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Early-warning performance monitoring system (EPMS) using the business information of a project

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dc.contributor.authorKim, Chang-Won-
dc.contributor.authorYoo, Wi Sung-
dc.contributor.authorLim, Hyunsu-
dc.contributor.authorYu, Ilhan-
dc.contributor.authorCho, Hunhee-
dc.contributor.authorKang, Kyung-In-
dc.date.accessioned2021-09-02T09:15:48Z-
dc.date.available2021-09-02T09:15:48Z-
dc.date.created2021-06-16-
dc.date.issued2018-07-
dc.identifier.issn0263-7863-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/74473-
dc.description.abstractAn early-warning performance monitoring system (EPMS) is proposed to objectively measure and monitor the performance of a project for early detection of inherent poor performance problems. The EPMS is built based on project progress data and consists of a database of business information, an optimized theoretical model used as a performance measurement baseline, and an index for monitoring and forecasting the performance. By monitoring the performance through an application of the EPMS to the Korean construction project, the quarterly variation of index was found to differ by project type. These results could explain the environmental changes in the project execution. Therefore, the EPMS is expected to be an alternative for objective performance monitoring and forecasting while applying the existing methods is difficult because of the limited available data on performance indicators. The development procedures may also be useful to researchers interested in approaches to quantitatively analyze trends in various industries. (C) 2018 Elsevier Ltd, APM and IPMA. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER SCI LTD-
dc.subjectCONSTRUCTION PROJECTS-
dc.subjectGENETIC ALGORITHM-
dc.subjectGROWTH-CURVES-
dc.subjectON-SITE-
dc.subjectMODEL-
dc.titleEarly-warning performance monitoring system (EPMS) using the business information of a project-
dc.typeArticle-
dc.contributor.affiliatedAuthorCho, Hunhee-
dc.contributor.affiliatedAuthorKang, Kyung-In-
dc.identifier.doi10.1016/j.ijproman.2018.03.010-
dc.identifier.scopusid2-s2.0-85045446922-
dc.identifier.wosid000437381900005-
dc.identifier.bibliographicCitationINTERNATIONAL JOURNAL OF PROJECT MANAGEMENT, v.36, no.5, pp.730 - 743-
dc.relation.isPartOfINTERNATIONAL JOURNAL OF PROJECT MANAGEMENT-
dc.citation.titleINTERNATIONAL JOURNAL OF PROJECT MANAGEMENT-
dc.citation.volume36-
dc.citation.number5-
dc.citation.startPage730-
dc.citation.endPage743-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBusiness & Economics-
dc.relation.journalWebOfScienceCategoryManagement-
dc.subject.keywordPlusCONSTRUCTION PROJECTS-
dc.subject.keywordPlusGENETIC ALGORITHM-
dc.subject.keywordPlusGROWTH-CURVES-
dc.subject.keywordPlusON-SITE-
dc.subject.keywordPlusMODEL-
dc.subject.keywordAuthorPerformance monitoring and forecasting-
dc.subject.keywordAuthorEarly-waming system-
dc.subject.keywordAuthorPerformance measurement baseline-
dc.subject.keywordAuthorPerformance index-
dc.subject.keywordAuthorConstruction project types-
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공과대학 (건축사회환경공학부)
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