Policy diffusion based on learning mechanisms has fascinated political science and public administration scholars for a long time. A robust and growing body of studies have identified the existence and importance of learning mechanisms in policy diffusion. However, there are still some gaps that need to be further improved. First, scholars identify the learning mechanism mainly based on indirect evidence, such as geographical proximity and successful innovation policies adopted by other jurisdictions, which lacking direct and systematic evidence. Second, little is known about how the hierarchical power structure affects the leap from learning behavior to policy adoption. This study provides direct evidence for the promoting effect of intergovernmental learning on policy diffusion by analyzing case of Chinese local financial subsidy policies for new energy vehicles. The empirical results reveal that policy learning in the form of site visits among local governments significantly promotes the policy diffusion, but superior government policy strategy attenuates the influence of interlocal learning on policy diffusion. Also, the initiators and themes of policy learning affect the learning-diffusion linkage, portraying the conditional effects and nuanced dynamics of interlocal policy learning in eliciting policy diffusion.
The rapid development of generative artificial intelligence (AI) has attracted global attention and posed challenges to existing data governance frameworks. The increased technical complexity and expanded scale of data usage not only make it more difficult to regulate AI but also present challenges for the current legal system. This article, which takes ChatGPT’s training data and working principles as a starting point, examines specific privacy risks, data leakage risks, and personal data risks posed by generative AI. It also analyzes the latest practices in privacy and personal data protection in China. This article finds that while China’s governance on privacy and personal data protection takes a macro-micro integration approach and a private-and-public law integration approach, there are shortcomings in the legal system. Given that the current personal data protection system centered on individual control is unsuitable for the modes of data processing by generative AI, and that private law is insufficient in safeguarding data privacy, urgent institutional innovation is needed to achieve the objective of “trustworthy AI.”
A considerable amount of literature has been published on increasing citizens’ satisfaction through satisfaction surveys. However, we know little about how to find the optimal design for a citizen satisfaction survey. Borrowing insights from dual-process theory, the study examines the effects of citizen satisfaction survey design on respondents’ effort and reported satisfaction. A fully randomized 23 between-subjects factorial experiment revealed a positive relationship between the number of anchors and the cognitive effort, while the effect of survey length is negative. Additionally, an increasing number of anchors will decrease the cognitive bias of participants. This study underscores the critical role of dual-process theory in understanding citizens’ evaluations and offers practical implications for survey design.
We investigate the unintended impact of minimum wage increases on workplace safety. Using establishment-level data from the United States and a cohort-based stacked difference-in-differences design, we find that large increases in minimum wages have significant adverse effects on workplace safety. Our findings indicate that, on average, a large minimum wage increase results in a 4.6 percent increase in the total case rate. Event study estimates show that this adverse effect persists in the medium run. Furthermore, we find a more salient effect for firms more likely to be financially constrained or subject to a higher labor market rigidity in firing workers. We provide suggestive evidence that small minimum wage increases might reduce injury rates, highlighting the potential heterogeneity in the impact of minimum wage changes. We do not find evidence that capital-labor substitution could be behind the findings.