TY - GEN
T1 - Project portfolio risk prediction and analysis using the random walk method
AU - Zou, Xingqi
AU - Yang, Qing
AU - Hu, Qian
AU - Yao, Tao
N1 - Funding Information:
This study was supported by the National Natural Science Foundation of China (No. 71472013, 71528005 and 71872011).
Publisher Copyright:
Copyright © 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
PY - 2019
Y1 - 2019
N2 - Based on the interdependency relationship among projects, the paper analyses risk factors in the project portfolio network via the random walk algorithm. Sustainability is one of the most important challenges of the project and portfolio management. This paper analyses the interdependencies among projects in a portfolio from the perspective of sustainable development and builds models to measure the relationship among risk factors via the Multidomain matrix (MDM) method. Using the interdependency relationship among projects and potential relationship between different risk factors as inputs, the paper builds the model of portfolio risk network to predict the risk in the project portfolio via a random walk algorithm. Because the random walk is a personalized recommendation algorithm, so our proposed method can achieve an accurate prediction of portfolio risk through predicting the risk factors and their probabilities in the portfolio. Our method can also help project managers to rank these risk factors in the portfolio through distinguishing the most concerned risks.
AB - Based on the interdependency relationship among projects, the paper analyses risk factors in the project portfolio network via the random walk algorithm. Sustainability is one of the most important challenges of the project and portfolio management. This paper analyses the interdependencies among projects in a portfolio from the perspective of sustainable development and builds models to measure the relationship among risk factors via the Multidomain matrix (MDM) method. Using the interdependency relationship among projects and potential relationship between different risk factors as inputs, the paper builds the model of portfolio risk network to predict the risk in the project portfolio via a random walk algorithm. Because the random walk is a personalized recommendation algorithm, so our proposed method can achieve an accurate prediction of portfolio risk through predicting the risk factors and their probabilities in the portfolio. Our method can also help project managers to rank these risk factors in the portfolio through distinguishing the most concerned risks.
UR - http://www.scopus.com/inward/record.url?scp=85064627130&partnerID=8YFLogxK
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U2 - 10.5220/0007357202850291
DO - 10.5220/0007357202850291
M3 - Conference contribution
AN - SCOPUS:85064627130
T3 - ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems
SP - 285
EP - 291
BT - ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems
A2 - Parlier, Greg H.
A2 - Liberatore, Federico
A2 - Demange, Marc
PB - SciTePress
T2 - 8th International Conference on Operations Research and Enterprise Systems, ICORES 2019
Y2 - 19 February 2019 through 21 February 2019
ER -