<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-06-05T19:23:58Z</responseDate><request verb="GetRecord" identifier="oai:riubu.ubu.es:10259/4213" metadataPrefix="marc">https://riubu.ubu.es/oai/request</request><GetRecord><record><header><identifier>oai:riubu.ubu.es:10259/4213</identifier><datestamp>2021-11-02T12:04:25Z</datestamp><setSpec>com_10259_3830</setSpec><setSpec>com_10259_5086</setSpec><setSpec>com_10259_2604</setSpec><setSpec>col_10259_4210</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dcterms="http://purl.org/dc/terms/" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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<subfield code="a">Acebes, Fernando</subfield>
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<subfield code="a">Pajares Gutiérrez, Javier</subfield>
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<subfield code="a">Galán Ordax, José Manuel</subfield>
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<subfield code="a">López Paredes, Adolfo</subfield>
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<subfield code="c">2014-03</subfield>
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<subfield code="a">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.</subfield>
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<subfield code="a">1877-0428</subfield>
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<subfield code="a">http://hdl.handle.net/10259/4213</subfield>
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<subfield code="a">10.1016/j.sbspro.2014.03.038</subfield>
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<datafield ind1=" " ind2=" " tag="653">
<subfield code="a">Uncertainty and variability</subfield>
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<subfield code="a">Risk Management</subfield>
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<subfield code="a">Monte Carlo Simulation</subfield>
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<subfield code="a">Criticality</subfield>
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<subfield code="a">Schedule Risk Baseline</subfield>
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<subfield code="a">Exploring the influence of seasonal uncertainty in project risk management</subfield>
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