Comprehensive Technical Efficiency Research Articles

National Modern Agricultural Industrial Parks: Development Characteristics, Regional Differences, and Experience Inspiration—Case Study of 200 NMAIPs in China

Agricultural industries are the foundation of the modernization of agricultural and rural areas in China. National Modern Agricultural Industrial Parks (NMAIPs) provides a considerable nationwide platform for agricultural industries. We take 200 NMAIPs in China as objects. Through spatial analysis, the Herfindahl–Hirschman index, and the SBM-DEA model, we analyzed the development characteristics and regional differences of NMAIPs from the muti-level perspective of national planning, provincial coordination, and county implementation to propose policy recommendations aimed at sustainable and high-quality development. The results are as follows: (1) Regarding geospatial characteristics, NMAIPs are unevenly distributed, with a decreasing gradient from east to west. The direction is east (northward) to west (southward), consistent with the direction of the Hu line. The distribution density shows that the east is dense and the west is sparse. (2) For industrial concentration, the leading industries in NMAIPs tend to be homogenous. The HHI indicates that the homogenization of leading industries is widely represented in each province. The low oligopolistic areas are in the central and eastern regions of China, while the highly oligopolistic locations are in the western and northeastern provinces. (3) In inputs–outputs efficiency, the comprehensive technical efficiency is high but not optimal, while the distribution of values is high in the south and low in the north. Ten provinces are non-effective. According to inputs and outputs, the ineffective contribution of population of townships covered, occupied area and the capital from the collective economy are development barriers, and the high output value of NMAIPs cannot fully drive the employment and income of farmers. Further improvements are needed in terms of both pure technical efficiency and scale efficiency, and adjustments to scale operations should be in response to different returns to scale. Our research results provide policy recommendations for NMAIPs, including the establishment of a multi-level management mechanism, balancing regional development, diversifying and coordinating regional leading industries, and improving the efficiency of utilization factors.

Efficiency Analysis of the Coastal Port Group in the Yangtze River Delta

In recent years, the coastal ports of the Yangtze River Delta have rapidly developed with the progress of science and technology, which has caused some problems on account of the rapid development of ports. On the one hand, there is fierce competition within the same port group; on the other hand, many ports waste resources. This study selected the three-stage data envelopment analysis (DEA) and Malmquist index models to calculate and analyze the efficiency value of the coastal port group in the Yangtze River Delta; the study was conducted to make a reference for the formulation of the optimization strategy from the perspectives of static and dynamic efficiency. The results show that from the perspective of static efficiency, the comprehensive efficiency of the Yangtze River Delta coastal port cluster is at the upper-middle level. However, it has not yet reached the frontier surface, and the low scale efficiency is why the port group has not been called the frontier surface. From the perspective of dynamic efficiency, the total factor productivity of the Yangtze River Delta port group has increased by 3.6% in the past five years. Technological progress and comprehensive technical efficiency have improved. The optimization strategy was formulated according to the problems faced by the Yangtze River Delta port group and the reasons for not reaching the frontier.

The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities' Ecological Welfare Performance.

In the “full world” where natural capital is scarce, within the limits of the ecological environment, the improvement of welfare is a fundamental requirement for sustainable development. The ecological wellbeing performance (EWP) of 284 cities in China from 2007 to 2020 was measured by the superefficient SBM-DEA model, considering undesirable output, and analyzing the evolutionary trends of overall comprehensive technical efficiency, pure technical efficiency, and scale efficiency. The Theil index was used to explore the source and distribution of the Chinese cities’ EWP differences. Exploratory spatial data analysis (ESDA) and the spatial Durbin model (SDM) were applied to analyze the spatial distribution characteristics and driving factors of cities’ EWP. The results showed the following: (1) Regarding spatial and temporal distribution, the EWP of Chinese cities showed a fluctuating upward trend, in which pure technical efficiency > scale efficiency. (2) Considering regional differences, the differences in cities’ EWP were mainly intraregional rather than interregional. The contribution rates of distinct regions to the differences in EWP varied, i.e., western region > eastern region > central region > northeastern region. (3) In terms of spatial correlation, China’s EWP showed positive spatial correlation, i.e., high–high agglomeration and low–low agglomeration. (4) Concerning influencing factors, the level of financial development, the structure of secondary industries, the level of opening-up, and the degree of urbanization significantly improved EWP. Decentralization of fiscal revenue significantly inhibited improvement of EWP. Decentralization of fiscal expenditure and technological progress had no significant impact on the EWP. In the future, to improve cities’ EWP, China should focus on reducing differences in intraregional EWP, overcoming administrative regional limitations, encouraging regions with similar locations to formulate coordinated development plans, promoting economic growth, reducing levels of environmental pollution, and paying attention to the improvement of social welfare.

Efficiency Decomposition Analysis of the Marine Ship Industry Chain Based on Three-Stage Super-Efficiency SBM Model—Evidence from Chinese A-Share-Listed Companies

Based on the micro-data of 79 listed companies in the Chinese marine ship industry chain from 2015 to 2019, this paper calculates the comprehensive technical efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE) of the upstream, midstream, and downstream of China’s marine ship industry chain by using a three-stage super-efficiency slacks-based model (SBM), and further analyzes the weak links in industrial chain efficiency and their influencing factors. It is shown that (i) the TE and PTE of the upstream, midstream, and downstream of China’s marine ship industry chain are in a “V”-shaped distribution, high at both ends and low in the middle, but that the SE is ranked as follows: upstream > midstream > downstream. In addition, the PTE is the main factor which hinders the improvement of TE in the industrial chain. (ii) The environmental variables have significant impacts on industrial chain efficiency. When the influences of environmental variables and random error terms are excluded, the industrial chain efficiency changes significantly. The values of SE and TE decrease significantly, and the distribution characteristic of TE changes. However, the PTE is still in a “V”-shaped distribution and appears to be the main driving force for the progress of TE. (iii) China’s marine ship industry chain has obvious weak links in terms of efficiency, and the midstream and downstream areas need to focus on development. Each link of the industry chain has high coupling and low coordination, and they are all closely related to each other, but the coordination ability is insufficient. The industrial chain in terms of efficiency and coordinated development can still be improved.

Measurement of local government green governance efficiency based on total waste emissions and PM2.5 concentration: Evidence from China.

The problem of environmental pollution is becoming more and more prominent. Making ecological governance take an effective and sustainable development path has become a complex problem for countries to think about. The proposal of green governance provides new ideas for governments to manage enterprises and local environmental governance. The DEA method is commonly used to measure the effectiveness of environmental governance, but the traditional DEA method ignores environmental factors and management factors, and the measurement error is significant. Therefore, this paper introduces the total waste discharge and PM2.5 average concentration and other unexpected outputs, using the three-stage DEA model and three-stage DEA Malmquist index model, creatively constructing the green governance measurement index system, which measures and evaluates the green governance efficiency of 30 provinces in China from 2004 to 2019 from static and dynamic perspectives. The research results show that the efficiency value obtained by the three-stage DEA model is higher than the first stage, which confirms that the external environmental factors have a specific impact on the GGE. At the same time, the comprehensive technical efficiency value presents a "U"-shaped trend with time. From the perspective of sub-regions, there is heterogeneity in the efficiency values between regions, showing a decreasing trend of "east, west, and middle." From the efficiency decomposition results, the main reason for the negative growth rate of GGE is the low efficiency of technological progress, which provides targeted suggestions for governance in various regions of China. This study will help provinces prepare to strengthen investment in technological innovation, maximize the benefits of input and output, and promote green and sustainable development.

Efficiency Evaluation and Spatial Autocorrelation Analysis of Primary Health Care Resources Distribution: The Panel Three-Stage DEA Model

Objective: To analyse the distribution of Primary Health Care (PHC) in efficiency among provinces from 2010 to 2019 in China, to examine the factors influencing performance, and to describe the spatial agglomeration characteristics of allocation efficiency, so as to optimize and balance the utilization thereof. Method: Using a panel Three-stage DEA comparative analysis model to describe factors that may lead to high efficiency, combined with a descriptive study for spatial agglomerating features of provinces using Spatial autocorrelation analysis. Results: The overall performance of PHC distribution efficiency is unreasonable, with an average comprehensive technical efficiency of 0.688 from 2010 to 2019. The external and management noise had a significant impact on the efficiency of PHC resource allocation. The increase in per capital GDP could enhance the efficiency, but the dependence ratio of the elderly population and the rate of urbanization were inversely. The effectiveness of PHC allocation had spatial agglomeration features. Moran’s I index was the lowest in 2016 (0.293) and the highest in 2019 (0.421) at the significance level of 1%. The Getis_Ord GI* index demonstrates that the general level of spatial agglomeration had improved, with the number of cluster provinces increasing from 11 to 15. Conclusion: The PHC distribution efficiency should be improved, the establishment of balanced eastern, central and western regions should be encouraged, and a new PHC ecosystem should be established. Further, new patterns should be created in the geographic area of primary health care, and citizens’ access to medical services should be increased.

Sustainable Financing Efficiency and Environmental Value in China’s Energy Conservation and Environmental Protection Industry under the Double Carbon Target

Difficulty in financing and low financing efficiency is one of the bottlenecks that restrict the high-quality development of China’s energy-saving and environmental protection industry and economy. The key to improving financing efficiency is to understand its influencing factors. This paper uses data envelopment analysis (DEA) and the Malmquist index to measure the overall financing efficiency and the efficiency of different financing methods of 205 Chinese energy-saving and environmental protection industries from 2015 to 2020 from static and dynamic perspectives, respectively, as well as the Tobit model to estimate the impact of factors such as the digital transformation and green technological innovation of enterprises on financing efficiency. The study shows the following: (1) Static analysis shows that: the financing efficiency of the comprehensive technical efficiency of China’s energy conservation and environmental protection industry is less than one, 5.8% to 23.41% of enterprises have very effective comprehensive technical financing efficiency, and fewer than 9% enterprises have very effective scale efficiency levels. Enterprises may have more room for improving their financing efficiency in the future. The four types of financing are, namely, internal financing, equity financing, fiscal financing, and debt financing, in descending order of efficiency. (2) Dynamic analysis shows that the financing efficiencies of debt financing and fiscal financing are both on an upward trend, while internal and equity financing efficiencies are on a downward trend. Additionally, the technological progress change index and scale efficiency are two key factors affecting the financing efficiency of different financing methods. (3) In terms of financing methods, the comprehensive technical efficiency and scale efficiency of endogenous financing and equity financing are high, while the comprehensive technical efficiency and scale efficiency of debt financing and fiscal financing are low and flat. (4) Digital transformation, green technology innovation, the asset–liability ratio, profitability, and operational capability have a significant positive impact on the financing efficiency of energy-saving and environmental protection enterprises. This paper studies the financing efficiency of China’s energy conservation and environmental protection industry under different financing methods and the mechanism through which key factors affect the financing efficiency of enterprises. It aims to provide a theoretical basis for managing financing methods scientifically and rationally and improving the financing efficiency of the energy conservation and environmental protection industry, as well as to provide practical reference for the implementation of digital transformation, green technology innovation and diversified financing in China and other developing economies.

Utility analysis of digital villages to empower balanced urban-rural development based on the three-stage DEA-Malmquist model.

Rural subjects, the agricultural industrial structure, public services and rural governance are fully empowered by digital villages. This empowerment effectively compensates for the urban-rural digital divide and promotes the equalization of urban-rural income, consumption, education, medical care, and governance. Based on the three-stage data envelopment analysis (DEA) model and Malmquist index, this article conducts an in-depth study of the static and dynamic efficiency trends of digital villages that empower urban-rural balanced development in 31 provinces in China from 2015 to 2020. The results show that comprehensive technical efficiency of 31 provinces is weak DEA effective, and that the scale efficiency is the main factor affecting comprehensive technical efficiency. The educational level, local finance and industrial structure optimization have a significant positive impact on efficiency evaluation, but technological innovation and the urbanization level have a significant negative impact. Total factor productivity shows diminishing marginal utility based on the Malmquist index and its decomposition change. Restricted by the change in technological progress, the efficiency of digital villages in China in enabling urban-rural equilibrium needs to be further improved.

Productive services agglomeration, financial development and regional innovation efficiency in the Yangtze River Economic Zone

We take cities along the Yangtze River Economic Belt as the research object, measure the regional innovation efficiency of the Yangtze River Economic Belt, and empirically test the relationship between the agglomeration of producer services and regional innovation efficiency. The results show that both productive services agglomeration and innovation efficiency show regional imbalance. The agglomeration of productive services can significantly improve innovation efficiency in neighboring cities but negatively impact the local comprehensive technical efficiency. This negative effect can be alleviated by upgrading the industrial structure and increasing financial development.

Evaluating the efficiency of municipal solid waste collection and disposal in the Yangtze River Delta of China: A DEA-model

ABSTRACT 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.

Evaluation of Green Logistics Efficiency in Northwest China

This paper develops an index system for assessing green logistics efficiency in Northwest China with the goal of “double carbon” (peak carbon dioxide emissions and carbon neutrality). The study employs a three-stage data envelopment analysis model of super efficiency to assess the spatial and temporal efficiency of the green logistics industry in Northwest China from 2010 to 2019. Our findings reveal that the overall logistics efficiency in Northwest China fluctuates. Each province has a high pure technical efficiency, but significant regional differences in comprehensive technical efficiency and scale efficiency are apparent. In Northwest China, government support and science and technology levels have a greater impact on green logistics efficiency. Based on the implementation of the “double carbon” strategy, this study offers pertinent insights and suggestions for the high-quality development of the green logistics industry in Northwest China.

The Heterogeneity of High-Quality Economic Development in China's Mining Cities: A Meta Frontier Function.

The transformation of mining cities and the realization of high-quality economic development are complicated processes. The objective existence of abundant resource factor endowment in mining cities does not mean that resource allocation is in the optimal state and can play the greatest role. The optimal allocation of factors for the high-quality economic development of mining cities is more important than the resource factors. The input–output allocation efficiency of high-quality economic development under the common frontier and group frontier of 99 mining cities in China from 2006 to 2019 is calculated by using the data envelopment analysis method and common frontier model, and the pure technical efficiency and scale efficiency are decomposed. The results show that (1) the comprehensive technical efficiency values under both common frontiers and group frontiers show that the factor allocation efficiency in the process of high-quality economic development of different mining cities shows obvious heterogeneity. (2) The growth of the input–output allocation efficiency of the high-quality economic development of mining cities has significant spatial convergence characteristics, but the convergence speed is different. (3) The high-quality development path of the mining city’s economy should not only focus on comprehensively improving the ability of resource element input and output allocation but also improve the group environment.

Measurement and Optimization Strategy of Urban Environmental Governance Efficiency in Different Provinces of China

The urban environment has certain attributes of public products, and its governance activities are often led by the government. Since the 18th National Congress of the Communist Party of China, China has actively promoted the coordination of resources and the environment, steadily promoted the construction of socialist ecological civilization, and sought breakthroughs in urban environmental governance methods, governance scopes, and governance concepts. Studying the level and efficiency of urban environmental governance in different regions is conducive to the realization of coordinated urban and rural development and the improvement of regional comprehensive environmental conditions. This paper uses data envelopment analysis to measure the urban environmental governance efficiency of 31 provinces in China in 2019, and quantitatively analyze and compare comprehensive technical efficiency score, pure technical efficiency score, scale efficiency score, and return to scale. It is found that (1) the urban development in various regions is unbalanced, and the efficiency of environmental governance varies greatly; (2) the overall efficiency of urban environmental governance in Jilin, Liaoning, Ningxia, and Tibet is relatively good. The pure technical efficiency score of urban environmental governance in Guangdong, Hunan, and Shandong performed relatively well; The economies of scale in Guizhou, Hainan and Qinghai are relatively obvious, and the growth level of urban environmental governance output factors is higher than that of input factors. China should refine the investment direction of environmental governance, introduce advanced environmental governance technologies, explore comprehensive governance models involving all citizens, and formulate environmental governance plans that meet the actual conditions of the city, so as to improve the efficiency of urban environmental governance, optimize the level of urban environmental governance, and realize the sustainable development of economy, resources and environment.

Evaluation of Green Logistics Efficiency in Jiangxi Province Based on Three-Stage DEA from the Perspective of High-Quality Development

The high-quality development of the logistics industry plays an important role in high-quality economic development. Green logistics is attracting more attention, owing to environmental concern. Based on the five concepts of “innovation, coordination, green, openness and sharing” of high-quality economic development, the input–output indicators of green logistics efficiency (GLE) have been designed. The correlation between the green logistics input and output indicators have been analyzed by Pearson, and the green logistics efficiency of 11 cities in Jiangxi Province has been calculated by three-stage DEA. The evolutionary characteristics of the high-quality development of green logistics efficiency in Jiangxi Province were analyzed and evaluated. The conclusions were achieved as follows: (1) Nanchang, Xinyu and Ganzhou city are at the forefront of efficiency, and are less affected by environmental factors. The logistics efficiency of other cities is obviously affected by environmental factors. (2) The comprehensive technical efficiency (TE) of green logistics in Jiangxi Province is strongly influenced by scale efficiency (SE). The poor scale efficiency reduces the comprehensive technical efficiency of green logistics. (3) There is a positive correlation between high-quality economic development and logistics efficiency. In these cities of Jiangxi province (Nanchang, Ganzhou, Jiujiang, etc.) the share of total economy and green logistics efficiency is high. This study proves that Jiangxi province is moving towards high-quality economic development due to good environmental protection. (4) In 2017, Jiangxi Province was recognized as one of the national ecological civilization pilot region by the State Council. Green logistics efficiency in Jiangxi Province showed an inflection point in 2017, indicating that the green concept is becoming more and more popular. From the government to enterprises, the province has achieved initial results in promoting the transformation of the economic development mode. It aims to provide reference for the high-quality development of other provinces.

Energy efficiency evaluation model based on DEA-SBM-Malmquist index

Energy efficiency represents the level of energy use. By evaluating the level of Total Factor Energy Efficiency (TFEE), we can more accurately analyze the ways to improve energy efficiency and provide suggestions for green energy conservation construction. From the perspective of TFEE, this paper takes capital stock, working population and total energy consumption as input indicators, GDP as expected output, and industrial sulfur dioxide, soot, wastewater discharge and PM2.5 as non-expected output. Select the panel data of 23 cities from 2012 to 2018, calculate the TFEE of each city by using DEA-SBM (Slack-Based Measurement) model and Malmquist index method, and decompose the total factor productivity into comprehensive technical efficiency change and technical progress. The results show that the change trend of TFEE in each region varies greatly during the sample period. The overall TFEE of Harbin and Shanghai shows a continuous upward trend. TFEE in Chengdu and Chongqing has little change and is basically in a state of continuous fluctuation. TFEE of Changsha is the first of the 23 cities studied in this paper, and the resource allocation in this area is more reasonable. TFEE of Shenzhen area has a trend of coming from behind, and the development of this area has made great progress. The lower ranking is Guizhou and Xiamen these two regions. The overall efficiency of the 23 cities selected in this paper shows a downward trend in the survey year, with an average decrease of about 11.2%. From the perspective of sub indicators, the main reason for the decline of TFP is the lack of technological innovation. The decline rate reached 12% in the investigation year, while other indicators basically showed a stable fluctuation state, generally around 1. In general, the development state of TFEE in most regions of China is poor and the absolute value level is too low, which indicates that there is a large space for improvement in resource allocation in each region.

Research on corn production efficiency and influencing factors of typical farms: Based on data from 12 corn-producing countries from 2012 to 2019.

Globally, corn is characterised by high production and high export concentrations, yet the world is experiencing an unprecedented, huge change in this regard. Ensuring the global supply of corn, and thereby the energy and food security of nations has become particularly important. To understand the importance of corn production as an influencing mechanism of global food supplies, the present study researched the corn production of typical farms in major corn-producing and importing countries around the world. I selected the corn input and output data of 18 typical farms in 12 countries from 2012 to 2019, used the data envelopment analysis (DEA) model to calculate the technical efficiency of corn production, and built a tobit model to explore the impact of farming methods, input elements, supporting services, and other factors on efficiency. The study established that the average comprehensive technical efficiency of corn production on a typical farm was 0.863, and the average loss was 13.7%. In addition, it concluded that intensive tillage and conservation tillage have high technical efficiency. It also demonstrated that the proportion of mechanical labour and technical efficiency is in a ‘U’-shaped relationship, among others.

Factors associated with the research efficiency of clinical specialties in a research-oriented hospital in China.

Research-oriented hospitals are responsible for medical services tasks, medical education, and scientific research, playing an important role in medical research and application. The research efficiency of a clinical specialty is influenced by factors such as the characteristics of the specialty, the organizational atmosphere, and the clinical director’s leadership. The present study aimed to describe the research efficiency of clinical specialties, explore the factors influencing it, and clarify the argument of co-evolution theory regarding the collaborative development of medical services, education, and research. Logistic regression and multiple linear regression were adopted to estimate the correlation between influencing factors and scientific research efficiency. Hospital H, which is representative of research hospitals in China, was taken as an example. Taking three efficiency values—comprehensive technical efficiency (CTE), pure technical efficiency (PTE), and scale efficiency (SE)—as dependent variables, the independent variables affecting research productivity were statistically analyzed. This study also examined the scientific research efficiency of 41 specialties between 2013 and 2017, and found that the independent variables affected CTE, PTE, and SE to various degrees. Collaborative innovation in medical education and research must be based on clinical research; how to balance medical and teaching quality, and research efficiency requires further discussion. While young people play a major role on the research team because of their creativity and initiatives, which improve CTE and PTE, high-level researchers with better research and leadership abilities lead to the rational allocation and effective utilization of resources, thus improving SE. In 2013–2017, discipline construction focused on scale expansion, resulting in the decline of SE in China. Therefore, this study suggests further improvements for the efficiency of clinical specialties in research hospitals.

Research on the Temporal and Spatial Distribution and Influencing Factors of Forestry Output Efficiency in China

Forestry output efficiency is key to forestry development. China is now promoting the development of forestry, and thus the research on forestry output efficiency is of practical significance. Through the data envelopment analysis (DEA)-Malmquist index, spatial autocorrelation model, and fixed effect model of panel data, in this study, we analyzed the forestry output efficiency of China with indicators, such as the fixed asset input, employed personnel, total output value, and timber output, and drew the following conclusions. In the time series, the forestry total-factor productivity (TFP) in China saw a rapid increase, which is attributed to the technological progress change (TC), whereas the efficiency change (EC) imposed negative influences upon the forestry TFP. In the spatial distribution, there was a difference in the increase in the forestry output efficiency among the eastern, central, and western regions of China, with the eastern region having the fastest growth and the central region having the slowest growth. According to the spatial autocorrelation, there was spatial aggregation (high–high (HH) and low–low (LL)) with a significant positive correlation. Through the optimized fixed effect regression model, the fixed asset input, employed personnel, total output value, and timber output all had significant influences on the comprehensive technical efficiency of the forestry output, wherein the input indicators had negative influences, and the output indicators had positive influences.

Efficiency evaluation of county-level public hospitals in Hainan, China: a four-stage data envelope analysis model based on panel data.

Efficiency evaluation of county-level public hospitals in Hainan, China: a four-stage data envelope analysis model based on panel data.

Spatial–temporal differences of industrial land use efficiency and its influencing factors for China’s central region: Analyzed by SBM model

The Chinese economy has been experiencing rapid growth since the implementation of the reform and opening-up policy. However, it faces problems regarding resource savings and environmental protection, which are important aspects of the new industrialization. To balance these important aspects, we construct an evaluation index system for industrial land use efficiency in 82 prefecture-level cities on the six provinces of Shanxi, Anhui, Henan, Hubei, Hunan and Jiangxi in the central region of China. We use the Slacks-Based Measure (SBM) model to analyze the temporal and spatial differences of industrial land use efficiency in the central region from 2003 to 2012. We found that the efficiency of industrial land use in various provinces has been significantly improved in terms of land use scale efficiency, pure technical efficiency or comprehensive technical efficiency, also the advantages of scale effect have been continuously improved. In the past 10 years, the number of cities with industrial land use efficiency reaching a relatively reasonable level has gradually increased; by the analyze of the regression model we learn that the tendency of influencing factors on industrial land use efficiency and its influence mechanism. We also conduct convergence analysis on the difference in industrial land use efficiency among central region provinces, there is a σ convergence before 2009; after 2009, the gap in the efficiency of industrial land use in different cities in the central region has widened over time. Based on our study, some beneficial policy implications and suggestions are provided. • Slacks-Based Measure (SBM) model was used to study the industrial land use efficiency of 82 prefecture-level cities in China’s central six provinces. • The convergence of industrial land use efficiency was studied by σ test and the β test. • There is a negative correlation on the scale efficiency of industrial land and fiscal expenditure increase.