摘要
针对电子商务信任评价机制中难以采取有效激励措施使客户进行真实评价的问题,根据客户对商家的评价行为具有不完全信息和有限理性特点,建立演化博弈模型对信任模型的激励措施进行分析和改进。该模型运用复制动态机制模拟客户的策略选择演化,对现有激励措施下演化稳定策略(ESS)的存在性进行论证,并基于系统动力学增加补偿收益进行改进。基于NetLogo系统动力学模块建模实验表明,相较于基于兴趣群组的信任激励模型(IGTrust),改进后的激励措施得到ESS并成功预测和控制了客户评价策略;同时模型具备鲁棒性,应对7%客户评价策略变异也能够保持演化稳定状态。
It＇ s difficult for incentive mechanism to effectively enable customers to make true evaluation in e-commerce. According to the evaluation behavior characteristics of incomplete information and limited rationality, an evolutionary game model was established to analyze and improve the incentive mechanism in trust model. Firstly, the Replicator Dynamics mechanism was used to simulate the evolution of the customer selection strategy. Then, the existence of Evolutionary Stable Strategy （ESS） in common incentive mechanism was discussed. Finally, the compensation benefits were proposed to improve the incentive system based on system dynamics. In the comparison simulation experiments with an Interest Group based Trust model （IGTrust） which conducted on NetLogo system dynamics modeler, the results show that the modified incentive mechanism achieved ESS, and also successfully predicted and controlled the customer evaluation strategy. The proposed model can possess robustness and maintain evolutionary stable state when dealing with 7% variation of evaluation strategy.
出处
《计算机应用》
CSCD
北大核心
2016年第12期3269-3273,共5页
journal of Computer Applications
基金
国家自然科学基金资助项目(61402530)
陕西省自然科学基金资助项目(2014JQ8301)~~
关键词
电子商务
评价策略
演化博弈
信任模型
激励机制
e-commerce
evaluation strategy
evolutionary game
trust model
incentive mechanism
