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The paper analyzes the relative technical efficiency of the transition economies of the Western Balkans in the period 2007–2021, in comparison with the former countries with a socialist state system, today members of the European Union (EU), based on selected macroeconomic indicators and panel data.

Data envelopment analysis (DEA), i.e. its extension, DEA Window analysis, is applied. Total technical efficiency, as a prerequisite of economic efficiency, is decomposed into pure technical efficiency (PTE) and scale efficiency (SE). Bootstrapping method and Mann–Whitney U test were used to check the robustness of the obtained results, i.e. efficiency values.

The results show that in 2020, all observed countries recorded a significant drop in economic efficiency as a result of a general, disproportionate drop in the value of selected macroeconomic variables, which occurred due to the global economic crisis and the slowdown in economic activity caused by the COVID-19 pandemic. This drop in efficiency was significantly greater in the former socialist states, now members of the European Union, which showed their greater sensitivity to global crises. None of the observed economies in the observed period was relatively efficient, that is, at the level of best practice, which occurred primarily as a consequence of the inefficiency of business conditions expressed in the economies of scale.

The main limitation of this study stems from the very nature of the concept of DEA efficiency, which is relative in nature. Also, the results and their interpretation are also significantly influenced by the choice of model variables, as shown by Lábaj et al. (2013), as well as a small number of decision-making units (DMUs). The mentioned limitations prevent unambiguous interpretation and generalization of the obtained results.

The study may be of importance to economic policy makers in macroeconomic decision-making. The application of the DEA concept in measuring the technical efficiency of national economies is a useful tool in the analysis of macroeconomic performance and a benchmarking approach for positioning and achieving competitive advantage on the international market.

Since research of this type is very limited, the results of this study make a theoretical and empirical contribution to the literature, creating a basis for future research and reexamination. The application of the DEA concept in measuring the technical efficiency of national economies is a useful tool in the analysis of macroeconomic performance and a benchmarking approach for positioning and achieving competitive advantage in the international market.

The purpose of this study is to evaluate the efficiency of the relative performances of Mother’s canteen across the regions of Tamil Nadu and find out the determinants of inefficiencies in the scheme.

An untargeted food security scheme called Amma (Mother's) canteen was started in Tamil Nadu, India, with an aim to provide the urban poor with hygienic and healthy food at an affordable price. Along with secondary data, interviews were conducted to understand the operational details of Mother's canteen. Data envelopment analysis (DEA) was used to find the relative efficiency of the scheme operated by nine corporations.

Based on the daily expenditure, number of meals served and revenue, seven of nine corporations were found to be inefficient. Further, sensitivity analyses found that among six procurement variables, procurement (quantity and price) of black gram and cooking oil were determinants of inefficiency.

As an untargeted scheme, the cost of delivering service-based evaluation was used for performance evaluation. Policymakers could use centralized procurement instead of open market procurement at the corporation level and standardized ingredients' usage (quantity) to further reduce the cost of the food security scheme.

The proposed DEA model may be used by policymakers to empirically evaluate the food security scheme's delivery effectiveness across various corporations in a region. Inefficient branches are identified here with empirical support for further performance improvement changes.

There are limited number of studies evaluating untargeted schemes. This paper presents the challenges of evaluating an untargeted scheme which allows self-selection of beneficiaries. The outcome of this study will help in identifying inefficient corporations, and further, improve the performance and cost of delivering untargeted food security scheme.

The main purpose of this paper is to determine the bias-corrected efficiencies and rankings of the selected hotels and restaurants (H&Rs) in India.

The data for the Indian H&R sector are collected from the Prowess database. The bootstrap data envelopment analysis (DEA) based on a constant return to scale (CRS), variable return to scale-input oriented (VRS-IP) and variable return to scale-output oriented (VRS-OP) are applied on H&Rs to obtain the bias-corrected efficiencies.

It is found that relative efficiencies using basic DEA methods of all the 45 H&Rs of India are overestimated. These efficiencies are corrected using bias correction through bootstrap DEA methods. The bounds for the efficiencies of each H&R are computed using all the adopted methods. All H&Rs are ranked using bias-corrected efficiencies, and the linear trend between ranks suggests that the H&Rs are ranked almost similarly by all the adopted methods.

To improve efficiency, Indian H&R companies must rethink their personnel needs by enhancing their workforce management capabilities. The government needs to extend more support to this sector by introducing a liberal legislation framework and supporting infrastructure policies.

There is a paucity of studies on H&Rs in India. The current study focused on measuring bias-corrected efficiencies of the selected H&Rs of India. This study is one of the few initiatives to explore bias-corrected efficiencies extensively using the bootstrap DEA method.

When the temperature of an air conditioning unit’s fin surface goes below its dew point temperature, condensation forms on the unit’s surface. As a result, the cooling coil’s performance is compromised. By altering the cross-section and heat conductivity of the fins, the performance of such systems can be improved. This study aims to analyze the thermal performance of longitudinal fins made up of a variable thickness (assuming constant weight) and functionally graded material.

Different grading parameters are considered for an exponential variation of thermal conductivity. The humidity ratio and the corresponding fin temperatures are assumed to follow a cubic relationship. The Bvp4c solver in MATLAB^® is used to solve the differential heat transfer equation resulting from balancing heat transfer in a small segment.

Validation of the methodology is provided by previous research presented in this area. For different combinations of grading parameters, geometry parameters and relative humidity, the normalized temperature distribution along the fin length and fin efficiency contours are plotted, and the results are very promising.

When compared to the efficiency of an isotropic homogenous rectangular longitudinal fin with optimal geometry and grading parameters, a 17% increase in efficiency under fully wet conditions is measured. When it comes to fin design, these efficiency contour plots are extremely useful.

The aim of this study is to analyze Turkey's blood collection efficiency at the regional level between 2018 and 2021 and discuss managerial implications.

The authors utilize data envelopment analysis (DEA) to evaluate the efficiency scores of the 18 regions for which the Turkish Red Crescent is responsible. The data set is obtained from the General Directorate of Blood Services in the Turkish Red Crescent.

The results reveal that the efficient regions over the years did not substantially change, and regions that were consistently efficient for a four-year period are identified. Another finding is that COVID-19 did not affect the blood collection efficiency of the regions. Moreover, the findings illustrate that concentrating on the operations would contribute more to the blood collection efficiency than changing the scale size. Furthermore, the authors observe that the service population is by far the most important variable in determining the efficiency of the regions.

In this study, the authors present a multi-dimensional perspective on the performance evaluation of blood collection operations. In addition, the authors present blood bank managers' feedback on the performance evaluation model, outlining managerial implications. Furthermore, the authors explore the effects of the pandemic on blood collection in Turkey and illustrate the changes in efficiency throughout a distinct period that incorporates the pandemic. The study would provide a guide for blood bank managers to improve the performance of their organizations.

The scope of this research is to investigate performing loan efficiency for fifty European banks during the period 2008–2017.

The study is structured as a two-stage analysis of performing loan efficiency and its driving factors. In the first stage of the proposed methodology “Data Envelopment Analysis” is used to estimate performing loan efficiency for each bank included in the sample. A bootstrap statistical procedure enhances the findings. In the second stage, the impact of other factors on the efficiency scores of loan performance using tobit regression is investigated.

The results are consistent with the findings of the individual banks' financial analyses. According to the findings of DEA implementation, the evaluated banks may enhance their cost efficiency by 39% on average. In addition, the results indicate that loan efficiency performance improves after 2015, coinciding with the business cycle's upward trend. The tobit regression is employed in the second stage to examine the influence of bank-related and macroeconomic factors on banks' loan management efficiency. According to the findings of the tobit regression, three factors, namely the capital adequacy ratio, GDP per capita and managerial inefficiency, have a substantial influence on performing loan efficiency.

This research investigates the effectiveness of European economic policy in protecting the European banking system from the consequences of the sovereign debt crisis in several euro area members. The results highlight the distance of the Eurozone from the level of the ‘optimal currency area’.

This study aims to explore the dynamic interplay of key resources (i.e. research and development (R&D), advertising and exports) in affecting the performance of USA manufacturing firms. Specifically, the authors examine the dynamic impact of joint resources and predict differential effect scales contingent on firm capabilities.

This study presents a combined multiple regression analysis (MRA)-multilayer perceptron (MLP) neural network modeling and investigates the complex interlinkage of capabilities, resources and performance. As an innovative approach, the MRA-MLP model investigates the effect of capabilities under the combinatory deployment of joint resources.

This study finds that the impact of joint resources and synergistic rents is not uniform but rather distinctive according to the combinatory conditions and that the pattern is further shaped by firm capabilities. Accordingly, besides signifying the contingent aspect of capabilities across a range of resource combinations, the result also shows that managerial sophistication in adaptive resource control is more than a managerial ethos.

The proposed analytic process provides scientific decision support tools with control mechanisms with respect to deploying multiple resources and setting actionable goals, thereby presenting pragmatic benchmarking options to industry managers.

Using the theoretical underpinnings of the resource-based view (RBV) and resource orchestration, this study advances knowledge about the complex interaction of key resources by presenting a salient analytic process. The empirical design, which portrays holistic interaction patterns, adds to the uniqueness of this study of the complex interlinkages between capabilities, resources and shareholder value.

This investigation is designed to quantify and appraise the efficiency of resource distribution in the provision of public digital cultural services in China. By acknowledging and incorporating the realities of China's social development, the authors offer recommendations for enhancement derived from the study’s data analysis results. The research zeroes in on the dissection and analysis of the integral elements that structure the provision of public digital cultural services, and it concentrates on the associated data computation. The conclusions drawn herein are expected to serve as a significant point of reference for ongoing academic investigations and practical explorations in affiliated domains.

In this research, the authors utilize a hybrid methodology to meticulously evaluate the efficiency of the components that underpin the provision of public digital cultural services (PDCS) in China. The authors embark on deconstructing the various constituents within the PDCS supply framework, conducting in-depth analyses and providing cogent interpretations of each integral element. Subsequently, the authors deploy the well-regarded SBM super-efficiency model to ascertain the operational efficiency of these components. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations.

The provision of PDCS in China as of 2021 had been characterized by overall good efficiency, significant regional disparity and a disconnect between inputs and outputs with weak correlations to economic and demographic data.

In this study, the authors provide an exhaustive deconstruction and interpretation of the public digital cultural services supply system, thereby proposing a framework for evaluating the efficiency of supply element allocation. Additionally, the authors have determined a set of distinct measurable indicators that are readily accessible for open collection. Notably, this analytical and evaluative framework designed for element analysis and measurement may also find application in efficiency evaluation research of the supply systems of other related cultural endeavors.

The purpose of this study is to examine the research efficiency of the research universities in Türkiye and to identify potential areas for improvement and to examine the factors affecting efficiency.

For this purpose, data envelopment analysis was conducted with the output-oriented Banker, Charnes and Cooper (BCC) model with five-year article and citation counts data of 23 universities which were obtained from the Web of Science Core Collection.

The findings of the study show that only eight research universities are efficient. There are areas of development for universities to be effective. In addition, the findings of the regression analysis conducted to reveal the determinants of efficiency revealed significant results.

Research universities in Türkiye should allocate their resources in a way to increase research performance. Policies should be developed to increase the number of publications and, more importantly, the quality of publications.

Potential areas for improvement were identified for the universities to become efficient. The results revealed that both publication quality and productivity need to be improved, but there is more room for improvement in publication quality. Regression analysis with the determinants of efficiency scores shows that the development level of the region where the universities are located has a positive effect on the research efficiency of universities. In addition, it is concluded that smaller universities have better efficiency scores.

This paper aims to assess whether incubation affects the technical efficiency of innovative firms after entering the market. The study of efficiency allows firms to understand how well resources have been used in production processes. The research intends to contribute to the literature on the performance of incubated firms.

This study estimates the relative efficiency of innovative firms adopting a DEA-based two-stage semi-parametric method. Incubation, firm age and initial capital are used for explaining the relative performance of previously incubated firms compared to non-incubated ones over a six-year period of activity. This research focuses on Italian innovative firms using a large sample of companies.

Results show that incubators have a positive and significant effect on efficiency for firms that have been in the market for more than two years. Efficiency also improves with age and with the level of initial capital of the firm.

This analysis is limited to the quantitative dimension of inputs as reported in the balance sheets, without qualitative considerations.

Findings enhance firms' understanding of the role of incubators as neutral places to develop a business culture of efficiency. From an empirical standpoint, this study provides useful insights to start-uppers who intend to attend incubation programs. Overall, incubators matter to the extent that they enable new firms, net of those that fail to survive in the first two years of activity, to improve their efficiency in the use of inputs. This research also suggests incubators consider the start-ups’ potential of being efficient.

Findings provide tips to policymakers when they are called upon to propose funding programs to support prominent firms entering the business scalability.

This study contributes to the literature on the relative performance of post-incubated firms, highlighting the efficiency frontier analysis. This methodological approach is relatively new in this field. It allows researchers to study the innovative firms' performance in relative terms, that is with respect to the input level. It integrates the performance-based with efficiency frontier analysis. Also, this study reinforces the idea that incubators prepare start-ups to develop capacities and managerial skills, which will be useful in post-incubation life to improve their cost competitiveness.