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dc.contributor.authorBatselier, Jordy
dc.contributor.authorVanhoucke, Mario
dc.date.accessioned2017-12-02T14:53:20Z
dc.date.available2017-12-02T14:53:20Z
dc.date.issued2015
dc.identifier.doi10.1061/(ASCE)CO.1943-7862.0001008
dc.identifier.urihttp://hdl.handle.net/20.500.12127/5255
dc.description.abstractThe ability to accurately forecast a project's final duration and cost is essential to successful project management. The technique of earned value management (EVM) is considered to provide an effective methodology for obtaining such forecasts, however, this has not yet been adequately tested on empirical data. Therefore, the accuracy of the most commonly used EVM time and cost forecasting methods is evaluated on a diverse and qualitative database consisting of 51 real-life projects. As most projects originate from the construction industry, an explicit focus on these construction projects is provided. Moreover, the desired real forecasting outcomes based on the actual project progress data are also supported by a Monte Carlo simulation study. It is demonstrated that highly accurate time and cost forecasts can be obtained by applying the EVM methodology. Furthermore, the best performing forecasting methods for the projects in the considered database are identified, also taking into account timeliness and the influence of the project network structure.
dc.language.isoen
dc.subjectDatabases
dc.subjectValue Engineering
dc.subjectEmpirical Equations
dc.subjectManagement Methods
dc.subjectProject Management
dc.subjectForecasting
dc.subjectInformation management
dc.subjectConstruction Costs
dc.titleEmpirical Evaluation of Earned Value Management Forecasting Accuracy for Time and Cost
dc.identifier.journalJournal of Construction Engineering and Management
dc.source.volume141
dc.source.issue11
dc.source.beginpage1
dc.source.endpage13
vlerick.knowledgedomainOperations & Supply Chain Management
vlerick.typearticleJournal article with impact factor
vlerick.vlerickdepartmentTOM
dc.identifier.vperid177000
dc.identifier.vperid58614
dc.identifier.vpubid6506


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