The application of risk management strategies is a common approach in emergency response scenarios. However, scant knowledge exists regarding its utilization in the specific context of an outbreak, both theoretically and practically. This study delves into the realm of risk management during the COVID-19 pandemic, focusing on four key measurements: risk avoidance (RA), risk reduction (RD), risk transfer (RT), and risk retention (RR). Using 800 valid responses collected from 31 provinces across China between August 1 and September 30, 2020, this study investigates spatial disparities in individuals’ intentions towards risk management. To achieve this, an extended version of the Theory of Planned Behavior (E-TPB) is applied. The Structural Equation Model’s path analyses revealed several findings: (1) discernible spatial disparities in RR, RA, and RD intentions between large and small cities; (2) RD and RR intentions were significantly associated with attitude, subjective norm, perceived behavioral control, and risk perception; (3) RA and RT intentions were significantly associated with attitude and risk perception; (4) risk perception exihibiting both direct and indirect effects on RA and RR intentions. This study contributs to the urban studies literature by extending the theoretical framework of risk management in the context of COVID-19. It enhances the measurement tools employed in the TPB model and scrutinizes spatial disparities in the adoption of preventative measures against COVID-19. The findings underscore the importance for local policymakers to consider geographical differences when formulating effective strategies for COVID-19 prevention.
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