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By constructing a rural revitalization index evaluation system and using measurement models and software such as AHP, the entropy method, the BCG matrix, and GeoDetector, this paper quantitatively analyzed the evolution mode and driving mechanism of rural revitalization performance based on the research of 131 cities and autonomous prefectures in western China to further put forward relevant policy suggestions and establish a new framework that integrates "performance evaluation, evolution model, driving mechanism, and management strategy". Findings: firstly, rural revitalization in western China showed slow development and significant regional heterogeneity, with a coefficient of variation of 0.46 or even higher; secondly, the different dimensions of rural revitalization and development varied greatly, with the order being: thriving businesses (about 0.04) < effective governance (about 0.06) < pleasant living environment (about 0.09) < social etiquette and civility (about 1.0) < prosperity (about 0.23); thirdly, the growth and decline of rural revitalization performance coexisted in the context of rapid development in western China, and the evolution was in diversified patterns; fourthly, there were many factors affecting the change of rural revitalization performance, and different factors exhibited significant synergistic effects with each other, with super-interacting factor pairs having a force of over 0. 7 (maximum 1), including permanent population, urbanization rate, added value of primary industry, and per capita GDP as key factors; fifthly, based on the superposition analysis of the evolution pattern and driving forces of rural revitalization, western cities are classified into 8 types (including external assistance zone, general development zone, general retention zone, general demonstration zone, internal governance zone, important development zone, important retention zone, important demonstration zone) for establishment of a zoning planning and management system and design of differentiated development policies, providing a basis for "evidence-based decision-making" for the government. [ABSTRACT FROM AUTHOR]

Agricultural green development is an essential direction for global sustainable agriculture. The academic literature, however, needs to place greater emphasis on studying the factors influencing agricultural green development performance and how such performance can be improved. A theoretical framework for agricultural green development performance was constructed in this paper using the Super-SBM model, which considers undesirable outputs, to measure the agricultural green development performance of 330 cities at or above the prefecture level in China (excluding Tibet Autonomous Region, Hong Kong, Macao and Taiwan of China) from 2007 to 2018. Furthermore, the influencing mechanism of agricultural green development performance was then analyzed using a spatial econometric model. The results show that: 1) from 2007 to 2018, China's agricultural green development performance experienced three stages of evolution: 'rise, decline and rise'. 2) The regions with high performance agricultural green development are mainly distributed in eastern China, northeastern China, and southern Qinghai Province. 3) The agricultural economic level, industrialization process, and labor quality play significant roles in promoting local agricultural green development performance, while such performance is obviously inhibited by the openness level and the government's environmental regulations. Local agricultural green development performance is significant inhibited by the agricultural economic level and accelerated industrialization process in neighboring cities, while significantly promoted by the agricultural industrial structure in neighboring cities. Some suggestions for improving agricultural green development performance are proposed based on these research results, which can provide scientific references for promoting sustainable agriculture. [ABSTRACT FROM AUTHOR]

Since the 21st century, the world has increasingly focused on the issue of sustainable development, and the green transformation issues have become a new hot topic worldwide. Green and low-carbon transformation has become an international consensus. Urban agglomerations are important connections between urban development and regional coordination, as well as important spatial carriers for economic activities. They are not only the main source of carbon emissions, but also the main battlefield for energy conservation and emission reduction. As an important field for carbon reduction, the green transformation of cities is crucial for achieving the "dual carbon" goals. This article focuses on 48 cities in the three most mature and influential urban agglomerations in China from 2011 to 2019, namely, the Beijing-Tianjin-Hebei urban agglomeration, the Yangtze River Delta urban agglomeration, and the Pearl River Delta urban agglomeration. The three-stage DEA model and Malmquist index model are used to measure the green transformation efficiency of the three urban agglomerations from both dynamic and static perspectives, and a Tobit regression model is constructed to explore the influencing factors of green transformation efficiency in urban agglomerations. Research has found that: 1) From a static perspective, the overall efficiency of green transformation in the three major urban agglomerations is at a high level, but from a temporal perspective, it shows a downward trend. The Pearl River Delta urban agglomeration is known for its green development, with the highest average efficiency of green transformation, followed by the Yangtze River Delta urban agglomeration. The Beijing-Tianjin-Hebei urban agglomeration has the lowest level of green transformation; 2) From a dynamic perspective, technological progress is the main driving factor for improving the efficiency of green transformation in the three major urban agglomerations. Therefore, the government should pay special attention to the progressiveness of technology when formulating relevant policies to promote urban green transformation; 3) From the perspective of spatiotemporal differences, there are significant differences in the spatiotemporal characteristics of green transformation among the three major urban agglomerations, and there are significant differences in green transformation strategies among different urban agglomerations. Eliminating environmental factors and random interference is necessary for accurately measuring the efficiency of green transformation in urban agglomerations; 4) From the perspective of influencing factors, factors such as industrial structure upgrading, green innovation level, and environmental regulation intensity jointly affect the efficiency of green transformation in urban agglomerations. Based on this, we should pay attention to the differences between urban agglomerations and implement policies tailored to local conditions; Strengthen the network system of urban agglomerations and avoid conflicts between cities; Encourage green technology innovation, accelerate industrial structure upgrading, and so on. This article focuses on the issue of green transformation in urban agglomerations, and conducts research from three perspectives: efficiency measurement, influencing factors, and implementation mechanisms. A relatively systematic theoretical framework for green transformation in urban agglomerations is formed, and an evaluation index system for green transformation efficiency in urban agglomerations is constructed and optimized. The composition mechanism of the five dimensional evaluation system for transformation efficiency is analyzed, and the bottleneck and breakthrough direction of the three major urban agglomerations in China in the development process are grasped. It has a good demonstration effect on the green transformation of other urban agglomerations. [ABSTRACT FROM AUTHOR]

The synergy of the digital economy and green total factor productivity (TFP) is the foundation for achieving beneficial outcomes for both the economy and environment. This synergy is also the catalyst for high-quality development and sustainable economic growth in China. The study applied a modified Ellison-Glaeser (EG) index, super-efficiency slacks-based measure (SBM) with a Malmquist-Luenberger (ML) index, coupling coordination degree, and other models to explore the spatiotemporal heterogeneity of the coupling between the digital economy and green TFP from 2011 to 2020 and also analyzed the influencing factors of the coupling. The results show that the coupling between the digital economy and green TFP showed an overall upward trend from imbalance to synergy during the study period. The distribution of the synergistic coupling expanded from point-like to band-like, and there was a significant spreading pattern from the east to the center or west China. The number of cities in a transition state decreased significantly. Spatial jumps, a coupling linkage effect, and evolution in time were prominent. Additionally, the absolute difference among cities expanded. Although coupling in the west experienced the fastest growth rate, the coupling in the east and resource-based cities showed significant benefits. Coupling did not reach an ideal coordinated state, and a neutral interaction pattern remains to be formed. Industrial collaboration, industrial upgrading, government support, economic foundation, and spatial quality all positively impacted the coupling; technological innovation had a lagged effect; and environmental regulation has not reached its full potential. Further, the positive effects of government support and spatial quality performed better in the east and in non-resource-based cities. Due to the optimization of industrial structure, the coupling of the west and resource-based cities achieved better dividends; however, spatial quality needs further improvement. Therefore, the efficient coordination of China's digital economy and green TFP requires a scientific, reasonable, localized, and distinctive approach. [ABSTRACT FROM AUTHOR]