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Background: Primary care is widely seen as a core component of resilient and sustainable health systems, yet its efficiency is not well understood and there is a lack of evidence about how primary care efficiency is associated with health system characteristics. We examine this issue through the lens of diabetes care, which has a well-established evidence base for effective treatment and has previously been used as a tracer condition to measure health system performance., Methods: We developed a conceptual framework to guide the analysis of primary care efficiency. Using data on 18 European countries during 2010-2016 from several international databases, we applied a two-stage data envelopment analysis to estimate (i) technical efficiency of primary care and (ii) the association between efficiency and health system characteristics., Results: Countries varied widely in terms of primary care efficiency, with efficiency scores depending on the range of population characteristics adjusted for. Higher efficiency was associated with bonus payments for the prevention and management of chronic conditions, nurse-led follow-up, and a financial incentive or requirement for patients to obtain a referral to specialist care. Conversely, lower efficiency was associated with higher rates of curative care beds and financial incentives for patients to register with a primary care provider., Conclusions: Our results underline the importance of considering differences in population characteristics when comparing country performance on primary care efficiency. We highlight several policies that could enhance the efficiency of primary care. Improvements in data collection would enable more comprehensive assessments of primary care efficiency across countries, which in turn could more effectively inform policymaking., (© 2023. The Author(s).)

Background: An international comparison of health system performance is a popular tool of health policy analysis. However, the efficiency evaluation of health systems is a practical example of an international comparison in which non-homogeneity is expected. The objective of this paper is to evaluate the efficiency of health systems by models in which a degree of non-homogeneity among countries is considered., Methods: We study the problem of non-homogeneity of health systems in the theoretical framework of the data envelopment analysis (DEA), which is a popular method of efficiency evaluation with hundreds of applications from various fields. DEA assume the homogeneity of production units and the homogeneity of the environment in which the production units operate. Hence, we compiled a summary of 14 recommendations on how to deal with the non-homogeneity in the DEA models. The analysed sample includes 38 OECD member countries. The data are from the year 2019., Results: As an example, we evaluated the health system efficiency of the Czech Republic. We used the DEA models with the neighbourhood measure of distance and the constraint limiting the comparison of countries with different levels of economic development. The health system inputs were the numbers of physicians, nurses, and hospital beds. In the production of the intermediate outputs (doctor consultations, inpatient care discharges), the Czech Republic should look at Poland, Slovakia and Slovenia. In the production of health outcomes (life expectancy), the peer countries are France, Italy and Switzerland., Conclusions: The results of the DEA analysis are only indicative because no single analytical method can determine whether a health system is better or worse than others. We need to combine different methods, and DEA is one of them. We consider DEA as an exploratory method, not a method providing definitive answers., (© 2023. The Author(s).)

The Indonesian government has evaluated the research performance of universities, whose measurement process is projected into resources, management, outputs, and revenues to determine the provision of incentives, grants, and program funding to universities. However, efficiency calculations have shown that the outputs and competition-based incentives that drive scientific productivity are more complex. The most competitive systems must also be the most productive when considering resources. This study aimed to analyze the research efficiency in the Indonesian higher education system. The efficiency was analyzed by maximizing the 13 product outputs from the research budget and university staff. The result was then compared with the existing performance measurement analysis. Data Envelopment Analysis (DEA) was used to evaluate the efficiency based on the data of 47 universities in the Mandiri cluster and 144 in the Utama cluster for the 2014-2018 period. These findings showed that about 68% of universities have an efficiency value of 1 for the Mandiri group, almost 40% in the Utama group, and 41% for the two groups combined. Additionally, this study compared the efficiency analysis and the impact of the performance evaluation. The comparison showed that adding efficiency or productivity factors in the performance evaluation assessment produced a more accurate result.

Studying the economic efficiency of freshwater fishery breeding is of great significance to the sustainable utilization of freshwater fishery resources. Based on the nonparametric research method, this study combines the super-SBM data envelopment analysis (DEA) model with the global Malmquist index (GMI) to evaluate the total factor productivity of freshwater fishery breeding (FTFP) of China from 2004 to 2019, so as to reflect the economic efficiency of freshwater fishery breeding in China. The empirical results show that (1) in general, FTFP has reached the effective level in China with a fluctuating trend in time, but it lacks a breakthrough value. (2) In China, FTFP shows significant differences in space, and its spatial development pattern has gradually evolved from "high in the south and low in the north" to "high in the north and low in the south." (3) The change of FTFP in China mainly depends on technological progress, while the change of scale efficiency and pure efficiency has no significant impact on it. (4) When environmental factors are taken into account, the FTFP value will decrease as a whole. Therefore, it is very important to optimize the structure of freshwater fishery breeding and strengthen the construction of aquatic science and technology system., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Environmental degradation has attained much attention from researchers and policymakers at national and global levels. The ever-increasing energy use in production methods is considered one of the fundamental reasons for environmental degradation. The concept of environmental efficiency in the wake of sustainable growth evolved in the last three decades. The present study has been designed to estimate environmental efficiency using the Malmquist-Luenberger productivity index (MLI) using annual data from 43 Asian countries from 1990 to 2019. The MLI is an established econometric approach to estimate cases where input variables are used to get output variables in desirable and undesirable forms. Labor, capital, and energy consumption are input variables, while carbon dioxide (CO 2 ) emissions (undesirable variable) and gross domestic product (undesirable variable) are taken as output variables. The results suggested that, on average, environmental efficiency has decreased by 0.3% over the period in selected Asian countries. Cambodia, Turkey, and Nepal have the highest total factor productivity (TFP) output growth rate on average among 43 Asian countries. These countries are excellent examples of sustainable development that balances environmental protection and efficiency. On the other hand, Kuwait, Mongolia, and Yemen showed the least TFP growth. The study also employed unconditional and convergence tests where the countries' conditional convergence is based on foreign direct investment, population density, inflation, industrialization, and globalization. Some policy implications for Asian countries are also discussed at the end of the study., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: China's primary health care system has undergone major changes since the new round of medical reform in 2009, but the current status of primary health care institution service efficiency is still unsatisfactory. The purpose of this study is to compare and evaluate the China's primary health care institution service efficiency and provide a reference for improving the efficiency and promoting the development of primary health care institution., Methods: Based on panel data of 31 provinces (municipalities directly under the central government and autonomous regions) in mainland China from 2011 to 2020, using the super efficiency slack-based measure-data envelopment analysis model, to analyze the data from a static perspective, and the changes in the efficiency of primary health care services were analyzed from a dynamic perspective by using the Malmquist index method. Spatial autocorrelation analysis method was used to verify the spatial correlation of primary health care service efficiency among various regions., Results: The number of Primary health care institutions increased from 918,000 in 2011 to 970,000 in 2020. The average primary health care institution service efficiency in the northeastern region including Jilin (0.324), Heilongjiang (0.460), Liaoning (0.453) and northern regions such as Shaanxi (0.344) and Neimenggu (0.403) was at a low level, while the eastern coastal regions such as Guangdong (1.116), Zhejiang (1.211), Shanghai (1.402) have higher average service efficiency levels. The global Moran's I showed the existence of spatial autocorrelation, and the local Moran's I index suggested that the problem of uneven regional development was prominent, showing a contiguous regional distribution pattern. Among them, H-H (high-efficiency regions) were mainly concentrated in Jiangsu, Anhui and Shanghai, and L-L regions (low-efficiency regions) were mostly in northern and northeastern China., Conclusion: The service efficiency of primary health care institution in China showed a rising trend in general, but the overall average efficiency was still at a low level, and there were significant geographical differences, which showed a spatial distribution of "high in the east and low in the west, high in the south and low in the north". The northwestern region, after receiving relevant support, has seen a rapid development of primary health care, and its efficiency was steadily improving and gradually reaching a high level. The average primary health care institution service efficiency in the northeastern region including the northern region of China was at a low level, while the average efficiency in the eastern coastal region and some economically developed regions was high, which also verifies the dependence and high symbiosis of primary health care institution service efficiency on regional economy., (© 2023. The Author(s).)

Introduction: Care services provided by long-term care facilities (LTCFs) are currently plagued by care resource shortages and insufficient utilization. The analysis on the temporal and spatial distribution of human resources and non-human resources in LTCFs, could provide a basis to optimize resource allocation and efficient use of limited resources., Methods: This study used data envelopment analysis to comprehensively evaluate the efficiency of human and non-human resources in different time spans and regions. The spatial Markov chain and spatial correlation were also applied to explore the heterogeneity of and correlation between the service efficiency of LTCFs in different regions and then analyzes the influencing factors of efficiency using Tobit regression model., Results: The quantitative changes in the service efficiency of LTCFs in various provinces showed a "W" shape in two periods, ranging from 0.8 to 1.6. The overall efficiency of LTCFs in different regions had a lower probability to achieve short-term cross-stage development. Non-human resource efficiency presented a "cluster" distribution mode, demonstrating a great probability to achieve cross-stage development, which might be due to the regional disparities of economic development and land resource. Tobit regression analysis results also showed that the comprehensive efficiency of LTCFs decreases by 0.210 for every square increase in construction space variation. However, human resource efficiency had a significant spatial polarization, making it difficult to develop area linkages. The reason for this might be the nursing staff have relatively stable regional characteristics, weakening the inter-provincial spatial connection. We also found that female workers, aged between 35 and 45 can positively affect the efficiency of LTCFs. Those staff stay focused and improve their skills, which might improve the efficiency of LTCFs. So improving technology and service quality changes by increasing female workers, aged between 35 and 45, and avoiding excessive construction space changes can enhance the growth of service quality and personnel stability of LTCFs., Conclusion: There is an urgent trade-off among staff quality improvement, resource reduction, construction excessive and substantial regional variation in efficiency. Therefore, strengthening policy support to encourage inter-regional initiatives, particularly highlighting the development of human resources interaction and common development is urgent., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhang, Han and Fang.)

The study's main objective is to assess and evaluate the models of socioeconomic determinants of environmental efficiency in the European Union countries from 2010 to 2018. The two-step data envelopment analysis is implemented, using both constant and variable returns to scale assumption. Moreover, the results of the model of environmental efficiency determinants from four areas-tourism, circular economy, energy and resources use and quality of life-are presented. Based on our findings, it can be concluded that it is necessary to develop the concept of sustainable tourism because the enormous increase in foreign tourists harms environmental efficiency. It is also necessary to gradually transform economies into less energy-intensive towards knowledge-based economies. The positive impact of measures related to the pain of the circular economy was also demonstrated. In conclusion, we present several recommendations for EU policies concerning the current economic and energy situation., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Innovation, human capital, economic, and environmental nexus is essential in sustainable development. The Middle East and North Africa (MENA) is an emerging market with the potential to transcend the dilemma of attaining economic and environmental sustainability. Data envelopment analysis through the Malmquist-Luenberger productivity index is utilized to estimate MENA country's innovation, human capital, economic, and economic sustainability efficiency and productivity. Results indicate an upward trend in efficiency, with a 26% increase in average efficiency between 2017 and 2019 compared to 2011 and 2016. However, there is variation in efficiency between countries. The decomposition of the productivity index into technical change and technological change indicates that the efficiency growth in 2017-2019 could be attributed to technical improvement than technological increase. However, there is a shift to more technological progress than technical increase. Study shows that developing human capital and capacity is as integral to sustainable development as innovation advancement. Strategies to simultaneously augment human capital and innovation towards sustainable development are presented., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

WHO's Health Systems Performance Assessment framework suggests monitoring a set of dimensions. This study aims to jointly assess productivity and quality using a treatment-based approach, specifically analyzing knee and hip replacement, two prevalent surgical procedures performed with consolidated technology and run in most acute-care hospitals. Focusing on the analysis of these procedures sets out a novel approach providing clues for hospital management improvements, covering an existing gap in the literature. The Malmquist index under the metafrontier context was used to estimate the productivity in both procedures and its decomposition in terms of efficiency, technical and quality change. A multilevel logistic regression was specified to obtain the in-hospital mortality as a quality factor. All Spanish public acute-care hospitals were classified according to their average severity attended, dividing them into three groups. Our study revealed a decrease in productivity mainly due to a decrease in the technological change. Quality change remained constant during the period with highest variations observed between one period to the next according to the hospital classification. The improvement in the technological gap between different levels was due to an improvement in quality. These results provide new insights of operational efficiency after incorporating the quality dimension, specifically highlighting a decreasing operational performance, confirming that the technological heterogeneity is a critical question when measuring hospital performance.

Objectives: This study aimed to analyze the efficiency levels of oral and dental health centers (ODHCs) affiliated to the Ministry of Health from the perspective of the development levels in the regions., Methods: Within the framework of this study, the efficiencies of 127 ODHCs are evaluated with the data envelopment analysis based on Charnes, Cooper, Rhodes (CCR); Banker, Charnes, Cooper (BCC); and scale efficiency methods., Results: It is found that CCR, BCC, and scale efficiencies of the 42 ODHCs located in the first region, the highest development region, are efficient by 31%, 50%, and 38% whereas 13%, 26%, and 26% of other 85 ODHCs located in other regions are efficient, respectively. Additionally, the average efficiency scores of 42 ODHCs in the first region by CCR (0.82), BCC (0.89), and score efficiency (0.93) are much higher than the average efficiency scores of 85 ODHCs in other regions by CCR (0.73), BCC (0.80), and scale efficiency (0.92)., Conclusions: According to the findings, it is considered that the individuals from the first region use the oral and dental healthcare more than the individuals do in other regions because the access to oral and dental healthcare is higher in the first region and the individuals living in this region have better predisposing and enabling factors. The study results are thought to present evidence-based information to health policy makers regarding the regional planning of oral and dental healthcare., (Copyright © 2022 International Society for Health Economics and Outcomes Research. Published by Elsevier Inc. All rights reserved.)

With increasing global awareness of sustainable development and environmental protection, the importance of green supplier selection has become widely recognized. Recently, more and more literature focus on the green supplier selection issue and measurement of supplier performance; the measurement indicators mainly defined two sets of criteria, including management criteria and green criteria. A novel methodology based on data envelopment analysis (DEA) has been developed, which is effective for solving multi-criteria decision problems in supplier selection and evaluating the performance of a set of homogeneous decision-making units (DMUs). To solve the green supplier selection problem, previous studies apply the DEA method by dividing management criteria as inputs and green criteria as outputs. This paper aims to propose a DEA-type green supplier selection methodology by considering the management criteria and green criteria. Unlike the previous method, we define a reasonable and effective division of measurement indicators, where management criteria consist of input variables, desirable and undesirable output variables, while green criteria consist of desirable and undesirable output variables. We also provide an improved model with multi-criteria and multi-objective programming by considering DEA efficiency decomposition, which evaluates management, green, and overall efficiency of candidate suppliers simultaneously. The multi-criteria decision model will help companies to select the best green supplier. To demonstrate the applicability and effectiveness of our proposed model, we present a numerical example at last., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In this study, we analyze the unified healthcare efficiency in China at the regional level from 2009 to 2019. To accurately evaluate the evolution of unified efficiency from both static and dynamic perspectives, we combine the non-radial directional distance function and the meta-frontier method to evaluate the unified healthcare efficiency and its dynamic changes. This new approach allows for regional heterogeneity and non-radial slack simultaneously. The decomposition of the meta-frontier non-radial Malmquist unified healthcare efficiency index (MNMHEI) can be used to identify the driving factors of dynamic changes. The results show that the unified healthcare efficiency in eastern China is generally higher than that in non-eastern China from the static perspective, implying significant regional differences. Moreover, the unified efficiency in both eastern and non-eastern regions shows similar time trends and reaches the maximum in 2012. From the dynamic perspective, the unified healthcare efficiency increases annually by 2.68% during the study period. This increase in eastern China as a technology leader is mainly driven by technological progress, whereas the increase in non-eastern China is mainly driven by a better catch-up effect. In addition, the impact of the reform on the non-eastern region is more significant for the decreasing technology gap, the stronger growth momentum of technological progress, and global innovative provinces., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Guo, Zhang and Fu.)

This study aims to measure the ability of 29 countries in producing competitive products and services that fulfill individual needs and improve the level of welfare with less utilization of natural resources. We build a two-stage network production process model to investigate the ecology efficiency and social welfare efficiency of the countries and then further discriminate the efficient countries in post-analysis. The two-stage network directional distance function is applied to assess the efficiencies of countries, and the network-based ranking approach is used to further discriminate the efficient countries following the panel data between the years 2013 and 2016. Results show that Poland and Spain are strongly referenced by other countries in the ecology stage, whereas Bulgaria, the United States, and Sweden are leaders in the social welfare stage. A remarkable observation is an absence of countries' efficiency in both ecology and social welfare efficiencies. Most of the 29 countries have lower efficiency in the social welfare stage than in the ecology stage. This study suggests the strengths and highlights the weaknesses of the countries to help the governments efficiently improve and operate their countries.

As a key choice for human sustainable development, green development is also one of China's five major vision points. To explore the level of green development in China since it was first written into national documents in 2011, this paper applies an improved non-radial distance function based on Data Envelopment Analysis method to analyze the progress against the development targets set in related national documents. The results show that: (1) China's green development efficiency has kept increasing in 2011-2017. (2) The growth in green development efficiency was significantly higher in the 13th Five-Year Plan period compared to the 12th Five-Year Plan period. (3) The green development efficiency shows a decreasing trend from south to north, east of the Hu line. This study provides a more practical idea for evaluating the quality of green development in mainland China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

This paper investigates the impact of several comprehensive risks such as credit risk, capital risk, liquidity risk, and insolvency risks on Pakistani banks' technical efficiency to assess the nexus between environmental investments with technical efficiency of banks. It also probes into the effect of competition among the Pakistani banks on technical efficiency. The data envelopment analysis (DEA) CCR and BCC models are used to estimate technical, purely technical, and scale efficiencies of the Pakistani banks. The Lerner index measures the banking competition. For estimation, the bootstrap truncated regression is used as an econometric technique. The robustness of results is cross-checked by using an alternative econometric technique (fractional logit regression) and an alternative competition measure (Boone indicator). The study revealed that capital risk has a positive impact on scale efficiency and insolvency risk has a negative impact on technical and pure technical efficiencies. Similarly, there is a positive significant relationship between technical efficiency and environmental investment. Furthermore, the competition has a significant negative effect on Pakistani banks' technical and pure technical efficiencies. The results suggest that the efficiency of the Pakistani banks is significantly affected by bank size, taxation, diversification, operational cost management, banking development, trade openness, and infrastructure development, which ultimately promotes environmental efficiency and protection. The comparative study indicates that the state-owned banks have higher technical, pure technical, and scale efficiencies than the private, foreign, and Islamic banks., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Aiming to assist the environmental sustainability of the Brazilian Amazonian agriculture, this article developed an eco-efficiency index, indicating the possible limits to maximize economic and environmental objectives, taking into account the best practices in the municipalities of the region. Shadow prices of degraded areas and forest preservation were also estimated using data envelopment analysis with directional distance functions. The results indicate that, on average, the analyzed municipalities are able to expand the production and the forest areas by 38% and reduce degraded areas and their inputs in the same proportion. The shadow prices allowed the estimation of the annual opportunity cost of the degraded areas and the preservation of the forest on the farms. The first, US$ 3,131,571, represented 0.04% of the annual output value, indicating that the internalization of that cost should be a low burden for the eco-efficient producer. The second, the total cost of preserving 80% of the area of property, represented US$ 120,890,662 or 1.7% of the annual income of the biome producers studied. Therefore, the main conclusion of this work is that the internalization of negative and positive externalities of agricultural production in the Amazonian biome does not make agricultural production economically unfeasible in the region. In addition, the reimbursement of damages avoided by carbon sequestration, through the Clean Development Mechanism (CDM) established by the Kyoto Conference, should further increase the economic and environmental sustainability of agriculture in the area., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Improving the level of public sports services enhances citizens' physical fitness by implementing the national fitness program. A systematic and scientific efficiency evaluation is a prerequisite for optimizing and improving the level of public sports services in China. Based on data of the Chinese Statistic Yearbook, this study adopted the three-stage data envelopment analysis (DEA) model to measure and analyze the efficiency of public sports services in 31 provinces in China in 2016. To analyze the efficiency of public sports services, technical efficiency was decomposed into pure technical efficiency and scale efficiency. Simultaneously, environmental variables were added to improve accuracy. The results showed that scale efficiency was overestimated, and external technical efficiency was underestimated, before the elimination of external factors and environmental variables. Environmental factors significantly impacted the efficiency of public sports services. Regional gross domestic product (GDP) had a potentially positive impact, while population size partially restricted public sports service efficiency. After eliminating the impact of environmental and random factors, the comprehensive efficiency, pure technical efficiency, and scale efficiency of public sports services all showed improvement in varying degrees. The results provide beneficial insights for the formulation of rational improvement policies for public sports services.

Chinese listed companies play a vital role in national economy, which has contributed more than half of the gross domestic product. But the environmental pollution existed in the production and operation of companies has been ignored, so an objective and comprehensive efficiency assessment of Chinese listed companies were urgent. This paper constructed an index system based on green perspective, employed a super-efficiency slacks-based measure DEA (SBM-DEA) model considering undesirable outputs to assess the sustainability efficiency of Chinese listed companies. The results indicated that (1) the green sustainability efficiency of listed companies needed to be greatly improved. The average efficiency score of samples was 0.461 over 3 years, so the improvement potential was about 53.9%, only 23 companies were relatively effective. (2) The sustainability efficiency of companies has shown a slow upward trend in volatility since 2017, the non-daily consumer goods sector was the most efficient, while utilities were relatively inefficient. (3) When efficient and inefficient companies were compared, the latter were found to have significant input surplus, especially in water consumption. (4) The analysis of sensitivity on inputs and outputs showed that attention should be paid to water consumption and greenhouse gas emissions. (5) Spearman non-parametric test verified that company size and debt-paying ability were the implicit factors affecting company sustainability efficiency. The results of performance evaluation can not only provide a potential reference for the operation and management of listed companies in China, but also have guiding significance for local governments to strengthen the supervision of companies., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Thanks to the booming industry, China has made a huge economic achievement during the past several decades. However, it is suffering severe environmental and sustainable problems now. To find a sustainable development path, it is necessary to assess Chinese industrial energy and environment productivity and explore the contributing reasons. It is known that the technical change is the one power that drives the growth of the industrial productivity. Nevertheless, the technical change bias of Chinese industrial energy and environment productivity has rarely been analyzed, such that the secrets of Chinese industrial energy and environment productivity cannot be further uncovered. Thus, in this paper, we first propose a global DEA-Malmquist productivity index to evaluate the industrial energy and environment productivity of China and then figure out the Chinese industrial technical change biases by relaxing the Hicks' neutral assumption and decomposing the industrial technical change. We find out that both the global DEA-Malmquist productivity and the technical change are increased. Furthermore, the technical change drives the improvement of the global Malmquist productivity, but the technical progress is mainly driven by labor, energy consumption and CO 2 emission biases. A multinomial logistic model is employed to find out the reasons for these biases. It finds that (1) the economic foundation has a significant positive impact on labor bias, while the infrastructures have negative impacts on labor bias. (2) CO 2 emission bias is influence by energy prices positively. (3) The energy prices and the energy consumption structure have a negative influence on labor and energy bias, but the cost of curbing air pollutants and the size of the firm influence labor and energy bias positively. (4) The infrastructures and energy prices affect energy and CO 2 emission bias positively, and the economic foundation and the size of the firm have negative impacts on energy and CO 2 emission bias., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper investigates the efficiency and total factor productivity (TFP) growth of the Pakistani banking industry and determines the impact of risk and competition on the efficiency and TFP growth. The data envelopment analysis (DEA)-based Malmquist productivity index is used to measure efficiency and TFP growth of the Pakistani banking industry. The generalized method of moments (GMM) model is applied to observe the impact of risk and competition on efficiency and TFP growth. The motivation behind the use of GMM model is its ability to overcome unobserved heterogeneity, autocorrelation, and endogeneity issues. The results of the study show that the credit and liquidity risks have positive while insolvency risk has negative effect on the efficiency and TFP growth. The competition leads to improve technological efficiency but declines the technical efficiency growth. Among other explanatory variables, operational cost management, banking sector development, GDP growth rate, and infrastructure development show significant relationships with various efficiencies and TFP growth. The banks also facilitate for the purchase of carbon-intensive products in order to reduce carbon emissions. Strong banking development successfully allocate their financial resources for the development of energy-efficient technology while banking sector development is found to be negatively related with environmental sustainability. The strong banking sector possesses a significant negative influence on carbon reduction and environmental degradation.

This study aims to evaluate the level of technical efficiency of companies that perform the integrated management of basic sanitation in Brazilian municipalities. A Multiple Data Envelopment Analysis (M-DEA) model was applied to estimate the performance of water supply and sewage services in 1628 municipalities covering more than 56% of the Brazilian population, identifying the factors that most influence the efficiency of the sector in the years 2008 and 2016. The M-DEA methodology is an extension of Data Envelopment Analysis (DEA) with multiple DEA executions considering all combinations of inputs and outputs to calculate efficiency scores. The methodology reduces possible biases in the selection of resources and products of the model, ability to support decision-making in favor of improvements in the sector's efficiency based on national regulatory framework. The analyses show that the companies analyzed can increase their operating results and attendance coverage by more than 60%, given the current levels of infrastructure, human and financial resources in the sector. Based on the simulation of potential efficiency gains in Brazilian basic sanitation companies, the estimates show that the coverage of the population with access to sanitary sewage would go from the current 59.9% to 76.5%. The evidence found provides indications to subsidize sanitation management in the country at the micro-analytical level, enabling a better competitive position in the sector for the integrated management of basic sanitation and its universalization in Brazil., Competing Interests: The authors declare no conflict of interest.

Water companies consume up to 8% of global energy demand, at billions of dollars' cost. Benchmarking of performance between utilities can facilitate improvements in efficiency; however, inconsistencies in benchmarking practices may obscure pathways to improvement. The aspiration was to conduct an unbiased efficiency comparison within a sample of 17 water only companies and water and sewerage companies in England and Wales, accounting for exogenous factors, whilst evaluating the accuracy of common proxies. Proxies were tested, and bias-corrected energy and economic efficiency scores with explanatory factors were analysed using a double-bootstrap data envelopment method. Bias correction altered the rankings of two companies for energy efficiency only. Results imply that on average, companies could reduce energy inputs by 91.7%, and economic inputs by 92.3%, which was symptomatic of the companies specialising in drinking water supply considerably out-performing combined water and sewerage companies. As exogenous influences were likely to be a factor in the disparity between the companies, five indicators were evaluated. The results varied but of note were average pumping head height, which displayed a significant negative effect for energy efficiency, and proportion of water passing through the largest four treatment works, that exhibited a significant negative effect on economic efficiency. Within proxy performance, population served for drinking water was an adequate replacement for volume of water produced, with results matching the core variable apart from two companies changing rank in the economic analysis. Conversely, length of water mains performed poorly when replacing capital expenditure, implying companies were on average 12.6% more efficient, resulting in ten companies changing their rank and causing explanatory variables to contradict direction of influence and significance. The findings contribute new insights for benchmarking, including how different types of water companies perform under bias-correcting methods, the degree to which factors affect efficiency and how appropriate some proxies are., Competing Interests: Declaration of competing interest None., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The results of the analysis of water utility performance studies based on data envelopment analysis (DEA) can be very sensitive to the methodological approach and the variables employed. This study investigates approaches and variables for developing countries in order to identify an adequate model for universal access. Three models were developed and compared. The first used traditional variables, the second considered the quality of service variables, and the last are expanded on the second by incorporating the realization of the human right to water into efficiency estimation. Methodological approaches comprising the variable returns to scale DEA (most common for developing countries) and slack-based directional distance function (employed in this study) were also compared. The case study of 77 Brazilian water utilities suggests that a model that incorporates the objective of universal access in the efficiency estimation changes substantialy utility efficiency scores. Therefore, utilities that make investments to reach the universal access can be penalized since traditional models incorporate the expenses, but fail to capture the results. The research conclusions suggest that approaches and variable choices are likely to impact on the analysis results, misrepresenting them regardless of the purpose for using DEA in the study., Competing Interests: Declaration of competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Higher education has always played an important role in promoting economic and social progress. With the rapid development of economy, China's higher education has entered a new stage and made a series of extraordinary achievements. However, the uneven development of higher education has become a critical factor restricting China's overall progress. In this paper, we propose Data Envelopment Analysis (DEA) approach to evaluate the performance of higher education resource utilization from the perspective of provincial level. In addition, we assess productivity changes of each province with the help of Malmquist Productivity Index (MPI). Further, by considering the enrollment quota as a special kind of resource, we construct a more reasonable allocation scheme, while keeping the total number of newly added enrollment quota unchanged in the next year. Finally, according to the results, some suggestions are put forward to help the Chinese government better solve the unbalanced development of higher education among provinces., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objectives: The Chinese government has greatly increased funding for disease control and prevention since the 2003 Severe Acute Respiration Syndrome crisis, but it is also concerned whether these increased resources have been used efficiently to improve public health services. We aimed to assess the efficiency of county-level Centers for Disease Control and Prevention (CDCs) of China and to identify strategies for optimising their performance., Methods: A total of 446 county-level CDCs were selected based on systematic sampling throughout China. The data envelopment analysis framework was used to calculate the efficiency score of sampled CDCs in 2010. The Charnes, Cooper and Rhodes (CCR) model was applied to calculate the overall and scale efficiency, and the Banker, Charnes and Cooper (BCC) model was used to assess technical efficiency. Models included three inputs and seven outputs. A projection analysis was conducted to identify the difference between projection value and actual value for inputs and outputs., Results: The average overall efficiency score of CDCs was 0.317, and the average technical efficiency score was 0.442 and 88.3% with decreasing returns to scale. Projection analysis indicated that all seven categories of outputs were underproduced. CDCs in the eastern region tended to perform better than CDCs in the middle and the western region., Conclusions: Most county-level CDCs in China were operated inefficiently. Emphasis should be put on increasing staff and general operating expenses through current governmental funding, upgrading healthcare providers' competencies and enhancing the standardisation of operational management, so that CDCs could utilise their resources more efficiently., (© 2016 John Wiley & Sons Ltd.)

This paper presents an integrative framework to evaluate ecommerce website efficiency from the user viewpoint using Data Envelopment Analysis (DEA). This framework is inspired by concepts driven from theories of information processing and cognition and considers the website efficiency as a measure of its quality and performance. When the users interact with the website interfaces to perform a task, they are involved in a cognitive effort, sustaining a cognitive cost to search, interpret and process information, and experiencing either a sense of satisfaction or dissatisfaction for that. The amount of ambiguity and uncertainty, and the search (over-)time during navigation that they perceive determine the effort size - and, as a consequence, the cognitive cost amount - they have to bear to perform their task. On the contrary, task performing and result achievement provide the users with cognitive benefits, making interaction with the website potentially attractive, satisfying, and useful. In total, 9 variables are measured, classified in a set of 3 website macro-dimensions (user experience, site navigability and structure). The framework is implemented to compare 52 ecommerce websites that sell products in the information technology and media market. A stepwise regression is performed to assess the influence of cognitive costs and benefits that mostly affect website efficiency., (Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.)

Critics opine that full expensing of research and development (R&D) depresses near-term profits and incentivizes myopic managers to under-invest in R&D, compromising firm efficiency. Advocates of the expensing rule argue that little rigorous research evidence supports the claimed adverse consequences. We examine the impact of the R&D expensing rule on firm efficiency by exploiting an exogenous shock: a shift in the accounting regime in Germany from full expensing to partial capitalization of R&D when it mandated International Financial Reporting Standard (IFRS) adoption in 2005. We employ Stochastic Frontier Analysis and Data Envelopment Analysis to estimate efficiency for the same German firms before and after the IFRS adoption. We find robust evidence of efficiency improvement in the post-period relative to the pre-period for German R&D firms that report R&D expenditures, and for both early adopters and timely adopters. We also document that financially constrained firms and firms experiencing rapid R&D growth prior to the IFRS adoption show greater efficiency improvement. Moreover, we conduct three falsification tests to make sure our results are not attributable to other accounting changes associated with the IFRS adoption, and find no efficiency improvement for the three control groups (German "no-R&D" sample, U.K. firms, and Australian firms), respectively. We conclude that the change in the R&D reporting rule is the likely catalyst for improvements in efficiency of German R&D firms. [ABSTRACT FROM AUTHOR]

The operating efficiency of fishermen's associations is significant for developing the fishery industry and fishing villages. Since fishermen's associations have economic, financial, and service sectors, this study evaluates their efficiency through multiactivity data envelopment analysis. In addition to exploring the overall efficiency of each fishermen association, this study further investigates the differences in the operating efficiency of each of the economic, financial, and service sectors. Fishermen's associations were divided according to their sizes and geographic areas for analyses and comparisons by considering the differences in their organizational scales and fishing activities. In the empirical study, 24 fishermen associations in Taiwan were selected as the research subjects, and the shared inputs of economic, financial, and service sectors were taken to conform to their practical operation. The overall efficiency of fishermen's associations was affected by their size and mainly varied by economic sector. The research results indicate room for improvement in the overall efficiency of fishermen's associations, but improving the efficiency of different fishermen's associations should occur in various sectors. [ABSTRACT FROM AUTHOR]

Several countries have focused on achieving optimal economic growth in the past decades, which has caused diverse environmental concerns among policymakers and managers. The present study aims to introduce new metric using mathematical modeling to examine strategies to promote environmental performance in OECD countries. Thus, we propose a target-oriented Distance Friction Minimization (TO-DFM) model to design a practical improvement strategy for low-efficiency DMUs. In this regard, considering the efficient and inefficient frontiers, we present two models, IDMU and ADMU, respectively, based on TO-DFM and DFM models. Then, the distance scores yielded by the two models are combined to evaluate the efficiency of each DMU using the hybrid index of relative closeness (RC). The results reveal that the proposed model has a better distinctive potential compared to the standard TO-DFM model. Overall, implementing the proposed model on a set of sustainability data, for OECD countries, resulted in a more logical performance in classifying countries regarding their distance from the efficient and inefficient frontiers. Therefore, less developed countries should pay considerable attention to implementing environmental policies to improve their performance and control environmental pollution with a reliable and healthy economy. For instance, the implementation of such policies in countries such as Turkey, Estonia, and Hungary, with lower efficiency scores, can affect the sustainability of their development performance. [ABSTRACT FROM AUTHOR]

Background: Primary healthcare management efficiency conditions the functioning of specialized care and has a direct impact on the outcomes of the health system and its sustainability. The objective of this research is to develop models to evaluate the efficiency, including health outcomes, of the primary healthcare centres (PHC) of the Clínico – La Malvarrosa Health District in Valencia. Methods: To evaluate efficiency, Data Envelopment Analysis (DEA) was used with output orientation and variable returns to scale, with panel data from the years 2015 to 2019. In rates per 10,000 inhabitants, the inputs are: medical and nursing staff and pharmacy cost. The outputs are: number of consultations, hospital emergencies, referrals, avoidable hospitalisations, avoidable mortality and pharmaceutical prescription efficiency. As exogenous variables: the percentage of population over 65 years old, over 80 and case-mix. Three models were developed, all of them with the same inputs and different combinations of outputs related to: healthcare activity, outcomes, and both, in order to study the influence of the different approaches on efficiency. Each model is analysed both without exogenous variables and with each of them. Results: The efficiency results vary depending on the model used, although certain PHCs are always on, or very close to, the efficient frontier, while others are always inefficient. When healthcare activity outputs are considered, efficiency scores improve and the number of efficient PHCs increases. However, in general, the PHC score decreases throughout the evaluated period. This decrease is more pronounced when only activity outputs are included. Conclusions: DEA allows the inefficiencies of PHCs to be analysed and the efficient ones are clearly distinguished from the inefficient, although different efficiency scores are obtained depending on the model used. Evaluation can be according to healthcare activity, health outcomes or both, making it necessary to identify the expected objectives of the PHCs, as the perspective of the analysis influences the results. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) is one of the widely used methods to measure the efficiency scores of decision making units (DMUs). Conventional DEA is unable to consider both uncertainty in data and decision makers' (DMs) judgments in the evaluations. This study, to address the shortcomings of the conventional DEA, proposes a new best worst method (BWM)- robust credibility DEA (BWM-RCDEA) model to estimate the efficiency scores of DMUs considering DMs' preferences and uncertain data, simultaneously. First, to handle uncertainty in input and output variables, fuzzy credibility model has been applied. Additionally, uncertainty in constructing fuzzy sets is modeled using robust optimization with fuzzy perturbation degree. In this paper, two new types of RCDEA models are proposed: RCDEA model with exact perturbation in fuzzy inputs and outputs and RCDEA model with fuzzy perturbation in fuzzy inputs and outputs. In addition, to deal with flexibility of weights and incorporating DMs' judgement into the RCDEA model, a bi-objective BWM-RCDEA model is introduced. Finally, the proposed bi-objective model is solved using min–max approach. To illustrate the usefulness and capability of the proposed model, efficiency scores of 39 distribution companies in Iran is investigated and results are analyzed and discussed. Finally, based on the results, recommendations have been made for policy makers. [ABSTRACT FROM AUTHOR]

Background: Health Complex Model was implemented to provide primary health care services in urban, especially in slum areas. As a pilot at a provincial level, Chamran Health Complex offers healthcare for more than 57,000 residents of Tabriz. Despite the necessity of cost information in healthcare decision-making, there was limited knowledge about the unit cost of services. This study aims to analyze the cost and efficiency of health centers. Methods: Activity-Based Costing method with direct and step-down allocation methods was adopted. We estimated unit costs in a hypothetical scenario according to national standards to quantify the gap between current and standard practice. Input-oriented Data Envelopment Analysis was administered to measure the efficiency of health centers. Results: The total cost of the complex was $2,841,897, of which 67% ($1910373) and 33% ($931523) were accounted for direct and indirect costs, respectively. The vaccination center had the lowest ($9), and the occupational health center had the highest average unit cost ($76). The average technical efficiency of the health centers was 0.519, where the HC1 and HC3 showed the best performance. Conclusion: There is remarkable variability in service costs across health centers, which must be addressed in performance management and contracting practices. Although we found a gap between current and standard practice in terms of staff and facilities according to national standards, Chamran Health Complex has an untouched capacity that can be utilized with better planning and without incurring additional costs. It raises the need for revising national standards by the Iran Ministry of Health. [ABSTRACT FROM AUTHOR]

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This paper presents an investigation of the interconnection between firm size and efficiency under the financial constraints lens. Specifically, we used the Data Envelopment Analysis (DEA) technique to measure the efficiency of a sample of large, medium-sized and small private Italian firms, using the firms' default risk as an undesirable output. Our findings indicate that larger companies perform better than medium-sized and smaller companies in terms of efficiency (across all business profiles), including default on bank loans. Based on indicators widely employed to characterize the bank-firm relationship, our study demonstrates the need to improve the efficiency of the Italian entrepreneurial system, consisting mainly of small companies, through their dimensional growth. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to measure and unveil the relationship between customer satisfaction and efficiency levels in the most relevant Brazilian airports. Design/methodology/approach: The authors utilize a two-stage network DEA (data envelopment analysis) and AHP (analytic hierarchy process) model as the cornerstones of the study. The first stage of the network productive structure focuses on examining the infrastructure efficiency of the selected airports, while the second stage assesses their business efficiency. Findings: Although the results indicate that infrastructure and business efficiency levels are heterogeneous and widely dispersed across airports, controlling the regression results with different contextual variables suggests that the impact of efficiency levels on customer satisfaction is mediated by a set of socio-economic and demographic (endogenous) and regulatory (exogenous) variables. Furthermore, encouraging investment in airports is necessary to achieve higher infrastructural efficiency and scale efficiency, thereby improving customer satisfaction. Originality/value: There is a scarcity of studies examining the relationships among customer satisfaction, privatization and airport efficiency, particularly in developing countries like Brazil. [ABSTRACT FROM AUTHOR]

This study explores the critical determinants of efficiency in European Higher Education Institutions (HEIs). The contemporary landscape presents a wide range of challenges and opportunities, necessitating unprecedented levels of efficiency. Our primary objective is to unravel the fundamental elements that drive the efficiency of European HEIs. To achieve this, we employ a novel methodological approach, integrating Data Envelopment Analysis (DEA) with a Machine Learning technique, specifically Feature Selection. This combination sheds new light on areas previously less explored in DEA, including the intricate interplay among variables. Our empirical investigation contributes to the academic discourse by presenting a comprehensive, multi-country analysis from a multifaceted viewpoint. We assess the efficiency levels of European universities, highlighting the influence of factors such as student fee funding, Ph.D. program intensity, and international mobility on achieving high efficiency scores. The findings of this study have some implications for policy-making, suggesting strategies to enhance the efficiency levels of HEIs. [ABSTRACT FROM AUTHOR]

AbstractMultinational firms establish foreign affiliates to reduce production and transaction costs and open markets. This study was conducted to determine whether foreign affiliates are efficient in production—the efficiency of foreign affiliates established by Korean multinationals through foreign direct investment from 2007 to 2018. DEA efficiency was measured by dividing it into pure, technical, and scale efficiency. An empirical analysis using the panel Tobit and Probit models examined the factors affecting efficiency decisions. It was confirmed that the total number of foreign affiliates’ employees significantly affects their efficiency. In addition, it was analyzed that establishments with traditional FDI motives, such as taking advantage of low wages and promoting exports, harm the efficiency of foreign affiliates. [ABSTRACT FROM AUTHOR]

Window analysis is a time-dependent variant of Data Envelopment Analysis (DEA) and it is based on the moving average method. It is used for showing the trend of Decision Making Units' (DMUs') performance over various times. The efficiency changes of 13 companies operating in Borsa Istanbul (BIST) Information Technology (IT) sector for quarterly periods between 2019:03 and 2021:06 are evaluated by DEA Window Analysis. The input-oriented CCR model and the input-oriented BCC Windows analysis models are applied on data set. When the CCR model and BCC model window analysis results are evaluated together, one of the first two periods with the highest average efficiency for both of them is 2021:06, and the period with the lowest average efficiency for both of them is 2019:09. DESPC company has the highest average efficiency for both models. [ABSTRACT FROM AUTHOR]

Purpose: The banking industry, which is one of the most significant industries when taking into account both deposit sizes and employment statistics in Turkey, is one of the country's primary economic drivers. In this regard, it is highly important to evaluate banks as it is necessary to present to what extent they use their resources efficiently. The main purpose of the study is to analyze the efficiencies of Turkish banks by the two-stage data envelopment analysis (DEA) and Malmquist productivity index (MPI). Design/methodology/approach: The authors aim to analyze both the efficiency and productivity of Turkish banks by two-stage DEA and the MPI, which enable decomposing into sub-sections of production processes. Hence, more detailed insight into the Turkish banking system can be presented through two-stage efficiency and production approaches. Findings: DEA results indicate that two out of three state-owned banks achieved resource efficiency while none of the investigated banks performed profit efficiency throughout the investigated period. Besides, average resource efficiency is found higher than average profit efficiency in Turkish banks. MPI results reveal that both technological and technical improvement prospects exist for Turkish banks. Originality/value: The original contribution of this paper is to employ two-stage DEA and the MPI, which reflect both the static and dynamic performance of the Turkish banking sector. In this regard, this study aims to be a pioneer by both reflecting the static and dynamic performance analysis of Turkish banks. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate environmental efficiency based on energy change by using energy-related or nonenergy-related variables by reckoning with months and years as decision-making units (DMUs) for a hospital under radial and nonradial models. Design/methodology/approach: The non-oriented slack-based measures (SBM)-data envelopment analysis (DEA) model considering desirable and undesirable outputs has been embraced in this study, where its obtained results were compared with the results of other DEA models are output-oriented SBM-DEA and Banker, Charnes, & Cooper-DEA. For this purpose, this research has used a data set covering the 2012–2018 period for a reference hospital, which includes energy-related and nonenergy-related variables. Findings: The results demonstrate that environmental efficiency based on energy reached the highest level in the winter months, whereas the summer months have the lowest efficiency values arising from the increasing electricity consumption due to high cooling needs. According to results of the non-oriented SBM model, the month with the highest efficiency in all periods is January with a 0.936 average efficiency score, the lowest month is August with a 0.406 value. Originality/value: This paper differs from other studies related to energy and environmental efficiencies in the literature with some aspects. First, to the best of the authors' knowledge, this study is the first one that takes into account time periods (months and years) as (DMUs for a single organization. Second, this study investigates environmental nonefficiencies, which are derived from energy uses and factors affecting energy use. [ABSTRACT FROM AUTHOR]

Senior managers are the customers of organizational performance measurement methods to help them make better decisions at the firm level. One of the most applicable methods is Network Data Envelopment Analysis (DEA). Network DEA models consider systems that have a network structure in which system inputs, after passing several intermediate interactions, are transformed into intermediate productions and finally leave the system as output products. However, many realworld cases do not necessarily conform to this network structure, which is related to the system outputs during multiple time periods or the same "dynamic" impacts. These structures cannot handle dynamic impacts. Therefore, this paper presents a novel structure that can consider the dynamic impacts and influences of sub-units on each other at various time periods. Besides, two models based on slack variables are proposed which can consider dynamic effects and calculate the efficiency of such networks. Using these models, the overall efficiency of networks is calculated for the whole time period. Finally, these models are applied to two examples, and the results obtained are compared with other methods. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the financial risk, debt, and efficiency of state-owned enterprises (SOEs) in Indonesia's construction industry and compare these aspects with those of private companies through financial ratio analysis and efficiency analysis approaches. Four SOEs from the construction sector were evaluated and compared to five private companies with financial data ranging from 2015 to 2022. Financial ratio analysis was applied to assess debt and financial risk, while efficiency analysis utilized data envelopment analysis (DEA) and paired t-tests to validate differences between the two groups of companies. This study reveals that the financial ratio performance of state-owned companies is relatively poor, with low profitability, critical liquidity, and a high debt ratio. Debt, as a source of capital in financing construction projects, causes companies to face a greater debt risk. This study also validates that SOEs have lower efficiency compared to private companies. In response to current challenges, SOEs should prioritize enhancing liquidity through faster receivable collections, debt restructuring, capital infusions, and divestment, reducing non-essential investments, focusing on asset recycling, and improving project efficiency. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency. Design/methodology/approach: The current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency. Findings: The results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency. Originality/value: Instead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants. [ABSTRACT FROM AUTHOR]

Abstract Background Primary healthcare management efficiency conditions the functioning of specialized care and has a direct impact on the outcomes of the health system and its sustainability. The objective of this research is to develop models to evaluate the efficiency, including health outcomes, of the primary healthcare centres (PHC) of the Clínico – La Malvarrosa Health District in Valencia. Methods To evaluate efficiency, Data Envelopment Analysis (DEA) was used with output orientation and variable returns to scale, with panel data from the years 2015 to 2019. In rates per 10,000 inhabitants, the inputs are: medical and nursing staff and pharmacy cost. The outputs are: number of consultations, hospital emergencies, referrals, avoidable hospitalisations, avoidable mortality and pharmaceutical prescription efficiency. As exogenous variables: the percentage of population over 65 years old, over 80 and case-mix. Three models were developed, all of them with the same inputs and different combinations of outputs related to: healthcare activity, outcomes, and both, in order to study the influence of the different approaches on efficiency. Each model is analysed both without exogenous variables and with each of them. Results The efficiency results vary depending on the model used, although certain PHCs are always on, or very close to, the efficient frontier, while others are always inefficient. When healthcare activity outputs are considered, efficiency scores improve and the number of efficient PHCs increases. However, in general, the PHC score decreases throughout the evaluated period. This decrease is more pronounced when only activity outputs are included. Conclusions DEA allows the inefficiencies of PHCs to be analysed and the efficient ones are clearly distinguished from the inefficient, although different efficiency scores are obtained depending on the model used. Evaluation can be according to healthcare activity, health outcomes or both, making it necessary to identify the expected objectives of the PHCs, as the perspective of the analysis influences the results.

Abstract Background Health Complex Model was implemented to provide primary health care services in urban, especially in slum areas. As a pilot at a provincial level, Chamran Health Complex offers healthcare for more than 57,000 residents of Tabriz. Despite the necessity of cost information in healthcare decision-making, there was limited knowledge about the unit cost of services. This study aims to analyze the cost and efficiency of health centers. Methods Activity-Based Costing method with direct and step-down allocation methods was adopted. We estimated unit costs in a hypothetical scenario according to national standards to quantify the gap between current and standard practice. Input-oriented Data Envelopment Analysis was administered to measure the efficiency of health centers. Results The total cost of the complex was $2,841,897, of which 67% ($1910373) and 33% ($931523) were accounted for direct and indirect costs, respectively. The vaccination center had the lowest ($9), and the occupational health center had the highest average unit cost ($76). The average technical efficiency of the health centers was 0.519, where the HC1 and HC3 showed the best performance. Conclusion There is remarkable variability in service costs across health centers, which must be addressed in performance management and contracting practices. Although we found a gap between current and standard practice in terms of staff and facilities according to national standards, Chamran Health Complex has an untouched capacity that can be utilized with better planning and without incurring additional costs. It raises the need for revising national standards by the Iran Ministry of Health.

Objective: This research aims to measure the efficiency of health services by using health indicators of OECD countries, to determine inefficiencies of countries that are not at the efficient border, to calculate idle use, and to determine super-efficiency values of countries at active borders.Methods: In the research, DEA was conducted using an input-oriented CCR model to measure the performance of the OECD countries in 2019, the last year before the pandemic. In the research, three input and two output variables were used. R Studio package programs were used for the analysis of research data.Results: It is seen that the productivity average of 15 countries is 0.81. 5 out of 16 countries have been identified as active. Finally, it has been determined that Hungary, with a super-efficiency value of 17.18, can still be on an efficient border even if it increases its input amounts 16 times.Conclusion: A notable observation is that some OECD countries with developed economies allocate substantial resources to long-term care services, and their capacities are at sufficiently high levels. It is recommended that low-productivity countries should reduce the idle use of input resources to increase their productivity.