L., "Applying Quantitative Marketing Techniques to the Internet," Interfaces, Vol.31, No.2(2001), pp.90-108. https://doi.org/10.1287/inte.31.2.90.10630
  29. Montgomery, A.L., S. Li, K. Srinivasan, and J.C. Liechty, "Modeling Online Browsing and Path Analysis Using Clickstream Data," Marketing Science, Vol.23, No.4(2004), pp.579-595. https://doi.org/10.1287/mksc.1040.0073
  30. Nakamoto, R., S. Nakajima, J. Miyazaki, and S. Uemura, "Tag-Based Contextual Collaborative Filtering," Proceedings of DEWS2007, Hiroshima, Japan, 2007, pp.25 -30.
  31. Park, Y.-H. and P.S. Fader, "Modeling Browsing Behavior at Multiple Websites," Marketing Science, Vol.23, No.3(2004), pp.280-303. https://doi.org/10.1287/mksc.1040.0050
  32. Resnick, P., N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl, "GroupLens：an open architecture for collaborative filtering of netnews," Proceedings of Proceedings of the 1994 ACM conference on Computer supported cooperative work Chapel Hill, North Carolina, United States 1994, pp.175 -186.
  33. Resnick, P. and H.R. Varian, "Recommender systems," Communications of the ACM, Vol.40, No.3(1997), pp.56-58
  34. Rojsattarat, E. and N. Soonthornphisaj, "Hybrid Recommendation：Combining Content- Based Prediction and Collaborative Filtering," Proceedings of IDEAL 2003, LNCS 2690, 2003, pp.337-344.
  35. Sarwar, B., G. Karypis, J. Konstan, and J. Riedl, "Item-based collaborative filtering recommendation algorithms," Proceedings of Proceedings of the 10th international conference on World Wide Web, Hong Kong, 2001, pp.285-295.
  36. Schafer, J.B., J. Konstan, and J. Riedl, "Recommender Systems in E-Commerce," Proceedings of E-Commerce, Denver, Colorado, 1999, ACM, pp.158-166.
  37. Schafer, J.B., J.A. Konstan, and J. Riedl, "E-Commerce Recommendation Applications," Data Mining and Knowledge Discovery, Vol.5, No.1-2(2001), pp.115-153. https://doi.org/10.1023/A:1009804230409
  38. Swaminathan, V., "The Impact of Recommendation Agents on Consumer Evaluation and Choice：The Moderating Role of Category Risk, Product Complexity, and Consumer Knowledge," Journal of Consumer Psychology, Vol.13, No.1-2(2003), pp.93-101. https://doi.org/10.1207/S15327663JCP13-1&2_08
  39. Tam, K.Y. and S.Y. Ho, "Web Personalization as a Persuasion Strategy：An Elaboration Likelihood Model Perspective," Information Systems Research, Vol.16, No. 3(2005), pp.271-291. https://doi.org/10.1287/isre.1050.0058
  40. Tam, K.Y. and S.Y. Ho, "Understanding The Impact of Web Personalization on User Information Processing and Decision Outcomes," MIS Quarterly, Vol.30, No.4 (2006), pp.865-890. https://doi.org/10.2307/25148757
  41. Xiao, B. and I. Benbasat, "E-Commerce Product Recommendation Agents：Use, Characteristics, and Impact," MIS Quarterly, Vol.31, No.1(2007), pp.137-209. https://doi.org/10.2307/25148784