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The purpose of this study is to evaluate the performance of the Champions League teams using the entropy-integrated Multi Attribute Ideal-Real Comparative Analysis (MAIRCA) and super-slack-based data envelopment analysis for the 2012–2022 period.

This study consists of two sections. First, this study uses the entropy-integrated MAIRCA approach, which is a novel multi-criteria decision-making (MCDM) technique developed by Gigović, to measure the performance of Champions League clubs. Second, this study proceeds with the super-slack-based DEA to evaluate the efficiency of the Champions League clubs.

As per the empirical results, Real Madrid is found to be the best-performing club over the past 10 years in terms of financial and sportive performance. Over the analyzed period, teams from the five Major Leagues of Europe perform better.

To the best of the authors’ knowledge, performance measurement studies in football have focused on either DEA or MCDM. This study aims to present novelty for football literature by evaluating holistically both the sportive and financial dimensions. This paper also analyzes Champions League teams from the perspective of both MCDM and super-slack-based DEA methods.

The purpose of this study is to propose a comprehensive benchmarking approach to help subsidiaries of a company to implement continuous improvement (CI).

The proposed approach classifies subsidiaries of a company into the three stages of CI. After that, the proposed approach employs data envelopment analysis (DEA)-super slacks-based measure (SBM) model and Malmquist Productivity Index (MPI) to evaluate the operational efficiency of the subsidiaries and selects benchmarking targets and sets benchmarking goals based on the operational efficiency for benchmarking of input and output criteria. Then, the proposed approach suggests a four-step benchmarking process for benchmarking of detailed efficiency. Finally, the proposed approach makes the subsidiaries achieve CI by implementing the input and output benchmarking and the efficiency benchmarking.

The results show that the proposed approach can help subsidiaries of a company to implement a staged benchmarking which considers input and output criteria and Malmquist productivity and efficiency comprehensively.

Generally, benchmarking is implemented in many aspects. However, due to the restriction of a company’s resource level, a practical and staged benchmarking is preferred. This study proposes a comprehensive approach to benchmark systematically and gradually, and provides a more reasonable benchmarking process for implementing CI.

The purpose of this paper is to suggest a model for evaluating the best power plants in the presence of weight restrictions.

The paper introduces a model, which is based on slacks‐based model (SBM) (one of the data envelopment analysis (DEA) models).

The paper depicts the power plant evaluation process through a DEA model, while allowing for the incorporation of preferences of decision maker (DM). The chief advantage of the proposed model is that it does not demand exact weights from the DM.

To the best of the author's knowledge, there is not any reference that evaluates power plants by means of SBM in the presence of weight restrictions.

The motivation for this paper stems from the 2001 financial crisis which emerged in the banking industry and spread over the other industries, creating a domino effect. The purpose of this paper is to examine the market efficiency of Istanbul Stock Exchange (ISE) listed non-financial firms from 2000 through 2002.

A four-stage data envelope analysis (DEA) is developed to measure the performance of firms before and after the 2001 financial crisis. At each stage, production, profitability, marketability and overall efficiencies are measured. Further, Malmquist Productivity Index is applied to compare total factor productivity over time.

The findings show that firms are more efficient at the profitability stage than at other stages. However, the 2001 financial crisis eroded profitability efficiency. Overall, ISE-listed firms experienced diseconomies of scale so that many firms were not able to transform production into sales and therefore earnings efficiently, particularly during the crisis period.

The sample is limited to manufacturing companies. All financial firms are excluded from the sample.

This paper extends the three-stage market value efficiency process outlined in Zhu (2000) by adding production stage. It proposes four-stage DEA approach to measure production, profitability, marketability and overall efficiency of ISE-listed firms. To the best of authors’ knowledge, there has been no study using four-stage DEA approach for Turkish firms.

The purpose of the research presented in this paper is to provide a new approach related to the definition of variables in disaggregating branch expenses and income for evaluating the overall technical efficiency of bank branches by means of data envelopment analysis (DEA).

By applying an input minimization DEA model to a sample of bank branches of a large commercial bank in Greece, this study identifies pure technical and scale inefficiencies, efficiency and size relationship and returns to scale patterns. Moreover, it explores target setting strategies for inefficient branches.

Results indicate that branch size has an important influence on efficiency and that superior insights can be obtained by pure technical efficiency (PTE) and scale efficiency (SE), as constituent components of global technical efficiency (TE) than the information obtained from the analysis based on selected key performance indicators (KPIs) used by the bank under study.

A direction of future research would be to extend the analysis to incorporate environmental factors, such as branch location, local competitive environment, investment portfolio risk, among others, into the DEA assessment.

The study shows that DEA which provides an overall summary measure with respect to global TE and its constituent components PTE and SE can be used to complement the in‐house performance management system of the bank under study for the evaluation of its branch network.

From a policy perspective, this study highlights the use of DEA combined with statistical analysis to support the reduction of burden by means of either expense reduction or revenue enhancement.

We adopt a super slack-based measurement (SBM) data envelopment analysis (DEA) model to estimate the efficiency of five biggest freight rail operators in Russia, which are included in the top 30 freight rail operators in terms of two dimensions – financial and operational efficiency during 2013–2017. The result shows that the private companies characterized by high financial and operational efficiency, while the Rossiiskye Zheleznye Dorogi (RZD) subsidiaries characterized by sufficiently low financial and operational efficiency scores. And the result also presents that operational efficiency score of operators handling universal rolling stock is higher than financial efficiency scores. In contrast, financial efficiency scores of operators handling special rolling stock is higher than operational efficiency scores. rail freight operators in addition to a special rolling stock park should have a universal rolling stock park for higher profitability. State-owned companies and its subsidiary operate inefficiently in the midst of a market economy in Russia. Rail freight operators for a higher level of financial efficiency should be transferred to the private sector.

This paper aims to assess the efficiency levels of World Cup teams via the slack-based data envelopment analysis (DEA) approach, which contributes to filling an important gap for performance measurement in football.

This study focuses on a comparative analysis of the past two World Cups. The authors initially estimate the efficiency of the World Cup teams via the slack-based DEA approach, which is a novel approach for sports performance measurement. The authors also present the conventional DEA results to compare results. The authors also include improvement ratios, which provide significant details for inefficient countries to enhance their efficiency. Besides, the authors include effectiveness ratings to present a complete performance overview of the World Cup teams.

According to the analysis results of the slack-based DEA approach, titleholder Germany and France are found as efficient teams in the 2014 and 2018 World Cup, respectively. Besides, Belgium and Russia recorded the highest efficiency improvement in the 2018 World Cup. The novel approach for sports performance measurement, the slack-based DEA approach, significantly overlaps with the actual performance of teams.

This study presents novelty in football performance by adopting the slack-based DEA with an undesirable output model for the performance measurement of the World Cup teams. This empirical analysis would be a pioneer study measuring the performance of football teams via the slack-based DEA approach.

Waste management is one of the vital objectives for the EU since it has a substantial effect on the environment. European Commission expects annual waste creation on Earth to increase by 70% by 2050. European Commission also estimates that efficient waste management might boost the EU economy's gross domestic product (GDP) by 0.5% by 2030. Hence, it is essential to conduct research including both efficiency and influencing factors analysis for effective waste management. First, we employ both slack-based measure (SBM) and super-SBM data envelopment analysis approaches to investigate the waste management efficiency of the EU region and distinguish between efficient countries. The countries with small areas such as Luxembourg and Ireland have demonstrated super efficiency. Second, we maintain our empirical research with ordinary least square analysis to explore the determinants of waste management. We also conclude that population density, GDP per capita, and tourism rise the amount of waste generated in the EU region.

This paper aims to research the relationship between income gap (IG) and green economic growth based on the perspective of economic inequality.

Based on the panel data of 283 prefecture-level cities in China from 2011 to 2020, this paper uses the super slack based model (Super-SBM) to measure the efficiency of regional green economic growth, and constructs a regression model of the IG and regional green economic growth.

Firstly, the IG has an inhibitory effect on the growth of regional green economy (GE). Secondly, the relationship between the IG and regional green economic growth will be affected by the threshold value of income level. Thirdly, environmental regulation and government competition will increase the inhibitory effect of the IG.

According to the characteristics of China's regional economy, the researchers construct an empirical model of the IG and green economic growth to study their relationship, the threshold effect of income level and the moderating effect of environmental regulation and local government competition. The research content, methods and conclusions of this paper provide new evidence for the sustainable growth of China's regional GE.

The purpose of this paper is to evaluate design performance of 51 gear shaping machines by using data envelopment analysis (DEA).

Existing studies extend traditional DEA by handling bounded and discrete data based on envelopment models. However, value judgment is usually neglected and fail to be incorporated in these envelopment models. In many cases, there is a need for prior preferences. Using existing DEA approaches as a backdrop, the current paper presents a methodology for incorporating assurance region (AR) restrictions into DEA with bounded and discrete data, i.e. the assurance region bounded discrete (AR-BD) DEA model. Then, the AR-BD DEA model is combined with a context-dependent DEA to obtain an efficiency stratification.

The authors examine different AR restrictions and calculate efficiency scores of five scenarios of AR restrictions by using the proposed AR-BD DEA model. It shows that AR restrictions have a great impact on the efficiency scores. The authors also identify nine efficient frontiers in total. For each decision-making unit, it could set benchmarks and improve its performance based on each higher efficient frontier.

This paper first evaluates efficiency of gear shaping machines by considering different (bounded and discrete) variable types of data and including AR restrictions. The AR-BD DEA model and context-dependent AR-BD DEA model proposed in this paper further enrich the DEA theory. The findings in this paper certainly provide useful information for both producers and consumers to make smart decisions.