Abstract
We argue that there is no one-fits-all “smart city” recipe to address the sustainability and socio-economic challenges of our ever-urbanizing world. If smartness is the ability to deliver useful information to citizens and urban actors in order to adapt their behaviors and policies dynamically and interactively in view of a particular social, economic or environmental objectives, we here suggest that each city should not prioritize the same type of information and infrastructure. Because large cities are often seen as centers of innovation and modernity, it is very tempting for urban investors to propose, and for policy makers to follow these investment paths and develop information systems irrespective of the characteristics and size of the city. This potential mismatch may limit the uptake or the most relevant and useful information needed for a city to develop more sustainably and equally. We suggest that smart cities cannot ignore scaling effects nor the evident deviations to these laws. We hence propose to cross tabulate a smart city typology of infrastructure and information with a set of urban archetypes based on key dimensions of cities, including their spatial forms and extents but also their relative positioning within their regional setting, within the urban hierarchy and within their path-dependent trajectories. We see this cross-tabulation as a first step to anchor (big) data realities and smart city practices in geographic knowledge and urban complexity theory. We advocate that tailor-made smart city policies are necessary to monitor and manage cities given their geodiversity.
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Caruso, G., Pumain, D., Thomas, I. (2022). No “Prêt à Porter” but a Multi-scalar Perspective of “Smart Cities”. In: Laurini, R., Nijkamp, P., Kourtit, K., Bouzouina, L. (eds) Knowledge Management for Regional Policymaking. Springer, Cham. https://doi.org/10.1007/978-3-031-15648-9_7
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