Publication:
A Multi-Criteria Decision Model for Architecturing Competence in Human Performance Technology

dc.contributor.authorsErensal, Yasemin C.; Gurbuz, Tuncay; Albayrak, Y. Esra
dc.date.accessioned2022-03-12T17:48:13Z
dc.date.accessioned2026-01-11T14:10:19Z
dc.date.available2022-03-12T17:48:13Z
dc.date.issued2010
dc.description.abstractIn a continuously changing environment, like globalization, technological innovation, restructuring and outsourcing, organizations can no longer cope without continually developing their competencies and human resources. As a result academic research and company practices have actively started to develop decision making models in operation and practices to meet toughening competence demands that, moreover, need to be developed at an ever faster pace. In this research paper, we bring together several processes and components in order to provide a comprehensive overview in search for conceptual representations designed to support and develop organizational competence mapping at the individual and organizational level. According to recent research, as a decision making tool Analytic Network Process (ANP) methodology may mitigate the elusiveness of the architecturing competence concept by assisting to determine the importance of criteria and selecting the best alternative between competency models.
dc.identifier.doidoiWOS:000285930800012
dc.identifier.eissn1875-6883
dc.identifier.issn1875-6891
dc.identifier.urihttps://hdl.handle.net/11424/229916
dc.identifier.wosWOS:000285930800012
dc.language.isoeng
dc.publisherATLANTIS PRESS
dc.relation.ispartofINTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectHuman Performance Technology
dc.subjectArchitecture of Competence
dc.subjectMCDM
dc.subjectAnalytic Network Process
dc.subjectCORE COMPETENCES
dc.subjectSELECTION
dc.subjectINDUSTRY
dc.subjectSUCCESS
dc.subjectSYSTEMS
dc.titleA Multi-Criteria Decision Model for Architecturing Competence in Human Performance Technology
dc.typearticle
dspace.entity.typePublication
oaire.citation.endPage831
oaire.citation.issue6
oaire.citation.startPage815
oaire.citation.titleINTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
oaire.citation.volume3

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