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This paper constructs a two-stage undesirable and desirable congestion model, which distinguishes purely technical inefficiency from congestion, to study the energy congestion of 30 transportation sectors in China from 2011 to 2020. The Heckman model is used to analyze the influence mechanism of various factors on the undesirable congestion of energy, which avoids sample selection bias. The results show that: (1) The undesirable congestion of energy mainly exists in the transport sector of the western region, while the desirable congestion of energy only exists in the transport sectors of the eastern and central regions. (2) Purely technical inefficiency in the transportation sector does not usually occur in isolation. (3) Population density and the proportion of clean freight turnover have a negative impact on the undesirable congestion of energy. • A two-stage undesirable and desirable congestion model is designed innovatively. • Energy efficiency in transport sector is assessed from the perspective of congestion. • The factors affecting the undesirable congestion in transport sectors are analyzed. • Rational allocation of energy in transport sector is realized based on congestion. [ABSTRACT FROM AUTHOR]

How to assess the performance of funds to support the rural revitalization is closely concerned by both academics and industries. In this paper, taking agricultural loans and financial allocations as inputs, we open the dynamic internal structure of the funding to support the rural revitalization system (FSRRS), including the agricultural support funds system (ASFS) and the rural revitalization system (RRS). With the consideration of regional heterogeneity, we propose the dynamic network data envelopment analysis (DEA) models based on convex and nonconvex metafrontiers to measure the metatechnology-specific technical efficiency (MTE), group-specific technical efficiency (GTE) and technology gap ratio (TGR) of the overall system and subsystems. The proposed models are empirically applied to assess the efficiency of funding to support rural revitalization and regional heterogeneity of technologies for 31 provinces in China during 2017–2020. The results show that: (i) compared to the nonconvex metafrontier model, its convex counterpart underestimates the efficiency of each decision making unit (DMU), resulting in the unfairness of evaluation, in particular for the central and western regions; (ii) there is a difference in the efficiency of the overall system and the subsystems, where the RRS performance is superior to the ASFS performance, implying that the inefficiency of FSRRS is mainly attributed to the low utilization of agricultural support funds; (iii) the period efficiency of the overall system and subsystems show an increasing trend over time, and the magnitudes of increases are different across provinces (regions); (iv) the TGRs of various provinces (regions) exhibit a significant heterogeneity. • We open the dynamic internal structure of the funding to support rural revitalization system (FSRRS). • We propose nonconvex metafrontiers based models to measure the performance of FSRRS. • We discuss the efficiency of FSRRS and regional heterogeneity of technologies. • We provide theoretical and empirical evidence for the model selection of FSRRS evaluation. [ABSTRACT FROM AUTHOR]

In the conventional data envelopment analysis (DEA) window analysis, a decision-making unit (DMU) in each window is treated as different units in each period so that the evaluation for one unit is performed on different scales over time. This paper proposes a novel window analysis based on common weight across time (CWAT), which evaluates each unit in each window by its common scale independent of time. The model for obtaining common weights is described as linear programming. And the paper suggests the Malmquist productivity index (MPI) on CWAT, CWAT MPI, to analyze productivity change by inheriting the result of window analysis. The numerical experiments are illustrated to examine the validity of CWAT and MPI, and the result shows that the proposed method provides a new evaluation scale compared to previous studies. The proposed model is applied to evaluate the performance of China 45 iron and steel enterprises during 2009–2017. The energy and environmental efficiency are calculated using CWAT, and CWAT MPI analyzes the productivity change. • We study a DEA window analysis based on common weights. • The proposed DEA window is represented by linear programming. • We discuss the Malmquist index in the DEA window. • The MPI is the geometric mean of all indices calculated in individual windows. • The performance of the iron and steel enterprises is evaluated. [ABSTRACT FROM AUTHOR]

In the context of the rapid development of Chinese economy and the advancement of urbanization and industrialization, the transportation industry caused serious environmental pollution and resource waste problems. The eco-efficiency of Chinese transportation industry has become a hot spot of society. Recently, China announced several initiatives to stabilize and expand employment, so that the efficient and sustainable development of industries cannot be based on the premise of reducing the labor force. However, traditional efficiency measures usually assume that inputs can be reduced at will, which is insufficient to correctly represent the observed practice. In this paper, we investigate the eco-efficiency of the transportation industry in 30 Chinese provinces incorporating the non-discretionary input labor and undesirable output CO 2 emission. Data envelopment analysis and directional distance function approaches are employed in constructing the measurement model. Our empirical results reveal explicit spatial features of the eco-efficiency in various provinces and show significant correlation between eco-efficiency and industrial structure, technological, and management factors. To examine the validity of our proposed models, comparative studies were further conducted and illustrated that the introduction of non-discretionary inputs and the selection of direction vectors have a crucial impact on the results of eco-efficiency. Based on the empirical results and our summarized policy implications, we found several deficiencies in the real policies and put forward corresponding policy suggestions for the industry and government. • Existing studies pay little attention to the non-discretionary input factors. • We propose a DEA model to incorporate the non-discretionary input. • This paper investigates the eco-efficiency of Chinese transportation industry. • Based on the empirical results and the existing policies, this paper puts forward several policy suggestions to the government and industry. [ABSTRACT FROM AUTHOR]

In the face of a rapidly ageing population, China's healthcare system is under mounting pressure to meet growing demand for more and better services. This paper aims to identify opportunities to improve the efficiency and quality of healthcare services in China. We first evaluate the healthcare performance of China's 31 provincial regions during the 2005–2019 period. The hospital efficiency is computed by using a window-based super-efficiency composite Data Envelopment Analysis model, while the healthcare quality is evaluated by using a window-based Technique for Order Preference by Similarity to an Ideal Solution method. Then, we investigate the impacts of socioeconomic factors, such as government subsidies, marketization, per capita Gross Domestic Product and demographic structure, on regional healthcare performance by use of regression analysis. The main findings include: 1) The nationwide healthcare performance has improved from 2005 to 2019 in part due to China's rapid economic growth, but more progress has been achieved in improving hospital efficiency than healthcare quality. 2) Government subsidies can improve both regional healthcare quality and hospital efficiency. While marketization can enhance hospital efficiency, private hospitals provide lower quality of care than public hospitals. 3) Regional hospital efficiency and healthcare quality are positively correlated, but a causal relationship cannot be established based on our empirical evidence. Based on our findings, we have the following recommendations for policymaking: 1) The government should increase subsidies to medical institutions in order to improve healthcare quality as well as hospital efficiency. 2) More subsidies should be allocated to regions having a high old-age dependency ratio. 3) More quality control and improvement efforts should be taken at private hospitals. • A comprehensive evaluation of China's provincial healthcare performance during 2005–2019. • Investigation of the socioeconomic determinants of regional healthcare performance. • Examination of the impacts of government subsidies and marketization on regional healthcare performance. • Analysis of the relationship between hospital efficiency and healthcare quality. [ABSTRACT FROM AUTHOR]

The development of higher education institutions (HEIs) is related to the future overall development of higher education in China. Studying the efficiency of provincial HEIs in China has great significance in deepening the reform of higher education evaluation, promoting coordinated regional development, and building a country powerful in its higher education. Based on the Super-SBM method, this paper creatively integrates meta-frontier theory and an index of international exchange and cooperation into an evaluation system for higher education efficiency. Taking 2011–2020 as the sample period, this study conducts a dynamic assessment of the higher education efficiency in 30 mainland Chinese provinces. It explores the differences in production technology in the eastern, central, and western regions, analyzing the environmental factors that affect the efficiency of higher education. The results show that during the sample period, the overall efficiency of higher education in China improved steadily. Efficiency Change is the main driving force. The three regions have significantly different technology gap ratio, and the structure of resource allocation significantly impacts efficiency. Therefore, this study's main recommendations are that the Chinese government should not only deepen the coordinated development of higher education between regions but also pay more attention to solving the problem of unbalanced development between China's geographical regions. At the same time, educational authorities should expand the number of ordinary colleges and universities in the central and western regions, develop non-financial funding sources, and improve the level of refined management of HEIs. • This study measures the efficiency and evolution of China's HESs in the second decade of the 21st century. • It considers the effects of regional heterogeneity on the efficiencies of HESs. • It incorporates higher vocational colleges into HES efficiency evaluation. • The result shows that the efficiency of Chinese HES show obvious geographical characteristics. [ABSTRACT FROM AUTHOR]

To obtain high-quality human resources and to gain advantages in the context of global competition, countries are constantly promoting the development of higher education. Enormous human and financial resources were invested in this "battle". However, the "inputs" consumed by universities are largely ignored. A major issue, evaluating how well a country's universities make use of input resources in their output path, is of economic and social significance. The focus of this study is to embed the concept of capacity utilization in education and to assess the university's performance. We construct an attainable output-oriented capacity utilization measurement model by taking into account the heterogeneity of the region. According to the usage of the input, we divide the decision making units into four areas and identify the causes of inefficiency. Thus, the methodology proposed in this study provides policymakers an applicable tool on differences in educational inputs across regions. To illustrate the method, we conduct an empirical analysis using data from 54 universities directly under the Ministry of Education in China. • By embedding the concept of CU in the education sector, we propose a conceptual theoretical framework and assessing the utilization of university inputs. • We construct an attainable output-oriented CU measurement model by taking into account the attainability of variable inputs. • By dividing decision making units into four types according to the causes of inefficiencies, this paper proposes an CU analysis paradigm. [ABSTRACT FROM AUTHOR]

In recent years, Chinese government and universities have been striving to improve the quality of higher education according to the continuously updated university performance evaluation. The university performance evaluation has played an important role in education reform. As an essential function of university, the research activities show some particular features in China. On the one hand, scientific research activities have parallel interactive network structures. On the other hand, university, as centrally governed institution, faces limited financial support, implying a fixed-sum constraint on government grant funding. However, previous studies have not developed an appropriate method to address the above features, which may lead to biased empirical results. In order to fill the gap of previous studies, this paper intends to provide a novel data envelopment analysis (DEA) approach by considering the shared fixed-sum input in the network DEA model. We first divide the scientific research activity into two sub-systems which interact with each other, and the government grant funding as a shared fixed-sum input is consumed for the two sub-systems. Then, considering the effect of shared fixed-sum input on performance, the minimum amount of input adjustments is calculated to identify the common equilibrium efficient frontier, and the total efficiency is obtained by weighting the sum of sub-system efficiency. Finally, our models are empirically applied to assess the performance of Chinese universities. The main findings show that the overall efficiency of Chinese research universities varies widely, and then some meaningful recommendations for central policymakers are proposed. • We evaluate 58 Chinese research universities by non-parametric frontier analysis. • We consider Chinese research universities as parallel interactive processes. • We address shared fixed-sum inputs in network data envelopment analysis model. [ABSTRACT FROM AUTHOR]

The performance of scientific research system is a key element in the assessment of higher education institutions (HEIs). The scientific research system mainly be constructed by two sub-systems: scientific research achievements production and the transformation of these achievements. Different from prior literature, this paper attempts to evaluate the performance of scientific research system of HEIs from a view of goal congruence. Specifically, it examines how and to what extent such two sub-systems are consistent with the goal of overall scientific research system. To this end, this study employs data envelopment analysis (DEA), a non-parametric frontier analysis approach, to present a goal congruence model which is used to measure the degree of both the overall goal congruence and the internal goal congruence. Then, the proposed model is applied to evaluate the performance of scientific research systems of 40 "first-class" universities and 62 "first-class disciplines" universities in China. Results show that only the scientific research systems of Tsinghua University and Central China Normal University achieve the goal congruence. Finally, both higher education policy recommendations and implications are discussed. • This study examines how to evaluate the performance of Higher Education Institutions (HEIs)based on goal congruence theory. • A two-stage network framework for HEIs is built in the context of high education transformation of research achievements. • A new DEA-based model is proposed to measure the degree of goal congruence between sub-systems and overall system for HEIs. • The real data from 40 "first-class" universities and 62 "first-class disciplines" universities in China are used to empirically validate the proposed model. • Both theoretical implications for performance evaluation and practical implications for HEIs development are discussed. [ABSTRACT FROM AUTHOR]

Technological innovation and low-carbon economy are significant for the high-quality development of China's industrial sectors. However, few scholars combine the two stages closely and discuss their coordinated development. This paper establishes an evaluation index system of technological innovation and low-carbon economy in China's industrial sectors. The technological innovation efficiency, low-carbon economy efficiency, and comprehensive efficiency of technological innovation and low-carbon economy are dynamically investigated by the two-stage data envelopment analysis (DEA) model and the DEA window analysis with 35 subsectors panel data during 1996–2018. The inter-industrial differences in the technological innovation efficiency and low-carbon economy efficiency are considered, and the influencing factors of the comprehensive efficiency of technological innovation and low-carbon economy are studied by the bootstrap truncation regression. The results show that: (1) The development of the technological innovation and low-carbon economy is uncoordinated, and the low-carbon economy efficiency needs improvement; (2) There is heterogeneous of the technological innovation efficiency and low-carbon economy efficiency in the 35 subsectors; (3) The density of science and technology institutions, and the average enterprises scale are positive to the comprehensive efficiency of technological innovation and low-carbon economy, while excessive reliance on technology introduction has a negative impaction. The corresponding suggestions are provided for promoting technological innovation efficiency and low-carbon economy efficiency of industrial sectors. • Establishing an evaluation index system of technological innovation and low-carbon economy in China's industrial sectors. • The coordinated development of technological innovation and low-carbon economy is noticeable. • The affecting factors of comprehensive efficiency of technological innovation and low-carbon economy are studied. • Exploring the win-win path of industrial growth and energy conservation and emission reduction. [ABSTRACT FROM AUTHOR]

This paper presents a framework for analyzing the changes in agricultural labor productivity with regards to the structural, land intensity, and land productivity effects. This approach allows for the residual-free decomposition of data from different levels of aggregation. The logarithmic mean Divisia index was applied for the analysis and a data envelopment analysis model was constructed to identify potential gains in agricultural labor productivity due to the optimization of input use and output production. The proposed approach was applied to the case of China over the period of 1997–2017. Province-level data were used to identify the major driving factors behind agricultural labor productivity change. Land productivity change appeared to be the major source of agricultural labor productivity gains in China. The structural change was rather negligible, suggesting that the reallocation of the agricultural labor force did not add to the agricultural labor productivity growth in China. A frontier analysis indicated that agricultural labor productivity could increase by some 45% on average in case full technical efficiency is achieved. • The paper analyzes the changes of agricultural labor productivity in China. • The Logarithmic Mean Divisia Index and Data Envelopment Analysis are applied. • Land productivity change is the major source of the labor productivity gains in China. • The results indicate the labor productivity could increase by about 45% on average. [ABSTRACT FROM AUTHOR]

To promote manufacturing transformation and upgrading, this paper proposes a comprehensive analytical framework for manufacturing development from an industrial network perspective. We explore the organizational structure of the manufacturing association network based on the industrial network analysis technique and the modern network analysis technique. A new data envelopment analysis (DEA) model, which considers the interrelated and interactive characteristics of various sectors, is used to evaluate the static and dynamic performance of manufacturing sectors combining the Malmquist productivity index (MLI). We adopt this framework to analyze the development of 18 manufacturing sectors in Hubei Province, China, during the 2012–2017 period. Key development sectors play a critical role in the stability and development of the manufacturing system, yet their performance did not show significant improvement during this timeframe. During the implementation of the Made in China 2025 strategy, most sectors followed the transformation path by enhancing technological strength first and technological application capabilities later. The manufacturing industry in Hubei Province suffers from insufficient informatization construction and slow productivity improvement. • A new DEA model that considers the interrelated and interactive characteristics of sectors is proposed. • A comprehensive analysis framework is proposed from an industrial network perspective. • Our analytical framework can depict the manufacturing state in the dimensions of structure and benefits. • The manufacturing structure, transformation path, and performance evolution are analyzed. • We explore the transformation paths of manufacturing sectors during the implementation of the Made in China 2025 plan. [ABSTRACT FROM AUTHOR]

In many real scenarios, all decision-making units (DMUs) fall under the umbrella of a central unit, such as banks, supermarkets and public universities, that has the power to supervise and control them. In such centralized decision-making circumstances, how to allocate fixed resources across DMUs when there is competition for resources has always been an important problem for managers. Data envelopment analysis (DEA) offers a new performance-based solution to resource allocation issues. In this paper, we propose a parallel DEA-based approach to reallocate multi-period resources among all DMUs by treating individual periods (e.g., years) as divisions operating at the parallel level. To balance the goals of the organization and the individual preferences of each DMU in resource allocation, we introduce the concept of cross-efficiency. Hence, we combined the operations of individual periods and the concept of cross-efficiency in one method simultaneously. Such allocations for multi-period resources are more acceptable by both the central manager and the evaluated DMUs. Finally, we assessed the R&D performance of each one of the 61 public universities in China and reallocated government funding resources among them. • This research provides a novel approach to reallocate limited input resources across DMUs and divisions. • The two-step approach is based on the parallel DEA model. • We consider the individual preference of each DMU by using a cross-efficiency concept. • This tool improves all DMUs' total output increment in a certain time period at the current productivity. • The model is applied to allocate the government funding to 61 public universities in China. [ABSTRACT FROM AUTHOR]

To promote manufacturing transformation and upgrading, this paper proposes a comprehensive analytical framework for manufacturing development from an industrial network perspective. We explore the organizational structure of the manufacturing association network based on the industrial network analysis technique and the modern network analysis technique. A new data envelopment analysis (DEA) model, which considers the interrelated and interactive characteristics of various sectors, is used to evaluate the static and dynamic performance of manufacturing sectors combining the Malmquist productivity index (MLI). We adopt this framework to analyze the development of 18 manufacturing sectors in Hubei Province, China, during the 2012–2017 period. Key development sectors play a critical role in the stability and development of the manufacturing system, yet their performance did not show significant improvement during this timeframe. During the implementation of the Made in China 2025 strategy, most sectors followed the transformation path by enhancing technological strength first and technological application capabilities later. The manufacturing industry in Hubei Province suffers from insufficient informatization construction and slow productivity improvement. • A new DEA model that considers the interrelated and interactive characteristics of sectors is proposed. • A comprehensive analysis framework is proposed from an industrial network perspective. • Our analytical framework can depict the manufacturing state in the dimensions of structure and benefits. • The manufacturing structure, transformation path, and performance evolution are analyzed. • We explore the transformation paths of manufacturing sectors during the implementation of the Made in China 2025 plan. [ABSTRACT FROM AUTHOR]

The super-efficiency technique aims to improve the discriminating power of data envelopment analysis (DEA) through re-evaluation after excluding the evaluated object from the reference set. However, the super-efficiency radial network DEA with undesirable production variables faces the infeasibility problem as the traditional DEA. To solve this issue, this paper detects one new origin of infeasibility in network DEA not existing in traditional DEA and provides the necessary and sufficient conditions of infeasibility occurrence. Then, a modified super-efficiency radial network DEA is developed without infeasibility. We apply the modified model to assess the regional sustainability performance in China from 2009 to 2017. Considering the internal connectivity and influences among the economic, environmental, and social dimensions of sustainability, we construct a three-stage network system, i.e., economic growth (EG), waste disposal (WD), and health protection (HP) subsystems. The results show that the regional sustainability performance of China was on a downward trend until 2015 but has improved significantly since then. Besides, the status quo of a regional disparity in sustainability performance is confirmed. The results suggest that the eastern region remains the leader in promoting the regional sustainability of China, the central and western regions are trying to catch up with it, and the northeast region still needs more support from the government to keep pace with the coordinated development of China. • We address the infeasibility of super-efficiency network data envelopment analysis. • One new origin of infeasibility is revealed. • Necessary and sufficient conditions of infeasibility are provided. • A modified super-efficiency model with no presence of infeasibility is proposed. • The modified model is applied to assess China's regional sustainability. [ABSTRACT FROM AUTHOR]

With the growing expenditure on the R&D activities of industrial enterprises above designated size (IEDSs) in China, it is important to evaluate the R&D efficiency of the Chinese IEDSs. However, few studies about R&D efficiency measurement of Chinese IEDSs have considered the internal structure of the R&D production process. To fill this gap, this paper investigates the R&D performance of IEDSs of 30 sample provinces on China's mainland from 2009 to 2014, based on a two-stage data envelopment analysis (DEA) model. The major findings from the empirical results are shown as follows: (i) serious imbalance exists in the R&D resources among Chinese IEDSs of 30 provinces; (ii) there is a decline in the average overall efficiencies after 2012; (iii) there are great differences regarding the performances of R&D activities among the Chinese IEDSs of 30 provinces; (iv) high attention to the R&D activities or strong scientific research atmosphere may promote the R&D efficiency of Chinese IEDSs; and (v) the IEDSs with the relatively high profitability or high government support in terms of R&D activities have relatively poor performance. Based on these findings, several policy suggestions are proposed for the R&D activities of Chinese IEDSs. • Few studies about R&D efficiency evaluation of Chinese IEDSs considered the internal production structure. • We investigate the R&D performance of IEDSs of 30 sample provinces on China's mainland. • A two-stage data envelopment analysis model is used in this paper. • We have several important findings from the empirical results. • Several policy suggestions are proposed for the R&D activities of Chinese IEDSs. [ABSTRACT FROM AUTHOR]

With growing investments in the state key laboratories (SKLs) of China, it is essential to assess the efficiency of the administrative departments regarding managing the SKLs of China. However, few studies have been conducted about the evaluation of the performance of Chinese administrative departments in managing SKLs. To fill this gap, this paper investigates the performance within 22 SKL administrative departments in China, based on a data envelopment analysis cross-efficiency prospect aggregation approach incorporating the risk preference of decision maker. The empirical results show the major findings: (a) serious imbalance exists regarding the investment of 22 SKL administrative departments; (b) there are great differences among the performance of 22 SKL administrative departments; (c) some SKL administrative departments face an insufficient situation regarding the outputs; (d) different risk attitudes of decision maker have the significant impact on the evaluation results of the 22 SKL administrative departments. Based on these findings, we provide several policy suggestions for the development of SKLs in China. • Cross-efficiency aggregation methods generally fail to capture the risk behavior. • We propose a cross-efficiency prospect (CP) function to reflect the risk attitude. • This paper establishes a weighting model to derive the optimal aggregated weights. • A CP aggregation method is developed based on the CP function and weighting model. • An application of state key laboratories in China is presented using the CP method. [ABSTRACT FROM AUTHOR]

This paper aims to measure the evolution of destocking performance of the Chinese Real Estate Industry based on a DEA (Data Envelopment Analysis)-Malmquist approach, which is seldom used in this industry in existing literature. In 2016, the Chinese government introduced a unified national destocking policy to reduce real estate inventory to save the downturn in the real estate market, but the effect was less than expected and led to soaring house prices in first-tier cities. By analysing the destocking performance over the period from 2005 to 2015, we find the following: (1) It is impossible to use a unified policy to effectively address the national destocking issue because of the difference of DMUs' destocking efficiency, input redundancy and total factor productivity score changes. (2) With the current destocking performance and investment status, the government is still ignoring the existing commercial real estate problems. (3) The redundancy of firm assets and staff indicates that zombie firms may exist and risk future unemployment in the real estate industry. (4) Despite the recently repeated government interventions in this industry, destocking performance remains falling since 2008, and problems in other regions is more severe than in central cities. (5) The financial crisis triggered by the US subprime mortgage crisis has had a great impact on China's real estate industry. The destocking performance dropped sharply in 2008, forcing the Chinese government to introduce policies to stimulate the real estate market. Policy recommendations are also put forward based on the findings. • This paper aims to measure the evolution of destocking performance of the Chinese Real Estate Industry based on a DEA-Malmquist approach. • By analysing the destocking performance over the period from 2005 to 2015, we have several important findings, which are useful for policymaking in Chinese real estate industry. • Based on the above findings, policy recommendations are also put forward forpolicy makers. [ABSTRACT FROM AUTHOR]

Macroeconomics has constantly been exposed to socio-economic shocks. The concept of resilience in the economy has been developed to predict these shocks, reduce damages, and recover quickly. This paper proposes a quantitative approach for analyzing macroeconomic resilience due to socio-economic shocks and suggests appropriate actions to improve resilience. In this way, the variables affecting macroeconomic resilience have been identified through the literature review. Next, an integrated indicator of macroeconomic performance based on Data Envelopment Analysis (DEA) has been developed. Finally, the periods of shocks are identified by determining the turning points of that indicator, and an appropriate approach for defining macroeconomic resilience is developed. The proposed approach is applied to three countries of the USA, China, and Iran in different shocks, including global crisis, COVID-19 pandemic, and oil price shock. Eventually, by analyzing the relationships between effective variables on the macroeconomic resilience, using the DEMATEL method, we determine the most important variables to improve macroeconomic resilience, which can be useful for socio-economic planning at a macro level. • An integrated indicator of macroeconomic performance has been developed. • The periods of shocks are identified by determining turning points of that indicator. • The proposed approach is applied to three countries of the USA, China, and Iran. • Global crisis, COVID-19 pandemic, and oil price shocks have been analyzed. • The most important variables to improve macroeconomic resilience have been determined. [ABSTRACT FROM AUTHOR]

Abstract: This paper re-examines a problem of congested inputs in the Chinese automobile and textile industries, which was identified by Cooper et al. [Cooper WW, Deng H, Gu B, Li S, Thrall RM. Using DEA to improve the management of congestion in Chinese industries (1981–1997). Socio-Economic Planning Sciences 2001;35:227–242]. Since these authors employed a single approach in measuring congestion, it is worth exploring whether alternative procedures would yield very different outcomes. Indeed, the measurement of congestion is an area where there has been much theoretical debate but relatively little empirical work. After examining the theoretical properties of the two main approaches currently available, those of Färe et al. [Färe R, Grosskopf S, Lovell CAK. The measurement of efficiency of production. Boston: Kluwer-Nijhoff; 1985] and Cooper et al., we use the data set assembled by Cooper et al. for the period 1981–1997 to compare and contrast the measurements of congestion generated by these alternative approaches. We find that the results are strikingly different, especially in terms of the amount of congestion identified. Finally, we discuss the new approach to measuring congestion proposed by Tone and Sahoo [Tone K, Sahoo BK. Degree of scale economies and congestion: a unified DEA approach. European Journal of Operational Research 2004;158:755–772]. [Copyright &y& Elsevier]

Hospital efficiency and equity in health care delivery are two enduring research topics. Yet little research has been done to examine the relationship between them. This paper studies the impact of hospital efficiency on equity in health care delivery based on a proprietary dataset of hospital characteristics and 630,000 inpatient records from 149 public hospitals in a representative Chinese city. To measure the hospitals' efficiencies, this study takes the hospitals' operational features and case-mix indexes into account, and computes the efficiency levels using data envelopment analysis with bootstrapping. Through regressions that control for a variety of the patients' personal characteristics (e.g., age, disease, residence, hospital visit frequency), this study shows that the gap between hospitalization expenses of urban and rural inpatients in more efficient hospitals is smaller than those in less efficient hospitals. Thus efficiency enhances equity in expenditure between urban and rural patients. But the dwindling urban-rural gap in expenditure is achieved by raising the spending of rural patients, thereby undermining their access to health care. This pattern is more conspicuous in large and sophisticated high-tier hospitals. Further analysis shows that hospital efficiency impacts equity of health care delivery by inducing different lengths of stay and uncovered parts of total expenditure for urban and rural groups. The findings imply that an efficiency-oriented health care policy may lead to social benefit loss. • The link between hospital efficiency and equity of medical expenditure is studied. • Hospital efficiency and urban-rural spending gap show an inverse relationship. • Falling urban-rural spending gap occurs with impaired access from rural patients. • An efficiency-oriented health care policy may lead to social benefit loss in China. [ABSTRACT FROM AUTHOR]

Traditionally, data envelopment analysis (DEA) requires all decision-making units (DMUs) to have similar characteristics and experiences within the same external conditions. In many cases, this assumption fails to hold, and thus, difficulties will be encountered to some extent when measuring efficiency with a standard DEA model. Ideally, the performance of DMUs with different characteristics could be examined using the DEA meta-frontier framework. However, some of these DMUs are mixed-type DMUs that may affiliate with more than one group. Furthermore, the total number of observations of these mixed-type DMUs is limited. This is one of the common problems when studies focus on faculty research performance in higher education institutions. In general, a faculty member is affiliated with a certain department, and if the departmental assessment policy is not suitable for faculty members who are involved in interdisciplinary research, their performance could be underestimated. Therefore, the proposed model is an extension of the DEA meta-frontier framework that can assess the performance of mixed-type DMUs by constructing the reference set without the same type of DMUs. In this paper, the scientific research efficiency of faculty members at the Inner Mongolia University is used as an example to provide a better understanding of the proposed model. The proposed model is intended to provide a fair and balanced performance assessment method that reflects actual performance, especially for mixed-type DMUs. • To assess the performance by constructing reference set without the same type of DMUs. • The proposed model is appropriate when mixed-type DMUs are involved. • Provide a fair and balanced performance assessment method. [ABSTRACT FROM AUTHOR]

As significant strategic players in China's economy, high-tech industries need to evaluate and analyze the technological innovation activities from a system point of view to understand and improve their technological innovation efficiency and, thereby, promote their development. Different high-tech industries have different characteristics and thus benefit from different industrial development policies. However, few studies to date have discussed this issue from a systematic perspective. In this study, technological innovation activities are divided into a research and development (R&D) stage and a commercialization stage. A high-tech industrial evaluation framework of technological innovation efficiency based on two-stage network data envelopment analysis (DEA) is constructed with shared inputs, additional intermediate inputs, and free intermediate outputs. Our empirical results indicate that the overall efficiency of most industries is relatively low and the differences between the five high-tech industries (i.e., sub-sectors) we examined are large. The Spearman correlation shows that overall efficiency and R&D efficiency are more correlated than overall efficiency and commercialization efficiency. Additionally, R&D has better average efficiency. The sub-sector with the highest average efficiency is computers and office equipment, and the one with the lowest average efficiency is medicines. These findings indicate the inadequacy but potential for breakthroughs in the evolution of high-tech industries in China. The analysis proves that it is necessary to create different industrial policies to encourage effective progress in certain high-tech industries, and some guidelines for doing so are provided. • Assessment framework of the technological innovation efficiency of China's high-tech industries is developed. • A two-stage network data envelopment analysis approach is used in this paper. • Significant findings can be obtained from empirical evidence. • Several policy suggestions are proposed for China's high-tech industries. [ABSTRACT FROM AUTHOR]

China's transport sector has been attracting great attention for its excessive energy consumption and ever-increasing pollution emissions. Thus, reducing energy intensity is one of the top priorities of China's ongoing transport upgrade. In this paper, by establishing a panel data regression model derived from the Cobb–Douglas cost function, we focus on investigating the impacts of energy price and transport productivity on transport energy intensity at the national and regional levels. The study uses the provincial panel data for 2005–2016 to perform regression analysis. The results show that: (1) energy price has a significantly negative effect on transport energy intensity in the whole China and the eastern region, whereas it has no significant impacts in the central and western China. (2) Improvements in transport productivity can effectively decrease transport energy intensity in the whole China and the three major regions. (3) Applying an extended data envelopment analysis (DEA) approach, we decompose transport productivity into four components (i.e., technical change, technology gap change, scale efficiency change, and pure efficiency change) and further differentiate their impacts in different regions. The results indicate that these four components have substantially different impacts in each region. These results provide some valuable insights for policymakers and enterprise entities aiming to adopt measures to reduce energy intensity and achieve sustainable development in China's transport sector. • The regional heterogeneous impacts of energy price and productivity on transport energy intensity in China are examined. • The transport productivity change is further decomposed into four components. • Energy price has a significantly negative effect on transport energy intensity in eastern region. • The impacts of four components of transport productivity change on energy intensity vary by region. [ABSTRACT FROM AUTHOR]

Since the "ZTE ban", the development of the integrated circuit (IC) industry has attracted wide attention, especially in China. The performance evaluation and prediction of the IC industry is of great significance for promoting the development of this industry. In this paper, a hybrid method is proposed to study the performance of the IC industry from the perspectives of evaluation and prediction, which is unique as it evaluates the performance at past, current and future terms simultaneously. Firstly, a dynamic data envelopment analysis model is used to explore the performances of the IC industry between China and the United States from 2008 to 2017. Furthermore, in order to figure out the main sources of the inefficiency, the projection analysis is implemented based on the performance scores. Then, the grey model GM(1, 1) is employed to predicted the performance of China's IC industry from 2018 to 2022, so as to point out the progressive direction for the future development of the industry. The empirical results show that: (1) as far as performance is concerned, there is a significant gap between China and the United States in the IC industry during 2008–2017, among which the most obvious gap is occurring in "IC packaging & testing", followed by "IC design" and "wafer fabrication"; (2) the primary cause of the low performance in China's IC industry is the redundancy of the inputs, especially in "IC packaging & testing", and the redundancy problem of labour investment is found to be the most serious; (3) according to the predicted results, the IC industry in China will steadily increase in terms of the performance scores in general, and the performance improvement of "IC packaging & testing" is relatively obvious, while the other two categories have a slight range of growth. Finally, the policy implications of improving the performance of the IC industry are put forward. • Develop a hybrid method to evaluate the performance at past, current and future terms, simultaneously. • Evaluates and analyzes the performance of the IC industry in China and the United States during 2008–2017. • Identifies the sources of operational inefficiency of the IC industry by a projection analysis. • Predicts the performance of the IC industry in China from 2018 to 2022. [ABSTRACT FROM AUTHOR]