Optimal investment and management of shared bikes in a competitive market. (May 2020)

• Record Type: Journal Article
• Authors: Jiang, Zhoutong; Lei, Chao; Ouyang, Yanfeng
• Is Part Of: Transportation research. Volume 135(2020)
• Page Start: 143
• Page End: 155
• Publication Date: 2020-05
• Subjects: Competition -- Bike-sharing -- Stochastic programming; Transportation -- Research -- Periodicals; Transportation -- Mathematical models -- Periodicals
• DOI: 10.1016/j.trb.2020.03.007
• Languages: English
• ISSNs: 0191-2615

Abstract

Highlights: Optimal investment and management strategies for bike-sharing companies under competition. Multi-period two-stage stochastic program under demand uncertainty and Nash equilibrium. Properties and insights on special cases and problem extensions. Numerical demonstration of applicability and effectiveness of the proposed approach. Abstract: Rapid growth, fierce competition, and repeated failures of bike-sharing companies in the market highlight urgent needs for a systematic modeling framework to analyze optimal investment and management strategies of bike-sharing companies under competition. The share of bike-sharing market depends on how the competing companies deploy their bikes over time and space since travelers typically choose the nearest available bikes. Hence, each individual company aims to maximize its profit through optimal investment and allocation/rebalancing strategies in response to time-varying demand as well as actions of the peer companies. In this paper, we propose a game-theoretical framework to model the competition between two bike-sharing companies, and a two-stage multi-period stochastic program is developed to model the decision process of each company. The effects of demand elasticity and uncertainty are also discussed. We then show existence of Nash equilibrium and insights into the solution for several special cases. For general cases, an iterative algorithm is proposed to solve the Nash equilibrium. Numerical experiments are conducted to demonstrate the applicability of the proposed model and to draw insights on the impacts of market competition.