Application of Multi-Criteria Decision Analysis in Enterprise Risk Management  

作　　者：Ruihan Zhang Ruihan Zhang(Nanjing Dongshan Foreign Language School, Nanjing, China)

机构地区：[1]Nanjing Dongshan Foreign Language School, Nanjing, China

出　　处：《Open Journal of Applied Sciences》2024年第11期3192-3201,共10页应用科学（英文）

摘　　要：Enterprise risk management has become increasingly crucial in today’s complex and volatile business environment. This study explores the application of Multi-Criteria Decision Analysis (MCDA) in enterprise risk management. MCDA provides a systematic approach to handling multidimensional risk assessment issues. The research begins by analyzing various types of risks faced by enterprises, including financial, operational, and strategic risks. It then examines the specific applications of major MCDA methods, such as the Analytic Hierarchy Process (AHP) and TOPSIS, in risk identification, assessment, and response. The study finds that MCDA can effectively integrate qualitative and quantitative risk information, enhancing the scientific nature of risk decision-making. However, MCDA also faces challenges in practice, such as the subjectivity in determining indicator weights. To address this issue, the research proposes improved methods combining fuzzy theory and group decision-making. Finally, case analyses illustrate the effectiveness of MCDA applications in risk management across different industries. This study provides theoretical guidance for enterprises to build more comprehensive and dynamic risk management systems.Enterprise risk management has become increasingly crucial in today’s complex and volatile business environment. This study explores the application of Multi-Criteria Decision Analysis (MCDA) in enterprise risk management. MCDA provides a systematic approach to handling multidimensional risk assessment issues. The research begins by analyzing various types of risks faced by enterprises, including financial, operational, and strategic risks. It then examines the specific applications of major MCDA methods, such as the Analytic Hierarchy Process (AHP) and TOPSIS, in risk identification, assessment, and response. The study finds that MCDA can effectively integrate qualitative and quantitative risk information, enhancing the scientific nature of risk decision-making. However, MCDA also faces challenges in practice, such as the subjectivity in determining indicator weights. To address this issue, the research proposes improved methods combining fuzzy theory and group decision-making. Finally, case analyses illustrate the effectiveness of MCDA applications in risk management across different industries. This study provides theoretical guidance for enterprises to build more comprehensive and dynamic risk management systems.

关 键 词：MCDA Enterprise Risk Management AHP TOPSIS Risk Assessment 

分 类 号：O17[理学—数学]