Public Organization Adaptation to Extreme Events: Evidence from U.S. Transit Agencies
*Names in bold indicate Presenter
Building on the organization learning and adaptation literatures, we first develop an integrated theoretical framework that sheds light on how public organizations make sense of and adapt to growing exposure and vulnerability to extreme weather events. We show that extreme events expose gaps in performance that demonstrate increased organizational vulnerability. Organizational adaptive capacity buffers the extent to which the organization is impacted by extreme events. But it is the perception of environmental risks as a result of repeated exposure and impact that explains decisions to build additional capacity to reduce future vulnerability. Organizational adaptations is not likely to occur when organizations fail to perceive the risks and fail to make sense of the impacts on their system and operations.
Based on a unique dataset from a 2016 national survey of mangers in approximately 200 U.S. transit agencies merged with weather data from National Oceanic and Atmospheric Administration (NOAA), we apply an agent-based model to test hypotheses that link organization experience with extreme weather events, risk perception and adaptive responses. We demonstrate how exposure to extreme events alters an organization’s vulnerability and adaptation behavior overtime. Variations in magnitude and frequency of events are used to model how the organizations’ risk perception and adaptive capacity change. We take a recursive approach to examine how the changes in the adaptive capacity feed into the organization’s performance during future shocks.
Our study extends the literature in several ways. First, compared with a more common event-based approach, this study responds to the call to connect the research on extreme events with organizational theories to enable a more systematic understanding and treatment of extreme events (Roux-Dufort 2007; Fischbacher-Smith 2010; Boin 2016). Second, the combination of survey data, extreme weather data and the simulation methods allows us to generate additional hypotheses about the rate at which organizations adapt to extreme events, the thresholds that trigger adaptive behavior, and how adaptive behavior conditions future performance. Results should inform management about adaptation lags, consequences of inaction and possible opportunities for intervention.