ABSTRACT Policy termination remains one of the least developed areas in policy process research, particularly outside Western contexts. This study investigates the widespread termination of science and technology awards across China's prefectural‐level cities beginning in 2017. Building on policy termination theory, we develop a framework that highlights the roles of program effectiveness, fiscal constraints, leadership incentives, and intergovernmental diffusion. We hypothesize that higher static effectiveness increases the likelihood of termination, while higher relative and dynamic effectiveness decreases it. We further propose that fiscal constraints, leadership turnover, leaders' second term, and regional diffusion are positively associated with policy termination. Using Cox proportional hazards models on an original panel dataset of 281 prefectural cities from 2017 to 2023, we find that higher static effectiveness and mayors' second‐term status are associated with a greater likelihood of termination, whereas higher relative effectiveness is associated with a lower risk. Termination also diffuses primarily within provincial boundaries. Contrary to expectations, dynamic effectiveness, fiscal constraints, and leadership turnover show no significant effects. By providing the first large‐N city‐level quantitative analysis of policy termination outside the Western system, this study extends termination theory by highlighting the role of performance evaluation, leadership incentives, and hierarchical dynamics.
Xi et al. (Thu,) studied this question.