Evolutionary game analysis of online car-hailing system under two-way credit evaluation mechanism

This paper aims to explore the dynamic evolution process of online car-hailing systems, and a two-way credit evaluation mechanism is introduced to investigate the management measures and government regulations of online car-hailing systems. First, by constructing evolutionary game models between passengers, drivers, the platform, and the government, the replicator dynamic equation of the online car-hailing system is explored. Second, the equilibrium stability of the evolutionary game system is analyzed to determine the evolutionarily stable strategy, and the location of local equilibrium points of the evolutionary game models is identified. Third, PyCharm software package is used to simulate the stability of different equilibrium points in the evolutionary game model, and the impact of different influencing factors on the evolutionarily stable strategy at optimal equilibrium points are analyzed. Results indicate that the impact on passenger strategy choice is most significant when the choice utility of passengers towards drivers is between 0.2 and 0.4. When the cost of setting up a two-way credit evaluation mechanism on the platform is between 0.2 and 0.4, the effect on the strategy choice of the online car-hailing platform is most obvious. If the platform does not set up a two-way credit evaluation mechanism, the negative externality brought to passengers has the greatest correlation with passenger strategy choice when it is between 0.4 and 0.6. The impact of social welfare on government strategy is greatest when it is between 0 and 3. This study proposes the management strategy and analysis method of setting up a two-way credit evaluation mechanism for the online car-hailing system, thus to clarify the evolutionary game relationship between government regulatory authorities and the online car-hailing market. Results and findings of this study may assist to ensure the effective implementation of online car-hailing operation and management regulations.