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The aim of this paper is to evaluate the efficiency of 22 cargo seaports situated in the regions of East Africa and Middle East.

The data envelopment analysis (DEA) with window analysis model evaluates the efficiency score in terms of normal efficiency and super efficiency. The analysis is based on the panel data for the period of 2000‐2005.

The number of efficient decision making units (DMUs) under super efficiency is more than the number under normal efficiency.

Using panel data, this paper is the first study to use super efficiency with window analysis that compares the efficiency estimated with the normal efficiency and with super efficiency.

The purpose of this paper is to longitudinally assess the technical efficiency and productivity, considering investment projects and technological change, in a second-generation petrochemical company.

The study uses data envelopment analysis (DEA) together with the Malmquist index to measure efficiency during the analysis periods. The working method consists of four main phases, namely development of the conceptual model, construction of the mathematical model, application of model to the case, and analysis of the results. The study utilizes a quantitative approach with descriptive goals seeking to evaluate the impacts of technical changes on the operational efficiency and productivity of the production process.

The use of DEA associated with the Malmquist index proved to be viable for analyzing a single company and identifying efficiency improvements, as well as the impacts of the learning process and the implementation of improvement projects. However, the results of the improvement projects and learning process were not representative and had no statistical significance on the actual change in efficiency of the company during the periods analyzed. For the case in question, the learning process and continuous improvement were not observed during all study periods.

The proposition that the improvement projects and investments implemented increased the efficiency of the company was rejected. Hence, with this work, it was possible to determine that the company unnecessarily invested resources in projects to increase efficiency. Furthermore, the company could have explored more internal resources before making significant investments in increased efficiency.

As for the value of this research in the theoretical and academic scope, this paper advances knowledge on the application of DEA because it proposes to establish an internal reference benchmarking for comparison. The literature contains few studies that analyze organizations using continuous processes, such as petrochemical processes, in longitudinal studies as a function of time, especially with the use of DEA.

The purpose of this paper is to estimate the relative efficiencies of banks of the Indian domestic banking sector by employing various models of data envelopment analysis (DEA) using the panel data of the recent decade (2008–2017). The paper provides a comparative analysis of these models based on the efficiency outputs. It compares the performance of banks based on their ownership and sizes and studies the decade-long trend of productivity using Malmquist indices.

This paper estimates overall technical, pure technical and scale efficiencies of 21 public sector banks and 17 private banks. It compares the descriptive statistics of efficiency estimates found out through 18 different DEA models and compares them using two non-parametric statistical tests. It studies the difference in efficiencies based on ownership and size by applying the same statistical tests. It employs the Malmquist index method to study the technological and technical progress in the banks’ productivity over the decade of FY 2008–FY 2017.

During FY 2016–2017, only 9 out of 38 banks were overall technically efficient with the whole sample having a mean overall technical inefficiency of 5 percent with scale inefficiency contributing more than pure technical inefficiency. The comparative study ascertains that private sector and public sector banks (PSBs) possess efficiencies that are similar based on super-efficiency slack-based model – variable returns to scale and non-oriented, a model that the authors argue to be the most suitable for the real-life business banking scenarios whereas the private sector banks possess better efficiency than the PSBs. The Malmquist indices prove that private sector banks have a higher increase in productivity based on both technological progress and efficiency improvements whereas PSBs had a loss of efficiency and comparatively less improvement in technology.

This study has a limitation of choosing a single model of inputs and outputs. Improved insights can be drawn by employing more models based on different inputs and outputs. Further, relevance of each input and output can be examined using a regression-based feedback mechanism (Ouenniche and Carrales, 2018). The influence of environmental factors on the efficiencies can be studied using second-stage regression models and the relationship between efficiency scores and financial ratios can be examined.

This study is based on the panel data of the recent decade (2008–2017) and provides insights into the efficiency scenario of the Indian banking industry and how it changed over the past decade, to the leadership of banks, the banking regulators and the policy makers. The comparative analysis of DEA models based on a sample of Indian banks is first of its kind in the Indian context and helps the researchers to select an appropriate model and delve into further research on the same.

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.

The purpose of this paper is to estimate retailing efficiency in a 26-store women clothing retail chain and to decompose it in several measures in order to contribute to the performance improvement of this retail service firm, as well as to compare the efficiency of the different decision making units.

This paper uses the following measures to estimate efficiency: sigma convergence analysis; efficiency analysis; technical efficiency (TE) analysis; pure technical efficiency (PTE) analysis and scale efficiency (SE) analysis for a set of 26 stores of a women retail service brand operating in Portugal. A cross-section input-oriented data envelopment analysis (DEA) is used to analyse quarterly data sets from 2010 to 2013.

The results show that costs with personnel are slightly increasing when analysed using the sigma convergence method, although there are some geographical differences. Moreover, it is possible to witness that the retail store chain’s TE diminishes as the operations outputs do not grow as fast as input savings. On the other hand, there are no SE problems as the levels of SE are larger than pure efficiency levels.

The main limitation of the study stems from the fact that the analysis is based on a simple retail chain, which makes it a single case study. Therefore, the generalisation of the conclusions for other firms or for other periods of analysis should be made cautiously.

It is shown that some stores have a good TE and other stores have some SE advantage. As such, it is possible to select some stores as benchmarks to deploy internal efficiency throughout the retail chain.

The contribution of this paper is based on the application of the sigma conversion and DEA techniques to evaluate efficiency in retail service store.

The purpose of this paper is to analyze the productive efficiency and the best operational practices in an armaments manufacturer.

A longitudinal case study is performed using data envelopment analysis (DEA). Using DEA, an assessment of six years in the company manufacturing process is conducted. The research aims at developing an internal benchmark on three production lines of the company.

The results show that only one of the three analyzed production lines increased efficiency over time. With this result, the most efficient production line may be used as a reference in relation to the best operational practices of the company. Moreover, it was found that the current indicators to evaluate efficiency are insufficient and may lead to wrong management decisions.

This research could allow a larger understanding of the factors that really contribute to increased operational efficiency. This is due to internal benchmark assist in the identification of the best practices. The identification of best practices can contribute to enhance the efficiency of inefficient operations without the need for external comparisons.

DEA contributes due to its robustness, for the evaluation of productive efficiency. One of the contributions of this study is to identify opportunities for improvement in key components of the operation through targets, internal benchmarking and robust assessment of productive efficiency.

In today’s multi-channel distribution environment, it is crucial for the competitiveness of retail stores and companies to improve efficiency of dedicated logistics centers (DLCs) servicing types of retail outlets such as large retail-stores, super supermarkets, and convenient stores. This paper derives efficiency improvement strategies for DLCs through efficiency analyses. To this end, this paper empirically analyzes the efficiency of DLCs by applying DEA (data envelopment analysis) approaches using real data from a Korean distribution company. In detail, this paper analyzes operations, finance, and service efficiencies of DLCs and performs a comparison analysis on the efficiency between DLCs. Finally, this paper discusses the analysis results considering the DLCs’ characteristics and derives managerial and operational implications.

The purpose of this paper is an analysis of the process of digital transformation of enterprises, by measuring the efficiency of the use of information and communication technologies (ICTs) in business in 29 European countries in the period from 2012 to 2020.

A Charnes, Cooper and Rhodes data envelopment analysis (CCR DEA, 1978) window model has been developed to measure the ICT efficiency of European countries. Several indicators of the use of information and communication technologies in enterprises are selected as the variables of the proposed models, which are available as such in the Eurostat database for European countries. Due to the sensitivity of the results obtained by applying the DEA method to measurement errors and output values, the robustness analysis of the obtained values of average efficiency is also performed, using the bootstrap method.

The obtained results show that the highest average technical efficiency of the use of ICT in companies by windows, in the observed period, is recorded in Belgium, while Denmark is in the second place. Bulgaria, Romania, Greece and Latvia have the lowest average technical ICT efficiency per window. The analysis of the obtained results by years in the same period brings identical conclusions. Only Belgium has been ICT efficient many times. In general, for all observed countries, the movement of average ICT efficiency in the observed period shows a slightly growing trend, with the exception of a significantly decline in 2013. However, the fact is that the ICT efficiency of the observed countries in the past period is relatively low and for all countries it is 46.36%, with no country being 100% efficient and with eight countries whose average efficiency is below 50% of best practice.

To measure and evaluate the efficiency of ICT use in enterprises, four variables for efficiency assessment are identified, given the fact that only these data are available continuously for the observed period from 2012 to 2020 in the Eurostat database.

Low efficiency of using digital potential in business of the observed countries indicates the need for better understanding of the nature and goals of the digital business transformation process by employees and management, to create conditions for effective implementation and optimization of business digitalization.

Measurement of digital transformation is the subject of a very small number of studies and research, which mainly focus on measuring and assessing the impact of digital transformation on individual countries and perform a comparative analysis of technological development in those countries. Also, analyses are mainly based on identifying similarities and differences between countries or ranking countries according to adopted evaluation criteria using different digitization indices. A step forward in this research is the application of the DEA window method for measuring the relative efficiency of the use of ICT in enterprises, and the development of a model that can be extended if necessary with indicators for which data are available.

Data envelopment analysis (DEA) and window analysis are used to follow the changes in Australian trading banks' pure technical efficiency, scale efficiency, and the nature of returns to scale. The main findings indicate declining average efficiency scores until 1991, followed by a steady rise thereafter. Pure technical inefficiency emerges as a greater source of inefficiency than scale inefficiency. Overall, regional banks exhibit increasing returns to scale and major trading banks exhibit decreasing returns to scale. Also worthy of note is the mixed size of banks operating at optimal returns to scale.

The main aim of the study was to measure and assess the efficiency of the healthcare system in Poland.

An output-oriented Data Envelopment Analysis model with a 2-years window analysis extension was used between 2013 and 2018. The analysis was completed with a determination of the sources of productivity changes (between the first and last year of the study period) and factors that influence efficiency.

Efficient regions have been identified and the spatial diversity in their efficiency was confirmed. The study identified individual efficiency trends together with “all-windows” best and worst performers. Using panel modeling, it was confirmed that the efficiency of health protection is influenced by, among others, accreditation certificates, the length of the waiting list or the number of medical personnel.

Although the analysis was conducted at the voivodeship level (NUTS2), which was fully justified, it would be equally important to analyze data with a lower aggregation level. It would be extremely valuable from the perspective of difficulties faced by the healthcare system in Poland.

The identification of areas and problems affecting the efficiency of the healthcare system in Poland may also be a hint for other countries with similar system solutions that also struggle with the same problems.

The paper explains the efficiency of the country's healthcare system while also paying attention to changes in its level, factors influencing it, spatial diversity and impact on the sector functioning.