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Open AccessArticle

Project Portfolio Risk Identification and Analysis, Considering Project Risk Interactions and Using Bayesian Networks

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Project and Construction Management, Faculty of Architecture and Urban Planning, University of Art, Tehran 1136813518, Iran
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Construction and Project Management, University of Tehran, Tehran 1417614418, Iran
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Civil Engineering Faculty, Vilnius Gediminas Technical University, Saulėtekio al. 11, LT 2040 Vilnius, Lithuania
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Author to whom correspondence should be addressed.
Sustainability 2018, 10(5), 1609; https://doi.org/10.3390/su10051609
Received: 18 April 2018 / Revised: 5 May 2018 / Accepted: 9 May 2018 / Published: 17 May 2018
(This article belongs to the Special Issue Sustainability in Construction Engineering)
An organization’s strategic objectives are accomplished through portfolios. However, the materialization of portfolio risks may affect a portfolio’s sustainable success and the achievement of those objectives. Moreover, project interdependencies and cause–effect relationships between risks create complexity for portfolio risk analysis. This paper presents a model using Bayesian network (BN) methodology for modeling and analyzing portfolio risks. To develop this model, first, portfolio-level risks and risks caused by project interdependencies are identified. Then, based on their cause–effect relationships all portfolio risks are organized in a BN. Conditional probability distributions for this network are specified and the Bayesian networks method is used to estimate the probability of portfolio risk. This model was applied to a portfolio of a construction company located in Iran and proved effective in analyzing portfolio risk probability. Furthermore, the model provided valuable information for selecting a portfolio’s projects and making strategic decisions. View Full-Text
Keywords: project portfolio risk; risk interactions; risk analysis; risk identification; Bayesian networks project portfolio risk; risk interactions; risk analysis; risk identification; Bayesian networks
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MDPI and ACS Style

Ghasemi, F.; Sari, M.H.M.; Yousefi, V.; Falsafi, R.; Tamošaitienė, J. Project Portfolio Risk Identification and Analysis, Considering Project Risk Interactions and Using Bayesian Networks. Sustainability 2018, 10, 1609.

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