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<dc:title>Exploring the influence of seasonal uncertainty in project risk management</dc:title>
<dc:creator>Acebes, Fernando</dc:creator>
<dc:creator>Pajares Gutiérrez, Javier</dc:creator>
<dc:creator>Galán Ordax, José Manuel</dc:creator>
<dc:creator>López Paredes, Adolfo</dc:creator>
<dc:subject>Uncertainty and variability</dc:subject>
<dc:subject>Risk Management</dc:subject>
<dc:subject>Monte Carlo Simulation</dc:subject>
<dc:subject>Criticality</dc:subject>
<dc:subject>Schedule Risk Baseline</dc:subject>
<dc:description>27th IPMA World Congress</dc:description>
<dc:description>For years, many research studies have focused on programming projects, assuming a deterministic environment and complete&#xd;
task information. However, during the project performance, schedule may be subject to uncertainty which can lead to&#xd;
significant modifications. This fact has led to an increasing scientific literature in the field. In this article we consider the&#xd;
presence of an uncertainty of seasonal type (e.g. meteorological) that affects some of the activities that comprise the project. We&#xd;
discuss how the project risk can be affected by such uncertainty, depending on the start date of the project. By means of Monte&#xd;
Carlo simulation, we compute the statistical distribution functions of project duration at the end of the project. Then, we&#xd;
represent the variability of the project through the so-called Project Risk Baseline.&#xd;
In addition, we examine various sensitivity metrics - Criticality, Cruciality, Schedule Sensitivity Index -. We use them to&#xd;
prioritize each one of the activities of the project depending on its start date. In the last part of the study we demonstrate the&#xd;
relative importance of project tasks must consider a combined version of these three sensitivity measures.</dc:description>
<dc:date>2016-08-31T10:37:46Z</dc:date>
<dc:date>2016-08-31T10:37:46Z</dc:date>
<dc:date>2014-03</dc:date>
<dc:type>info:eu-repo/semantics/conferenceObject</dc:type>
<dc:identifier>1877-0428</dc:identifier>
<dc:identifier>http://hdl.handle.net/10259/4213</dc:identifier>
<dc:identifier>10.1016/j.sbspro.2014.03.038</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>Procedia - Social and Behavioral Sciences. 2014, V. 119, p. 329-338</dc:relation>
<dc:relation>http://dx.doi.org/10.1016/j.sbspro.2014.03.038</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/JCyL/VA056A12-2</dc:relation>
<dc:rights>http://creativecommons.org/licenses/by-nc-nd/3.0</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:rights>Attribution-NonCommercial-NoDerivs 3.0 Unported</dc:rights>
<dc:publisher>Elsevier</dc:publisher>
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