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Congestion is a well-known economic phenomenon in which excessive inputs lead to a decrease in the maximum possible outputs. This study analyzes the relationship between congestion and overinvestment using a data envelopment analysis framework to reveal that some congestion can be eliminated by increasing inputs. The proposed approach classifies congestion into two categories, relative and absolute congestion, depending on the possibility of eliminating congestion by increasing inputs. Corresponding methods for identifying and measuring congestion are proposed and employed for empirical analyses examining China's papermaking and paper products industry. We find that most congestion in 2013–2016 is in the relative congestion and could be eliminated by increasing inputs. The primary causes of congestion are identified based on our analysis and corresponding policy suggestions are proposed for eliminating congestion. [ABSTRACT FROM AUTHOR]

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]

There are a great number of DEA models proposed to deal with ecological efficiency problems with undesirable outputs. However, which model should be used in a specific scenario or how about the discriminability of a given DEA model is hard to decide in practice. This paper uses the ecological Shannon DEA procedure based upon the existing study to obtain an ecological comprehensive efficiency score for each decision units. The procedure is used to appraise the ecological evaluation to 32 paper mills along the Huai River in China. The results seem reasonable since they integrate the results of existing relevant DEA models, and calculate the importance degree of each model. The procedure can also be used to determine the pollutant emission quotas for those paper mills. [ABSTRACT FROM AUTHOR]

Accurate understanding of the marginal energy-saving costs of energy-using entities is critical for regulatory authorities to formulate and implement energy-saving policies. This article brings out an easy-to-operate analytical framework to measure the marginal energy-saving cost and construct energy conservation supply curve with the help of data envelopment analysis and quantitative model. Furthermore, taking China's pulp and paper industry as an example, the authors discuss the difference of economic costs between industry energy-saving task assignment with and without considering the difference of marginal energy-saving costs of different energy using entities with the help of linear programming model. The main empirical results are as follow. First, there is a big difference in the industrial marginal energy-saving costs in different provinces. The difference between the highest and lowest energy-saving costs is twice as large. Second, the optimal energy-saving task assignment based on an accurate energy conservation supply curve can help to save nearly 35% of total economic cost. • An alternative method of measuring energy conservation cost is provided. • An optimal energy saving task assignment model is constructed. • The problem of trade-off between efficiency and equity in policy making is discussed. [ABSTRACT FROM AUTHOR]

Purpose: This study provides a bibliometric analysis of bank efficiency and competition over the past years (from 1993 to 2022) to (1) discover the past and current state of knowledge on bank competition and efficiency, (2) identify leading and authoritative journals and scholars who made significant contributions to the distribution of knowledge and impact, (3) identify nations that made a significant contribution and impact to the literature and (4) identify the structure of collaboration that exists between scholars in the areas of bank competition and efficiency and key thematic areas. Design/methodology/approach: A total number of 868 documents made up of articles, reviews, book chapters, book and conference papers from the Scopus database were gathered. This study used a bibliometric analytic approach. Findings: The number of documents on bank competitiveness and efficiency has increased significantly, as have their total publications, citations and national output. Additionally, the most esteemed and prestigious academic journals of eminent academics who have had a significant impact on the dissemination of knowledge on bank efficiency and competition literature champion papers on banking efficiency and competition. In terms of citation performance and collaborative efforts, the United States tops the developed countries, led by China, which is also the most productive. Additionally, single-country publications predominate in the literature, with China ranking first among the top five countries with corresponding authors. While the Lerner index, H-statistic, concentration index and market power were used to measure bank competitive behaviour, the data envelopment analysis approach predominates efficiency estimation techniques that are linked to cost, profit or revenue, scale, technical and productivity indexes. Originality/value: This study is one of the first to offer bibliometric evidence of both bank competition and efficiency. It also offers proof of the distribution of knowledge and intellectual structure of the concepts and concerns in bank competition and efficiency. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the urban human settlements of 21 megacities and supercities from 2011 to 2020 in China and improve urban human settlements planning and management. First, the data envelopment analysis (DEA)–Malmquist–Tobit model is used to conduct a static and dynamic evaluation of the efficiency of urban human settlements and analyze the main factors that affect it. Then, the coupling coordination degree model is utilized to quantitatively evaluate the coupling coordination degree between urban human settlements and high-quality economic development. Finally, the GM (1, 1) model is established to predict each city's average input–output index during the 14th Five-Year Plan period. It is hoped that this paper could promote sustainable urban development. The empirical results are as follows: (1) the technical efficiency (TE) from CRS DEA of human settlements in China's megacities and supercities is low. Management and technology are the shortcomings in the development of urban human settlements; (2) total factor productivity (TFP) has shown negative growth. Technical progress efficiency (TC) is the key to improving the efficiency of urban human settlements; (3) urban infrastructure has the most significant role when promoting the efficiency of urban human settlements; (4) the coupling degree between the efficiency of human settlements and high-quality economic development is mainly high-level coupling. The degree of coordination is gradually rising; and (5) during the 14th Five-Year Plan period, the investment in human settlements in both types of cities will continue to increase. With the continuous expansion of investment, the output will be imbalanced. [ABSTRACT FROM AUTHOR]

Purpose: In China, engineering insurance has been questioned as not being beneficial as expected. This paper seeks to further understand how China's engineering insurance industry functions and to provide a macro perspective explanation for engineering insurance's underdevelopment. Design/methodology/approach: Three industrial organization hypotheses were extended to the engineering insurance context: structure conduct performance (SCP), relative market power (RMP) and efficiency structure (ES) hypotheses. This paper employed the Generalized Method of Moments (GMM) and Data Envelopment Analysis (DEA) bootstrap to test the hypotheses using panel data from 2008 to 2017. Findings: The results suggest that the SCP paradigm is validated in China's engineering insurance market, indicating a concentrated market where the welfare of consumers (e.g. owners, contractors and designers) may be eroded. Several factors are identified to have significant impacts on engineering insurers' performance, such as the investment return, percentage of engineering business, the ratio of outstanding claims, the number of large contractors, market rivalry and entry barriers. Originality/value: Despite the sheer size of China's construction industry and the urgent need to improve risk management, the insurance industry that serves construction firms engineering insurance is underdeveloped. Engineering insurance is yet to be understood from a macro perspective, which may reveal the underlying reasons for engineering insurance's underdevelopment. The industrial organization theories provided a theoretical framework to test the functioning of this specific industry. The disaggregated data (engineering line specific) is employed to ensure effective regulation and policymaking. [ABSTRACT FROM AUTHOR]

Watershed ecological compensation is an important means to protect the ecological environment and an important part of China's ecological civilization construction. It can promote the sustainable and coordinated development of a region, enhance the advantages of the ecological environment in the upstream area, and lay the foundation for the high-quality development of ecological tourism in the upstream area. The accurate evaluation of the effect and efficiency of ecological compensation is a prerequisite for optimizing and perfecting the ecological compensation system. In order to evaluate the effect and efficiency of watershed ecological compensation, this paper used the case study area of Anyuan County, an important ecological area of the Dongjiangyuan watershed in the pilot area of China's interprovincial watershed ecological compensation. This paper established an evaluation index system, used the entropy method and the data envelopment analysis (DEA) method to construct a watershed ecological compensation effect and efficiency evaluation model, and selected the ecological compensation index data from 2015 to 2020 to evaluate the effect and efficiency. This paper also constructed an econometric model to analyze their driving factors. The results showed that the effect of watershed ecological compensation was generally on the rise. Low pure technical efficiency (PTE) was the main reason for low comprehensive efficiency (CE), and the management efficiency of ecological compensation projects needs to be improved. The overall performance of scale efficiency (SE) was good, but there was still a problem of capital redundancy. Ecological compensation expenditure had a significant negative impact on the efficiency of ecological compensation, and ecotourism had a significant positive impact on the effect and efficiency of the ecological compensation. The results of this study can provide a scientific basis and theoretical reference for improving the effect and efficiency of watershed ecological compensation schemes. [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]

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]

This study examines performance of provincial health‐care system in China, using a dynamic network data envelopment analysis (DEA) approach. We focus on efficiency improvements both within provincial health‐care system and within two separate internal sub‐divisions. The administration division engages in financial management while the medical care division provides medical care services. Then there are two main results. First, the average overall efficiency score of provincial health‐care system is 0.9316 from 2010 to 2017. Second, the productivity progress in administration division is lower than that in medical care division, and the technical advances contribute most of the productivity progress. The research gap and the innovation of this paper lie in three aspects: First, this paper opens the black box of health production function and use the network DEA to analyze Chinese provincial health‐care system and its inner two constructs. Second, this paper discusses the efficiency scores as well as dynamic changes in one model. Finally, this paper tries to reveal the regional heterogeneity of static efficiency as well as the dynamic efficiency changes. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to provide scientific guidance for the integration of industrialization and information (TIOII). In recent years, TIOII has promoted the development of intelligent manufacturing in China. However, many enterprises blindly invest in TIOII, which affects their normal production and operation. Design/methodology/approach: This study establishes an efficiency evaluation model for TIOII. In this paper, entropy analytic hierarchy process (AHP) constraint cone and cross-efficiency are added based on traditional data envelopment analysis (DEA) model, and entropy AHP–cross-efficiency DEA model is proposed. Then, statistical analysis is carried out on the integration efficiency of enterprises in Guangzhou using cross-sectional data, and the traditional DEA model and entropy AHP–cross-efficiency DEA model are used to analyze the integration efficiency of enterprises. Findings: The data show that the efficiency of enterprise integration is at a medium level in Guangzhou. The efficiency of enterprise integration has no significant relationship with enterprise size and production type but has a low negative correlation with the development level of enterprise integration. In addition, the improved DEA model can better reflect the real integration efficiency of enterprises and obtain complete ranking results. Originality/value: By adding the entropy AHP constraint cone and cross-efficiency, the traditional DEA model is improved. The improved DEA model can better reflect the real efficiency of TIOII and obtain complete ranking results. [ABSTRACT FROM AUTHOR]

Purpose: With the rapid economic growth and urbanization development, regional environmental problems have attracted increasing attention. The study on analyzing cities' capacity on resource utilization and environmental protection is practically significant because of the industrial agglomeration in an urban area. This study aims to measure environmental efficiency of urban industrial water utilization by comparing input, output and undesirable outputs variables of cities. Design/methodology/approach: This paper combines data envelopment analysis basic approach with regression to discover the environmental efficiency score of cities and their influence factors. A set of slack-based measure (SBM) model is constructed for calculating the environmental efficiency score by considering both desirable and unendurable outputs. Findings: This paper analyzes the industrial water utilization efficiency for China from the city level by evaluating the performance for up to 200 mainland Chinese cities during 2012–2016 under SBM model. Then, 2C Tobit regression is used to measure the determining factors of industrial water utilization efficiency from the angle of natural, social, municipal and industrial structure factors. The empirical study results show huge room for improvement in industrial water utilization in China, while the average citizen efficiency scores maintain a level of about 0.5. Originality/value: Significant differences exist in the regional efficiency in different cities in China. Per capita GDP, a total length of drainage pipe and whether the area is coastal or not have significant positive impacts on the water utilization efficiency, while the proportion of secondary industry to GDP has a significant negative influence. Specific recommendations are proposed based on the local industrial water utilization efficiency scores, such as improving urban infrastructure and adopting a more flexible water pricing system. [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]

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]

In the context of increasing global resource and environmental problems, it is of great practical significance to accurately test the impact of various factors on energy use efficiency for maintaining national energy security and formulating relevant policies. This paper measures firms' total factor energy efficiency (TFEE) using the two-stage stochastic frontier method within the data envelopment analysis (DEA) framework, leveraging data from listed firms in China spanning 2010 to 2022. Employing the establishment of free trade zones (FTZs) as a quasi-natural experiment, we apply the staggered differences-in-differences (DID) and stacked DID methods and analyze the impact of FTZs on firms' TFEE. The results show that the establishment of FTZs significantly promotes the improvement of firms' TFEE, and it has a greater promotion effect on heavily polluting, non-manufacturing, state-owned, private, and small-scale firms. The results of the mechanistic analysis showed that the promotion effect of FTZs on firms' TFEE is mainly realized through three channels: increasing government subsidies, reducing the financing constraint effect, and encouraging the technology innovation effect. Furthermore, industry-level decomposition results indicate that the surge in industry energy efficiency primarily results from improvements within firms rather than inter-industry variations. This paper's results propose that countries can enhance energy efficiency by progressively endorsing the implementation of FTZs. [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]

As the "sixth largest city group in the world", the Yangtze River Delta region is an important economic growth point and core economic area in China. While achieving rapid economic growth, the amount of waste generated is increasing day by day, and the investment in environmental protection is constantly increasing. Among them, MSW collection and disposal funds accounted for 57.40% of the fixed assets investment in environmental sanitation in 2017. To improve the efficiency of existing environmental protection investment, this paper is based on the existing academic research at China and abroad, with the help of the Data Envelopment Analysis (DEA) model. This paper analyzed the economic indicators of 27 cities in the Yangtze River Delta for MSW collection, transportation and disposal to measure economic efficiency, identify and improve inefficiencies. The research results show that the average efficiency of the 27 cities in the Yangtze River Delta is at a relatively high level. Six cities have the most effective comprehensive technical efficiency. These six cities constitute the effective frontier of the municipal solid waste transfer system. The overall efficiency has a comparative advantage; 9 cities have the best pure technical efficiency, accounting for 33 of all cities. %, the pure technical efficiency of the remaining 18 cities is low, indicating that these cities have not fully utilized their resource input under the current scale, and the efficiency of resource utilization needs to be improved. Finally, this paper proposes suggestions for improvement from the perspective of environmental sustainability. To improve MSW collection and disposal efficiency, differentiated management should be implemented in cities in the Yangtze River Delta. Implications: This paper conducts an empirical analysis on the efficiency of MSW collection and disposal in the Yangtze River Delta in China in 2017. Based on the calculation of the DEA model, our conclusion is that although the collection and disposal system of MSW in the Yangtze River Delta has been significantly improved, the level of collection and disposal of some MSW has not reached the optimal level: (1) Comprehensive technical efficiency is the most effective Cities accounted for 22% of the total number of cities studied. (2) 33% of the cities in the Yangtze River Delta achieve the best pure technical efficiency; (3) Among the 27 cities, 6 cities have the best scale efficiency, and the remaining 21 cities have not reached the best scale efficiency. [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]

Our objective in this paper is to evaluate the benefits of bus transit. To obtain the more accurate and highly discrimination results, this study establishes an evaluation indicator system from a stakeholder perspective and proposes a novel combined method consisting of dynamic network data envelopment analysis, cross-efficiency evaluation, and Shannon entropy aggregation method. An empirical study of bus transit systems in 33 key Chinese cities from 2016 to 2019 is provided. The results show that the benefit of bus transit in most key cities was ineffective. In contrast to production efficiency, focusing on improving service effectiveness is more conducive to improving the benefits of bus transit. Small cities have higher benefits than large cities. Meanwhile, the benefits of bus transit vary geographically. This evaluation outcome provides a more appropriate basis for decision-making related to the benefits of public transit services, as well as for operational and management studies. [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]

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]

The massive production and accumulation of industrial solid waste (ISW) have led to environmental pollution and natural resource underutilization. China's efforts to build trial industrial waste resource utilization centers provide strong support for sustainable development. However, these centers and the factors driving ISW utilization have yet to be evaluated. This paper utilizes context-dependent data envelopment analysis models without explicit inputs (DEA-WEI) to evaluate the overall utilization performance of 48 industrial waste resource utilization centers in China from 2018 to 2020. It also builds a Tobit model to assess which indicators and waste types affect overall ISW utilization. The results show overall ISW utilization performance of centers in the sample has improved, with the average value falling from 1.7193 in 2018 to 1.5624 in 2020. However, there are clear regional performance gaps, with East China having the highest utilization performance (1.3113) while the Southwest had the lowest (2.2958). Finally, this paper proposes measures to improve the overall utilization of industrial waste resources based on an analysis of the factors driving solid waste utilization. [ABSTRACT FROM AUTHOR]

The ocean plays a crucial role in human society's survival and development. While China's marine economy has grown rapidly in recent years, it has also led to serious problems inhibiting ecosystem sustainability. This paper proposes high-quality development of the marine economy and combines the improved entropy value method, fuzzy hierarchical analysis method (FAHP), and data envelopment analysis (DEA) method to establish a quadratic relative evaluation model. A two-layer comprehensive index framework with 19 indicators is built to measure various aspects of the marine economy, including innovation, coordination, green, openness, and sharing. Empirical analysis conducted on 11 coastal provinces in China using data mainly collected from the Chinese Statistical Yearbook reveals significant spatial patchiness in the high-quality development level of the marine economy. This discrepancy is largely due to differences in geographical locations, resources, and government policies. The study analyzes four benchmark provinces of high-quality development and summarizes their experiences. The paper concludes by providing suggestions and implications to support government decision-making. [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]

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]

With China's economy entering the stage of high-quality development, manufacturing energy carbon emission efficiency has become the focus of academic attention. It is of great significance to study the convergence of manufacturing energy carbon emission efficiency for realizing high-quality development of manufacturing in China. Based on the panel data of China's manufacturing sub-sectors, this paper measures and analyzes the evolution trend of manufacturing energy carbon emission and its efficiency. On this basis, this paper uses the coefficient of variation and convergence model to test the convergence of manufacturing energy carbon emission efficiency. The results show that China's manufacturing energy carbon emissions and its efficiency demonstrate an increasing trend. Coal was the main source of manufacturing energy carbon emissions. The manufacturing energy carbon emission efficiency does not have σ convergence, but has β convergence, and its convergence has industry heterogeneity. The manufacturing energy carbon emission efficiency exits scale effect and technology effect, but not the effect of opening to the outside world and institutional effect, and its effect exists industry heterogeneity. By reducing carbon emissions, adopting differentiated policies, adjusting the industry scale, and enhancing the industry technology intensity, China's manufacturing can improve the energy carbon emission efficiency and promote high-quality economic development. [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]

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]

Virtual water trade can generate an aggregate value gain or loss when there is a regionally disparity in the value of water resources. This paper proposes a novel integrated model to evaluate the impact of virtual water trade on the gain and loss in both environmental and economic dimensions. Environmentally, when virtual water flows from regions rich in water to regions short of water, the scarcity of water resources at the aggregate level is alleviated and positive gains are obtained. Economically, as virtual water is transferred from economically less developed regions to those that are economically developed, the marginal economic value of water resources is enhanced, resulting in a positive gain. China is characterized by significant disparities in the degree of water scarcity and the level of economic development in different areas of the country. This study therefore focuses on China as a case of how interregional virtual water trade leads to a loss or gain in aggregate value. We employ a Multi-regional Input–Output model to analyze the virtual water flows within China and adopt the Data Envelopment Analysis to evaluate the water shadow price. Results show that the virtual water flow in China in 2015 was mostly from water-scarce to water-rich regions, resulting in a loss of 8 billion m3 of scarce water; however, at the same time, economically developed areas received large amounts of virtual water from less developed areas, thereby generating a net economic gain of 8.5 trillion CNY. In particular, the virtual water trade from Heilongjiang to Shandong yielded the largest of environmental gains, saving 1.65 billion m3 of scarce water, and the virtual water trade from Xinjiang to Guangdong produced the largest of economic gains, hitting 479 billion CNY. This paper aims to serve as an inspiration for regional, national and even global virtual water trade practices. [ABSTRACT FROM AUTHOR]

With rapid economic growth in the twenty-first century, innovation has become an essential component of national development, and industry-university-research regional collaborative innovation is the key to implementing China's innovation plan. Using panel data from 30 provinces and cities in China (excluding Tibet Autonomous Region) from 2011 to 2018, this paper employs the two-stage dynamic DEA model to develop a rating index system of regional collaborative innovation performance, which is divided into knowledge innovation stage and technology innovation stage, and measures the collaborative innovation efficiency of 30 provinces in China. The environmental regulation score is then determined by using the entropy method. Finally, an experimental application of the panel Tobit model is conducted to investigate the impact mechanism of environmental regulation on regional collaborative innovation. The results reveal that the collaborative innovation efficiency values of the majority of provinces are between 0.5 and 0.7, leaving ample room for growth. When the efficiency value of collaborative innovation is broken down by region, the eastern, central, and western regions show a pattern of "rising in the east, stable in the center, and falling in the west." The findings of the Tobit regression reveal that the effect of environmental regulation on regional collaborative innovation performance follows a "U"-shaped distribution, confirming the "Porter Hypothesis." This study proposes remedies and proposals to enhance regional collaborative innovation performance from the perspective of environmental regulation. [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]

China's New Energy Vehicle (NEV) industry has entered an accelerated development stage, with the technology innovation efficiency becoming an essential factor affecting the speed of its development. Therefore, to explore ways to improve the efficiency of technology innovation, this paper divides the technology innovation process into two stages: the research and development (R&D) stage and the commercialization stage. This paper introduces a framework for evaluating the technology innovation efficiency of NEV enterprises based on data envelopment analysis (DEA), meta-frontier, and tobit regression. Then, the technology innovation efficiencies of 45 vehicle, battery, and motor & electronic control NEV enterprises are analyzed. The results show that: (i) During the survey period, the overall technology innovation capability of Chinese new energy vehicle enterprises is not strong, especially regarding economic transformation. However, the general development trend is on the rise. (ii) Different types of enterprises have different technology gap ratios in the two stages. The technology innovation efficiency level of motor and electronic control enterprises is relatively weak in the new energy vehicle industry. (iii) Many measures can be implemented to help improve technology innovation efficiency: encouraging the large-scale development of enterprises, reasonably increasing the shareholding ratio of significant shareholders, improving the ratio of capital investment, stimulating the vitality of innovation within the enterprise, and optimizing the number of employees. [ABSTRACT FROM AUTHOR]

The contradiction between ecological maintenance and economic production is increasingly prominent with the rapid development of forestry. Uncovering the forestry eco-efficiency which integrates ecology, resources and economic production is the premise of mitigating the hazards of strict reliance on heavy inputs and improving the resource utilization efficiency in forestry. This paper applies a three-stage data envelopment analysis (DEA) model combined with the DEA-Malmquist approach to eliminate the interferences of external environment and random errors and reveal the evolution of real forestry eco-efficiency and its decomposition. Besides, it is beneficial to understand the convergence of forestry eco-efficiency for grasping the long-term efficient operation mechanism of ecological production. The empirical results demonstrate that the forestry eco-efficiency progress is closely related to an excellent environment and efficient internal management by comparing the results between stage I and stage III. Different environmental variables have different effects on the slack of different inputs in stage II. Moreover, the convergence analysis proves the existence of absolute convergence and conditional convergence of forestry eco-efficiency in the whole China and six regions; that is, the catch-up effect is observed in backward provinces. Hence, targeted policy suggestions are provided to achieve forestry return to its green essence. [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]

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]

With social progress and economic development, urban rail transit systems have been developed to satisfy the growing travel demands in China. Undoubtedly, it is necessary to evaluate the operation efficiency of urban rail transit systems and analyze their influence factors, which are highly significant for promoting management performance. In the present paper, an integrated approach is proposed, which consists of a data envelopment analysis (DEA) model, a Malmquist productivity index, and a Tobit regression model. For evaluating the operation efficiency of urban rail transit systems in China, the DEA model and the Malmquist productivity index provide an evaluation metric, and the Tobit regression model is used to carry out influential factor analysis. The test data are collected from six typical cities at different stages of rail transit system development from 2013 to 2017, in order to investigate the effectiveness of the proposed methodology. The experimental results demonstrate the operation efficiency of different rail transit systems and the effects of several influencing factors. The conclusions from this paper can guide policymaking and provide references for enterprises to improve the operation efficiency of rail transit in China. [ABSTRACT FROM AUTHOR]

China is advocating the ecological civilization for a sustainable society and resource–economic–environmental system due to its environmental and climate problems. As a special resource–economic–environmental system, island systems are facing severe challenges due to the vulnerable coordination ability between ecological environment and economic development. To measure the sustainable performance of island systems more directly and specifically, this paper extends the concept of ecological efficiency to inclusive ecological efficiency. For the first time, we analyze the inclusive eco-efficiency of Hainan Island, the second largest island in China, from 2008 to 2017. Due to the large technological heterogeneity among the diverse industries, this paper combines inclusive eco-efficiency with meta-frontier data envelopment analysis (DEA). And we propose a revised meta-frontier slack-based measure (SBM) model and meta-frontier non-radial directional distance function (NRDDF) model, which makes the technology gap rate (TGR) no larger than 1. The empirical results show that the average inclusive total factor energy efficiency (ITFEE) of the tertiary industry under the group-frontier is the largest while the average ITFEE of the primary industry is the highest under the meta-frontier. Moreover, the technology gap rate of the primary industry is the largest. Policy implementations are presented based on the empirical results. [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]

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]

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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]