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Efficient Inaccuracy: User-Generated Information Sharing in a Queue

Author

Listed:
  • Jianfu Wang

    (Nanyang Business School, Nanyang Technological University, Singapore 639798;)

  • Ming Hu

    (Rotman School of Management, University of Toronto, Toronto, Ontario M5S 3E6, Canada)

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.

Suggested Citation

  • Jianfu Wang & Ming Hu, 2020. "Efficient Inaccuracy: User-Generated Information Sharing in a Queue," Management Science, INFORMS, vol. 66(10), pages 4648-4666, October.
  • Handle: RePEc:inm:ormnsc:v:66:y:2020:i:10:p:4648-4666
    DOI: 10.1287/mnsc.2019.3447
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    References listed on IDEAS

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    1. Mujahid Ghouri, Arsalan & Mani, Venkatesh & Jiao, Zhilun & Venkatesh, V.G. & Shi, Yangyan & Kamble, Sachin S., 2021. "An empirical study of real-time information-receiving using industry 4.0 technologies in downstream operations," Technological Forecasting and Social Change, Elsevier, vol. 165(C).

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