Complex Adaptive Systems and the New Mobilities Paradigm
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In view of the environmental impact of high levels of car use, stimulating people to choose sustainable transport modes instead is of importance. Transport mode choice has proven to be resilient to policy measures. Previous studies suggest qualitative methods do more justice to the complex nature of mobility systems, however the use of such research to policymakers is highly debated. Literature suggests that policymakers prefer quantitative results, and that qualitative studies are needed to investigate the way these results are interpreted and employed. As predictive models become increasingly sophisticated, they can include more aspects of human behavior. Currently, there is only a limited amount of literature on the value of agent-based modeling of mobility systems to policymakers and social scientists. This dissertation investigates the theoretical tangents between complexity theory and the field of transport geography. The starting point for this discussion is the new mobilities paradigm that adopts a view of mobility systems as context dependent, dynamic systems. In addition, this dissertation explores the application of agent-based modeling in the analysis of mode choice behavior. This agent-based model includes socio-economic and behavioral variables. The results suggest that applying complexity theory to transport geography offers promising ways of looking at mobility systems and that concepts of the former field are consistent with recent insights in the latter. In addition, the results suggest that agent-based modeling can be a viable alternative to traditional multinomial logit models. These findings imply that complexity theoretic methods are potentially valuable to policymakers to develop, test and inspire policy measures that contribute to achieving a more sustainable modal split.