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China's paper industry accounts for a larger proportion of the global paper industry and consumes large amounts of energy. Energy conservation and pollution reduction of the industry have become the focus of China's national development strategy. Energy efficiency is an important index which directly determines the amounts of energy consumption and pollution emissions. To understand the energy efficiency evolution of China's paper industry, this paper establishes an input-output data of the paper industry for 29 provinces in China and applies DEA method and econometric models to estimate and comprehensively discuss the energy efficiency issues based on the framework of total factor efficiency. Our results indicate that China's paper industry has a large energy saving potential even though its energy efficiency has improved during the period 1990–2013. The saving potential is about 65% under the meta-frontier and 44% under the group-frontier. Moreover, there are significant differences between different regions in production technology and energy efficiency. The performance of eastern China is better than other regions. But the technology gaps between the different regions are shrinking and converging over time. Finally, some policy recommendations are proposed to improve the energy efficiency of the industry. [ABSTRACT FROM AUTHOR]

In real applications of data envelopment analysis (DEA), there are cases in which undesirable outputs are produced along with desirable outputs in such a way that the total sum of the produced undesirable outputs over the production units must be fixed and constant. In this case, a trade-off between the decision-making units (DMUs) is needed to balance the production of undesirable outputs. In a rational sight, this trade-off is done in such a way that all DMUs improve their relative performances. In this paper, a single DEA-based model is proposed to model fixed and variable-sum undesirable outputs in production processes. A common equilibrium efficient frontier is constructed and after reallocating the input/output factors, all decision-making units (DMUs) prevail as efficient. A real case of 32 paper mills in China is given. The results of the analysis demonstrated that some economically developed paper mills have better performance than less developed paper mills; in particular, all efficient paper mills are the developed ones. [ABSTRACT FROM AUTHOR]

The Solow residual method, traditionally pivotal for calculating total factor productivity (TFP), is typically not applied to green TFP calculations due to its exclusion of undesired outputs. Diverging from traditional approaches and other frontier methodologies such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA), this paper integrates undesired outputs and three types of spatial spillover effects into the conventional Solow framework, thereby creating a new spatiotemporal econometric Solow residual method (STE-SRM). Utilizing this novel method, the study computes the industrial green TFPs for 280 Chinese cities from 2003 to 2019, recalculates these TFPs using DEA-SBM and Bayesian SFA for the same cities and periods, and assesses the accuracy of the STE-SRM-derived TFPs through comparative analysis. Additionally, the paper explores the statistical properties of China's urban industrial green TFPs as derived from the STE-SRM, employing Dagum's Gini coefficient and spatial convergence analyses. The findings first indicate that by incorporating undesired outputs and spatial spillover into the Solow residual method, green TFPs are computable in alignment with the traditional Solow logic, although the allocation of per capita inputs and undesired outputs hinges on selecting the optimal empirical production function. Second, China's urban industrial green TFPs, calculated using the STE-SRM with the spatial Durbin model with mixed effects as the optimal model, show that cities like Huangshan, Fangchenggang, and Sanya have notably higher TFPs, whereas Jincheng, Datong, and Taiyuan display lower TFPs. Third, comparisons of China's urban industrial green TFP calculations reveal that those derived from the STE-SRM demonstrate broader but more concentrated results, while Bayesian SFA results are narrower and less concentrated, and DEA-SBM findings sit between these extremes. Fourth, the study highlights significant spatial heterogeneity in China's urban industrial green TFPs across different regions—eastern, central, western, and northeast China—with evident sigma convergence across the urban landscape, though absolute beta convergence is significant only in a limited subset of cities and time periods. [ABSTRACT FROM AUTHOR]

A significant industrial transformation in China's tourism sector is currently taking place in response to carbon peak and carbon neutrality targets. This paper applies the data envelopment analysis (DEA) model to calculate the efficiency of the tourism industry under carbon emission constraints and further investigates its influencing factors through the Tobit regression. The results are as follows: (1) The tourism efficiency under carbon emission constraints of China from 2000 to 2019 showed a trend of first rising and then declining, and there were obvious regional differences; (2) from 2000 to 2019, the total factor productivity of tourism in China increased significantly, while the contributions of technical progress, pure technical efficiency, and scale efficiency decreased sequentially; (3) the factors of industrial structure, transportation convenience, economic development level, degree of opening to the outside world, and the level of scientific and technological development have varying degrees of influence on tourism efficiency. Based on the analysis results, this paper puts forward several policy suggestions on tourism efficiency and low-carbon development. The findings of this paper have some bearing on developing nations' efforts to boost tourism efficiency and realize high-quality industry growth within the framework of sustainable development. [ABSTRACT FROM AUTHOR]

Ensuring food security is not only vital to the adequate supply of food in the world, but also the key to the economic development and social stability of various countries. Based on the panel data of 29 provinces in China from 2016 to 2020, this paper selects the number of foodborne diseases patients and iodine deficiency disease patients as reference objects, uses stunting rate of children under 5 years old, malnutrition rate of children under 5 years old, obesity rate of children under 5 years old, and newborn visit rate to measure improving nutrition, proposes Meta Entropy Two-Stage Dynamic Direction Distance Function (DDF) Under an exogenous Data Envelopment Analysis (DEA) model to measure the efficiency of hunger eradication, food security, and improving nutrition under the influence of exogenous variable rainfall. The research results indicate that the sustainability of China's agricultural economy is insufficient, and the focus of attention should be different in different stages. In addition, the average efficiency of the three regions generally shows a decreasing level in the eastern, western, and central regions. In order to improve China's ability to guarantee food security, we must continue to strengthen the construction of agricultural infrastructure, increase policy support for green agricultural production, promote the diversification of agricultural production, and enrich people's agricultural product consumption varieties. [ABSTRACT FROM AUTHOR]

Factor price distortions and resource misallocation are important sources of productivity differences between regions. Promoting the free flow of factors of production is conducive to giving full play to the decisive role of the market in allocating resources, which is crucial to helping a country's economy develop in a high-quality and sustainable manner. This paper proposes a new approach to measuring factor market distortions and establishes the relationship between factor price distortions and a country's economic growth. This paper examines the resource misallocation and efficiency loss of 31 provinces in China from 2004 to 2020, and proposes an analytical framework for resource misallocation among regions, with which the Total Factor Productivity (TFP) and the factor price distortion of provinces in China are calculated. The calculation results indicate that the TFP of China's provinces gradually declines from the eastern coast to the western inland. The resource allocation efficiency in the eastern and central areas is higher than that in the western areas, so is the factor price, and its distortion causes nearly 6% of loss of output value in China. China's economic growth is still reliant on the increase of factor input and technological development and the improvement of resource allocation efficiency has no significant effect on growth. [ABSTRACT FROM AUTHOR]

Ecological efficiency (EE) provides much reference for formulating appropriate regional economic, social and environmental policies to promote sustainable development. Interactive subsystems of economy, society and environment within EE system have been considered in this paper. By innovatively integrating the merits of two advanced economic research methods (global super efficiency network data envelopment analysis (GSE-NDEA) and panel vector autoregression (PVAR) and updating the EE evaluation indicator system by following the new features of sustainable development in the recent China, this paper comprehensively evaluates EE by drawing evidence from 3 regions in China during the period of 2011–2020, and further reveals how the three subsystems within EE system interact to achieve EE enhancement. The findings show EE and its three subsystems’ trend, the major constrains of EE development, the regional discrepancies in EE progress, and the interactions among the subsystems of economy-society-environment within the EE system in different regions of China. The policy implications are proposed accordingly. [ABSTRACT FROM AUTHOR]

Since the "double carbon" target was proposed in 2020, emissions reduction has become the focus of the Chinese government's work. Industrial development is a crucial factor contributing to the increase in carbon emissions. Therefore, implementing carbon reduction in the industrial sector is an important part of China's goal of "double carbon." In this context, this paper uses a three‐stage data envelopment analysis model to calculate the green total factor productivity (GTFP) of 18 industry sectors in Shanxi Province. The results show that: (1) the external environment has influence on the GTFP of energy revolution reform pilot area industrial sectors, and the efficiency value of two industries is overestimated before excluding environmental factors; (2) the industry difference of GTFP is significant, among which pharmaceutical manufacturing industry has the greatest promoting effect on GTFP, and ferrous metal mining and dressing industry has the greatest inhibiting effect on GTFP; (3) there is a serious redundancy in R&D investment of energy revolution reform pilot area in China, and only six industries belong to zero redundancy. (4) To reflect the GTFP of various industrial sectors more clearly, this paper divides four industries: "Double‐high" industry, "High‐low" industry, "Low‐high" industry, and "Double‐low" industry. [ABSTRACT FROM AUTHOR]

In order to further develop and improve the management theory of public libraries, this paper studies the impact of library information on the utilization of regional environmental resources from the perspective of intelligent adaptive learning. Firstly, based on the data envelopment analysis method, this paper measures the efficiency of Public Libraries in various regions of China. Then, using Tobit model, this paper analyzes the environmental factors affecting the efficiency of public libraries from three aspects: financial allocation, per capita GDP, and per capita years of education. The results show that there is a significant correlation between per capita GDP, per capita years of education, and the efficiency of public libraries. There is a significant negative correlation between per capita GDP and public library efficiency (the coefficient is -5.73x10-6, and the probability of two-sided t-test is 0.0229); There is a significant positive correlation between the number of years of education per capita and the efficiency of Public Libraries (the coefficient is 0.0684, and the probability of two-sided t-test is 0.0169). Conclusion: This study provides a reference for the performance evaluation of provincial public libraries. [ABSTRACT FROM AUTHOR]

The paper utilizes the data envelopment analysis (DEA) method based on the OECD policy classification to evaluate the performance of the agricultural support policy at the provincial and agricultural commodity levels from the respective viewpoints of agricultural input and output. The analysis at the provincial level mainly focuses on the similarities and differences in the performance of the agricultural support policies between the primary grain-producing areas and the secondary grain-producing areas; at the agricultural commodity level, 17 representative Chinese agricultural commodities are selected and their performance compared. The results are then used to proffer suggestions for the future agricultural support policy optimization in China. The paper found that 50% of the provinces were DEA-efficient, in general, during the study period due to the low overall province-level scale efficiency. The performance values of the secondary grain-producing areas were significantly lower than those of the primary grain-producing areas due to the overall low scale and technical efficiency values. These results show that the support policies for agricultural commodities in China altogether require a further improvement, mainly due to the low technical efficiency of agricultural commodities. [ABSTRACT FROM AUTHOR]

Using basic data from China's 30 provincial regions from 2005 to 2015, the slacks-based measure of super-efficiency in data envelopment analysis (super-efficiency SBM-DEA) is used to measure industrial green economic efficiency (IGEE). Moreover, the temporal change and spatial equilibrium of IGEE are analyzed, and the panel quantile regression model (PQRM) is used to empirically analyze the impacts of the degree of agglomeration of pollution-intensive industries (PIIs) and other influencing factors on IGEE. The results reveal the following. (1) The kernel density distribution curve of China's IGEE exhibits a double-peaked distribution, and the overall peak value of the curve changes relatively greatly, exhibiting obvious spatial inequality. (2) Based on their trajectories, the centers of gravity of IGEE are all distributed in the central region. The moving speed of the centers of gravity exhibits a trend of "accelerating–decreasing–quickly accelerating." Judging from the changes of the standard deviation ellipse (SDE), the spatial distribution pattern of China's IGEE generally presents a northeast–southwest pattern, and it has exhibited the trend of shifting to a north–south pattern in recent years. (3) The agglomeration level of PIIs has a significant positive effect on the development of China's IGEE at each quantile level, and the most significant impact on China's IGEE is at the 75th quantile level. This paper empirically analyzes the impact of the agglomeration level of PIIs on IGEE to aid in the greening of industrial economic efficiency and the sustainable development of the ecological environment in China and other developing countries. [ABSTRACT FROM AUTHOR]

In recent years, the vigorous development of the wind power industry has become an important measure in the transformation of energy structure in China. However, the overall low technical efficiency of wind farms has severely hindered wind power industrial development. It is of great practical significance to evaluate the technical efficiency (TE) of wind power in China and analyze its main factors. Most of the existing literature on the assessment of the TE of wind power in China focuses only on large listed companies and applies the traditional data envelopment analysis (DEA) while ignoring its potential shortcomings for TE estimation. Based on panel data, this paper used stochastic frontier analysis (SFA) to construct an analytical model for assessing the TE and influencing factors of Chinese wind farms and compared the results with those from DEA to verify the robustness. The empirical results showed that the TE of Chinese wind farms was generally low. The age of a wind farm and its power consumption have a negative impact on its technical efficiency, while the utilization of power generation equipment has a positive impact on its technical efficiency. Enhancing the technological innovation capabilities of wind power companies, speeding up the construction of supporting infrastructure and solving structural problems of wind power supply and demand are important measures for the wind power industry to improve the overall TE and promote industrial development in China. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) has been widely applied to evaluate the performance of banks, enterprises, governments, research institutions, hospitals, and other fields as a non-parametric estimation method for evaluating the relative effectiveness of research objects. However, the composition of its effective frontier surface is based on the input-output data of existing decision units, which makes it challenging to apply the method to predict the future performance level of other decision units. In this paper, the Slack Based Measure (SBM) model in DEA method is used to measure the relative efficiency values of decision units, and then, eleven machine learning models are used to train the absolute efficient frontier to be applied to the performance prediction of new decisions units. To further improve the prediction effect of the models, this paper proposes a training set under the DEA classification method, starting from the training-set sample selection and input feature indicators. In this paper, regression prediction of test set performance based on the training set under different classification combinations is performed, and the prediction effects of proportional relative indicators and absolute number indicators as machine-learning input features are explored. The robustness of the effective frontier surface under the integrated model is verified. An integrated models of DEA and machine learning with better prediction effects is proposed, taking China's regional carbon-dioxide emission (carbon emission) performance prediction as an example. The novelty of this work is mainly as follows: firstly, the integrated model can achieve performance prediction by constructing an effective frontier surface, and the empirical results show that this is a feasible methodological technique. Secondly, two schemes to improve the prediction effectiveness of integrated models are discussed in terms of training set partitioning and feature selection, and the effectiveness of the schemes is demonstrated by using carbon-emission performance prediction as an example. This study has some application value and is a complement to the existing literature. [ABSTRACT FROM AUTHOR]

The Chinese government clearly put forward a strategy to speed up the development of the digital economy in "the 14th Five-Year" Plan, which will become the booster of China's development. China has a vast territory and the state of development of the digital economy varies greatly across different regions. It is crucial to clarify the reasons for these differences and take measures to narrow them. Therefore, the evaluation and analysis of the current situation are conducive to the further development of the digital economy. Taking 30 provinces (excluding Tibet, Hong Kong, Macao and Taiwan) of China as the research objects, this paper constructs an index system taking digital infrastructure, digital technology and digital talent as input variables and taking digital industrialization and industrial digitization as output variables. The data envelopment analysis (DEA) cross-efficiency model is constructed to calculate and compare the cross-efficiency of the digital economies in each province. The results show the following: (1) The development efficiency of China's digital economy has generally been low, and there is a large "digital divide" between provinces. (2) The input of digital talents is crucial for the digital economy in order to achieve high output and high efficiency, and high output is often accompanied by high efficiency. Based on the above conclusions, this paper puts forward some suggestions to promote the development of China's digital economy. [ABSTRACT FROM AUTHOR]

Purpose: The banking industry plays a key role in China's financial industry. In the past decade, the speed of the development of China's commercial banks has gradually declined. Commercial banks with different ownership structures also have certain differences in terms of operating efficiency, and their monetary policies are often different. Therefore, the authors study the impact of ownership structure on the efficiency of commercial banks under different monetary policies. This study also provides relevant reference opinions with regard to the healthy, sustainable and stable development of China's banking industry. Design/methodology/approach: This paper mainly uses the two-stage data envelope analysis (DEA) model under meta-frontier and group frontier to study the deposit and loan efficiency changes of 16 banks from 2007 to 2014 under ownership structure heterogeneity. Furthermore, the model introduces the balance parameters between deposits and loans, in order to realize the mathematical abstraction description of macro-monetary policy. Findings: First, based on bank efficiency analysis, the paper finds that most banks' loan efficiency is higher than their deposits. Second, the paper concludes that different monetary policies have little effect on bank deposit and loan efficiency, while ownership heterogeneity has a significant impact on bank performance. Finally, through the decomposition of the sources of inefficiency in bank performance, this paper finds that management and technology are two factors that affect the inefficiency of banks. Originality/value: The authors work contributes to the existing literature in the following ways: First, to the best of the authors' knowledge, this is the first attempt to use the DEA model to study the relationship between monetary policies and bank supply chain efficiency. The results may provide additional managerial implications for the banking industry from the perspective of monetary policies. The result is helpful in terms of explaining how and why banks should strengthen risk management, as well as how to deal with non-performing loans in management terms and finally, why banks should make financial technology innovations in technology terms. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the scientific productivity of China's science system. This paper employs the Malmquist productivity index (MPI) based on Data Envelopment Analysis (DEA). The results reveal that the overall efficiency of Chinese universities increased significantly from 2009 to 2016, which is mainly driven by technological progress. From the perspective of the functions of higher education, research and transfer activities perform better than the teaching activities. As an implication, the indicator selection mechanism, investigation period and the MPI model can be further extended in the future research. The results indicate that Chinese education administrative departments should take actions to guide and promote the teaching activities and formulate reasonable resource allocation regulations to reach the balanced development in Chinese universities. This paper selects 58 Chinese universities and conducts a quantified measurement during the period 2009–2016. Three main functional activities of universities (i.e. teaching, researching, and application) are innovatively categorized into different schemes, and we calculate their performance, respectively. [ABSTRACT FROM AUTHOR]

In order to analyze the international competitiveness of China-made mobile phones, this paper combines data mining algorithms to analyze the international competitiveness of China's mobile phone industry, improve the international market share of China-made mobile phones, and study the concept of multiattribute problems and related research methods. Moreover, the paper carries out the model description of the selected research methods combining principal component analysis, data envelopment analysis, and sorting method approaching the ideal solution. In addition, this paper expounds on the principles and models of PCA, DEA, and TOPSIS and selects an intelligent algorithm suitable for this model. Finally, this paper verifies the validity of the model proposed in this paper, conducts statistical analysis through the data mining model, evaluates the data mining effect through multiple simulation exercises, and verifies the validity of the system model. [ABSTRACT FROM AUTHOR]

This paper adopts the super-efficient DEA (data envelopment analysis) model to measure the forestry eco-efficiency (FECO) of 30 Chinese provinces and cities from 2008 to 2021, and then introduces the Tobit model to explore the influencing factors of FECO to better understand the sustainable development level of forestry. It draws the following conclusions: (1) The average value of FECO in China is 0.504, which is still at a low level, and the FECO of each region has significant regional heterogeneity; the provinces with higher FECO are mainly concentrated in the eastern region, while the FECO of the central and western regions is lower; (2) In terms of the main factors affecting FECO in China, the regression coefficients of market-based environmental regulations are significantly positive in the national, eastern and central regions, while they are significantly negative in the western region. The coefficient of impact of scientific research funding investment on forestry industry eco-efficiency is negative and shows a significant promotion effect in the eastern region, but the elasticity coefficient in the central and western regions is negative but not significant. Economic development has a positive but insignificant effect on FECO, with the eastern region showing a positive correlation, while the central and western regions are insignificant. Industrial structure has a significant negative effect on FECO in the national, eastern and central regions, but the effect of industrial structure on FECO in the western region is not significant. The effect of foreign direct investment on FECO was negative for the national, central and western regions, but the central region did not pass the significance test, while the eastern region reflected a significant promotion effect. [ABSTRACT FROM AUTHOR]

To promote the integration of the information industry, chain is of great significance for enterprises to improve quality, efficiency cost reduction and high-quality industry development. In this paper, based on the data envelopment analysis method, the efficiency measurement models of series structure, parallel structure and hybrid structure industrial chain are constructed under two different scenarios of central decision-making mechanism and decentralized decision-making mechanism. By quantifying the input and output resources that is in each link of the information industry chain integration process, measuring the input and output efficiency under different industrial chain integration structure; comparing and analyzing the integration efficiency of different regions, different links, discussing the cause of the differences in the integration efficiency of industry chain; thus, providing policy recommendations for the efficiency of industrial chain integration. In addition, taking the actual situation of two industrial parks with the main characteristics of carbon emission in a city of China as an example, the paper analyzes the difference of the integration efficiency of the information industry chain between the two parks. The empirical analysis shows that the information industry chain integration efficiency measurement model based on data envelope analysis theory is feasible and effective. It can not only measure the industry chain efficiency as a whole but also compare and analyze the integration efficiency of enterprises in different links of the industry chain. [ABSTRACT FROM AUTHOR]

The digital economy has deeply integrated into various sectors, becoming a significant driving force for economic transformation and development, as new generation information technology continues to advance and mature. This paper builds upon theoretical analysis and employs the global Data Envelopment Analysis (DEA) method, along with relevant data from China's information transmission, software and information services industry spanning the years 2003 to 2020, to dynamically measure the output efficiency of China's digital economy. Based on this, the paper examines the overall characteristics of efficiency changes in the digital economy using distribution dynamics. Additionally, common descriptive statistics and data mapping techniques are utilized to reveal the spatiotemporal patterns of efficiency changes. The findings of the study are as follows: (1) The efficiency of the digital economy in the 31 provincial regions of China remains stable, but the factors influencing this efficiency vary both over time and among specific provinces. (2) From a temporal perspective, the digital economy in China demonstrates an overall positive increase in efficiency, with its volatility and differentiation largely shaped by the shifting factors of technological advancements and technological efficiency. (3) From a spatial perspective, there exists a distinct pattern of spatial disparities in China's digital economy efficiency, with higher efficiency observed in the eastern regions and lower efficiency in the western regions. [ABSTRACT FROM AUTHOR]

In order to explore the statistical measurement and influencing factors of green total factor productivity in tourism, this paper proposes the use of gray absolute correlation to measure the similarity between input variable sequences. Moreover, this paper obtains the key parameters of the combination of radial and nonradial in the model based on the proximity index of gray correlation and calculates the economic efficiency of the decision-making unit according to the steps. In addition, this paper combines the DEA-EBM model to carry out the statistical measurement of China's tourism industry green total factor productivity and the analysis of influencing factors and verify it through data. Through research, it can be seen that the DEA-EBM model proposed in this paper can play an important role in the statistical measurement and analysis of influencing factors of green total factor production in the tourism industry. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper uses the data of fixed observation points in the country's rural areas, the Data Envelopment Analysis model is used to calculate the production efficiency of pig farmers, which shows the efficiency level of pig breeding in the country. Then, the Tobit model is used to analyze that epidemic prevention and control has a positive effect on production efficiency. Finally, the threshold regression model was used to analyze the results: the effect of disease control on production efficiency was different under different breeding scales. When the breeding scale was less than 6.0002, the disease control had a negative impact on the production efficiency. When the breeding scale was greater than 12.9994, the disease control had a positive impact on the production efficiency. The research results of this paper not only help farmers to correctly understand the relationship between epidemic prevention and production efficiency, guide farmers to expand their breeding scale, and actively participate in epidemic prevention and control, but also provide a reference for the government to formulate policies according to different scales to guide farmers to carry out epidemic prevention and control. Epidemic disease prevention plays a critical role in ensuring the healthy development of livestock farming, and the subjective willingness of breeders can be affected by the cost of epidemic disease prevention. To correct the misconception that farmers regard the cost of disease control as an ineffective cost, and to promote the healthy development of the pig breeding industry, our study employed the data envelopment analysis super-efficiency model and panel threshold regression model to evaluate the combination of the cost of epidemic disease prevention and swine productivity using data collected from 1998–2018 across 30 provinces in China. The following results were obtained. (1) The cost of epidemic disease prevention generated a non-linear on swine productivity when the swine farming scale was limited; (2) When the number of animals at the beginning of the year was less than 6.0002, swine productivity was impacted negatively; (3) When the number of animals at the beginning of the year ranged between 6.0002 and 12.9994, the impact was insignificant; (4) A strong correlation was observed between the expenses of epidemic disease prevention and animal productivity when the number of animals at the beginning of the year exceeded 12.9994. These results indicate that publicity should be enhanced to elucidate the combination of epidemic disease prevention and swine productivity among breeders. In addition, the government should introduce relevant policies to encourage the development of large-scale pig farming, such as subsidies for the construction of large-scale farms and insurance. [ABSTRACT FROM AUTHOR]

In this paper, the data envelopment analysis (DEA) approach is put forward to deal with the spatial efficiency evaluation issue for the outdoor environment in high-rise residential (HRR) areas in China. The principles of quantifiable and objectivity are utilized to empirically research for the area of 10 high-rise residential houses. For the outdoor environment in HRR areas, our aim is to take appropriate optimization suggestions that not only satisfy the different conditions of the outdoor environment but also improve the efficiency of site space. By resorting to the data envelopment analysis technique, some practical methods are acquired for evaluating the outdoor environment for HRR areas. [ABSTRACT FROM AUTHOR]

This paper uses the data envelopment analysis (DEA) method to evaluate the total factor productivity of China's listed ocean shipping enterprises in 2016-2018. The results show that in recent years, the total factor productivity of these enterprises is in a good level in the transportation industry; the main reasons for the inefficiency of the ocean shipping enterprises are low technical inefficiency and management efficiency, and the technical and management level should be enhanced. In addition, China's ocean shipping enterprises should further control their investment and strengthen cost management. Finally, this paper proposes the reform direction of state-owned enterprises such as increasing R&D investment, improving corporate governance, reforming the assessment system, and performing market-oriented reforms. [ABSTRACT FROM AUTHOR]

China is currently the world's largest producer and consumer of iron and steel. This industry is one of the most energy- and emission-intensive industries in China. It is unsuspicious that energy conservation and emission reduction in this industry are crucial for China to fulfill its obligations of reducing greenhouse gas emission and mitigating global climate change. An appropriate allocation of CO2 emissions permit is the most important precondition for establishing an efficient and effective emissions trading system that had recently been launched in China's pilot regions. This paper proposes a new emissions permit allocation method based on a Nash equilibrium data envelopment analysis model. This method is more appropriate in emissions permit allocation for China's iron and steel firms in an imperfectly competitive market where the product price is endogenous. A noncooperative game is formulated and the mixed complementarity problem is utilized to identify a Nash equilibrium in the allocation of emissions permit (AEP). The most up-to-date AEP using a unique data set of China's major iron and steel enterprises in 2014 is provided in this paper. The results show that the AEP improves the desirable output generation by satisfying the reduction targets of the undesirable outputs. [ABSTRACT FROM AUTHOR]

In order to make a complete ranking of intertemporal environmental efficiency in a dynamic manner, this paper combines the network-based dynamic data envelopment analysis (DEA), super-efficiency with the unified efficiency under natural and managerial disposability, and designs a dynamic DEA model and the corresponding dynamic super-efficiency DEA model. Compared with previous studies, the proposed measure can fully rank the overall environmental efficiency of all decision making units (DMUs) in a dynamic manner, and more importantly, it provides the information about when and what factors lead to inefficiency or efficiency of DMUs. The proposed models are applied to examine the environmental efficiency of 30 provinces in China from 2008 to 2017. The results show that there are significant regional differences of environmental efficiency in China. In addition, slack analysis shows that most eastern efficient provinces have no obvious advantages in energy consumption, labor and waste water emission; most central and western efficient provinces have no advantages in sulfur dioxide (SO2) emissions and GDP. To improve overall efficiency, eastern inefficient provinces should mainly focus on reducing energy consumption, SO2 emissions and labor, and increasing capital investment in right years, central and western inefficient provinces can focus on reducing SO2 emissions and labor in most years, most of provinces need to increase gross domestic capital formation. [ABSTRACT FROM AUTHOR]

Global climate change caused by greenhouse gas emissions has a direct impact on the sustainable development of human society and has gained widespread concern globally. Biological carbon sequestration measures, mainly forests, are conducive to improving the ecological carbon sink capacity and play an important role in mitigating global climate change. Therefore, assessing the efficiency of forest carbon storage (FCS) is key. In view of the lack of evaluation methods for forest carbon storage efficiency (FCSE) on a large spatial scale and long time series, a method based on Data Envelopment Analysis (DEA) was proposed in this paper. The FCS was calculated using the forest storage expansion method, and the FCSE was calculated using the DEA-Malmquist index to solve the dynamic balance between regional forestry economic input and carbon storage output efficiency. The FCSE in Chinese provinces was analyzed. The results showed that from 1999 to 2018, China's FCS increased annually, from 7558.34 million tons to 9476.73 million tons, and the spatial distribution pattern of total FCS was always different among regions. The average TFP value of FCSE was 1.089, which proves that the FCSE in China has been on the rise in the past 20 years, but the efficiency growth differed between provinces and was affected by different factors such as technical efficiency and technological progress. [ABSTRACT FROM AUTHOR]

As an important embodiment of a country's economic strength and national health, pharmaceutical manufacturing industry has made rapid development in China in recent years. But at the same time, the pharmaceutical manufacturing industry is facing many environmental problems, such as large pollution emissions, complex pollution components, controlling difficulties and so on. This paper measures the total factor productivity of pharmaceutical manufacturing industry (HTFP) by using data envelopment analysis with unexpected output, which is more accurate and effective than the traditional model. It also studies the effect of environmental regulation on the total factor productivity of pharmaceutical manufacturing industry (HTFP) by establishing panel data regression model and spatial econometric model based on 30 provinces in China from 2004 to 2019, which enriches the research results in the field of cleaning in pharmaceutical manufacturing industry. The conclusions are as follows: (1) Environmental regulation and total factor productivity of pharmaceutical manufacturing industry have significant spatial autocorrelation, showing "high-high" or "low-low" spatial aggregation characteristics; (2) Environmental regulation has a significant promoting effect on improving pharmaceutical manufacturing total factor productivity in local and surrounding areas, and there are differences in the impact of eastern, central and western regions; (3) Green technology, production technology and industrial structure play an important role in the impact of environmental regulation on pharmaceutical manufacturing total factor productivity, which provides theoretical guidance and policy recommendations for improving the level of total factor productivity of pharmaceutical manufacturing industry in the environmental aspect. [ABSTRACT FROM AUTHOR]

As China's strategic support belt, the green development of industry in the Yangtze River Economic Zone is of great significance to promote the construction of China's ecological civilization, build a modern industrial system and accelerate high-quality economic development. The study of green total factor productivity of industry in the Yangtze River Economic Zone has important theoretical and practical value for exploring the green development path of China's industry. This Paper takes the Yangtze River Economic Zone, a key strategic region in China, as the research object, selects the input and output data of industrial production from 2006 to 2018, based on DEA model. To construct an MML index considering expected and unexpected output, and to quantitatively analyze the changes of industrial GTFP in the Yangtze River Economic Zone. The results show that: (1) During the sample period, the industrial green total factor productivity in the Yangtze River Economic Zone shows the spatial characteristics of differential growth and the temporal characteristics of volatile growth. It shows the fluctuation characteristics of "N" shape. (2) According to the order of "upper, middle, and lower" reaches, the spatial pattern of industrial green total factor productivity is characterized by "lower ladder". But the difference between the upper and middle reaches is small. (3) Cities with higher green total factor productivity and lower green total factor productivity each form the characteristics of "club convergence" of spatial agglomeration. (4) Technological efficiency and technological progress efficiency have heterogeneous effects on different river basins in the upper, middle, and lower reaches, and technological progress efficiency is conducive to promoting the evolution of green total factor productivity to a high level. According to the above empirical results, this paper finally puts forward the policy recommendations to improve the industrial green total factor productivity of the Yangtze River Economic Zone and the policy recommendations to reduce the industrial differences between the Yangtze River Economic Zone. [ABSTRACT FROM AUTHOR]

China is striving to build a new dual-circulation development pattern with the aim of leading the coupling of science, technology, and innovation through the active role of financial factors, ultimately promoting the country's optimal economic development. As a result, this paper constructs a coupled dual-circulation-STI (scientific and technological innovation) relationship model. The domestic and foreign components of the input–output relationship are used to portray the extent of the dual circulation, combined with Index DEA to measure the quality of science and technology innovation under the role of financial factors and the coupled coordination model to analyze the intrinsic correlation between the two. The study used an Index-DEA and value chain analysis model to measure each industry's technological effectiveness and the degree of internal and external circulation, respectively. The coupled coordination model approach was used to measure the coordination relationship between the double-loop model and technological innovation. Based on the coordination assessment table, the degree of coupling and the natural state of science and technology innovation and dual cycle in each industry were assessed. The study found that the country's dual-circulation pattern gradually strengthened from 2015–2019, with the financial element also driving an increase in STI. However, due to the twists and turns of the external environment, the coupling power of the dual-circulation STI weakened in some years. On this basis, the paper concludes that the quality of STI, driven by financial factors, has been increasing year on year, and the coupling with dual circulation has been trending upwards. Regarding policy implications, developing countries such as China should continue to invest more financially to create a healthy and sustainable innovation model. Through the innovation-dual-circulation development model, the country should eliminate the sloppy development model in construction and use the power of science and technology to lead social progress. [ABSTRACT FROM AUTHOR]

Data envelopment analyses have been widely used to evaluate the relative efficiency of decision‐making units (DMUs). However, the traditional data envelopment analysis model has not considered the problem of DMUs' nonhomogeneity. If nonhomogeneous DMUs are evaluated under the same production frontier, conclusions may not be precise. For example, some DMUs' input redundancy and output deficit cannot be adjusted as per planning results, which may lead to mistakes in management. This paper loosens the assumption of DMU homogeneity and builds a global system‐ranking efficiency model based on existing literature, which divides the problem of DMUs' nonhomogeneity into external nonhomogeneity and internal homogeneity. Data have been collected from 114 listed enterprises in China's solar power industry, and the analysis results indicate that this paper's model is stable and reliable and can be used as a reference for production managers. [ABSTRACT FROM AUTHOR]

In recent years, Chinese economic development has slowed down and competition in the financial industry has become increasingly fierce. The purpose of this paper is to study the efficiency characteristics of China's banking industry in the new environment and provide suggestions for banks to improve efficiency. This paper uses a data envelopment analysis (DEA) SBM-undesirable model and window analysis to measure the technical efficiency of 13 nationwide commercial banks in China during the period from 2008 to 2017. Furthermore, the convergence characteristics of bank technical efficiency are examined. The empirical results show that state-owned banks were more efficient than joint stock banks before 2012. After 2012, state-owned banks were less efficient than joint stock banks. Finally, this paper explores the influential factors of technical efficiency. Noninterest income ratio, net interest margin, growth rate of total investment in fixed assets, and consumer price index have a significant positive impact on bank efficiency. The cost-to-income ratio has a significant negative impact on bank efficiency. Further research using the threshold model shows that noninterest income ratio has a threshold effect on bank efficiency. [ABSTRACT FROM AUTHOR]

As the forerunner and policy test field of the sustainable development, the sustainable development pilot zones are an important strategy for China to explore the mechanism and model of the coordinated development of human and land in different regional units. However, the impact of sustainable development pilot zones, especially on the improvement of environmental efficiency, needs to be assessed. In this paper, 187 prefecture-level cities in China were taken as samples (22 sustainable development pilot zones and 165 nonpilot ones). Firstly, the environmental efficiency of 187 prefecture-level cities between 2006 and 2016 was measured by data envelopment analysis (DEA). Then, the effect of construction of sustainable development pilot zones on environmental efficiency was assessed using the difference-in-difference (DID) model. The assessment results were further verified by propensity score matching with difference-in-difference (PSM-DID). In addition, the impact mechanism of construction of the sustainable development pilot zones on the environmental efficiency was discussed. Results show that the environmental efficiency of sustainable development pilot zones is 27.7∼31.7% greater than that of nonsustainable one, which is mainly attributed to the environmental regulation and industrial structure adjustment. [ABSTRACT FROM AUTHOR]

At this stage, China's logistics industry is developing rapidly and has become one of the important areas of China's economic development. However, there are few techniques for measuring the efficiency of logistics supply chain systems. In order to be able to effectively analyze the efficiency measurement of the urban and rural logistics supply chain system and obtain higher accuracy, using a method derived from analysis of data envelopes, this essay examines the impact elements by establishing a data envelopment analysis model, using compound DEA analysis method and linear regression analysis method. The composite DEA analysis shows that all indicators in the indicator system are positively correlated, and the amount of people working in the field of distribution has the greatest impact on logistics efficiency. The annual average of pure technical efficiency is 0.932, and the annual average of scale efficiency is 0.910. In the eastern region, it is a lower-middle level. The empirical results of changes in the efficiency of the urban and rural logistics industry show that there is a significant positive correlation. This paper also builds a fuzzy algorithm optimization model and designs an overall fuzzy algorithm to solve the LRPPD problem. The simulation results show that the algorithm has good optimization performance, high computational efficiency, and strong convergence speed. [ABSTRACT FROM AUTHOR]

In 2018, the Chinese government proposed the Rural Revitalization Strategy with the objective of bolstering economic development, social progress, and ecological protection in rural areas, thereby achieving rural modernization. This paper employs the Data Envelopment Analysis (DEA) method and the Malmquist index model to measure the efficiency and changes of the agricultural circular economy in 31 provinces and cities in China from 2017 to 2020. Using Tobit regression, we further examine the correlation analysis in the context of the rural revitalization policy. The study reveals that the efficiency of China's agricultural circular economy continued to grow between 2017 and 2020. The policy of the rural revitalization strategy significantly impacts the efficiency of the agricultural circular economy. Government financial support has a significant positive influence on the efficiency of the agricultural circular economy. Based on the research findings, we proposed several constructive suggestions. [ABSTRACT FROM AUTHOR]

With the increasingly urgent demand for innovative talents, college students should have strong collaborative innovation ability because they are the backbone of future sci-tech innovation in China. Existing methods can be used to measure and evaluate to some extent the collaborative innovation and achievement transformation efficiency of college students. However, many of the methods focus on data of a certain period and neglect dynamic analysis. Dynamic comparisons of different periods need to be made because innovation activities and achievement transformation may be influenced by time factors in practical situations. In addition, some methods only focus on the quantity index of achievement transformation, and neglect quality evaluation. Therefore, this paper aimed to study the collaborative innovation ability cultivation of college students by improving the achievement transformation efficiency. Three-stage data envelopment analysis (DEA)-Windows model was used to calculate the collaborative innovation and achievement transformation efficiency of college students. This paper elaborated in detail the calculation process of these three stages, namely, the first-stage DEA-Windows analysis, the second-stage panel stochastic frontier analysis (SFA), and the third-stage adjusted DEA-Windows analysis. Based on the research needs of collaborative innovation ability cultivation of college students by improving the achievement transformation efficiency, this paper constructed an evaluation index system using Fare-Primont index model and Pastor method, and focused on the sci-tech innovation achievement transformation factors, such as output results and ability improvement. Finally, this paper showed the analysis results by combining with examples, which verified the proposed method was effective. [ABSTRACT FROM AUTHOR]

Total factor productivity (TFP) growth measures usually focus on a certain direction of optimization and ignore the general setting encompassing the input and output orientations simultaneously. This paper uses the generalized Luenberger-Hicks-Moorsteen (LHM) TFP indicator which is additively complete and can be decomposed by three mutually exclusive elements. The input- and output-oriented analysis is undertaken in order to derive the generalized TFP measured. The paper uses the corn production data from 19 Chinese provinces over the period of 2004–2017. This research is important as China is the second largest corn producer in the world. The TFP growth was observed for Chinese corn farming the rate of 0.56% per year. The technological progress (0.48%) was the major source of the TFP growth, whereas the importance of the technical efficiency change (0.09%) and scale efficiency change (–0.01%) was negligible. [ABSTRACT FROM AUTHOR]

As the main factor of China's higher education, effective evaluation of the scientific research efficiency of domestic universities is extremely significant to improve the scientific research management system of local universities, optimize the allocation of scientific research resources, and promote regional economic development. Based on the ten-year statistical data of the compilation of science and technology statistics of colleges and universities, this paper adopts the data envelopment analysis (DEA) model to study the scientific research efficiency of 31 provincial universities in Shandong Province from three dimensions: level, type, and region. The results show that, first, the overall scientific research efficiency of the sample universities is not high and takes on a downward trend; there are some differences, changes in the same direction, and level convergence in each dimension of scientific research efficiency. Second, there is a positive correlation between the comprehensive scientific research strength of the sample universities and the technical efficiency. Third, the level of regional economic development has a positive impact on the scale efficiency of scientific research, which is closely related to the technical efficiency, and there is no positive correlation between these two. Thus, the research suggests that, in the future, colleges and universities should formulate differentiated management policies, build a "Government University" two-level scientific research performance evaluation system guided by scientific research quality, change the concept of scientific research managers, and improve the ability of personnel to improve the efficiency of scientific research in colleges and universities. [ABSTRACT FROM AUTHOR]

In the arid zone of northwest China, the Heihe River Basin (HRB), as a typical inland river basin, has a fragile regional ecological environment, obvious ecological degradation characteristics, and extremely serious problems in the utilization of agricultural land resources. Meanwhile, the shortage of water resources, the low reduction of land quality, and excessive agricultural activities have greatly increased the local water and land pressure. In this paper, firstly, using the Malmquist DEA model and coupling coordination degree model, the agroecological risk assessment system on account of the coupling of water and land resources (WLR) is constructed. Secondly, taking HRB from 1995 to 2020 as an example, we carry out spatial correlation analysis based on the degree of risk-correlated WLR. Thirdly, we analyze the evolution process and spatial correlation of ecological risk of agricultural WLR in the HRB at the county scale, then we conclude and put forward policy suggestions for improvement. The results show that: (1) On the whole, the average ecological risk of agricultural water resources in the HRB from 1995 to 2020 was 0.933, indicating that the risk was declining; the average ecological risk of agricultural land resources in the HRB from 1995 to 2020 was 0.938, indicating that the risk was declining also. (2) The degree of ecological risk coupling and coordination of agricultural soil and water resources upstream of the HRB is on the rise, while that in the middle and lower reaches is on the decline. (3) Through panel model analysis, the matching suitability of WLR drives agroecological risk. The correlation between them is positive. In conclusion, this method can effectively evaluate the agroecological risk of WLR and provide technical support for agricultural production and management in arid areas. [ABSTRACT FROM AUTHOR]

The high-quality development of national high-tech zones is a matter of great concern for both the government and scholars as it serves as an important base for realizing scientific and technological innovation and industrialization of achievements. This paper constructs a conceptual model of the national high-tech zone innovation system by breaking it down into two subsystems: the innovation R&D subsystem and the innovation incubation subsystem. Through the use of a two-phase Data Envelopment Analysis (DEA) model, the innovation efficiency of each subsystem is measured for the 42 national high-tech zones in Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta urban agglomerations. The research conclusion indicates that the majority of the high-tech zones in China are high in both research and development (R&D) efficiency and achievement conversion rate, indicating generally high overall innovation efficiency. However, there is a gap between the three urban agglomerations in terms of innovation resources and transformation environment, with Beijing-Tianjin-Hebei High-tech Zone having low transformation efficiency, and some areas of Yangtze River Delta and Pearl River Delta having low efficiency in technology R&D. Furthermore, the study finds that the innovation modes and paths of high-tech zones within urban agglomerations are quite different in the process of coordinated development of innovation. Therefore, the paper proposes two innovative development paths: the endogenous growth path and the exogenous driving path. The research results provide a tool for more objective evaluation of the innovation efficiency of national high-tech zones in different urban agglomerations in China, and provide a decision-making basis for different regions to implement corresponding innovative development paths. [ABSTRACT FROM AUTHOR]

The trend of market-oriented land transaction scheme and the optimal allocation of land resources have become two important components of ecological sustainable development. However, the relevance of analyzing effects of land marketization on ecological and environmental development cannot be overemphasized. The ecological and environmental effects of land marketization are the focus of this paper. We begin by developing a theoretical framework to investigate how land marketization affects eco-efficiency. Moreover, we develop a data envelopment analysis model to measure eco-efficiency. We empirically investigate the effect of land marketization on eco-efficiency using a data set of 251 cities in China over the period of 2003 to 2018. Both theoretical and empirical results show that the land marketization exerts positive effects on eco-efficiency. Specifically, a 100% increase in land marketization level leads to a 2.4 percent increase in eco-efficiency. The heterogeneous effects and spatial effects of the land marketization on eco-efficiency are also examined. Besides, the endogeneity issues are also discussed using instrumental variable approach. Finally, the mechanism analysis shows that land marketization improves eco-efficiency primarily through improving efficiency change, best practice change and technology gap change, respectively. The main conclusions are confirmed by several robustness checks. [ABSTRACT FROM AUTHOR]

Technical efficiency (TE) and total factor productivity (TFP) are important criteria to ensure the enhancement of the quality and efficiency of state-owned enterprises (SOEs) and function as important indicators to assess the quality of their accomplishments. The purpose of this study is to explore whether the efficiency of SOEs is higher or lower than that of private enterprises. Transcendental logarithmic production function and stochastic frontier analysis (SFA) are used to assess the TE and TFP of listed central SOEs, local SOEs, and private enterprises, the data of which were taken from 2006–2020. The results show that the sampled private enterprises had the highest average TE during the study period, followed by the central and local SOEs. The private enterprises also had the highest average TFP growth rate, followed by the local and central SOEs. The TFP decompositions show that the TE change (TEC) and technical change (TC) indices of the SOEs were lower than those of the private enterprises. The TC, TEC, and scale change (SC) are limiting the TFP growth rates of the SOEs in labor-intensive industries. The SC of the SOEs has changed less than that of private enterprises in the sampled capital-intensive industries. Northern and southern China had the highest rates of TE and TFP growth. Indeed, this paper measures and decomposes TFP, and analyzes the efficiency of SOEs and private enterprises in different industries and regions in an international context. [ABSTRACT FROM AUTHOR]

The rapid development of renewable energy enterprises has produced important benefits for contemporary efforts to address serious environmental pollution and depletion of fossil energy resources. However, the environmental pollution that exists in the production and operation of enterprises has been ignored, and so an objective evaluation of this issue is becoming urgent. This paper established an evaluation index system for green technology innovation efficiency and used dynamic data envelopment analysis (DEA) considering undesirable output to measure the green technology innovation efficiency of renewable energy enterprises, and the improvement potential of ineffective enterprises was put forward. The results show that: (1) the green technology innovation of renewable energy enterprises needs to be greatly improved. The average efficiency score of sample was 0.385 over four years, and only 16 enterprises were found to operate effectively; (2) when effective and inefficient DMUs were compared, the latter were found to have significant output shortfalls, especially in environmental tax, and were found to show an improvement potential of 55.71 percent; (3) the efficiency analysis of different types of renewable energy enterprises found that the green technology innovation efficiency score of nuclear energy enterprises was the highest, and rapidly rose; (4) the green technology innovation efficiency of renewable energy enterprises in the western region greatly exceeded the efficiency of the eastern and central regions. The efficiency evaluation results could not only provide a guidance for central and local governances to optimize the structure of renewable energy sector, but also potentially provide a reference for the operation and management of renewable energy enterprises in China. [ABSTRACT FROM AUTHOR]

Background and Purpose: In the early 21st century, the coronavirus alone has ravaged the world three times. Public health emergencies have caused a tremendous negative impact on public health, daily life, and global economic development, for having the characteristics of complexity and great harm. To tackle these problems, a pre-generation of emergency reference plan model of public health emergencies is proposed to better deal with the outbreak and spread of public health events. Methods: The method is divided into three stages. First, the modified SEIR model is used to predict the attribute values of the target case. Then, the similar case sets are extracted and filtered by calculating the similarity through the cross-efficiency evaluation method with the parallel system. Finally, the multi-stage emergency effect evaluation model is conducted so that the emergency plan with the best response effect at this stage can be made for reference. Results: We collected 25 typical events of COVID-19 that occurred in 11 cities in China as historical case bases and target cases, respectively. The result of the experiment verified the feasibility and effectiveness of the proposed method. Conclusion: This paper presents a new perspective on making a public health emergency plan, which could improve the decision-making accuracy and efficiency, maximize the emergency effect and save precious time for emergency response. This model can provide rapid decision supports for decision-making for public services such as government departments, centers for disease control, medical emergency centers and transport authorities, etc. [ABSTRACT FROM AUTHOR]

Green buildings are an important carrier for the transformation of the construction industry to green, efficient and energy-saving, and an important part of the national sustainable development strategy. At present, the development of green building in China is still in the primary stage, the willingness of construction enterprises to develop green building is low, and the promotion of green building is facing the problem of insufficient power. The main reason is that the incremental cost of green building is too high. Therefore, this paper takes green building as the research object, and studies the quantification and evaluation of its incremental cost-benefit. Firstly, the incremental cost composition of green buildings is analysed from the perspective of the whole life cycle, and the incremental benefits are divided into economic benefits, environmental benefits and social benefits. Secondly, the green building incremental cost-benefit evaluation model is constructed by combining the entropy weight method and the data envelopment analysis (DEA) method. Finally, the feasibility of this evaluation method is verified through the analysis of practical engineering cases. By evaluating the input-output benefits of incremental costs, the projects with DEA effectiveness and DEA ineffectiveness are identified, and specific suggestions are put forward for them respectively. The research results not only provide theoretical support for the quantification and evaluation of incremental costs and benefits of green buildings, but also provide a reference for the formulation of corresponding cost control measures, and lay a foundation for the realization of the cost minimization and benefit maximization of green buildings. [ABSTRACT FROM AUTHOR]

Chinese sea perch (Lateolabrax Maculatus) is one of the main marine fish culture species in China, its green development has received increasing attention and its ecological economic study is rare. Based on field survey, this paper takes water pollution tax of China as conversion indicator for aquaculture eutrophication to simulate aquaculture waste fee for further analyzing the ecological impact of Chinese sea perch's aquaculture. For data analysis, data envelopment analysis model has been used. The comparison for Chinese sea perch's economic performance and ecological economic performance under its main aquaculture systems has been done. The results show that: 1. The simulated waste fee has no significant impact for the comparison. 2. Ranking for ecological economic performance' s ecological economic, technical and scale efficiency is as follow: pond farming, offshore cage culture and cage culture. 3. Offshore cage culture is the only system presenting positive increase for ecological economic performance, which makes its aquaculture activity more sustainable than other systems. 4. The key point of green development is to maximize the ecological economic efficiency of main aquaculture systems. Thus, offshore cage culture is the most sustainable aquaculture system among China's current marine fish culture systems, and other systems need innovation for achieving the green development of China' s aquaculture. [ABSTRACT FROM AUTHOR]

Considering that the real estate industry is a critical industry to promote the economy in China, it is necessary to measure the real estate performance. However, few studies about the performance evaluation of China's real estate industry have focused on the production process. To fill this gap, this paper proposes a two-stage framework to investigate the real estate productivity of 30 sample provinces on mainland China from 2008 to 2015, based on a common-weight global Malmquist productivity index (MPI). The major findings are shown as follows: (a) the real estate efficiency is low, and it is mainly caused by the inefficiency in the sales stage, not the development stage; (b) the development trend of the real estate sector in China is sensitive to the government policies, and the fluctuations of MPI are consistent with the direction of policy adjustment during the observation period; (c) as for the regional analysis of MPI, we introduce the concept of the dependence degree of the economy on the real estate industry and predict that MPI in economically underdeveloped regions may decline in the future. Finally, policy recommendations are provided for the high-quality development of China's real estate industry. [ABSTRACT FROM AUTHOR]

The two-stage data envelopment analysis models are among the widely used mathematical programming approaches to evaluate the performance of two-stage structures. In this paper, a two-stage structure with shared inputs and feedback is studied. To reduce undesirable outputs, an additive slack-based measure model is proposed to evaluate the stages and overall efficiencies, while undesirable outputs are weakly disposable. As it does not require determining the weights for combining stages' efficiencies, all Pareto optimal stages' efficiencies can be gained. In addition, the proposed approach can identify desirable outputs from undesirable outputs, thereby avoiding the need for weighting. This advantage from the aspect of multiobjective programming helps internal evaluation of the network model to match priorities of managers. The proposed nonlinear model is reformulated as a second-order cone program, which is a convex optimization problem that can be solved to global optimality. This is a computational improvement over the parametric models in the literature. Furthermore, the proposed model is applied for country-wise and area-wise performance evaluations of a real industrial application dataset in mainland China. Results show that the efficiency of the overall system relies between the efficiencies of the two stages and for all DMUs, the first stage's efficiency scores are always higher than the second stage ones in both evaluations. Also, the Pearson correlation coefficient test results show that the overall efficiency is more correlated with the waste disposal stage. Finally, to show the effect of the decision maker's preference, a detailed sensitivity analysis is performed. [ABSTRACT FROM AUTHOR]

The conventional convexity assumptions frequently placed on piecewise linear frontiers of production technologies modeled using data envelopment analysis imply non-increasing marginal products. Assuming geometric convexity in the context of the exponential technology represents a more general alternative that imposes no underlying restrictions on the marginal products, while simultaneously reducing the impact of the outlying observations. In this paper, we propose an exponential by-production technology capable of generating the outputs deemed undesirable from the society's point of view. We subsequently rely on this technology to measure environmental productivity. Our empirical illustration uses data from the Chinese industrial sector, which is both a major energy consumer and polluter. By comparing our findings with the results from a conventional production model we demonstrate that our proposed indicator mitigates the impact of outlying observations when gauging the contributions of inputs and outputs to green growth. Our results suggest that the Chinese industrial sector experienced the annual productivity growth rate of around 0.40% during 1999–2016 and that the green productivity was mostly driven by technological progress. We also demonstrate that technological progress has been a bigger contributor to the growth in industrial output in China's east than its inland or western regions. [ABSTRACT FROM AUTHOR]

In the process of human survival and sustainable development, water security, energy security and food security have become the three most prominent issues, but they are interrelated and directly affect each other, that is, to form a Water–Energy–Food (WEF) nexus. Scientific understanding and correct response to the relationship between WEF is important to realize the sustainable development of natural resources. There are some deficiencies in the existing research on the input–output efficiency of WEF system. There are few articles that can study the efficiency relationship between internal and external factors (such as the economy and environment) of the WEF system at the same time, or the research is not perfect. In view of the shortcomings of the existing research, this paper establishes a three-dimensional network structure to describe the water–energy–food–economy (WEF-Eco) system and establishes the corresponding network Data Envelopment Analysis (DEA) model. We use the data of 19 provinces in Northeast, East, and central China to show the application results of this model. [ABSTRACT FROM AUTHOR]