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An on-demand service platform with self-scheduling capacity: Uniform versus multiplier-based pricing
Journal article   Peer reviewed

An on-demand service platform with self-scheduling capacity: Uniform versus multiplier-based pricing

Mingyang Chen, Daozhi Zhao, Yeming Gong and Yacine Rekik
International Journal of Production Economics
01/01/2022

Abstract

sharing economy On-demand service platform Self-scheduling capacity Pricing scheme
On-demand service platforms use multiplier-based pricing to provide services via self-scheduling participants. In a multiplier-based pricing scheme, consumers pay lower prices during non-peak periods and higher prices equal to the non-peak period price multiplied by a surge multiplier during peak periods. However, the reasons underlying multiplier-based pricing and when it should be used remain unclear. In this paper, we examine the effects of two pricing schemes—uniform pricing and multiplier-based pricing—on platform profits, participant payoff, and consumer surplus by formulating game-based models, and investigate the conditions and feasible region for use of multiplier-based pricing. The results show that the non-peak price in the multiplier-based pricing scheme is lower than the uniform price, which is in line with reality. When the number of potential participants in non-peak periods is larger, the multiplier-based pricing model generates more profits if compensation ratios in the two models are higher or the compensation ratio in the multiplier-based pricing model is lower. Participants are better off joining a platform that uses uniform pricing given one of the following conditions: lower commission ratio in the two models, lower compensation ratio in the multiplier-based pricing model and higher commission ratio in the two models, and higher commission and compensation ratios in the two models. Consumers are better off in the uniform pricing model if the proportion of non-peak periods, consumer sensitivity to surge multiplier change, and the ratio of potential participants in peak and non-peak periods are higher.
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https://doi.org/10.1016/j.ijpe.2021.108329View
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Collaboration types
Domestic collaboration
International collaboration
Citation topics
4 Electrical Engineering, Electronics & Computer Science
4.84 Supply Chain & Logistics
4.84.260 Supply Chain Optimization
Web of Science research areas
Engineering, Industrial
Engineering, Manufacturing
Operations Research & Management Science
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