Open AccessA Study of Taxi Service Mode Choice Based on Evolutionary Game Theory
Author(s) -
Bai Zhu,
Mingxia Huang,
Shuai Bian,
Huandong Wu
Publication year - 2019
Publication title -
journal of advanced transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.577
H-Index - 46
eISSN - 2042-3195
pISSN - 0197-6729
DOI - 10.1155/2019/8607942
Subject(s) - evolutionary game theory , service (business) , mode (computer interface) , game theory , stochastic game , evolutionarily stable strategy , mode choice , computer science , operations research , convergence (economics) , process (computing) , business , transport engineering , microeconomics , economics , engineering , marketing , public transport , human–computer interaction , economic growth , operating system
The emergence of online car-hailing service provides an innovative approach to vehicle booking but has negatively influenced the taxi industry in China. This paper modeled taxi service mode choice based on evolutionary game theory (EGT). The modes included the dispatching and online car-hailing modes. We constructed an EGT framework, including determining the strategies and the payoff matrix. We introduced different behaviors, including taxi company management, driver operation, and passenger choice. This allowed us to model the impact of these behaviors on the evolving process of service mode choice. The results show that adjustments in taxi company, driver, and passenger behaviors impact the evolutionary path and convergence speed of our evolutionary game model. However, it also reveals that, regardless of adjustments, the stable states in the game model remain unchanged. The conclusion provides a basis for studying taxi system operation and management.