Slacks-based Measure Research Articles

Network Centrality and Road Freight Efficiency: A Spatial Econometric Analysis of South Korea’s Transport Regions

Purpose - The purpose of this research is to investigate the road freight efficiency in 15 regions of South Korea using a super-efficiency SBM model and to understand the role of network centrality in influencing this efficiency. It aims to analyze how in-degree and out-degree centrality within the road freight network impacts the efficiency of road freight and how these effects manifest spatially across different regions. Design/Methodology – The study applied a super-efficiency Slacks-Based Measure (SBM) model to evaluate the efficiency of road freight across various regions. It incorporated two indices, indegree and out-degree centrality, to measure the network centrality of regions within the road freight network. Furthermore, it utilized the Spatial Durbin Model (SDM) to decompose and analyze the direct and indirect effects of network centrality on road freight efficiency, considering different spatial weight matrix. Findings – The study found that road freight efficiency in a region positively correlates with its centrality within the road transport network, indicating regions that are central to the network tend to utilize their inputs more effectively and improve transport efficiency. It also discovered positive spillover effects of network centrality, suggesting that a region’s central role in the network benefits not only itself but also adjacent regions. Originality/value - The research is valuable for its application of the super-efficiency SBM and SDM models to the context of road transport networks in South Korea, a relatively underexplored area in transportation studies. It contributes original insights into the spatial dynamics of road freight efficiency, emphasizing the role of network centrality and its variable effects across different regions.

Sustainable Impact of Green Building on the Eco-Economic Efficiency of the Construction Industry: Evidence from China

Addressing the global warming challenge, the carbon emissions reduction potential of green building (GB) is garnering increasing attention. However, the extent to which GB can impact the eco-economic efficiency (EE) of the construction industry remains unclear. To fill this gap, based on panel data for 30 regions of China from 2003 to 2018, in this study, a comprehensive analysis of the EE and sustainable impact of GB is conducted using a super slacks-based measure (SBM-DEA), panel vector autoregression (PVAR) and threshold models. The findings reflect that only about 10% of provinces have achieved EE effectiveness, with pure technical effectiveness being a significant driving force behind this. The average comprehensive, pure technical, and scale EE show a 62.23%, 46.42%, and 31.91% improvement potential regarding the efficiency frontier. The EE in the Eastern Region is relatively high, while the Western Region surpassed the Central Region in regards to EE in the areas of scale and pure technical efficiency. EE is significantly reduced in the current period (year) when it is subject to the positive impact of a standard deviation from the existing economic level. This impact was the strongest in period 1, then gradually disappeared until period 6, aligning with the Kuznets curve’s theoretical assumption. GB awareness negatively impacted the current period, but is expected to gradually show a positive effect after period 2. The urbanization, green building awareness, and green building coverage make a very small contribution to the EE, accounting for 8.6%, 1.6%, and 9%, respectively, with early EE and economic level identified as the primary variables affecting the current EE. The impact of GB on EE exhibits a threshold effect, with the ecological effect of GB significant only in cities with economic levels higher than 11.063. This research contributes to the existing knowledge of the eco-economic mechanism of GB and provides insights for government policies, promoting the sustainable development of the GB market.

Decomposing the comprehensive efficiency of major cities into divisions on governance, ICT and sustainability: network slack-based measure model

The rapid urbanization and population growth in major cities have given rise to enduring urban challenges, prompting local governments to assess urban development performance and customize urban planning strategies to meet these challenges. This study aims to formulate an evaluation framework for the comprehensive efficiency of major cities, centering on governance, Information and Communication Technology (ICT), and sustainability as fundamental aspects. Distinct from prior research, the framework employs the network slack-based measure (SBM) to unravel efficiency, concurrently scrutinizing input/output slack and link efficiency. Utilizing the network SBM model, the study assesses the comprehensive operational efficiencies of 38 major Chinese cities spanning from 2015 to 2019. The application of the Kruskal–Wallis test discerns differences in comprehensive efficiency between coastal and inland areas. The results indicate that governance, ICT, and sustainability significantly influence the comprehensive operations of cities. In addition to general and short-term policies, the implementation of the National New-Type Urbanization Plan by the Chinese central government has led to an increase in the number of cities demonstrating sustainable efficiency. Despite fluctuations in the efficiency gap during the study period, coastal cities consistently outperform their inland counterparts in terms of efficiency. Persistent geographical disparities underscore the imperative for balanced development. While acknowledging positive strides in sustainable urbanization, the study emphasizes the ongoing necessity to address the adverse impacts of urban development, positioning governance, ICT, and sustainability as indispensable elements in confronting the multifaceted challenges inherent in urban development. The research findings contribute significantly to the field of urban efficiency evaluation, accentuating the collaborative impact of governance, ICT, and sustainability.

Impacts of Low-Carbon Pilot Policies on the Land Green Use Efficiency in Adjacent Non-Pilot Cities: An Empirical Study Based on 257 Prefecture-Level and above Cities in China

In the context of global climate change, the low-carbon city pilot policy has become an important strategy to promote green development. Based on the panel data from 257 prefecture-level and above cities in China, this study utilized the Super-Efficiency SBM (Slacks-Based Measure) to measure the land green use efficiency and analyzes the impact of the policy on adjacent non-pilot cities using a difference-in-differences model. The findings indicate that the implementation of low-carbon pilot policies can significantly improve the land green use efficiency in adjacent non-pilot cities, which can be primarily ascribed to the spillover effect and catfish effect. A heterogeneity analysis further revealed the positive effects of the policies in the eastern region and non-resource-based cities. This study provides valuable references for relevant legal provisions on environmental regulation and for continuously monitoring and evaluating the policy effects to achieve sustainable development goals.

Evaluation of China’s Marine Aquaculture Sector’s Green Development Level Using the Super-Efficiency Slacks-Based Measure and Global Malmquist–Luenberger Index Models

Given China’s rapidly expanding marine aquaculture industry, the associated ecological issues have garnered widespread attention. Therefore, it is crucial to speed up the green growth of marine aquaculture in order to save the environment and use resources sustainably. In order to statically assess and dynamically analyze the green development efficiency levels of marine aquaculture in nine coastal provinces of China from 2012 to 2021, this study uses the non-expected output super-efficiency Slacks-Based Measure model and the Global Malmquist–Luenberger index method. Additionally, it integrates input–output redundancy rates to analyze the causes of efficiency loss. Static efficiency primarily reflects whether a region’s inputs and outputs at a given point in time reach an effective efficiency level, while the level of dynamic efficiency mainly gauges the dynamic changes in the efficiency of green production. The results show that, from 2012 to 2021, China’s marine aquaculture industry’s average static efficiency of green output was 0.705. The southern marine economic zone exhibited the highest static efficiency value in the green development of marine aquaculture, displaying a stepped distribution pattern of “south–north–east” in decreasing order. The input–output redundancy analysis reveals that the primary causes of static efficiency loss in China’s marine aquaculture industry are attributed to varying degrees of redundant inputs and carbon emission outputs. Looking through the lens of the GML index, the annual average growth rate of the green total factor productivity in China’s marine aquaculture stands at 11.1%, with an annual average change in technical efficiency of 1.8%, while the annual average change in technological progress amounts to 9.1%, suggesting that technological advancement is the primary driver of the rise in green total factor productivity in China’s marine aquaculture sector. According to the study, in order to encourage China’s marine aquaculture industry to grow sustainably, efforts should be made not only to accelerate technological advancements but also to enhance technical efficiency. Policies that are specifically designed for the local environment should be developed to support the sustainable development of the marine aquaculture sector and to make resource allocation easier.

Spatiotemporal patterns, effects, and the interactive driving mechanisms of urban sustainability based on the eco-efficiency framework: Evidence from Chinese prefecture-level cities

Eco-efficiency is a vital tool for evaluating and advancing regional sustainable development. This study presents an urban eco-efficiency (UEE) framework that deserves widespread application. By using the Super Slacks-Based Measure model, the research calculates the UEE of 284 prefecture-level cities in China from 2005 to 2022. The study employs the Standard Deviational Ellipse to illustrate the spatiotemporal pattern of UEE in China and examines its effects using non-parametric kernel density estimation, the coefficient of variation, and both global and local Moran's I. The integration of UEE with urban development patterns, which is not immediately clear, is achieved through the entropy-based TOPSIS model. Additionally, the Malmquist index, the Two-way Fixed Effects (TWFE) model, and the Panel Vector Autoregression (PVAR) model reveal the dynamic changes and interactive driving mechanisms of UEE in China. The results indicate that: (1) UEE in China displays a consistent “core-periphery” pattern, exhibiting a notable hierarchical impact from regional, scale, and administrative perspectives. The complexity of UEE's spatiotemporal variations has increased due to the impact of COVID-19. (2) The UEE of Chinese cities shows a significant ‘club’ effect, with efficiency thresholds for high-high and low-low aggregations set at 0.8. (3) Only 25% of Chinese cities have achieved optimal UEE levels. Notably, cities in the west contribute most to national UEE growth, while midland cities contribute the least. The decreasing trend in UEE growth underscores the urgent need for a shift in China's urban development model. (4) UEE in China benefits from a resilient self-reinforcing mechanism, with urban development and economic growth significantly aiding UEE growth. Despite a non-significant negative impact from government intervention, the inhibitory effect of an intensive industrial structure on UEE turns into a promotional effect, especially following COVID-19.

Spatial and temporal variation and convergence in the efficiency of high-standard farmland construction: Evidence in China

To assess the efficiency of high-standard farmland construction (HSFC), this study utilized data spanning from 1998 to 2020 obtained from 30 provinces, autonomous regions, and municipalities in China. This assessment was conducted using a three-stage super-efficient slack-based measure data envelopment analysis(SBM-DEA)model. Furthermore, we investigated the spatial and temporal variances and convergence of HSFC efficiency using the Dagum Gini coefficient and convergence analysis. The results firstly show that from 2007 to 2020, China's HSFC efficiency displayed fluctuations and declines, significantly influenced by environmental and stochastic factors. Secondly, it showed that the gap in China's HSFC efficiency has widened, with super-variable density being demonstrated as the primary source of spatial imbalance in HSFC efficiency. Thirdly, it showed that the deviation in the efficiency of HSFC in the central region of China from the average level has shown a gradually declining trend, while the deviation in the efficiency of HSFC in the national, western, eastern, and northeastern regions has not presented a downward trend. Fourthly, it demonstrated that over time, the efficiency of building high-standard agriculture throughout the nation and its four main areas will converge to the same level.

Unveiling the Patterns and Drivers of Ecological Efficiency in Chinese Cities: A Comprehensive Study Using Super-Efficiency Slacks-Based Measure and Geographically Weighted Regression Approaches

Urban ecological efficiency stands as a pivotal indicator that mirrors the level of sustainable development within cities. To unravel the sustainable development status of Chinese cities and illuminate the factors impacting the diverse developments among them, this study leveraged the super-efficiency SBM (slacks-based measure) model to assess the ecological efficiency of 284 prefectural-level and above cities across China in 2019, divulging their spatial distribution. Furthermore, a GWR (geographically weighted regression) model was also employed to scrutinize the factors influencing the ecological efficiency of these cities. Key findings include: (1) The mean ecological efficiency of Chinese cities in 2019 stood at 0.555, signaling moderate urban sustainability, with southern cities outperforming their northern counterparts. (2) A pronounced spatial clustering of ecological efficiency was evident, featuring positive spillover effects around high-efficiency cities and conversely, negative spillover effects around low-efficiency cities. (3) Economic development and population density positively influenced urban ecological efficiency, while urbanization levels exhibited a negative impact. The influences of industrial structure, technological level, and opening-up level varied, showcasing both positive and negative impacts contingent upon the spatial disposition of the cities. Hence, policymakers are advised to recognize the spatial nuances in the impacts of distinct factors on urban ecological efficiency and tailor measures accordingly to fortify urban sustainability.

Assessing the impact of prefabricated buildings on urban green total factor energy efficiency

Prefabricated buildings (PB) are assembled using prefabricated components, known for their cost-effectiveness and high efficiency. They are seen as an effective means to achieving sustainable development goals and mitigating climate change. This paper examines the impact of prefabricated buildings on urban green total factor energy efficiency (GTFEE) using panel data from 278 cities in China. The analysis is conducted through the application of a super-efficiency slack-based measure (SBM) model and a difference-in-differences model. The results of the study indicate that the promotion of PB can significantly improve urban GTFEE; there is heterogeneity in the improvement of urban GTFEE by PB; the innovation effect, industrial effect and marketization effect of PB are the main ways to improve urban GTFEE. Specifically, PB exerts an innovation effect by promoting technological innovation. It influences consumer and investor demand, leading to increased activity in the secondary industry, thereby creating an industrial effect. Moreover, PB facilitates the marketization effect by phasing out outdated industries, encouraging autonomous enterprise innovation, and fostering the growth of new advanced enterprises. This study reveals the critical role of PB in urban GTFEE improvement. It clarifies its mechanism of action, which provides a reference for urban sustainable development strategies and energy efficiency.

Analysis of regional differences and evolution features for waterway transport efficiency in the Yangtze River Economic Belt considering undesired outputs

Waterway transport plays an increasingly important role in pursuing the sustainable development of the transportation industry and promoting regional economic development. Understanding the regional differences and evolution features of waterway transport efficiency (WTE) is a requisite for formulating waterway transport development policies. However, many studies of transport efficiency mainly focus on road, railway, and air transportation. Few studies have conducted an in-depth analysis of the WTE in the Yangtze River Economic Belt (YREB) from the perspective of considering undesired output. Adopting the Super slack-based measure (Super-SBM) model, Dagum Gini coefficient, and kernel density estimation as an analysis tool, this study explored the WTE’s region disparities and dynamic evolution features based on the data from 2011 to 2020 in YREB. The analysis results represent that: (1) there represented a fluctuating and slowly upward trend of waterway transport efficiency during the study period. (2) The midstream region has the highest waterway transport efficiency, followed by the upstream region, and last is the downstream region. (3) The regional disparities in waterway transport efficiency exist in YREB, and the primary source of these differences is the inter-regional difference. And (4) the polarization phenomenon and agglomeration characteristics of waterway transport efficiency in YREB are gradually weakened and decreased, respectively. In the end, this article summarized the implications of this study to improve the waterway transport efficiency and service capabilities in YREB.

Pathways to enhance the efficiency of forestry ecological conservation and restoration: empirical evidence from Heilongjiang Province, China

This paper proposes a theoretical framework for assessing ecological protection and restoration from the perspective of ecological efficiency. We applied the super-efficiency Slack-based measure model to examine the social and economic impacts of ecological resource consumption transformation in Heilongjiang Province, China. Additionally, a convergence analysis was used to evaluate and test the impact of the standard deviation ellipse method on regional sustainability. The results indicated that the land use structure was unstable; the conversion rate of resource consumption was low; and the average Ecological efficiency was only 0.343 in terms of the land use structure. Funds for forest ecological restoration have a significant impact on the effectiveness of ecological resource transformation. Implementing the Chinese ecological restoration project improves the ecological efficiency level of the communities. The center of gravity of ecological efficiency moved greatly in the years when forestry investment increased. Technological transfer and diffusion, experience imitation in environmental regulation, and eventually convergent steady-state levels of the ecological efficiency of different regions are necessary to improve the economic and social development level of regions with low environmental quality efforts should be made to reduce resource consumption intensity, increase fund utilization efficiency, and form a comprehensive and systematic system of ecological environment governance through reasonable enhancement of regional environmental regulations, increased investment in technological advancement, and funds for ecological protection and restoration.

A Sustainable Development Study on Innovation Factor Allocation Efficiency and Spatial Correlation Based on Regions along the Belt and Road in China

The level of development of the innovation factor plays a crucial role in supporting the high-quality sustainable development of China’s economy. In order to advance the sustainable development of regional innovation factor allocation efficiency along the Belt and Road this study introduces the super-efficient slacks-based measure (SBM)-data envelopment analysis (DEA)-Malmquist model for static and dynamic analyses of innovation factor allocation efficiency in 17 provinces along the Belt and Road from 2012 to 2021. This study used the Moran index model to analyze spatial correlation. The results show the following: (1) The overall innovation factor allocation efficiency along the Belt and Road is not high, and there are obvious differences among different regions. The eastern region’s efficiency is the highest compared to other regions. (2) According to the efficiency decomposition results, pure technical efficiency (PTE) is the main reason for the low innovation factor allocation efficiency. (3) Through the Malmquist index and decomposition index, it was found that pure technical efficiency (PECH) and scale efficiency (SECH) are key factors in improving technical efficiency (TECH). (4) The analysis of spatial correlation revealed a strong spatial agglomeration feature among the provinces along the Belt and Road. Innovation factor allocation efficiency is mainly manifested in the third quadrant. Finally, drawing on the results of the analysis, suggestions and policies are put forward to improve innovation factor allocation efficiency in the regions along the Belt and Road. This study is of great significance for promoting the sustainable development of the regional innovation level along the Belt and Road in China.

Evaluation of Energy Efficiency and Analysis of Influencing Factors of Company CW’s Manufacturing Workshops

In this work, the Slacks-Based Measure (SBM) model within Data Envelopment Analysis was employed toestablish a set of indicators for evaluating the energy efficiency of manufacturing workshops. The energy efficiency of 12 Company CW’s manufacturing workshops from 2016 to 2022 was assessed. The findings indicated that aside from a few workshops operating at the production frontier, the rest exhibit significant fluctuations in energy efficiency and generally low energy efficiency. Subsequently, a combined GRA-Tobit analysis model was introduced to identify factors influencing the energy efficiency of Company CW’s manufacturing workshops. Regression analysis revealed that technological investments, employee quality, workshop production scale, investment in clean energy, and the level of pollution control all significantly impact the energy efficiency of Company CW’s manufacturing workshops. By evaluating the energy efficiency of Company CW’s manufacturing workshops and studying their influencing factors, this research aids companymanagers in understanding the energy efficiency of the manufacturing process. It optimizes the combination of various production elements, thereby offering effective guidance for improving the energy efficiency issues of the company’s manufacturing workshops, which can contribute to enhancing the corporation’s overall energy efficiency.

Clean air policy and green total factor productivity: Evidence from Chinese prefecture-level cities

Clean air policy is an important mechanism for improving the urban environment and promoting green economic development. Green total factor productivity (GTFP) is an important way to measure these impacts. We apply the super-efficiency slack-based measure model, considering undesirable output, and the Global Malmquist-Luenberger index to measure the GTFP of 278 prefecture-level cities in China from 2005 to 2020. We find that GTFP growth is driven by both green technology progress (GTC) and green technology efficiency change (GEC). The traditional total factor productivity is overestimated, because energy and environmental factors are not considered. GTFP growth is higher in the cities in the eastern coastal regions compared to the western regions. We analyze the effect of clean air policy on GTFP using a difference-in-differences model and spatial-difference-in-differences model, and further conduct a heterogeneity analysis and mechanism analysis. The results show that clean air policy promotes GTFP growth. In addition, there is a significant negative spatial spillover effect with respect to the impact of clean air policy on GTFP. The heterogeneity analysis results show that the impact of clean air policy on GTFP growth is lower in resource-based cities and cities in the northern region, compared with non-resource-based cities and cities in the southern region. Further, the impact of clean air policy on GTFP growth is mainly achieved through GTC, GEC, innovation, and financial development. In resource-based cities and cities in the northern region, clean air policy decreases GTFP by inhibiting GTC, innovation, and financial development.

Sustainable energy efficiency in China from the perspective of environmental development: A comprehensive analysis of regional disparities and policy implications

Global agreements have emerged in order to achieve carbon neutrality as the needs for renewable energy sources and carbon reduction continue to grow. To achieve the global carbon neutrality goals, China, one of the largest carbon emitters, must improve urban energy efficiency. Using a three-stage slacks-based measure (SBM) technique, this study analyses the total factor energy efficiency of 270 prefecture-level cities from 2011 through 2020. It tries to monitor and evaluate energy efficiency without taking into account variations in the outside environment. China's total factor energy efficiency shows an overall rising trend, despite significant regional variations. Improved energy efficiency levels can be attributed to technical advancements, while limitations in technology contribute to lower energy efficiency in certain areas. The study highlights the importance of considering external environmental factors in evaluating energy efficiency, able to avoid an overestimation of China's overall energy efficiency. It is noteworthy that the eastern region consistently outperforms the national average in terms of energy use efficiency. Even after taking environmental factors out of the equation, the central, west, and northeast regions still have worse energy efficiency and slower rates of growth. On this basis, from strengthening energy management and planning; facilitating cross-regional sharing of expertise; take targeted policy measures to adapt to the characteristics of the western and northeastern regions and put forward policy suggestions. These guidelines contribute to international energy cooperation and carbon reduction initiatives, while promoting sustainable energy development in China.

Socioeconomic inequalities in healthcare system efficiency in Japan during COVID-19 pandemic: an analysis of the moderating role of vaccination.

In the context of the COVID-19 pandemic, limited research has focused on socioeconomic disparities in Local Healthcare System Efficiency (LHSE) among Japanese prefectures. This study seeks to investigate the moderating impact of vaccination on the relationship between LHSE and socioeconomic characteristics and endowments. To explore these relationships, we first utilized the Data Envelopment Analysis with Slack-Based Measure to measure the LHSE, based on data from Japanese prefectures during waves 2 to 5 of the pandemic. Then estimating the impact of socioeconomic variables on LHSE. Finally, we assessed the changes in the way socioeconomic variables affect LHSE before and after vaccine deployment using the Seemingly Unrelated Estimation t-test methodology. The research findings suggest an overall reduction in LHSE disparities across various regions due to the utilization of vaccines. Particularly in areas with relatively nsufficient bed resources, a significant improvement in LHSE was observed in most regions. However, there was no evidence supporting the role of vaccine deployment in mitigating socioeconomic inequalities in LHSE. Conversely, the utilization of vaccines showed a positive correlation between the improvement in LHSE and the proportion of older adult population in regions with sufficient bed resources. In regions facing bed shortages, the enhancement of LHSE became more reliant on reducing the occupancy rate of secured beds for severe cases after the introduction of vaccination. In regions facing bed shortages, the enhancement of LHSE became more reliant on reducing the occupancy rate of secured beds for severe cases. This underscores the importance for policymakers and implementers to prioritize the treatment of severe cases and ensure an effective supply of medical resources, particularly secured beds for severe cases, in their efforts to improve LHSE, in the post-COVID-19 era with rising vaccine coverage.

Regional efficiency and total factor productivity change for small and medium sorghum producers in Zambia: A slacks-based measure and Malmquist index approach

Zambia's efforts to promote countrywide production of sorghum is backed by a number of apropos factors. It is not only an adaptive response to the climate change challenge, but also a dietary diversity improvement measure, to achieve food and nutrition security. Further, improved sorghum production will supply emerging agro-industries, especially specialty foods, beverages and stock feed manufacturing in the country. However, regional sorghum production efficiencies in Zambia are not well known. This paper attempts to evaluate regional sorghum production technical efficiencies (TE), as well as Total Factor Productivity (TFP) change from 2011 to 2022. To study these aspects, we apply non-parametric Data Envelopment Analysis (DEA) techniques such as the Slacks-Based Measure (SBM), and the Malmquist Productivity Index (MPI), followed by bootstrap OLS regression respectively. Cross-sectional estimates from the SBM model for the 2022 cropping season indicate that average TE for small and medium sorghum farmers in Zambia was 85 percent. Sorghum production could be expanded by 411.90 t by improving TE in five of ten provinces in Zambia. The MPI shows that TFP for sorghum production in Zambia declined by 21 percent, mainly due to deteriorating sorghum production technology. Populations, rurality, agro-ecological zone IIB are the factors associated with EC and TFP decline.

Assessment of working capital management efficiency – a two-stage slack-based measure of data envelopment analysis

PurposeThis study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.Design/methodology/approachThe current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.FindingsThe results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.Originality/valueInstead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.

Energy Poverty Impact on Sustainable Development of Water Resources in China: The Study of an Entropy Recycling Dynamic Two-Stage SBM Model

Water scarcity is increasingly being recognized as a global concern. Sustainable Development Goal 6 (SDG-6) was established by the United Nations to address water resource governance within its sustainable development framework. This study employs the entropy weight method and a two-stage cyclical dynamic slacks-based measure (SBM) model to scientifically evaluate water resource utilization and governance across various regions in China. The findings reveal notable disparities in both the production and governance efficiency of water resources. Recognizing governance efficiency is crucial for promoting sustainable water resource utilization and socioeconomic development. The eastern, central, and western regions encounter unique challenges in attaining sustainability. The eastern region exhibits minimal potential for enhancing technical efficiency, necessitating interventions in management strategies and resource allocation. Conversely, the challenges in the central and western regions are more pronounced, demanding immediate implementation of new technologies and equipment. The data analysis in this study yields conclusions that offer targeted improvement recommendations to address disparities across China’s eastern, central, and western regions, and this is achieved by considering various developmental stages and regional contexts. These recommendations cover areas such as technical support, financial investment, and policy incentives, with the aim of enhancing the sustainable utilization of water resources in the country.

Linking natural resource abundance and green growth: The role of energy transition

A better understanding of the impact of natural resource abundance on green growth in the context of the energy transition could serve to break the resource curse and avoid pollution transfer, thereby promoting green and sustainable development. To this end, this study combines the Slack-Based Measure (SBM) method and the Global Malmquist-Luenberger (GML) index to measure the green growth in 77 countries from 2002 to 2019, and examines the impact of natural resource abundance on green growth. This study also investigates the moderating role of energy transition, heterogeneity analysis, and asymmetry analysis. The results show that (i) the average green growth levels for most countries surpassed 1, indicating green growth is the trend. (ii) The impact of natural resource abundance on green growth is negative, indicating that the natural resource abundance hinders the improvement of green growth. Moreover, this negative impact is more prominent in countries with lower natural resource abundance and lower green growth. (iii) Energy transition can effectively alleviate the negative impact of natural resource abundance on green growth. Besides, this mitigation effect is greater in high-resource-abundance countries than in low-resource-abundance countries. Finally, this study highlights several policy implications to break the resource curse and achieve green growth.