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Who will stay with the brand after posting non-5/5 rating of purchase? An empirical study of online consumer repurchase behavior

Author

Listed:
  • Dan Ke

    (Wuhan University)

  • Heci Zhang

    (Wuhan University)

  • Ning Yu

    (Wuhan University)

  • Yanbin Tu

    (Robert Morris University
    Jianghan University)

Abstract

Customer retention has been fully examined in marketing research. It has been noticed that satisfied customers do not always retain and customer churn happens repeatedly in an e-Business context. In this paper, we focus on online consumer repurchase behavior on online business to consumer platforms after posting a non-5/5 rating of the purchased product. The non-5/5 rating can be taken as buyer’s self-claimed non-fully satisfaction on shopping experience. We investigate whether online consumers’ self-claimed non-fully satisfied shopping experience of a brand would attenuate their repurchase intention of the same brand, and further, what factors would impact their repurchase frequency and the time interval to the next purchase of this brand. We applied multinomial logit regression and ordinary least square regressions to Amazon review data to test the research hypotheses. We collected more than 241 thousand review records involving over 182 thousand buyers of Amazon beauty products. 44% of these buyers rated below 5, and 19% out of whom had repurchase records. The empirical results showed that consumers’ past shopping experience and the non-5/5 rating level significantly impact the possibility of repurchase intention; consumers’ emotional stability is associated with their repurchase frequency positively; their relationship proneness to a certain brand shortens the time interval to the next purchase of the brand. Managerial implications and future research directions are discussed last.

Suggested Citation

  • Dan Ke & Heci Zhang & Ning Yu & Yanbin Tu, 2021. "Who will stay with the brand after posting non-5/5 rating of purchase? An empirical study of online consumer repurchase behavior," Information Systems and e-Business Management, Springer, vol. 19(2), pages 405-437, June.
    • Handle: RePEc:spr:infsem:v:19:y:2021:i:2:d:10.1007_s10257-019-00416-9
    DOI: 10.1007/s10257-019-00416-9
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    References listed on IDEAS

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    1. Young Kwark & Jianqing Chen & Srinivasan Raghunathan, 2014. "Online Product Reviews: Implications for Retailers and Competing Manufacturers," Information Systems Research, INFORMS, vol. 25(1), pages 93-110, March.
    2. Kyle B. Murray & Gerald Hubl, 2007. "Explaining Cognitive Lock-In: The Role of Skill-Based Habits of Use in Consumer Choice," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(1), pages 77-88, March.
    3. Kumar, Anil & Luthra, Sunil & Khandelwal, Dinesh Kumar & Mehta, Rajneesh & Chaudhary, Nityanand & Bhatia, Sukhdev, 2017. "Measuring and improving customer retention at authorised automobile workshops after free services," Journal of Retailing and Consumer Services, Elsevier, vol. 39(C), pages 93-102.
    4. Zeelenberg, M. & Pieters, R., 2004. "Beyond valence in customer dissatisfaction : A review and new findings on behavioral responses to regret and disappointment in failed services," Other publications TiSEM 7bfb4aa9-cba7-4786-850d-1, Tilburg University, School of Economics and Management.
    5. Cobb-Clark, Deborah A. & Schurer, Stefanie, 2012. "The stability of big-five personality traits," Economics Letters, Elsevier, vol. 115(1), pages 11-15.
    6. Dezhi Yin & Sabyasachi Mitra & Han Zhang, 2016. "Research Note—When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth," Information Systems Research, INFORMS, vol. 27(1), pages 131-144, March.
    7. Alba, Joseph W & Hutchinson, J Wesley, 1987. "Dimensions of Consumer Expertise," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(4), pages 411-454, March.
    8. Engler, Tobias H. & Winter, Patrick & Schulz, Michael, 2015. "Understanding online product ratings: A customer satisfaction model," Journal of Retailing and Consumer Services, Elsevier, vol. 27(C), pages 113-120.
    9. Odekerken-Schroder, Gaby & De Wulf, Kristof & Schumacher, Patrick, 2003. "Strengthening outcomes of retailer-consumer relationships: The dual impact of relationship marketing tactics and consumer personality," Journal of Business Research, Elsevier, vol. 56(3), pages 177-190, March.
    10. Ruth N. Bolton, 1998. "A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction," Marketing Science, INFORMS, vol. 17(1), pages 45-65.
    11. Marshall Freimer & Dan Horsky, 2008. "Try It, You Will Like It—Does Consumer Learning Lead to Competitive Price Promotions?," Marketing Science, INFORMS, vol. 27(5), pages 796-810, 09-10.
    12. Huei-Ting Tsai & Hsin-Cheng Chang & Ming-Tien Tsai, 2016. "Predicting repurchase intention for online clothing brands in Taiwan: quality disconfirmation, satisfaction, and corporate social responsibility," Electronic Commerce Research, Springer, vol. 16(3), pages 375-399, September.
    13. Zeelenberg, Marcel & Pieters, Rik, 2004. "Beyond valence in customer dissatisfaction: A review and new findings on behavioral responses to regret and disappointment in failed services," Journal of Business Research, Elsevier, vol. 57(4), pages 445-455, April.
    14. Yubo Chen & Jinhong Xie, 2005. "Third-Party Product Review and Firm Marketing Strategy," Marketing Science, INFORMS, vol. 24(2), pages 218-240, February.
    15. Wang, Feng & Liu, Xuefeng & Fang, Eric (Er), 2015. "User Reviews Variance, Critic Reviews Variance, and Product Sales: An Exploration of Customer Breadth and Depth Effects," Journal of Retailing, Elsevier, vol. 91(3), pages 372-389.
    16. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    17. Hui Zhang & Huguang Rao & Junzheng Feng, 2018. "Product innovation based on online review data mining: a case study of Huawei phones," Electronic Commerce Research, Springer, vol. 18(1), pages 3-22, March.
    18. Fan, Zhi-Ping & Che, Yu-Jie & Chen, Zhen-Yu, 2017. "Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis," Journal of Business Research, Elsevier, vol. 74(C), pages 90-100.
    19. Sarah G. Moore, 2015. "Attitude Predictability and Helpfulness in Online Reviews: The Role of Explained Actions and Reactions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 42(1), pages 30-44.
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