The digital economy exerts both positive and negative influences on urban sustainable development, yet there is a notable gap in the existing research concerning its impact on energy intensity and the underlying mechanisms. this study pioneers the investigation of a nonlinear relationship between the digital economy and energy intensity, revealing a significant inverted U-shaped relationship. Specifically, we observe a noteworthy reduction in energy intensity when the digital economy index surpasses 0.286. Our empirical findings indicate that the digital economy not only directly influences energy intensity but also exerts an indirect impact through initiatives such as the promotion of green innovation and the agglomeration of high-tech industries. Importantly, the promotional effects of the digital economy exhibit heterogeneity with respect to geographical location, resource endowment, and urban scale. This paper contributes to the theoretical understanding of information technology in urban green development by analyzing the mechanisms of the digital economy at the urban level and its intricate impact on energy intensity.

The No.1 document of the Central Government of China has been on the theme of "agriculture, rural areas and farmers" for nearly ten years, placing the solution of "agriculture, rural areas and farmers" at the forefront of the Chinese government's work. Located in the Central Plains, Henan Province in China is one of the major agricultural provinces in China and plays an extremely important role in the field of agricultural production in China. This paper uses an empirical approach and the DEA-Malquist model to study the efficiency of rural public financial inputs to rural revitalisation in Henan Province. The results show that due to different levels of regional economic development, the efficiency of rural public finance investment in Henan Province in promoting rural revitalisation varies, and there is a phenomenon of unreasonable allocation of funds. At the same time, the region's agricultural base also has a greater impact on the efficiency of financial investment. Therefore, Henan Province should adjust measures according to the different regional economic levels and agricultural bases to improve the efficiency of the use of fiscal funds.

This study examines the effects of artificial intelligence on oil shocks (supply, demand, and risk shocks) across different time scales and market conditions, using the wavelet-based quantile-on-quantile approach. The empirical results have discovered that in the short term, artificial intelligence exerts significant negative impacts on supply and risk shocks, with these adverse effects gradually diminishing over time. Notably, artificial intelligence begins to positively influence supply shock in the medium to long term. In contrast, demand shock is initially positively affected, but these benefits diminish over time. The outcomes gained from this study not only give policymakers valuable insights for developing more precise energy policies, but also provide investors with nuanced market perspectives and risk assessments.

Influenced by traditional notions of solidarity, when a province’s planning can be highly aligned with that of the central government, the province is perceived to be more collective and thus able to receive financial or resource favors from the central government. This consistency, as is often the case, reflected in doing the same thing as the central government. This situation may lead governors to ignore local economic performance and thus reduce regional innovation efficiency, as in the case of China’s Great Leap Forward. Likewise, it is possible to get better resources (energy or capital) by demonstrating managerial submissiveness, thus improving the regional innovation efficiency. Therefore, to verify the relationship between imitative governance and regional innovation efficiency, we collected relevant data from 31 major provincial administrative units in China, calculated the degree of imitative governance between provincial government work reports and central government work reports through text similarity, as well as utilized the SBM-DEA model to evaluate regional innovation efficiency. Meanwhile, we provide a new explanation of the phenomenon from the perspective of resource inclination. Finally, the empirical results show that imitative governance promotes local innovation efficiency and is moderated by resource inclination.

The digital transformation of manufacturing industry can promote the development of green transformation and promote the differentiation of workers’ skill structure; On the other hand, it will also hinder the green development due to the huge energy consumption generated by the application of digital technology and facilities. In addition, the green transformation of manufacturing industry will also have differentiated impacts on the employment of labour with different skills due to the innovation of green technology. The existing research has not discussed too much about the interaction among the digital transformation and green transformation in manufacturing industry and labour structure. So, this paper uses the PVAR model to examine the dynamic relationship between digital and green transformation within the industrial sector from the perspective of labour structure, specifically analyzing the impact difference across regions. The results suggest that there is a reciprocal connection between the digitization of manufacturing sector and the labour structure, particularly in the eastern region of China, but the overall interaction between the two remains weak. The interactive between the green transformation of manufacturing industry and the labour structure in the central and western areas has been delayed over periods 1-6. Digital and green manufacturing transformation reinforce each other in central and western regions. However, the digital revolution in the manufacturing industry is hindered by the green transformation in eastern region.