Bilateral Pricing of Ride-Hailing Platforms Considering Cross-Group Network Effect and Congestion Effect

Author:

Li Jing1,Huang Hongfu2,Li Li2ORCID,Wu Jieyu2

Affiliation:

1. School of Cyber Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

2. School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China

Abstract

The pricing of ride-hailing platforms (e.g., Didi Rider and Uber) is heavily and simultaneously influenced by the cross-group network effect and congestion effect. To analyze the bilateral pricing of ride-hailing platforms under the influence of these two effects, in this paper we construct a game-theoretic model under four different scenarios and analyze the equilibrium outcomes. The results show that: (1) when both passengers and drivers are sensitive to hassle costs, if the cross-group network effect on the passenger side is higher than that on the driver side, then the platform’s pricing on both sides increases with the increase in the congestion effect, otherwise the prices on both sides of the platform decrease with the increase in the congestion effect; (2) when passengers are sensitive to hassle costs and drivers are sensitive to price, if the ratio for passengers’ and drivers’ different perceptions of price and hassle cost is greater than a certain threshold, then the platform’s pricing on the passenger side increases with the increase in the congestion effect and the platform’s pricing on the driver side decreases with the increase in the congestion effect, otherwise the platform’s pricing on the passenger side decreases with the increase in the congestion effect and the platform’s pricing on the drivers’ side increases with the increase in the congestion effect; (3) when passengers are sensitive to price and drivers are sensitive to hassle costs, if the ratio for passengers’ and drivers’ different perceptions of price and hassle costs is greater than a certain threshold, then the platform’s pricing on the passenger side decreases with the increase in the congestion effect and the platform’s pricing on the drivers’ side increases with the increase in the congestion effect, otherwise the platform’s pricing on the passenger side increases with the increase of the congestion effect and the platform’s pricing on the driver side decreases with the increase in the congestion effect; (4) when both passengers and drivers are price-sensitive, if the cross-group network effect on the passengers’ side is larger than that on the drivers’ side, then the platform should decrease its pricing on both sides with the increase in the congestion effect, otherwise, if the cross-group network effect on the passengers’ side is less than that on the drivers’ side, the platform should increase its pricing on both sides with the increase in the congestion effect; (5) the platform is able to generate the highest profit in each scenario, and the results of the profit comparison between the four scenarios depends on the cross-group network effects and the congestion effects on both the passengers’ and the drivers’ sides.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

China Postdoctoral Science Foundation

Fundamental Research Funds for the Central Universities

General Project of Philosophy and Social Sciences Research in Colleges and Universities of Jiangsu Province

Publisher

MDPI AG

Subject

Computer Science Applications,General Business, Management and Accounting

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