Project portfolio risk prediction and analysis using the random walk method

Xingqi Zou, Qing Yang, Qian Hu, Tao Yao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems
EditorsMarc Demange, Federico Liberatore, Greg H. Parlier
PublisherSciTePress
Pages285-291
Number of pages7
ISBN (Electronic)9789897583520
StatePublished - Jan 1 2019
Event8th International Conference on Operations Research and Enterprise Systems, ICORES 2019 - Prague, Czech Republic
Duration: Feb 19 2019Feb 21 2019

Publication series

NameICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems

Conference

Conference8th International Conference on Operations Research and Enterprise Systems, ICORES 2019
CountryCzech Republic
CityPrague
Period2/19/192/21/19

Fingerprint

Sustainable development
Prediction
Project portfolio
Risk factors
Random walk
Portfolio risk
Managers
Interdependencies
Portfolio management
Project management
Project manager
Sustainability

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Control and Systems Engineering
  • Management Science and Operations Research

Cite this

Zou, X., Yang, Q., Hu, Q., & Yao, T. (2019). Project portfolio risk prediction and analysis using the random walk method. In M. Demange, F. Liberatore, & G. H. Parlier (Eds.), ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems (pp. 285-291). (ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems). SciTePress.
Zou, Xingqi ; Yang, Qing ; Hu, Qian ; Yao, Tao. / Project portfolio risk prediction and analysis using the random walk method. ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems. editor / Marc Demange ; Federico Liberatore ; Greg H. Parlier. SciTePress, 2019. pp. 285-291 (ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems).
@inproceedings{1b48f78546814719b835662514578728,
title = "Project portfolio risk prediction and analysis using the random walk method",
abstract = "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.",
author = "Xingqi Zou and Qing Yang and Qian Hu and Tao Yao",
year = "2019",
month = "1",
day = "1",
language = "English (US)",
series = "ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems",
publisher = "SciTePress",
pages = "285--291",
editor = "Marc Demange and Federico Liberatore and Parlier, {Greg H.}",
booktitle = "ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems",

}

Zou, X, Yang, Q, Hu, Q & Yao, T 2019, Project portfolio risk prediction and analysis using the random walk method. in M Demange, F Liberatore & GH Parlier (eds), ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems. ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems, SciTePress, pp. 285-291, 8th International Conference on Operations Research and Enterprise Systems, ICORES 2019, Prague, Czech Republic, 2/19/19.

Project portfolio risk prediction and analysis using the random walk method. / Zou, Xingqi; Yang, Qing; Hu, Qian; Yao, Tao.

ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems. ed. / Marc Demange; Federico Liberatore; Greg H. Parlier. SciTePress, 2019. p. 285-291 (ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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

PY - 2019/1/1

Y1 - 2019/1/1

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

UR - http://www.scopus.com/inward/citedby.url?scp=85064627130&partnerID=8YFLogxK

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 - Demange, Marc

A2 - Liberatore, Federico

A2 - Parlier, Greg H.

PB - SciTePress

ER -

Zou X, Yang Q, Hu Q, Yao T. Project portfolio risk prediction and analysis using the random walk method. In Demange M, Liberatore F, Parlier GH, editors, ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems. SciTePress. 2019. p. 285-291. (ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems).