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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.

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.

Since airlines that employ their resources effectively will achieve operating profitability, air route resource allocation is significant for airlines. This study aims to investigate an appropriate model to reallocate resources into each air route of an airline company.

This study proposes a network centralized data envelopment analysis (DEA) models with slack-based measure (SBM). The proposed model not only takes into account the two interconnected stages but also considers the nonradial approach with transfer-in and transfer-out slacks for resource reallocating. Furthermore, the authors modify the objective function to an input-oriented function with SBM, and divide the model into passenger and freight parts, which makes the model more realistic for the characteristic of air routes.

The empirical analysis using an airline company's internal data provides airline operators with information on how they increase or decrease input resources, which can serve as a practical guideline of resource reallocation. Specifically, the results indicate that the airline company should increase their input resources into long-haul air routes such as KOR-OCN while decreasing their input resources into short-haul air routes such as Korean-Oceania (KOR-OCN), Korean-Chinese (KOR-CHN), Korean-Southeast Asian (KOR-SEA), Korean-Japanese (KOR-JPN).

Although some papers evaluate air route efficiencies based on the DEA approach, a few existing papers have addressed resource allocation for air routes. This paper is the first to study the resource reallocation for air routes based on the DEA approach, contributing to the literature in expanding the scope of research on resource reallocation.

The purpose of this study is to measure the technical efficiency of 20 Algerian insurance companies from 2016 to 2020, by using slacks-based measure (slacks-based measure [SBM] data envelopment analysis [DEA]) model. This research aims to provide a comprehensive assessment of this companies' efficiency, taking into account both the desirable and undesirable outputs.

The study uses a nonoriented, SBM model with the assumption of constant returns to scale to estimate the technical efficiency of commercial insurance companies over a five-year period. The inputs used are labor expense, agent expense and investments, while the outputs included are gross premiums and investment income as desirable outputs and gross claims as undesirable output.

Among 20 insurance companies evaluated, only 5 companies consistently achieved technical efficiency during the study period (Caisse Nationale de Mutualité Agricole [CNMA], MACIR, CARDIF, MUTUALISTE and AGLIC); so they represent the best practices in the Algerian insurance sector, with overall average of the technical efficiency is 81%. However, the reference sets analysis showed that CNMA and AGLIC had high robustness. Also, the results demonstrate the impact of ignoring the undesirable outputs on the accuracy of the assessment.

The sample of the study consists of the active insurance companies in Algeria, based on the Annual Insurance Reports of Algeria; there are 20 companies as shown in the table. The data are taken from the annual reports of insurance companies during the 2020 period, issued by the Algerian Ministry of Finance.

The challenge for insurance company is how to find a balance between reducing claims paid and simultaneously improving the quality of insurance services. In fact, it is observed that studies evaluating their efficiency ignore claims in the analysis process. Therefore, the study highlights the importance of considering undesirable outputs within the DEA framework; this allows for a more accurate assessment of the company's performance and helps in improvement. Furthermore, although the insurance sector plays a crucial role, it has not received enough research attention compared to other financial sectors, especially in Arab and developing countries.

The literature on efficiency assessment in the insurance companies shows a lack of addressing undesirable outputs (such as claims) within the DEA framework; so this study aims at bridging this research gap. Also, the study provides an overview of the efficiency of Algerian insurance companies.

Data envelopment analysis (DEA) calculates the efficiency of a business unit if all the inputs are creating outputs within a “black box.” Under traditional DEA, the detailed process of that business unit is ignored. However, a network DEA can explain the black box structure and provide efficiency results for sub-sections within any business process. This study aims to propose a network DEA model that explains a bank's total operation.

Earlier studies have focused only on bank efficiency ignoring this breakdown. This study departs from them by using a slack-based two-stage network DEA under a novel banking business perspective.

The results reveal that network DEA provides better benchmarking insights than the traditional DEA. As such, better benchmarking can guide both the banking industry managers and policy makers in Bangladesh.

The major contribution of this study includes dividing a bank's total operation efficiency into two sub-operations: “core operations – collecting deposits and giving loans” and “additional operations – fees, commissions and other services.”

This study aims to investigate environmental efficiency based on energy change by using energy-related or nonenergy-related variables by reckoning with months and years as decision-making units (DMUs) for a hospital under radial and nonradial models.

The non-oriented slack-based measures (SBM)-data envelopment analysis (DEA) model considering desirable and undesirable outputs has been embraced in this study, where its obtained results were compared with the results of other DEA models are output-oriented SBM-DEA and Banker, Charnes, & Cooper-DEA. For this purpose, this research has used a data set covering the 2012–2018 period for a reference hospital, which includes energy-related and nonenergy-related variables.

The results demonstrate that environmental efficiency based on energy reached the highest level in the winter months, whereas the summer months have the lowest efficiency values arising from the increasing electricity consumption due to high cooling needs. According to results of the non-oriented SBM model, the month with the highest efficiency in all periods is January with a 0.936 average efficiency score, the lowest month is August with a 0.406 value.

This paper differs from other studies related to energy and environmental efficiencies in the literature with some aspects. First, to the best of the authors’ knowledge, this study is the first one that takes into account time periods (months and years) as (DMUs for a single organization. Second, this study investigates environmental nonefficiencies, which are derived from energy uses and factors affecting energy use.

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.

Performance evaluation is a good way to improve competitiveness, and leveraging competitiveness is vital to developing optimal strategies and sustainable development for the growing restaurant industry in the USA and across the globe. This study can benefit from the methods to inform business strategies and decisions. Through the combination of two methods, this paper aims to provide novel perspectives to realize each restaurant company’s resource allocation and performance, to know their market position compared to with other competitors, and then to develop their own business strategies.

This study proposes an application of slack-based measure (SBM) to determine input excesses and output shortfalls of the restaurant industry. Subsequently, context-dependent data envelopment analysis (DEA) is used to identify the level of each restaurant company and compute the relative attractiveness and progress scores for each restaurant at each level, positioning each restaurant company’s stance in their markets.

The empirical results reveal that management teams need to pay more attention to human resources, asset management and food cost control because the analysis of SBM model shows an opportunity for restaurant companies to adjust their hiring numbers to reach the optimal amount of employees. In addition, restaurant companies are categorized by their efficient frontiers into four levels using context-dependent DEA. Furthermore, the findings provide the four quadrants that each restaurant company falls into. Each of those four quadrants can guide the types of strategies a restaurant should adopt.

This study can help the publicly traded restaurant companies to identify their market position with target benchmarks, and then to develop optimal strategies and future plans for growth.

The purpose of this paper is to develop a suitable framework of sustainable urbanization performance evaluation from the view of efficiency for mitigating the unbalance between the theoretical research of sustainable urbanization and the practical need of sustainable urbanization.

A slack-restricted slack-based measure data envelopment analysis (DEA) model and two sustainable urbanization benchmarking methods with individual and centralized view, respectively, are developed based upon the classical DEA theory.

The empirical results show that China is now suffering a relatively low level of sustainable urbanization. Too much waste water emission, too small an urban population proportion, and too much resource wastage are the major factors that drive China’s urbanization away from sustainability.

Having the overall aim of practical urbanization, the proposed framework can help stakeholders recognize different sustainable urbanization performance levels by offering them accurate sustainable urbanization performance scores. The framework can also direct governments to improve the sustainable urbanization performance. The empirical analysis of China’s provincial region sustainable urbanization performance with the proposed framework further demonstrates the theoretical and practical value of this research.

This paper introduces the concept of policy efficiency of banks as their efficiency in implementing the government's policies. It further compares the Indian public sector banks (PSBs) and private sector banks (PVBs) on two efficiency paradigms, operational efficiency and policy efficiency.

A three-stage analysis is carried out on data collected for 19 PSBs and 16 PVBs for ten years. Non-radial DEA with slack-based measure (SBM) is used to obtain efficiency scores of the banks for the two efficiency paradigms. The efficiency scores and the changes in efficiency and Malmquist index are further analysed by Tobit regression and seemingly unrelated regression (SUR) models.

PVBs are found to be more operationally efficient than PSBs. On the contrary, PSBs are found to be more policy efficient. Among the PSBs, the older and larger banks performed better in both the paradigms. Though Indian banks have become more operational and policy efficient over the years, the rate of improvement is slowing down.

Results imply that evaluating banks, especially PSBs, only on their operational efficiency is myopic. Their efficacies must also be measured by the roles they play on social and policy front. The loss of efficiency of Indian PSBs in a competitive environment should provoke thoughts of reforms. The study suggests that the proposed merger of PSBs to form large banks might be fruitful.

The study contributes to the literature by introducing the measure of policy efficiency. It shows that the Indian PSBs are indispensable as vehicles of government policy implementation.