Efficient Inaccuracy: User-Generated Information Sharing in a Queue

53 Pages Posted: 3 Oct 2017 Last revised: 9 Jul 2019

See all articles by Jianfu Wang

Jianfu Wang

City University of Hong Kong

Ming Hu

University of Toronto - Rotman School of Management

Date Written: October 2, 2017

Abstract

We study a service system which 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 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

Suggested Citation

Wang, Jianfu and Hu, Ming, Efficient Inaccuracy: User-Generated Information Sharing in a Queue (October 2, 2017). Rotman School of Management Working Paper No. 3046905, Available at SSRN: https://ssrn.com/abstract=3046905 or http://dx.doi.org/10.2139/ssrn.3046905

Jianfu Wang

City University of Hong Kong ( email )

Kowloon
Hong Kong
Hong Kong

Ming Hu (Contact Author)

University of Toronto - Rotman School of Management ( email )

105 St. George st
Toronto, ON M5S 3E6
Canada
416-946-5207 (Phone)

HOME PAGE: http://ming.hu

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