Mapping the scientific structure of organization and management of enterprises using complex networks

Abstract

Understanding the scientific structure of doctoral research is essential for identifying and evaluating knowledge production. This study examines doctoral theses in the field of Business Organization (Organización de Empresas) in Spain, using complex network analysis of the TESEO database maintained by the Spanish Ministry of Education. By analyzing co-participation in thesis committees across nine UNESCO-classified subdisciplines, we identify modular communities and assess their thematic specialization through normalized entropy measures. Results reveal nine distinct academic communities, with high specialization in Marketing and Advertising and intermediate specialization in other subdisciplines. The network backbone highlights the role of the most active scholars in shaping research lines and committee structures. Additionally, we explore the interdisciplinary composition of the field through bipartite network projections, showing a clear division between quantitative, technology-oriented domains and disciplines linked to sociology and psychology. These findings provide insights into the organization of research communities, the identification of thematic niches, and potential strategies for optimizing faculty allocation and designing diverse, well-balanced evaluation boards.

José Luis Garrido-Labrador

Assistant Lecturer in Computer Languages and Systems

PhD in Machine Learning, researching in semi-supervised learning and restricted set classification. Assistant Lecturer in Computer Languages and Systems at Universidad de Burgos.