Efficient Inaccuracy: User-Generated Information Sharing in a Queue

Jianfu Wang () and Ming Hu ()
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Jianfu Wang: Nanyang Business School, Nanyang Technological University, Singapore 639798;
Ming Hu: Rotman School of Management, University of Toronto, Toronto, Ontario M5S 3E6, Canada

Management Science, 2020, vol. 66, issue 10, 4648-4666

Abstract: We study a service system that does not have the capability of monitoring and disclosing its real-time congestion level. However, the customers can observe and post their observations online, and future arrivals can take into account such user-generated information when deciding whether to go to the service facility. We perform pairwise comparisons of the shared, full, and no queue-length information structures in terms of social welfare. Perhaps surprisingly, we show that the shared queue-length information may provide greater social welfare than full queue-length information when the hassle cost of the customers entering the service facility falls into some ranges, and the shared and full queue-length information structures always generate greater social welfare than no queue-length information. Therefore, the discrete disclosure of congestion through user-generated sharing can lead to as much, or even greater, social welfare as the continuous stream of real-time queue-length information disclosure and always generates greater social welfare than no queue-length information disclosure at all. These results imply that a little shared queue-length information—inaccurate and lagged—can go a long way and that it may be more socially beneficial to encourage the sharing of user-generated information among customers than to provide them with full real-time queue-length information.

Keywords: observable queue; unobservable queue; information sharing; service operations (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:66:y:2020:i:10:p:4648-4666

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