系统管理学报2026，Vol.35Issue(1)：72-84,13.DOI:10.3969/j.issn2097-4558.2026.01.006
基于计算实验的重大工程风险管理激励效率演化分析
Evolutionary Analysis of Incentive Efficiency in Mega Project Risk Management Based on Computational Experiments:Considering the Role of Insurance Institutions
摘要
Abstract
In response to the high-risk exposure in mega projects and considering the potential role of insurance institutions in onsite risk management,this paper develops a multi-period incentive model for owners and contractor groups under the participation of insurance institutions.Based on a computational experimental approach,it simulates the evolution of risk management behaviors of different stakeholders under various scenarios,exploring the effects of fairness preferences,incentive mechanisms,and insurance participation on the efficiency of risk management incentives.The results indicate that the fairness preference of contractors significantly impacts incentive effectiveness.Dynamic incentives implemented by owners and insurance institutions are significantly more effective than static,constant incentives.Proactive participation by insurance institutions effectively promotes the risk management efforts of mega projects,enhancing the payoffs of all parties involved.These findings offer new theoretical insights and decision-making guidance for risk management in mega projects.关键词
重大工程保险/风险管理/激励/计算实验Key words
mega project insurance/risk management/incentives/computational experiments分类
管理科学引用本文复制引用
时茜茜,姚隆玉,李博雅,朱建波..基于计算实验的重大工程风险管理激励效率演化分析[J].系统管理学报,2026,35(1):72-84,13.基金项目
国家自然科学基金资助项目(72301132,72101055) （72301132,72101055）
江苏省社会科学基金资助项目(20GLC019) （20GLC019）
国家资助博士后研究人员计划(GZC20240247) （GZC20240247）
江苏省卓越博士后计划资助项目(2024ZB176) （2024ZB176）
中国博士后科学基金面上项目(2024M750456) （2024M750456）
中央高校基本科研业务费(NR2023004) （NR2023004）
南京航空航天大学研究生科研与实践创新计划资助项目(xcxjh20230917) （xcxjh20230917）
