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dc.contributor.authorOlivares Gil, Alicia 
dc.contributor.authorArnaiz Rodríguez, Adrián
dc.contributor.authorRamírez Sanz, José Miguel 
dc.contributor.authorGarrido Labrador, José Luis 
dc.contributor.authorAhedo García, Virginia 
dc.contributor.authorGarcía Osorio, César 
dc.contributor.authorSantos Martín, José Ignacio 
dc.contributor.authorGalán Ordax, José Manuel 
dc.date.accessioned2022-02-02T10:19:46Z
dc.date.available2022-02-02T10:19:46Z
dc.date.issued2022-01
dc.identifier.urihttp://hdl.handle.net/10259/6385
dc.description.abstractUnderstanding the scientific and social structure of a discipline is a fundamental aspect for scientific evaluation processes, identifying trends and niches, and balancing the trade-off between exploitation and exploration in research. In the present contribution, the production of doctoral theses is used as a proxy to analyze the scientific structure of the knowledge area of business organization in Spain. To that end, a complex networks approach is selected, and two different networks are built: (i) the social network of co-participation in thesis examining committees and thesis supervision, and (ii) a bipartite network of theses and thesis descriptors. The former has a modular structure that is partially explained by thematic specialization in different subdisciplines. The latter serves to assess the interdisciplinary structure of the discipline, as it enables the characterization of affinity levels between fields, research poles and thematic clusters. Our results have implications for the scientific evaluation and formal definition of related fields.en
dc.description.sponsorshipSpanish Ministry of Science, Innovation and Universities (RED2018-102518-T), the Spanish State Research Agency (PID2020-118906GB-I00 and PID2020-119894GB-I00 via AEI/10.13039/501100011033), the Junta de Castilla y León – Consejería de Educación (BU055P20), Fundación La Caixa (2020/00062/001) and from NVIDIA Corporation and its donation of the TITAN Xp GPUs that facilitated this research. This work was partially supported by the European Social Fund, as the authors José Miguel Ramírez-Sanz, José Luis Garrido-Labrador and Alicia Olivares-Gil are the recipient of a predoctoral grant from the Department of Education of Junta de Castilla y León (VA) (ORDEN EDU/875/2021). In addition, this work was also partially supported by the Generalitat Valenciana via its Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, as Adrián Arnaiz is recipicient of a predoctoral grant.en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherUniversitat Politécnica de Valénciaes
dc.relation.ispartofInternational Journal of Production Management and Engineering. 2022, V. 10, n. 1, p. 65-76en
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectComplex networksen
dc.subjectCommunity detectionen
dc.subjectDoctoral thesesen
dc.subjectPattern recognitionen
dc.subjectInterdisciplinarityen
dc.subjectOrganization and management of enterprisesen
dc.subject.otherEmpresas-Gestiónes
dc.subject.otherIndustrial managementen
dc.subject.otherInvestigación científicaes
dc.subject.otherResearchen
dc.titleMapping the scientific structure of organization and management of enterprises using complex networksen
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.4995/ijpme.2022.16666es
dc.identifier.doi10.4995/ijpme.2022.16666
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RED2018-102518-T/ES/SISTEMAS COMPLEJOS SOCIOTECNOLOGICOSes
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-118906GB-I00/ES/INTERACCIONES DINAMICAS DISTRIBUIDAS: PROTOCOLOS BEST EXPERIENCED PAYOFF Y SEPARACION ENDOGENAes
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-119894GB-I00/ES/APRENDIZAJE AUTOMATICO CON DATOS ESCASAMENTE ETIQUETADOS PARA LA INDUSTRIA 4.0es
dc.relation.projectIDinfo:eu-repo/grantAgreement/Junta de Castilla y León//BU055P20//Métodos y Aplicaciones Industriales del Aprendizaje Semisupervisadoes
dc.relation.projectIDinfo:eu-repo/grantAgreement/Fundación Bancaria Caixa d'Estalvis i Pensions de Barcelona//2020%2F00062%2F001es
dc.identifier.essn2340-4876
dc.journal.titleInternational Journal of Production Management and Engineeringen
dc.volume.number10es
dc.issue.number1es
dc.page.initial65es
dc.page.final76es
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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