Beyond temporary measures: How experiential learning in street experiments shapes urban mobility transitions

Zhao, Kristen J ORCID: https://orcid.org/0000-0002-4251-5462 and Sun, Guibo (2025) Beyond temporary measures: How experiential learning in street experiments shapes urban mobility transitions. Environmental Innovation and Societal Transitions, 57. 101007. ISSN 2210-4224

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Abstract

Tactical urbanism aims to rapidly transform urban environments through iterative experimentation. However, we know little about how learning shapes the long-term effectiveness and transformative potential of these interventions. This paper examines the role of local government implementers’ learning in sustaining tactical urbanism practices, specifically through the lens of street experiments implemented during the COVID-19 pandemic. Using experiential learning theory as a conceptual framework, we conducted and analysed interviews with 40 government representatives associated with 28 street experiments across 21 cities globally. Our analysis reveals three distinct learning processes among the implementers, arranged progressively: (1) implement and execute, (2) experiment and perpetuate, and (3) experiment and conceptualise. While implementers engaging primarily in the first two processes demonstrated responsiveness by leveraging tactical urbanism during systemic disruptions, they rarely generated transferable knowledge or sustained transformative impacts. By contrast, implementers who adopted the third approach – experiment and conceptualise – actively reflected on and generalised their experiences, leading to deeper learning and structural changes. These implementers effectively harnessed street experiments as catalysts for broader urban mobility transitions. By providing empirical evidence from diverse global contexts, this study advances our understanding of how learning processes influence the development of tactical urbanism projects. These insights could assist urban practitioners in seeking to embed meaningful, lasting change in urban mobility through iterative experimentation.