Smart city policy (SCP) is crucial to addressing climate change and achieving sustainable urban development with low carbon emissions. The purpose of this paper is to investigate the mechanisms through which smart city policies have an impact on carbon emission efficiency (CEE). In terms of research methodology, we construct a quasi-natural experiment on smart city policies in China and use the time-varying DID approach to study this issue. The DEA method was used to measure the CEE. For the data sample, panel data from 281 cities in China between 2007 and 2020 was used in this study. The findings are as follows: ① SCP has a significant impact on CEE. This conclusion remains valid after introducing parallel trend tests, placebo tests, and other robustness tests. ② The mechanism test result reveals that SCP has a positive impact on urban CEE through three main channels: promoting industrial upgrading, increasing public environmental attention, and enhancing marketization. ③ The analysis of heterogeneity reveals that the impact of SCP on CEE is noticeable in cities that belong to well-developed economic regions with a lower intensity of environmental regulations, higher levels of green finance, and fewer official changes. This research contributes to the existing literature on the environmental assessment of SCP and offers valuable policy insights for cities to tackle climate change and sustainable urban planning.

Enhancing urban innovation resilience is crucial for adapting to change and pursuing innovation-driven, high-quality development. The global trend of digital transformation has profound implications for urban innovation; however, the specific effects of digital transformation on urban innovation resilience remain insufficiently explored. This study utilizes panel data from 285 prefecture-level and above cities in China, spanning from 2007 to 2022. It treats the Broadband China Pilot (BCP) policy as a quasi-natural experiment of digital transformation and employs a time-varying Difference-in-Differences (DID) method to investigate the impact of digital transformation on urban innovation resilience. The results yield several important insights: (i) digital transformation enhances urban innovation resilience; (ii) the effect of digital transformation on urban innovation resilience is heterogeneous across regions and city sizes; (iii) digital transformation improves urban innovation resilience through the mediation effect of green total factor productivity (GTFP); (iv) urban industrial upgrading and urban innovation vitality play significant moderating roles in the relationship between digital transformation and urban innovation resilience. These findings contribute to a deeper theoretical understanding of the relationship between digital transformation and urban innovation resilience.

The establishment of high-tech zones in China represents a significant policy tool aimed at fostering urban scientific and technological innovation while ensuring steady and sustainable economic growth. Using high-tech zones as a quasi-natural experiment and 233 prefecture-level cities in China from 1990 to 2021 as a research sample, this article constructs a difference-in-difference model to test the impact of high-tech zones on urban economic resilience. Our findings reveal several key insights. First, high-tech zones play a crucial role in enhancing urban economic resilience, which is robust across multiple tests. Second, there is significant variation in the influence of high-tech zones on urban economic resilience. Large cities, cities in the Yangtze River Economic Belt (YEB), and eastern cities are more affected than other cities. Third, improving urban innovation ability and optimizing resource allocation are important ways through which high-tech zones influence urban economic resilience. These findings contribute significantly to the evaluation of the high-tech zones policy and form empirical evidence of the policy arrangements’ regional-level impact on economic resilience.

Given the phenomenon of “financing is difficult and expensive” for MSEs, this paper empirically investigated the influencing mechanism of the credit demand side characteristics on the financing constraints of MSEs based on the information conveyance perspective. The conclusions show that MSEs in China are severely suffering from financing constraints and 57.17% and 50.00% of MSEs with credit demand have not applied for loans from formal and informal financing channels, respectively. In terms of enterprise characteristics, MSEs have low asset size, short establishment history, weak profitability, and lack of tools such as fixed assets, complete financial management system, professional technicians, and private brands to convey risk information to financing institutions, which are key factors resulting in their financing constraints. In terms of owner characteristics, young owners lack financing experience and convey higher risk information to financing institutions; therefore, owners’ age negatively influences the financing constraints of MSEs. These findings suggest that banks can use big data credit technology as a tool to obtain risk information about MSEs, and the government should implement diversified interventions to improve the information environment in financial markets. These findings provide empirical evidence for banks and governments to address the financing constraints of MSEs.