TY - JOUR
T1 - Strategic sourcing selection for bike-sharing rebalancing
T2 - An evolutionary game approach
AU - Gu, Wei
AU - Li, Meng
AU - Wang, Chen
AU - Shang, Jennifer
AU - Wei, Lirong
N1 - Funding Information:
This work is supported by the National Natural Science Foundation of China (Grant Number 72072010, 71702009, 71803007), Beijing Social Science Fund (Grant Number 20GLB017), and the Fundamental Research Funds for the Central Universities and the Youth Teacher International Exchange & Growth Program (Grant Number QNXM20210049).
Publisher Copyright:
© 2021
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
KW - Bike-sharing systems
KW - Evolutionary game theory
KW - Reverse logistics
KW - Sourcing strategy
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U2 - 10.1016/j.tre.2021.102522
DO - 10.1016/j.tre.2021.102522
M3 - Article
AN - SCOPUS:85118531516
SN - 1366-5545
VL - 156
JO - Transportation Research, Part E: Logistics and Transportation Review
JF - Transportation Research, Part E: Logistics and Transportation Review
M1 - 102522
ER -