The Micro-level Underpinnings of City Response to the Climate Crisis

The increasing frequency and severity of global disruptions diminish governments’ capacity to effectively serve their constituencies. Many long-standing policies and practices are rapidly becoming obsolete or untenable in the face of technological, environmental, and social shocks, while public demands mount for nimble, responsive policymaking (Head and Alford 2015). The proposed research examines how cities are responding to such disruptions, focusing on the myriad challenges posed by the climate crisis. Cities are a key locus of governance: More than 55 percent of the world’s population currently lives in urban areas, and this number is expected to climb to nearly 70% by 2050 (UN 2018). When a disruption occurs, local decision-makers can react in a range of ways, from doing nothing or making small adjustments at the margins of current practices, to fundamentally changing policy processes and outcomes. These choices have important implications for community health, safety, and quality of life, but we do not know enough about the decision processes that produce these variegated outcomes.

This project seeks to delineate and analyze the networked micro-decision context (NMDC), which is the arena wherein interactions among policy actors shape a government’s decisions about whether and how to tackle a public problem. We leverage and combine insights from political, policy, and network sciences to assess how variations within NMDCs affect the degree of transformativeness of governance responses (Moser and Ekstrom 2010). Understanding how governments respond to challenges that threaten public sector performance directly speaks to the DRMS program’s mission to increase the understanding and effectiveness of decision-making. 

Networked Micro-Decision Context
PI's:Gwen Arnold. Ph.D., UC DavisRachel Krause, Ph.D., University of KansasLe Anh Nguyen Long, Ph.D., University of Twente
The material provided on this website is based upon work supported by the National Science Foundation under Grant No. 2049917.Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.