Search Results (8)

Understanding the efficiency of agricultural eco-product value realization is critical for sustainable development and regional equity. Here, we present a comprehensive analysis of the spatiotemporal patterns and regional disparities in the value realization efficiency of agricultural ecological products across China’s 31 provinces from 2010 to 2022. Utilizing an advanced Super-NSBM model, we quantify three dimensions of efficiency: overall value realization, economic value conversion, and social welfare value realization. Spatial mapping and dynamic evolution analysis are conducted through Dagum Gini coefficient decomposition and conditional kernel density estimation. Our results reveal three key insights: (1) China’s agricultural eco-product value realization efficiency remains suboptimal, with a gradual upward trend. Economic value conversion outperforms social welfare value realization, which exhibits significant regional heterogeneity. A distinct east–west gradient is observed, with Western regions demonstrating notable progress despite initial inefficiencies. (2) Inter-regional disparities are narrowing, particularly between Eastern and Central regions. While polarization in Northeast China has diminished, Western regions show widening efficiency gaps and emerging polarization trends. (3) Regional differences are predominantly driven by inter-group disparities, with Eastern China exhibiting the lowest intra-regional variability. Cross-regional differences follow a U-shaped trajectory, decreasing initially before rebounding in recent years. These findings provide a robust empirical foundation for optimizing regional strategies in ecological product value conversion and offer critical insights for addressing spatial inequities in sustainable agricultural development. Full article

Sustainable tourism entails balancing economic growth, environmental protection, and energy utilisation. However, the current interactive dynamics between urban agglomeration tourism systems and the energy–economy–environment (EEE) system, as well as the sustainable efficiency of the tourism–energy–economy–environment (TEEE) system, remain unclear. For the first time, this study employs a super-efficiency network slacks-based measure (SE-NSBM) model to interact with tourism and EEE systems, proposing a novel network structure that includes feedback variables. To validate the proposed model, this study evaluated the efficiency of the TEEE system and its subsystems in the Yangtze River Delta urban agglomeration (YRDUA) from 2016 to 2020. The study revealed significant variations in the efficiency of the TEEE, tourism, and EEE systems among cities in the YRDUA, with a discernible downward trend. The TEEE and tourism systems exhibit relatively weak coping capabilities when faced with significant unforeseen events, highlighting the urgent need to strengthen system resilience. The results also demonstrate that the new model effectively resolves the issue of efficiency overestimation in the TEEE system observed in traditional models, which tend to overestimate actual efficiency by 3%. The novel model and empirical results offer decision-makers new perspectives and practical insights into formulating sustainable tourism policies. Full article

Using the differential game model, this study examines the impact of the digital economy and regional cooperative innovation on green innovation efficiency. Additionally, based on the two-stage Super-NSBM model, this study evaluates the effects of the digital economy on green innovation efficiency, its spatial spillover effects, and the moderating role of regional cooperative innovation. The findings of the study indicate that (1) the digital economy significantly enhances green innovation efficiency but has negative spatial spillover effects on surrounding regions. (2) Regional cooperative innovation positively moderates the promotional effect of the digital economy on green innovation efficiency. Moreover, the moderating effect exhibits a single-threshold effect. (3) The influence of the digital economy on green innovation efficiency is more significant in regions with advanced industrialization, robust transportation infrastructure, and high R&D intensity. The coordinated development of digital industrialization and governance is crucial for effectively promoting the development of green innovation. Full article

Resolving the conflict between economic growth and ecological sustainability is crucial when transitioning from traditional economic development towards a sustainable green model. In this context, the super-NSBM model was applied to measure the efficiency of green innovation technology research and development. Additionally, it was applied to measure the efficiency of the green innovation achievement transformation among 30 Chinese provinces. This evaluation was conducted for the period from 2011 to 2021, and it utilized a two-stage innovation value chain perspective. The entropy method was used to comprehensively calculate the digital economy development index, and the impact of digital economy development on the two-stage green innovation effect was empirically explored using SDM. The findings revealed the following: Firstly, both two-stage green innovation efficiency and digital economy development exhibited significant spatial characteristics. Secondly, digital economy development had a positive effect on two-stage green innovation efficiency not only in the local region but also in neighboring regions. This conclusion remained valid throughout a series of robustness tests. Thirdly, in terms of regional heterogeneity, the eastern region and non-resource-based regions had greater digital economy development dividends than the central, western, and resource-based regions; therefore, the effect on two-stage green innovation efficiency was more significant. Lastly, both intellectual property protection and data factor endowment exerted positive moderating effects on the influence of the digital economy on two-stage green innovation efficiency. The conclusions of this research provide a theoretical backing for and empirical proof of the mechanism of digital economy development and its impact on two-stage green innovation efficiency. Policy implications are suggested based on these findings, such as reinforcing digitalization, establishing targeted policies, and fostering a favorable external environment conducive to technological innovation. Full article

The urban agglomerations in the Yellow River Basin are important carriers for China’s high-quality development. It is an inevitable trend to promote sustainable development and people’s well-being in the urban agglomerations of the Yellow River Basin. A case study of 70 cities of seven urban agglomerations in the Yellow River Basin from 2011 to 2017 is presented. The two-stage super-efficiency network slacks-based measure (Super-NSBM) model considering undesirable outputs is adopted to measure the ecological well-being performance (EWP), and the spatial correlation analysis method is used to analyze the spatio-temporal evolution characteristics of the EWP. The results show that the average EWP of the seven urban agglomerations in the Yellow River Basin was less than 1, showing a trend of firstly rising and then slowly decreasing. The average EWP presents the distribution pattern of the highest in the middle reaches, followed by the upper reaches, and the lowest in the lower reaches of the Yellow River Basin, respectively. The average ecological economic efficiency in the first stage of urban agglomerations of the Yellow River Basin was greater than the average economic well-being efficiency in the second stage. The average EWP in the Yellow River Basin shows local spatial heterogeneity during the study period. Policy measures are proposed to promote the improvement of the EWP of urban agglomerations in the Yellow River Basin. This study can provide reference for the policy formulation of high-quality green development and sustainable construction of urban agglomeration in the Yellow River Basin. Full article

Under the constraints of resources and the environment, improving the urban ecological well-being performance (EWP) is a fundamental requirement and inevitable choice for urban ecological civilization construction and sustainable development. In this paper, 36 Chinese major node cities along the Belt and Road were selected as the research area, and an EWP evaluation index system was constructed. The two-stage Super Network Slack-based measure (Super-NSBM) model was used to evaluate the static EWP from 2011 to 2018, and the Malmquist–Luenberger productivity index was used to evaluate the dynamic EWP. It was found that: (1) The EWP value of 36 Chinese major node cities along the Belt and Road from 2011 to 2018 did not reach effectiveness, with Sanya, Shenzhen, and Haikou being the top three performers. (2) In terms of two-stage efficiency, the ecological economic efficiency in the first stage was significantly lower than the economic well-being efficiency in the second stage, which indicated that the low ecological economic efficiency was the main reason for the low average value of the EWP. (3) From the dynamic analysis results, the Malmquist–Luenberger productivity index experienced a fluctuating upward trend, and the technical change was the main factor for the improvement in the EWP. Finally, policy recommendations were proposed based on the above findings. This study will contribute to the sustainable development of Chinese major node cities along the Belt and Road, and can provide a reference for other Belt and Road regions. Full article

With the continuous progress in global sustainable development, green innovation has become the primary driving force for the development of all countries and regions. China has implemented the strategy of constructing a cross-regional green innovation network. As the spatial correlation network structure of green innovation efficiency is complicated, it is necessary to study the change rules of the network structure to coordinate regional green and innovative development. In this paper, the Super-NSBM model is used to calculate the values of two-stage green innovation efficiency of China’s industrial enterprises from 2006 to 2019. Social network analysis is used to explore the rule of changes and causes of the spatial correlation network of two-stage green innovation efficiency. Our findings are as follows. Green innovation efficiency in the two stages presents the relationship of a non-adjacent complex network, and the network of green innovation and R&D efficiency is closely interconnected. Strong hierarchical correlation breaks down when searching for the best spatial configuration relationship. The transformation efficiency of the networked cooperation of green innovation achievements is stable. In the spatial correlation of green innovation and R&D efficiency, Guangdong, Shandong, Beijing, Jiangsu and Zhejiang are at the center of the network. In the spatial correlation of transformation efficiency of green innovation achievements, Shandong, Jiangsu, Guangdong, Henan and Hubei are in the center. The northern coastal areas fall within the scope of green innovation and R&D spillover has and have a close cooperation with the green innovation spillover plate in the southern coastal areas, making green innovation achievements spill over to the Chengdu-Chongqing region and northern region. The cooperation and connection of green innovation activities conform to the rule of geographical proximity. Environmental regulation and marketization are characterized by “hierarchy”, but the economic level is “non-hierarchical”. The government can implement relevant green innovation policies according to local characteristics. Our findings are of great significance to narrow regional green innovation gaps. Full article

Maintaining low ecological consumption and high well-being while making economic progress and thus achieving sustainable development is a significant issue facing the world today. Ecological well-being performance (EWP) is one indicator that tracks this progress. Although EWP has been typically assessed at the national, provincial and urban levels, investigations into EWP units in the Great Lakes region are lacking. This study applied the two-stage super-efficiency slack-based measure (Super-NSBM) model and DEA window analysis to evaluate the EWP and sub-stage efficiency in the Poyang Lake (largest freshwater lake in China) area and analyzed its spatial differences at the local level. Redundancy analysis was conducted to explore the EWP improvement paths of different counties in the Poyang Lake region and Dagum’s Gini coefficient was applied to clarify the policy priorities of coordinated regional development. Results showed that the EWP of the Poyang Lake area presents an improving trend from 2007 to 2019, although the overall level is still low. The Poyang Lake area mainly faces the incongruity of ecological and economic development, which is the main reason for the low overall level of EWP. Excessive resource input and severe environmental pollution are common in most counties, but the focus of measures to improve EWP differs from county to county. The expansion of spatial differences in eco-economic efficiency leads to the spatial differences of EWP in the Poyang Lake area being still apparent at the local level. Reducing inter-basin disparities while alerting the widening of intra-basin differences is the policy focus for the future coordinated development of the Poyang Lake area. Full article