Data-driven traffic management on the last mile: understanding manufacturing industry in smart city ecosystems

We identify interdependencies in cities as complex systems to determine which data-driven traffic management solutions have the highest impact and where they should be applied. To address this, we present a systematic approach to evaluate key variables of both an industry and city ecosystem by using approaches from Vester’s sensitivity model. We apply our research in the context of a German city and focus on how the supply chains of manufacturers can be secured on the ‘last mile’ with data-driven traffic applications as part of an industry ecosystem within a city ecosystem. Using a qualitative approach that involves interviews, we apply our findings to a criteria matrix and enrich it with insights from our study participants. We therefore demonstrate how a participative approach can help in deriving relevant variables for complex systems. With our research we contribute to the theory of complex systems and ecosystems while providing results from practice.