Despite academics’ and practitioners’ increasing focus on project portfolio management over the last three decades, very few methods and tools have been proposed for modeling and analyzing interdependencies among projects within a portfolio. This paper proposes the use of a novel approach that integrates three techniques: social network analysis (SNA), fuzzy technique for order of preference by similarity to ideal solution (TOPSIS), and cross-impact matrix multiplication applied to classification (MICMAC). Network mapping provides project managers with a holistic view of interdependencies among projects; fuzzy TOPSIS MICMAC and SNA measures are used to classify projects in terms of their driving power and dependence power and out- and in-degree centrality. This categorization offers a helpful tool for project managers to distinguish among projects and classify them based on their interdependency levels, and thus, aids in identifying critical projects. For the demonstration, the approach is applied to model and analyze interdependencies between projects within a real-life portfolio from the industry. The results of this application show that the proposed approach can serve as a viable and practical means of capturing and analyzing interdependencies among projects within a portfolio.

尽管在过去的三十年中，学者和从业人员越来越重视项目组合管理，但很少有人提出用于建模和分析项目组合中项目之间相互依赖性的方法和工具。本文提出了一种新方法的使用，该方法集成了三种技术：社交网络分析（SNA），通过与理想解决方案的相似性进行偏好排序的模糊技术（TOPSIS），以及应用于分类的互影响矩阵乘法（MICMAC）。网络映射为项目经理提供了项目之间相互依赖关系的整体视图；模糊TOPSIS MICMAC和SNA度量用于根据项目的驱动力和依存力以及度数和度数中心度对项目进行分类。这种分类为项目经理提供了一个有用的工具，可以区分项目并根据项目的相互依赖程度对其进行分类，从而有助于识别关键项目。对于演示，该方法用于对行业中的真实投资组合中的项目之间的相互依赖性进行建模和分析。该应用程序的结果表明，所提出的方法可以用作捕获和分析项目组合中项目之间相互依赖关系的可行且实用的方法。