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Online Reviews and Collaborative Service Provision: A Signal‐Jamming Model

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  • Haoying Sun
  • Lizhen Xu

Abstract

We study the provision of collaborative services under online reviews, where the service outcome depends on the effort of both the service provider and the client. The provider decides not only her own effort but also the client's, at least to some extent. The client gives the review based on his net utility upon service completion. We develop a signal‐jamming model in which the provider's inherent capability or type is unobservable, and the market infers the provider type through observable signals such as the service outcome, the client review, or both. We show that compared to the benchmark case when the service outcome is observed as a signal, the client review generally leads to less effort of both the provider and the client. The review hence tends to sacrifice the service effectiveness in favor of the efficiency of the client's effort input. Nevertheless, when clients incorporate private information about the provider type into their reviews, service providers are better motivated to devote effort. Interestingly, we find the provider's effort choices may be either strategic complements or substitutes. With a reasonable level of informativeness, online reviews could lead to favorable performance in service effectiveness, client effort efficiency, and provider type distinguishability. Surprisingly, we demonstrate that when both the review and the outcome are available, the provider may lack sufficient incentive to devote effort, resulting in inferior distinguishability of provider types. It thus illustrates that richer information may not necessarily generate favorable strategic outcomes.

Suggested Citation

  • Haoying Sun & Lizhen Xu, 2018. "Online Reviews and Collaborative Service Provision: A Signal‐Jamming Model," Production and Operations Management, Production and Operations Management Society, vol. 27(11), pages 1960-1977, November.
  • Handle: RePEc:bla:popmgt:v:27:y:2018:i:11:p:1960-1977
    DOI: 10.1111/poms.12592
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    Cited by:

    1. Sulin Ba & Yuan Jin & Xinxin Li & Xianghua Lu, 2020. "One Size Fits All? The Differential Impact of Online Reviews and Coupons," Production and Operations Management, Production and Operations Management Society, vol. 29(10), pages 2403-2424, October.
    2. Zibo Liu & Zhijie Lin & Ying Zhang & Yong Tan, 2022. "The Signaling Effect of Sampling Size in Physical Goods Sampling Via Online Channels," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 529-546, February.
    3. Awasthy, Prakash & Hazra, Jishnu, 2020. "Collaboration under outcome-based contracts for information technology services," European Journal of Operational Research, Elsevier, vol. 286(1), pages 350-359.
    4. Zhanfei Lei & Dezhi Yin & Sabyasachi Mitra & Han Zhang, 2022. "Swayed by the reviews: Disentangling the effects of average ratings and individual reviews in online word‐of‐mouth," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2393-2411, June.
    5. Greiff, Matthias & Paetzel, Fabian, 2020. "Information about average evaluations spurs cooperation: An experiment on noisy reputation systems," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 334-356.
    6. Dominik Gutt & Jürgen Neumann & Wael Jabr & Dennis Kundisch, 2020. "The Fate of the App: Economic Implications of Updating under Reputation Resetting," Working Papers Dissertations 76, Paderborn University, Faculty of Business Administration and Economics.
    7. Pal Singh, Satender & Adhikari, Arnab & Majumdar, Adrija & Bisi, Arnab, 2022. "Does service quality influence operational and financial performance of third party logistics service providers? A mixed multi criteria decision making -text mining-based investigation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).

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