Alicia Olivares-Gil1, Adrián Arnaiz-Rodríguez1, José Miguel Ramírez-Sanz1, José
Alicia Olivares-Gil1, Adrián Arnaiz-Rodríguez1, José Miguel Ramírez-Sanz1, José Luis Garrido-Labrador1, Virginia Ahedo2, César García-Osorio1 , José Ignacio Santos2 and José Manuel Galán2
1 Universidad de Burgos, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Ed. A1, Avda. Cantabria s/n 09006, Spain
2 Universidad de Burgos, Departamento de Ingeniería de Organización, Escuela Politécnica Superior, Ed. A1, Avda. Cantabria s/n 09006, Spain
<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>Keywords: Complex networks, community detection, doctoral theses, pattern recognition, interdisciplinarity, Organization and management of enterprises.
Understanding the scientific structure is a fundamental step in identifying and evaluating scientific production [1]. Among the different options and tools available for analysis, doctoral theses are particularly interesting. Doctoral work usually entails more investment and effort than other scientific products that may have a more exceptional and opportunistic approach. This characteristic makes its analysis very relevant for establishing robust research lines and trends. Moreover, in the case of Spain, the influence of thesis supervisors in proposing the committees allows us to understand the academic structure of the different scientific fields and, at the same time, the social structure on which they are supported.
In this work, we analyze the scientific structure of doctoral theses in the knowledge area of business organization —Organización de empresas— in Spain. We use complex network analysis [2] on the TESEO database maintained by the Spanish Ministry of Education, Culture and Sports (https://www.educacion.gob.es/teseo). Previous studies in this field have shown that participation in thesis committees has a modular structure and a strongly unequal degree distribution compatible with a truncated power-law [3].
We have retrieved all the theses assigned to one or more of the nine subdisciplines in which knowledge in Organization and management of enterprises is specialized (i.e., Sales Management, Industry Studies, Manpower Management, Financial Management, Operations Research, Marketing, Optimum Production Levels, Organization of Production and Advertising) according to the UNESCO 6-digit codes [4]. The communities found on co-participation in doctoral thesis committees combined with the thematic information of each thesis have allowed us to identify the level of thematic specialization of each scientific community. The network backbone, focused on the most active scholars in the field, shows nine different communities. The average profile of each group has been calculated from the specific doctoral experience of each researcher. The level of specialization of each community has been estimated using the normalized entropy of the subdisciplines distribution. The analysis shows highly specialized academic groups in the