Super-efficiency Slack-based Measure Research Articles

The threshold effect and driving path of the rapid transit system on tourism eco-efficiency in China

Rapid transit is important for the green development of China’s tourism industry because it profoundly affects the optimal structural layout and rational allocation of elements that impact regional tourism. Based on provincial panel data from 2009 to 2020, the entropy weight method, tourism carbon emission measurement model, Super efficiency slacks-based measure model and threshold regression model were used to determine the impact of the rapid transit system on tourism eco-efficiency in China. The findings showed that rapid transit system has increased steadily, while tourism eco-efficiency has fluctuated significantly, and the relative development characteristics of rapid transit system and tourism eco-efficiency gradually changed from “lagging rapid transit system” to “lagging tourism eco-efficiency.” In addition, the rapid transit system and the highway and civil aviation have a nonlinear relationship with tourism eco-efficiency, while the high-speed railway has not passed the threshold effect test, and at the regional level, the impacts of rapid transit system have heterogeneous characteristics. As the deepening construction of rapid transit system, its threshold effect on tourism eco-efficiency will change from positive “V” to positive “U” type, promoting the more efficient development of environmentally friendly tourism.

Has the Digital Economy Improved the Urban Land Green Use Efficiency? Evidence from the National Big Data Comprehensive Pilot Zone Policy

The advancement of the big data industry is playing a pivotal role in urban land management refinement. Recently, China initiated a big data strategy, establishing national big data comprehensive pilot zones (NBDCPZs) across diverse regions. These initiatives present substantial opportunities for enhancing the urban land green use efficiency (ULGUE). Consequently, in this study, we utilized the super-efficiency slack-based measure (SBM) model with undesirable outputs to assess the ULGUEs across 281 prefecture-level cities in China from 2006 to 2021. Subsequently, leveraging the NBDCPZ establishment as a quasi-natural experiment, we employed the difference-in-differences (DID) method to empirically explore the impact of the NBDCPZ policy on the ULGUE for the first time. The findings revealed the following: (1) The implementation of the NBDCPZ policy significantly enhances the ULGUE; (2) the effects are mediated through mechanisms such as fostering technological innovation, mitigating resource misallocation, and promoting industrial agglomeration; (3) the heterogeneity analysis emphasizes the increased policy effectiveness in cities characterized by fewer natural resources, lower economic growth pressures, stable development stages, and moderate digital infrastructure and human capital levels; and (4) further analysis demonstrates the significant positive spillover effects of the NBDCPZ policy on the ULGUEs of neighboring non-pilot cities, with a diminishing impact as the proximity between pilot and non-pilot cities decreases. Overall, this study contributes to the literature on the relationship between the digital economy and land utilization, offering valuable insights for achieving sustainable urban development.

Analysis of dynamic relationship between agricultural products circulation service industry and circulation efficiency in less developed regions: based on data from Western China

The market circulation system for agricultural products in less-developed regions lags behind; it fails to meet the requirements for efficient circulation. Therefore, it is crucial to explore the dynamic relationship between the Agricultural Products Circulation (APC) service industry and circulation efficiency. Using panel data from 29 regions in China, the entropy method measured the Development Level (DL) of the APC service industry, while the non-oriented super-efficiency Slacks-Based Measure (SBM) model was employed to assess the APC efficiency. A Panel Vector Autoregressive (PVAR) model was built for estimation. The impulse response function and variance decomposition were utilized to analyze the differences in the DL of the APC service industry, circulation efficiency, and their interaction mechanism across the Western, Central, and Eastern regions of China. The findings indicate that the DL of the APC service industry and APC efficiency in the less-developed regions of the West have a positive driving effect on each other. However, the magnitude of this effect was asymmetric and transient. The APC service industry’s DL and APC efficiency are more dependent on their inertia, and no efficient two-way feedback mechanism has been formed. This study provides a reference for the construction and sustainable development of modernized APC systems in less-developed regions.

Provincial-scale assessment of vulnerability and resilience to drought in China

Frequent droughts have caused severe disaster losses in China. Such events can be minimized by enhancing the country's resilience and reducing its vulnerability, where this can ensure socioeconomic stability and sustainable development. Evaluating the vulnerability and resilience to drought is thus crucial for effectively managing the risk of disasters and promoting sustainable socioeconomic development. In this study, we constructed a comprehensive framework to assess the spatiotemporal characteristics of China's vulnerability and resilience to drought at the provincial scale from an input-output perspective by using the Super-efficiency Data Envelopment Analysis (DEA) model and the Super-efficiency Slacks-Based Measure DEA (SBM-DEA) model. This study focused on drought drivers, the disaster-forming environment, drought bearers, disaster intensity, and recovery. The results showed that the vulnerability to drought of 42 % of China's provinces decreased from 2010 to 2022, that of only 29 % of the provinces increased, while the status of a majority of provinces improved in general. The center of gravity of the vulnerability to drought moved toward the southwest over time and a spatial clustering of vulnerability was observed, with High-High clusters moving from the north to the south. Moreover, the resilience to drought declined in 36 % of provinces and increased in only 20 %, reflecting poor resilience overall. The center of gravity of China's overall resilience to drought moved northward, with a relatively stable spatial pattern and prominent clusters of Low-Low resilience indicating a pressing need for improvement. Areas with high vulnerability and low resilience were concentrated in inland western and eastern regions, and this highlights the importance of drought prevention and mitigation in provinces like Xinjiang, Inner Mongolia, Jiangxi, and Fujian. The findings here provide valuable insights for mitigating the risk of drought and promoting sustainable socioeconomic development.

The Impact of the Carbon Emission Trading Shadow Price on the Green Total Factor Productivity of the Power Industry in China

To mitigate the problem of global climate change, governments have taken measures to reduce greenhouse gas emissions. Carbon emission trading has gradually attracted attention as a market-oriented option. Power industry panel data from 30 provinces in China were used for an empirical analysis in this study. The super-efficiency Slack-Based Measure (SBM) model was used to calculate the shadow price of carbon trading and the green total factor productivity (GTFP), and the Ordinary Least Squares (OLS) regression model was used to quantitatively analyze the correlation between the shadow price of carbon trading and the GTFP of the power industry. The results showed that the shadow price of carbon trading had a significantly negative impact on the GTFP of the power industry; therefore, it needs to be improved and perfected. Through a further analysis using the heterogeneity test, it was found that there were problems in the current carbon trading price mechanism. In the face of the above problems, we offer suggestions for improvement from the perspectives of the government and companies. This study helps deepen the understanding of carbon trading prices and the GTFP in the power industry, and it provides a reference for formulating more effective carbon trading policies and corporate green management strategies.

Impact of rural digital economy development on agricultural eco-efficiency: evidence from mainland China

The integration of the digital economy with rural development is of great significance as it plays a pivotal role in mitigating carbon emissions and environmental pollution in agriculture, thereby contributing to the evolution of agriculture in a green and sustainable manner. This study aims to examine the impact and mechanisms of rural digital economy development (RDED) on agricultural eco-efficiency (AEE). Specifically, based on provincial-level panel data from China spanning from 2011 to 2021, we evaluate China’s AEE by employing the super-efficiency slacks-based measure (Super SBM) model, taking into account the positive externality of agricultural carbon sinks. Then we analyze the impact and mechanisms of RDED on AEE using the two-way fixed effects model. The findings indicate that: (1) RDED significantly promotes AEE, and this conclusion remains robust even after being tested by replacing the explained variable, altering the sample interval, and including more control variables; (2) RDED can significantly drive AEE in the midwestern regions of China, but the promotion effect on the eastern region has not been fully demonstrated. Additionally, the promotion effect in southern China is greater than that in northern China; (3) agricultural science and technology investment partially mediates the impact of RDED on AEE. Moreover, agricultural science and technology innovation has a positive moderating effect on the relationship between RDED and AEE. Lastly, this study provides new evidence and policy recommendations for developing countries, such as China, to proactively facilitate the coordinated development of the rural digital economy and agricultural ecology, and attain green and sustainable ecological agriculture.

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.

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.

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.

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.

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.

Spatial-temporal evolution and trend prediction of ecological civilization construction efficiency from the perspective of audit

The performance evaluation of ecological civilization construction is an important content of ecological civilization audit. The super-efficiency slacks-based measure model measured inter-provincial ecological civilization construction efficiency based on the panel data of Chinese provinces and cities during 2000–2020. Based on the time series and spatial correlation analyses, the traditional and spatial Markov probability transfer matrixes were constructed to explore the spatial and temporal dynamic evolution characteristics of China’s ecological civilization construction efficiency and predict its long-term trend. The study revealed that China’s ecological civilization construction efficiency has a “bimodal” distribution with a stable increase in fluctuation. The gap between the peak heights is small; however, the overall ecological civilization construction efficiency is low. We also revealed that from the long-term evolution trend forecast, most provinces and cities gradually shift to higher levels of ecological civilization construction efficiency and gradually evolve into having a gradual increase pattern in the geographical context of low ecological civilization construction efficiency, resulting in the long-term evolution of the stable state performance. In the geographic context of low ecological civilization construction efficiency, the long-term evolution of the stable state is a partial “single-peaked” distribution. Finally, we analyzed the directions for improvement in this study and suggested that inter-regional ecological civilization construction policy connections and the fortification of inter-regional ecological civilization construction cooperation and exchange can effectively improve China’s ecological civilization construction efficiency, narrow the gap between provinces and cities, and promote the construction of ecological civilization.

Evaluation of Low-Carbon Economic Efficiency under Industrial Clustering and Study of Regional Differences, Taking Xinjiang as an Example

As a major resource region, Xinjiang is both China’s energy security base and an important hub connecting Asia and Europe. Following the country’s call for carbon emission reduction, the Xinjiang government proposes to accelerate the construction of eight major industrial clusters in 2023. The concept of sustainable development is also reflected in the industrial clusters in areas such as new energy. In this study, we combined panel data from 14 regions and cities in Xinjiang from 2006 to 2020 and analyzed the synergy between the development of industrial clusters, carbon emissions, and economic growth using a coupling coordination degree model. Subsequently, we used the super-efficiency slack-based measure (SE-SBM) and Dagum’s Gini coefficient to analyze the spatial disequilibrium of efficiency measures and efficiency cases. The results show the following: (1) Overall, the industrial clusters, carbon emissions, and economic growth in the 14 regions and cities of Xinjiang are not well coordinated. The best reported level has been medium coordination, but there exists a certain degree of correlation among the three. (2) Low-carbon economic efficiency under the influence of industrial clusters in the 14 regions and cities shows significant regional differences. The regions and cities with low-carbon economic efficiency greater than 0.8, which is significantly better than the other regions in terms of efficiency, are all located in northern Xinjiang. (3) During the study period, the overall regional difference in low-carbon economic efficiency under industrial clusters in Xinjiang decreased from 0.183 to 0.17. However, the regional differences were still large. The conclusions indicate that policies for industrial clusters in Xinjiang can promote industrial development, and there may be a correlation between them and the low-carbon economy. This will effectively contribute to local sustainable development. However, overall regional differences are significant, and the degree of coordination is low. Therefore, we suggest that the government can share the advantages of development by constructing cross-regional cooperation platforms. At the same time, the Xinjiang government should make full use of the rich local wind and solar energy resources and explore a low-carbon path toward transforming the traditional energy industry. It can also be seen that industrial clusters in Xinjiang can effectively promote local sustainable development.

Spatial and temporal distribution characteristics and influencing factors of tourism eco-efficiency in the Yellow River Basin based on the geographical and temporal weighted regression model.

With economic progression in China, Yellow River Basin serves as a critical economic belt, which has also been recognized as a cradle of Chinese culture. A watershed is a complex structure of social, economic, and natural factors, and the diversity of its components determines its complexity. Studies on the spatiotemporal distribution characteristics and factors influencing the tourism eco-efficiency at the watershed scale are crucial for the sustainable regional socio-economic development, maintaining a virtuous cycle of various ecosystems, and comprehensively considering the utilization and coordinated development of various elements. Based on tourism eco-efficiency, the coordination degree of regional human-land system and the sustainable development levels can be accurately measured. With the tourism eco-efficiency in the Yellow River Basin from 2009 to 2019, the present study considers 63 cities in the Yellow River Basin as the research area by adopting the super-efficiency slacks-based measure (Super-SBM) model. Methods such as trend surface analysis, spatial autocorrelation analysis, elliptic standard deviation analysis, and hot spot analysis were used to explore their spatiotemporal distribution and evolution characteristics. The geographical and temporal weighted regression (GTWR) model was used to determine the factors influencing the tourism eco-efficiency value. The findings are as follows: ①The level of tourism eco-efficiency in the Yellow River Basin is not high, exhibiting a fluctuating upward trend. ②The tourism eco-efficiency in the Yellow River Basin shows significant spatial interdependence and agglomeration. Furthermore, the track of the center of gravity moves from northeast to southwest. ③ The tourism eco-efficiency in the Yellow River Basin is affected by various factors, with the economic development level having the greatest influence.

A Comparative Study of the Driving Factors of Water Resources Use Efficiency in China’s Agricultural and Industrial Sectors

The efficient use of water resources has become an important topic in China. Research on measurement and driving factors is the foundation for improving water resources use efficiency (WRUE). In this paper, the super-efficiency slacks-based measure (SE-SBM) model is used to measure the WRUE of China from 2005 to 2021. The agricultural carbon emissions and chemical oxygen demand (COD) in industrial wastes are taken as undesirable by-products. The driving factors of WRUE are discussed with use of the Tobit regression model. The results show that China’s agricultural WRUE ranges from 1.185 in Jilin to 0.687 in Ningxia. In the industrial sector, the WRUE ranges from 1.399 in Beijing to Jiangxi 0.212. The economic structure and development level, water resources endowment, government influence and environmental regulation, agricultural planting scale and urbanization rate have impacts on WRUE. Precautionary measures need to be applied to prevent inefficient WRUE caused by the declining share of the industrial sector in the economic structure. More financial support should be focused on water-saving irrigation in agriculture and energy and resource efficiency in industry. The organizational structure and technological advantages of urbanization should also be emphasized in efforts to improve water efficiency.

Analysis of spatial spillover effects and influencing factors of transportation carbon emission efficiency from a provincial perspective in China.

Globally, the transportation industry has become one of the leading sectors in carbon emission, and all countries are committed to environmental protection and energy conservation while experiencing rapid development. Under China's "dual-carbon" goal, the carbon emission problem hinders the construction of China's green transportation system and affects the high-quality development of transportation, so it is of great significance to study the spatial pattern of carbon emission efficiency in the transportation industry and the factors affecting it. Firstly, this paper measures the carbon emission value of transportation in 30 provinces in China from 2010 to 2020 based on the IPCC method and measures the carbon emission efficiency through the super-efficiency slack-based measurement model. Secondly, spatial autocorrelation analysis was conducted to determine the spatial clustering characteristics of the efficiency values. Finally, two spatial Durbin models are constructed to measure the spatial spillover effects and analyze the short-term immediate effects of each influencing factor on the static model and the long-term effects of the dynamic model considering the time lag of the transportation carbon emission efficiency. The results of the study show that (1) the average value of efficiency in the central and eastern regions is basically higher than 0.5; in the western and northeastern regions, it is basically lower than 0.3.The overall efficiency of carbon emission in the region shows a fluctuating upward trend but with increasing regional differences. (2) The number of regions with positive spatial correlation increased from 21 to 25 during the study period, and the degree of provincial transportation carbon emission efficiency agglomeration increased. (3) Although urbanization and energy intensity have a large detrimental influence on transportation carbon emission efficiency, environmental regulation has a major favorable effects on it both long and short term. Population scale, opening level, and urbanization all have significant spatial spillover effects. Accordingly, relevant policy recommendations are put forward to provide theoretical guidance for promoting the realization of low-carbon transportation.

Does agricultural mechanization improve agricultural environmental efficiency?

Improving agricultural environmental efficiency (AEE) is critical for sustainable and green agricultural advancement. However, there is limited research on the impact of agricultural mechanization on agricultural environmental efficiency. This study innovatively used micro-level survey data from the national fixed observation points of China’s Ministry of Agriculture and Rural Affairs to employ a super-efficiency slacks-based measure (SBM) model with undesirable outputs for quantifying AEE. Additionally, a Tobit regression model was used to examine the influence of agricultural mechanization on AEE. Our findings revealed a “U-shaped” relationship between agricultural mechanization and AEE. Specifically, when the extent of mechanization fell below a particular threshold, any further increase adversely affected the AEE. Conversely, surpassing this threshold enhanced the AEE. This “U-shaped” effect was mediated by agricultural carbon emissions. Furthermore, our analysis indicated that relative to other village categories, the benefits of mechanization in elevating AEE are more pronounced in plain, agriculturally focused, and affluent villages. To promote the improvement of agricultural environmental efficiency, it is advisable to advance agricultural mechanization, reduce agricultural carbon emissions, and develop agricultural mechanization tailored to local conditions.

The Effects and Driving Factors of Low-Carbon Transition of International Oil Companies: Evidence from a Super-SBM Model

As the main source of energy supply and carbon emissions, the oil and gas industry has entered the comprehensive low-carbon transition stage driven by various factors. Since different oil companies possess distinct understandings of transition paths, the effect of low carbon transition varies greatly. Obviously, it is necessary to evaluate the performance of low-carbon transitions within the oil and gas industry. Therefore, in this paper, 10 major international oil companies are taken as examples, and a super-efficiency slack-based measurement (super-SBM) model is applied in the present study to analyze the efficiency of low-carbon transitions. Furthermore, the logarithmic mean Divisia index (LMDI) is used to decompose the driving factors of carbon emissions and analyze their impact on the low-carbon transition of international oil companies. The obtained results reveal that although major oil companies have taken different measures in low-carbon transition and achieved a year-on-year reduction in carbon emissions, from the perspective of the efficiency of the entire production and operation process, these oil companies are inefficient in carbon emissions and need to adopt more effective low-carbon transition strategies; Moreover, after the further decomposition of the carbon emission driving factors of the 10 companies, it is found that improving the energy consumption intensity and development level of oil companies can effectively improve the effect of low-carbon transition of international oil companies. Drawing on the above findings, this paper puts forward suggestions for the low-carbon transition of energy companies, thus providing theoretical support and guidance for energy companies in different countries to implement low-carbon transition and green development strategies.