2026-06-05T19:23:23Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/42132021-11-02T12:04:25Zcom_10259_3830com_10259_5086com_10259_2604col_10259_4210

Exploring the influence of seasonal uncertainty in project risk management Acebes, Fernando Pajares Gutiérrez, Javier Galán Ordax, José Manuel López Paredes, Adolfo Uncertainty and variability Risk Management Monte Carlo Simulation Criticality Schedule Risk Baseline For years, many research studies have focused on programming projects, assuming a deterministic environment and complete task information. However, during the project performance, schedule may be subject to uncertainty which can lead to significant modifications. This fact has led to an increasing scientific literature in the field. In this article we consider the presence of an uncertainty of seasonal type (e.g. meteorological) that affects some of the activities that comprise the project. We discuss how the project risk can be affected by such uncertainty, depending on the start date of the project. By means of Monte Carlo simulation, we compute the statistical distribution functions of project duration at the end of the project. Then, we represent the variability of the project through the so-called Project Risk Baseline. In addition, we examine various sensitivity metrics - Criticality, Cruciality, Schedule Sensitivity Index -. We use them to prioritize each one of the activities of the project depending on its start date. In the last part of the study we demonstrate the relative importance of project tasks must consider a combined version of these three sensitivity measures. 2016-08-31T10:37:46Z 2016-08-31T10:37:46Z 2016-08-31T10:37:46Z 2014-03 info:eu-repo/semantics/conferenceObject 1877-0428 http://hdl.handle.net/10259/4213 10.1016/j.sbspro.2014.03.038 eng Procedia - Social and Behavioral Sciences. 2014, V. 119, p. 329-338 http://dx.doi.org/10.1016/j.sbspro.2014.03.038 info:eu-repo/grantAgreement/JCyL/VA056A12-2 http://creativecommons.org/licenses/by-nc-nd/3.0 info:eu-repo/semantics/openAccess Attribution-NonCommercial-NoDerivs 3.0 Unported Elsevier