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Annual preventive care is essential for diabetes patients to reduce the risk of complications including hypoglycemic events and blindness. Our aim was to examine the relative efficiency of Diabetes Belt (DB) and non-Diabetes Belt (NDB) counties in providing recommended preventive care for Medicare beneficiaries with diabetes using available health professional resources and to understand county-level socioeconomic factors associated with inefficient provision of preventive care. A data envelopment analysis (DEA) model was developed to assess relative efficiency of counties in providing diabetes preventive care. Logistic regression was performed to identify socioeconomic characteristics associated with inefficiencies. We used Medicare claims data to extract individual-level information of diabetes preventive service use and obtained county-level estimates of health resources information from the Area Health Resources File. More than 80% of counties had more than 10% inefficiencies on average. Compared to counties in the NDB, the odds of being inefficient were 2.44 times more likely in the DB (OR 2.44, CI 1.67–3.58). Counties with lower median income, with a smaller proportion of non-Hispanic Black population, and in a rural area had higher odds of being inefficient in providing preventive care. Our DEA results showed that counties in the DB and NDB were mostly inefficient. The availability of care providers may be less of a problem than how efficiently the resources are used in providing preventive care. Identifying sources of inefficiency within each community with low resource utilization and developing targeted strategies is needed to improve uptake of preventive care cost-effectively. [ABSTRACT FROM AUTHOR]

The banking industry is one of the most important pillars of the economy of any country, which plays a decisive role in the economic development and growth of countries due to the provision of various financial and credit services. With the globalization of the banking industry, it is very important to use income diversification strategies to improve value and efficiency. Using the data and information obtained from the financial statements of banks, this research has investigated the effect of income diversification strategies on efficiency in banks admitted to the Tehran Stock Exchange. The statistical population of this research includes all the banks admitted to the Tehran Stock Exchange during 2011-2021, and 10 banks were selected as a statistical sample using the targeted elimination method. In this research, the data envelopment analysis (DEA) approach was used to measure efficiency, and the autoregressive model approach with distributed intervals (ARDL) was used to estimate the research model. The present research findings showed that the strategy of income diversification (interest and non-interest) both in the short term and in the long term has a positive and significant effect on the efficiency of banks admitted to the Tehran Stock Exchange. [ABSTRACT FROM AUTHOR]

Applications of data envelopment analysis (DEA) often include inputs and outputs that are embedded in some other inputs or outputs. For example, in a school assessment, the sets of students achieving good academic results or students with special needs are subsets of the set of all students. In a hospital application, the set of specific or successful treatments is a subset of all treatments. Similarly, in many applications, labour costs are a part of overall costs. Conventional variable and constant returns-to-scale DEA models cannot incorporate such information. Using such standard DEA models may potentially lead to a situation in which, in the resulting projection of an inefficient decision making unit, the value of an input or output representing the whole set is less than the value of an input or output representing its subset, which is physically impossible. In this paper, we demonstrate how the information about embedded inputs and outputs can be incorporated in the DEA models. We further identify common scenarios in which such information is redundant and makes no difference to the efficiency assessment and scenarios in which such information needs to be incorporated in order to keep the efficient projections consistent with the identified embeddings. [ABSTRACT FROM AUTHOR]

The aim of this research is to investigate the effect of corporate social responsibility (CSR) on total factor productivity (TFP) in the European mining industry, considering micro- and macroeconomic indicators of the relationship between CSR and TFP. Employing data from 40 European mining companies from content analysis, CSR Hub, and the World Bank between 2018 and 2021, this paper utilizes a combination of Data Envelopment Analysis (DEA) and panel regression techniques to test the research hypotheses. The findings suggest that the TFP of European mining firms is positively affected by CSR initiatives implemented by the companies. Also, the empirical results depict that the CSR-TFP relationship is mainly established on institutional criteria. The results also indicate that CSR-related factors, namely, transparency and reporting, training, health and safety, and resource management, are the impacting indicators. The study broadens the horizons of this line of research and can be beneficial to CEOs, managers, experts, policymakers, decision-makers, and economists in the field of mining who are willing to promote responsible and sustainable mining. [ABSTRACT FROM AUTHOR]

Managerial ability and managerial efforts play key role in the performance of business enterprises. However, this indicator is not directly observable. The current paper focuses on estimating managerial ability in the context of the Indian and Iranian general insurance sectors. The study is based on 140 firm-year observations in India and 140 firm-year observations in Iran spread over 7 years (2012–13 to 2018–19). For measuring managerial ability, we have used a three-stage procedure that involves the estimation of insurer-wise efficiency using Data Envelopment analysis (DEA) in the first stage and then regression of the logarithm of technical efficiency on a set of explanatory variables. In the final stage, we have estimated managerial ability from regression residuals (the difference between the observed and fitted values of insurer efficiency). In order to test the validity of the relationship between return on equity and managerial ability we use the general additive model (GAM). Our results confirmed that there is a positive relationship between return on equity and managerial ability. Our findings also revealed that the mean technical and output allocative efficiencies and managerial ability of Iranian markets highly fluctuated with a high variance. In contrast, these indicators did not fluctuate much in India. [ABSTRACT FROM AUTHOR]

This paper evaluates the stock performance of Islamic banks relative to their conventional counterparts during the initial phase of the COVID-19 crisis (from December 31, 2019, to March 31, 2020). Using 426 banks from 48 countries, we find that stock returns of Islamic banks were about 10–13% higher than those of conventional banks after controlling for a host of the bank- and country-level variables. This study explains the Islamic banks' superior crisis stock performance by exploring the potential role of pre-crisis bank efficiency. In a univariate analysis, we document higher non-parametric Data Envelopment Analysis (DEA) efficiency levels for Islamic banks than conventional banks in the year preceding the COVID-19 crisis. Our multivariate regressions show that the risk-adjusted DEA efficiency scores can explain crisis stock returns for Islamic banks but not conventional banks. The evidence is robust to alternative measures of stock returns, efficiency models, and other empirical strategies. Finally, we present insight on the importance of key bank characteristics in determining the stock returns of conventional banks during the crisis period. [ABSTRACT FROM AUTHOR]

Purpose: The main goal of this paper is better understand the risk/return trade-off of investing in socially responsible investment funds (SRIF) and green investment funds (GIF). Design/methodology/approach: To achieve our aim a green investment fund portfolio, a socially responsible investment portfolio and a conventional fund (CF) portfolio from the United States of America (USA) were selected to compare the efficiency of these three different portfolios, by using Value-Based Data Envelopment Analysis (DEA) methodology. Findings: The results point out that SRIF and GIF are more efficient than CF. For five years, the CFs have not outperformed the GIF. Originality/value: The results suggest that there is a growing awareness on the part of investors that sustainable companies are the companies that will allow a better quality of life and a more sustainable environment. It seems that somehow managers and investors are aware that the market will compensate them for thinking about a cleaner and more equitable world. [ABSTRACT FROM AUTHOR]

Accessibility to financial resources is considered a prevalent problem in the agricultural sector. We develop an approach to quantify the long‐term opportunity costs of financial constraints in relation to peers who do not face any financial constraints. Using data on past financial performance, we assess creditworthiness and the size of an additional accessible bank loan to farmers. Combining this with data on reported expenditure, we determine the accessible finance. We quantify the opportunity cost as the forgone dynamic profit (intertemporal profit in current‐value terms) from financial constraints. Using data envelopment analysis, we apply our approach to 264 specialised Dutch dairy farms for the years 2006–2017 and explore the potential impact of changes in finance provision for several scenarios. Our results show an increasing gap between frontrunners and other farmers, as the latter generate progressively less dynamic profit in comparison to their best peers. The gap between the dynamic profit of the average farm and that of its best peers from their production and investment decisions made over the span of 1 year grew from €40,040 in 2009 to €114,548 in 2017. However, the growth is not driven by insufficient access to finance. Financial constraints can only explain 6% of the forgone dynamic profit in 2009 and as little as 1% for 2017. The number of farms classified as financially constrained in comparison to their peers decreases in our sample from 44% in 2009 to 8% in 2017. This suggests that non‐financial factors are driving the growing gap. [ABSTRACT FROM AUTHOR]

The purpose of this study is to measure the efficiency and stability of zakat institutions in Indonesia and Malaysia. There are 14 zakat institutions that will be analyzed using data envelopment analysis (DEA) window analysis during the period of 2016 to 2020. The result shows that the average efficiency of zakat institution is 78% during the observation period. The inefficiency of zakat institutions from both countries is caused by the lessthan-optimal distribution of zakat funds. The best performing zakat institutions are Selangor, BSMU, BRI Foundation, and Baznas because they have the highest efficiency and stability. This study has filled the gap in previous studies that measure the efficiency of zakat institutions with the standard DEA approach. Zakat institution managers can identify potential improvements in input and output variables to achieve maximum level of efficiency. [ABSTRACT FROM AUTHOR]

The need of translating increasing outlays into better outcomes on various public programmes has attracted the attention of researchers worldwide to focus more on the quality of public spending, often assessed in terms of its efficiency. The present article is a contribution to the existing literature on the subject in that it assesses the efficiency of government expenditure of Indian states for two most basic social services—elementary education and nutrition during 2014–2015 and 2018–2019 using data envelopment analysis and Malmquist productivity index techniques, in both input‐oriented as well as output‐oriented settings under variable returns to scale assumption; it constructs the average performance index for children at elementary education and malnutrition index for women and children to utilise them as output indicators; and it adopts a robust bootstrap truncated regression procedure to avoid various econometric issues while estimating the impact of selected environmental factors on bias‐corrected inefficiency scores. The major findings of this article seem to suggest that, while states should be provided greater flexibility in their fiscal operations, they have to complement their fiscal autonomy with good governance to improve the efficiency of their spending on basic social services. Towards this end, states like Bihar, Jharkhand and those belonging to North‐Eastern and Himalayan regions need special attention with a different set of development policies. [ABSTRACT FROM AUTHOR]

New Public Management-inspired reforms in the Norwegian hospital sector have introduced several features from the private sector into a predominantly public healthcare system. Since the late 1990s, several reforms have been carried out with the intention of improving the utilization of resources. There is, however, limited knowledge about the long-term, and sector-wide effects of these reforms. In this study, using a panel data set of all public hospital trusts spanning nine years, we provide an analysis of the efficiency of hospital trusts using data envelopment analysis (DEA), as well as a Malmquist productivity index. Thereafter we use the efficiency scores as the dependent variable in a second-stage panel data regression analysis. We show that during the period between 2011 and 2019, on average, efficiency has increased over time. Further, in the second-stage analysis, we show that New Public Management features related to incentivization are associated with the level of hospital efficiency. We find no association between degree of competition and efficiency. [ABSTRACT FROM AUTHOR]

Introduction/purpose: Data Envelopment Analysis (DEA) is commonly used to calculate the efficiency of similar Decision-Making Units (DMUs), which as such are elements of one set. In the article, it is considered that each such element of a set (of similar elements) is at the same time an element of a system (of various elements). An example of DMUs are 27 railway stations in the Republic of Serbia (RS) as an element of a set of railway stations and as an element of the railway transportation system, in the function of transporting goods, after division of the company Serbian Railways in 2015 (into "passengers" and "goods"). For the sake of better service, attraction and retention of clients, in the newly opened, free, transport market, the purpose of this article is to find the efficiency of the RS stations iin the period of 2018- 2022. Methods: Set-systemic-model comparative DEA analysis of railway stations as a DMUs. A unit is an element of the set, a unit is an element of the system, and a unit is the subject of the mathematical DEACCR/BCC/SE model. Results: The final efficiency, the average of all average values, is 0.7666, as a result of a triple comparative DEA analysis: 27 DMU, three DEA models and five years of functioning. Conclusion: Stations are functionally different in terms of efficiency and each station functionally differs by years and by model. The final aim is an input-output balance and the 27/27 option which is achieved with corrective actions – reduction/addition, input or output. [ABSTRACT FROM AUTHOR]

This paper aims to propose a method to measure the operational efficiency of the movie theater businesses. The method is based on a bootstrap data envelopment approach to test the statistical significance of the performance difference between companies in the movie theater industry. The proposed method is utilized to investigate the operational efficiency of the three major U.S. movie theater chains. This article utilizes data from each company's individual financial filings to estimate their bias-corrected efficiency scores. An aggregate report of the efficiency scores shows that the movie theater industry is experiencing a significant decline in both scale and technical efficiencies. The efficiency assessment of the three movie theater chains reports statistically significant differences. Based on the constant returns to scale assumption, the efficiency scores are different among the three movie theater chains. Closely, two significant differences are identified when considering the variable returns to scale assumption. The kernel density of the efficiency scores is estimated as well. Results suggest that the movie theater chains are in imperative need of developing an innovative strategic plan to tackle poor attendance and weak managerial practices. Other contributions and managerial issues are also discussed. [ABSTRACT FROM AUTHOR]

We present a cohesive generalized framework for an aggregation of the Nerlovian profit indicators and of the directional distance functions, frequently used in productivity and efficiency analysis in operations research and econometrics (e.g., via data envelopment analysis or stochastic frontier analysis). Our theoretical framework allows for greater flexibility than previous approaches, and embraces many other approaches as special cases. In the proposed aggregation scheme, the aggregation weights are mathematically derived from assumptions made about the optimization behavior and about the chosen directions of measurement. We also discuss various interesting special cases of popular directions, including the case of Debreu-Farrell-type efficiency. [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]

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]

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 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]

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]

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 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]

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]

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]

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]

It is well-known that the weighted averages of two competing forecasts may reduce mean squared prediction errors (MSPE) and may also introduce certain inefficiencies. In this paper, we take an in-depth view of one particular type of inefficiency stemming from simple combination schemes: Mincer and Zarnowitz inefficiency or auto-inefficiency for short. Under mild assumptions, we show that linear convex forecast combinations are almost always auto-inefficient, and, therefore, greater reductions in MSPE are almost always possible. In particular, we show that the process of taking averages of forecasts may induce inefficiencies in the combination, even when individual forecasts are efficient. Furthermore, we show that the so-called "optimal weighted average" traditionally presented in the literature may indeed be inefficient as well. Finally, we illustrate our findings with simulations and an empirical application in the context of the combination of headline inflation forecasts for eight European economies. Overall, our results indicate that in situations in which a number of different forecasts are available, the combination of all of them should not be the last step taken in the search of forecast accuracy. Attempts to take advantage of potential inefficiencies stemming from the combination process should also be considered. [ABSTRACT FROM AUTHOR]

Efficiency was instituted as one of the principles that guide public administration and, given the budgetary constraints found in Brazil, it has become a challenge for public agents, demanding that costs be optimized while still providing the best service to society. In this sense, studies on efficiency in health establishments and in the Armed Forces demonstrate the relevance and use of accounting to improve results. However, no studies were found that addressed the analysis of efficiency in health establishments linked to the Brazilian Navy (MB). Thus, the main objective of the study was to analyze the efficiency of medical and hospital care provided by the Military Organizations (OM) of MB health through Data Envelopment Analysis (DEA). For this, a quantitative study was used, in which the DEA method was applied in 10 OM of the health area of the MB, and the inputs (annual cost of consultations and exams carried out and registered in the Macroactivity “31.00 – Health System of the MB - SSM”) were collected through the Federal Government Cost Information System (SIC) and the outputs (number of diagnostic service exams performed and medical consultations performed in the OH and in hospitals and/or by contracted physicians to the SSM) were obtained through the Navy Statistical Yearbook (ANEMAR), both referring to the 2021 financial year. Data analysis was carried out with the aid of the R software, which allowed obtaining the DEA model to be used. The results re)veal the MO that were considered efficient (OH 1, OH-2, OH-3, OH-8 and OH-9) and, consequently, the benchmark for the MO considered inefficient (OH-4, OH-5, OH -6, OH-7 and OH-10). [ABSTRACT FROM AUTHOR]

The rate of increase in the world population has caused the rapid growth and differentiation of transportation systems. Therefore, it is becoming increasingly important for transportation systems to provide safe, faster, and less expensive transportation. The present study analyzed the efficiency of 14 European and Turkish railways selected from the International Union of Railways database using data from between 2000 and 2017. The system, production, and consumption process activities of these 14 railways were estimated using Relational Network Data Envelopment Analysis and interpreted with performance matrices. Significant variables affecting production, consumption, and system activities were identified by Tobit Regression Analysis. The most important variables affecting system efficiency were found to be passenger and freight train occupancy rates, gross national income per capita, and population density. [ABSTRACT FROM AUTHOR]

The private pension system (PPS) is a growing source of funds for an individual's retirement. Thus, the efficiency of PPS concerns not only the companies in the sector, but also the countries at the macroeconomic level. The objective of the research is determining the efficiency of PPS in Turkey. Using monthly data for 2013-2019, the extent to which state contribution affected PPS efficiency is investigated by Data Envelopment Analysis (DEA). Efficiency estimates are calculated first without and then with the government contribution. The results show that the state contribution increased the efficiency of the PPS system. [ABSTRACT FROM AUTHOR]

Background: Cambodia is undergoing a series of reforms with the objective of reaching universal health coverage. Information on the causes of inefficiencies in health facilities could pave the way for a better utilization of limited resources available to ensure the best possible health care for the population. Objectives: The purpose of this study is to evaluate the technical efficiency of health centers and the determinants for inefficiencies. Methods: This cross-sectional study used secondary data from a costing study on 43 health centers in six Cambodian provinces (2016–2017). Firstly, the Data Envelopment Analysis method with output-orientation was applied to calculate efficiency scores by selecting multiple input and output variables. Secondly, a tobit regression was performed to analyze potential explanatory variables that could influence the inefficiency of health centers. Results: Study findings showed that 18 (43%) health centers were operating inefficiently with reference to the variable returns to scale efficiency frontier and had a mean pure technical efficiency score of 0.87. Overall, 22 (51%) revealed deficits in producing outputs at an optimal scale size. Distance to the next referral hospital, size and quality performance of the health centers were significantly correlated with health center inefficiencies. Conclusion: Differences in efficiency exist among health centers in Cambodia. Inefficient health centers can improve their technical efficiency by increasing the utilization and quality of health services, even if it involves higher costs. Technical efficiency should be continuously monitored to observe changes in health center performance over time. Highlights: • A total of 41% of the sample health centers were identified as technically inefficient with the potential to increase their output capacity. • With the given financial resources of health centers, a 13%-increase in service delivery would be possible. • Substantial efficiency gains could be generated by improved utilization and increased quality of health services. • Technical efficiency of health centers in Cambodia will improve if quality of services, organizational and health center management are strengthened. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) obtains the relative efficiency of decision-making units (DMUs) based on their inputs and outputs. In many situations, some variables can play the role of input or output for a DMU. It is important to provide a suitable model that can maximize the efficiency of the unit under evaluation by correctly choosing the role of these variables. One of the production technologies in DEA is semi-additive production technology. In addition to the observed DMUs, this technology also considers the set of all aggregations corresponding to these DMUs in the evaluation of efficiency. In this paper, we presented the semi-additive production technology in DEA in the presence of flexible measures. This technology is created based on the observed DMUs and their corresponding aggregations DMUs. We have shown that we can provide semi-additive production technology in the presence of flexible measures based only on the observed DMUs by removing the region with decreasing returns to scale from the production possibility set (PPS). In the following, we present two different approaches for measuring the efficiency of DMUs in the presence of flexible measures in semi-additive production technology. These two approaches allocate flexible measure as input or output in such a way that the efficiency of the unit under evaluation is maximized. Also, we use the proposed approach to evaluate the efficiency of data sets related to academic units. [ABSTRACT FROM AUTHOR]

Objective : Today, the development mode of public hospitals in China is turning from expansion to efficiency, and the management mode is turning from extensive to refined. This study aims to evaluate the efficiency of clinical departments in a Chinese class A tertiary public hospital (Hospital M) to analyze the allocation of hospital resources among these departments providing a reference for the hospital management. Methods : The hospitalization data of inpatients from 32 clinical departments of Hospital M in 2021 are extracted from the hospital information system (HIS), and a dataset containing 38,147 inpatients is got using stratified sampling. Considering the non-homogeneity of clinical departments, the 38,147 patients are clustered using the K-means algorithm based on workload-related data labels including inpatient days, intensive care workload index, nursing workload index, and operation workload index, so that the medical resource consumption of inpatients from non-homogeneous clinical departments can be transformed into the homogeneous workload of medical staff. Taking the numbers of doctors, nurses, and beds as input indicators, and the numbers of inpatients assigned to certain clusters as output indicators, an input-oriented BCC model is built named the workload-based DEA model. Meanwhile, a control DEA model with the number of inpatients and medical revenue as output indicators is built, and the outputs of the two models are compared and analyzed. Results: Clustering of 38,147 patients into 3 categories is of better interpretability. 14 departments reach DEA efficient in the workload-based DEA model, 10 reach DEA efficient in the control DEA model, and 8 reach DEA efficient in both models. The workload-based DEA model gives a relatively rational judge on the increase of income brought by scale expansion, and evaluates some special departments like Critical Care Medicine Dept., Geriatrics Dept. and Rehabilitation Medicine Dept. more properly, which better adapts to the functional orientation of public hospitals in China. Conclusion: The design of evaluating the efficiency of non-homogeneous clinical departments with the workload as output proposed in this study is feasible, and provides a new idea to quantify professional medical human resources, which is of practical significance for public hospitals to optimize the layout of resources, to provide real-time guidance on manpower grouping strategies, and to estimate the expected output reasonably. [ABSTRACT FROM AUTHOR]

Objectives: Vaccination is an important part of public health services. We aim to assess the efficiency of vaccination services in Beijing, the capital of China, and to further study the influencing factors of efficiency. Methods: Using the immunization service data of Beijing, China in 2020, we firstly developed a data envelopment analysis (DEA) model to calculate the score of vaccination efficiency. Secondly, we used DEA model scenario simulations with different combinations of input–output factors to derive the magnitude of the effect of each input factor on the efficiency. Finally, combined with the data from the Beijing Regional Statistical Yearbook 2021, we developed the Tobit model to examine the effect of external social environmental factors on efficiency. Results: The average scores of efficiency of POVs (Point of Vaccination) in different areas of Beijing vary greatly. Different input factors had different degrees of positive effects on the efficiency score. In addition, the number of populations served by POV was positively associated with efficiency, the GDP and financial allocation of the POVs' district was also positively associated with efficiency score, while the total dependency ratio of the POVs' district was negatively associated with efficiency score. Conclusion: The efficiency of vaccination services varied considerably across POVs. Constrained by limited resources, efficiency scores can be increased by increasing input factors that have a larger impact on efficiency score and reducing those that have a smaller impact on efficiency. In addition, the social environment should be considered in allocating vaccination resources, and more resources should be invested in areas with low levels of economic development, low financial allocation, and high population. [ABSTRACT FROM AUTHOR]

The data envelopment analysis is related to a non-parametric mathematical tool used to assess the relative efficiency of productive units. In different studies on productive efficiency, it is common to employ semi-parametric procedures in two stages to determine whether any exogenous factors of interest affect the performance of productive units. However, some of these procedures, particularly those based on conventional statistical inference, generate inconsistent estimates when dealing with incoherent data-generating processes. This inconsistency arises due to the efficiency scores being limited to the unit interval, and the estimated scores often exhibit serial correlation and have limited observations. To address such inconsistency, several strategies have been suggested, with the most well-known being an algorithm based on a parametric bootstrap procedure using the truncated normal distribution and its regression model. In this work, we present a modification of this algorithm that utilizes the beta distribution and its regression structure. The beta model allows for better accommodation of asymmetry in the data distribution. Our proposed algorithm introduces inferential characteristics that are superior to the original algorithm, resulting in a more statistically coherent data-generating process and improving the consistency property. We have conducted computational experiments that demonstrate the improved results achieved by our proposal. [ABSTRACT FROM AUTHOR]

Purpose: In this study, the impact of owner-operator and non-owner operator rice mills on productive efficiency is investigated. Design/methodology/approach: Primary data collected from a survey of 111 rice mills in the Mwea region of Kenya are used. A metafrontier approach is employed to measure overall technical efficiency which is decomposed into managerial and organisational efficiency. Findings: The results reveal no significant difference in overall technical and managerial efficiency between owner and non-owner operated mills. However, a significant difference exists in organisational efficiency of mills: non-owner operated mills were found to be performing significantly better than owner-operated. Practical implications: The authors provide supporting evidence to the study and discuss some of the significant policy implications stemming from the study. Originality/value: It is recognised that for owners to take the risk of divesting control to a hired manager rather than manage the firm themselves can have major strategic, financial and often emotional consequences. However, there is little empirical evidence on how production efficiency will develop as a result of hiring a manager with the underlying economic theory providing ambiguous guidance. Standard economic theory assumes that firms behave as profit maximisers, which can be achieved by operating efficiently. However, this may not always be the case and as the literature indicates, this may especially be so for small businesses in low- and middle-income countries. [ABSTRACT FROM AUTHOR]

A P- stage network is studied in different time periods here which contains ratio data. Thus a method is given to evaluate the technical efficiency in each time period and overall efficiency after several desired time periods. Also, the efficiency of each stage of such a structure is evaluated in each time period and after several time periods. It has been shown that overall efficiency scores and the efficiency of each process obtained after several desired time periods are not less than to overall efficiency scores and the efficiency of each process in each time period. In addition, a unit becomes efficient after several periods of time if it is efficient in at least one period of time. [ABSTRACT FROM AUTHOR]

In 2015, at the United Nations forum, the 17 Sustainable Development Goals (SDGs) were approved to be met by 2030. This research aims to know what has been the behavior of productivity and efficiency of the manufacturing industry in the province of Pichincha, Ecuador, and the relationship with the achievement of some goals of the SDG 8, 9 and 12. The research methodology has a quantitative, non-experimental, and longitudinal approach. The information from the economic and financial reports of the manufacturing companies between 2010 and 2018 was processed. The values of efficiency were estimated using the data enveloping analysis technique. With the annual information, the evolution of productivity and efficiency was predicted until 2022. In the nine years, the results show that the productivity indicators and the number of companies that are related to goals 8.2 and 8.3 depend on the size of the companies and would maintain a constant trend until 2022. In addition, in the same period, it was shown that efficiency has had variations, and its trend is to remain constant until 2022, which shows that there will be no progress in meeting the targets 9.4, and 12.2 of the SDGs for this industrial sector. [ABSTRACT FROM AUTHOR]

Islamic Commercial Banks must be aware of their degree of efficiency to optimize each bank's potential and take advantage of every opportunity. For a bank to succeed, its operations must be efficient; if they are, the value of the business will rise. This investigation used 12 Islamic commercial banks as its subject to assess the level of efficacy of Islamic retail banks in Indonesia. The data analysis method in this study is the Data Envelopment Analysis (DEA) method using the Charnes Chooper and Rhoodes (CCR) model, specifically the Constant Return to Scale (CRS) approach. The two variables employed in this study were used as input and output variables. TPF, Assets, Operational Costs, and Non-Operational Costs are the input variables. The function of funding is the output variable--income from operations and non-operational sources. In addition, a SWOT analysis is conducted based on the findings of the DEA study to determine the strategies used during the Covid-19 pandemic. According to the Input and Output method, two banks have been inefficient for 4 years, and five have changed BUS efficiency from 2015 to 2018. BTPN Syariah, BJB Syariah, Bank Mega Syariah, Bank Syariah Bukopin, Bank Victoria Syariah, and Bank Panin Dubai Syariah are the five (five) banks in question. The average efficiency of Indonesia's Islamic Commercial Banks for that period, from 2015 to 2018, was 91%, which suggests that despite falling short of 100% (excellent). [ABSTRACT FROM AUTHOR]

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

To grow the sugar beet crop in the new lands is of great importance in closing the sugar gap in Egypt, so the research aims to study the factors affecting the production of sugar beet crop in the new lands in Assiut Governorate, the highest productive province of the crop in the new lands in 2017, and to achieve this goal the research relied on the use Data envelopment analysis (DEA) in accordance with the concept of fixed return of capacity and variable return of capacity to estimate the Technical Efficiency- Allocation Efficiency- Economic Efficiency. of the sugar crop in the sample of 92 farms collected randomly, he results indicated that the technical efficiency of the study sample assuming the fixed return of capacity averaged 97.4% and the number of farms achieved for optimum technical efficiency 39 farms or about 42.39% of the total farms of the sample research, while the average technical efficiency assuming variable return of capacity was 99.5% and the number of farms achieved for optimum technical efficiency was 83 farms or about 90.22% of the total farms of the research sample, The results also indicated that the Allocation al-Sample farms' Allocation efficiency by assuming a fixed return on capacity averaged 78.3%, i.e. the redistribution of the economic resources used will provide 21.7% of the resources used for the 91 farms that did not reach optimal Allocation efficiency, representing about 98.91% of the total research sample farms, in addition to the economic efficiency averaged 76.3%. That is, the same level of production can be achieved at a cost 23.7% below the actual cost for the 91 farms that did not reach optimal economic efficiency, representing about 98.91% of the total research sample farms, and when estimating the Allocation efficiency of al Ain farms. Assuming a variable capacity return, it averaged 80.4%, which means that the redistribution of the economic resources used will save 19.6% of the resources used for farms that did not reach optimum Allocation efficiency, which represents about 98.91% of the total. Of the total research sample farms. The average economic efficiency was 80.1%, which means that the same level of production can be achieved at a cost 19.9% below the actual cost for the 91 farms that did not reach optimal economic efficiency, representing about 98.91% of the total. To the farms sample research, the research recommends activating and activating the role of guidance in encouraging farmers to start planting sugar beets, and educating farmers about the optimal fertilizer decisions so that they do not overuse them, in addition to increasing the incentive in farmers to determine the appropriate prices for the supply of sugar beet crop for factories, as well as providing production supplies at affordable and timely prices. [ABSTRACT FROM AUTHOR]

In connection with industrialization, technological developments and population growth, the need for energy is increasing and supplying the energy needed for the welfare of countries and societies is of great importance. Increasing energy need requires emphasis on energy resources all over the world, providing the highest level of benefit from these resources, and establishing efficiency and effectiveness in terms of the use and production of resources. In this study, it is aimed to determine the efficiency and the efficiency change in Turkish coal mining and to determine the appropriate arrangements to be made in line with the analysis result. Periodic efficiency analysis has been carried out regarding the Turkish Coal Enterprises Institution and the Turkish Hard Coal Enterprise Institution, which are producing lignite and hard coal in Türkiye, and the issues that need to be done at the point of ensuring efficiency have been tried to be determined. In the study, in which the period 2001-2020 was chosen as the review period, the activities related to lignite and hard coal mining were determined by the data envelopment analysis method. According to the results of the analysis, there is a variable activity in lignite and hard coal mining by periods. According to the results of the data envelopment analysis, it is observed that there is a need for regulations regarding maximizing salable production and net sales according to the current investment expenditure and operating expense in coal enterprises in the years when efficiency is not in question. [ABSTRACT FROM AUTHOR]

This research is to analyze efficiency, causes of inefficiency, and potential improvements that can be made and the determination of efficiency in Bank BSI Region V Jakarta 2 Branch Offices using the DEA production approach and profit approach methods. The research method uses quantitative methods, for efficiency analysis with Data Envelopment Analysis (DEA) which is measured using the DEAP program and difference test and panel regression which is measured using the Eviews program and for causes of inefficiency using slack analysis. The results of the study show that hypothesis 1, the DEA method with a production approach is accepted and hypothesis 2, the DEA method with a profit approach is accepted. The causes of the inefficiency of the BSI Bank office include, among others, most of the resources used are still unable to generate maximum net profit, wasteful in the use of goods and services, labor costs, depreciation costs, education and training costs, maintenance and repair costs and rental costs. Potential improvements that can be made are by increasing the execution of growth in Third Party Funds and channeling financing and switching transaction strategies to digital. [ABSTRACT FROM AUTHOR]

Retail supply chains are key on any market. Their significance has long been recognized in the literature and in practice. Various factors such as pandemics, economic crises, wars, and natural disasters have further increased interest in this area. However, the most recent research has focused more on resilience, sustainability, energy consumption, and a circular economy, while the efficiency of logistics processes has been almost completely overlooked. Logistics process efficiency in retail supply chain is a fundamental principle without which all mentioned performances cannot have desired values. This gap is precisely the main motivation of this research. In this paper, research models in literature are presented which can be used, with some modifications, to measure the efficiency of the retail supply chain. The models were based on the data envelopment analysis (DEA) approach. Four main groups were identified: standard DEA models, efficiency decomposition models, network models, and game-theory-based models. In the second part of the paper, various approaches were tested on a real example of a trading company operating in Serbia. Seven supply chains were observed, each consisting of a distribution center (DC) and retail store (RS). Variables used were the number of pallet places, logistics costs, number of deliveries, accuracy of deliveries, and turnover. The results showed the advantages and disadvantages of different approaches in real examples. The main contributions of this paper lie in unique approaches to measuring the efficiency of the retail supply chain. The paper creates an excellent foundation for future research and measurements on real systems, which is equally useful for researchers and industry experts. [ABSTRACT FROM AUTHOR]

Foreign direct investment (FDI) is an important factor in building a strong economy for a country, particularly in developing and emerging markets. Both domestic enterprises and policy makers have been motivated to attract FDI for the benefits of FDI, such as technological transfers, spillover benefits, and rising competition. There is a need for a functional model to assess how the competitive index affects FDI attractiveness. Therefore, in this study, the authors use an integrated model of Grey Delphi, the Data Envelopment Analysis Super Slack-Based Measure Model (DEA–Super SBM), and the Malmquist Model (DEA–Malmquist) to evaluate the FDI attractiveness of Vietnamese provinces from 2017 to 2021. Firstly, ten critical dimensions of the provincial competitive index (PCI) affecting the number of FDI by cases and amount of FDI capital were validated via the Grey Delphi method. Secondly, the Super-SBM model is applied to assess the FDI efficiency of 63 provinces in Vietnam from 2017 to 2021. Then, the DEA–Malmquist model is employed to analyze the total change in the productivity of 63 provinces' FDI performance in Vietnam. The findings of this study revealed that the efficiency of FDI in Vietnam's provinces is relatively low, and there is a significant variation in the attractiveness of FDI among the provinces. This study can provide valuable insights for policy makers and other stakeholders in developing effective strategies to attract FDI and foster economic development. [ABSTRACT FROM AUTHOR]

This paper analyzes the efficiency and efficiency changes of 57 Turkish natural gas distribution firms in the period 2016-2021 with input-oriented Data Envelopment Analysis (DEA) and Malmquist Total Factor Efficiency (TFP) Index, respectively. The efficiencies of the distribution firms are analyzed using both the aggregated data of all years and the six‐year multiperiod analysis. According to the results of the aggregated model, the technical efficiency, pure technical efficiency, and scale efficiency of the firms on average are 77.4%, 81.2%, and 95.4%, respectively. 32 (14) scale-inefficient firms have increasing (decreasing) returns to scale. Only three of the 10 firms that are technically efficient in the aggregated model are found to be fully efficient in all periods. Natural gas distribution firms are classified as small firms and large firms according to their gas delivery amounts, and the scale efficiency of these firms and the changes in the number of large and small firms with increasing or decreasing returns to scale are examined on a yearly basis. Over the period 2016-2021, total factor productivity decreased by an average 1.8% annually, as a result of an annual average decrease of 1% in technical efficiency and an annual average decrease of 0.8% in technological change. The reduction in technical efficiency is due to 0.6% decrease in pure technical efficiency and 0.4% decrease in scale efficiency. [ABSTRACT FROM AUTHOR]

Online reviewers are site users who share their opinion & experience over the internet and influence the perception & purchasing intentions of potential customers. Therefore, considerable attention is needed to identify credible and trustworthy online reviewers. For marketing through electronic-word-of-mouth (eWOM), it is important to find those online reviewers who have the potential to spread the product image efficiently and can positively influence the buying intention of potential customers. In this paper, we develop an innovative model based on data envelopment analysis (DEA) to identify good quality reviewers that have a commendable impact on readers or potential customers, by considering the determinants related to credibility, trustworthiness, expertise, travel experience, and identity disclosure of online reviewers as inputs/outputs in the DEA-based models. We have also ranked the reviewers using the balance index (BI) based technique. The results of this paper will aid the e-marketers to understand the variables related to reviewers which help them in finding the highly influential reviewers available on their website. The managerial and theoretical implications are also discussed for the practitioners, business managers, and researchers in the e-service sector. [ABSTRACT FROM AUTHOR]

Congestion is one of the main problems in economic issues. In fact, congestion is a wasteful step in the production process, where outputs decrease as a result of increasing inputs. In the economy, congestion is important because its elimination reduces the cost and also increases the output. Therefore, there is a great benefit in identifying congestion and reducing it. Since it is difficult to compute congestion for DMUs with interval data, owing to the computational complexity of the existing methods, we first present a new method for computing congestion and then obtain congestion in the case of interval data. It is well known that if DEA inputs and outputs are in the form of intervals, there will be an efficiency interval for each DMU. Since we assume interval data in this paper, we obtain an interval for the amount of congestion possible in each DMU and prove that the interval indicates the upper and lower bounds of congestion for each DMU. [ABSTRACT FROM AUTHOR]

Malaysia has great geo-economic advantages, especially in becoming a major logistics and investment hub. However, as operational risk events create uncertainties, logistics companies suffer from supply and demand issues which affect their bottom lines, customer satisfaction and reputations. This is a pioneer paper to propose the optimization of the efficiency of listed logistics companies in Malaysia with operational risk factor using a data envelopment analysis (DEA) model. The basic indicator approach (BIA) is used as an output indicator for the operational risk capital requirement factor in the proposed model. This paper has practical and managerial implications with the identification of potential improvements for the inefficient listed logistics companies based on the optimal solution of the DEA model. This proposed model can be applied in emerging fields such as finance and project-based construction companies, where operational risk is a high concern. [ABSTRACT FROM AUTHOR]

Technical efficiency (TE) and total factor productivity (TFP) are important criteria to ensure the enhancement of the quality and efficiency of state-owned enterprises (SOEs) and function as important indicators to assess the quality of their accomplishments. The purpose of this study is to explore whether the efficiency of SOEs is higher or lower than that of private enterprises. Transcendental logarithmic production function and stochastic frontier analysis (SFA) are used to assess the TE and TFP of listed central SOEs, local SOEs, and private enterprises, the data of which were taken from 2006–2020. The results show that the sampled private enterprises had the highest average TE during the study period, followed by the central and local SOEs. The private enterprises also had the highest average TFP growth rate, followed by the local and central SOEs. The TFP decompositions show that the TE change (TEC) and technical change (TC) indices of the SOEs were lower than those of the private enterprises. The TC, TEC, and scale change (SC) are limiting the TFP growth rates of the SOEs in labor-intensive industries. The SC of the SOEs has changed less than that of private enterprises in the sampled capital-intensive industries. Northern and southern China had the highest rates of TE and TFP growth. Indeed, this paper measures and decomposes TFP, and analyzes the efficiency of SOEs and private enterprises in different industries and regions in an international context. [ABSTRACT FROM AUTHOR]