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The development of digital villages plays a critical role in advancing green agriculture steadily and with high quality. This study measures the efficiency of agricultural water resource allocation using provincial-level rural data from 2011 to 2022 and a super Slacks-Based Measure model accounting for non-desirable outputs. Using the ArcGIS tool, this study illustrates the spatiotemporal patterns and provincial clustering of the green allocation of agricultural water resources. A spatial Durbin model further examines interactions between digital villages and water resource efficiency. Findings indicate the following: (1) The green water resource efficiency in China's 30 provinces showed a gradual, steady increase, albeit with notable regional differences, particularly a "northwestern depression" in spatial distribution. (2) Moran's I index indicates a strong positive spatial correlation between digital villages and green water resource efficiency, manifested as either "high–high" or "low–low" clustering. (3) The spatial Durbin model results demonstrate that digital villages enhance the green water resource efficiency of neighboring areas, a phenomenon referred to as the "Matthew effect". (4) Different aspects of digital village construction, operation, and lifestyle positively influence green water resource efficiency, while digital loops have a negative impact. Aligning resource allocation efficiency with the establishment of digital village infrastructure is paramount. This symbiotic relationship bolsters the structural foundation of agricultural production, optimizing resource utilization and fostering technological advancements in rural settings. [ABSTRACT FROM AUTHOR]

The development of digital villages plays a critical role in advancing green agriculture steadily and with high quality. This study measures the efficiency of agricultural water resource allocation using provincial-level rural data from 2011 to 2022 and a super Slacks-Based Measure model accounting for non-desirable outputs. Using the ArcGIS tool, this study illustrates the spatiotemporal patterns and provincial clustering of the green allocation of agricultural water resources. A spatial Durbin model further examines interactions between digital villages and water resource efficiency. Findings indicate the following: (1) The green water resource efficiency in China’s 30 provinces showed a gradual, steady increase, albeit with notable regional differences, particularly a “northwestern depression” in spatial distribution. (2) Moran’s I index indicates a strong positive spatial correlation between digital villages and green water resource efficiency, manifested as either “high–high” or “low–low” clustering. (3) The spatial Durbin model results demonstrate that digital villages enhance the green water resource efficiency of neighboring areas, a phenomenon referred to as the “Matthew effect”. (4) Different aspects of digital village construction, operation, and lifestyle positively influence green water resource efficiency, while digital loops have a negative impact. Aligning resource allocation efficiency with the establishment of digital village infrastructure is paramount. This symbiotic relationship bolsters the structural foundation of agricultural production, optimizing resource utilization and fostering technological advancements in rural settings.

Providing diversified jobs for workers and achieving green development are important goals of the new-type urbanization construction (NTUC) in China. We constructed a difference-in-difference model to investigate the effect of the NTUC on the shift-share of employment (SSE), using panel data of 272 Chinese prefecture-level cities from 2005 to 2019. The relationship between the SSE and CO2 emissions was explored. The results show that the NTUC effectively promotes the SSE and exhibits the significant regional and industry heterogeneity. In addition, the SSE under the NTUC pilot policy can effectively reduce CO2 emissions and presents the obvious regional and industrial differences. Promoting the industrial structure advancement and improving public services and digital levels can enhance the inhibitory effect of the SSE on CO2 emissions. Meanwhile, the SSE has an inhibitory effect on CO2 emissions in local regions but promotes the CO2 emissions in the neighboring regions. Finally, these findings provide an important decision-making reference for restructure employment and reduce CO2 emissions during the period of urban transformation and development. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is an effective way to achieve carbon neutrality in the context of growing advocacy for a green economy in both academia and government. In this study, we analyzed the impact mechanism of the manufacturing agglomeration on total factor energy efficiency. Based on this work, we identified 30 provinces (autonomous regions and municipalities) in China using 2002 to 2017 panel data. We used the data envelopment analysis game cross-efficiency model to calculate the interprovincial current state of energy efficiency. We constructed a spatial Durbin model and used an adjacent space weight matrix, geographic distance weight matrix, and economic distance weight matrix to study the impact of manufacturing agglomeration on total factor energy efficiency. The results showed that under different spatial weights, the interprovincial total factor energy efficiency had a significant spatial dependence; under the three spatial weights, we identified a U-shaped relationship between manufacturing agglomeration and total factor energy efficiency. Industrial agglomeration had obvious spatial spillover effects on total factor energy efficiency, and the spillover effects under the weight of geographic distance were higher than other spatial weights. During the sample period, the direct, indirect, and total effects of the manufacturing industry had an impact on energy efficiency. It all had a negative number indicating that there was a crowding effect in manufacturing agglomeration, and it had an inhibitory effect on energy efficiency.

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The increasingly severe water crisis is restricting sustainable development of the Yangtze River Delta Urban Agglomeration (YRDUA), highlighting the importance of collaborative water resources management. Based on the dataset from 26 cities between 2001 and 2020 in the YRDUA, this study applies Social Network Analysis to research the spatial correlation of urban water utilization, which helps identify the interaction of water use behaviors among different cities. Results show that the close relationships among urban water consumption in the YRDUA have formed a network, and there is no isolated city in the water use correlation network. During the research period, the water network affinity and network density showed an overall upward trend, meaning the number of actual connections in the network was increasing. However, the network hierarchy first decreased and then raised, and the network efficiency first increased and then decreased, indicating the structural evolution of the water network was gradually detrimental to the effective dissemination of water use information. The urban water consumption correlation network also shows a core-peripheral structure. Shanghai, Wuxi, Suzhou, and Hangzhou have higher coreness and centralities, dominating the water network and controlling major information spillover channels. Therefore, it is essential to focus on the overflow effects of urban water consumption and management among different regions, optimize the structure of the water consumption correlation network, exploit the core cities’ radiation effects, and realize collaborative management for regional water resources.