https://doi.org/10.1140/epjs/s11734-022-00470-4
Regular Article
Detecting contagious spreading of urban innovations on the global city network
1
Earth System Analysis, Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14473, Potsdam, Germany
2
Institute for Physics and Astronomy, University of Potsdam, 14476, Potsdam, Germany
3
Institute for Theoretical Biology, Department of Biology, Humboldt University of Berlin, 10115, Berlin, Germany
4
Bernstein Center for Computational Neuroscience, Humboldt University of Berlin, 10115, Berlin, Germany
5
Stockholm Resilience Centre, Stockholm University, 10691, Stockholm, Sweden
6
High Meadows Environmental Institute, Princeton University, 08544, Princeton, NJ, USA
7
Germany Science of Intelligence, Research Cluster of Excellence, Marchstr. 23, 10587, Berlin, Germany
Received:
4
November
2021
Accepted:
28
January
2022
Published online:
21
February
2022
Only a fast and global transformation towards decarbonization and sustainability can keep the Earth in a civilization-friendly state. As hotspots for (green) innovation and experimentation, cities could play an important role in this transition. They are also known to profit from each other’s ideas, with policy and technology innovations spreading to other cities. In this way, cities can be conceptualized as nodes in a globe-spanning learning network. The dynamics of this process are important for society’s response to climate change and other challenges, but remain poorly understood on a macroscopic level. In this contribution, we develop an approach to identify whether network-based complex contagion effects are a feature of sustainability policy adoption by cities, based on dose-response contagion and surrogate data models. We apply this methodology to an exemplary data set, comprising empirical data on the spreading of a public transport innovation (Bus Rapid Transit Systems) and a global inter-city connection network based on scheduled flight routes. Although our approach is not able to identify detailed mechanisms, our results point towards a contagious spreading process, and cannot be explained by either the network structure or the increase in global adoption rate alone. Further research on the role of a city’s abstract “global neighborhood” regarding its policy and innovation decisions is thus both needed and promising, and may connect with research on social tipping processes. The methodology is generic, and can be used to compare the predictive power for innovation spreading of different kinds of inter-city network connections, e.g. via transport links, trade, or co-membership in political networks.
© The Author(s) 2022
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