基于复杂网络演化博弈的企业低碳创新合作行为网络演化机理研究

doi:10.12005/orms.2019.0130

运筹与管理 ›› 2019, Vol. 28 ›› Issue (6): 70-79.DOI: 10.12005/orms.2019.0130

基于复杂网络演化博弈的企业低碳创新合作行为网络演化机理研究

徐建中¹, 赵亚楠¹, 朱晓亚²

1.哈尔滨工程大学经济管理学院,黑龙江哈尔滨 150001;
2.苏州大学政治与公共管理学院,江苏苏州 215123

收稿日期:2018-03-09 出版日期:2019-06-25
通讯作者: 赵亚楠(1988-),女,黑龙江哈尔滨人,博士研究生,主要从事技术创新、创新网络研究;朱晓亚(1988-),女,山东菏泽人,讲师,主要从事企业创新与知识管理研究。
作者简介:徐建中(1959-),男,河北丰润县人,教授、博士生导师,主要从事现代管理理论与方法、经济管理与战略研究。
基金资助:
国家自然科学基金项目(71273072);国家自然科学基金应急管理项目(71841054);黑龙江省哲学社会科学研究规划项目(17JYH49)

Network Evolution Mechanism of Low Carbon Innovation Cooperation Behaviorin Enterprises Based on Evolutionary Game Theory on Complex Network

XU Jian-zhong¹, ZHAO Ya-nan¹, ZHU Xiao-ya²

1.School of Economics and Management, Harbin Engineering University, Heilongjiang, Harbin 150001, China;
2.School of Politics and Public Administration, Soochow University, Jiangsu, Suzhou 215123, China

Received:2018-03-09 Online:2019-06-25

摘要/Abstract

摘要： 针对企业低碳创新合作所面临的复杂问题,基于现实复杂网络结构特征,运用演化博弈理论研究有限理性下企业低碳创新合作行为网络演化机理,利用Matlab仿真技术探究无标度网络载体上微观因素对低碳创新合作行为的影响。研究结果表明:低碳创新利益分配、协同效益和违约惩罚对低碳创新合作行为网络演化结果的影响最为显著,网络规模越大网络演化速度越慢,网络规模越小对协同系数和利益分配系数的敏感性越强,网络规模越大对技术溢出系数和违约惩罚的敏感性越强。研究结论可以为企业低碳创新合作策略制定提供解决依据。

关键词: 低碳创新, 合作行为, 复杂网络演化博弈, EWA学习模型

Abstract: In view of the complex problems in low-carbon innovation cooperation faced by China's enterprises, evolutionary game theory is used to study the evolution mechanism of low carbon innovation cooperation behavior of enterprises under bounded rationality based on the characteristics of complex network structure. The Matlab simulation technology is employed to explore the impact of micro factors on the cooperative behavior of low-carbon innovation on scale-free network. The results show that the low-carbon innovation synergy benefit and default penalty and distribution of interests have a significant effect on the evolution of low carbon innovation cooperative behavior network. Network size is negatively related to network evolution velocity, and smaller scale networks are more sensitive to the synergistic coefficient and benefit distribution coefficient, and greater scale networks are more sensitive to the technology spillover coefficient and the default penalty. The conclusions provide a basis for the strategy formulation of low-carbon innovation cooperation.

Key words: low-carbon innovation, cooperation behavior, evolutionary game theory on complex network, EWA learning model

中图分类号:

F272.3

徐建中, 赵亚楠, 朱晓亚. 基于复杂网络演化博弈的企业低碳创新合作行为网络演化机理研究[J]. 运筹与管理, 2019, 28(6): 70-79.

XU Jian-zhong, ZHAO Ya-nan, ZHU Xiao-ya. Network Evolution Mechanism of Low Carbon Innovation Cooperation Behaviorin Enterprises Based on Evolutionary Game Theory on Complex Network[J]. Operations Research and Management Science, 2019, 28(6): 70-79.

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基于复杂网络演化博弈的企业低碳创新合作行为网络演化机理研究

Network Evolution Mechanism of Low Carbon Innovation Cooperation Behaviorin Enterprises Based on Evolutionary Game Theory on Complex Network

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