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Efficient and Sustainable Risk Management in Large Project Portfolios
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. International Institute for Applied Systems Analysis, IIASA, Austria.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. International Institute for Applied Systems Analysis, IIASA, Austria.
2018 (English)In: Perspectives in Business Informatics Research: Proceedings / [ed] Jelena Zdravkovic, Jānis Grabis, Selmin Nurcan, Janis Stirna, Springer, 2018, p. 143-157Conference paper, Published paper (Refereed)
Abstract [en]

In an ever-increasing competitive business environment, it has become increasingly important to be able to obtain efficient and sustainable business operations not only by efficient core procedures but also by being able to minimise losses incurred by risk taking. The latter by handling both operational risks and financial risks in a unified model. This is important not least in businesses that handle sets of simultaneous large projects, which is the topic of risk handling in project portfolios. In this paper, we present a novel method for business risk handling for project portfolios under strong uncertainty. The method is based on event trees representing each adverse consequence modelled, together with mitigation costs and effects. The aggregation of all consequences for all projects together constitutes the risk portfolio for the business. This method is used in one of Sweden’s largest manufacturing enterprises having a vast portfolio of projects in the form of ongoing tenders for orders.

Place, publisher, year, edition, pages
Springer, 2018. p. 143-157
Series
Lecture Notes in Business Information Processing, ISSN 1865-1348, E-ISSN 1865-1356 ; 330
Keywords [en]
Efficient risk analysis, Probability theory, Belief distribution, Sustainable risk management
National Category
Other Computer and Information Science
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-163201DOI: 10.1007/978-3-319-99951-7_10ISBN: 978-3-319-99950-0 (print)ISBN: 978-3-319-99951-7 (electronic)OAI: oai:DiVA.org:su-163201DiVA, id: diva2:1271951
Conference
17th International Conference, BIR 2018, Stockholm, Sweden, September 24-26, 2018
Available from: 2018-12-18 Created: 2018-12-18 Last updated: 2019-01-02Bibliographically approved

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CiteExportLink to record
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