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The herpesvirus UL51 protein is a multifunctional tegument protein involved in the regulation of multiple aspects of the viral life cycle. This article reviews the biological characteristics of the UL51 protein and its functions in herpesviruses, including participating in the maintenance of the viral assembly complex (cVAC) during viral assembly, affecting the production of mature viral particles and promoting primary and secondary envelopment, as well as its positive impact on viral cell-to-cell spread (CCS) through interactions with multiple viral proteins and its key role in the proliferation and pathogenicity of the virus in the later stage of infection. This paper discusses how the UL51 protein participates in the life cycle of herpesviruses and provides new ideas for further research on UL51 protein function.

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Introduction: China is a large agricultural nation with the majority of the population residing in rural areas. The allocation of health resources in rural areas significantly affects the basic rights to life and health for rural residents. Despite the progress made by the Chinese government in improving rural healthcare, there is still room for improvement. This study aims to assess the spatial spillover effects of rural health resource allocation efficiency in China, particularly focusing on township health centers (THCs), and examine the factors influencing this efficiency to provide recommendations to optimize the allocation of health resources in rural China. Methods: This study analyzed health resource allocation efficiency in Chinese rural areas from 2012 to 2021 by using the super-efficiency SBM model and the global Malmquist model. Additionally, the spatial auto-correlation of THC health resource allocation efficiency was verified through Moran test, and three spatial econometric models were constructed to further analyze the factors influencing efficiency. Results: The key findings are: firstly, the average efficiency of health resource allocation in THCs was 0.676, suggesting a generally inefficient allocation of health resources over the decade. Secondly, the average Malmquist productivity index of THCs was 0.968, indicating a downward trend in efficiency with both non-scale and non-technical efficient features. Thirdly, Moran's Index analysis revealed that efficiency has a significant spatial auto-correlation and most provinces' values are located in the spatial agglomeration quadrant. Fourthly, the SDM model identified several factors that impact THC health resource allocation efficiency to varying degrees, including the efficiency of total health resource allocation, population density, PGDP, urban unemployment rate, per capita disposable income, per capita healthcare expenditure ratio, public health budget, and passenger traffic volume. Discussion: To enhance the efficiency of THC healthcare resource allocation in China, the government should not only manage the investment of health resources to align with the actual demand for health services but also make use of the spatial spillover effect of efficiency. This involves focusing on factors such as total healthcare resource allocation efficiency, population density, etc. to effectively enhance the efficiency of health resource allocation and ensure the health of rural residents.

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This study examines the effectiveness of the countries' health systems in the Horn of Africa region. It also investigates the perspectives of actors who have played an active role in health affairs in Somalia carried out by Türkiye. Using the Data Envelopment Analysis and Malmquist Total Factor Efficiency Analysis, we investigated the effectiveness of the health systems and improvements made throughout the years. In the countries of interest, efficiency levels and average total factor productivity showed positive and/or negative trends between 2000 and 2020. Kenya showed a marked performance in achieving improved average total factor productivity thanks to the effective use of current technology in health, success in integrating new technologies into the health system, and a high potential to produce more output despite insufficient existing inputs. The remaining countries lagged behind in improving their production factors. Since 2014, Türkiye has provided health services in Somalia through health diplomacy and conducted medical examinations for numerous patients in a well-equipped hospital.

Cette étude examine l'efficacité des systèmes de santé des pays de la région de la Corne de l'Afrique. Il étudie également les perspectives des acteurs qui ont joué un rôle actif dans les affaires de santé en Somalie menées par Türkiye. En utilisant l'analyse de l'enveloppe des données et l'analyses d'efficacité des facteurs totales de Malmquist, nous avons étudié l'efficience des systèmes de santé et les améliorations apportées au cours des années. Dans les pays intéressés, les niveaux d'efficacité et la productivité totale moyenne du facteur ont montré des tendances positives et/ou négatives entre 2000 et 2020. Le Kenya a fait preuve d'une performance marquée dans l'amélioration de la productivité totale moyenne du facteur grâce à l'utilisation efficace de la technologie actuelle dans le domaine de la santé, au succès de l'intégration de nouvelles technologies dans le système de santé et au potentiel élevé de produire plus de produits malgré l'insuffisance des produits existants. Les autres pays sont en retard dans l'amélioration de leurs facteurs de production. Depuis 2014, Türkiye a fourni des services de santé en Somalie par le biais de la diplomatie de santé et a effectué des examens médicaux pour de nombreux patients dans un hôpital bien équipé.

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Aim: This study aimed to evaluate the operational efficiency of traditional Chinese medicine (TCM) hospitals in China. Methods: Pearson's analysis was used to test the correlation between the input and output variables. Data envelopment analysis (DEA) was utilized to analyze the input and output variables of 16 TCM hospitals, and each hospital efficiency score was computed by Deap 2.1, assuming variable return to scale (VRS), which is an input-oriented model. t tests were conducted to confirm the significant difference of efficiency scores at the hospital level and by hospital type, and ANOVA was used to test for significant differences in efficiency scores according to hospitals' size. Results: The correlation coefficient of the input and output indicators was between 0.613 and 0.956 (p < 0.05). The difference in number of doctors (ND) and numbers of pharmacists (NP) were statistically significant (p < 0.05) at the hospital level. The mean efficiency scores for technical efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE) in secondary TCM hospitals were 0.766, 0.919, and 0.838, respectively. Additionally, the lowest TE, PTE, and SE were 0.380, 0.426, and 0.380, respectively. Eight TCM hospitals in this study were DEA efficient, with an efficiency score of 1. There were no statistically significant differences in TE, PTE, and SE among hospital levels, hospital types or hospital sizes groups (p > 0.05). Conclusion: This study revealed that tertiary TCM hospitals had a greater level of efficiency than secondary TCM hospitals. In our study, 50% of TCM hospitals had inefficient management. Therefore, to activate the new development power of TCM hospitals, it is necessary to reform and improve the management system and mechanism of TCM hospitals, optimize the development environment of TCM hospitals and formulate development plans and measures based on local conditions.

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The Water-Energy-Food (WEF) nexus approach is increasingly being used for supporting a transition to sustainable development, with initiatives involving the concept of circular economy (CE). In the agricultural sector in particular, assessing this nexus is crucial to ensure food security, control the consumption of key resources such as water and energy, as well as measure atmospheric emissions linked to climate change. This manuscript aims to propose a novel approach by coupling the WEF nexus with a circularity indicator, seeking to capture in a single index (the WEF+CEi) both performances in a sample of companies. The novel approach is applied to 30 dairy farms located in Galicia (NW Spain) to benchmark them in a holistic manner. To do this, the WEF nexus of each farm was represented through the following indicators: carbon footprint, water footprint, energy footprint, and food productivity. In addition, the percentage of circularity for each farm, and for the agro-industrial cooperative was measured thanks to the application of a circularity tool in percentage terms. Finally, the WEF+CEi indicator was obtained using the multicriteria mathematical tool of Data Envelopment Analysis (DEA). The results show that without considering the agro-industrial cooperative, the system is 51 % circular. On the other hand, considering the farms and the cooperative, the system goes up to 80 % of circularity. Finally, the proposed approach can support decision-making and provide insights for producers and stakeholders in the area.

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BACKGROUND: Medical diagnostic laboratories are an essential work environment that plays an important role in diagnosing, treating, and being sensitive to diseases. One way to evaluate laboratories' performance is to calculate their efficiency. This study investigates the efficiency of laboratories that are related to health centers in the south of Iran. METHODS: This study was conducted in 2021. The input numbers include: the number of technical personnel and the number of cell counters, and the output data includes: the scores obtained from the level 2 health laboratory evaluation list. And efficiency was calculated with DEAP software. The analysis is accomplished by the assumption of input-oriented. FINDINGS: The efficiency of laboratories of Orzueeyeh and Ravar Cities had the highest efficiency with the assumption of variable returns to scale efficiency 1, and the model of all laboratories is the laboratory of Ravar City. The laboratories of Kuhbanan and Rabor cities had the lowest efficiency with the assumption of variable returns to scale efficiency of 0.859 and 0.899, respectively. The average scale efficiency, Variable returns to scale, and constant returns to scale for laboratories in the cities of Kerman province are 0.842, 0.943, and 0.895, respectively. CONCLUSIONS: To increase the efficiency of laboratories, significant resources and funds should be used, as well as few studies have been done on the efficiency of laboratories, which requires more attention.

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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.

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The fishing sector constitutes an important source of economic revenue in northern Spain. In this context, various research studies have focused on the application of the five-step Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) methodology to quantify environmental impacts of fishing systems. However, some of them have used environmental indicators that focus on individual environmental issues, hindering the goal of achieving integrated resource management. Therefore, in this study, the Water-Energy-Food (WEF) Nexus is employed as an integrative perspective that considers the synergies and trade-offs between carbon footprint, energy requirements, and water demand. The main objective of this study is to evaluate the operational efficiency and environmental impacts of Cantabrian fishing fleets. To this end, the combined use of LCA and DEA, along with the WEF Nexus, was applied to the Cantabrian purse seine fleet. DEA matrices were generated using the LCA-derived WEF nexus values as inputs to calculate efficiency scores for each vessel. Subsequently, based on the efficiency projections provided by the DEA model, a new impact assessment was performed to understand the eco-efficiency and potential environmental benefits of operating at higher levels of efficiency within this fleet. The average efficiency of the fleet was above 60 %. Inefficient units demonstrated a greater potential to reduce their environmental impacts (up to 65 %) by operating according to efficiency projections. Furthermore, the results revealed a strong dependence of environmental impacts on one of the operational inputs, i.e., fuel consumption. These findings highlight the significance of embracing holistic approaches that combine technical, economic, and social factors to achieve a sustainable balance in fisheries systems. In this regard, the five-step LCA + DEA method applied in conjunction with the WEF Nexus emerged as a suitable tool for measuring operational and environmental objectives.

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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.

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The multifunctional tegument protein pUL21 of HSV-2 is phosphorylated in infected cells. We have identified two residues in the unstructured linker region of pUL21, serine 251 and serine 253, as phosphorylation sites. Both phosphorylation sites are absent in HSV-1 pUL21, which likely explains why phosphorylated pUL21 was not detected in cells infected with HSV-1. Cells infected with HSV-2 strain 186 viruses deficient in pUL21 phosphorylation exhibited reductions in both cell-cell spread of virus infection and virus replication. Defects in secondary envelopment of cytoplasmic nucleocapsids were also observed in cells infected with viruses deficient in pUL21 phosphorylation as well as in cells infected with multiple strains of HSV-2 and HSV-1 deleted for pUL21. These results confirm a role for HSV pUL21 in the secondary envelopment of cytoplasmic nucleocapsids and indicate that phosphorylation of HSV-2 pUL21 is required for this activity. Phosphorylation of pUL21 was substantially reduced in cells infected with HSV-2 strain 186 mutants lacking the viral serine/threonine kinase pUL13, indicating a requirement for pUL13 in pUL21 phosphorylation. IMPORTANCE: It is well known that post-translational modification of proteins by phosphorylation can regulate protein function. Here, we determined that phosphorylation of the multifunctional HSV-2 tegument protein pUL21 requires the viral serine/threonine kinase pUL13. In addition, we identified serine residues within HSV-2 pUL21 that can be phosphorylated. Phenotypic analysis of mutant HSV-2 strains with deficiencies in pUL21 phosphorylation revealed reductions in both cell-cell spread of virus infection and virus replication. Deficiencies in pUL21 phosphorylation also compromised the secondary envelopment of cytoplasmic nucleocapsids, a critical final step in the maturation of all herpes virions. Unlike HSV-2 pUL21, phosphorylation of HSV-1 pUL21 was not detected. This fundamental difference between HSV-2 and HSV-1 may underlie our previous observations that the requirements for pUL21 differ between HSV species.

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The extensive waste emissions and energy consumption in the construction industry has spurred calls for sustainable development reform. Identifying valuable development paradigms through evaluating the spatial-temporal environmental efficiency (EE) of the construction sector offers an effective avenue for practice guidance. However, a comprehensive and detailed global analysis of the construction sector's EE remains lacking. This study applies the super-slack-based measure (Super-SBM) model to assess EE of the construction sector across 112 countries from 2006 to 2016. The results reveal relatively low overall EE performance of global construction sector, with notable disparities among countries and improvements were observed in certain years. Singapore, Malta, and Paraguay emerge as top performers, while Moldova, Swaziland, and Iceland rank at the bottom. The findings highlight significantly better EE in European and coastal Asian countries compared to inland Asian and African nations. Using the Tobit model, we identify that industrial structure, trade dependency, international cooperation, energy intensity, and geographic factors significantly influence EE, with varying impacts across countries of different income levels. These findings provide a comprehensive overview of the global construction sector's environmental efficiency, emphasizing the urgent need for increased awareness and the adoption of sustainable practices. The study offers practical policy implications, advocating for targeted strategies to balance economic development with environmental protection.

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This study aims to evaluate the technical efficiency levels of healthcare systems in underdeveloped countries and to reveal the impact of COVID-19 along with some other factors on the efficiency levels via a two-stage data envelopment analysis. The study covers panel data from 2013 to 2020. The results show that technical efficiency scores decreased during the pandemic period. It is also understood from the results that immunization and the ratio of population ages 65 and above have significant and negative effects on inefficiency scores while carbon dioxide emissions have significant and positive effects. It is thought that the results of this study can guide decision-makers regarding efficiency gains in healthcare systems.

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The improvement of energy-related efficiency has promoted energy-sustainable development in China; however, it may be inhibited by energy poverty. This paper constructs an index system to measure China's energy poverty. Subsequently, we evaluate energy-related efficiency towards SDG7 comprised of energy production efficiency and energy sustainable utilization efficiency using a dynamic two-stage data envelopment analysis model. Furthermore, we adopt fixed effect models to quantify the impact of energy poverty on improving energy-related efficiency and the underlying mechanism. The findings indicate that: (1) China's energy poverty situation gradually improves from 2011 to 2020. The energy-related system's performance is medium due to the poor performance in its energy production stage in 30 provinces during 2011-2020. Energy-related efficiency is greater in areas with a higher response to SDG7. (2) The impact of energy poverty on improving energy-related efficiency is significantly negative. Addressing energy poverty significantly improves energy-related efficiency in regions characterized by a high energy poverty index and low energy-related efficiency. However, it bears no impact in regions with a low energy poverty index and high energy-related efficiency. (3) The moderating effect of technological innovation effectively improves energy-related efficiency, whereas the marketization level has an inverse effect. Consequently, this paper suggests several policy implications.

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BACKGROUND: With Primary Health Care (PHC) being a cornerstone of accessible, affordable, and effective healthcare worldwide, its efficiency, especially in developing countries like China, is crucial for achieving Universal Health Coverage (UHC). This study evaluates the efficiency of PHC systems in a southwest China municipality post-healthcare reform, identifying factors influencing efficiency and proposing strategies for improvement. METHODS: Utilising a 10-year provincial panel dataset, this study employs an enhanced Data Envelopment Analysis (DEA) model integrating Slack-Based Measure (SBM) and Directional Distance Function (DDF) with the Global Malmquist-Luenberger (GML) index for efficiency evaluation. Tobit regression analysis identifies efficiency determinants within the context of China's healthcare reforms, focusing on horizontal integration, fiscal spending, urbanisation rates, and workforce optimisation. RESULTS: The study reveals a slight decline in PHC system efficiency across the municipality from 2009 to 2018. However, the highest-performing county achieved a 2.36% increase in Total Factor Productivity (TFP), demonstrating the potential of horizontal integration reforms and strategic fiscal investments in enhancing PHC efficiency. However, an increase in nurse density per 1,000 population negatively correlated with efficiency, indicating the need for a balanced approach to workforce expansion. CONCLUSIONS: Horizontal integration reforms, along with targeted fiscal inputs and urbanisation, are key to improving PHC efficiency in underdeveloped regions. The study underscores the importance of optimising workforce allocation and skillsets over mere expansion, providing valuable insights for policymakers aiming to strengthen PHC systems toward achieving UHC in China and similar contexts.

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BACKGROUND: Policymakers, who are constantly discussing growing health expenditures, should know whether the health system is efficient. We can provide them with such information through international health system efficiency evaluations. The main objectives of this study are: (a) to evaluate the efficiency of health systems in 28 developed countries by multiple-criteria decision analysis (MCDA) and data envelopment analysis (DEA) and (b) to identify reasonable benchmark countries for the Czech Republic, for which we collect information on the relative importance of health system inputs and outputs. METHODS: We used MCDA and DEA to evaluate the efficiency of the health systems of 28 developed countries. The models included four health system inputs (health expenditure as a relative share of GDP, the number of physicians, nurses, and hospital beds) and three health system outputs (life expectancy at birth, healthy life expectancy, and infant mortality rate). The sample covers 27 OECD countries and Russia, which is also included in the OECD database. To determine the input and output weights, we used a questionnaire sent to health policy experts in the Czech Republic. RESULTS: We obtained subjective information on the relative importance of the health system inputs and outputs from 27 Czech health policy experts. We evaluated health system efficiency using four MCDA and two DEA models. According to the MCDA models, Turkey, Poland, and Israel were found to have efficient health systems. The Czech Republic ranked 16th, 19th, 15th, and 17th. The benchmark countries for the Czech Republic's health system were Israel, Estonia, Luxembourg, Italy, the UK, Spain, Slovenia, and Canada. The DEA model with the constant returns to scale identified four technically efficient health systems: Turkey, the UK, Canada, and Sweden. The Czech Republic was found to be one of the worst-performing health systems. The DEA model with the variable returns to scale identified 15 technically efficient health systems. We found that efficiency results are quite robust. With two exceptions, the Spearman rank correlations between each pair of models were statistically significant at the 0.05 level. CONCLUSIONS: During the model formulation, we investigated the pitfalls of efficiency measurement in health care and used several practical solutions. We consider MCDA and DEA, above all, as exploratory methods, not methods providing definitive answers.

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How to accurately assess logistics industry efficiency to identify production issues and provide support for optimizing logistics efficiency has become a current research challenge. Range adjust measure (RAM) is a method for efficiency assessment in data envelopment analysis. Currently, the RAM model only applies under the variable returns to scale condition and not to other conditions. This paper aims to establish a modified RAM (MRAM) model by revising the ranges for inputs and outputs of the RAM model. Under the constant returns to scale (CRS) condition, we first develop the RAM-CRS model. Then, by introducing radial models to define the lower bounds of inputs and the upper bounds of outputs, the MRAM is proposed. The logistics data from 18 provinces are collected to validate the practicality of the MRAM model. We compare the results of the MRAM with those of the RAM-CRS and conclude that the range bounds under RAM-CRS are too tight, which results in efficiency values at a relatively low level. The MRAM with modified bounds appropriately alleviates this restriction. We also compare the MRAM and the additive model. The results show that the efficiency of the MRAM is more accurate.

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This study investigates the potential economies of scope in the Norwegian public hospital sector after a major structural and organizational reform. Economies of scope refers to potential cost savings occurring from the scope of production rather than the scale. We use a data driven approach to distinguish between relatively specialized and differentiated hospitals. Using registry data spanning the period 2013-2019, we use non-parametric data envelopment analysis with bootstrapping procedures to investigate the potential presence of economies of scope. This is done separately for three different dimensions of which hospital production can be either specialized or differentiated. The findings suggest that economies of scope are present in the Norwegian hospital sector, meaning that there are cost savings related to the optimal differentiation of the activity. It is difficult to conclude on how these findings relate to the reform.

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Maternal, neonatal, and child health play crucial roles in achieving the objectives of Sustainable Development Goal (SDG) 2030, particularly in promoting health and wellbeing. However, maternal, neonatal, and child services in Moroccan public hospitals face challenges, particularly concerning mortality rates and inefficient resource allocation, which hinder optimal outcomes. This study aimed to evaluate the operational effectiveness of 76 neonatal and child health services networks (MNCSN) within Moroccan public hospitals. Using Data Envelopment Analysis (DEA), we assessed technical efficiency (TE) employing both Variable Returns to Scale for inputs (VRS-I) and outputs (VRS-O) orientation. Additionally, the Tobit method (TM) was utilized to explore factors influencing inefficiency, with hospital, doctor, and paramedical staff considered as inputs, and admissions, cesarean interventions, functional capacity, and hospitalization days as outputs. Our findings revealed that VRS-I exhibited a higher average TE score of 0.76 compared to VRS-O (0.23). Notably, the Casablanca-Anfa MNCSN received the highest referrals (30) under VRS-I, followed by the Khemisset MNCSN (24). In contrast, under VRS-O, Ben Msick, Rabat, and Mediouna MNCSN each had three peers, with 71, 22, and 17 references, respectively. Moreover, the average Malmquist Index under VRS-I indicated a 7.7% increase in productivity over the 9-year study period, while under VRS-O, the average Malmquist Index decreased by 8.7%. Furthermore, doctors and functional bed capacity received the highest Tobit model score of 0.01, followed by hospitalization days and cesarean sections. This study underscores the imperative for policymakers to strategically prioritize input factors to enhance efficiency and ensure optimal maternal, neonatal, and child healthcare outcomes.

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The rational allocation of carbon emission quotas is crucial for improving the orderly operation of carbon markets. As a major energy-consuming province in China, Jiangsu's cities must allocate allowable carbon emissions effectively to meet China's 2030 peaking target. This study aims to achieve an optimal allocation of carbon emission quotas by considering principles such as responsibility, efficiency, and equity. To accomplish this goal, we developed a three-stage progressive optimization allocation process. This process incorporates the entropy weight TOPSIS allocation model, zero-sum game-DEA model, and Gini coefficient. The initial allocation scheme revealed that cities in southern Jiangsu, which have higher economic development levels, also received higher carbon emission quotas, compromising efficiency and equity. In response, the second stage involves adjusting the allocation to optimize efficiency for each city, aligning the quotas more closely with historical levels. Finally, the third stage uses the Gini coefficient to further refine the allocation scheme, achieving a more balanced distribution that aligns responsibility, efficiency, and fairness. This research highlights the importance of a structured approach to carbon quota allocation, ensuring a balance that supports both environmental goals and equitable development.

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Countries have become increasingly concerned about the impact of their activities and their alignment with sustainable development goals. Consequently, it is necessary to examine their performance efficiency in a unified manner, accounting for economic, environmental, and social variables. A country's performance efficiency is defined as the ratio of observed output to frontier output, given the country's productive resources. In this paper, we use the frontier technique of Data envelopment analysis (DEA) to estimate the frontier output. The objective of this study is to assess the performance efficiency of 111 worldwide countries and to examine whether gender inequality, the share of renewable energy consumption, the government control of corruption and government expenditure on education could explain differences in performance. We employed the non-parametric DEA model using three inputs (capital, labor, and primary energy consumption) and one output (GDP). We also considered an additional output (CO2 emissions); however, the results were identical to the one output model because CO2 emissions and primary energy consumption are highly correlated (0.96). We find that there is a negative impact of gender inequality, a positive impact of the share of renewable energy consumption and government control of corruption on performance efficiency. Our results also indicate that reducing CO2 emissions required transitioning towards renewable energy and using the energy efficiently. However, we did not find a positive relationship between government expenditures on education and country efficiency.

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