Decomposition of efficiency using DEA window analysis: A comparative evidence from Islamic and conventional banks

A Survey of DEA Window Analysis Applications

This article aims to review, analyze, and classify the published research applications of the Data Envelopment Analysis (DEA) window analysis technique. The number of filtered articles included in the study is 109, retrieved from 79 journals in the web of science (WoS) database during the period 1996–2019. The papers are classified into 15 application areas: energy and environment, transportation, banking, tourism, manufacturing, healthcare, power, agriculture, education, finance, petroleum, sport, communication, water, and miscellaneous. Moreover, we present descriptive statistics related to the growth of publications over time, the journals publishing the articles, keyword terms used, length of articles, and authorship analysis (including institutional and country affiliations). To the best of the authors knowledge, this is the first survey reviewing the literature of the DEA window analysis applications in the 15 areas mentioned in the paper.

The Efficiency Analysis of Large Banks Using the Bootstrap and Fuzzy DEA: A Case of an Emerging Market

In this study, banks’ business performance efficiency was analysed using data envelopment analysis (DEA), with expense categories as inputs and income categories as outputs. By incorporating a bootstrap method and a fuzzy data approach into a DEA model, additional insights and sensitivity analysis of the results were obtained. This study shows how fuzzy and bootstrap DEA can be used for investigating real market problems with uncertain data in an uncertain sample. The empirical analysis was based on the period of 2009–2018 for a sample of seven of Croatia’s largest private banks. The aim of the study was also to interpret the DEA results with regards to the specific market, legal, and macroeconomic conditions, caused by the changes introduced in the last decade. The results, and the changes in the inputs and outputs over time, revealed that the market processes occurring in the observed period had a significant impact on banks’ business performance, but led to a more efficient banking system. Two banks were found to be dominant over the others regardless of the changes in the sample and data fuzziness. DEA results were additionally compared to the most important financial indicators and accounting ratios, as an alternative or additional measure of banks’ efficiency and profitability.

Developing a new super-efficiency DEA model in the presence of both zero data and stochastic data: a case study in the Iranian airline industry

Purpose

The purpose of this study is to propose a novel super-efficiency DEA model to appraise the relative efficiency of DMUs with zero data and stochastic data. Our model can work with both variable returns to scale (VRS) and constant returns to scale (CRS).

Design/methodology/approach

This study proposes a new stochastic super-efficiency DEA (SSDEA) model to assess the performance of airlines with stochastic and zero inputs and outputs.

Findings

This paper proposes a new analysis and contribution to the knowledge of efficiency assessment with stochastic super-efficiency DEA model by (1) using input saving and output surplus index for efficient DMUs to get the optimal solution; (2) obtaining efficiency scores from the proposed model that are equivalent to original stochastic super-efficiency model when feasible solutions exist. A case study is given to illustrate the applicability of our proposed model. Also, poor performance reasons are identified to improve the performance of inefficient airlines.

Originality/value

For the first time, a new SSDEA model for ranking DMUs is proposed. The introduced model produces a feasible solution when dealing with zero input or output. This paper applies the input saving and output surplus concept to rectify the infeasibility problem in the stochastic DEA model.

Ownership type, bank models, and bank performance: the case of the Yemeni banking sector

Purpose

The purpose of this paper is to examine bank performance using the different performance measures, namely, return on assets, return on equity and bank margins (MAR).

Design/methodology/approach

Unbalanced panel data were constructed to test the related hypotheses and provide evidence on the relationship between ownership types, banking models and performance indicators adopting the random effects techniques.

Findings

The findings of the paper substantiate that the banking models are significant performance indicators. However, the results are contingent on the GDP growth of the country. Moreover, the evidence indicates that the impact of ownership types is inconclusive in all measures of performance. However, the GDP is significant when it interacts with the types of ownership, particularly for foreign and government banks, although the evidence is mixed and unfavourable for government banks.

Practical implications

The results of the study provide insights for bankers and policymakers to enhancement Yemen’s banking sector.

Originality/value

This study is considered as the first attempt in examining the role of banking model and ownership type and their link to banking model.