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2022 | 48 | 100-112

Article title

Dempster–Shafer Theory for Risk Assessment in Project Management

Content

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Abstracts

PL
Project management (PM) involves decision-making processes related to reaching project goals, resources allocation, timelines, intended outputs, outcomes, long-term impacts, etc. Decisions create challenges for those involved in leading and managing projects, such as information overload, time constraints, uncertainty, and biases. Decision-making in PM is especially supported by risk analysis focused on the identification and assessment of factors that could affect (positively or negatively) a successful project delivery. Uncertainty in estimating project risks is considered one of the major challenges in Management Science. The paper draws attention to the root cause of uncertainty in human reasoning in relation to decision-making processes with particular emphasis on risk analysis. A literature review revealed that the area of risk assessment in PM has been dominated by qualitative methods that do not take uncertainty into account. Therefore, the main objective of this paper was to apply the Dempster–Shafer theory (DST), which provides a framework for representing uncertainties by allowing beliefs to not be assigned to a specific subset. Accordingly, the applied research design was employed in this study. The re-search sample included 60 experts that assessed project risks. In order to determine the belief (Bel) and plausibility (Pl) functions, all the evidence was combined using Dempster’s rule of combination, in order to arrive at quantified beliefs. The final results of the study showed that this evidence-based framework for project risk assessment is applicable and easy to use, even for a large number of experts and could support PM practitioners in risk management and decision-making.

Year

Issue

48

Pages

100-112

Physical description

Dates

published
2022

Contributors

  • Jan Kochanowski University in Kielce

References

  • Kremljak, Z. (2011). Risk Management Methods Project Risk. In: B. Katalinic (Ed.), DAAAM International Scientific Book, 10 (pp. 119-132). Publisher DAAAM International Vienna.
  • Labedzka, J., Poteralska, B., & Brozek, K. (2022). Computer-Based Knowledge Management for Futures Literacy, May 12-13, 2022, Vilnius, Lithuania. DOI: 10.3846/bm.2022.808
  • Liu, J., Yang, J.-B., Wang, J., & Sii, H. S. (2002). Review of Uncertainty Reasoning Approaches as Guidance for Maritime and Offshore Safety-Based Assessment. Journal of UK Safety and Reliability Society, 23(1), 63-80.

Document Type

Publication order reference

Identifiers

Biblioteka Nauki
22180856

YADDA identifier

bwmeta1.element.ojs-doi-10_17512_znpcz_2022_4_08
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