2026-04-20T09:40:21Zhttps://riubu.ubu.es/oai/requestoai: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
2022-02-02T10:19:46Z
urn:hdl:10259/6385
Mapping the scientific structure of organization and management of enterprises using complex networks
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
Complex networks
Community detection
Doctoral theses
Pattern recognition
Interdisciplinarity
Organization and management of enterprises
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.
2022-02-02T10:19:46Z
2022-02-02T10:19:46Z
2022-01
info:eu-repo/semantics/article
http://hdl.handle.net/10259/6385
10.4995/ijpme.2022.16666
2340-4876
eng
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
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Universitat Politécnica de Valéncia