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Timing of Adaptive Web Personalization and Its Effects on Online Consumer Behavior

Author

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  • Shuk Ying Ho

    (School of Accounting and Business Information Systems, College of Business and Economics, The Australian National University, Canberra, ACT 0200, Australia)

  • David Bodoff

    (Graduate School of Management, University of Haifa, Haifa 31905, Israel)

  • Kar Yan Tam

    (Department of Information Systems, Business Statistics, and Operations Management, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong)

Abstract

Web personalization allows online merchants to customize Web content to serve the needs of individual customers. Using data mining and clickstream analysis techniques, merchants can now adapt website content in real time to capture the current preferences of online customers. Though the ability to offer adaptive content in real time opens up new business opportunities for online merchants, it also raises questions of timing. One question is when to present personalized content to consumers. Consumers prefer early presentation that eases their selection process, whereas adaptive systems can make better personalized content if they are allowed to collect more consumers' clicks over time. A review of personalization research confirms that little work has been done on these timing issues in the context of personalized services. The current study aims to fill that gap. Drawing on consumer search theory, we develop hypotheses about consumer responses to differences in presentation timing and recommendation type and the interaction between the two. The findings establish that quality improves over the course of an online session but the probability of considering and accepting a given recommendation diminishes over the course of the session. These effects are also shown to interact with consumer expertise , providing insights on the interplay between the different design elements of a personalization strategy.

Suggested Citation

  • Shuk Ying Ho & David Bodoff & Kar Yan Tam, 2011. "Timing of Adaptive Web Personalization and Its Effects on Online Consumer Behavior," Information Systems Research, INFORMS, vol. 22(3), pages 660-679, September.
    • Handle: RePEc:inm:orisre:v:22:y:2011:i:3:p:660-679
    DOI: 10.1287/isre.1090.0262
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    11. Sriram Thirumalai & Kingshuk K. Sinha, 2013. "To Personalize or Not to Personalize Online Purchase Interactions: Implications of Self-Selection by Retailers," Information Systems Research, INFORMS, vol. 24(3), pages 683-708, September.
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    13. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2019. "Technology in the 21st century: New challenges and opportunities," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 321-335.
    14. Johannes Klumpe & Oliver Francis Koch & Alexander Benlian, 2020. "How pull vs. push information delivery and social proof affect information disclosure in location based services," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(3), pages 569-586, September.
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