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dc.contributor.authorAndré de Andrade, Paulo
dc.contributor.authorVanhoucke, Mario
dc.contributor.authorMartens, Annelies
dc.date.accessioned2024-06-10T14:23:49Z
dc.date.available2024-06-10T14:23:49Z
dc.date.issued2024en_US
dc.identifier.issn0254-5330
dc.identifier.doi10.1007/s10479-023-05269-7
dc.identifier.urihttp://hdl.handle.net/20.500.12127/7491
dc.description.abstractForecasting an ongoing project’s actual duration is an essential aspect of project management which received considerable attention in the research community. In studies using Earned Value Management forecasting, it has been argued that the network topology is a driver to indicate the accuracy of these forecasts. However, a new project indicator has been recently defined, i.e. the project regularity, which reflects the value accrue according to the plan. It has shown to outperform the serial/parallel network topology indicator in specifying the accuracy of project forecasts. This paper introduces a novel way to define the project regularity, which provides project managers with an improved indication of the expected forecasting accuracy for their projects. The study is carried out on an empirical database consisting of 100 projects from different sectors, and the results are compared to the academic literature. The experiments show that the new indicator provides a better categorisation compared to the existing approaches. Further, they have shown that the ability of project categorisers to indicate the expected forecasting accuracy is affected by industry sector and project size.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectProject Managementen_US
dc.subjectProject Forecastingen_US
dc.subjectEarned Value Managementen_US
dc.subjectForecasting Accuracyen_US
dc.subjectEmpirical Databaseen_US
dc.subjectProject Regularityen_US
dc.subjectEarned Duration Managementen_US
dc.titleAn empirical project forecasting accuracy framework using project regularityen_US
dc.identifier.journalAnnals of Operations Researchen_US
dc.source.volume337en_US
dc.source.beginpage501en_US
dc.source.endpage521en_US
dc.contributor.departmentTechisa do Brasil, Av. Malibu, 260 (2/901), Barra da Tijuca, Rio de Janeiro, 22.793-295, Brazilen_US
dc.contributor.departmentFaculty of Economics and Business Administration, Ghent University, Tweekerkenstraat 2, 9000, Ghent, Belgiumen_US
dc.contributor.departmentUCL School of Management, University College London, 1 Canada Square, London, E14 5AA, UKen_US
dc.contributor.departmentFaculty of Economics and Business Administration, Ghent University, Tweekerkenstraat 2, 9000, Ghent, Belgiumen_US
dc.identifier.eissn1572-9338
vlerick.knowledgedomainOperations & Supply Chain Managementen_US
vlerick.typearticleJournal article with impact factoren_US
vlerick.vlerickdepartmentTOMen_US
dc.identifier.vperid58614en_US


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