Strategic sourcing selection for bike-sharing rebalancing: An evolutionary game approach

Wei Gu, Meng Li, Chen Wang, Jennifer Shang, Lirong Wei

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Bike-sharing systems (BSSs) offer convenient transportation services with environmental and social benefits. However, they also bring operational complexity, with rebalancing bikes being a very challenging one. The importance and difficulty of building the reverse logistics for BSSs are evident from the data obtained from Mobike, one of the largest dockless bike-sharing platforms in China. This paper proposes an evolutionary game theoretic approach to identify the best bike-sharing sourcing strategies, including self-operation, joint venture, and outsourcing. We show that the self-operation mode is an evolutionary stable strategy to rebalance Mobike. However, if bike-sharing firms cannot achieve economies of scale and significantly reduce the variable costs of the self-operation mode, the outsourcing mode will become the optimal choice. From a long-term perspective, the joint venture mode is never an attractive strategy for the bike-sharing firms under study. Our model can select the optimal sourcing strategy to rebalance bikes in BSS to maximize profit when competition and cooperation are jointly considered.

Original languageEnglish (US)
Article number102522
JournalTransportation Research Part E: Logistics and Transportation Review
StatePublished - Dec 2021

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Civil and Structural Engineering
  • Transportation


  • Bike-sharing systems
  • Evolutionary game theory
  • Reverse logistics
  • Sourcing strategy


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