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• Examine the regional and temporal evolution of LCEE and its influencing factors. • Investigate LCEE on a global scale and analyze LCEE for each country. • Add carbon dioxide emissions as an undesired exportation to the LCEE evaluation indicator system. • Propose countermeasures to improve global LCEE. Nations worldwide must collaborate to tackle the challenge of improving carbon emission efficiency and optimizing land use effectively. This study extends the study area from provinces and cities, regional city clusters, and countries to 136 major countries in the world, and shows the differences between countries. The paper analyzed the spatiotemporal evolution characteristics and influencing factors of land use carbon emission efficiency (LCEE) in these 136 countries from 2000 to 2019 using the super-efficiency slacks-based measure data envelopment analysis (Super-SBM DEA) model, global malmquist index, spatial autocorrelation measurement tools and Spatial Durbin model. It can help to promote low-carbon and green development while simultaneously improving the global LCEE. The findings indicate that: (1) Over the study period, there is a trend toward a decline in the LCEE worldwide. (2) The primary cause of the worldwide LCEE's declining trend during the study period is the reduction in technical efficiency. (3) The low-low cluster type accounts for more, while the high-high agglomeration type accounts for less and exhibits a sluggish growth pattern. On the whole, there is a phenomenon of non-aggregation and non-uniformity. It is necessary to increase the driving effect of high-high cluster radiation. (4) Economic development level, investment level, population size, public service level and environmental sustainability level all have a significant impact on LCEE, while industrial development level has no significant impact on LCEE. From a global perspective, the radiation driving role of countries with high LCEE should be increased. Improve the efficiency and technological level of land use emission in light of local conditions, and promote independent innovation in green and low-carbon technologies. This is conducive to the establishment of long-term low-carbon growth. [ABSTRACT FROM AUTHOR]

[Display omitted] • We adopts a perspective of equity and efficiency and constructing a framework to assess the improvement of ESV in China. • We reveals the regional unfairness between China's ESV and economic growth. • We evaluates the ESV improvement in China, considering both static and dynamic efficiency. • We provides policy suggestions for ecological environmental governance. Ecosystems provide the material and energy resources necessary for human development, improving people's quality of life and well-being. Thus, enhancing the effectiveness of ecosystem services valuation has become a focal point of concern. Here, we adopt a perspective of equality and efficiency and construct a framework based on the ecological Gini coefficient (E-Gini coefficient) and the three-stage Data Envelopment Analysis-Malmquist (DEA-Malmquist) model, by evaluating the input of financial investments and human resources and the output of ecosystem service value (ESV) production, to assess the improvement of ESV in China from 2008 to 2020. The research findings reveal that the E-Gini during the study period remained consistently above 0.54, which is categorized as "high inequality". ESV equality across different regions follows the order of northwest > south > north concerning economic and social development. Furthermore, through efficiency analysis, we find that there is room to improve the improvement efficiency of China's ESV. Static efficiency analysis indicates that the average improvement efficiency of China's ESV is low (0.331). This indicates that the input resources did not achieve the optimal ESV production. Dynamic efficiency analysis reveals that there is a 3.2 % decline in ESV improvement efficiency over the entire study period. Encouragingly, ESV improvement efficiency has been increasing annually since 2017. Moreover, there exists spatial heterogeneity in ESV improvement efficiency, with the northwest region showing significantly higher than the north and south. The research results can provide policy recommendations for ecological environmental governance, production efficiency, and ecological compensation. [ABSTRACT FROM AUTHOR]

[Display omitted] • A base point network DEA model is proposed to evaluate ISW prevention and treatment efficiencies. • The CCD model is constructed to investigate the CCD of ISW prevention and treatment efficiencies. • ISW prevention efficiency is higher than treatment efficiency. • The CCD in three regions (Jiangxi, Guangxi, Shaanxi) is imbalanced. • The improvement of CCD mainly depends on industrial servitization and industrial structure. Both prevention and treatment are crucial for reducing industrial solid waste (ISW). The primary objective of this study is to explore the coupling coordination degree (CCD) of China's provincial ISW prevention and treatment from the perspective of efficiency analysis during 2011–2020 and then investigate its driving factors in three steps. The first step is to develop a base point network slacks-based measure data envelopment analysis model to address the issue where the indicators (ISW discharged, ISW stored) of some regions are zero during the evaluation of the ISW prevention and treatment efficiencies. Secondly, the CCD model is constructed to investigate the CCD of ISW prevention and treatment efficiencies. Finally, the driving factors of the CCD are explored using the spatial Tobit model. The results show that: (1) In 76.67% of regions, the prevention efficiency is higher than treatment efficiency, and in 23.33% of regions, the treatment efficiency is higher than prevention efficiency. The prevention efficiency of the entire country exhibits a steady downward trend, while the treatment efficiency, on the whole, is increasing. (2) The regions with high coordination are mainly situated in the east, those with moderate coordination are primarily located in the central region, and those with basic coordination are mostly located in the west. Only three regions (Jiangxi, Guangxi, Shaanxi) exhibit moderate imbalance. (3) The improvement of CCD mainly depends on industrial servitization and industrial structure, while property structure, ISW treatment investment intensity, and traffic infrastructure construction significantly impede the increase of the CCD. [ABSTRACT FROM AUTHOR]

• Four social capital groups are defined based on the result of life cycle assessment. • The members of each social group are determined using data envelopment models. • Strong ties are provided in each group between inefficient and efficient farmers. • It is expected that social capital groups reduce energy use and environmental impacts. Agricultural production inevitably poses adverse impacts on local environment, while the collective action of farmers can also contribute positively to sustainable resources management. The structural component of economic actors' integration is often related to social capital. This study analyses the impacts of farmers' socio-economic conditions on energy use and life cycle environmental impacts of Iranian rice production. Based on the local socio-economic status and life cycle assessment, some types of social capital groups are suggested to achieve cooperative rice production with lower burden on the environment. Four social capital groups, namely "water, fertilizer and pesticide users", "consolidated farming", "new technology users" and "micro-finance", are suggested according to the life cycle assessment. The members of each social capital group were determined by data envelopment analysis to guarantee that each social capital group moves toward better rice production methods with lower burden on the environment. Technical efficiency of farmers was determined by data envelopment analysis models which in turn help us identify core and target members of each social capital group. The results show that the lowest energy input for rice production is 28,000 MJ/ha, which appeared in groups with medium aged farmers who have medium farming experiences. The sample farmers with higher net income, larger farms and participating in extensional classes contribute to mitigate total energy consumption of rice production. The life cycle assessment confirms that those socio-economic groups consuming lower energy also impose lower burden on the environment. [ABSTRACT FROM AUTHOR]

• DPSIR-DEA model. • Evaluate the "quality" of ES. • Dynamic assessment of ES. • Internal relationship between DPSIR. • Driving mechanism of ES. Ecological security (ES) is an important element in the construction of an ecological civilization and plays a vital role in ensuring the sustainable development of social economies. Further, ES is an important measure of regional sustainable development. Based on ecosystem theory, this study constructs a comprehensive evaluation framework using the driving force-pressure-state-impact-response (DPSIR) and slacks-based measure of data envelopment analysis (SBM-DEA) models. Taking the Three Gorges Reservoir Area as an example, the study develops an ES evaluation system and realizes a transformation from "efficiency" to "quality".Gray correlation theory and spatial autocorrelation and are adopted to analyze the ecosystem's spatial–temporal evolution and driving factors. The results demonstrate that the overall level of ES in the Three Gorges Reservoir Area from 2010 to 2020 was good; however, the spatial distribution of ES revealed an unbalanced state. The influence of each subsystem on the result of the ES evaluation is state > response > impact > driving force > pressure. The spatial correlation analysis of ES in the Three Gorges Reservoir area exhibited a positive autocorrelation, and the agglomeration effect was significant; on this basis, the key factors affecting ES were identified. The ratio of environmental protection investment, sewage treatment rate, green coverage rate of built-up areas, proportion of primary industry in GDP, and proportion of tertiary industry in GDP had notable effects on the ES of the study area. The research contributes to the theory of ES and provides guidance for ecologically sustainable development. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Provincial agricultural WUE was assessed based on data envelopment analysis in China. • We compared the results between the blue-only and the green-blue scenarios. • The lower potential can be improved under the green-blue scenario while higher potential for blue-only scenario. • The pure technical efficiency was higher under the green-blue scenario in Northern provinces. • Improving blue water use in NC and green water use in SC is a priority to enhance national WUE. Abstract Uneven water resources and growing food demand due to an increasing population bring challenges to China. One important mechanism to address these challenges is to enhance water use efficiency (WUE). This requires information on current efficiencies in water use for agricultural production. In this study, we provide a benchmarking tool to assess relative agricultural WUE in 31 provinces in China during 2003-2013. Data Envelopment Analysis (DEA) was used with both green-blue water and blue-only scenarios. Results show that China's agricultural WUE has improved evidently after 2008. Overall technical efficiency (TE) and the pure technical efficiency (PTE) in China based on the green-blue scenario are relatively high, with the average potential increase less than 10% (8% and 4%, respectively). However, there is a larger potential for blue water use efficiency (14% and 7% respectively). The PTE in Northern China (NC) is higher than that in Southern China (SC) while the TE in NC is lower under green-blue scenario. Moreover, the TE and PTE in NC are lower than that in SC under blue-only scenario. These results indicate that green water management techniques in NC are superior to SC but the scale efficiency (SE) in NC is lower. There are four provinces where the efficiency values are on the frontier in four cases, i.e. two scenarios (green-blue and blue-only) and two assumptions in DEA, but fourteen provinces where the efficiency values are not on the frontier in any case and most of them were located in SC. Our results also suggest that improving SE can substantially contribute to national WUE, but exploring the solutions to enhance blue water use efficiency in China is also a key task in the future works. The research results have important implications for China and different provinces to improve agricultural WUE by water policies and management. [ABSTRACT FROM AUTHOR]

The high-frequency on-line measurements coming from sensors installed in wastewater treatment plants (WWTPs) can be used for alert systems and decision support tools. Given the complexity of WWTPs, many authors developed efficient techniques for plant assessment. By contrast, few contributions are focussed on the identification of regime shifts in WWTPs on short-term, even if the early detection of occurring inefficiencies is a relevant information for plant managers. In order to fill this gap, the present paper uses a daily LCA + DEA analysis in order to monitor the potential deterioration of the eco-efficiency. This approach consists of an original combination of environmental life cycle assessment (LCA), data envelopment analysis (DEA), time series analysis and statistical tests. The main innovation in DEA algorithm consists of the set of decision-making units (DMUs), here composed of the 1-day operation datasets of a single WWTP. The results show a good performance in the regime shifts classification, for which the receiving operating characteristic (ROC) analysis returned a score of 0.8 (in a range 0–1). [ABSTRACT FROM AUTHOR]

Decreasing carbon emissions is of great significance to the development of the strategy for a low-carbon economy and for the choice of a carbon dioxide (CO 2 ) emission mitigation path. In order to realize the purpose of energy saving and emission reduction during the process of urbanization, both China and Jiangsu province have been urged to improve their energy efficiency and carbon dioxide efficiency. A Malmquist index based on an undesirable output data envelopment analysis (DEA) model was calculated to study the scalable industrial CO 2 emissions of 13 cities in Jiangsu province from 2000 to 2014. The impact factors on the efficiency of the CO 2 emissions are analyzed using a Tobit model, which takes the level of urbanization as the core variable and four other factors (energy consumption structure, industrialization level, foreign trade, and R&D expenditure) as the control variables. The results show that the total factor productivity (TFP) index of the low-carbon economy in Jiangsu grew by an average annual rate of 0.7%, and the total efficiency of the low-carbon economy increased by 9.3%. The main contributing factor was the average annual increase of 1.5% in technological progress during 2000–2014, but the pure technical efficiency and scale efficiency are declining. Jiangsu has not realized the full use of its resources and energy for many years. The level of industrialization and structure of energy consumption are the main impact factors on carbon emissions. In the process of urbanization, both China and Jiangsu should pay attention to optimizing the structure of energy consumption, adjusting the industrial structure, increasing the R&D, and introducing environmental protection technology. These are effective paths to achieve the goal of carbon emission reduction in China. [ABSTRACT FROM AUTHOR]

Eco-efficiency is of great significance in facilitating a region’s sustainable development. However, there are some inconsistencies among the concepts and also relationships of eco-efficiency and its relevant efficiencies in recent studies. This paper integrates eco-efficiency and three related-efficiencies (economic efficiency, energy efficiency, and environmental efficiencies) into a total-factor analysis framework, regarding them as composite eco-efficiency indicators. Employing a new data envelopment analysis approach, named Meta-US-SBM, which considers meta-frontier, undesirable outputs, super efficiency, and slacks simultaneously, the measure system of these four efficiencies is established. An empirical study is conducted using Chinese provincial data from 2001 to 2014. Results indicate that, overall, the regional economic efficiency is better than other related efficiency indicators. Furthermore, different provinces are adopting different development modes, as denoted by significant heterogeneity among eco-efficiency indicators. [ABSTRACT FROM AUTHOR]

Data Envelopment Analysis (DEA) is a production-theoretical benchmarking process that allows us to compare the relative efficiency of so-called “decision-making units” (DMUs). Although the method was originally applied to the comparison of production lines or companies, a previously published paper (Deilmann et al., 2016) has shown its suitability for the investigation of cities. In this approach, cities (specifically local administrations and municipal councils) are understood to be DMUs. The DMUs are Germany’s kreisfreie Städte , which are towns and cities with special status as independent administrations. The primary interest was to investigate efficiency in land use. In this previous study an economic and an ecological model were used to apply the DEA to cities. The efficiency values of both models are presented in a nine-field matrix. The current study goes beyond these principal findings by introducing two further interpretative approaches. First: In addition to the input and output indicators of the DEA, other illustrative indicators are adopted as a second stage of investigation in order to understand which specific structural, economic, ecological and social feature values can be attributed to highly efficient cities as opposed to less efficient cities. Under this interpretative approach, DEA helps shed light on the concept of efficiency. Findings show that medium-sized cities make the most efficient use of land (developed as settlement and traffic area), that settlement area is not the only factor determining high efficiency, that high density alone is no guarantee of efficiency, that some large cities show high land productivity yet low economic efficiency (in Germany there is a clear division between old industrialised cities and cities benefitting from the new economy). Second: By combining variable and constant returns to scale, it is possible to calculate scale efficiency scores for cities. Under this second interpretative approach, development pathways can be discerned for cities to increase efficiency. Some cities seem to have the potential to improve their economic and ecological efficiency without changing the amount of land developed for settlements and traffic ( e.g . by unsealing and restoring brownfields). Furthermore, cities operating in the range of increasing returns of scale should be able to increase their settlement area without jeopardizing efficiency. Although the focus of the presented model is on urban quality connected to the efficient usage of settlement and traffic area, it may also be applied to the investigation of other relations depending on the respective research interest. Such observations can support urban developers in estimating the effects of land-use change, brownfields restoration and redevelopment, as well as pinpointing factors to improve economic and ecological performance. [ABSTRACT FROM AUTHOR]

• An empirical study on the impact of environmental regulation on capacity utilization. • Utilization of sector-level panel data of China's manufacturing industry. • Analysis of the impact degree and mechanism from a sector-level perspective. • Heterogeneity tests based on the degree of overcapacity and environmental pollution. Under the pressures of environmental pollution and overcapacity, environmental regulation is adopted by the Chinese government to reduce excess capacity of China's manufacturing industry. Sector-level empirical research on the impact of environmental regulation on overcapacity is necessary since both of them are highly variable among different manufacturing sectors. Based on the panel data from 2001 to 2010, capacity utilization and its two factors, namely technical efficiency and equipment utilization, of 28 manufacturing sectors in China have been calculated using data envelopment analysis (DEA). The results of empirical tests indicate that environmental regulation has a significant impact on equipment utilization rather than on technical efficiency, leading to an overall negative effect on capacity utilization. In addition, the impact of environmental regulation on capacity utilization shows sector heterogeneity when the manufacturing sectors are classified according to the degree of overcapacity or pollution. To be specific, environmental regulation is not an effective means of reducing excess capacity of mild-pollution sectors and severe-overcapacity sectors. Capacity utilization of moderate- and severe-pollution sectors can be increased by combining environmental regulation and other policies to stimulate technical innovation. Excess capacity of mild- and moderate-overcapacity sectors can be reduced by environmental regulation; meanwhile, policy guidance on promoting technical innovation should also be provided to mild-overcapacity sectors. Therefore, it is crucial to formulate differentiated policies and maintain a reasonable range of intensity in the process of reducing overcapacity by means of environmental regulation. [ABSTRACT FROM AUTHOR]

Currently, water and sewer companies face the challenge of improving their quality of service to customers (QSC). Performance indicators are essential to monitor and benchmark the QSC of water companies; however, individual indicators do not provide a holistic evaluation of the quality of water and sewer services provided to customers. This study proposes an innovative QSC index based on distance-function techniques that makes it possible to compare changes in the QSC of water companies among locations and temporal periods. A case study assesses changes in QSC for a sample of Chilean water and sewer companies from 2007 to 2014. The results show that in spite of the efforts made by the water regulator, QSC has remained almost constant over a number of years, with 2010 having the best performance. The methodology proposed in this study is useful for water regulators to benchmark water companies when developing policies that prompt QSC improvements. [ABSTRACT FROM AUTHOR]

Based on energy and CO 2 emission efficiencies, this paper proposes a definition of the elasticity of the potential of emission reduction to energy saving ( E peres ), and measures the elasticity in China’s 30 provincial regions. Although E peres is a relative definition, it can be used (1) to measure the amount of reduced CO 2 emissions per unit fossil energy saving, (2) to reflect the effectiveness of fossil energy saving for CO 2 emission reduction in different regions, and (3) to provide decision-making criteria for selecting pathways for emission reductions in different regions. The results show that compared with energy saving, emission reduction is a more serious issue in China. This indicates that energy saving policies have been highly effective since their implementation during the 11th “Five-Year Plan”. With respect to provincial disparities, the emission reductions caused by fossil energy saving are not significant in Beijing, Shanghai, and Guangdong. Fujian province has significant E peres , indicating that emission reduction causing by fossil energy saving is effective. E peres has been increasing over time in Hunan and Hubei. Hainan’s E peres has remained less than 1, indicating that its emission-reduction effect of fossil energy saving is worse than in other provinces. Moreover, the elasticity of Eastern China is greater than that of Central China and Western China. This finding sheds light on pathway selection for energy saving and emission reduction in China: it would be more appropriate to encourage fossil energy saving in Eastern China, and to promote clean energy use (e.g., water electricity and solar energy) in Central China and Western China. [ABSTRACT FROM AUTHOR]

This article aims to estimate the efficiency of 26 different European Countries over 2001 and 2012 comparing their performance. Data Envelopment Analysis technique is used in a first step to evaluate the performance of each European country. The output-oriented model was used with two specifications (Variable and Constant Returns to Scale) including as inputs labour and capital productivity, the weight of fossil energy and the share of renewable energy in GDP (gross domestic product), being the output GDP per GHG (greenhouse gases) emissions. In a second step, the quantile regression technique was used, to explain different efficiency scores through variables as Environmental Taxes Revenues, Resources Productivity and Domestic Material Consumption. Results indicate that share of renewables and non-renewable energy sources are important to explain differences in emissions. They suggest a significant change in the trend of economic and environmental efficiency in European countries and put forward the high disparities existing among them. Policy recommendations point for the need of higher steps if the goal is to equal countries efficiency scores. Moreover, environmental tax revenue effects are negatively stronger in less efficient countries, whereas also exerting negative influence over those more eco-efficient. Transport taxes affect negatively more eco-efficient countries and positively less eco-efficient countries. Energy taxes only seem to positively influence the lower eco-efficient countries. There is also evidence for a negative premium of efficiency considering domestic materials consumption. Finally, resources productivity shows a positive and significant influence independently of the country technical eco-efficiency level. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore CO 2 emission efficiency in china’s agricultural sector during the period 2001–2012. We also analyze the CO 2 emission reduction potential as well as its two main contributors (i.e. technology gap inefficiency and managerial failure). The meta-frontier framework is adopted to reflect technology heterogeneities in China’s agricultural sector among the eastern, central and western regions. Based on the DEA (data envelopment analysis) method, the models are estimated by means of linear programming. Empirical results indicate that CO 2 emission efficiency of the agricultural sector in western China is the lowest compared with eastern and central China; stemming from the fact that most provinces in western China generally fall behind in terms of technology. The total potential agricultural CO 2 emissions reduction is estimated at 1161.33 million tons, which can be attributed to managerial failure in the case of eastern and central China. For western China, it can be attributed to both technological gap inefficiency and managerial failure. [ABSTRACT FROM AUTHOR]

This paper utilizes the slacks-based measure (SBM) undesirable model to analyze the environmental regulation efficiency (ERE) from 2003 to 2013, and uses the Data Envelopment Analysis (DEA) Malmquist productivity index to divide the environmental regulation total factor productivity (ERTFP) into a technical progress index, pure technical efficiency index and a scale efficiency index from the perspective of scale change. The results show that the ERE presents “polarized” effect and the ERTFP has an obvious “agglomeration” effect in China. There is also a very significant “match-up” effect between the ERE and economic development level. In addition, the paper also finds that the technical progress index has the largest contribution to ERTFP, followed by pure technical efficiency index and then the scale efficiency index. The preceding results can provide scientific suggestions for regional environmental departments. [ABSTRACT FROM AUTHOR]

Environmental management, being an important component in strategies for achieving sustainable development of processes and products, has emerged as a proactive approach in majority of the manufacturing organizations. From the strategic perspective environmentally conscious manufacturing (ECM) programs lead to better environmental management practice. The objective of the current paper is to present an integrated and holistic framework to evaluate ECM programs. This framework combines three multi-criteria decision analysis (MCDA) methods to consider eight major environmentally conscious manufacturing indicators (ECMI) in order to identify the efficiency of each ECM program. First the interdependence relationship among the ECMIs is established using decision-making trail and evaluation laboratory (DEMATEL). Then a range of weightage (i.e. upper and lower bounds) is created for each ECMI using analytic network process (ANP) to include managerial preferences. Finally, this range of weightage for each indicator is applied to perform restricted multiplier data envelopment analysis (RMDEA). Results show that the technical efficiency of the inefficient ECM programs for integrated RMDEA, on average, is calculated as 53.2% whereas traditional input oriented DEA provides the same score as 72.3%. This clearly indicates that integrated RMDEA is better than the input oriented DEA because same level of output could be produced with lesser resources if the ECM programs perform on the frontier. Hence, the advantage of this methodology is that the managerial preferences are successfully implemented through this newly developed hybrid methodology that will help to reduce less resource consumption and lead to better environmental policy. [ABSTRACT FROM AUTHOR]

The widespread need to reduce public expenditure and meet the targets for separate collection established by current national and European legislation requires regulatory authorities to reorganize their municipal waste management systems to improve both their economic and environmental performance. This process can be helped to a great extent by the availability of empirical measures of comparative efficiency. Adding to the literature that evaluates this through data envelopment analysis (DEA) – usually focused on economic (cost) efficiency alone – this article proposes a joint evaluation of the two aspects through a modified DEA model that includes unsorted waste as an undesired output to be minimized. The article also provides an application using data for 289 municipalities located in an Italian region, Abruzzo, for the period 2011–2013. The main focus of the empirical analysis is on dimensional aspects. In particular, comparing the results obtained through DEA models based on different hypotheses concerning returns to scale, in the first place it is verified whether a particular municipal dimension emerges as an efficient benchmark, and secondly if waste collection is organized above or below its optimal scale in the municipalities taken into consideration. Tobit and probit regression models are then applied to some of the results to isolate the influence of territorial specificities on different kinds of scale inefficiencies. The information obtained allows to shed light on the usefulness of designing multi-municipal optimal territorial areas (OTAs) to improve the joint benefits of environmental and cost efficiency in waste collection, and to understand which variables the regulator should preferably take into account in the process. [ABSTRACT FROM AUTHOR]

• Evaluation system of urban health development efficiency (HDE) was constructed. • Urban HDE from 2009 to 2019 was measured using the super-efficient SBM model. • Transfer probability matrix was constructed to examine the transfer status of HDE. • Spatial Markov chain model was used to identify the spillover effects of HDE. • Markov chain model was used to forecast the long-term evolution trend of HDE. Construction healthy city is a global strategy advocated by the WHO to address the social and environmental problems brought about by urbanization worldwide, and is also an important grip for China to promote the strategy of Beautiful China and Healthy China in the new era. This study constructed an evaluation system for health development efficiency (HDE) of Chinese cities from an input–output perspective, evaluated the HDE of 284 prefecture-level and above cities in China from 2009 to 2019 using the super-efficient SBM model, and further explored the dynamic transfer characteristics, spatial spillover effects, and future development trends of urban HDE in depth using Markov chain model and spatial Markov chain model. The main findings were as follows. (1) From 2009 to 2019, the average level of HDE in Chinese cities generally showed a "W-shaped" fluctuating upward trend, increasing from 0.6106 to 0.6538, an overall increase of 7 %. However, the overall input–output efficiency was still relatively low, with only 27.11 % of cities in a high efficiency state in 2019. (2) The spatial distribution pattern of HDE of cities nationwide showed a gradually decreasing pattern with the urban cluster cities as the core, specifically "eastern cities > western cities > central cities" and "mega cities > super cities > large cities > medium cities > small cities". (3) There was a significant spatial spillover effect on the HDE of Chinese cities. When a city was adjacent to a region with low HDE, the probability of its HDE type shifting downward increased, and when it was adjacent to a region with high HDE, the probability of its HDE type shifting upward increased. (4) In the long term, the distribution of urban HDE in China gradually shifted from intermediate (ML and MH) to high (H) or low (L) state over time, with the greatest possibility (27.40 %) of dynamic shift to high (H) states. After further classification and prediction based on spatial neighborhood states, heterogeneity in the future evolutionary impact of different neighborhood contexts on urban HDE was found. These findings can provide references for improving the quality of healthy cities work and optimizing healthy cities guidance policies. [ABSTRACT FROM AUTHOR]

• The relation between efficiency and sustainability is an open dilemma. • The eco-efficiency is an agricultural sustainability index for policy makers. • The methodology proposes an indicator for each environmental resource. • The northern regions best performing via minimizing the use of environmental resources. • The critical point emerging from the analysis is the missing reduction of waste in agriculture. Agriculture is a key activity in guarantying food security, one of the Sustainable Development Goals set by the UN Agenda 2030 for sustainable development. However, agriculture can be an environmental impacting activity when it is managed without attention towards its environmental efficiency. Thus, the assessment of eco-efficiency in agriculture is a crucial tool to evaluate this economic activity in terms of both natural resources exploitation and revenue generation. To address the complex issues associated with this problematic trade-off, the application of a Data Envelopment Analysis (DEA) has been to assess the environmental and economic performance of agriculture in terms of eco-efficiency. DEA has been applied the Italian case study at regional level, to provide policy-makers with a synthetic indicator of agricultural sustainability, when implementing funding policies. In particular, the analysis of the case study has taken into account the implementation of the European Common Agricultural Policy (CAP), as implemented through the Rural Development Plans. Our approach is a first step in the direction of assessing the long-lasting issue of developing benchmarking policies between the different Italian regions. This works paves the way to future and more in-depth studies needed to determine the eco-efficiency at local scale and, thus, the possibility to identify specific forms of agriculture as nature-based solutions. [ABSTRACT FROM AUTHOR]

• Improving marine ecological welfare is essential for development of marine economy. • No unified method for measurement of marine ecological welfare performance exists. • Environmental factors strongly affect regional marine ecological welfare performance. This study used three-stage data envelopment analysis (DEA) and Tobit regression models to comprehensively evaluate the performance levels, trends, and differences of marine ecological welfare (MEW) in China, and explore its influencing factors to derive relevant policy suggestions. The evaluation results indicate that the three-stage DEA model performed better on MEW than the traditional DEA model by effectively eliminating the influence of random errors and external environmental factors. However, it underestimated the coastal MEW performance of the country. The southern marine economic circle showed an overall improvement, whereas the overall northern marine economic circle did not improve much; the eastern marine economic circle was stable. Moreover, the external environmental factors significantly impacted the performance of MEW, and the value of average MEW performance of each province changed to some extent under the influence of the slack variables of resource consumption and environmental consumption input. Other factors that significantly influenced China's coastal MEW performance were the level of economic developments on land and government environmental regulations, which correlated positively. Meanwhile, inadequate development momentum in marine research and technology or poor achievement transformation rate negatively influenced it. Finally, countermeasures and suggestions were proposed based on the results of empirical analysis. [ABSTRACT FROM AUTHOR]

Many cities are experiencing rapid urbanization and ecological degradation, which has resulted in unsustainable development. It is essential to conduct a scientifically rigorous method to assess the regional sustainability. Among many indicators, eco-efficiency could be an effective instrument to promote a transformation towards sustainability. This study applied the emergy ecological footprint analysis and data envelopment analysis to evaluate the eco-efficiency using data collected from 1993 to 2012 for Jiangsu Province, China. The results showed that Jiangsu’s emergy ecological footprint and ecological deficit experienced an ascending trend in general during the period 1993–2012, indicating that the regional development of Jiangsu has been moving away from sustainability for a long time. In six types of biologically productive areas, fossil land and arable were the major parts of emergy ecological footprint. Furthermore, the growth of green gross domestic product was only about 52% of the conventional gross domestic product, and the pollutants emission, energy and resources consumption increased yearly as the gross domestic product increased. Finally, the result of the data envelopment analysis model showed that the effective years only accounted for 20% during the 20 years. In the inefficient years, biological resources, energy resources, pollutant emission (wastewater, gas and solid) and labor were overmuch, and the efficiency of fund usage achieved the optimal in Jiangsu Province. Therefore, improving the level of agricultural modernization, increasing the proportion of non-fossil energy, developing renewable energy and reducing pollutant emission are recommended to promote the regional sustainability. [ABSTRACT FROM AUTHOR]

The transportation sector, particularly the road and the railway sectors, is an important source of CO 2 emissions in China. This study combines the non-radial data envelopment analysis (DEA) model with window analysis to measure the energy-environment efficiency of the road and railway sectors of 30 provinces in China, then uses the Tobit regression model to analyze the factors affecting the energy-environment efficiency. The findings suggest that, first of all, although these two sectors are both with high energy-environment efficiency, there is a higher probability for railway sector to improve its energy-environment efficiency than that of road sector, with the average energy-environment efficiency 0.9307 and 0.9815, respectively. Second, the road sector in eastern China with the highest average energy-environment efficiency, lower in the western region, and lowest in the central region. As for the railway sector, the western region has the highest average energy-environment efficiency, followed by the central and the eastern regions. Third, the relationship between energy-environment efficiency and income level in the road and railway sectors follow the U-shaped and inverted U-shaped curves, respectively. [ABSTRACT FROM AUTHOR]

This paper estimates water use efficiency of 31 provinces in China during 2004–2013 using slack based measure-data envelopment analysis (SBM-DEA) model which takes consideration of sewage. By using panel data model, factors that influence water use efficiency are explored. The results show that: (1) water use efficiency is higher in economically developed provinces such as Beijing, Shanghai and Tianjin. (2) In general, inefficiencies of labor input and water input are larger than that of capital input. (3) After taking into account sewage as unexpected output, inefficiency of gross domestic product (GDP) for each province is quite low, but most provinces have inefficient sewage emission. (4) It is found in the analysis of influencing factors that the ratio of added value of agricultural sector, water usage per capita and sewage per unit of output have negative impact on water resources use efficiency, while the import dependence and export dependence have positive impact. The results are robust. [ABSTRACT FROM AUTHOR]

• Environmental regulations can improve energy-environment efficiency of firms. • Environmental policies have asymmetric impact on heterogeneous firms. • End treatment and source control are important channels for improving efficiency. • Impact of different policy tools on energy-environment efficiency is heterogeneous. • Micro evidence for evaluating the effect of environmental regulation is provided. Energy-environment efficiency can be used as a means of control to change the mode of economic development by considering the pollution reduction factor. Taking China as an example, this study uses a nonradial superefficiency data envelopment analysis method to measure microlevel energy-environment efficiency and investigates the relationship between environmental regulation and efficiency. The findings show that for every 1% increase in environmental regulation, firms' energy-environment efficiency increases by approximately 0.04% and that environmental regulations have a greater impact on pollution-intensive firms and private firms compared to other types of firms. A median effect model shows that end treatment and source control are important channels through which environmental regulation can improve firms' energy-environment efficiency. In addition, the influence of different environmental regulation policy tools on firm energy-environment efficiency is heterogeneous. With every 1% increase in a command-and-control and market-based incentive policy, energy-environment efficiency increases by 0.01–0.02%, while the effect of public participation policy tools is not significant. This study provides not only new micro empirical evidence for evaluating the effect of environmental regulation but also a reference for applying and coordinating different types of environmental policy tools. [ABSTRACT FROM AUTHOR]

The efficiency of an intercropping system depends mainly on the cropping system and on the crops, which should complement each other. However, the choice of crops and factors of production are extremely important for maximizing the advantages of intercropping, which, in turn, means maximizing the bio-agro-economic performance of the system. The present study sought to assess, based on appropriate indexes and indicators and using univariate and bivariate analysis, the agronomic/biological and economic returns from a system in which salad rocket was intercropped with carrot at different population densities and one of spontaneous species of the semi-arid region of Brazil, namely hairy woodrose ( Merremia aegyptia L.), was used as green manure. The population densities of both the crops were maintained at 40%, 60%, 80%, or 100% of the recommended population for a sole crop (RPSC). The following values were recorded or calculated: green biomass of rocket, biomass of carrot roots, aggressivity indexes, competitive ratio, land equivalent ratio, productive efficiency index, canonical variable score, and four economic indicators, namely gross and net returns, rate of return, and net profit margin. The most effective combination was carrot at 40% of its RPSC intercropped with rocket at 100% of its RPSC with hairy woodrose as green manure because the combination resulted in the highest values of land equivalent ratio (1.72), productive efficiency index (0.91), canonical variable score (1.68), gross returns (R$ 41,186.91 ha −1 ), net returns (R$ 18,621.64 ha −1 ), rate of return (1.84), and net profit margin (52.77%), making it a highly profitable combination for the north-eastern semi-arid region of Brazil. The most effective indicators of economic value were yield and the rate of return. [ABSTRACT FROM AUTHOR]

To better understand the economic performance of cities and the accompanying social and environmental implications, one focus of research has been on ways to quantify performance advantages of growth and size while considering the impact of economies of scale. An important aspect of the current discussion is the introduction of the merely environmental driven concept of resource efficiency, defined as minimizing resource consumption while enhancing the quality of life. However, as yet there is no commonly agreed method on how best to measure efficiency. In order to contribute to this debate, an approach is described here of applying Data Envelopment Analysis (DEA) to study the resource efficiency of cities. Originating in the field of economics, DEA is a non-parametric, deterministic method to measure the efficiency of economic production, specifically the relative efficiency of Decision Making Units (DMUs). Here we test the usefulness of DEA to analyze urban efficiency by applying it to an investigation of 116 cities throughout Germany. This entailed the development of two separate economic and ecological models in order to allow more precise identification of the relevance of individual parameters during the evaluation process. The results allow a ranking of cities as well as an estimation of the ratios of economic and ecological efficiencies of the investigated cities, realized with the aid of a nine-field matrix (portfolio). DEA is at the same time a promising heuristic tool to help draw the basic outlines of a resource efficient city and to shed light on the underlying factors that boost or reduce efficiency. We recommend a three-step approach. First, two separate models should be defined (ecological, economic) and used to feed the DEA computation. Second, the results are spread in a portfolio to give an overview of the ecological and economic efficiency scores. This provides a basic overview of the DEA results for the selected cities following a basic and abstract model without determination of causal relationships between these values. Third, the field-dependent commonalities between the cities are considered. Additional indicators that also characterize the selected cities (but which were not selected as inputs to the algorithm) can now be examined. In this way, it is possible to understand the common factors that determine the level of efficiency as well as to learn about the qualitative difference and specific features of cities in the particular matrix quadrants. [ABSTRACT FROM AUTHOR]

REDD+ reference levels directly impact the benefits which a country may receive. However, the existing “Compensation Reduction” (CR) and “Compensated Successful Efforts” (CSE) are only considered from a unilateral perspective of outputs or inputs. The combination of these two approaches is considered to estimate the REDD+ reference levels through the Zero-Sum-Gains Data Envelopment Analysis in this paper. The agricultural labor force and agricultural land area are used as input variables, and the gross agricultural production and carbon emissions from deforestation are considered as output variables. The REDD+ reference levels of 89 countries are calculated and classified through the Zero-Sum-Gains DEA model. The results demonstrate that the REDD+ reference levels are estimated efficiently through the Zero-Sum-Gains DEA model, and all countries with deforestation are in the Zero-Sum-Gains DEA frontier, indicating the overall Pareto optimality has been achieved. The empirical results also indicate that the use of Zero-Sum-Gains DEA model is more beneficial for Latin American and the Caribbean, while the countries that may see a revenue drop in REDD+ are in Africa, Asia and Oceania. Consequently, the final REDD+ reference levels should take into account both efficiency and fairness by selecting the appropriate fairness-efficiency weighting factor. [ABSTRACT FROM AUTHOR]

• An LCA procedure at corporate level which incorporated the absorption of CO 2 by trees. • A joint LCA and time-series DEA methodology to calculate eco-efficiency score. • An input–output indicator system constructed to assess the eco-efficiency. • Environmental impact, wood fiber and energy are key factors to enhance eco-efficiency. Complex forestry enterprises have the potential to lead the current industrial upgrade under the strategy of carbon neutrality and carbon peaking. This paper aims to investigate the inputs and outputs influencing the eco-efficiency of complex forestry enterprises through a case study. A hybrid ensemble approach of life cycle assessment (LCA) and time-series data envelopment analysis (time-series DEA) was proposed to evaluate the case enterprise's eco-efficiency. It is found that, from the perspective of the average intensity of key input and output factors, environmental impact in efficient years is 45.25% of that in inefficient ones, and when it comes to the fiber consumption and the energy consumption, this percentage turns into 65.53% and 77.66%. With the findings, we provide guidelines for complex forestry enterprises to enhance the eco-efficiency in improving environmental impact and in giving full play to the advantages of forestry industrial chain resources. Our findings also contribute to the existent literature by providing a systematic study based on a corporate time-series dataset. [ABSTRACT FROM AUTHOR]

As a main method for achieving environmental protection, improvement of environmental efficiency is vitally important for reducing environmental risk and level of ecological scarcity. Thus, quantitative analysis of environmental efficiency is not only an important premise for understanding the situation of regional environmental protection, but also a prerequisite for designing and adjusting relevant policies. In this paper, we treat the undesirable output in an economic activity by a linear monotonic decreasing transformation approach. We employ data envelopment analysis (DEA) technique to evaluate environmental efficiency in 30 provinces of China during the period 2001–2010, and conduct hypothesis tests on these environmental efficiencies. Furthermore, we investigate the horizontal differences of environmental efficiency in six regions of China and the vertical differences among different years. The results show that our empirical tests have a high statistical reliability that provides support for prompting environmental policies in different parts of China. [ABSTRACT FROM AUTHOR]

This paper adopts data envelopment analysis method to calculate the regional energy efficiency from the perspective of total-factor energy efficiency. The Markov chain and spatial Markov chain are the common methods to test the club convergence of regional energy efficiency in China. Results indicate that the regional energy efficiency in China has been globally characterized by “club convergence” since 1999, and the energy efficiency transitions in China are closely connected with regional characteristics. A high level of energy efficiency has a positive influence on a region, whereas a low level of energy efficiency has a negative influence. This empirical analysis provides a spatial explanation to the “convergence clubs” of regional energy efficiency in China. [ABSTRACT FROM AUTHOR]

This study measures the environmental efficiency of China based on environmental super-efficiency data envelopment analysis (SEDEA) model by using data of 30 provinces in China during the period of 2000–2010. We find that environmental efficiencies across 30 provinces show regional disparities. Cities such as Beijing and Shanghai have experienced improvement in efficiency while Qinghai showed worse performance. More generally, East areas are more efficient in production while the west rank the last with central areas ranking in between during the period studied. Policies should be established to further promote production efficiency. [ABSTRACT FROM AUTHOR]

As environmental problems become more and more serious all over the world, environmental efficiency evaluation has drawn increasing interests of many scholars and governments’ decision makers. Data envelopment analysis (DEA) as a non-parametric approach for evaluating the relative efficiency of a group of decision making units (DMUs) has been widely extended and applied in many areas. Among various DEA models, enhanced Russell measure (ERM) model can measure the inefficiencies from input orientation and output orientation simultaneously. In this paper, we proposed a new non-orientation DEA approach based on enhanced Russell measure for measuring the environmental efficiency of a DMU and meanwhile, provided the closest target for the evaluated DMU to efficient with less effort. At last, our approach was applied to a practical example about thermal power enterprises. The results show that our model can provide a much easier way for the inefficient enterprises to improve their efficiencies than the enhanced Russell measure method. Moreover, the provided benchmarks for enterprises through our model can be used to further rank the efficient ones. [ABSTRACT FROM AUTHOR]

Numerous studies have linked individual nutrient loadings from the Mississippi and Atchafalaya Rivers to the growth of the hypoxic, or oxygen depleted, zone in the northern Gulf of Mexico. However, in the discussion of policy to remediate Gulf hypoxia, it is beneficial for stakeholders and policymakers to obtain a single measure for water quality that characterizes information from multiple water pollutants. This study aggregates loadings from six nutrients measured at the entrance to the Gulf of Mexico into a single time-varying index of water quality. The index is constructed using traditional index number theory originating from economic production theory, mainly, Shephard’s distance functions calculated using data envelopment analysis (DEA). The methodology is an advance over other index construction schemes because the determined metric weights are endogenous, calculated from the data itself, and do not require external user input. To validate the index, May values of the index are used within a statistical regression model to model the areal extent of Gulf hypoxia using mid-July cruise measurements from 1985 to 2013, excluding 1989 when no cruise data were available. Regression results ( R 2 adj = 0.81) suggest the index is successful at aggregating multiple pollutants into a single measure of water quality and may be useful for tracking their aggregated effect on the growth of the hypoxia area in the northern Gulf of Mexico. Calculation of the water quality index described here is automatic in the sense that no human intervention is required for variable selection, statistical analysis or assignment of weights. This is very useful for specifying a water quality objective in a multiple objective optimization for watershed management. [ABSTRACT FROM AUTHOR]

[Display omitted] • Green innovation could be divided into R&D and achievement conversion stages. • Tourism green achievement conversion efficiency was relatively high. • Western provinces outperformed eastern ones in tourism green R&D. • Energy utilization technology has the greatest influence on tourism GIE. • Combination improvement paths were either in technology or non-technology. For the high-quality development of China's tourism industry, improving the tourism green innovation efficiency (GIE) to promote the green development of tourism from the perspective of technological innovation is essential. However, the level of development and specific promotion path of tourism GIE in China's provinces remains unknown, which this study attempts to determine. GIE has two stages: research and development (R&D) and achievement conversion. A two-stage relational data envelopment analysis model with shared inputs was used to evaluate the efficiencies of these two stages in tourism in 30 Chinese provinces during 2002–2017; and according to the relationship between these two efficiencies; tourism GIE was divided into four types: low/high green R&D and low/high achievement conversion. Furthermore, fuzzy set qualitative comparative analysis was used to design combination improvement paths of China's tourism GIE. The results show that: (1) western provinces outperformed eastern ones in green R&D and the opposite was true for green achievement conversion; (2) 30% of the provinces were in the low/low, 50% in the low/high, and 20% in the high/high stages; (3) combination improvement paths were either in the technology or non-technology path. The results of this study can provide a reasonable reference for the Chinese government to build a high-quality tourism development pathway from the perspective of green technology. Due to the lack of statistical data for China's tourism industry, this study was limited to using only the number of patent applications as an output indicator when measuring the tourism green R&D efficiency, thus the resulting selection of indicators was less comprehensive than expected. [ABSTRACT FROM AUTHOR]

• A new framework is proposed to measure the sustainability of Chinese cities. • New models are proposed to determine desirable and undesirable congestions. • Most Chinese cities have poor economic and environmental performance. • There exists serious resource waste, requiring a new economic growth mode. • Efficiency inequality persists across Chinese cities, but declines over time. As the second largest economy in the world, China faces serious environmental issues. Currently, how to promote sustainability has become an important priority for policymakers and has attracted great attention from researchers. To evaluate sustainability, this study proposes a new methodological framework. This framework consists of a new data envelopment analysis (DEA) model, concepts of natural and managerial disposability, strong complementary slackness conditions, efficiency Theil index and K-Means clustering method. With the use of this framework, this study obtains unified efficiency measures, technology-based measures, and efficiency inequality measures. These measures assist decision makers in promoting efficiency, mitigating environmental degradation and promoting sustainability. Empirically, this study considers the case of 198 Chinese cities from 2010 to 2016. Five main conclusions are presented. First, Chinese cities improved their unified efficiency scores under both natural and managerial disposability. Second, there is a significant number of occurrences of undesirable congestion, which means that most Chinese cities can save considerable resources during the production process. Third, there is a limited number of occurrences of desirable congestion, implying that only a small portion of Chinese cities have achieved a high level of sustainability. Fourth, efficiency inequality across Chinese cities has gradually decreased over time, where technology diffusion plays an important role. Finally, China faces considerable regional/provincial inequality. Looking ahead, cities that lag behind should put significantly more effort into enhancing both economic prosperity and environmental protection. [ABSTRACT FROM AUTHOR]

Highlights: [•] Use data envelopment analysis for city eco-efficiency assessment. [•] The environmental emission is treated as “undesirable output”. [•] Proposed a super efficiency DEA model for eco-efficiency discrimination. [•] The DEA results well represent the city sustainable development. [Copyright &y& Elsevier]

Abstract: With the implementation of the strategic policy and the construction of Wanjiang demonstration area recently, the government cares more about the natural environment. To protect the environment of this demonstration area, a quantitative analysis of environmental efficiency and its influencing factors is needed. In this paper, we measure the environmental efficiency of the demonstration area, and then analyze the total factor productivity of the area by Malmquist productivity index through data envelopment analysis (DEA) approach. Through the index and its decomposition, we are able to reveal the changing trend of the environmental efficiency. Moreover, we apply Bayesian estimation approach to analyze the influencing factors of the efficiency and discuss the relationship between these factors and the environmental efficiency. Results show that the efficiency of Wanjiang demonstration area bares a significant difference among constituent cities. Each area should devise proper environmental policy according to its particular circumstance. [Copyright &y& Elsevier]

Abstract: The degree to which regions can produce desirable socioeconomic and environmental outcomes while consuming fewer resources and producing fewer undesirable outcomes can be viewed as measure of productivity. Economists have frequently used Malmquist Indices to evaluate intertemporal productivity changes of economic entities, such as firms and countries. We use Malmquist Indices to evaluate the predicted environmental performance of the rapidly growing Charlotte, NC, metropolitan area under alternative future land use scenarios. These scenarios project population, urban development, and environmental impacts from the base year 2000 to the year 2030 within the region's 184 watersheds. The first scenario is based on a continuation of current growth trends and patterns (“Business as Usual” or BAU). The second scenario uses compact “smart growth” development (“Compact Centers” or CC). We use data envelopment analysis (DEA) to estimate Malmquist Indices, which in this case, combine multiple variables into a single indicator that measures the relative impact of different development patterns on the consumption of natural resources. The results predict that the CC scenario maintains the region's current productivity, while the BAU scenario results in lower productivity. As watersheds in the study area are about the same size, weighting the results by area makes little difference. Watershed populations, however, vary greatly, and our results predict that watersheds with higher population densities also have higher Malmquist Index efficiencies. The model also predicts that low population watersheds will benefit more from the CC scenario. While the application of these analytical techniques in this case study is limited in scope, the results demonstrate that the Malmquist Index is a potentially powerful tool for interdisciplinary environmental impact analysis [Copyright &y& Elsevier]

Abstract: Agriculture in Scotland is facing immense challenges for the future. Scottish policy now promotes sustainable economic growth, which to many implies both a growth in resource use and the requirement to meet targets for reducing greenhouse gas emissions. Attempts to increase economic gains can be in conflict with environmental aims and the question arises how both objectives can be met simultaneously. This paper examines the relationship between the technical and environmental efficiency of dairy farms in Scotland with respect to greenhouse gas emissions. It estimates the technical efficiency of a sample of dairy farms based on survey data, applying a number of approaches based on the non-parametric Data Envelopment Analysis (DEA) method. The farms’ greenhouse gas emissions are calculated using a variety of sources and were used to estimate environmental efficiency. This paper finds that, within the study sample, farms which are more technically efficient, are bigger or have higher yields are also more efficient in their emissions of GHG emissions. These results suggest that the potential exists for, Scottish dairying to improve its competitiveness and lower greenhouse gas emissions by increasing efficiency, though the extent of the environmental benefits achieved largely depends on how efficiency is increased. [Copyright &y& Elsevier]

Abstract: This paper presents a methodology for building a composite indicator to evaluate the sustainability of nature-based tourism destinations. It combines Principal Component Analysis (PCA), the distance to a reference point, and Data Envelopment Analysis (DEA) with the aim of addressing some of the objections related to the aggregation procedure. The synthetic index obtained is based on a representative series of sub-indicators of the concept of sustainable tourist development as outlined by the World Tourism Organization (WTO). We apply it to evaluate Cuban nature-based tourism destinations. The results identify the strengths and weaknesses of destinations according to sustainability, and serve as a guideline for tourism planning in the future. [Copyright &y& Elsevier]

Abstract: The non-parametric Data Envelopment Analysis approach is increasingly used to construct composite indicators for country performance monitoring, benchmarking, and policy evaluation in a large variety of fields. The flexibility in the definition of aggregation weights is praised as the method's most important advantage: DEA allows each evaluated country to look for its own optimal weights that maximize the composite indicator relative to the other countries. However, this flexibility also carries a potential disadvantage as it may allow countries to appear as a brilliant performer in a manner that is hard to justify: by ignoring or overemphasizing one or multiple of the judiciously selected performance indicators. To illustrate this issue of undesirable specialization in DEA-based evaluations, this paper compares the Environmental Performance Index (EPI) as computed by the optimistic and pessimistic version of the DEA-model as proposed by Zhou et al. (2007). Based on both computed composites, undesirable specialization in performance is identified. [Copyright &y& Elsevier]

[Display omitted] • Define IE as an evolutionary process characterized by the dimensions of industry and ecology. • Industrial efficiency and eco-efficiency were analyzed from spatial-temporal perspectives. • Cities were classified as coordinated development mode and professional development mode. • Social network analysis was used to examine the spatial correlations of IE. • The IE interaction network was characterized by "scale-free" and "small world." Industrial ecology (IE) was defined as a dynamic evolution process characterized by the coupling coordination relationship between ecological efficiency and industrial efficiency. This paper used data envelopment analysis and technique for order preference by similarity to ideal solution method to explore the spatiotemporal evolution of ecological efficiency and industrial efficiency in China's loess plateau region (LPR) from 2006 to 2017. Based on the definition, LPR's IE development and spatial correlations were studied separately using coupling evaluation model and social network analysis. Findings include: Although eco-efficiency and industrial efficiency were mutually promoted, and both have improved during the study period, LPR's human-earth relation was still facing uncertainties. There were significant disparities in industrial efficiency, ecological efficiency, and IE levels among cities. The evolutionary patterns of cities were classified as coordinated development mode and professional development mode. The IE interactive network was characterized by "scale-free" and "small world," where provincial capitals and big cities functioned as growth poles and intermediaries. The correlations of IE brought challenges as well as favorable conditions for setting up a cross-regional coordination mechanism. This paper provided a new perspective to understand IE and a "quantity and structure" driven development idea for policymakers. [ABSTRACT FROM AUTHOR]

• A method to examine the effectiveness-efficiency nexus in municipal waste management is presented. • Data Envelopment Analysis is employed to measure technical, scale and congestion municipality efficiency. • Panel Tobit regression is used to evaluate how efficiency impacts on effectiveness. • Municipality heterogeneities and unobserved factors are considered. • Municipal solid waste management performance in Apulia from 2010 to 2017 is evaluated. The scope of this work is to present a comprehensive approach to analyze the effectiveness-efficiency nexus in the evaluation of the performance of municipal solid waste (MSW) management. The rate of separate MSW collection is used to measure service effectiveness. A multiple set of non-parametric indicators is employed to obtain measurements of technical, scale and congestion efficiencies of waste service provision. This approach was implemented to conduct an empirical study to evaluate the performance of MSW management in 258 municipalities in the Apulia region (Southern Italy) from 2010 to 2017. The study was organized in two phases. In the first phase, measures for the three efficiency indicators were calculated applying Data Envelopment Analysis (DEA) with an output-oriented model specification. In the second phase, Panel Tobit analysis with random parameters was employed to examine the effectiveness-efficiency one way nexus, considering both municipalities' heterogeneities and context-specific variables. The efficiency analysis shows that several municipalities are still far from achieving acceptable performance scores. Between 2010 and 2017 the average rate of separate MSW collection increased only from 16.6% to 39.6%, while the average loss of technical efficiency ranged from 27% to 39%. On average, such inefficiency was due to an important extent to the low pure technical efficiency that ranged from about 69% to 81%, and to a lesser extent to scale and congestion inefficiencies. Indeed, scale efficiency was between 85.4% and 92.6%, whereas congestion efficiency was higher than 99%. The study also highlights that there is no trade-off between effectiveness and efficiency. For the largest part of the municipalities, high levels of effectiveness and efficiency can be achieved at the same time. For about 83% of the municipalities the decrease of the sorted waste collection rate is associated to a decrease of the pure technical efficiency. A drop of the output congestion efficiency due to a relatively high collection of the unsorted fraction of waste reduces the rate of the sorted waste collection for most of municipalities (77.3%). Results also indicate that for many municipalities (about 87%) improving the MSW service effectiveness necessarily requires reducing the average quantity of waste generated by people. [ABSTRACT FROM AUTHOR]

• Evaluated the quality but not the quantity of tourism ecological security. • A new evaluation framework of tourism ecological security was created. • Spatial autocorrelation analysis was applied to examine the tourism ecological security pattern. • There is the significant spatial spillover effect on tourism ecological security in the YRD. Tourism ecological security (TES) is an essential component and basic guarantee of the tourism regional system, and it is of great significance for scientific measurement of the operational status of a regional tourism ecological security system. The study focuses on the "quality" of tourism ecological security that has been neglected in the previous literature. From the perspective of system efficiency, taking the Yangtze River Delta as the case, we build the index system of regional tourism ecological security measurement based on the "DPSIR" model, and identify the quality of the tourism ecological security system using the data envelopment analysis method. On this basis, the study uses spatial autocorrelation to visualize the spatiotemporal patterns of evolution and regional differences, and uses spatial econometric model to study the spatial effects of regional tourism ecological security. The study shows that: the tourism ecological security follows an overall rising trend of "W" fluctuation with regional differences in the Yangtze River Delta (YRD). Tourism ecological security of Jiangsu, Zhejiang and Shanghai is in good condition, that of Anhui Province is poor, and Hangzhou, Zhoushan, Huangshan, Shanghai, Nanjing and other cities perform well. The overall spatial autocorrelation of tourism ecological security is significant and shows a trend of fluctuation intensification. The local correlation indicates that the tourism ecological security space is highly dependent and has a spatial differentiation pattern of "south to north" in Yangtze River Delta. The direct effects of park greenspace per capita, proportion of total tourism revenue in GDP, number of employees in the tertiary industry, and education expenditure on the regional tourism ecological security are significant. And the indirect spatial spillover effect of park greenspace per capita, the proportion of total tourism revenue in GDP, and education expenditure is obvious. Finally, from the perspective of efficiency, quality can effectively clarify the operational process and mutual relationships of regional tourism ecological security systems, and provide a scientific basis and reference for formulating targeted tourism development policies. [ABSTRACT FROM AUTHOR]

• DEA was used to evaluate the industrial eco-efficiency of Chinese provinces. • The determinants of eco-efficiency were analyzed using a random-effects Tobit model. • China's overall industrial eco-efficiency trend was upward in the 2005–2015 period. • Chinese provinces still face huge regional disparities in eco-efficiency. • Economic factors and the share of state-owned companies were major determinants. China has undergone momentous changes and achieved remarkable economic progress since its economic reform and opening-up in 1978. However, the consequent resource depletion and environmental degradation have seriously restricted China's potential for sustainable industrial development. As a practical tool contributing to sustainable development, the concept of eco-efficiency is considered increasingly important for reducing the trend of resource exhaustion and environmental degradation. This study first evaluated industrial eco-efficiency in 30 Chinese provinces during 2005–2015 using data envelopment analysis (DEA), and then identified the determinants of the resulting eco-efficiency scores using random-effects Tobit regression analysis. The DEA results showed that although China's overall industrial eco-efficiency trend was upward, there were great disparities between provinces. Provinces with high industrial eco-efficiency were mainly distributed across the eastern region, while those in the often economically less developed western region had lower industrial eco-efficiency due to technological deficits and weak environmental policies. The Tobit regression results indicated that internal research and development expenditure in industrial enterprises, per capita gross regional product, and investment in wastewater treatment had positive effects on provincial industrial eco-efficiency. By contrast, the proportion of state-owned enterprises and investment in waste gas treatment had negative impacts. These findings provide valuable insights that can help provinces with low industrial eco-efficiency to pursue high-quality, green development. [ABSTRACT FROM AUTHOR]

[Display omitted] • Investigating the urban wastewater governance under the context of China's River Chief system. • Quantifying the spatiotemporal distribution and driving effects in wastewater governance efficiency. • The SBM-DEA model with undesirable outputs and LMDI decomposition model are developed. • Wastewater treatment efficiency is improved through the implementation of China's River Chief system. Investigating the wastewater treatment efficiency (WTE) is an important component in fostering sustainable water management. This study proposes an environmental production technology framework based on eutrophication levels and heavy metal concentrations caused by wastewater discharge. The slack based measure (SBM) model with undesirable outputs and logarithmic mean Divisia index (LMDI) decomposition model are developed to quantitatively investigate the spatiotemporal distribution and driving effects in urban wastewater treatment under the context of China's River Chief system. Results showed that the distribution curve of WTE changes from double peaks to a single peak, and WTE value appears a decreasing (2001–2010)-increasing (2011–2020) trend. Provinces with high WTE are mainly distributed in eastern China, with low WTE are in western China. Overall, wastewater treatment efficiency has been generally improved through the implementation of China's River Chief system. And provinces with low WTE are shrinking, with high WTE are extending from southeastern to northwestern China. To achieve a simultaneous improvement in wastewater treatment efficiency, it is necessary to improve the WTE in corresponding provinces that belong to barely effective development and inefficient development. Meanwhile, provinces in superiorly effective development and slightly effective development should be encouraged to maintain their high-level WTE. [ABSTRACT FROM AUTHOR]

[Display omitted] • A framework for evaluating land use efficiency was built from the perspective of decision-makers' preferences. • As the unexpected output increases, the overall efficiency decreases. • It is necessary to abandon the previous view of "development first" in order to improve overall efficiency. • The efficiency of compact land development is higher than that of the type of expansion. • A two-stage DEA model was constructed to evaluate the efficiency of land use systems. Land resources are not only the spatial carriers of social and economic development, but also the carriers of environmental and ecological services. With the accelerated urbanization, the non-coordinated development of land resources and environmental protection will restrict economic growth and the benefits of land use changes. Moreover, the economic efficiency and environmental efficiency of land use largely depend on the value judgment of the decision makers on the future human environment. Therefore, it is extremely important to achieve a win–win outcome of land development and ecological protection. In this research, a new analysis framework for land use efficiency was proposed from the perspective of decision makers' different benefit preferences. This framework uses the unexpected output of environmental pollution as a bridge to build a two-stage data envelopment analysis (DEA) model to evaluate the economic efficiency, environmental efficiency and overall efficiency of land development, and weight parameters were constructed to express decision-makers' preferences. The model not only considers the objectivity of the scores of land use efficiency, but also guarantees the subjectivity of decision-makers in land use management. This is also the biggest difference between previous studies in this study. The specific conclusions are: (I) as decision makers tend to focus on economic benefits, economic efficiency first rises and then declines. It can be seen that ignoring the problem of environmental pollution will reduce economic efficiency. (II) Generally speaking, the efficiency of compact land development (0.883) in various counties and cities in Taiwan is greater than the efficiency of expanded land development (0.737). This research can provide guidance on the distribution of land resources and the development of land space on a macro-regional scale. [ABSTRACT FROM AUTHOR]

• We built a life-cycle data envelopment analysis framework to study atmospheric environmental efficiency (AEE). • AEE was decomposed into CO 2 and PM 2.5 emission efficiencies. • PM 2.5 efficiency increase was the main driver of China's transport AEE improvement. • The western region led China's transport sector AEE since 2014. • China needs market-oriented mechanisms to alleviate environmental regulation cost. The synergistic reduction of CO 2 emissions and air pollutants is of great concerns in China's transport sector environmental regulation. This study built up a life-cycle data envelopment analysis model to inclusively measure CO 2 and PM 2.5 management performance of China's 30 provinces' transport sectors during 2013–2017 using the atmospheric environmental efficiency (AEE). We showed that the PM 2.5 efficiency improvement was the main driver of China's AEE increase from 0.544 in 2013 to 0.649 in 2017. The west of China exhibited the fastest growth and led the AEE since 2014; the central region also increased its AEE by 14.6% in the study period, while the east showed a negligible AEE improvement. Furthermore, the results showed that strict environmental regulation in the transport sector may cost China's economic growth. Hence, we suggest that CO 2 management demands more regulatory attention, and that market-oriented regulatory mechanisms, such as integrating the transport sector into carbon and PM 2.5 emission trading systems, is needed to lower cost and enhance AEE. [ABSTRACT FROM AUTHOR]

• The proposition of transition cycles for a low-carbon economy based on human development and climate action. • A climate justice index in line with the United Nations' concepts of sustainable development. • A climate justice index that benchmarks nations with the same level of economic development. • The proposed index can help policy-makers and national government to identify synergy between climate actions and human development policies. Since the climate change context is increasingly the focus of decision-makers, indices capable of helping them in the transition to a low-carbon economy are considered necessary. Therefore, the objective of this work is to propose an index of climate justice that includes factors of human development and climate action. The index was developed using the Data Envelopment Analysis (DEA) technique and, in this study, assessed the climate justice of 198 nations. After the calculation, statistical analysis was used to compare the climate justice of the aforementioned countries, grouped by level of development and geographical location. The results obtained were: a) there is currently no nation that fully guarantees climate justice to its population; b) there is a difference in the performance of climate justice between the Annex I, Non-Annex I and Least Developed Countries (LDCs) groups; c) nations located in Africa, Latin America and the Caribbean, Asia and Eastern Europe are similar in terms of climate justice index performance. The main contribution of this paper is in the fact that the proposed index can help policy-makers and national governments to define climate and development policies, creating a synergy between such policies. [ABSTRACT FROM AUTHOR]