业务
制度分析
自然资源经济学
环境资源管理
激励
气候变化
环境规划
适应能力
环境经济学
经济
环境科学
生态学
社会科学
社会学
生物
微观经济学
标识
DOI:10.1016/j.jenvman.2023.118292
摘要
Unrestrained human industrial and agricultural production activities exacerbate climate change and environmental pollution. Climate change leads to an increase in flood risks and the spread of water and soil pollution, resulting in challenges in urban stormwater management. Institutional adaptation to climate change is vital for realizing effective local urban stormwater management. However, the accumulated knowledge on climate adaptation over the past decade has been concentrated at the technical and economic levels, with limited research on institutional adaptation. The Sponge City Program in China selects 30 pilot cities to promote a novel stormwater management approach that combines the reliability of traditional gray infrastructures made of concrete materials with the adaptability and sustainability of green-blue infrastructures based on natural-based solutions, but the extent of institutional adaptation in this process varies considerably across pilot cities. To explain what drives institutional adaptation, a configurational analysis of pilot cities is conducted using the fuzzy-set qualitative comparative analysis method. Based on data from 628 official reports and 36 interviews, we demonstrate local governments are significant institutional entrepreneurs, and high institutional adaptation occurs with the combined effects of institutional capacity, financial resources, and reputational incentives. There are three types of paths driving institutional adaptation: "strong institutional capacity-strong financial resource-low reputational reserve," "strong institutional capacity-strong financial resource-high reputational competition," and "strong institutional capacity-weak financial resource-low reputational reserve." These three paths account for 72% of the instances of high institutional adaptation outcomes, and 90% of cases share a given configuration of conditions associated with an outcome. Our conclusion advances a theoretical understanding of the drivers of institutional adaptation and provides guidelines for future climate adaptation practices.
科研通智能强力驱动
Strongly Powered by AbleSci AI