摘要
针对排污权拍卖中厂商信息交互结构对其策略演化的影响,运用网络演化博弈方法,将小世界网络引入到排污权统一价格拍卖的博弈分析之中。采用小世界网络刻画厂商的信息交互结构,同时将厂商的学习速度引入到博弈参与人的博弈策略更新规则中,并运用eclipse仿真研究厂商的策略演化与其学习速度及信息交互结构的关系。研究结果表明:厂商的策略收敛速度与学习速度、度正相关;与网络聚类系数、社团结构数目先正相关、后反相关;社团内部厂商的策略收敛速度快于社团外部厂商,存在最优网络聚类系数与最优社团结构数目。研究结果为排污权出让方如何有效诱导竞买方真实报价,提高双方的决策效率提供了建议参考。
In order to study the effects of manufacturers' information interaction structure on their strategies evolution in emissions permits auction,the method of evolutionary games on networks is utilized and a small-world network is introduced into the analysis of auction,and a small-world network is employed to portray manufacturers' information interaction structure.Meanwhile,learning speed is integrated into the strategy updating rule.Then,eclipse is used to simulate the effects of manufacturers' information interaction structure and their learning speed on the strategies evolution.The simulation results show that,manufacturers' strategies convergence speed has a positive correlation with their learning speed and degree,but has a first positive later negative correlation with clustering coefficient as well as the number of community structure.In addition,the strategies convergence speed of manufacturers in community is faster than that of manufacturers out community.There exits an optimal network clustering coefficient and an optimal number of community structure.At last,several suggestions are provided for government and manufacturers.The conclusion of this paper is helpful for emission rights licensors to induce the bidders to offer real price and can be regarded as a reference to improve the efficiency of decision-making on both sides.
出处
《中国管理科学》
CSSCI
CSCD
北大核心
2017年第3期76-84,共9页
Chinese Journal of Management Science
基金
国家自然科学基金资助项目(71371147)
关键词
信息交互结构
策略更新规则
小世界网络
学习速度
information interaction structure
strategies updating rule
small-world networks
learning speed
