Evaluation of healthcare efficiency in China: a three-stage data envelopment analysis of directional slacks-based measure.

Background: A consensus on the changing pattern of healthcare efficiency in China is current absent. This study tried to identify temporal fluctuations in healthcare efficiency from 2012 to 2021, and conducted a comparative analysis on the performance of 31 regions in China using region-level balanced panel data. Methods: Employing three-stage data envelopment analysis (DEA) as the analytical framework, we measured healthcare efficiency and its changes using the directional slacks-based measure and global Malmquist-luenberger (GML) indexes. We also decomposed the sources of healthcare inefficiency and extended our analysis to changes in healthcare efficiency across different primary medical service levels and regional economic development tiers. Results: The average efficiency score of medical institutions (0.956) was slightly higher than that of hospitals (0.930). We found that the average GML indexes of medical institutions in China stood at 0.990, while the average technical change (TC) index was 0.995 and the average efficiency change (EC) index was 0.998 from 2012 to 2021. The GML indexes, TC indexes, and EC indexes of hospitals were 1.002, 1.009, and 0.994, respectively. The healthcare inefficiency for both inputs and desirable outputs in medical institutions was primarily attributed to the redundant numbers of institutions, outpatient visits slacks and inpatient surgery volume slacks, accounting for 50.040, 49.644, and 28.877%, respectively. The undesirable output inefficiency values of medical institutions concerning in-hospital mortality stood at 0.012, while the figure for hospital regarding the average length of stay (LOS) was 0.002. Additionally, healthcare efficiency in both medical institutions and hospitals exhibited an upward trend from 2012 to 2021, corresponding to an increase in the volume of primary medical services, primary medical staff, and the total gross domestic product (GDP). Conclusion: Total factor productivity (TFP) of medical services declined in China from 2012 to 2021. The excessive number of medical institutions and the slack of medical service volumes were the main sources of healthcare inefficiency. Regions prioritizing primary medical services and boasting higher GDP levels exhibited superior healthcare efficiency. These findings are expected to inform policymakers' efforts in building a value-based and efficient health service system in China.

Valuating the efficiency of social security and healthcare in OECD countries from a sustainable development.

Under the goal of sustainable development, coping with the increase in social security and healthcare expenses caused by population aging is becoming increasingly important, but it is rare in the literature to evaluate the impact of social security efficiency on healthcare efficiency. This research uses the dynamic SBM two-stage model to observe the efficiencies of social security and healthcare in OECD countries. There are two findings as follows. First, the higher social security efficiency is, the better is the healthcare efficiency of countries with lower per capita GDP. Second, higher social security efficiency of National Health Service (NHS) countries denote better healthcare efficiency. When the financial source of the social security system is taxation, then it is more likely to bring higher efficiency to healthcare.

Impact assessment of construction waste policy intensity on environmental efficiency based on system generalized method of moments.

With the acceleration of urbanization in recent years, China has witnessed large-scale construction across its provinces, generating massive amounts of construction waste that pose challenges to environmental protection and sustainable development. This study evaluated the impact of construction waste policy intensity on its environmental efficiency. Firstly, the content analysis method was used to analyze the construction waste policy text quantitatively. Second, this study constructed a slack-based measure (SBM) model based on data envelopment analysis (DEA), considering resource input and construction waste output to measure environmental efficiency. Finally, we built and tested an econometric model of how policies affect environmental efficiency using the system generalized method of moments (SYS-GMM). The findings indicate a non-linear U-shaped link between policy intensity and environmental efficiency. Among all five control variables, population density, urbanization level, and technological innovation enhance environmental efficiency, while economic development and highway density will lower it. This study advances the research on construction waste policies and offers some insights for the construction industry to pursue sustainable development.

Estimating the Distribution and Convergence of County-level Healthcare Resources Allocative Efficiency in China Based on DEA and Spatial Panel Model.

Although China's 2009 New Healthcare Reform aimed to correct the imbalance in the spatial allocation of healthcare resources with a focus on the county level, its impact on county-level allocative efficiency evolution and convergence remains unclear. This paper for the first time performs a spatial analysis to explore the distribution, evolution, and convergence of the allocative efficiency of healthcare resources with county-level data. This paper uses the sample data of 158 countries in Henan Province, China, to evaluate the evolution and convergence of the allocative efficiency of healthcare resources. Based on the estimated Data Envelopment Analysis (DEA) allocative efficiency, analysis of variance (ANOVA), and spatial descriptive analysis, we explore the county heterogeneity and efficiency evolution; a spatial panel model is then utilized to test the county-level convergence of the allocative efficiency of healthcare resources. Although the number of efficient counties has not increased, the number of inefficient individuals keeps decreasing, and the allocative efficiency of municipal districts is lower than that of nonmunicipal counties. There exists a positive spatial correlation of allocative efficiency in Henan Province, and significant and robust convergence results can be found at the county level after China's 2009 reform. This study reveals a diversified picture of China's county-level spatial evolution of allocative efficiency in healthcare resources, showing a more balanced spatial distribution of allocative efficiency since the triggering of China's 2009 reform. However, long-term investment incentives and a targeted allocation of healthcare resources are still needed to promote further efficiency convergence and increase the number of counties with efficiency.

Healthcare Service Efficiency: An Empirical Study on Healthcare Capacity in Various Counties and Cities in Taiwan.

As human lifespan increases and the need for elderly care grows, the demand for healthcare services and its associated costs have surged, causing a decline in the operational efficiency of universal healthcare. This has created an imbalance in medical services across different regions, posing a long-standing challenge for the public. To address this issue, strategies to enhance the capacity, efficiency, and quality of healthcare services in various regions must be developed. The appropriate allocation of medical resources is a fundamental requirement for countries to establish a robust healthcare system. This empirical study utilized data envelopment analysis (DEA) to evaluate the efficiency of medical service capacity and identify potential improvement strategies for counties and cities in Taiwan during the period from 2015 to 2020. The results of this study show that (1) the annual average efficiency of medical service capacity in Taiwan is approximately 90%, indicating that there is still room for a 10% improvement; (2) among the six municipalities, only Taipei City has sufficient healthcare capacity, whereas the efficiency of the remaining municipalities needs improvement; and (3) most counties and cities demonstrated increasing returns to scale, indicating a need to scale up the capacity of medical services as appropriate. Based on the findings of this study, it is recommended that medical personnel be increased accordingly to balance the workload, a favorable working environment be provided to stabilize the medical workforce, and urban-rural medical disparities be balanced to improve service quality and reduce cross-regional health services. These recommendations are expected to provide a reference for society as a whole to promote and enhance public health policies, leading to a continual improvement of the quality of medical services.

Application of the data envelopment analysis technique to measure the environmental efficiency of the 27 countries of the European Union during the period 2012-2020.

In the last decade, we have experienced a changing geopolitical context that has caused changes in the energy context. In addition, human activity contributes to global warming or sea level rising, i.e., climate change. A set of action policies have been implemented to continue fighting against this environmental situation (such as the Paris Agreement, the COP27, or the European Green Deal for 2030); therefore, it is necessary to determine whether we are on the right track. It is compulsory to develop predictive models that accurately analyze the current status and the already path undertaken. To this end, this article analyzes the environmental efficiency of the 27 countries of the European Union (excluding the UK) using the so-called data envelopment analysis (DEA). In particular, economic (GDP and GDP per capita), environmental (CO2 and CH4 emissions), electricity production data, the volume of vehicles, and the industrial production rate of the different countries were collected to calculate environmental efficiency. Once these data were collected, the environmental efficiency was calculated using two methods based on the DEA. The results show that out of the 27 countries, only 12 have a relatively high environmental efficiency, although it could be improved, implementing a set of corrections. However, other countries have a low eco-efficiency performance and they must improve in the coming years. We can highlight that rich countries are closer to achieving high environmental efficiency than less developed countries. Graphical Abstract: Political map of the European Union indicating the average eco-efficiency with colors of the 27 countries of the DEA method. Supplementary Information: The online version contains supplementary material available at 10.1007/s10098-023-02553-9.

Assessment of airline industry using a new double-frontier cross-efficiency method based on prospect theory.

Cross-efficiency method (CEM) is a well-known technique based on data envelopment analysis that provides policymakers with a powerful tool to measure the efficiency of decision-making units. However, there are two main gaps in the traditional CEM. First, it neglects the subjective preferences of decision-makers (DMs), and therefore, cannot reflect the importance of self-evaluation compared to peer-evaluations. Second, it ignores the importance of anti-efficient frontier in the overall evaluation. The present study aims to incorporate the prospect theory into the double-frontier CEM to deal with these drawbacks while considering the preferences of DMs towards gains and losses. To address these drawbacks, this paper utilizes an aggregation method based on the prospect theory and consensus degree (APC) to reflect the subjective preferences of DMs. The second issue is also addressed by incorporating APC into the optimistic and pessimistic CEMs. Finally, the double-frontier CEM aggregated using APC (DAPC) is obtained by aggregating two viewpoints. As a real case study, DAPC is applied to evaluate the performance of 17 Iranian airlines based on three inputs and four outputs. The findings demonstrate that both viewpoints are influenced by DMs' preferences. The ranking results achieved for more than half of the airlines based on the two viewpoints are significantly different. The findings confirm that DAPC deals with these differences and leads to more comprehensive ranking results by considering both subjective viewpoints simultaneously. The results also show that to what extent DAPC efficiency for each airline is influenced by each viewpoint. In this regard, the efficiency of IRA is most influenced by the optimistic point of view (80.92%), and on the other hand, the efficiency of IRZ is most influenced by the pessimistic viewpoint (73.45%). KIS is the most efficient airline, followed by PYA. On the other hand, IRA is the least efficient airline, followed by IRC.

How has China's industrial eco-efficiency been improved? Evidence from multi-scale countrywide study.

The process of industrialization often causes resource depletion and environmental pollution. To shed light on China's resource use and pollution trends in the context of the country's rapid industrial growth, this study analyzes the eco-efficiency of China's industry from 2000 to 2015. We quantify industrial eco-efficiency (IEE) for China and its provinces using data envelopment analysis (DEA) and analyze potential influencing factors at national and regional levels using Tobit regression. IEE in China and in most provinces shows a clear upward trend with some fluctuations, with national scores increasing from 0.394 to 0.704. There is strong regional disparity, with average IEE scores in eastern provinces (0.840) higher than those in central provinces (0.625), which are in turn higher than those in the northeast (0.537) and west (0.438). We next consider potential drivers. Economic development and foreign direct investment (FDI) are positively associated with IEE but appear to show diminishing returns. Environmental enforcement and market for technology are also positively associated with IEE, as expected. The impact of economic development, industrial sector structure, and investment in research and development (R&D) are modified by the stage of industrialization in each region. Targeted measures that can adjust industry structure, enhance environmental enforcement, attract FDI, and increase R&D investment may help further improve IEE in China.

Carbon emission efficiency evaluation of wastewater treatment plants: evidence from China.

A scientific evaluation of the carbon emission efficiency is crucial for ensuring the sustainable development of wastewater treatment plants (WWTPs). In this paper, we applied a non-radial data envelopment analysis (DEA) model to calculate the carbon emission efficiency of 225 WWTPs located in China. The results showed that the average carbon emission efficiency of China's WWTPs was 0.59, indicating that the efficiencies of most samples still require improvement. The carbon emission efficiency of WWTPs from 2015 to 2017 decreased because of the decrease in technology efficiency. Among the influencing factors, different treating scales had positive impact on carbon emission efficiency improvement. WWTPs with anaerobic oxic process and the first-class A standard were likely to have higher carbon emission efficiency in the 225 WWTPs. By incorporating direct and indirect carbon emissions into WWTP efficiency evaluation, this study helped decision-makers and related water authorities to better understand the contribution of WWTPs to the aquatic and atmospheric environments.

Assessment of equity and efficiency of magnetic resonance imaging services in Henan Province, China.

BACKGROUND: By evaluating equity and effectiveness, this study provides evidence-based knowledge for scientific decision-making and the optimization of magnetic resonance imaging (MRI) configuration and utilization at the provincial level. METHODS: Using data from 2017, we applied a Gini coefficient to analyze the equity of MRI services in 11 sample cities in Henan province. An agglomeration degree was then applied to measure equity from the perspective of population and geography, and a data envelopment analysis was used to evaluate MRI efficiency. RESULTS: The overall Gini coefficient of MRI allocation by population in the 11 sample cities is 0.117; however, equity varies considerably among the sample cities. The sample's comprehensive efficiency is only 0.732, indicating the overall ineffectiveness of provincial MRI utilization. The pure technical and scale efficiencies of four sample cities are below 1, indicating lower MRI effectiveness than the rest. CONCLUSIONS: Although the overall equity of configuration at the provincial level is relatively good, equity varies at the municipal level. Our results demonstrate a low MRI utilization efficiency; accordingly, policymakers should dynamically adjust the policy based on equity and efficiency.

Achieving Net Zero-An Illustration of Carbon Emissions Reduction with A New Meta-Inverse DEA Approach.

To achieve the goal of limiting global warming to 1.5 °C above preindustrial levels, net-zero emissions targets were proposed to assist countries in planning their long-term reduction. Inverse Data Envelopment Analysis (DEA) can be used to determine optimal input and output levels without sacrificing the set environmental efficiency target. However, treating countries as having the same capability to mitigate carbon emissions without considering their different developmental stages is not only unrealistic but also inappropriate. Therefore, this study incorporates a meta-concept into inverse DEA. This study adopts a three-stage approach. In the first stage, a meta-frontier DEA method is adopted to assess and compare the eco-efficiency of developed and developing countries. In the second stage, the specific super-efficiency method is adopted to rank the efficient countries specifically focused on carbon performance. In the third stage, carbon dioxide emissions reduction targets are proposed for the developed and developing countries separately. Then, a new meta-inverse DEA method is used to allocate the emissions reduction target to the inefficient countries in each of the specific groups. In this way, we can find the optimal CO2 reduction amount for the inefficient countries with unchanged eco-efficiency levels. The implications of the new meta-inverse DEA method proposed in this study are twofold. The method can identify how a DMU can reduce undesirable outputs without sacrificing the set eco-efficiency target, which is especially useful in achieving net-zero emissions since this method provides a roadmap for decision-makers to understand how to allocate the emissions reduction targets to different units. In addition, this method can be applied to heterogeneous groups where they are assigned to different emissions reduction targets.

How to improve the future efficiency of Covid-19 treatment centers? A hybrid framework combining artificial neural network and congestion approach of data envelopment analysis.

Covid-19 virus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) threatens the health of human beings worldwide, imposing a concern for the world and prompting governments to control the contagion. Although vaccination is a proper tool to control the transmission, the efficient allocation of limited health-care resources to massive patients can improve the effectiveness of medical services. Relying on the Artificial Neural Network (ANN), the aim of this research is to enhance the future efficiency of Covid-19 treatment centers by forecasting their efficiency and providing benchmarks. To do this, we use the congestion approach of data envelopment analysis (DEA) based on the theory of economies of scale principles. In the traditional input-oriented DEA, inefficient decision-making units (DMUs) can become efficient merely by reducing the inputs. However, this may not always be true in real-world applications such as improving the efficiency of COVID-19 treatment centers (DMUs). Meaning that the treatment centers with less congested inputs (e.g., ventilators, test equipment, pulmonologists, and nurses, etc.) normally have higher mortality rates. For this reason, in this study, we take the congested inputs approach into account to provide proper benchmarks for the inefficient treatment centers. According to the congestion approach of DEA, an optimum increase in congested inputs can lead to a greater than a proportional increment in outputs. In other words, if more respiratory equipment, pulmonologists, patient rooms, nurses and beds, etc. are allocated to Covid-19 treatment centers, not only the number of deaths (undesirable outputs) are decreased, but also the number of recoveries (desirable outputs) are increased. Such an optimal rise in the congested inputs is determined in pairwise comparisons derived from the model. Accordingly, in this study, first, considering the congestion approach of DEA and historical data of five periods, we identify the initial efficiency of Iranian Covid-19 treatment centers. Then, by running ANN, we forecast the future inputs and outputs, the overall efficiency, and rank of the treatment centers. By doing this, the prospective efficient and inefficient DMUs are identified, and appropriate benchmarks are determined.

Evaluating sustainable efficiency of decision-making units considering undesirable outputs: an application to airline using integrated multi-objective DEA-TOPSIS.

Sustainable development has gained significant attention in the literature due to the increased global awareness of environmental sustainability during the last decade. Sustainable development has three aspects, including economic, social, and environmental. The challenge of sustainable development is to establish a balance between these three aspects. Assessing the efficiency of a company contributes comprehensive information to improve its overall performance. Despite numerous studies in this field, the literature lacks studies that simultaneously consider all three aspects of sustainable development, especially the social aspect. The main objective of this paper is to calculate the technical, social, and environmental efficiency scores. We also introduce a new efficiency called sustainable efficiency that merges all three sustainable development aspects in one efficiency score. This study applies two existing data envelopment analysis (DEA) models to evaluate technical, social, environmental, and sustainable efficiencies. These models, namely the three-step method and the modified three-step method, are computationally intensive. Also, this paper introduces two new DEA models, namely the common weight goal programming DEA and the common weight DEA, to assess the efficiencies with much fewer computations. Each model produces results that are different from one another. Therefore, the TOPSIS approach is applied to provide an overall result by integrating the results obtained from the four presented models. For this purpose, the implementation of four TOPSIS models is required. To illustrate the capability and validity of the developed models in efficiency calculation, a case of Iranian airlines is presented. The selected airlines are evaluated in different aspects, and final results are obtained by applying TOPSIS. The findings show that using TOPSIS to combine the results of several DEA models leads to a fully ranking of airlines in four aspects of technical, social, environmental, and sustainable efficiencies. Also, it is recommended to managers to probe pairwise comparison between different efficiencies of airlines in order to find and improve the weak ones.

R&D performance and relevant factors of renewable energy projects: separating innovation and economic perspectives.

Many countries, including South Korea, focus on securing renewable energy technologies to cope with climate change and foster new industries. This study analyzed R&D performance and relevant factors through tracking data on the Korean government's renewable energy R&D project, which ended in 2010-2014. The main findings provide several meaningful information. First, the overall performance of completed projects is relatively low, both innovation and economic perspectives. Second, renewable energy source, R&D organizer, and The R&D stage are relevant factors on R&D performance. The R&D stage significantly influences innovation performance. Lastly, R&D performance is under an imbalance between innovation and economic perspectives. This paper can provide useful information to policy and decision-makers to improve future R&D project performance. In addition, scholars also may refer to related researches. Ultimately, we expect to promote renewable energy R&D projects and help manage their performance.

'Cyclic syndrome' of arrears and efficiency of Indian judiciary.

One of the four pillars of democracy in India is the judiciary, which in the recent past has experienced the 'cyclic syndrome' of arrears. There are 3.5 crore cases pending in the Indian judicial system that has a bearing on contract enforcement. A burgeoning stream of literature has reported the role of the judiciary in economic growth and development. In the wake of a given potential economic multiplier of the judicial system, examining the factors affecting the performance of the judiciary should merit attention. The present study juxtaposes jurisprudence and production theory, not frequently examined in the same gust by employing Data Envelopment Analysis (DEA), Malmquist Productivity Index (MPI), Stochastic Frontier Analysis (SFA), and regression for High Courts and Subordinate Courts. Employing the dataset for the years 2014-19, we investigate the technical efficiency and productivity of the High Courts and their Subordinate Courts and examine the factors influencing the dissolved cases. Furthermore, we examine the impact of COVID-19 on the cases instituted and cases disposed of. To sum up, the paper, thus, touches upon two basic dimensions of justice for High Courts and Subordinate Courts in India: Timeliness in the disposal of cases and the proportionate use of the state's resources. The study confirms the role of judges, judicial staff, and demand for justice on the supply of justice. Shreds of evidence point toward the need to introduce a "cocktail-based" approach instead of a "one-size-fits-all". Supplementary Information: The online version contains supplementary material available at 10.1007/s43546-022-00377-1.

Assessing the Efficiency and Productivity of the Hospital Clinics on the Island of Rhodes during the COVID-19 Pandemic.

(1) Background: The aim was to measure the efficiency and productivity of 15 specialty clinics during the COVID-19 pandemic period 2020-2021 in the General Hospital of Rhodes. (2) Methods: An input-oriented data envelopment analysis and the Malmquist productivity index are used. Labor and capital were used as inputs, and in-patient discharges and days were used as outputs. (3) Results: Five out of the seven clinics in the pathology sector appeared fully efficient with an optimal productivity, and the rest showed progress in 2021. In 2020 the COVID-19 pathology clinic appeared to be inefficient and less productive, while in 2021, it showed a positive performance change. The surgical sector showed very high efficiency rates or even reached an optimal efficiency in both years. The productivity measurement, in most of the surgical clinics, was satisfactory to very high. In 2020 the COVID-19 surgical clinic appeared to be more efficient and productive than in 2021 when its performance declined. (4) Conclusions: The hospital responded to the pressure during the pandemic, by increasing its efficiency and productivity from 2020 to 2021. This was due to the accomplishment of the appropriate organizational changes in the infrastructure, human resources, and technology. The efficiency and productivity assessments should be incorporated in the hospitals' decision making.

Evaluation of technical efficiency of some rain-fed cereal and legume crops production in Syria: does crisis matter?

Background: Syria is a developing country whose economy is still dominated by the agricultural sector. The agricultural sector is considered as the main source of food in Syria and a major source of employment and income generation. Food and agricultural policies in Syria focus heavily on achieving food security and improving its four pillars (availability, accessibility, stability and utilization). As a result, until 2011, a good progress has been attained in food availability. The food security situation deteriorated in Syria after 2011 crisis, with the number of people facing acute food insecurity rising from 7.9 million in 2020 to a staggering 12.4 million in 2021. This is the result of many shocks that the agricultural sector has been exposed to, such as the relative decrease in cultivated areas, high costs of production, reduced input availability including labour, prevailing violence, related damage to farm equipment, and abandoned land. In view of the changes that the agricultural sector has been exposed to in Syria as a result of the crisis, the study concerns measuring the technical efficiency of production of some rain-fed cereal and legume crops in Syria and comparing it in the pre and post-crisis period, which has started in 2011. A non-parametric (DEA) method is applied for measuring technical efficiency during the time period 2003-2010 (pre-crisis) and the period 2011-2018 (post-crisis) with censored regression (the tobit model) to investigate the determinants of technical efficiency. A t test is used to test the null hypothesis (H0) that there was no difference in technical efficiency of the production of studied crops before and after the crisis in Syria and the alternative hypothesis (Ha) that there was a significant difference in technical efficiency. Results: The findings show low level of technical efficiency in the post-crisis period. The results verified differences in the technical efficiency of pre- and post-crisis period. The use of censored regression with dummy for crisis has shown negative and significant effect on technical efficiency of each of the durum wheat and lentil crops, while it had no significant effect on the other studied crops. Conclusions: This study can provide important information to the government to pursue a new policy for recovery and improving the agricultural production and productivity. There is an urgent need to adopt new policies that focus on providing production requirements in the form of low-interest loans, sustainable use of resources, providing support for the marketing process, and focusing on the export markets of some study crops (chickpeas and lentils). Government should improve agricultural extension services for farmers and encouraging them to adopt new technologies.

The association of dairy cattle longevity with farm level technical inefficiency.

Prolonging dairy cattle longevity is regarded as one of the options to contribute to a more sustainable milk production. Cattle longevity is a direct result from culling decisions, which is primarily driven by economic considerations. As a consequence, at the herd level, cattle longevity can have effects on the efficiency of dairy production. This study investigates the technical inefficiency of dairy input, and its association with cattle longevity under Dutch commercial dairy production conditions, using a two-stage data envelopment analysis (DEA) approach. First, the technical inefficiency of capital, labor, land, seed & crop protection expenses, veterinary services, livestock purchase & services, feed purchase, miscellanea, livestock units and total input on total farm revenues was computed using DEA. Secondly, a bootstrap truncated regression analysis was applied to identify the association of cattle longevity with the evaluated input-specific and total input scores for technical inefficiency. Data were compiled from performance and accountancy records of 1,037 commercial Dutch dairy herds over the period of 2007 to 2014. In general, Dutch dairy farms displayed a relatively good overall technical efficiency, represented by an average inefficiency score of 0.09. The economic benefit of extending cattle longevity was evidenced by the negative association of cattle longevity with total input inefficiency. Of the evaluated inputs, the utilization of livestock units and feed was most efficient, with inefficiency scores below 0.26. This contrasts with the poor input efficiency of capital and livestock purchase & services with inefficiency scores around 0.52. Although the strength of the evaluated associations was generally low, the regression results illustrated that, except for labor, the age of culled cows was significantly negatively associated (P < 0.05) with each of the input inefficiencies. This contrasts with the significant associations of input inefficiencies with lifetime milk production, which were mostly positive. Since lifetime milk production is driven by length of cattle lifespan in combination with production level of the cows, the reverse direction of the associations with the two longevity indices illustrates that prolonging cattle longevity can improve efficiency performance of a dairy farm as long as the milk yield per cow remains unchanged.

The impact of human resources for health on the health outcomes of Chinese people.

Human resources for health (HRH) is a cornerstone in the medical system. This paper combined data envelopment analysis (DEA) with Tobit regression analysis to evaluate the efficiency of health care services in China over the years between 2007 and 2019. Efficiency was first estimated by using DEA with the choice of inputs and outputs being specific to health care services and residents' health status. Malmquist index model was selected for estimating the changes in total factor productivity of provinces and exploring whether their performance had improved over the years. Tobit regression model was then employed in which the efficiency score obtained from the DEA computations used as the dependent variable, and HRH was chosen as the independent variables. The results showed that all kinds of health personnel had a significantly positive impact on the efficiency, and more importantly, pharmacists played a critical role in affecting both the provincial and national efficiency. Therefore, the health sector should pay more attention to optimizing allocation of HRH and focusing on professional training of clinical pharmacists.

Managing Efficiency in Digital Transformation - EU Member States Performance during the COVID-19 Pandemic.

The COVID-19 pandemic context asserted the digitalization process in the European Union member countries five years forward (at least). The digital divide, a frequent debated issue was brought to the fore, and, under these circumstances, the proposed aim of the paper is to analyze the digitalization process, considering the data provided by Digital Economy and Society Index (DESI) and, additionally, the Stringency Index, that measure the governmental restrictions during the pandemic for 2020. From a methodological perspective, the empirical study focused on performing the Data Envelopment Analysis (DEA) non-parametric test. Measuring the digitalization efficiency or inefficiency of the European member states was conducted by using an output-oriented model, focused on output maximization for a given level of input, assuming Constant Returns to Scale (CRS). The results highlighted major discrepancies between the European countries. Solely eight countries out of 27 can be considered efficient in the digitalization processes during the COVID-19 pandemic. Based on the model, the most efficient EU countries could be considered peers/benchmarks for the inefficient ones, which should examine the best practices in order to improve their current situation.