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The development of transportation infrastructure plays a pivotal role in the regional economy from multiple dimensions. The aim of this paper is to examine the relationship between transportation infrastructure development and income inequality in urban and rural areas of China. The study utilizes panel data from 30 provinces, spanning the years 2010 to 2020, and employs the spatial Dubin model to measure and test the impact of transportation infrastructure on the urban-rural income gap. Furthermore, an intermediary effect test method is used to investigate the potential mediating effect of urbanization in this relationship. The results indicate that transportation infrastructure has a significantly negative direct, indirect, and total effect on the urban-rural income gap, with the indirect effect being greater than the direct effect. This suggests that transportation infrastructure can effectively reduce income disparities, with a noticeable spatial spillover effect. The level of urbanization plays a significant intermediary effect on the effect of transportation infrastructure on the urban-rural income gap, highlighting the role of transportation infrastructure in improving urbanization and narrowing income disparities. These findings underscore the importance of enhancing both the level of urbanization and cooperation between neighbouring regions in order to maximize the benefits of transportation infrastructure development for reducing income disparities and promoting regional balance in China.

The logistics and manufacturing industries’ co-agglomeration (LMCA) and deep integration, as well as the industries’ digital transformation and intelligent upgrading, are of great significance to enhance regional economic resilience (EcoResi). This paper establishes a theoretical framework for LMCA and EcoResi based on the economic development theory and the new economic geography theory, explores the spatial spillover effect of LMCA on EcoResi, and measures the levels of LMCA and EcoResi. The data set is consisted of the indicators of LMCA and GDP growth rate of 30 provinces, centrally administered municipalities, and autonomous regions in China from 2006 to 2020. Spatial econometric models were used to empirically analyze the impact of LMCA on EcoResi based on provincial panel data. The results show that the improvement in LMCA not only improves the resilience of local economy, but it also has a significant spatial spillover effect. Further regional analyses show that LMCA has significant stimulating effects and spatial spillover effects on EcoResi in the central and western regions of China. However, the same effects are not significant in the eastern region of China. This research enriches the literature by suggesting effective ways to enhance EcoResi through LMCA.

Using the panel data of 274 cities from 2011 to 2019, this article studied the impact of the digital economy on the low-carbon transformation and space overflow effect on the city’s low-carbon transformation and used the panel threshold model to calculate the regulatory effect of public attention. Studies found the following: (1) The digital economy, the urban low-carbon transformation level, and public attention show regional differences, manifesting as the distribution of "point clusters" and "decreasing from east to west", and as far as the speed of change, after the year 2015, the annual increase of various indicators increased. (2) The role of digital economy development and urban low-carbon transformation levels have a "U" relationship. At present, most cities across the country have passed the point of inflection, which presents a significant promotion effect. However, in a comparison of regional coefficients, the Eastern region > Western region > Midlands. (3) The development of the digital economy has a significant “siphon effect” on the impact of urban low-carbon transformation. (4) With the increase in public attention in the region, the positive promotion of the digital economy on the urban low-carbon transformation has gradually increased.

Based on Chinese provincial panel data (2011–2020), the CRITIC-EWM, kernel density estimation, Dagum Gini coefficient and a spatial Dubin model were used for analyzing endogenous and exogenous factors to enhance grain supply chain resilience. The results illustrated the following: (1) Ensuring the resilience of the grain supply chain’s ability to digest, recover and learn was fundamental to internal system robustness. (2) Overall, China’s grain supply chain resilience increased year over year, but the growth rate was low and showed an attenuation trend of east-middle-west. (3) There was a significant spatial positive correlation among provinces and grain supply chain resilience, however, the large gap and slow development led to the formation of polarization with high-high and low-low clusters. (4) The exogenous drivers were all significant and had a significant positive spillover effect on the grain supply chain resilience. (5) Subregional regressions reflected the heterogeneity of the influence factors, which highlighted the implementation of targeted strategies as the key to achieving synergy.

Industrial agglomeration in a region changes the economic structure, strategic layout and resource status of a city, and has an important impact on sustainable economic development. The relationship between industrial agglomeration, air pollution and economic sustainability is a key issue concerning the high-quality development of national economy. China is a developing country that once experienced severe air pollution. Now, the Chinese government is aiming to achieve the goal of sustainable and high-quality economic development in China. In this paper, a spatial Dubin model was developed to study the relationship between industry, environment and the economy. The statistical analysis used the air pollutant data of 273 prefecture-level cities in China from 2015 to 2018. The results showed that: (1) there was a positive U-shaped nonlinear relationship between industrial agglomeration and sustainable economic development, and there was a spatial spillover effect. (2) There was a positive U-shaped nonlinear relationship between air pollution and sustainable economic development, and there was a spatial spillover effect between them. (3) The effect of industrial agglomeration on sustainable economic development was influenced by air pollution, an intermediary variable. The existence of air pollution weakens the promoting effect of industrial agglomeration on sustainable economic development.

Green innovation has become an important combination of high-quality economic growth and ecological sustainability. In this paper, the super-efficiency network SBM model was used to measure the two-stage green innovation efficiency of the industrial technology research and development (R&D) stage and achievement transformation stage in China (30 provinces and cities) from 2009 to 2019. The results show the following points. Firstly, in terms of temporal series, the efficiency of technology R&D and achievement transformation has experienced three stages of “upward-declining-revitalized period”. Secondly, in terms of spatial trend, the industrial green innovation efficiency gradually increases from northwest to southeast. The high-efficiency areas are still concentrated in the eastern coastal region, with a clear trend towards balanced development in the central and western regions. Finally, openness, industrial structure, government technical expenditures, enterprise scale, and environmental regulation all have different degrees of impact on the efficiency of green innovation in the two stages. Based on the above, this paper is helpful for the government to formulate laws and regulations and coordinate the level of regional economic development and clarify the spatio-temporal characteristics and influencing factors of the efficiency of green innovation.

Modern tourism plays an increasingly important economic role in regional development. However, in the practice of regional economic development, there is often a lag in economic development where the tourism industry is prosperous. We explored the potential impact of the development level of informatization on the coupling and coordination relationship between the tourism industry and regional economic development. Using provincial panel data from 2008 to 2017, we constructed a spatial Dubin model for empirical research. We established an evaluation model for the coupling and coordination relationship between tourism and regional economic development based on the establishment of evaluation models and indicator systems for informatization, tourism, and regional economic development. The results show that improvements to informatization generally promoted the coupling and coordination of tourism and regional economic development. Informatization not only improved the coupling and coordination of tourism and economic development in the region but also had significant spatial spillover effects. In addition to the influencing factors at the information level, the advantages of tourism resources and the level of economic development on the whole also helped to improve the degree of coupling and coordination, while the widening of the income gap between urban and rural areas hindered coordinated development. Further discussion shows that informatization will affect the degree of coupling and coordination between the tourism industry and regional economic development by influencing the level of institutional environment. The findings highlight the need to focus on diversified development of the regional tourism industry and economy while improving the level of informatization and strengthening cross-regional cooperation during informatization. The conclusions contribute to improving the coordinated development of regional tourism and regional economy and provide a scientific basis for the development of informatization and the formulation of tourism and economic policies.