Understanding scientific communities: a social network approach to collaborations in Talent Management research.

dc.contributor.authorArroyo Moliner, Liliana
dc.contributor.authorGallardo-Gallardo, Eva
dc.contributor.authorGallo de Puelles, Pedro
dc.date.accessioned2018-05-16T09:57:02Z
dc.date.available2018-05-16T09:57:02Z
dc.date.issued2017-12
dc.date.updated2018-05-16T09:57:02Z
dc.description.abstractResearch on talent management (TM) is an emerging field of study and little is known about the connections among authors in this research community. This paper aims at disclosing the dynamics in TM research by offering a detailed picture of its evolving collaboration networks. By means of social network analysis (SNA), we both show and explain the extent of collaboration, taking articles' co-authorship as an indicator of collaboration. We graphically display how the network builds up throughout time, which has allowed us to examine its main structural characteristics. We analyze the contribution of individual researchers and identify key players in the research network and their characteristics. The co-authorship network is composed by loose and low-density collaborations, mainly consisting in two big components and surrounded by scattered and weak relationships. Two main research perspectives are built and consolidated through time, but they are missing the richness of exchanging ideas among different views. Our results complement recent studies on the dynamics of TM research by offering evidence on how and why collaboration among researchers shapes the current debates on the field. Some basic hypothesis about network indicators are also tested and provide further evidence for the SNA advancement. The findings can be of value in the design of strategies that might improve both system and individual performance.
dc.format.extent24 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec678350
dc.identifier.issn0138-9130
dc.identifier.urihttps://hdl.handle.net/2445/122396
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.isformatofVersió postprint del document publicat a: https://doi.org/10.1007/s11192-017-2537-1
dc.relation.ispartofScientometrics, 2017, vol. 113, num. 3, p. 1439-1462
dc.relation.urihttps://doi.org/10.1007/s11192-017-2537-1
dc.rightscc-by-nc-nd (c) Elsevier B.V., 2017
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es
dc.sourceArticles publicats en revistes (Sociologia)
dc.subject.classificationCerca de talents (Treball)
dc.subject.classificationXarxes socials
dc.subject.classificationPolítica científica
dc.subject.otherTalent identification
dc.subject.otherSocial networks
dc.subject.otherScience and state
dc.titleUnderstanding scientific communities: a social network approach to collaborations in Talent Management research.
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/acceptedVersion

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