Emergent entrepreneurial networks for the transition to automated urban mobility

Abstract

Simulation models show significant benefits can accrue to cities from integrating shared, automated, electric vehicles into an optimized mobility system. Gains include reduced air pollution, lower carbon emissions, reduced traffic congestion, and more green space. Yet the current enthusiasm for such visionary systems ignores the transition period, the time during which AV must share limited road space with human-driven vehicles. Such social-technical transitions are marked by great uncertainty regarding technology performance, legal/regulatory acceptance, and customer preference. This, in turn, creates a high-risk business environment for entrepreneurs and corporate innovators. Emergent entrepreneurial networks are uniquely suited to managing the risk and accelerating the transition to fully optimized urban mobility systems. These combine the skills of entrepreneurs and corporate innovators into highly adaptable, learning-based networks. We can observe 4 distinct models for these networks emerging into the urban mobility market. A better understanding of the competition among these models can inform national policies promoting shared, automated electric mobility service. We propose a case-learning process through which the needed understanding can be achieved.