Project Portfolio Resource Risk Assessment considering Project Interdependency by the Fuzzy Bayesian Network
Resource risk caused by specific resource sharing or competition among projects due to resource constraints is a major issue in project portfolio management, which challenges the application of risk analysis methods effectively. This paper presents a methodology by using a fuzzy Bayesian network to...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/5410978 |
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| _version_ | 1832550097965023232 |
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| author | Libiao Bai Kaimin Zhang Huijing Shi Min An Xiao Han |
| author_facet | Libiao Bai Kaimin Zhang Huijing Shi Min An Xiao Han |
| author_sort | Libiao Bai |
| collection | DOAJ |
| description | Resource risk caused by specific resource sharing or competition among projects due to resource constraints is a major issue in project portfolio management, which challenges the application of risk analysis methods effectively. This paper presents a methodology by using a fuzzy Bayesian network to assess the project portfolio resource risk, determine critical resource risk factors, and propose risk-reduction strategies. In this method, the project portfolio resource risk factors are first identified by taking project interdependency into consideration, and then the Bayesian network model is developed to analyze the risk level of the identified risk factors in which expert judgments and fuzzy set theory are integrated to determine the probabilities of all risk factors to deal with incomplete risk data and information. To reduce the subjectivity of expert judgments, the expert weights are determined by combining experts’ background and reliability degree of expert judgments. A numerical analysis is used to demonstrate the application of the proposed methodology. The results show that project portfolio resource risks can be analyzed effectively and efficiently. Furthermore, “poor communication and cooperation among projects,” “capital difficulty,” and “lack of sharing technology among projects” are considered the leading factors of the project portfolio resource risk. Risk-reduction strategic decisions based on the results of risk assessment can be made, which provide project managers with a useful method or tool to manage project risks. |
| format | Article |
| id | doaj-art-bf1c530e3dc64b9f8cc06576685d644c |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-bf1c530e3dc64b9f8cc06576685d644c2025-02-03T06:07:41ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/54109785410978Project Portfolio Resource Risk Assessment considering Project Interdependency by the Fuzzy Bayesian NetworkLibiao Bai0Kaimin Zhang1Huijing Shi2Min An3Xiao Han4School of Economics and Management, Chang’an University, Xi’an, Shaanxi 710064, ChinaSchool of Economics and Management, Chang’an University, Xi’an, Shaanxi 710064, ChinaSchool of Economics and Management, Chang’an University, Xi’an, Shaanxi 710064, ChinaSchool of Science, Engineering and Environment, University of Salford, Manchester M5 4WT, UKSchool of Economics and Management, Chang’an University, Xi’an, Shaanxi 710064, ChinaResource risk caused by specific resource sharing or competition among projects due to resource constraints is a major issue in project portfolio management, which challenges the application of risk analysis methods effectively. This paper presents a methodology by using a fuzzy Bayesian network to assess the project portfolio resource risk, determine critical resource risk factors, and propose risk-reduction strategies. In this method, the project portfolio resource risk factors are first identified by taking project interdependency into consideration, and then the Bayesian network model is developed to analyze the risk level of the identified risk factors in which expert judgments and fuzzy set theory are integrated to determine the probabilities of all risk factors to deal with incomplete risk data and information. To reduce the subjectivity of expert judgments, the expert weights are determined by combining experts’ background and reliability degree of expert judgments. A numerical analysis is used to demonstrate the application of the proposed methodology. The results show that project portfolio resource risks can be analyzed effectively and efficiently. Furthermore, “poor communication and cooperation among projects,” “capital difficulty,” and “lack of sharing technology among projects” are considered the leading factors of the project portfolio resource risk. Risk-reduction strategic decisions based on the results of risk assessment can be made, which provide project managers with a useful method or tool to manage project risks.http://dx.doi.org/10.1155/2020/5410978 |
| spellingShingle | Libiao Bai Kaimin Zhang Huijing Shi Min An Xiao Han Project Portfolio Resource Risk Assessment considering Project Interdependency by the Fuzzy Bayesian Network Complexity |
| title | Project Portfolio Resource Risk Assessment considering Project Interdependency by the Fuzzy Bayesian Network |
| title_full | Project Portfolio Resource Risk Assessment considering Project Interdependency by the Fuzzy Bayesian Network |
| title_fullStr | Project Portfolio Resource Risk Assessment considering Project Interdependency by the Fuzzy Bayesian Network |
| title_full_unstemmed | Project Portfolio Resource Risk Assessment considering Project Interdependency by the Fuzzy Bayesian Network |
| title_short | Project Portfolio Resource Risk Assessment considering Project Interdependency by the Fuzzy Bayesian Network |
| title_sort | project portfolio resource risk assessment considering project interdependency by the fuzzy bayesian network |
| url | http://dx.doi.org/10.1155/2020/5410978 |
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