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项目组合中外部利益相关者风险应对策略的选择

External stakeholder risk response strategies selection in project portfolio.

作者信息

Bai Libiao, Kang Shuyun, Li Fang, Zhang Ziwen, Li Jiayu, Luo Xixi

机构信息

School of Economics and Management, Chang' an Univ, Xi'an, Shaanxi, 710064, China.

出版信息

Heliyon. 2024 May 22;10(11):e31709. doi: 10.1016/j.heliyon.2024.e31709. eCollection 2024 Jun 15.

Abstract

To improve the effectiveness of external stakeholder risks (ESRs) management in project portfolios (PPs), a portfolio-wide risk response approach is required. However, current research is inadequate to effectively identify response strategies for ESRs, which brings challenges to managing ESRs in PPs. In this context, the purpose of this study is to select an appropriate combination of response strategies for ESRs by considering interactions among ESRs, projects, and response strategies in the PP. A Bayesian influence diagram (BID) coupled with a multi-objective optimization model is deemed suitable for this context. Firstly, a probability-sensitivity matrix is established to determine the key ESRs. Then, a BID is constructed to calculate the expected values of different combinations of response strategies. Finally, integrating stakeholder satisfaction and strategy cost, an optimization model for risk response strategy selection is established to obtain candidate combinations. By combining expected values and candidate combinations, the optimal strategy combination is selected. The proposed model comprehensively considers and evaluates the interactions between risks, projects, and risk responses. This enhances the desirability of expected outcomes and reduces project execution costs.

摘要

为提高项目组合中外部利益相关者风险(ESR)管理的有效性,需要一种全项目组合的风险应对方法。然而,当前的研究不足以有效识别ESR的应对策略,这给项目组合中的ESR管理带来了挑战。在此背景下,本研究的目的是通过考虑项目组合中ESR、项目和应对策略之间的相互作用,为ESR选择合适的应对策略组合。贝叶斯影响图(BID)与多目标优化模型相结合被认为适用于此背景。首先,建立概率敏感性矩阵以确定关键ESR。然后,构建BID以计算应对策略不同组合的期望值。最后,综合考虑利益相关者满意度和策略成本,建立风险应对策略选择优化模型以获得候选组合。通过结合期望值和候选组合,选择最优策略组合。所提出的模型全面考虑并评估了风险、项目和风险应对之间的相互作用。这提高了预期结果的可取性并降低了项目执行成本。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9567/11153191/72716effb82a/gr1.jpg

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