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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.

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.

There is ample empirical evidence to show that larger banks are more efficient than smaller banks in developed countries. However, there is very little empirical evidence to show that in small developing economies, such as Vietnam, bank size is associated with increased risk, especially credit risk. This paper aim to provide empirical evidence to fill in this gap. This paper employs a slack-based directional distance function using the intermediation approach in measuring the inefficiency of banks in Vietnam during the period 2006–2015. Non-performing loans are used as an undesirable output to capture credit risk. The results show that small banks are more efficient than large banks at the mean level and across the entire distributions of inefficiency of the two groups. Input waste, output shortage and risk surplus of big banks are nearly three times higher than those of small banks. The results are robust under constant and variable returns to scale for production technologies. The study’s empirical results contribute to the ongoing debate on the merits of enlarging bank size in a small transitional economy and suggest that policy makers should pay attention to the risk and inefficiency of large banks to enhance the performance of Vietnam's banking system as a whole.

This paper uses the non-radial slack-based directional technology distance function developed by Färe and Grosskopf (2010) to estimate the efficiency of banks using the data envelopment analysis technique. Data for 44 commercial banks are used.

The empirical results of the paper contribute to the ongoing debate on the merits of enlarging bank size in a small transitional economy and suggest that policy makers should pay attention to the risk and inefficiency of large banks to improve the performance of Vietnam's banking system as a whole.

This paper extends the extant literature by examining whether efficiency is associated with size in a typical transitional developing economy. The classic Cournot model, the structure-conduct-performance and the efficiency structure hypotheses state that larger banks are more efficient than smaller banks (Bikker and Bos, 2008). Empirical studies of Berger (2003), Mester (2005), Wheelock and Wilson (2012) lend support to the statement in developed countries. However, not much empirical literature focuses on small developing economies such as Vietnam to show that bank size is associated with increased risk, especially credit risk. The study’s empirical results show that size enlargement is not positively associated with risk-adjusted efficiency. Input waste, output shortage and risk surplus of big banks are nearly three times higher than those of small banks. The results are robust under constant and variable returns to scale for production technologies.

This paper aims to measure the comparative managerial efficiency of 24 leading third‐party logistics providers (3PLs) in North America and identify best‐practice firms among these 3PLs.

This paper proposes data envelopment analysis to measure the slack‐based efficiency, pure technical efficiency, and mixed efficiency of 24 leading 3PLs in North America, relative to their rivals in world‐wide 3PL markets. In particular, this paper develops both the Charnes, Cooper and Rhodes (CCR) model under constant returns to scale and the Banker, Charnes, and Cooper (BCC) model under varying returns to scale that are designed to derive weights without being fixed in advance.

With respect to managerial efficiency, this study did not find any significant performance differences between asset based 3PLs and non‐asset based 3PLs. Defying the common sense, relatively small but niche‐oriented 3PLs with limited service offerings tended to perform better than their larger counterparts with a wide variety of service offerings to customers all across the world. A majority of leading 3PLs in North America suffer from overcapacity and the subsequent underutilization of their physical and human resources.

This paper provides practical guidelines as to how 3PLs can find right niche markets, manage slack/idle resources, and cope with increasing competition.

This paper is one of the first to develop a variety of efficiency measures for 3PL operational performances including pure technical (managerial) efficiency, slack‐based efficiency, scale efficiency, and mix efficiency under both constant and varying returns to scale. This paper also considers the much larger number of 3PLs than those considered by prior benchmarking studies for performance evaluation; thus, it captures the “true” managerial efficiency of 3PLs relative to their competitors in the more crowded North American 3PL industry.

This paper aims to examine the efficiency of Islamic vs conventional banks in Malaysia by unveiling the traditional efficiency concept – black box – with a three-stage network structure of bank operations.

This paper applies data envelopment analysis (DEA) for examining bank efficiency. An adaptive three-step network DEA (NDEA) model is demonstrated for redefining the traditional black box of banking operations. Slack-based variable returns to scale approach is used. Data from all 43 commercial banks in Malaysia are examined over a six-year study period (2010-2015). Inputs and outputs of the model are selected based on CAMELS rating. Undesired output is also considered in time of examining bank efficiency in Malaysia.

The empirical results of this study signify that only a few banks in Malaysia have been performing well in converting deposits and equities into profit as well as minimizing loan loss provisions. Islamic banks in Malaysia have performed better both in production (converting deposits and equities into earning assets) and profitability (converting loans into net income). Conventional banks, however, have over scored in intermediation (converting earning assets into loans).

An adaptive NDEA approach proposed in this paper defines the core banking process instead of traditional approaches in examining bank efficiency based on individual functions (nodes in the network model). This approach has proven to provide better benchmark capacity.

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.

This paper uses various Data Envelopment Analysis (SBM-DEA) approaches to study the efficiency of major airlines in Asia-Pacific region. To evaluate the operation efficiency of fourteen major airlines in Asia-Pacific region from 2003-2011, Available Seat Kilometers(ASK), Available Ton Kilometers(ATK), the number of employees are used as input factors, Revenue Passenger Kilometers(RPK), Revenue Ton Kilometers(RTK), the amount of Sales are used as output factors.

The non-radial SBM-DEA (Slacks-based Measure of Efficiency) model was able to provide a more comprehensive efficiency of combining economic performance and regional difference. And it was also able to capture slack values in input excess and output shortage.

The results demonstrate that Korea and Japan airlines are operated efficiently and could be regarded as the benchmarking airlines. On the other hand, most of the China and ASEAN airlines are deemed to be inefficient. Also analyzing slacks may be more suitable way for the evaluation or suggestion of an improvement scheme for the inefficient airlines. The excess of labor is the major cause of the airlines’ inefficiency.

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.

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.

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.