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dc.contributor.authorBallesteros-Pérez, Pablo
dc.contributor.authorCerezo-Narváez, Alberto
dc.contributor.authorOtero-Mateo, Manuel
dc.contributor.authorPastor-Fernández, Andrés
dc.contributor.authorVanhoucke, Mario
dc.date.accessioned2020-12-02T10:51:47Z
dc.date.available2020-12-02T10:51:47Z
dc.date.issued2019en_US
dc.identifier.issn0926-5805
dc.identifier.doi10.1016/j.autcon.2019.102906
dc.identifier.urihttp://hdl.handle.net/20.500.12127/6598
dc.description.abstractIn Schedule Risk Analysis (SRA), activity sensitivity metrics measure the importance of activities in a project schedule. Highly sensitive activities are those more likely to increase project duration variability and/or cause project duration extensions. Several activity sensitivity metrics have been proposed over the years, but a comparison of all of them has never been made. This has made it difficult to know which metrics perform better and under what circumstances. In this paper, an extensive comparison of all relevant SRA activity sensitivity metrics is performed using a set of 4100 artificial projects. Unlike previous studies, the comparison framework is decoupled from corrective actions (e.g. activity crashing) which allows the merits of each metric to be assessed individually. Additionally, a new metric that performs better for overall sensitivity ranking is proposed. Results show that most sensitivity metrics do not perform well unless they are applied iteratively (the sensitivity of the remaining scheduled activities has to be recalculated whenever the duration variability of at least one activity has been restricted). However, if applied iteratively, most metrics can enhance project monitoring and control, while significantly shortening project duration.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectSchedulingen_US
dc.subjectSchedule Risk Analysisen_US
dc.subjectActivity Sensitivityen_US
dc.subjectProject Delaysen_US
dc.subjectProject Controlen_US
dc.titlePerformance comparison of activity sensitivity metrics in schedule risk analysisen_US
dc.identifier.journalAutomation in Constructionen_US
dc.source.volume106en_US
dc.source.issueOctoberen_US
dc.source.beginpage68
dc.source.endpage78
dc.contributor.departmentDpto. de Ingeniería Mecánica y Diseño Industrial, Escuela Superior de Ingeniería, Universidad de Cádiz, Avda. Universidad de Cádiz 10, Puerto Real, 11519 Cádiz, Spainen_US
dc.contributor.departmentGhent University, Tweekerkenstraat 2, 9000 Gent, Belgiumen_US
dc.contributor.departmentUCL School of Management, University College London, 1 Canada Square, London E14 5AA, UKen_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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