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The influence of information cascades on online purchase behaviors of search and experience products

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  • Qihua Liu

    (Jiangxi University of Finance and Economics)

  • Shan Huang

    (Wuhan University)

  • Liyi Zhang

    (Wuhan University)

Abstract

Online users usually observe or refer to others’ behaviors and discount their own information when purchasing products online. This research employed a fixed-effect regression model to elucidate how information cascades could influence online purchase behaviors and how they moderated the influence of online word-of-mouth and product prices. To uncover the underlying mechanisms behind informational cascades, we compare search products and experience products. In particular, we utilize publicly available data from a B2C e-commerce site in China, i.e., Tmall.com. Our results indicate that online users’ choice of products was heavily driven by changes in product rankings after controlling for cumulative sales, online user reviews and product price, as predicted by informational cascades theory. Due to the information cascades effect, review volume had no impact on online users’ choice of products with high rankings, whereas it did exert a significant positive impact on consumer purchase decisions of products with low rankings. User rating had no impact on online users’ purchase decisions. Product price had a significant and negative impact for products with high rankings, but had a significant and positive influence on users’ choice for products with low rankings. Moreover, information cascades were more prominent for experience goods than for search goods.

Suggested Citation

  • Qihua Liu & Shan Huang & Liyi Zhang, 2016. "The influence of information cascades on online purchase behaviors of search and experience products," Electronic Commerce Research, Springer, vol. 16(4), pages 553-580, December.
    • Handle: RePEc:spr:elcore:v:16:y:2016:i:4:d:10.1007_s10660-016-9220-0
    DOI: 10.1007/s10660-016-9220-0
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    4. 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.
    5. Huan Liu & Qiang Chen & Richard Evans, 2022. "How Official Social Media Affected the Infodemic among Adults during the First Wave of COVID-19 in China," IJERPH, MDPI, vol. 19(11), pages 1-18, May.
    6. Yang, Xiao & Liu, Ying & Dong, Jichang & Li, Sirui, 2023. "Impact of streamers’ characteristics on sales performance of search and experience products: Evidence from Douyin," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
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    8. Lu, Jian & Su, Xiang & Diao, Yajing & Wang, Nianxin & Zhou, Bin, 2021. "Does online observational learning matter? Empirical evidence from panel data," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    9. Cuixia Jiang & Jun Zhu & Qifa Xu, 2022. "Dissecting click farming on the Taobao platform in China via PU learning and weighted logistic regression," Electronic Commerce Research, Springer, vol. 22(1), pages 157-176, March.
    10. Plotkina, Daria & Munzel, Andreas & Pallud, Jessie, 2020. "Illusions of truth—Experimental insights into human and algorithmic detections of fake online reviews," Journal of Business Research, Elsevier, vol. 109(C), pages 511-523.
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