Proximity and Innovation: Analyzing the path through topic modeling and business model design

This thesis aims to deepen the relationship between the different forms of proximity that emerge between economic actors and the consequent influence on their innovative capacity. Over the years, this topic has generated a great deal of attention in conference proceedings and scientific publications. The first step to deepen the understanding of this amount of knowledge was to identify a suitable methodology. In so do- ing, the recent advances of the Machine Learning community – particularly Natural Language Processing academics - have offered interesting insights. In particular, "Topic Modeling" was identified as a suitable methodology to bring out latent semantic structures. Therefore, the first chapter tries to study how this methodology has been implemented in the social sciences and, in particular, in management. The contribution offered is a rationalization of the achievable goals and their relationship with evaluation practices. Once clarified how to use this algorithm, the second chapter studied the relationship between proximity and innovation. Using an unsupervised machine learning technique, the research attempts to identify thematic management cores in a multifocal literature such as proximity. Together with a qualitative analysis, the study attempts to bring out the theoretical and empirical contributions offered to the management community. Once the theoretical and empirical expectations have been clarified, the third chapter introduces a strategic theme, namely the business model. This section proposes a mediating effect of the business model concerning the central relationship between proximity and innovation. After a theoretical introduction, the conceptual model is studied with an exploratory approach. Without any presumption of generalizability and completeness, a novel analytical key is offered to open further debate in the community of proximity.