Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/89945
| Title: | Cyclic pricing when customers queue with rating information | Authors: | Huang, F Guo, P Wang, Y |
Issue Date: | Oct-2019 | Source: | Production and operations management, Oct. 2019, v. 28, no. 10, p. 2471-2485 | Abstract: | Consider a situation where a service provider serves two types of customers, sophisticated and naive. Sophisticated customers are well-informed of service-related information and make their joining-or-balking decisions strategically, whereas naive customers do not have such information and rely on online rating information to make such decisions. We demonstrate that under certain conditions a service provider can increase its profitability by simply “dancing” its price, that is, replacing the static pricing strategy with a high-low cyclic pricing strategy. The success of this strategy relies on two key conditions: the potential market size is large enough so that congestion is a key concern in the service system, and the rating provides the average price and average utility information. Finally, we show that the cyclic pricing strategy is not socially optimal. | Keywords: | Customer rating Game theory Pricing Queueing strategy Unobservable queue |
Publisher: | Wiley-Blackwell | Journal: | Production and operations management | ISSN: | 1059-1478 | EISSN: | 1937-5956 | DOI: | 10.1111/poms.13052 | Rights: | © 2019 Production and Operations Management Society This is the peer reviewed version of the following article: Huang, F., Guo, P. and Wang, Y. (2019), Cyclic Pricing When Customers Queue with Rating Information. Prod Oper Manag, 28: 2471-2485, which has been published in final form at https://doi.org/10.1111/poms.13052. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. |
| Appears in Collections: | Journal/Magazine Article |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| a0795-n01_1642.pdf | Pre-Published version | 6.28 MB | Adobe PDF | View/Open |
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