Procesos sociales y desarrollo sostenible: un ámbito de aplicación para la ciencia de redes

The starting point of this dissertation is the realization of two facts. On one side, the need of methodologies to develop the research around social aspects of Sustainable Development (SD). Social aspects have been usually underestimated in favour of technical and environmental ones, though being equally (or even more) decisive (Folch, 2005). The second fact is the emergence of a research field focused on the interplay among structure and dynamics, observed in many complex systems (called by some authors “Science of Networks” (Barabasi, 2002)). Within this new field, works dealing with social systems have stood out because of their quantity and relevance. Taking into account this scenario, the objective of this dissertation is to highlight the potentialities of applying tools, concepts and methodologies normally found in the “Science of the Networks” to the analysis of certain social aspects of SD (paying special attention to those ones related to social organization). In order to reach this goal, a succession of steps have been followed: Highlighting the role of social aspects in general and the social organization in particular in SD; Pointing out how the concepts and the methodological tools borrowed from “The Science of Networks” can contribute to the analysis of this aspects; and presenting particular examples of application. Development Among all the available approaches to the SD concept, we have centred on the one that describes the Society and Nature as two interdependent adaptive systems (Antequera et al., 2005), and the different development strategies as interaction mechanisms and flows between them (Jimenez, 2000). Note that, from this viewpoint, it makes sense to analyze how the social organization (seen as an expression of social system’s internal complexity) can condition these interactions between Society and Nature. Regarding the application of the “Science of Networks” to the study of social aspects of SD, we notice two application perspectives: Concepts and tools. From the conceptual viewpoint, certain ideas proposed in the ‘social’ literature about SD (such as the Development at a Human Scale by Max-Neef (1998), or the importance of organization’s size for development (Schumacher, 1973)), can be developed by applying approaches borrowed from the “Science of Networks” (for example, studying the interplay between structure and dynamics at different topological scales). On the other side, certain modelling techniques applied to complex networks can enrich the applications for decision-support and scenarios forecast, which are usually applied in SD research. This enhancement can be especially useful when dealing with highly heterogeneous populations (since the usual homogeneous approaches, based on the mean field, are not adequate in these cases). Finally, the last part of the dissertation presents three concrete examples of application. These works are interesting within the scope of the thesis in a twofold way. First, they are focused on the study of three social processes related to SD: Human cooperation, the resilience of local and regional economic systems, and social cohesion. Second, they provide examples of application of tools from the “Science of networks”, from the reproduction by means of quantitative models of qualitative scenarios presented in previous works, to the development of completely new models combining Game Theory and empirical social networks. Conclusions and extensions Summarizing, this thesis highlights social and organizational aspects of SD, and presents some possibilities of application to study this issue of concepts and methodologies borrowed from the “Science of Networks”. This work could be further developed by increasing the number of application fields (including, for instance, the influence of the social structure over processes of diffusion of ideas and values related with the SD). Another line of development would be the integration of a higher number of tools coming from the “Science of Networks” taking into account its current state of high productivity and continuous presentation of new methodological possibilities.