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When crowding‐in and when crowding‐out? The boundary conditions on the relationship between negative online reviews and online sales

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  • Ao Shen
  • Peng Wang
  • Yongyuan Ma

Abstract

Drawing on the motivation crowding theory, we propose a novel framework concerning the moderating effects of customer‐initiated reviews and merchant‐initiated replies on the relationship between negative online reviews and online sales performance. Using 14,096 online reviews collected from Meituan.com, we found that the detrimental effect of negative online reviews will be mitigated with a greater level of customer‐initiated reviews and a medium level of merchant‐initiated replies. This study enhances the current understanding of the dyadic interaction between online customers and offline merchants, thereby suggesting the crowding‐in and crowding‐out effects of the merchant online replies toward negative online reviews.

Suggested Citation

  • Ao Shen & Peng Wang & Yongyuan Ma, 2022. "When crowding‐in and when crowding‐out? The boundary conditions on the relationship between negative online reviews and online sales," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 2016-2032, September.
  • Handle: RePEc:wly:mgtdec:v:43:y:2022:i:6:p:2016-2032
    DOI: 10.1002/mde.3505
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    1. Ert, Eyal & Fleischer, Aliza & Magen, Nathan, 2016. "Trust and reputation in the sharing economy: The role of personal photos in Airbnb," Tourism Management, Elsevier, vol. 55(C), pages 62-73.
    2. Donghui Yang & Yan Wang & Shue Mei, 2021. "How to balance online healthcare platforms and offline systems? A supply chain management perspective," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(2), pages 502-515, March.
    3. Monic Sun, 2012. "How Does the Variance of Product Ratings Matter?," Management Science, INFORMS, vol. 58(4), pages 696-707, April.
    4. Wu, Jintao & Wu, Tong & Schlegelmilch, Bodo B., 2020. "Seize the Day: How Online Retailers Should Respond to Positive Reviews," Journal of Interactive Marketing, Elsevier, vol. 52(C), pages 52-60.
    5. Yong Liu & Wen‐xue Gan & Wen‐wen Ren, 2021. "Influence mechanism of online consumer comments on e‐retailer," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(5), pages 1132-1145, July.
    6. Tobias Berger & Frank Daumann, 2021. "Anchoring bias in the evaluation of basketball players: A closer look at NBA draft decision‐making," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(5), pages 1248-1262, July.
    7. Jonah Berger & Alan T. Sorensen & Scott J. Rasmussen, 2010. "Positive Effects of Negative Publicity: When Negative Reviews Increase Sales," Marketing Science, INFORMS, vol. 29(5), pages 815-827, 09-10.
    8. Sparks, Beverley A. & So, Kevin Kam Fung & Bradley, Graham L., 2016. "Responding to negative online reviews: The effects of hotel responses on customer inferences of trust and concern," Tourism Management, Elsevier, vol. 53(C), pages 74-85.
    9. Yi, Jisu & Lee, Youseok & Kim, Sang-Hoon, 2019. "Determinants of growth and decline in mobile game diffusion," Journal of Business Research, Elsevier, vol. 99(C), pages 363-372.
    10. Liye Ma & Baohong Sun & Sunder Kekre, 2015. "The Squeaky Wheel Gets the Grease—An Empirical Analysis of Customer Voice and Firm Intervention on Twitter," Marketing Science, INFORMS, vol. 34(5), pages 627-645, September.
    11. Zike Cao & Kai-Lung Hui & Hong Xu, 2018. "When Discounts Hurt Sales: The Case of Daily-Deal Markets," Information Systems Research, INFORMS, vol. 29(3), pages 567-591, September.
    12. van Noort, Guda & Willemsen, Lotte M., 2012. "Online Damage Control: The Effects of Proactive Versus Reactive Webcare Interventions in Consumer-generated and Brand-generated Platforms," Journal of Interactive Marketing, Elsevier, vol. 26(3), pages 131-140.
    13. 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.
    14. Zhuang, Mengzhou & Cui, Geng & Peng, Ling, 2018. "Manufactured opinions: The effect of manipulating online product reviews," Journal of Business Research, Elsevier, vol. 87(C), pages 24-35.
    15. Salois, Matthew J. & Moss, Charles B., 2011. "A direct test of hyperbolic discounting using market asset data," Economics Letters, Elsevier, vol. 112(3), pages 290-292, September.
    16. Yi Zhao & Sha Yang & Vishal Narayan & Ying Zhao, 2013. "Modeling Consumer Learning from Online Product Reviews," Marketing Science, INFORMS, vol. 32(1), pages 153-169, May.
    17. Luigino Bruni & Vittorio Pelligra & Tommaso Reggiani & Matteo Rizzolli, 2020. "The Pied Piper: Prizes, Incentives, and Motivation Crowding-in," Journal of Business Ethics, Springer, vol. 166(3), pages 643-658, October.
    18. Davide Proserpio & Georgios Zervas, 2017. "Online Reputation Management: Estimating the Impact of Management Responses on Consumer Reviews," Marketing Science, INFORMS, vol. 36(5), pages 645-665, September.
    19. Bruno S. Frey & Reto Jegen, 2001. "Motivation Crowding Theory," Journal of Economic Surveys, Wiley Blackwell, vol. 15(5), pages 589-611, December.
    20. Alain Yee Loong Chong & Eugene Ch’ng & Martin J. Liu & Boying Li, 2017. "Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5142-5156, September.
    21. Moutaz Haddara & Jenny Hsieh & Asle Fagerstrøm & Niklas Eriksson & Valdimar Sigurðsson, 2020. "Exploring customer online reviews for new product development: The case of identifying reinforcers in the cosmetic industry," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(2), pages 250-273, March.
    22. Sang Ho Kim & Namkee Park & Seung Hyun Park, 2013. "Exploring the Effects of Online Word of Mouth and Expert Reviews on Theatrical Movies' Box Office Success," Journal of Media Economics, Taylor & Francis Journals, vol. 26(2), pages 98-114, June.
    23. Wei Chen & Bin Gu & Qiang Ye & Kevin Xiaoguo Zhu, 2019. "Measuring and Managing the Externality of Managerial Responses to Online Customer Reviews," Service Science, INFORMS, vol. 30(1), pages 81-96, March.
    24. Mingfeng Lin & Nagpurnanand R. Prabhala & Siva Viswanathan, 2013. "Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending," Management Science, INFORMS, vol. 59(1), pages 17-35, August.
    25. Judith A. Chevalier & Yaniv Dover & Dina MayzlinDina Mayzlin, 2018. "Channels of Impact: User Reviews When Quality Is Dynamic and Managers Respond," Marketing Science, INFORMS, vol. 37(5), pages 688-709, September.
    26. Du, Yiwei & Cui, Miao & Su, Jingqin, 2018. "Implementation processes of online and offline channel conflict management strategies in manufacturing enterprises: A resource orchestration perspective," International Journal of Information Management, Elsevier, vol. 39(C), pages 136-145.
    27. Park, Sangwon & Nicolau, Juan L., 2015. "Asymmetric effects of online consumer reviews," Annals of Tourism Research, Elsevier, vol. 50(C), pages 67-83.
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