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Beyond weekdays: The impact of the weekend effect on eWOM of hedonic product

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  • Du, Jiangang
  • Zhu, Liya
  • Ma, Yuanning
  • Zhang, Yu

Abstract

This study investigates the influence of the ‘weekend effect’, a temporal factor associated with enhanced mood positivity during weekends, on online reviews, a pivotal form of electronic word-of-mouth (eWOM). Leveraging a dataset of 588,011 online reviews from 806 products on leading Chinese e-commerce platforms, supplemented by a laboratory experiment, we discerned a significant increase in review scores for hedonic products during weekends, which are intrinsically linked to emotional responses. However, this effect is not observed for utilitarian products. Additionally, our findings reveal that platform membership status moderates the impact of the ‘weekend effect’ on online reviews, with members demonstrating more objective review behavior and reduced susceptibility to the ‘weekend effect’. This research expands the understanding of eWOM antecedents by incorporating temporal factors and enriches the existing body of research on the ‘weekend effect’. It also provides practical insights for online retailers and platforms aiming to manage and leverage online reviews effectively.

Suggested Citation

  • Du, Jiangang & Zhu, Liya & Ma, Yuanning & Zhang, Yu, 2024. "Beyond weekdays: The impact of the weekend effect on eWOM of hedonic product," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:joreco:v:77:y:2024:i:c:s0969698923003752
    DOI: 10.1016/j.jretconser.2023.103624
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    1. Wagner A. Kamakura & Rex Yuxing Du, 2012. "How Economic Contractions and Expansions Affect Expenditure Patterns," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 39(2), pages 229-247.
    2. Wang, Bin & Xie, Fengyuan & Kandampully, Jay & Wang, Jin, 2022. "Increase hedonic products purchase intention through livestreaming: The mediating effects of mental imagery quality and customer trust," Journal of Retailing and Consumer Services, Elsevier, vol. 69(C).
    3. Weisstein, Fei L. & Song, Lei & Andersen, Peter & Zhu, Ying, 2017. "Examining impacts of negative reviews and purchase goals on consumer purchase decision," Journal of Retailing and Consumer Services, Elsevier, vol. 39(C), pages 201-207.
    4. Zhao, Ling & Lu, Yaobin & Wang, Bin & Chau, Patrick Y.K. & Zhang, Long, 2012. "Cultivating the sense of belonging and motivating user participation in virtual communities: A social capital perspective," International Journal of Information Management, Elsevier, vol. 32(6), pages 574-588.
    5. Kelley Gullo & Jonah Berger & Jordan Etkin & Bryan Bollinger & Vicki G MorwitzEditor & J Jeffrey InmanEditor & Andrea C MoralesAssociate Editor, 2019. "Does Time of Day Affect Variety-Seeking?," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 46(1), pages 20-35.
    6. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "When are extreme ratings more helpful? Empirical evidence on the moderating effects of review characteristics and product type," Grenoble Ecole de Management (Post-Print) halshs-01923243, HAL.
    7. Vijay Singal & Jitendra Tayal, 2020. "Risky short positions and investor sentiment: Evidence from the weekend effect in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(3), pages 479-500, March.
    8. Zhao, Lu & Zhang, Mingli & Tu, Jianbo & Li, Jialing & Zhang, Yan, 2023. "Can users embed their user experience in user-generated images? Evidence from JD.com," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    9. Loch, Christoph H. & Huberman, Bernardo A. & Stout, Suzanne, 2000. "Status competition and performance in work groups," Journal of Economic Behavior & Organization, Elsevier, vol. 43(1), pages 35-55, September.
    10. 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.
    11. Pangarkar, Aniruddha & Patel, Jayesh & Kumar, Sampath K., 2023. "Drivers of eWOM engagement on social media for luxury consumers: Analysis, implications, and future research directions," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    12. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "When are extreme ratings more helpful? Empirical evidence on the moderating effects of review characteristics and product type," Post-Print hal-03511272, HAL.
    13. Hu, Xin & He, Liuyi & Liu, Junjun, 2022. "The power of beauty: Be your ideal self in online reviews—an empirical study based on face detection," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    14. Verma, Deepak & Prakash Dewani, Prem & Behl, Abhishek & Pereira, Vijay & Dwivedi, Yogesh & Del Giudice, Manilo, 2023. "A meta-analysis of antecedents and consequences of eWOM credibility: Investigation of moderating role of culture and platform type," Journal of Business Research, Elsevier, vol. 154(C).
    15. Leif Brandes & Yaniv Dover, 2022. "Offline Context Affects Online Reviews: The Effect of Post-Consumption Weather [Mobile Ad Effectiveness: Hyper-Contextual Targeting with Crowdedness]," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 49(4), pages 595-615.
    16. Dongpu Fu & Yili Hong & Kanliang Wang & Weiguo Fan, 2018. "Effects of membership tier on user content generation behaviors: evidence from online reviews," Electronic Commerce Research, Springer, vol. 18(3), pages 457-483, September.
    17. Rese, Alexandra & Schreiber, Stefanie & Baier, Daniel, 2014. "Technology acceptance modeling of augmented reality at the point of sale: Can surveys be replaced by an analysis of online reviews?," Journal of Retailing and Consumer Services, Elsevier, vol. 21(5), pages 869-876.
    18. Lee, Ju-Yeon & Fang, Eric & Kim, Jisu J. & Li, Xiaoling & Palmatier, Robert W., 2018. "The Effect of Online Shopping Platform Strategies on Search, Display, and Membership Revenues," Journal of Retailing, Elsevier, vol. 94(3), pages 247-264.
    19. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "When are extreme ratings more helpful? Empirical evidence on the moderating effects of review characteristics and product type," Post-Print halshs-01923243, HAL.
    20. David Godes & José C. Silva, 2012. "Sequential and Temporal Dynamics of Online Opinion," Marketing Science, INFORMS, vol. 31(3), pages 448-473, May.
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