Search Results (41)

Ensuring food security necessitates a high level of coordinated development between agricultural trade and production. Based on China’s provincial panel data from 2010 to 2023, this study constructs an evaluation index system for agricultural trade and production, employing an entropy-weighted TOPSIS model to measure their development levels. On this basis, a coupling coordination degree model and Moran’s I indices are used to analyze the coordinated development level’s temporal changes and spatial effects. The research finds that the development levels of China’s agricultural trade and production show an upward trend but currently still exhibit the pattern of higher levels in Eastern China and lower levels in Western China. The coupling coordination level between them demonstrates an increasing trend, yet the overall level remains relatively low, with an average value of only 0.445, consistently staying in a marginal disorder “running-in stage” and spatially presenting a distinct “east-high–west-low” stepped distribution pattern. Furthermore, from a spatial perspective, the Global Moran’s index decreased from 0.293 to 0.280. The coupling coordination degree of agricultural trade and production in China generally exhibits a positive spatial autocorrelation, but this effect has been weakening over time. Most provinces show spatial clustering characteristics of high–high and low–low agglomeration in local space, and this feature is relatively stable. Building on these insights, this study proposes a refinement of the coordination mechanisms between agricultural trade and production, alongside the implementation of differentiated regional coordinated development strategies, to promote the coupled and coordinated advancement of agricultural trade and production. Full article

The evolutionary patterns and influencing factors of the coupling coordination among multiple functions of cultivated land serve as an important basis for emphasizing the value of cultivated land utilization and promoting coordinated regional development. The entropy weight TOPSIS model, coupling coordination degree (CCD) model, spatial autocorrelation analysis, and Geodetector were employed in this study along with panel data from 125 cities in the Yangtze River Economic Belt (YREB) for 2010, 2015, 2020, and 2022. Three key aspects in the region were investigated: the spatiotemporal evolution of cultivated land functions, characteristics of coupling coordination, and their underlying influencing factors. The results show the following: (1) The functions of cultivated land for food production, social support, and ecological maintenance are within the ranges of [0.023, 0.460], [0.071, 0.451], and [0.134, 0.836], respectively. The grain production function (GPF) shows a continuous increase, the social carrying function (SCF) first decreases and then increases, and the ecological maintenance function (EMF) first increases and then decreases. Spatially, these functions exhibit non-equilibrium characteristics: the grain production function is higher in the central and eastern regions and lower in the western region; the social support function is higher in the eastern and western regions and lower in the central region; and the ecological maintenance function is higher in the central and eastern regions and lower in the western region. (2) The coupling coordination degree of multiple functions of cultivated land is within the range of [0.158, 0.907], forming a spatial pattern where the eastern region takes the lead, the central region is rising, and the western region is catching up. (3) Moran’s I index increased from 0.376 in 2010 to 0.437 in 2022, indicating that the spatial agglomeration of the cultivated land multifunctionality coupling coordination degree has been continuously strengthening over time. (4) The spatial evolution of the coupling coordination of cultivated land multifunctionality is mainly influenced by the average elevation and average slope. However, the explanatory power of socioeconomic factors is continuously increasing. Interaction detection reveals characteristics of nonlinear enhancement or double-factor enhancement. The research results enrich the study of cultivated land multifunctionality and provide a decision-making basis for implementing the differentiated management of cultivated land resources and promoting mutual enhancement among different functions of cultivated land. Full article

Under China’s dual carbon strategy, low-carbon city construction is expected to help reduce urban flood risks. However, the flood resilience of low-carbon communities remains unclear, limiting effective disaster prevention. This study examines traditional and newly built low-carbon communities in Kunming, establishing indices for community flood resilience and low-carbon development according to current national and local standards. Flood resilience (UFR) and low-carbon development level (ULC) were measured using the critic–entropy weight and TOPSIS methods, and a coupling coordination analysis model was used to analyze their correlation and coordination. The results are as follows: (1) The two communities exhibit marked spatial heterogeneity in both UFR and ULC. On average, the UFR in traditional communities is 21.53% higher than in low-carbon communities, while the ULCs are 4.33% higher in low-carbon communities compared to traditional ones. (2) UFR and ULC showed a high coupling level in both communities (over 98%), indicating a strong correlation. (3) The Moran’s I index of 0.664 for coupling coordination indicates notable spatial dependence. These results suggest that, initially, low-carbon communities in Kunming may not exhibit stronger flood resilience, but low-carbon development can significantly improve flood resilience over time. This paper also provides recommendations for enhancing flood resilience in urban low-carbon communities. Full article

Ensuring the security of agricultural systems is essential for achieving national food security and sustainable development. Given that agricultural systems are inherently complex and composed of coupled subsystems—such as water, land, and energy—a comprehensive and multidimensional assessment of system security is necessary. This study focuses on Northeast China, a major food-producing region, and introduces the concept of agricultural system coupling security, defined as the integrated performance of an agricultural system in terms of resource adequacy, internal coordination, and adaptive resilience under external stress. To operationalize this concept, a coupling security evaluation framework is constructed based on three key dimensions: reliability (Rel), coordination (Cor), and resilience (Res). An Agricultural System Coupling Security Index (AS-CSI) is developed using the entropy weight method, the Criteria Importance Through Intercriteria Correlation (CRITIC) method, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, while obstacle factor diagnosis is employed to identify key constraints. Furthermore, bivariate and trivariate Copula models are used to estimate joint risk probabilities. The results show that from 2001 to 2022, the AS-CSI in Northeast China increased from 0.38 to 0.62, indicating a transition from insecurity to relative security. Among the provinces, Jilin exhibited the highest CSI due to balanced performance across all Rel-Cor-Res dimensions, while Liaoning experienced lower Rel, hindering its overall security level. Five indicators, including area under soil erosion control, reservoir storage capacity per capita, pesticide application amount, rural electricity consumption per capita, and proportion of agricultural water use, were identified as critical threats to regional agricultural system security. Copula-based risk analysis revealed that the probability of Rel–Cor reaching the relatively secure threshold (0.8) was the highest at 0.7643, and the probabilities for Rel–Res and Cor–Res to reach the same threshold were lower, at 0.7164 and 0.7318, respectively. The probability of Rel–Cor-Res reaching the relatively secure threshold (0.8) exceeds 0.54, with Jilin exhibiting the highest probability at 0.5538. This study provides valuable insights for transitioning from static assessments to dynamic risk identification and offers a scientific basis for enhancing regional sustainability and economic resilience in agricultural systems. Full article

This study proposes a multi-dimensional urban transportation network optimization framework (MTNO-RQDC) to address structural failure risks from aging infrastructure and regional connectivity bottlenecks. Through dual-dataset validation using both the Baltimore road network and PeMS07 traffic flow data, we first develop a traffic simulation model integrating Dijkstra’s algorithm with capacity-constrained allocation strategies for guiding reconstruction planning for the collapsed Francis Scott Key Bridge. Next, we create a dynamic adaptive public transit optimization model using an entropy weight-TOPSIS decision framework coupled with an improved simulated annealing algorithm (ISA-TS), achieving coordinated suburban–urban network optimization while maintaining 92.3% solution stability under simulated node failure conditions. The framework introduces three key innovations: (1) a dual-layer regional division model combining K-means geographical partitioning with spectral clustering functional zoning; (2) fault-tolerant network topology optimization demonstrated through 1000-epoch Monte Carlo failure simulations; (3) cross-dataset transferability validation showing 15.7% performance variance between Baltimore and PeMS07 environments. Experimental results demonstrate a 28.7% reduction in road network traffic variance (from 42,760 to 32,100), 22.4% improvement in public transit path redundancy, and 30.4–44.6% decrease in regional traffic load variance with minimal costs. Hyperparameter analysis reveals two optimal operational modes: rapid cooling (rate = 0.90) achieves 85% improvement within 50 epochs for emergency response, while slow cooling (rate = 0.99) yields 12.7% superior solutions for long-term planning. The framework establishes a new multi-objective paradigm balancing structural resilience, functional connectivity, and computational robustness for sustainable smart city transportation systems. Full article

Cultivated land (CL), as the foundation of agricultural production, possesses multifunctionality, and its utilization mode directly influences the agricultural modernization process. This study systematically analyzed the coupled and coordinated development characteristics and driving mechanisms of cultivated land multifunction (CLM) and agricultural mechanization (AM) using data from 31 Chinese provinces between 2011 and 2021, aiming to reveal the complexity of regional agricultural modernization and provide scientific evidence for differentiated agricultural development strategies. Key research findings: (1) From 2011 to 2021, the levels of CLM utilization, AM development index, and their coupling coordination consistently increased, but regional development disparities were prominent. The CLM level in western regions was significantly lower than in eastern and central regions, with regional differences in AM development gradually expanding. (2) Driving factors of coupled and coordinated development varied significantly across regions: eastern regions were primarily driven by technological innovation, central regions were influenced by production efficiency and social security, and western regions were mainly constrained by ecological functions. (3) Natural conditions such as cultivated land area, quality, and land flatness significantly impact the coordinated development of AM and CLM. This study innovatively constructed an evaluation index system for CLM and AM coupling coordination, integrating socio-economic and remote sensing data. By employing entropy weight TOPSIS and coupling coordination models, it conducted an in-depth analysis of long-term temporal changes and revealed the internal mechanisms of regional coordinated development through spatial econometric methods. The research results not only provide theoretical support for regional agricultural modernization but also offer scientific references for formulating differentiated agricultural development policies, promoting synergistic development of agricultural modernization and ecological civilization construction, and exploring more precise and sustainable regional agricultural development paths. Full article

The digital economy plays a crucial role in facilitating the flow of resources between urban and rural areas and addressing developmental imbalances. This study analyzed the coordinated development of the digital economy (DE) and urban–rural integration (URI) across 41 cities in the Yangtze River Delta (YRD) from 2010 to 2022. Using the entropy-weighted TOPSIS method and the coupling coordination degree model, we evaluated the spatial distribution of coordination levels. A modified gravity model and social network analysis revealed spatial correlation structures, while geographic detectors identified dominant influencing factors. The results showed that: (1) the digital economy has advanced faster than urban–rural integration, leading to regional disparities; (2) the coupling coordination level improved over the study period, with cities exhibiting higher coordination concentrated in the eastern and southeastern parts of the region, showing an M-shaped distribution; (3) the coupling coordination degree displayed a spatial distribution pattern from northwest to southeast, with the center shifting southeastward, while overall the central area outperformed the northern and southern areas and the eastern area outperformed the western area; (4) core cities in the spatial correlation network have expanded from Shanghai, Suzhou, and Wuxi to include Nanjing and Changzhou, with increasing influence, but uneven mediating roles; (5) the coordinated development of the digital economy and urban–rural integration was influenced by different factors over various time periods, with the flow of urban–rural resources, agricultural modernization, and social equalization being the primary contributors. Targeted optimization strategies using the geographic detector model would provide a reference for regional urban–rural development. Full article

Understanding the coupling mechanisms and coordinated development dynamics of the water–energy–food (WEF) system is crucial for sustainable river basin development. This study focuses on the Yellow River Basin, conducting a comprehensive analysis of the system’s coupling mechanisms and influencing factors. A structured evaluation framework is established, integrating the entropy weight–TOPSIS method, the coupling coordination degree model, and spatial correlation analysis. Empirical analysis is conducted using data from nine provinces (regions) along the Yellow River from 2003 to 2022 to assess the spatiotemporal evolution of the coupling coordination level. The Tobit regression model is employed to quantify the impact of various factors on the system’s coupling coordination degree. Results indicate that the comprehensive evaluation index of the WEF system in the Yellow River Basin exhibits an overall upward trend, with the system coupling degree remaining at a high level for an extended period, up from 0.231 to 0.375. The interdependence among the three major systems is strong (0.881–0.939), and while the coupling coordination degree has increased over time despite fluctuations, a qualitative leap has not yet been achieved. The evaluation index follows a spatial distribution pattern of midstream > downstream > upstream, characterized by a predominantly high coupling degree. However, the coordination degree frequently remains at a forced coordination level or below, with a general trend of midstream > downstream > upstream. From 2003 to 2008, a positive spatial autocorrelation was observed in the coupling and coordinated development of the WEF system across provinces, indicating a strong spatial agglomeration effect. By 2022, most provinces were clustered in “high-high” and “low-low” areas, reflecting a positive spatial correlation with minimal regional differences. Key factors positively influencing coordination include economic development levels, industrial structure upgrading, urbanization, and transportation networks, while technological innovation negatively affects the system’s coordination. Based on these findings, it is recommended to strengthen balanced economic development, optimize the layout of industrial structures, improve the inter-regional resource circulation mechanism, and promote the deep integration of technological innovation and production practices to address the bottlenecks hindering the coordinated development of the water–energy–food system. Policy recommendations are proposed to provide strategic references for the sustainable socioeconomic development of the Yellow River Basin, thereby achieving the high-quality coordinated growth of the water–energy–food system in the region. Full article

Achieving green, low-carbon, and sustainable development in the Yangtze River Basin is an important part of promoting the modernization of agriculture and rural areas. Based on the panel data of 19 provinces in the Yangtze River Basin from 2002 to 2022, this article constructed a comprehensive evaluation system for the agricultural economy–population development–ecological environment system. By using the entropy-weighted TOPSIS method and the coupling coordination degree model, the comprehensive development level and the coupling coordination status of the agricultural economy, population development, and ecological environment system in the Yangtze River Basin were quantitatively analyzed. The results show the following: (1) The comprehensive index of the agricultural economy–population development–ecological environment system in the Yangtze River Basin shows a fluctuating upward trend, with obvious regional differences, and the comprehensive level showed a trend of gradual improvement from west to east. (2) The coupling degree of the agricultural economy–population development–ecological environment system in the Yangtze River Basin exhibits a volatile characteristic, initially increasing, then decreasing, and subsequently increasing again. Overall, the trend is moving toward a tighter coupling state. (3) The coupling degree of the agricultural economy–population development–ecological environment system in the provinces of the Yangtze River Basin shows a steadily increasing trend, yet the overall coupling coordination degree is not high and remains in a barely coordinated state. Accordingly, suggestions are put forward to optimize the economic structure, improve the population quality, adhere to ecological protection, and accelerate regional linkage so as to promote the coordinated development of economic development, population growth, and ecological protection in the basin. Full article

Driven by the dual imperatives of global economic green transformation and the advancement of digital technologies, achieving synergistic enhancement through digitalization and greenization to promote sustainable development has become a focal point for both academia and practical fields. This study, utilizing a sample of Chinese A-share listed companies from 2010 to 2023, aims to explore the transformative potential of digital–green synergy (DGS) for enhancing enterprise sustainable development within the realm of production efficiency improvement. Employing a coupling coordination model based on the entropy-weighted TOPSIS method, the research measures the DGS levels of enterprises. Grounded in strategic synergy theory, the resource-based view, and dynamic capability theory, this study thoroughly investigates the direct impacts of DGS on corporate TFP, intermediary mechanisms, moderating effects, and heterogeneous roles. The research findings robustly demonstrate that DGS can significantly improve enterprise TFP through optimizing resource allocation, reducing cost stickiness, and enhancing operational efficiency, thereby facilitating the dynamic reorganization of production factors and the creation of sustainable value. Furthermore, external factors, such as financing constraints and environmental regulation, alongside internal organizational factors like executive characteristics, are shown to exert significant moderating effects on the effectiveness of DGS. In summary, this research not only highlights the crucial role of DGS in enhancing production efficiency as a driver for high-quality corporate development and the pursuit of sustainable goals but also provides important theoretical guidance for policymakers to incentivize digital and green transformation. It also offers practical insights for enterprise managers to strategically formulate synergistic development strategies, enhance economic benefits, and achieve long-term sustainable performance. Beyond these practical implications, this study further enriches the theoretical landscape by first extending strategic synergy theory to firm-level digital–green synergy in emerging markets; second by enhancing sustainability research by adopting a broader “environment-society” framework; methodologically innovating by developing a novel “goal-strategy-input-technology” synergy measurement framework; and finally, deepening the theoretical understanding of DGS-TFP relationships through mechanism and moderator exploration. Full article

This study investigates the level of sustainable development, evolution patterns, and obstacles in Qinghai Province. Considering the province’s unique characteristics and ecological significance, we have established an evaluation indicator system based on the DPSIR model. The entropy weight–TOPSIS model is used to assess the overall sustainability of Qinghai from 2008 to 2022. The grey GM(1,1) model is used to predict future sustainability trends, while the coupling coordination model quantifies the degree of coordination among subsystems. Furthermore, the barrier degree model is used to explore the factors hindering the improvement of Qinghai’s sustainable development. (1) The study finds that Qinghai’s overall sustainable development has shown a fluctuating upward trend, increasing from a weaker phase in 2008 to a stronger phase in 2022. All five subsystems in the sustainability evaluation system have shown gradual improvements in their index scores. This suggests that Qinghai’s sustainability level is expected to continue improving in the future. (2) From 2008 to 2022, the highest barrier degrees were observed in the pressure and state systems, with the barrier degrees of other systems gradually decreasing. Nine main factors, including the number of students in higher education, urban unemployment rate at year-end, and input–output ratio, have been identified as the obstacles to improving the province’s sustainable development level. (3) The coupling coordination degree of the five subsystems has shown a positive development trend, progressing through three stages: mild imbalance, basic coordination, and good coordination. The coordination type has shifted from deterioration to improvement. To achieve high-level sustainable development in Qinghai, leveraging the province’s advantageous environmental resources is crucial. Strengthening ecological protection, optimizing the industrial structure, accelerating urbanization, and emphasizing science and education are key pathways for Qinghai’s future development. Full article

Taking Inner Mongolia as a case, this study systematically analyzes the coupling and coordination relationship between carbon emissions from land use (CELU) and high-quality economic development (HQED). The aim is to provide empirical support and policy inspiration for archiving the “dual carbon” goal and HQED strategy in border areas. Panel data from 12 cities in Inner Mongolia from 2000 to 2020 were selected. We established an evaluation index system for CELU and HQED using the entropy-weight TOPSIS method and scientifically evaluated the level of HQED. We applied exploratory spatial data analysis, topic decoupling, coupling coordination degree (CCD), and geographic detector models to comprehensively analyze the coupling coordination status and spatial heterogeneity of CELU and HQED. The driving factors affecting CCD were explored in detail. Although the total CELU in Inner Mongolia has increased, its growth rate has slowed significantly. The CCD of CELU and HQED was low, and an obvious spatial disequilibrium was observed. Seven key factors, including land-use structure, efficiency, and energy intensity, have significant driving effects on the CCD. To support supply-side structural reform, promote HQED, and achieve emission reduction and green development goals, we offer a series of policy recommendations: promote the transformation of resource-based cities, optimize the energy structure, promote industrial structure upgrading, strengthen scientific and technological innovation and green technology applications, and improve regional cooperation and policy coordination. This study reveals the internal relationship between CELU and HQED and provides practical and instructive countermeasures and suggestions for the sustainable development of border areas, such as Inner Mongolia, which have important reference value for promoting the green transformation of regional economies and achieving the “dual carbon” goal. Full article

The interaction between supply and demand of civil aviation passenger transport serves as an important reference for airport planning, transportation structure optimization and dynamic matching of supply and demand. Based on the panel data of 31 province-level administrative divisions (excluding Hong Kong, Macao, and Taiwan) in China spanning from 2004 to 2019, this study employs the entropy-weighted TOPSIS method to evaluate the supply level and demand level of civil aviation passenger transport. On this foundation, this study uses the modified coupling coordination degree model to measure the coupling coordination degree of civil aviation passenger transport supply and demand, further analyzes the spatio-temporal evolution characteristics of coupling coordination degree and employs the double fixed-effect model to investigate the influencing factors. The results indicate that China’s civil aviation passenger supply, demand and supply and demand coupling coordination degree are increasing year by year. The level of provincial supply and demand coupling coordination has risen to the upper-middle level, and has shown significant spatial differences. Economically developed regions demonstrate a higher level of coordination. Economic development, urbanization rate and the degree of opening to the outside world have a positive impact on the coupling and coordinated development. Full article

Given the deficiencies in the definition of connotation, the construction of index systems, and the coordination of targets within the research on sustainable development in the manufacturing industry, an evaluation index system for sustainable development has been established. This system includes economic benefits, social benefits, resource management, and environmental goals and is built upon a clear definition of the concept’s connotation. The CRITIC–entropy–TOPSIS–CCDM approach is employed for the computation of the coordinated development level of the manufacturing industry. To identify the main factors influencing the coupling coordination degree (CCD) from a mechanistic and compositional point of view, a logarithmic mean divisia index (LMDI) is used. Furthermore, the obstacle degree model analyzes the factors that restrict subsystem development. The results show the following. (1) The coordinated development level of the Chinese manufacturing industry has been maintained at 0.6–0.7, while the CCD of Hainan, Qinghai, and Xinjiang remains to be enhanced. (2) The key factor affecting the CCD is the coupling degree. The evaluation value of the economy and employment system determines the trend of coordinated development in the regional manufacturing industry. (3) The economic and employment scenarios in most provinces (cities) led to a significant decrease in the CCD compared to the baseline scenario, with average growth rates of −10.55% and −12.69%. This suggests that policymakers’ priorities significantly influence the CCD. The research presents a theoretical framework for assessing the sustainability of the manufacturing industry, offering valuable insights to guide the industry towards more sustainable practices. Full article

Developing industries and promoting employment are essential for rural revitalization. This study establishes a theoretical framework to support the coordinated development of rural industry and employment (RIE) with Chongqing, China as the study area. Methods include GIS spatial analysis, the entropy-weighted TOPSIS method, a coupled coordination degree model, and an optimal-parameter-based GeoDetector. The analysis examines the spatio-temporal evolution and driving mechanisms of the coordinated development of RIE. The main findings are as follows. (1) During the study period, Chongqing’s RIE improved significantly overall, although rural industry is relatively lagging. (2) The evolution characteristics of the coordinated development of RIE exhibit “spatio-temporal ripple” and “spindle-shaped” patterns, and the spatial agglomeration has been enhanced. The growth of RIE is accompanied by the spatial diffusion of rural industry and the spatial echo of rural employment. (3) The primary driving mechanism for the coordinated development of RIE is “human-centered, natural resource-based socio-economic development.” Finally, this study discusses employment-centered strategies for rural industrial development, providing a theoretical foundation for policy-making in rural industrial development. Full article