The digital economy plays an important role in promoting regional green innovation. Based on the panel data of 30 provincial administrative regions in mainland China (except Tibet) from 2011 to 2018, this paper constructs a comprehensive development index of the digital economy and explores the potential path of the digital economy affecting regional green innovation through factor analysis and regression analysis. The results show the following: Firstly, the digital economy can effectively promote regional green innovation capability. The causal relationship is mainly realized through scientific research funds and human resources. Secondly, in terms of regional heterogeneity, the role of the digital economy in promoting green innovation and R&D investment in eastern China is stronger than that in central and western China. Thirdly, further analysis showed that the digital economy has a significant nonlinear influence on regional green innovation capability. This feature is mainly reflected in the influence of R&D personnel on regional green innovation. Therefore, the rational allocation of R&D resources is conducive to the development of regional green innovation. Finally, it is suggested to improve the two mechanisms of R&D funds and personnel investment to actuate regional green innovation development.

With the rapid development of information and communication technology, the new quality productive force has gradually become one of the key factors to promote scientific and technological innovation and promote the transformation and upgrading of industrial structure. Based on the essential connotation and three key characteristics of the new quality productive force, this study constructs a comprehensive evaluation index system and measures the development level of the new quality productive force by the entropy method, while the industrial structure advancement coefficient is employed to assess provincial industrial upgrading. This study examines the relationship and transmission mechanisms between the new quality productive force (NQPF), scientific and technological innovation (STI), and industrial structure optimization (ISO) using China’s provincial data (2012–2022) from the National Bureau of Statistics of China through the stepwise regression method. Based on a balanced panel of 330 province-year observations, the results show that NQPF significantly enhances STI, with stronger effects in regions with higher NQPF development. However, regional heterogeneity exists, with the eastern and central regions benefitting more than the western region. Additionally, mediation tests reveal that the NQPF fosters STI, thereby driving industrial upgrading. These findings highlight NQPF’s role in regional innovation and structural transformation.

As the core engine of the digital economy, the digital transformation can make modern enterprises survive and develop better now. By the sample data of listed companies in the years from 2015 to 2020, this paper identifies the degree of enterprise digital transformation through text analysis, empirically examines the impact mechanism of digital transformation on corporate risk-taking, and fully considers the heterogeneity problems. The findings are as follows: (1) Digital transformation can improve the level of enterprise risk taking, especially the improvement of enterprise financial stability and strategic risk taking; (2) in terms of enterprise attribute structure, digital transformation can significantly enhance the risk-taking level of non-state-owned enterprises and high-tech enterprises; (3) the mechanism identification test finds that innovation-driven and enterprise value enhancement play a strengthening role in the role of digital transformation in promoting enterprise risk-taking level, and resource allocation efficiency as a mediating path weakens the role of digital transformation on enterprise risk-taking level. This study provides a basis for promoting the improvement of enterprises risk-taking: digital transformation can help enterprises maintain financial stability, improve innovation output capacity, enterprise value level, enterprise risk-taking capacity and sustainable development. At the same time, the Chinese government should take measures to further stimulate the willingness of state-owned enterprises to digital transformation.

Digital technology has energized the development of inclusive finance in China and is beneficial in lowering the threshold and transaction costs of financial services and expanding financial coverage. However, it is a key issue whether digital inclusive finance can help SMEs overcome financing difficulties, obtain liquidity, reduce corporate leverage, and thus achieve sustainable development. By using the data from China’s small- and medium-sized listed companies and an aggregate development index of digital inclusive finance at the county level in China from 2015–2019, this empirical analysis finds that the development of digital inclusive finance can significantly reduce the leverage ratio of SMEs; specifically, the development of digital inclusive finance can cut down the leverage ratio of enterprises through easing financing constraints and reducing finance costs. Heterogeneity analysis shows that digital inclusive finance is more effective in reducing leverage for those low- and medium-leverage and non-private enterprises. Accordingly, it is suggested that the government continue to promote the development of digital inclusive finance, deepen the financial supply-side structural reform, and improve the efficiency of financial recycling. SMEs should speed up digital transformation to enable digital finance to provide precise financing services and achieve high-quality sustainable development. Digital financial institutions should improve the digital inclusive financial system as soon as possible, realize scientific supervision and risk prevention, and promote the sustainable development of digital finance.

Developing rapidly over the long term makes it easy for a developing country to fall into the middle-income trap, which can only be solved by a new technological revolution. The deep integration of digital technology and industry has gradually become a new impetus to promote the sustainable development of China’s economy. Based on the panel data of 30 provinces and cities from 2010 to 2019, this paper analyzes the coupling coordination relationship between digital transformation level and economic development in China by the entropy method, coupling coordination degree model and spatial autocorrelation model. The results show that the following: (1) from 2010 to 2019, the comprehensive index of China’s digital transformation and economic growth level showed an upward trend, and the development level showed a gradual decline in eastern–middle–western regions; (2) the level of coupling and coordination between China’s digital transformation and economic growth has been increasing each year. Except Guangdong Province, all provinces have shown digital lag coordinated development, and it is necessary to strengthen their economic sustainability; (3) the coupling and coordination degree of digital transformation and economic growth in China shows a remarkable spatial correlation and agglomeration. High–high agglomeration areas are mainly concentrated in the Beijing–Tianjin–Hebei and Yangtze River Delta regions, low–low agglomeration areas are concentrated in northeast and western regions, and low–high agglomeration areas and high–low agglomeration areas are concentrated in southeast provinces. It is suggested that China should strengthen its regional balance in the future, let digital technology continue to lead the development of eastern developed regions, and transform and promote the traditional economy in other regions, overtaking in corners and enhancing the sustainable development of the overall layout of China’s economy.

In rural areas of China, the challenges of efficient and cost-effective distribution are exacerbated by underdeveloped infrastructure and low population density, with last mile logistics distribution posing a significant obstacle. To address the gap in drone application for last mile logistics in rural areas, a truck–drone distribution model was developed based on the specific conditions of rural regions. The improved fuzzy C-means algorithm (FCM) and genetic simulated annealing algorithm (GASA) were employed to tackle real−world cases in rural areas. The focus of the truck–drone system is to optimize the rural logistics distribution process, reduce delivery time, and minimize costs while considering factors such as maximum mileage of trucks and drones as well as customer priority. Compared to traditional methods, this system has demonstrated notable improvements in distribution efficiency and cost reduction, offering valuable insights for practical drone applications in last mile rural logistics.