Super-efficiency Slack-based Measure Research Articles

Does green finance promote the improvement of regional eco-efficiency? Direct and spillover effects

IntroductionGreen finance plays a pivotal role in advancing China’s ecological civilization construction and achieving sustainable economic and social development.MethodsUsing panel data from 30 provinces in China from 2009 to 2021, this study applies the entropy weighting method and the super-efficiency slack-based measure (Super-SBM) model to assess the levels of green finance and eco-efficiency in each province. Employing spatial statistical methods such as the spatial standard deviation ellipse (SSDE) and the spatial Markov chain, the study reveals the spatiotemporal evolution characteristics of green finance and eco-efficiency. Additionally, the spatial Durbin model is used to analyze the direct effects, spatial spillover effects, and spatial heterogeneity features of green finance on regional eco-efficiency.ResultsThe results show that (1) From 2009 to 2021, green finance and regional eco-efficiency levels exhibited an overall upward trend, though with notable spatiotemporal differences. (2) The direct and spatial spillover effects of green finance on regional eco-efficiency followed a notable inverted U–shaped relationship. However, in most provinces, green finance levels had not yet reached the turning point during the study period, and the impact of green finance on regional eco-efficiency remained largely positive. (3) The effects of green finance on regional eco-efficiency showed considerable structural differences due to regional heterogeneity, with the strongest effects observed in the Eastern regions.DiscussionThis study provides policymakers with strategies to enhance regional eco-efficiency through the development of green finance, offering valuable insights for promoting ecological civilization construction and achieving sustainable development.

Assessment of land use efficiency under carbon emission constraint: An empirical study of Pearl River Delta, China

Land use efficiency (LUE) is the comprehensive reflection of the input and output in the process of land resource utilization. However, carbon emission during this process will lead to a decrease in LUE. It is necessary to evaluate LUE under carbon emission constraint for urban sustainable development. Although the carbon emission and efficiency of land use have been extensively studied, few researches considered the uncertainties in carbon emissions when evaluating LUE. In this study, a comprehensive assessment model of LUE was proposed. Interval parameter is introduced to a super efficiency slack-based measurement (SBM) model, leading to an assessment method of interval LUE, which can analyze the impact of carbon emission on LUE. A case study in Pearl River Delta (PRD) was conducted from 2005 ~2020. Results revealed that the overall carbon emissions of land use in the PRD increased significantly during the study period. Particularly, Zhuhai and Huizhou had a relatively larger increase. In terms of the total amount of carbon emission, it was relatively higher in Guangzhou and Shenzhen than the other cities in the region. Taking the carbon emission into account, the LUE of PRD still improved, especially in Shenzhen, Guangzhou, Foshan, and Jiangmen. However, an opposite trend was found for the LUE of Huizhou and Zhaoqing, changing from effective to ineffective. The LUE of Zhuhai and Zhongshan was always effective, while that of Dongguan was ineffective during the study period. In conclusion, the assessment method of LUE considering carbon emissions should be used to promote the efficient use of land resource. The results of the case study in this research can also provide decision-making reference for PRD and other urban agglomerations to improve LUE.

The Interaction and Sustainable Efficiency Between Tourism Systems and the Energy–Economy–Environment System: A Novel Parallel Network Super-Efficiency Slacks-Based Measure Model

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.

Assessing the provincial renewable energy generation efficiency in China considering the energy justice and sustainable development

The rapid increase in renewable energy (RE) installed capacity and the resulting issues of energy justice and RE generation efficiency (REGE) require urgent attention. Therefore, this study calculated the China’s RE justice indexes (REJIs) and the provincial RE justice contribution degree from 2012 to 2021 via the Gini coefficient and modified coupling cooperation degree model. Hydropower, wind, and solar power generation efficiencies (HPGE, WPGE, and SPGE) were evaluated using the super-efficiency slack-based measure model. The results show that the REJIs of wind and solar power demonstrated an increasing trend, whereas that of hydropower slowly declined in the following order: wind power > solar power > hydropower. The HPGE fluctuated without remarkable change. The WPGE and SPGE gradually increased, but the SPGE increased rapidly. Furthermore, the Global Malmquist-Luenberger productivity index results revealed that the HPGE and SPGE were driven by efficiency change (catch-up effect), whereas the WPGE was driven by technical change (innovation effect). The REGE exhibited considerable regional heterogeneity. It was the highest in Western China, followed by that in Central China, and the lowest in Eastern China. Our findings can guide policymakers in improving policies to enhance REGE and promote just and equitable energy transition development.

Synergistic Impacts of Carbon Emission Trading Policy and Innovative City Pilot Policy on Urban Land Green Use Efficiency in China

Reducing the conflict between economic expansion and environmental conservation requires green-based innovation policies. The synergistic impacts of these policies on promoting urban land green use efficiency (ULGUE) remain underexplored. Utilizing panel data from 285 prefecture-level cities in China (2006-2020), we apply the super-efficiency slacks-based measure (SBM) to calculate ULGUE. Employing the staggered difference-in-difference (SDID) model and mediation model, we investigate the synergistic effects of the Carbon Emissions Trading Policy (CETP) and the Innovative City Pilot Policy (ICPP), along with their influencing mechanisms on ULGUE. The results demonstrate that the average ULGUE keeps increasing from 2006 to 2020 and the simultaneous implementation of CETP and ICPP enhances ULGUE, with a more pronounced effect when CETP precedes ICPP. The concurrent implementation of dual policies boosts ULGUE by leveraging technological innovation and industrial structure as mediators. The magnitude of the mediating effect is as follows: green innovation > general innovation > rationalization of industrial structure > advancement of industrial structure. We also observe heterogeneous synergistic impacts of CETP and ICPP on ULGUE, with greater effectiveness in non-resource-based and large-scale cities. These results offer valuable insights for crafting effective policy combinations to advance sustainable development trajectories for China and other developing countries.

Mutual Causality Between Urban Transport Superiority Degree and Urban Land Use Efficiency: Insights from County Cities in Gansu Province Under the Belt and Road Initiative

Exploring the coupled coordination and interaction between urban transport superiority degree (UTSD) and urban land use efficiency (ULUE) is the key to promoting efficient land use in cities and coordinated development. This paper adopts the improved UTSD model, super-efficiency slack-based measure–undesirable output model, coupling coordination degree model (CCDM), panel Granger causality test, random forest model, and the mixed geographically and temporally weighted regression model to reveal the spatial and temporal evolution and coupling characteristics of UTSD and ULUE in Gansu from 2005 to 2020 and to validate and explore the interaction mechanism between UTSD and ULUE. The results show that (1), from 2005 to 2020, the average UTSD in Gansu increased from 0.56 to 1.01 and the Belt and Road Initiative accelerated the construction of the transportation network in Gansu. The average ULUE increased from 0.52 to 0.62; the spatial distribution of ULUE was high in the west and north and low in the east and south. (2) From 2005 to 2020, the average CCDM of UTSD and ULUE in Gansu increased from slightly unbalanced (0.37) to slightly balanced (0.52). A spatially high UTSD and high ULUE agglomeration area can be found along the transportation arteries. (3) The UTSD and ULUE were mutually causal, with the degree of transportation arterial influence degree being the strongest driver of ULUE among the components of UTSD (30.41% contribution) and tax revenue being the strongest driver of UTSD among the components of ULUE (15.10% contribution). Overall, the connotation of ULUE puts forward the demand for improving the transportation infrastructure and, at the same time, provides the guarantee for UTSD upgrading, which in turn affects the ULUE. In the future, the Xinan region of Gansu should prioritize planning and construction of a transportation network. The results of this study can provide a scientific basis for the construction of transportation networks and the efficient use of urban land in Gansu and other regions.

Quantitative evidence of the community of shared future for mankind as a driver of sustainable development in human society

In an era marked by global economic challenges, an increasing array of non-traditional security threats, and a proliferation of conflicts and issues, China has put forth the building of a community of shared future for mankind as a way to address this question of the times. The theory of the community of shared future for mankind offers a framework to address contemporary issues by promoting equality, mutual benefit, security, justice, openness, innovation, multicultural exchange, and green development. This paper innovatively quantifies the five core principles of the theory of the community of shared future for mankind using the entropy method. It calculates the proxy variable for sustainable development, green total factor productivity, using the super-efficiency Slack-Based Measure model in Data Envelopment Analysis. Baseline regression is conducted on this basis. The Principal Component Analysis method and another Data Envelopment Analysis method, the Malmquist index, are utilized to recalculate the indicators, followed by another round of regression analysis. The results are consistent with the baseline regression. Additionally, Ordinary Least Squares, Partial Least Squares, Maximum Likelihood Estimation, Ridge regression, and Lasso regression are employed to ensure the robustness of the results. The findings indicate a significant positive relationship between the community of a shared future for mankind and the sustainable development of human society, with consistent conclusions drawn from different calculation methods and regression techniques. Through value recognition, international cooperation based on benefit-sharing and mutual reciprocity can guide humanity towards a harmonious coexistence with nature, irrespective of regional and economic disparities. This study provides quantitative evidence of the impact of the community of a shared future for mankind on the sustainable development of human society, filling a gap in existing research. Based on these findings, feasible policy recommendations are proposed to promote sustainable development in human society.

Using super-efficiency slack-based measure data envelopment analysis with enhanced neural network frontier to evaluate the operating efficiency of Chinese-listed real estate companies

China's real estate industry has faced significant changes and challenges in the aftermath of the COVID-19 pandemic and recent years, and has been unable to maintain its former prosperity. Facing a rapidly changing market environment and new loan restriction policies, real estate companies are encountering unprecedented challenges. Efficiency evaluation and analysis of real estate companies are essential to guide them in improving operational efficiency and adapting to new development models. This paper examines 87 real estate development companies listed on the Shenzhen and Shanghai markets, first evaluating and analyzing their operational efficiency in 2023 using the output-oriented super-efficiency slack-based measure data envelopment analysis (SBM-DEA) method. To address the issue of overestimated operational efficiency in the original model, this paper integrates it with the backpropagation neural network (BPNN) algorithm to obtain more robust re-evaluated efficiency scores. The results align with expectations, showing an overall decline in efficiency scores, and more significant decreases for companies with smaller output shortfalls in the original evaluation. The re-evaluated efficiency scores do not excessively underestimate efficiency and can serve as a reliable proxy for the original scores. The enhanced model combining BPNN with super-efficiency SBM DEA provides reliable and robust efficiency evaluations for these 87 listed real estate companies.

Research on the dynamic characteristics and improvement path of urban sustainable development level: Based on gravitational model and scenario simulation method

The rapid expansion of cities has brought new challenges to sustainable development (SD). Therefore, how to balance between SD and the economic growth has become the key to regional development. With the aim of enhancing the research system of SD level, founded on the deep research of SD level from a new perspective of “input-output” and the dynamic evolution law of SD level, this paper has explored the path for cities to improve their level of SD to achieve regional coordinated development. By virtue of the Super-efficiency Slack-Based Measure model based on unexpected output (unexpected super efficiency SBM model), it has measured the SD level of 21 cities in Sichuan from 2010 to 2019. Using methods such as equilibrium coefficient, obstacle analysis and gravitational model, this paper has studied the spatiotemporal evolution law of SD level and constructed six scenarios to simulate the future trend of SD level. The results have indicated that the level of SD in Sichuan is showing a gradual decline with significant constraints. The focus of SD in Sichuan is gradually shifting from Chengdu to a city cluster centered around Chengdu, Ziyang, and Meishan. In an ideal development scenario, the level of SD has significantly improved. This study has revealed the current status and potential of SD in Sichuan. In the future, with more concentration on the role of core urban agglomerations, Sichuan should adjust policies to address input–output barriers to promote SD throughout the province.

How free trade pilot zones enhance agricultural green total factor productivity? Theory and evidence from China

IntroductionGiven the dual constraints of limited resources and environmental concerns, achieving green development in agriculture helps to enhance national food security, resource security, and ecological security.MethodsUtilizing panel data sourced from 30 provinces within China, spanning the years from 2001 to 2021, this paper employs the super-efficiency Slack-Based Measure (SBM) model and the Global Malmquist-Luenberger (GML) index to measure agricultural green total factor productivity (AGTFP). It utilizes methods such as the stepwise Differences in Differences (DID), mediation effect models, and moderating effect models to systematically explore the impact of the implementation of Free Trade Pilot Zones (FTPZs) on AGTFP and its mechanisms of action.ResultsThe study finds: (1) Establishing FTPZs significantly boosts AGTFP, indicating a profound positive influence; (2) The promotional effect of FTPZs on AGTFP is stronger in the eastern and central regions, as well as in major grain-producing areas; (3) FTPZs may enhance AGTFP by promoting the effect of agricultural structure upgrading, i.e., a transmission mechanism exists from FTPZs to the agricultural structure upgrading effect to AGTFP; (4) The agricultural scale effect plays a positive moderating role in the impact of FTPZs on AGTFP.DiscussionIt is advisable to optimize agricultural measures related to FTPZs, promote agricultural structural upgrading and scale enhancement, adapt strategies to local conditions to advance green agricultural development, and thereby promote the coordinated development of FTPZs and AGTFP.

Digital transformation and corporate green total factor productivity: Based on double/debiased machine learning robustness estimation

With the rapid development of the digital economy, China's digital technology and industry continue to integrate deeply into all areas of society. Digital transformation(DT) has become an important engine and key pedestal for economic and social transformations and upgrades. This paper takes 3525 listed companies from 2013 to 2021 as a sample to measure the green total factor productivity(GTFP) of listed enterprises based on the super-efficiency slacks-based measure with the Global Malmquist-Luenberger Index (SBM-GML) and the super-efficiency epsilon-based measure with the Global Malmquist-Luenberger Index (EBM-GML). It draws on the two existing DT indicators to explore the impact and mechanism of enterprise DT on GTFP. The results show that DT can significantly enhance GTFP, and this conclusion still holds after double/debiased machine learning and other robustness tests; the heterogeneity analysis shows that DT of high-tech enterprises, manufacturing industries and low-financialisation enterprises has a more obvious effect on the enhancement of GTFP; and the four-stage mediated impact mechanism suggests that the effect of DT on GTFP can be achieved by improving internal control ability and technological innovation ability. This paper will provide relevant policy insights on how to better drive enterprise DT and green low-carbon development under the “dual-carbon” goal.

Land ecological security evaluation and prediction based on SBM-BP model: a case study of Yangtze River Economic Belt, China

Land ecological security is the foundation for ecological environmental protection and regional sustainable development. Therefore, examining the land ecological security and spatial heterogeneity in the Yangtze River Economic Belt (YREB) in China can guide effective land ecological protection in this region. Using a driving force-pressure-state-impact-response (DPSIR) index system, a global super-efficiency slacks-based measure (SBM) model, and a backpropagation (BP) neural network model, this study evaluated the land ecological security in 126 YREB prefecture-level cities and then employed spatial correlation analysis to identify the spatial distribution characteristics. It was found that: (1) from 2012 to 2021, the land ecological security in the study area decreased and then increased, with the eastern and western regions being better than the central regions; (2) from 2015 to 2017, the high land ecological security was clustered in the Yangtze River Delta urban agglomeration and the low value was clustered in Yunnan Province, Hubei Province, and the Chongqing Municipality; (3) from 2022 to 2026, the land ecological security in the study area is expected to gradually increase, but in the southwest is expected to remain low. These research results provide a theoretical basis for the evaluation and prediction of land ecological security and practical guidance for land ecological protection in areas with similar natural conditions.

Spatial spillover effects and correlation network analysis of green construction development efficiency in China

Green construction has been implemented globally to address resource depletion and environmental degradation. The effectiveness of green construction development depends on the efficiency of resource utilization and the common progress of all regions. However, existing studies have paid limited attention to green construction development efficiency (GCDE) and its spatial correlation. This study uses the super-efficiency slacks-based measure (Super-SBM) model, spatial econometric models, and social network analysis (SNA) method to reveal the spatial distribution, spatial spillover effects, and spatial correlation of GCDE across 30 provinces in China. The results indicate significant disparities in GCDE among regions, with the eastern region exhibiting considerably higher GCDE than the western and northeastern regions. There is evidence of spatial spillover effects, and the spatial correlation of GCDE is strengthening. Provinces with high GCDE occupy central positions in the GCDE network and exert spillover effects on other provinces, while underdeveloped provinces have opportunities to benefit from regional cooperation. The findings provide policy insights for the implementation and enhancement of green construction development actions. Moreover, they provide Chinese experience for green construction practices in other areas of the world.

Effects of Industrial Structure on the Green Utilization Efficiency of Urban Land: A Case Study of the Bohai Rim Region, China

The green utilization of urban land is a critical component of regional high-quality development. Enhancing the green utilization efficiency of urban land (GUEUL) is of great significance to improving the quality of ecological environment and achieving a green lifestyle and low-carbon production. With the process of urbanization, the industrial structure is constantly adjusted, which has an impact on the structure and efficiency of urban land utilization. Taking 43 cities in the Bohai Rim region as an example, the super-efficiency slack-based measure model with undesirable outputs (super-SBM-undesirable model) was employed to evaluate the GUEUL from 2006 to 2021, and the panel quantile model was used to explore the impact of industrial structure on GUEUL. The results showed that the GUEUL in the Bohai Rim region appeared a fluctuating upward trend from 0.664 in 2006 to 0.837 in 2021. High-value zones shifted from western Liaoning province and southern Shandong province to a “C”-shaped belt around the coastline and expanded continuously, while low-value zones decreased significantly. Furthermore, the influence of industrial structure on GUEUL was significantly positive, but there were significant differences among different efficiency levels. Industrial structure upgrading exerted the most significant effect on GUEUL improvement in low-value zones, while industrial structure rationalization was dominant in high-value zones, and the influence of industrial structure technologization was more significant in medium-low-value zones. Therefore, differentiated industrial structure adjustment policies should be formulated based on the actual condition of each city to improve GUEUL.

Can the Development of Renewable Energy Improve Total-Factor Carbon Emissions Efficiency? Evidence from 30 Provinces in China

Abstract The global temperature is exceeding 1.5°C above pre-industrial levels due to the increasing carbon emissions, and developing renewable energy is expected to be one of the most effective solutions. However, whether the development of renewable energy contributes to curbing the carbon emissions while maintaining economic development is still under investigation. Using the total-factor carbon emission efficiency (TFCEE), this paper first measures the carbon emission abatement and economic development of 30 provinces in China from 2005 to 2019. Then, based on the super-efficiency slacks-based measure (SE-SBM) model, the panel threshold models and spatial Durbin models are established to comprehensively investigate the impact of RED on TFCEE. The findings reveal that: (1) RED significantly improves TFCEE. For every 1% increase in RED, TFCEE experiences a rise ranging from 0.020% to 0.035%. (2) The beneficial effect of RED on TFCEE increases with economic restructuring and technological progress. (3) The indirect impact of RED on TFCEE through spatial spillover is significantly greater than its direct effect. Potential transmission mechanisms for this spatial spillover effect are the cross-regional mobilization of renewable electricity and the diffusion and absorption of low-carbon knowledge and technologies. The above conclusions provide empirical evidence for China and other developing countries to formulate appropriate energy transformation strategies. Keywords: Renewable energy development; Total-factor carbon emissions efficiency; Transmission mechanism; Spatial spillover effect; Nonlinear effect.

Evaluation of urban low-carbon development efficiency: evidence from 30 cities in China

With the acceleration of global urbanization, the issues faced by urban development are becoming increasingly apparent. Some countries and regions have placed less emphasis on low-carbon emissions in the development process and prioritized urban development. However, blindly pursuing rapid urbanization has led to excessive urban carbon emissions, which outweigh the gains. Therefore, based on panel data from 30 cities in China from 2010 to 2019, this study combines the super-efficiency slacks-based measure (SBM) model and the Malmquist index, taking urban carbon emissions as undesirable outputs, to evaluate urban development efficiency. Through a multidimensional comparative analysis, this study reveals the developmental challenges encountered by various cities. The results show that: statically, the overall urbanization progress of these 30 cities is commendable, but significant fluctuations are observed in the development trend. The mean super-efficiency of cities in the eastern coastal areas is relatively high, whereas other regions exhibit instances of ineffective mean super-efficiency. Dynamically, there are few periods of efficiency improvement during 2010–2019, and there is an imbalance in the sources of efficiency improvement. Shanghai and Hangzhou exhibit the best continuous dynamic improvement status, with small fluctuations in dynamic efficiency, whereas Guiyang has the worst dynamic efficiency improvement status, indicating poor urban development. This study underscores the urgent need for a balanced approach to urban development that incorporates low-carbon initiatives to ensure sustainable progress and mitigate adverse environmental impacts.

Spatial differentiation and driving factors of scientific and technological innovation efficiency under the background of the digital economy

Scientific and technological innovation (STI) activities are facilitated under the influence of the digital economy and depend on digital elements to support innovation activities. This study measures digital element inputs and outputs using data related to the digital economy and estimates STI efficiency in 29 provincial regions in mainland China from 2010 to 2021 employing the global super-efficiency slacks-based measure (SBM) model. Then, spatial characteristics and driving forces of STI efficiency are quantified using spatial autocorrelation and geographic detectors. The results reveal that STI efficiency exhibits a fluctuating, W-shaped pattern, and the spatial correlation effect shows a gradually declining trend from 2010 to 2021. The findings reveal that the core drivers of STI efficiency are digital financial development, e-commerce development, digital access level, and related factors. Therefore, strengthening inter-regional innovation links, promoting the construction of 5 G mobile internet and accelerating the integration of digital industries into traditional industries are recommended.

Measurement of Tourism Ecological Efficiency and Analysis of Influencing Factors under the Background of Climate Change: A Case Study of Three Provinces in China’s Cryosphere

Against the backdrop of climate change and the “dual carbon” goals, enhancing the ecological efficiency of cryospheric tourism is crucial not only for the high-quality development of the tourism industry itself but also for the protection of the ecological environment and the promotion of green sustainable development in the cryospheric region. In light of this, this study, taking climate change as its background and based on the perspective of carbon emission constraints, integrates multidimensional factors such as “climate change, carbon emission constraints, and cryospheric resources” into a unified measurement framework to construct a model for evaluating the ecological efficiency of tourism in the cryosphere. Specifically, the model considers inputs, expected outputs, and unexpected outputs. Subsequently, employing the super-efficiency slack-based measure (SBM) model, this study measures the tourism ecological efficiency (TEE) of three provinces (Xinjiang, Qinghai, Tibet) in the cryosphere from 2013 to 2021 and utilizes the Malmquist–Luenberger index and gray correlation model to reveal their dynamic changes, efficiency decomposition, and influencing factors. The results indicate that: (1) The overall mean of TEE in the cryosphere is between 0.2428 and 1.2142, Over the study period, the average annual growth rate and corresponding confidence interval were 14.74%, (−8.61%, 64.23%), showing a significant fluctuating growth trend. Among them, Xinjiang stands out, with its mean scores ranging from 0.2418 to 1.6229, surpassing the overall average level of the cryosphere. (2) During the study period, the overall dynamic efficiency of tourism ecology in the cryosphere increased by 21.54%, driven by the synergy of technological progress (TC), pure technical efficiency (PET), and scale efficiency (SE). For each province, the dynamic efficiency of tourism ecology has improved, but to varying degrees. (3) Regarding the driving factors of TEE in the cryosphere, each driving factor is closely related to TEE, ranked from large to small as follows: carbon emission structure, level of economic development, infrastructure, intensity of technological input, industrial structure, resource endowment, and environmental regulation. This article holds theoretical and practical significance for promoting the high-quality development of polar tourism and achieving synergistic progress between the economy and environment.

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.

A Study on the Evaluation and Determinants of Green Economic Efficiency: Empirical Evidence from Provincial Panel Data in China

In the past decades, China has continued to pursue the quantitative expansion of economic development at the expense of the environmental quality resulting in high environmental degradation. Hence, this study evaluates the economic efficiency under the constraints of energy and environment, as well as unravels the determinants of economic efficiency in 30 provinces in China during 2005 to 2019. It deploys the improved super-efficiency Slack-Based Measure (SBM) model and Tobit regression model. The statistical results show that economic growth efficiency displays a declining trend in recent years in China. However, there is a regional heterogeneity of green economic efficiency across the provinces, with the efficiency values exhibiting a clear downward stepwise distribution from the eastern to western region. Moreover, the regression results indicate that energy consumption and GDP growth have significant adverse effects on green economic efficiency. This implies that China’s economic growth is excessively reliant on energy consumption which exceeds the environmental carrying capacity, causing a decline in green economic efficiency. The study of China’s economic efficiency is fundamental because it explores the potential space for sustainable growth as well as provides clarity on the current status and prospects of economic development with a view to avoiding economic stagnation and providing policy support for sustainable economic development. Therefore, policy makers should proactively take measures to improve energy efficiency and shift economic development targets from quantitative expansion to qualitative improvement that facilitates green economic efficiency. Based on the empirical results of the different regions, this study also provides some respective policy recommendations.