关联型决策分析方法研究综述

Review on interdependent-decision analysis methods

关联型决策分析是决策科学领域近年来快速发展的重要研究分支,特别是供应链整合与管理协同创新,促进了跨组织、跨流程、跨任务、跨阶段的关联型决策分析研究的蓬勃发展.对该领域最新动向进行系统性综述,有助于理清关联型决策分析方法的研究脉络,提高方法应用有效性,推动方法的前沿性探索.首先,聚焦决策要素的深度解析,明晰了研究趋势的变化以及不同决策要素在关联类型、关联结构和关联信息等方面的差异与特点;然后,以适用的关联情境为划分依据,以应用价值挖掘和理论贡献凝练为切入点,从原理、创新与贡献、信息处理能力、应用复杂性等视角比对了各类关联型决策分析方法.最后,探讨了关联型决策分析方法研究的未来发展方向和关键问题.

Interdependent-decision analysis is an important research stream in the area of decision sciences in recent years. Particularly, the development of studies on interdependent-decision analysis with cross- organizations, cross-processes, cross-tasks and cross-stages is promoted by supply chain integration and the management of collaboration innovation. Systematic review on the newest trends in this area will contribute to clear the research streams, improve the effectiveness of method application and promote state-of-the-art research development. Firstly, an in-depth analysis of interdependent-decision elements is conducted to clarify the changes of research trends as well as the differences and features of different decision elements in terms of types, structures and information. Then, interdependent-decision analysis methods in the existing literature are classified according to the applicative scenarios. Furthermore, to know the applicable and theoretical values, these methods are compared from the perspectives of principles, innovation and contribution, information processing capabilities and application complexities. Finally, new research opportunities of interdependent-decision analysis methods are discussed.