Policy adaptations by central governments are often viewed as essential for institutional agility. However, little is known about how often such adaptations should be implemented to improve policy outcomes at the local level, particularly in hierarchical governance settings. To address this gap, we considered policy adaptation frequency as a structural driver of local outcomes, using China’s Business Environment Optimization reform as a case study. Specifically, we constructed an original policy document database and gathered city-level panel data for 253 cities across 31 provinces. Our analysis revealed an inverted U-shaped relationship: moderately frequent adaptation enhanced local policy outcomes, whereas excessively frequent adaptation diminished them. Mechanism analysis indicated that overly frequent adaptation undermines effectiveness by weakening policy goal clarity, overloading policy instruments, and increasing interdepartmental coordination costs. Conceptually, we shifted the focus of policy adaptation research from the traditional questions of ‘why’ and ‘how’ to the often-overlooked dimension of ‘how often.’ Per our findings, we underscore the need to manage the frequency of central interventions to enhance local policy outcomes. Thus, we offer new insights into the dynamic tension between central flexibility and local stability in China’s governance system.
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Chen et al. (2026) studied this question.
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