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dc.contributor.authorGuan, Xin
dc.contributor.authorServranckx, Tom
dc.contributor.authorVanhoucke, Mario
dc.date.accessioned2021-09-22T09:15:46Z
dc.date.available2021-09-22T09:15:46Z
dc.date.issued2021en_US
dc.identifier.issn0360-8352
dc.identifier.doi10.1016/j.cie.2021.107657
dc.identifier.urihttp://hdl.handle.net/20.500.12127/6970
dc.description.abstractRisk is inherent and inevitable during project execution. Its occurrence often has an adverse impact on the project or even leads to project failure. In order to ensure the successful project completion, risk prevention used for reducing the risk probability and risk protection used for reducing the risk loss should be considered. Given the different effects and costs of these two strategies and the limited project budget, project managers should be able to reasonably divide the budget among these two strategies. This study proposes a budget allocation method consisting of three modules for mitigating the project risks. First, we model the relation between the effect and cost of each strategy as linear and non-linear relations. Second, two mathematical models are built and the corresponding analytical solutions are obtained. Afterwards, a three-step procedure for budget allocation is proposed. To validate the analytical results and investigate the impacts of the characteristics of the project risk and response on the optimal budget allocation, numerical experiments are conducted and managerial insights are drawn. Finally, the budget allocation model is extended with multiple risks, secondary risk and risk transfer, and validated using an empirical analysis.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectBudget Allocationen_US
dc.subjectRisk Preventionen_US
dc.subjectRisk Protectionen_US
dc.subjectAnalytical Solutionen_US
dc.subjectProject Risk Managementen_US
dc.titleAn analytical model for budget allocation in risk prevention and risk protectionen_US
dc.identifier.journalComputers & Industrial Engineeringen_US
dc.source.volume161en_US
dc.source.issueNovemberen_US
dc.contributor.departmentFaculty of Economics and Business Administration, Ghent University, Tweekerkenstraat 2, 9000 Ghent, Belgiumen_US
dc.contributor.departmentUniversity College London, Canada Square 1, London E14 5AA, United Kingdomen_US
vlerick.knowledgedomainOperations & Supply Chain Managementen_US
vlerick.typearticleJournal article with impact factoren_US
vlerick.vlerickdepartmentTOMen_US
dc.identifier.vperid58614en_US


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