Financial efficiency of commercial banks listed in Egyptian stock exchange using data envelopment analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahmoud Abdelrahman Kamel ◽  
Mohamed El-Sayed Mousa ◽  
Randa Mohamed Hamdy
Keyword(s):  
Data Envelopment Analysis ◽  
Commercial Banks ◽  
Stock Exchange ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Financial Efficiency ◽  
Content Type ◽  
Egyptian Stock Exchange

PurposeThis study used data envelopment analysis (DEA) models to measure financial efficiency of twelve commercial banks listed in the Egyptian stock exchange (CBLSE), along with evaluating changes to the financial efficiency during the period 2017–2019.Design/methodology/approachThe study used BCC-I, cross-efficiency, super-efficiency models, and Malmquist productivity index (MPI) to assess financial efficiency of the examined banks. The available data from both inputs and outputs were analyzed using R. studio V.I.3. 1056 software.FindingsOut of twelve banks examined, only four banks were efficient under BCC-I model over different years of the study period; however, only one bank (CIB) appeared to be the most efficient compared to other peers in the study sample. Moreover, MPI results revealed decreased financial efficiency during the study period, due to the decreased technological innovation, except for HDB. Tobit regression results confirmed that total assets and total equity are significant factors impacted financial efficiency of CBLSE.Practical implicationsThis study sheds light on the importance of evaluating financial efficiency of CBLSE to all stakeholders, to pinpoint weaknesses in banks' performance, and for evaluating financial policies and investment decisions.Originality/valueSeveral studies sought to implement different models of DEA to assess banking performance in different regions of the world, but very few studies examined financial efficiency of banks. To the best of authors’ knowledge, this study is one of those few that addressed financial efficiency of banks in Egypt.

Technical efficiency of private sector hospitals in India using data envelopment analysis

2018 ◽  
Vol 25 (9) ◽  
pp. 3570-3591 ◽  
Author(s):  
Aradhana Vikas Gandhi ◽  
Dipasha Sharma
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Hospital Industry ◽  
Technological Advancement ◽  
Tobit Regression ◽  
Content Type ◽  
Input Variables

Purpose The purpose of this paper is to ascertain the performance of Indian hospitals in recent past and derive meaningful insights for policy makers and practicing managers in this area. Design/methodology/approach This paper analyses the technical efficiency of select Indian private hospitals using three related methodologies: data envelopment analysis (DEA), Malmquist Productivity Index (MPI) and Tobit regression. Two output variables (i.e. total income and profit after tax) and four input variables (i.e. cost of labour, net fixed assets, current assets and other operating expenses) were selected for the purpose of the study. Findings DEA analysis has shown that 14 out of 37 hospitals are found to be efficient under the Cooper and Rhodes model of DEA and 20 out of 37 hospitals are efficient under the Banker, Charles and Cooper model of DEA. The empirical results pertaining to MPI indicate an overall productivity progress in the private Indian hospital industry during the study period, which is largely due to technological advancement in the industry. Tobit regression demonstrates that chain affiliated, specialized and multi-city located hospitals exhibit a higher technical efficiency. Research limitations/implications This study has a limitation with reference to the unavailability of data on the input and output parameters of the model. The data related to the number of beds, number of doctors, number of nurses, etc., were not available for the period under consideration. Originality/value This study seems to be one of the few studies applying productivity and performance analysis using DEA, MPI and Tobit regression for the Indian private hospital industry.

Efficiency measurement of Indian retailers using Data Envelopment Analysis

2014 ◽  
Vol 42 (6) ◽  
pp. 500-520 ◽  
Author(s):  
Aradhana Gandhi ◽  
Ravi Shankar
Keyword(s):  
Data Envelopment Analysis ◽  
Driving Forces ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Retail Sector ◽  
Data Envelopment ◽  
Productivity Analysis ◽  
Tobit Regression ◽  
Content Type ◽  
Retail Outlets

Purpose – The purpose of this paper is to analyze the performance of Indian retailers in recent past and derive meaningful insight for practicing managers in this area. Design/methodology/approach – This paper analyses the economic efficiencies of select Indian retailers using three related methodologies: Data Envelopment Analysis (DEA), Malmquist Productivity Index (MPI) and Bootstrapped Tobit Regression. Findings – DEA analysis has shown that five retail firms out of selected 18 are found as efficient under the CCR model of DEA and seven out of 18 retail firms are efficient under the BCC model of DEA. MPI results indicate that 61 percent of the firms have progressed in terms of the MPI during the period under consideration. The Bootstrapped Tobit Regression shows that number of retail outlets and mergers and acquisitions can be considered as the driving forces influencing efficiency of retailers in India. Research limitations/implications – The paper has a limitation with reference to the availability of data for a few retail outlets, especially in the modeling through the Bootstrapped Tobit Regression. Originality/value – This study seems to be the first in applying productivity analysis using DEA, MPI and Bootstrapped Tobit Regression for the Indian retail sector.

Effects of cross-border acquisitions on efficiency and productivity of acquired companies: evidence from cement industry

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slađana Savović ◽  
Predrag Mimović
Keyword(s):  
Data Envelopment Analysis ◽  
Transitional Economies ◽  
Cement Industry ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Content Type ◽  
Cross Border ◽  
Efficiency And Productivity ◽  
Practical Implications

PurposeThe purpose of this paper is to explore the effects of cross-border acquisitions on the efficiency and productivity of acquired companies in the cement industry in the context of a transitional economy.Design/methodology/approachThe Data Envelopment Analysis (DEA) and Malmquist Productivity Index were used to assess the efficiency and productivity of the acquired companies over the period 2000–2018. DEA and Malmquist index are combined with bootstrapping to perform succinct statistical inferences for determining the accuracy of results. The study assesses partial efficiency and productivity of three inputs: material, capital and labour, as well as the total factor efficiency and productivity of the acquired companies in the short and long term after the acquisitions.FindingsThe research results suggest that efficiency of material, efficiency of labour and the total factor efficiency of the acquired companies are higher after the acquisitions than before, while efficiency of capital is lower. In addition, the results show that the acquisitions had a positive impact on total factor productivity of the acquired companies.Practical implicationsThe results of this study have practical implications for managers, especially for policy-makers and industry analysts in deciding whether to encourage or discourage cross-border acquisitions in transitional economies.Originality/valueThe study contributes to a better understanding of the impact of cross-border acquisitions on efficiency and productivity of acquired companies in the manufacturing industry. Research in transitional economies related to subject matter is limited, and this study is the first empirical investigation of the effect of cross-border acquisitions on the efficiency and productivity in the cement industry in Serbia by applying the Data Envelopment Analysis.

Measuring the operational and financial efficiency using a Malmquist data envelopment analysis: a case of Egyptian hospitals

2020 ◽  
Vol 27 (9) ◽  
pp. 2521-2536
Author(s):  
Ahmed Mohamed Habib ◽  
Tamer Mohamed Shahwan
Keyword(s):  
Data Envelopment Analysis ◽  
The United States ◽  
Decision Makers ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Mena Region ◽  
Financial Efficiency ◽  
Content Type ◽  
Factors Affecting ◽  
Dea Approach

PurposeThe efficient use of organizational resources is integral to the existence of prime firms. This study, using Malmquist data envelopment analysis (DEA), aims to assess in the level of operational and financial efficiency and its determinants for ensuring and sustaining excellent performance in 33 Egyptian private hospitals.Design/methodology/approachThis study adopted a Malmquist DEA approach to assess the changes in operational and financial efficiency in Egyptian hospitals. Tobit regression was also used to identify the significant variables affecting their efficiency. In addition, a sensitivity analysis is carried out for model validations.FindingsOut of 33 hospitals, 17 were found inefficient due to the decline in their technical efficiency. Moreover, the total value of the software programs and operational expenses and the total number of employees are common factors affecting both operational and financial efficiency. In addition, the number of physicians significantly affects the hospital's financial efficiency.Practical implicationsThe study sheds light on the value of using DEA to assess efficiency. DEA in the context of emerging economy such as Egypt's can be a useful tool for decision-makers and practitioners in identifying and addressing performance weaknesses and thus supports continuous improvement in performance.Originality/valueSeveral studies have adopted the DEA approach to assess the overall efficiency of hospitals in Europe and the United States. However, in the MENA region, these studies are uncommon. This study is thought to be one of the earliest attempts to assess hospitals' efficiency in Egypt.

Eco-innovation analysis of OECD countries with common weight analysis in data envelopment analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reza Kiani Mavi ◽  
Neda Kiani Mavi ◽  
Reza Farzipoor Saen ◽  
Mark Goh
Keyword(s):  
Sustainable Development ◽  
Data Envelopment Analysis ◽  
Oecd Countries ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Environmental Research ◽  
Data Envelopment ◽  
Discrimination Power ◽  
Content Type ◽  
Dea Models

PurposeDespite unanimity in the literature that eco-innovation (EI) leads to sustainable development, evidence remains limited on measuring EI efficiency with the Malmquist productivity index (MPI). In conventional data envelopment analysis (DEA) models, decision-making units (DMUs) are inclined to assign more favorable weights, even zero, to the inputs and outputs to maximize their own efficiency. This paper aims to overcome this shortcoming by developing a common set of weights (CSW). Design/methodology/approachUsing goal programming, this study develops a CSW model to evaluate the EI efficiency of the organization for economic co-operation and development (OECD) countries and track their changes with MPI during 2010–2018. FindingsAchieving a complete ranking of DMUs, findings show the higher discrimination power of the proposed CSW compared with the original DEA models. Furthermore, results reveal that Iceland, Latvia and Luxembourg are the only OECD countries that have incessantly improved their EI productivity (MPI > 1) from 2010 to 2018. On the other hand, Japan is the OECD country that has experienced the highest yearly EI efficiency during 2010–2018. This paper also found that Iceland has the highest MPI over 2010–2018. Practical implicationsMore investment in environmental research and development (R&D) projects instead of generic R&D enables OECD members to realize more opportunities for sustainable development through minimizing energy use and environmental pollution in any form of waste and greenhouse gas emissions. Originality/valueIn addition to developing a novel common weights model for DEA-MPI to measure and evaluate the EI of OECD countries, this paper develops a CSW model by including the undesirable outputs for EI analysis.

Data envelopment analysis of efficiency of real estate investment trusts in Singapore

2017 ◽  
Vol 59 (6) ◽  
pp. 826-838 ◽  
Author(s):  
Aminath Amany Ahmed ◽  
Azhar Mohamad
Keyword(s):  
Data Envelopment Analysis ◽  
Real Estate ◽  
Productivity Growth ◽  
Real Estate Investment Trusts ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Real Estate Investment ◽  
Content Type ◽  
Investment Trusts

Purpose In this study, the authors use data envelopment analysis to assess the technical efficiency and performance of real estate investment trusts (REITs) in Singapore, for the years 2009 through 2013. Design/methodology/approach The authors apply the Malmquist Productivity Index to express the productivity change of the REITs over time. Findings The authors find that while most REITs have experienced efficiency improvements, there has been little productivity growth at the frontier during the study period. Originality/value The finding indicates that it is possible to improve the performance of the REITs by further improving technological efficiency because technological regress has been the main reason for the poor productivity growth of the REITs in Singapore.

Are the best African banks really the best? A Malmquist data envelopment analysis

2016 ◽  
Vol 24 (4) ◽  
pp. 588-610 ◽  
Author(s):  
Tesfatsion Sahlu Desta
Keyword(s):  
South Africa ◽  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Commercial Banks ◽  
Productivity Index ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Global Finance ◽  
Content Type ◽  
Efficiency And Productivity

Purpose This paper aims to examine whether the African commercial banks selected as the best African banks by Global Finance Magazine really are the best. Design/methodology/approach Panel data envelopment analysis (DEA) was used, as well as the Malmquist total factor productivity index, to distinguish productive banks from unproductive banks. Nineteen commercial banks were selected from the 30 best African banks as identified by the Global Finance Magazine. Findings Of the 19 banks, five were found to be unproductive. Bank productivity was attributed mainly to technological change, and different methods marked different results, for example, the regional winner bank (Standard Bank of South Africa) selected by Global Finance Magazine ranked ninth in this study, whereas the Bank Windhoek Limited, Namibia, ranked first. Practical implications The study confirms the applicability of DEA for the banking industry. The model shows variability among the banks’ efficiency and productivity and provides different results to the Global Finance Magazine’s best bank selection. For example, the Standard Bank of South Africa, which is selected as the regional winner, is now ranked ninth under the DEA Malmquist’s total factor productivity. Originality/value The study shows that the DEA model can be applied not only for analysing the firm’s efficiency but also for objective rating, ranking and selecting best banks.

scholarly journals Comparing the productivity of major shipyards in China, South Korea, and Japan – an application of a metafrontier framework

2020 ◽  
Vol 5 (2) ◽  
pp. 193-210
Author(s):  
Shih-Liang Chao ◽  
Yi-Hung Yeh
Keyword(s):  
Data Envelopment Analysis ◽  
South Korea ◽  
Design Methodology ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Shipbuilding Industry ◽  
Content Type ◽  
Substantial Progress

Purpose This study aims to measure the productivity of 21 major shipyards in China, South Korea and Japan. Design/methodology/approach Data envelopment analysis was applied to measure the productivity of shipyards. The contemporaneous and intertemporal productivity scores of each shipyard were measured. Additionally, the technical gaps among shipyards in China, South Korea and Japan were measured and compared. Findings The results indicate that Japan led the global shipbuilding industry in 2014 and South Korea dominated in 2015. Additionally, from 2014 to 2015, shipyards in South Korea and Japan maintained their levels of productivity. Comparatively, major shipyards in China made substantial progress from 2014 to 2015, revealing their strong ambition to improve productivity. Originality/value This study first used a metafrontier framework to measure the technical gap of shipyards among major shipbuilding countries. The model and approach objectively analyze the productivity of major shipyards and considers their nationalities. Additionally, this study is the first to measure changes in the productivity of shipyards. By decomposing the metafrontier Malmquist productivity index, major shipyards were categorized into eight sets. The results of this study can provide a clear direction for shipyards to improve their productivity.

scholarly journals Measuring the Productivity of Energy Consumption of Major Industries in China: A DEA-Based Method

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Xishuang Han ◽  
Xiaolong Xue ◽  
Jiaoju Ge ◽  
Hengqin Wu ◽  
Chang Su
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Policy Makers ◽  
Time Periods ◽  
Decision Making Units

Data envelopment analysis can be applied to measure the productivity of multiple input and output decision-making units. In addition, the data envelopment analysis-based Malmquist productivity index can be used as a tool for measuring the productivity change during different time periods. In this paper, we use an input-oriented model to measure the energy consumption productivity change from 1999 to 2008 of fourteen industry sectors in China as decision-making units. The results show that there are only four sectors that experienced effective energy consumption throughout the whole reference period. It also shows that these sectors always lie on the efficiency frontier of energy consumption as benchmarks. The other ten sectors experienced inefficiency in some two-year time periods and the productivity changes were not steady. The data envelopment analysis-based Malmquist productivity index provides a good way to measure the energy consumption and can give China's policy makers the information to promote their strategy of sustainable development.

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