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Supply chain resilience (SCRes) as the supply chain network's (SCN) capacity is essential to recover from disruptions. The economic, environmental, and geopolitical regional characteristics of the Pacific region present many challenges and opportunities for building supply chain resilience. This study aims to measure the resilience of supply chains (SCs) considering the characteristics of the network under which they operate. In this study, we proposed a new common set of weights (CSW) model in data envelopment analysis to evaluate the resilience of SCNs. Many external variables beyond decision-makers' direct control impact SC operations and their resilience. Therefore, the proposed CSW model formulates the non-discretionary and non-controllable inputs in measuring the resilience of SCNs and provides a complete ranking with a higher discrimination power. To improve SCRes, SC managers are recommended to enhance the clustering coefficient and node degree of their SCN by establishing more connections with other SCNs in order to pinpoint the essential capabilities that companies should prioritise in order to develop a stronger and more adaptable SC in the post-COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Measuring and understanding the evolution of the electricity generation efficiency sector is a relevant task for policymakers. This study focuses on assessing the determinants of electricity generation efficiency across 24 countries in Latin America and the Caribbean between 2000 and 2020. A hurdle model was employed to account for the censored nature of the dependent variable. The findings show a positive impact of opening up the electricity sector in fully efficient countries. Market liberalization and the involvement of privately owned power plants contribute to efficiency gains in inefficient countries. Additionally, the tariff protectionism level exhibits positive effects for completely efficient and inefficient countries. These results provide valuable insights, as less-efficient countries can glean strategies from their more efficient counterparts to enhance their electricity generation efficiency. [ABSTRACT FROM AUTHOR]

This paper proposes a new proportional-sharing approach for fixed cost allocation (FCA) among a group of decision-making units (DMUs) based on data envelopment analysis (DEA). We first prove the proportional invariance in DEA-based FCA. Then, we show that the "all-efficient" assumption in existing models usually leads to the use of unrealistic weights in efficiency analysis. To address this issue, we relax this assumption and adopt a weight constraint approach. Further, we illustrate that some DMUs would always be allocated with zero fixed cost if only the goal of efficiency maximizing is considered. Therefore, some weight constraints are added, and a new bi-objective model is proposed to allocate the fixed cost among the DMUs in order to simultaneously maximize the efficiencies of the DMUs and make the allocation as close as possible to the one generated according to the DMUs' operation sizes. A mono-objective nonlinear program, which can be solved using dichotomy and a linear program solver, is used to obtain a non-dominated or Pareto-optimal trade-off solution for the bi-objective model. With the use of our approach, neither unrealistic weights nor zero fixed cost appears in the result. Finally, the proposed approach is applied to a numerical example and a commercial bank case study. [ABSTRACT FROM AUTHOR]

Multilevel measurement models are more frequently applied to help answer questions when data arise from hierarchically structured multivariate data. In this simulation study of multilevel factor models, we evaluated the relative efficiency among three estimation methods: robust maximum likelihood, unweighted least squares, and weighted least squares. We found that weighted least squares yielded more or equally efficient parameter estimates under all sample size conditions for all model parameters. The relative efficiency of standard errors was less straightforward where maximum likelihood was more efficient for loadings and residual variances, but weighted least squares was more efficient for the factor covariance matrices. Finally, we give recommendations for estimating multilevel confirmatory factor analysis models and directions for future research. [ABSTRACT FROM AUTHOR]

Since the mid-1990s, the main airports in Latin America have been privatised. This is the result, on the one hand, of the liberalisation of the aviation industry in almost all the countries of the region, and on the other hand, of the application of an extensive and uninterrupted programme of air public policies, currently underway. Based on this, this paper first analyse how public policies have influenced the development of airports in Latin America, generating the privatisation of the most important in the region (in a context of structural reform still in progress). Second, it studies how the COVID-19 pandemic affected the technical efficiency of the privatised airports in the region. Therefore, in this paper, the measurement of technical efficiency is carried out (using only technical variables, that is, infrastructure and aeronautical or air traffic variables) on a representative set of Latin American privatised airports, both in the pre-pandemic period (2017–19) and in the severest pandemic period (2020). The methodology used to carry out the study is data envelopment analysis (DEA). The main results of the research reveal high, and in some cases ideal, technical efficiency indices in the pre-pandemic period, and not very severe drops in technical efficiency in the pandemic period. [ABSTRACT FROM AUTHOR]

This study aimed to apprehend the scale’s role in education planning and performance. The national scale approaches tend to neglect local specificities. The relevance of the provincial and local scales is underlined in Draa-Tafilalet region (Morocco). By comparing the provincial data and indicators to study the education system’s efficiency, we argue that these are pertinent scales to further understanding the needs, causality and key parameters of education. Collected data is analyzed using the data envelopment analysis (DEA). Useful indicators to compare the spatial variability of the education system’s efficiency were produced and discussed at a provincial scale and interpreted considering the local socioeconomic characteristics in each province. The five provinces of the region (Errachidia, Ouarzazate, Tineghir, Midelt, and Zagora) are considered as adapted decision-making unit (DMU) in the study. The results show the provincial scale is relevant to apprehend the education system’s performance. It is also important in education planning. The spatial differences in education efficiency at this scale show evidence of weak education impacts among rural populations in the recently created provinces such as Tineghir, Midelt, and Zagora. The criterion of education efficiency measured by DEA ranks Tineghir in the last position. This province needs special attention in planning and development. [ABSTRACT FROM AUTHOR]

Copyright of Efil Journal of Economic Research / Efil Ekonomi Araştırmaları Dergisi is the property of Efil Journal of Economic Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

RESEARCH OBJECTIVES: Innovation is a significant factor in socio-economic development, and it is principal in achieving a competitive advantage among enterprises, regions, and countries. The purposes of this paper are: (1) to present, on the basis of the available literature, the essence and metrics of eco-innovation activities in EU countries, (2) to analyze the effectiveness of eco-innovation activities in EU countries using the Data Envelopment Analysis (DEA) method. THE RESEARCH PROBLEM AND METHODS: The research primarily focuses on a review of the recent literature and an analysis of the efficiency of eco-innovation activity using the DEA method. The empirical analysis is based on the Eco-innovation Scoreboard. THE PROCESS OF ARGUMENTATION: The analysis mainly determines the efficiency of eco-innovation. The theoretical basis for the considerations is a diagnosis of the existing state of eco-innovation in EU countries. RESEARCH RESULTS: The results illustrate the efficiency of eco-innovation activity in some EU countries against the backdrop of other EU countries. The analysis of eco-innovation activities and strategies to support them in the EU countries presented in this study is based on a diagnosis of the current state of their economies in this area using the methods of DEA and literature review. The results of this research enable us to draw concrete conclusions on the efficiency of eco-innovation activities. CONCLUSIONS, INNOVATIONS, AND RECOMMENDATIONS: The results of the Eco-innovation Scoreboard for these countries illustrate an inefficient use of materials, water and energy resources, as well as low resource productivity. The gaps in this scope between Central-Eastern and Western EU countries are diminishing, but there are still institutional, legislative, and economic shortcomings in eco-innovation that should be addressed. The analysis indicates the level of eco-innovation development in EU countries, its efficiency, and the potential for supporting activity in this field by these countries. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to examine the relationship between economic freedom and Islamic rural banks' efficiency in the case of Indonesia. Design/methodology/approach: The study covers 40 Islamic rural banks in 34 Indonesian regions from 2014 to 2020. Tobit regression is utilized to expose the impact of economic freedom on the efficiency of Islamic rural banks, and nonparametric frontier data envelopment analysis is used to acquire banks' technical efficiency. Findings: The findings reveal that overall economic freedom has a strong favorable impact on the efficiency of Islamic rural banks. The study's breakdown components suggest that business freedom, government spending and investment freedom are favorable indicators, whereas government integrity and tax burden are negative indicators, and all indicators agree with previous studies. Practical implications: This research can serve as a guideline for Islamic rural bank management in terms of maintaining financial efficiency. The government should think about the ramifications of financial sector liberalization and reforms, according to these findings. When financial intermediaries operate in a less constrained environment, they are more likely to pursue competitive practices that increase their operating rate and other efficiency metrics. Finally, academics might utilize this information to investigate the economic flexibility of Islamic rural banks. Originality/value: The novelty of this study is in using data envelopment analysis and Tobit regression to identify economic freedom and Islamic rural banks' efficiency. To the best of the authors' knowledge, the study of the role of economic freedom in Islamic rural bank's efficiency is limited, particularly in the context of Indonesia. [ABSTRACT FROM AUTHOR]

In this research we evaluate the impact that various types of private contributions to public schools can have on their performance. We start from the assumption that greater involvement in the social role of business is key to accelerating the achievement of development goals. Although there is abundant literature that measures different types of effects from private aid to education at an individual level, this study provides an aggregate measure of the effect of simultaneous interventions. We use a benchmarking approach on a sample of 269,117 Colombian students from 1,224 schools, of which 53% received some assistance. The findings may help to stimulate companies to participate in solving the problems of development, while calling attention to some social criteria that can improve the allocative efficiency of such resources. The results suggest that a consistent process of accountability is also required to quantify the real impact of these contributions. [ABSTRACT FROM AUTHOR]

This study aims to present the meaningful implications of introducing a tramway as a new mode of transportation in the Daejeon Metropolitan Area, a major metropolitan area in South Korea. An efficiency comparison by data envelopment analysis (DEA) was carried out, using variables selected from the 2021 Public Transportation Investigation by the Korea Transportation Safety Authority (KTSA) (2021), and the 'Guidelines for selecting new transportation means' announced by the Ministry of Land, Infrastructure, and Transport in 2021. As a result, the efficiency of public transportation in major metropolitan areas outside of the capital region was higher than in the capital metropolitan area. In particular, the Daejeon Metropolitan Area ranked high in efficiency compared to other major metropolitan areas with similar conditions. In the V-super efficiency results of the efficiency model based on the input of operational costs for each new mode of transportation, considering variable returns to scale (VRS), the bus rapid transit (BRT) ranked first, the tramway second, and the bimodal tram third. Regarding construction cost input, the tramway ranked first, the bimodal tram second, and BRT third. [ABSTRACT FROM AUTHOR]

This paper addresses the efficiency measurement of firms composed by multiple components, and assessed at different decision levels. In particular it develops models for three levels of decision/production: the subunit (production division/process), the DMU (firm) and the industry (system). For each level, inefficiency is measured using a directional distance function and the developed measures are contrasted with existing radial models. The paper also investigates how the efficiency scores computed at different levels are related to each other by proposing a decomposition into exhaustive and mutually exclusive components. The proposed method is illustrated using data on Portuguese hospitals. Since most of the topics addressed in this paper are related to more general network structures, avenues for future research are proposed and discussed. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Social Security / SGD-Sosyal Güvenlik Dergisi is the property of Journal of Social Security / SGD-Sosyal Güvenlik Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The issue of measuring and analyzing the dynamics of financial performance and trading efficiency is continuously current, significant and complex. Based on that, this paper measures and analyzes the financial performance and efficiency of trade in Serbia using the strategic profit model and the DEA ( Data Envelopment Analysis) Super-Radial model. According to the strategic profit model, the financial performance of trade in Serbia has recently improved. According to the results of the Super-CCR-I model in the period 2002 - 2020 trade in Serbia was not efficient in any year. According to the results of the Super-CCRO model, trade in Serbia in the period 2002-2020 was not efficient in any year. According to the results of the Super-BCC-I model in the period 2002 - 2020, trade in Serbia was efficient in 2020. According to the results of the Super-BCC-O model, trade in Serbia in the period 2002 - 2020 was efficient in 2002 and 2015. In order to to improve the financial performance and efficiency of trade in Serbia in the future, it is necessary to manage input - output elements (human resources, assets, capital, sales and net profit) as efficiently as possible. Digitization of the entire business plays a significant role in this. [ABSTRACT FROM AUTHOR]

Appraising some sustainability indicators for changes of others, or comprehensively assessing all metrics, while maintaining sustainability performance, is a crucial consideration for decision-makers. Moreover, numerous real-world applications involve factors that possess an ambiguous status as either input or output, commonly referred to as flexible measures, as well as imprecise measures. Accordingly, this research introduces a fuzzy flexible directional distance model for evaluating sustainable systems with fuzzy flexible measures. Subsequently, a fuzzy inverse directional distance approach, founded on data envelopment analysis and incorporating flexible measures, is proposed to assess the alteration of some imprecise sustainability criteria in response to changes in other measures while maintaining sustainability performance. Also, the modifications of all sustainability dimensions are dealt with while the sustainability performance level remains unchanged. An instance of numerical illustration and practical implementation within the healthcare industry has been presented to showcase the introduced methodology. The findings suggest that the technique proposed in this study has proven to be advantageous and enlightening for evaluating specific dimensions of sustainability in relation to alternations of other indicators or comprehensively addressing modifications of all sustainability indicators, while simultaneously preserving the ability of entities with fuzzy flexible measures. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The first problem in merging units is an estimation of the inherited inputs/outputs of the merged unit from merging units and the identification of the least and most achievable efficiency targets from the merged unit is the second one. There are some models to attain a response to these problems. However, these models could not be employed when a deviation from the frontier is observed due to noise and random error in the data. In order to deal with this problem, this paper presents a novel method according to inverse data envelopment analysis for estimating the inherited input/output levels of the merged unit to reach the pre-determined efficiency score in the level of significance α ∊ (0; 1). This paper also suggests a stochastic programming model for estimating the least possible efficiency score via the given merging. The practical applicability of these proposed methodologies is further validated through a comprehensive example within the banking sector. [ABSTRACT FROM AUTHOR]

Objective: This research paper aims to evaluate the relative efficacy of pharmacognosy research on the top 40 tertiary hospitals and its pharmacy in India according to Newsweek's 2021 ranking. Purpose: India's pharmaceutical market is now estimated to be worth $50 billion. India is a significant pharmaceutical exporter, reaching more than 200 nations with its exports. This study will help to identify whether the pharma industry is working efficiently in selected Indian hospitals or not. Thus, to create a bench marking for the hospital pharmacies in India. Design/methodology/approach: Data for the study came from public and private hospitals' official websites, financial records, and government notifications. Crosssectional data analyses were done using a Slack-Based model and data envelopment analysis (DEA). STATA was the software used to scrutinize the results effectively. Results: Thirteen hospital pharmacies out of a total of 40 are judged to be relatively technically efficient overall, according to the research. The findings of the slack analysis demonstrate that government hospitals and pharmacies are better able to handle slack and effectively manage input and output. Conclusion: The researchers also set upped a benchmarking hospital both for private and government healthcare settings for pharmacognosy research. Thus, it can be utilized for the betterment of the pharmacies. [ABSTRACT FROM AUTHOR]

Objectives: To assess the relative productivity of primary medical services in England and the impact of the COVID-19 pandemic on productivity levels. Setting: Primary medical services for 59 million patients (98% of the population in England), in 101 clinical commissioning groups (CCGs), across two time periods: period 1, pre-pandemic, April to December 2019 and period 2, pandemic, April to December 2020. Methods: We use data envelopment analysis (DEA) to assess relative productivity with four input measures (the number of full-time equivalent general practitioners, nurses, other direct patient contact staff and administrators), and five output measures (face-to-face appointments, remote consultations, home visits, referrals to secondary care and prescriptions). Our units of analysis were CCGs. DEA assigns an efficiency score to a CCG, taking a value between 0 and 100%, by benchmarking it against the most productive CCGs. We use Tobit regression to examine the association between productivity and other factors. Results: The mean bias-corrected efficiency score of primary medical services in CCGs was 92.9% (interquartile range 92.0% to 95.7%) in period 1, falling to 90.6% (interquartile range 86.8% to 95.2%) in period 2. In period 1, CCGs with a higher proportion of registered patients aged over 65 years, higher levels of deprivation, lower levels of disease prevalence, higher nurse to GP ratios and higher GP to other direct patient contact staff ratios, achieved statistically significantly higher general practice efficiency scores (p < 0.05). In period 2, only the ratio of GP to other direct patient contact staff was associated with efficiency scores (p > 0.05). Conclusions: Our analysis indicates only modest geographic variation in productivity of primary medical services when measured at the level of clinical commissioning groups and a small reduction in productivity during the pandemic. Further work to establish relative productivity of individual GP practices is warranted once sufficient data on appointment rates by GP practice is available. [ABSTRACT FROM AUTHOR]

The main goal of every company is to gain as much profit as possible, and a very important goal is also to obtain a competitive advantage in the market. In this paper, it has been developed and applied an integrated model, which is based on a PCA-DEA-MCDM approach, with the aim of evaluating the efficiency of a transport company from Bosnia and Herzegovina. At the very beginning, using the PCA (Principal Component Analysis)–DEA (Data Envelopment Analysis) model, efficient and inefficient business years were identified, and then, using CRITIC (Criteria Importance Through Inter Criteria Correlation) and the Entropy method, weight values of defined parameters were determined. After that, the decision-making units were ranked using MARCOS (Measurement Alternatives and Ranking according to the Compromise Solution). In addition, the sensitivity analysis includes the formation of scenarios of changes in weight values of five most significant criteria and the calculation of SCC and WS correlation coefficients. The application of this integrated model, in addition to identifying efficient/inefficient years of operation, enables the identification of influencing factors of the most efficient year of operation, which can serve as a benchmark to further contribute to the efficiency of the transport company. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper investigates Public Sector Performance (PSP), Public Sector Efficiency (PSE), and Data Envelopment Analysis (DEA) scores for 11 CEE countries, using the methodology proposed by Afonso et al. (various years). Our calculations are based on seven components of the public sector, described by 12 opportunity indicators and six Musgravian indicators. Moreover, we adapt and extend the Afonso, Schuknecht, and Tanzi methodology in order to be able to compute annual scores for PSP and PSE. The results show that expenditure performance is higher in the group of medium-sized governments. Additionally, medium-sized government groups obtained the highest efficiency scores. [ABSTRACT FROM AUTHOR]

One of the sophisticated mathematical techniques for evaluating the relative efficiency of decision-making units (DMUs) in a multi-inputs-output setting is data envelopment analysis. A non-parametric productivity index called the Malmquist index (MI) tracks changes in a DMU's overall factor output over time. This study seeks to present a broad overview of the changes in the MI for nearly all of the world's nations over 19 years beginning in 3061. This research evaluates a time series data set made up of 16 economic indexes. Each nation's MI, which compares 2000 and 2019, shows how each nation has changed over that period. One of the most important purposes of this study comparing the countries by their MI is that it allows for a fair comparison of productivity across different time periods and regions. It also provides insights into the sources of productivity growth, such as changes in technology or improvements in efficiency. As a result, the countries can allocate resources more wisely and develop more effective investment plans by understanding the elements that lead to productivity increase. By implementing some statistical techniques, nations are further divided into four categories based on their MI. Furthermore, a yearly distribution of the MI has been included to illustrate its trends between the years 2000 to 2019. Finally, the changing flow for some countries of each category is shown in three-year tracks. [ABSTRACT FROM AUTHOR]

Purpose: Zakat is an important Islamic economic instrument that plays significant role in Sustainable Development Goals. Accordingly, Zakat Institutions must manage zakat in a proper and efficient manner. This study aims to examine the efficiency of Zakat Institutions based on their clusters which are government, business and social organizations. Design/methodology/approach: This study uses three quantitative methods: data envelopment analysis (DEA), free disposal hull and super-efficiency DEA. The analytical method is based on production approach, variable return to scale assumption and output orientation. The sample consists of 14 Zakat Institutions from three clusters: Zakat Institutions managed by government, Zakat Institutions managed by corporation and Zakat Institution managed by social organizations. Findings: The results revealed that all of three techniques culminate the same ranking order of efficiency. Zakat Institution managed by the government is the most efficient Zakat Institution, with the average value of 0.87 by using three approaches combined. Meanwhile, Zakat Institutions owned by company and social institutions cluster are in second and third position, with the average value of 0.65 and 0.4, respectively, based on the results of the three approaches. This study contends that the level of efficiency of Zakat Institutions may be supported by clusters (affiliations) in their management. Research limitations/implications: This study's limitation is the inadequacy of the required data. Nonetheless, this study provides insights to improve the efficiency of Zakat Institutions based on their clusters. Zakat Institutions in each cluster can improve their efficiency by optimizing inputs to produce multiple outputs. Originality/value: This study enhances research on the efficiency of Zakat Institutions using three methods to assess the consistency and strength of Zakat Institutions' efficiency values. In addition, this study examines the efficiency level of Zakat Institutions based on their clusters. [ABSTRACT FROM AUTHOR]

With the epidemics in recent years (such as Covid-19), the importance of efficiency in the health sector has been understood once again. The fact that human needs are unlimited but resources are scarce has created the understanding that resources should be used at the most optimal level in the domain of health, as in every domain. Data Envelopment Analysis, which provides the opportunity to evaluate the efficiency by making it possible to compare the performance of enterprises in the same sector, is widely used in many research areas. In this study, it is purposed to assess the service efficiency in the health sector of the Statistical Regional Units Classification-1 (NUTS-1) regions in Turkey. As a result of the literature review, 3 input and 3 output variables were selected and health data in 12 regions were subjected to Data Envelopment Analysis (DEA). Input-output variables ascertained for DEA methods in the study were acquired from the Ministry of Health Statistical Yearbook 2020 reports. The data were conveyed to the "R" program and analyzed according to both inputoriented as well as output-oriented CCR and BCC models. Considering the control power of the input-oriented BCC Model, this model was preferred, and potential improvement rates were calculated by creating reference sets for ineffective DMUs. According to the BCC model based on the health indicators of the provinces, it was deduced that solely 3 regions out of 12 were inefficient, and all other regions were effective in terms of health indicators. Potential recovery rates for inactive areas are presented. In order to increase the quality of the health services provided, it is critical to evaluate the current situation of the regions. This study makes an important contribution to the literature in terms of analyzing the productivity of the regions using up-to-date data and presenting suggestions for inactive regions. In addition, when the findings of the study are compared with the existing literature, it is seen that the findings overlap with the findings of the existing studies. [ABSTRACT FROM AUTHOR]

This paper aims to examine how the data envelopment analysis (DEA) technique can be applied to evaluate managerial ability and productivity growth for 29 European forest sectors over the period 2011–2020. Toward this end, we first applied DEA to evaluate the technical efficiency (TE) from both periodical-frontier and met-frontier perspectives in which results showed that the average TE was 0.645 and the annual operating efficiency of the years studied was reduced by 35%. A modified regression test is secondly developed in order to determine the effect of contextual variables on the log of TE. The findings showed that the regional density, time series and gross domestic product had the highest positive influence on improving the TE results, respectively. In the following, by considering the explanatory variables, a modified DEA-based Malmquist productivity index is used to calculate the productivity growth over the period 2011–2020. The results indicated that there was a decline of 12% for total factor productivity in 2019–2020 compared to 2014–2015 and 7% compared to 2015–2016 which is due to the uniform growth of technological change (TC) and efficiency change recession compared to previous periods. Hence, productivity growth is mainly due to frontier shift (TC). [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic caused an unusual population mortality rate. This paper aims to determine a causal relationship and its incidence between the Technical Efficiency (TE) of health systems and the Covid-19 mortality rate. Using the Data Envelopment Analysis (DEA) methodology and the OLS, GLS and 2SLS adjustment methods, in 108 countries grouped according to per capita health expenditure, it was found that a 1% increase in the TE of the health systems of the analyzed countries reduces the number of deaths from Covid-19 by between 61 and 127 per hundred thousand inhabitants, concluding that the efficiency of expenditure was transcendental in the prevention of mortality caused by the pandemic. [ABSTRACT FROM AUTHOR]

The study looked into the use of input in sesame production with the view on seeing the returns to its production in Ringim Local Government Area, Jigawa State, Nigeria. Data were obtained from 100 randomly selected farmers using the multistage sampling technique. Descriptive statistics, net farm income and regression model were used in data analysis. The result showed that the mean age of the respondents was 38 years with secondary education been most popularly attained. The respondents had a household size of 3 persons cultivating a farm size of 3.5ha with experience of 8 years on average in sesame production. The results also reveal net farm income and return on naira invested of N 46,190.59 and 1.54 respectively, an indication of a profitable enterprise. The semi-log functional form gave the best fit based on the normal econometric criteria with coefficient of multiple determination of 0.312 implying that about 31 percent of the variation in yield of sesame was explained by the specified explanatory variables. It also revealed that there was under utilization of all the production inputs under consideration. It is therefore encouraged that more of the limiting factors (farm size, quantity of seed and quantity of organic manure) observed be put into cultivation. [ABSTRACT FROM AUTHOR]

Using Data Envelopment Analysis (DEA) oriented to input resources under variable returns to scale, the efficiency of production factors by administrative-territorial areas of Bulgaria as of 2021 in terms of gross value added (GVA) has been assessed. It is established that the factors of production are used effectively in only five of the 28 districts of Bulgaria. These efficiency regions are Vratsa, Gabrovo, Sofia, Sofia (capital) and Stara Zagora. The average value of the efficiency coefficient is 0.8178 and shows that the produced GVA in Bulgaria in 2021 should be achieved on average with 18.22% less production factors than the used ones – costs for acquiring fixed assets and employed persons. In connection with the latter, it is rational to direct production factors toward economic activities in which there are competitive advantages and potential for development on the territory of the respective area. [ABSTRACT FROM AUTHOR]

Copyright of Tourism & Management Studies is the property of Escola Superior de Gestao, Hotelaria e Turismo, Universidade do Algarve and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Producao Online is the property of Associacao Brasileira de Engenharia de Producao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Producao Online is the property of Associacao Brasileira de Engenharia de Producao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Data envelopment analysis (DEA) model has been applied for evaluating bank branches and recognizing efficient and inefficient branches can help bank managers to provide appropriate strategies to improve the inefficient branches' performance. Conventional DEA models are based on the 'black box' approach. However, the process of providing services in banks is made up of interactive and interdependent processes. Additionally, some managers tend to incorporate their preferences in evaluation process. In this paper, best worst method (BWM) is used for incorporating decision maker (DM) preferences in two‐stage DEA model. First, BWM model is applied to obtain the weights of inputs, intermediate measures and outputs based on DM's judgement. Second, generated weights are imposed on two‐stage DEA model as additional constraints and a novel bi‐objective BWM‐two stage DEA model is introduced. Finally, the proposed bi‐objective BWM‐two stage DEA model is solved using min‐max approach. To illustrate the capability of proposed model, 45 Agricultural Bank (Agribank) branches in West Azerbaijan province of Iran are evaluated. The branches' processes are considered as two stages 'production' and 'profitability' and efficiency of branches are calculated in each stage. According to the efficiencies of each sub‐stage, branches are divided to four groups and recommendations are made for each group. [ABSTRACT FROM AUTHOR]

This research aims to design a helpful methodology for estimating universities' relative impact on students as a sustainability factor in higher education. To this end, the research methodology implemented a two-stage approach. The first stage involves the relative efficiency analysis of the study units using Fuzzy Data Envelopment Analysis. The second stage consists of a predictive evaluation of the efficiency of the study units. Consequently, among the most relevant results of the research, it is observed that the methodology identifies the institutions that need to strengthen the academic competencies of the industrial engineering program. Additionally, we developed a benchmark analysis called Efficient Route to help inefficient units achieve efficiency, associating efficiency, and sustainability as pillars of higher education processes. [ABSTRACT FROM AUTHOR]

The efficiency of bulk solid and general cargo terminals, where ore, grain, and many raw materials are handled, plays a crucial role in socioeconomic development and lays the groundwork for reasonable trade costs. This study evaluates the relative performance of drybulk and general cargo terminals in Türkiye with interval data envelopment analysis (DEA). The dataset consists of 21 terminals operated by private companies for 2018-2021 and has been transformed into an interval form to apply interval DEA to imprecise data. The results imply that the efficiency levels of dry-bulk and general cargo terminals in the Marmara and Mediterranean tend to increase. It can be inferred that the average efficiency level of the Black Sea terminals has remained stable over the years, and the loss of efficiency in the Aegean is remarkable. The application of the Interval DEA in evaluating the efficiency of dry-bulk and general cargo terminals in the case of imprecise data can contribute significantly to the seaport efficiency literature. [ABSTRACT FROM AUTHOR]

The study aims to evaluate the efficiency of the Republic of Kazakhstan's healthcare sector over the period 2014-2021 using the non-parametric method of data envelope analysis. The analysis was carried out based on quantitative indicators of the medical statistics of the Republic of Kazakhstan. The study's results prove that efficiency tends to change over the medium term. Simultaneously, implementing digital technologies based on the computerisation and digitalisation of the healthcare sector in the short term is revealed to reduce overall efficiency, but that efficiency increases in the long term. The events of the COVID-19 pandemic did not reduce the overall efficiency of the healthcare sector in the Republic of Kazakhstan.

The research aims to determine the level of TPI efficiency using the DEA (Data Envelopment Analysis) method in the research area. The sampling technique used was purposive sampling with judgment. The data source used is secondary data collected through Annual Reports. Data collection was carried out in two ways, namely documentation and literature. The analysis method used is the DEA (Data Envelopment Analysis) method with indicators for the input variables used: floor area, base length, number of boats, number of baskets, number of fishing gear, and indicators for the output variables used: Total production. The results of the research are the efficiency of the Sibolga Fish Auction Place which has a score of 100% in January, February, March, and April. In November it gets an efficiency score of 92.07%. This efficiency is at a high level of efficiency because it gets a value of > 81%. while efficiency in May, June, July, August, September, October, and December is 60-80%. This efficiency is at a medium efficiency level because it gets a value of 60-80%. Fish Auction Places in Sibolga that have achieved high efficiency in January, February, March, April, and November have been able to utilize input optimally to manage output. Meanwhile, moderate efficiency was shown in May, June, July, August, September, October, and December. It is hoped that we can utilize input optimally to manage output.

This paper aims to determine the factors affecting cost and profit efficiency of commercial banks in Turkey and to examine the ownership effect on cost and profit efficiency in an emerging market. Another aim of the study is to carry out the most recent and longitudinal (2006-2020) analysis of efficiency in the Turkish banking industry. This study uses an intermediation approach with data envelopment analysis (DEA) as its methodology. A total of 23 commercial banks were selected as the study sample and their quarterly data from 2006- 2020 was collected. In addition, an external two-stage DEA model with Tobit regression was applied to examine the determinants of cost and profit efficiency. The results show that Turkish banks currently work with relatively higher cost efficiency than profit efficiency. On the other hand, foreign banks display a lower cost and profit efficiency performance. The downward trend in profit efficiency in the Turkish banking system sends a warning signal on the health and stability of the banking sector. Multivariate Tobit regression analysis reveals how Total Assets, Deposit Share, Asset Growth, Time Deposits, NPL, and Ownership Structure significantly affect cost and profit efficiency. Ratio of liquid assets to total assets is positively correlated with the efficiency values, in contrast to results from previous studies. Previous studies have mostly been limited to scale and technical efficiency and focused on the cost efficiency of Turkish banks. In this study, the gap in the literature is filled by a comparative examination of the cost and profit efficiency at the scale of bank ownership. The study will look at and discussed these issues at the most stable period and the pre-pandemic period in the Turkish economy.

Purpose. This research aims to analyze the level of economic efficiency of cassava farming and the determinants that affect the efficiency level in the Wonogiri Regency, Indonesia. Methodology / approach. The research location was determined using the stratified random sampling method, and three sub-districts were selected in Wonogiri Regency, namely Ngadirojo, Jatiroto, and Puhpelem. Furthermore, this research used a random sampling method with respondents of 74 monoculture cassava farmers. The analysis method was the Data Envelopment Analysis (DEA) approach to analyze the economic efficiency of cassava farming and Tobit regression to analyze the determinants that affected it. Furthermore, primary data was obtained from respondents through interviews, and secondary data as a complement was obtained from relevant agencies. Results. This research showed that the level of economic efficiency (EE) of cassava farming in the Wonogiri Regency was 68.3 %. From the results of economic efficiency, there was an opportunity to improve efficiency by reducing input inefficiency by 13.1 % and minimizing input costs by 21.1 %. The determinants of factors that affected cassava farming were considered from the socio-economic factors, namely experience, educational level, and participation of farmers in farmer groups. Originality / scientific novelty. Studies on the effectiveness of cassava have never been conducted in Central Java, even though Central Java is one of the three centers of cassava production in Indonesia. The efficiency of farming cassava in this research was not only considered from the technical side but also from the allocative and economic side, as well as the socio-economic character of the farmer’s environment. This research analyzed the efficiency of cassava farming with a nonparametric approach, namely Data Envelopment Analysis. Usually, efficiency research is approached with parametric analysis, namely production function analysis with Stochastic Frontier Analysis (SFA). Practical value / implications. It is recommended to use optimal inputs, especially seeds and fertilizers, which can be applied in cassava farming to reduce inefficiency. The need for fertilizer is related to the land’s condition, where the land in Wonogiri Regency has a steep slope, making it prone to erosion and sedimentation. Then, it affects the decline of the soil layer and the need for fertilizer. The role of the government is required because it is necessary to facilitate access to farmers and provide information about input use.

Purpose – This study aims to analyze the efficiency of BAZNAS performance for 20 years, during 2002-2021. Methodology – This research uses a quantitative approach with the Data Envelopment Analysis (DEA) method. The secondary data source is an annual report from the official National Amil Zakat Agency (Badan Amil Zakat Nasional, BAZNAS) website from 2002-2021. The analysis technique is assisted by maxDEA software. Findings – The results showed BAZNAS gained an average efficiency of over the period 2002 - 2021 worth 90.86%, meaning that over the 20 years, BAZNAS operated showed a level of inefficiency. Further analysis, during 2018-2021, BAZNAS has shown its productivity in improving performance efficiency by achieving an optimal efficiency level worth 100%. That implies BAZNAS needs to improve its management performance by considering the suitability of inputs and outputs. Implications – This research contributes to improving knowledge about BAZNAS performance efficiency. This research also provides insights for policymakers as an evaluation and decision-making in improving the performance of zakat institutions, especially BAZNAS. Originality – This research saw the efficiency of BAZNAS’ performance for 20 years or from its operation until now. It can show the level of public trust in BAZNAS in the management of zakat, infaq, and sadaqah (ZIS) in Indonesia.

The pandemic conditions in 2020-2021 resulted in problems for the potato chip micro, small, and medium-enterprise (SMEs) cluster, including an imbalance in sales numbers with the resulting production due to a drastic decline in demand, marketing, and business performance. The first trimester of 2022 shows an increased demand for potato chips. Therefore, efficient performance is needed to support production recovery and business performance by increasing supply chain institutional efficiency. This research aimed to analyze the efficiency performance value and the sub-variables input with the most influence on supplier efficiency performance. This research used the Data Envelopment Analysis (DEA) model CCR-I Dual with input sub-variables (i.e., cash-to-cash-cycle-time, lead time, and flexibility) and output sub-variables (i.e., percentage of conformance quality standards, order fulfilment, and delivery performance). The analysis was carried out on the flow of suppliers to potato chip MSMEs. The results show that 8 decision-making units (DMUs) were inefficient (55.56% and 33.33%), and 1 DMU was in efficient condition (100% green), namely is DMU 6. The results also show that the input sub-variable with the most influence on supplier efficiency performance was the flexibility of sending raw materials followed by cash-to-cash-cycle-time.