Social Network Analysis for an Innovation System Generated Starting from an Agent-Based Simulation Model
The following work presents the results obtained after a Social Network Analysis applied to an innovation system, with the particularity that the system is generated starting from an Agent-Based Simulation model. The main objective of this work is to show that the combination of both methodologies (Social Network Analysis and Agent-Based Simulation) could be successful to obtain new findings and contributes to understanding how the innovation systems conform and behave. The simulation allows to observe how the system emerges and study its behaviors, it shows how the innovation capabilities of the agents condition their relationship and how these relationships determine their adaptation, specialization, their survival over time and the evolution of the network itself. Subsequently, the Social Network Analysis allows to understand the relational structure of the system and how it affects its behavior, the analysis is applied in four moments of time which are separated from each other by five periods, and in each of them different network indicators are analyzed, both at the nodal level and the structural level. The constructed analysis serves as a tool for understanding and guidance to governments for the formulation of policies associated with regional and national innovation systems. Finally, it is shown how, from virtual micro-worlds, important information can be extracted about the dynamics of the innovation systems, thus opening the possibility of answering questions of the type What would happen if ...?