Evolutionary game research on the decision-making of shared bike placement quantity based on dynamic and static punishment mechanisms

Abstract

Abstract This paper optimizes the total amount of shared bike placement from the supply side. Firstly, we used the evolutionary game method to study the dynamic evolution process of the decision-making of government departments and bike-sharing enterprises about the amount of placement. Secondly, we analyze the stability of the equilibrium point in the game system. Finally, we use MATLAB simulation to analyze the stability of its evolution, and then discuss the influence of the core parameters on the evolution of the behavior of the participating parties. The results show that solving the problem of the massive placement of shared bikes requires the government to participate and play a leading role. When the benefit of strict government regulation is less than the cost, a dynamic punishment mechanism should be used. When the benefit is greater than the cost, a static punishment mechanism should be used. Under the static punishment mechanism, the government’s strategy is insensitive to changes in the amount of punishment. But under the dynamic punishment mechanism, the amount of punishment is negatively correlated with the probability of strict government regulation. So the government can reduce its regulatory costs by increasing the amount of punishment.