城市轨道交通产业协同创新投机行为治理研究——基于复杂网络博弈的仿真分析

为了探索城市轨道交通产业协同创新过程中投机行为的微观决策所导致的宏观涌现现象，采用复杂网络演化博弈，将城市轨道交通产业协同创新的所有企业看作小世界网络，建立无约束条件下和治理机制下成员的微观决策模型，使用 Python软件编程仿真研究微观决策影响因素对协同创新网络的影响。仿真结果表明，在无约束条件下，协同创新成员的创新收益、投入成本与挪用收益之间的关系大小对投机行为的最终选择比例有显著影响；网络规模对成员最终选择投机行为影响不大，但对演化时间进程有显著影响。在治理机制下，加大惩罚力度、监管概率与声誉损失能够有效抑制投机行为。

Simulation Study on Collaborative Innovation and Speculative Behavior of Urban Rail Transit Industry Based on Complex Network Evolutionary Game Theory

In order to explore the macro emergence phenomenon caused by the micro decision-making of speculative behavior in the process of urban rail transit industry collaborative innovation, the Complex network evolution game was used to treat all enterprises of urban rail transit industry collaborative innovation as a small world network, establish a micro Decision model for members under unconstrained conditions and governance mechanisms, and Python software was used to program and simulate the impact of micro decision-making influencing factors on the collaborative innovation network.The simulation results show that under unconstrained conditions, the relationship between the innovation benefits, investment costs, and misappropriation benefits of collaborative innovation members has a significant impact on the final selection proportion of speculative behavior.The size of the network has little impact on the final choice of speculative behavior among members, but it has a significant impact on the evolutionary time process. Under the governance mechanism, increasing punishment, regulatory probability, and reputation loss can effectively suppress speculative behavior.