ABSTRACT

Crowd logistics is believed to be an innovative idea that can solve the dilemma lying in the scattered transportation resources and unstable demands of urban freight transport. However, the negative interactions among the participants have left crowd logistics an unstable development. In order to reveal the interactions, which occur under the bounded rationality and discover influencing factors to participants’ strategy selections, this article develops the system evolutionary game model and system dynamics model. Also, it investigates how tripartite participants respond to the governance policies under static and dynamic scenario. The simulation results show that dynamic scenario has a better performance in restraining strategy fluctuations among the participants. Under the dynamic scenario, the strategy combination of participants eventually converges to the evolutionarily stable strategy. The probability that shippers adopt “price-exploitation” strategy is positively correlated with extra profits while negatively correlated with the upper bond of the penalties. The profits are the key factor affecting the willingness of drivers joining crowd logistics platform (CLP).

摘要

人群物流被认为是一种创新理念，可以解决城市货运资源分散、需求不稳定的困境。然而，参与者之间的负面互动使人群物流发展不稳定。为了揭示有限理性下发生的相互作用并发现影响参与者策略选择的因素，本文建立了系统演化博弈模型和系统动力学模型。此外，它还调查了三方参与者如何响应静态和动态场景下的治理策略。仿真结果表明，动态情景在抑制参与者之间的策略波动方面具有更好的性能。在动态场景下，参与者的策略组合最终收敛到进化稳定的策略。托运人采取“价格剥削”策略的概率与额外利润正相关，而与罚款上限负相关。利润是影响司机加入众包物流平台（CLP）意愿的关键因素。