2026-04-20T06:31:15Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/63852024-05-15T07:33:45Zcom_10259_6336com_10259_6335com_10259.4_106com_10259_2604com_10259_4219com_10259_5086com_10259_3830col_10259_6337col_10259_4220col_10259_3832

Olivares Gil, Alicia Arnaiz Rodríguez, Adrián Ramírez Sanz, José Miguel Garrido Labrador, José Luis Ahedo García, Virginia García Osorio, César Santos Martín, José Ignacio Galán Ordax, José Manuel 2022-02-02T10:19:46Z 2022-02-02T10:19:46Z 2022-01 http://hdl.handle.net/10259/6385 10.4995/ijpme.2022.16666 2340-4876 Understanding 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. Spanish 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. application/pdf eng Universitat Politécnica de Valéncia International Journal of Production Management and Engineering. 2022, V. 10, n. 1, p. 65-76 https://doi.org/10.4995/ijpme.2022.16666 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RED2018-102518-T/ES/SISTEMAS COMPLEJOS SOCIOTECNOLOGICOS info: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 ENDOGENA info: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 4.0 info:eu-repo/grantAgreement/Junta de Castilla y León//BU055P20//Métodos y Aplicaciones Industriales del Aprendizaje Semisupervisado info:eu-repo/grantAgreement/Fundación Bancaria Caixa d'Estalvis i Pensions de Barcelona//2020%2F00062%2F001 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess Complex networks Community detection Doctoral theses Pattern recognition Interdisciplinarity Organization and management of enterprises Gestión de empresas Investigación Industrial management Research Mapping the scientific structure of organization and management of enterprises using complex networks info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion International Journal of Production Management and Engineering 10 1 65 76