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Efficient and Susta...
Efficient and Sustainable Risk Management in Large Project Portfolios
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- Danielson, Mats (författare)
- Stockholms universitet,Institutionen för data- och systemvetenskap,International Institute for Applied Systems Analysis, IIASA, Austria
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- Ekenberg, Love (författare)
- Stockholms universitet,Institutionen för data- och systemvetenskap,International Institute for Applied Systems Analysis, IIASA, Austria
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(creator_code:org_t)
- 2018-08-26
- 2018
- Engelska.
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Ingår i: Perspectives in Business Informatics Research. - Cham : Springer. - 9783319999500 - 9783319999517 ; , s. 143-157
- Relaterad länk:
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https://urn.kb.se/re...
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visa fler...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
Nyckelord
- Efficient risk analysis
- Probability theory
- Belief distribution
- Sustainable risk management
- Computer and Systems Sciences
- data- och systemvetenskap
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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