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The interaction effects of information cascades, word of mouth and recommendation systems on online reading behavior: an empirical investigation

Author

Listed:
  • Qihua Liu

    (Jiangxi University of Finance and Economics)

  • Xiaoyu Zhang

    (Jiangxi University of Finance and Economics)

  • Liyi Zhang

    (Wuhan University)

  • Yang Zhao

    (Wuhan University)

Abstract

While ranking systems, electronic word of mouth (eWOM) channels and recommendation systems might appear as three separate tools that influence consumer choice, consumers at online reading platforms are often exposed to all three simultaneously during a searching session of e-books. This study conducts an empirical analysis to examine the interaction effects of these three decision-supporting tools on online reading behavior. To do so, we collect a 25-week panel data set on Yuedu.163.com, which is one of the earliest online reading platforms in China. Our results indicate that informational cascades are particularly prominent on the online reading market. Under the influence of informational cascades, eWOM volume and valence have no impact on the clicks of e-books with high rankings, but have positive impact on the clicks of e-books with low rankings. Recommendation strength has a positive impact on popular e-books clicks, but has no impact on the clicks of less popular e-books. Moreover, we find that eWOM valence and recommendation strength have a substitute relationship in affecting the clicks of e-books with high rankings. However, eWOM and recommendation system have a complementary relationship in affecting the clicks of less popular e-books. To our best knowledge, this paper is the first to investigate the interaction effects of information cascades, eWOM and recommendation systems on online user behavior. Our findings provide important theoretical contributions and managerial implications.

Suggested Citation

  • Qihua Liu & Xiaoyu Zhang & Liyi Zhang & Yang Zhao, 2019. "The interaction effects of information cascades, word of mouth and recommendation systems on online reading behavior: an empirical investigation," Electronic Commerce Research, Springer, vol. 19(3), pages 521-547, September.
    • Handle: RePEc:spr:elcore:v:19:y:2019:i:3:d:10.1007_s10660-018-9312-0
    DOI: 10.1007/s10660-018-9312-0
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    Cited by:

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    5. Blasco-Arcas, Lorena & Lee, Hsin-Hsuan Meg & Kastanakis, Minas N. & Alcañiz, Mariano & Reyes-Menendez, Ana, 2022. "The role of consumer data in marketing: A research agenda," Journal of Business Research, Elsevier, vol. 146(C), pages 436-452.
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