scholarly journals Measuring Firm and Sector Efficiency in Pakistan: An Application of Data Envelopment Analysis

2019 ◽  
Vol 14 (3) ◽  
pp. 239-257
Author(s):  
Touqeer Saher ◽  
Muhammad Asad Saleem Malik ◽  
Saif Ullah ◽  
Atta Ullah
Keyword(s):  
Data Envelopment Analysis ◽  
Positive Impact ◽  
Efficiency Score ◽  
Brand Value ◽  
Data Envelopment ◽  
Probit Regression ◽  
Firm Efficiency ◽  
Listed Firms ◽  
Dea Analysis ◽  
Using Data

AbstractThis study aims to determine the firm and sector efficiency using data envelopment analysis for 121 listed firms, 3 from 2004 to 2016. Based on the efficiency score of 1 and 0, DEA analysis results indicate that 10% firm was highly efficient in the whole sample, 80% are semi-efficient in selected sectors and 10% slightly inefficient. Thus, we can conclude that all firms are not equally efficient. Also, the study used a Logit/ Probit Regression model, and results indicate that the brand value and type of sector has a positive impact on firm efficiency. The study concludes that Brand value increases firm efficiency, so managers should put more focus on building firm brand value.

scholarly journals Performance Assessment Based on the Relative Efficiency of Indian Opencast Coal Mines Using Data Envelopment Analysis and Malmquist Productivity Index

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4902
Author(s):  
Biswaranjita Mahapatra ◽  
Chandan Bhar ◽  
Sandeep Mondal
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Primary Source ◽  
Efficiency Score ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Significant Difference ◽  
Using Data

Coal is the primary source of energy in India. Despite being the second-largest coal-producingcountry, there exists a significant difference in demand and production in India. In this study, the relativeefficiency of twenty-eight selected opencast mines from a large public sector undertaking coal companyin India for 2018–2019 was assessed and ranked by using data envelopment analysis (DEA). This studyused input-oriented DEA with efficiency decomposition to pure technical efficiency, technical efficiency,and scale efficiency. The result showed that 25% and 36% of mines were efficient in technical efficiencyand pure technical efficiency, respectively, whereas the eight mines scale efficiency was inefficient witha decreasing return to scale. Further, in this study, theMalmquist Productivity Index (MPI)was employedto measure the efficiency of the selected mines for three consecutive years (2016–2017 to 2018–2019).The result shows that in only three mines the efficiency is continuously improving from 2016–2017 to2018–2019, whereas in more than 20% of mines the efficiency score is decreasing. Comparing theMPIefficiency and productivity assessment throughout the years, changes in innovation and technology areincreasing from 2017–2018 to 2018–2019. Finally, the study concluded with a comprehensive evaluationof each variable with mines performance. The author formulated the strategies, which in turn help coalprofessionals to improve the efficiency of the mine.

Fuzzy C-means based data envelopment analysis for mitigating the impact of units’ heterogeneity

Kybernetes ◽  
2016 ◽  
Vol 45 (3) ◽  
pp. 536-551 ◽  
Author(s):  
Seyed Hossein Razavi Hajiagha ◽  
Shide Sadat Hashemi ◽  
Hannan Amoozad Mahdiraji
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Negative Impact ◽  
Positive Impact ◽  
Efficiency Score ◽  
Data Envelopment ◽  
Content Type ◽  
Fuzzy C Means ◽  
The Impact ◽  
Decision Making Units

Purpose – Data envelopment analysis (DEA) is a non-parametric model that is developed for evaluating the relative efficiency of a set of homogeneous decision-making units that each unit transforms multiple inputs into multiple outputs. However, usually the decision-making units are not completely similar. The purpose of this paper is to propose an algorithm for DEA applications when considered DMUs are non-homogeneous. Design/methodology/approach – To reach this aim, an algorithm is designed to mitigate the impact of heterogeneity on efficiency evaluation. Using fuzzy C-means algorithm, a fuzzy clustering is obtained for DMUs based on their inputs and outputs. Then, the fuzzy C-means based DEA approach is used for finding the efficiency of DMUs in different clusters. Finally, the different efficiencies of each DMU are aggregated based on the membership values of DMUs in clusters. Findings – Heterogeneity causes some positive impact on some DMUs while it has negative impact on other ones. The proposed method mitigates this undesirable impact and a different distribution of efficiency score is obtained that neglects this unintended impacts. Research limitations/implications – The proposed method can be applied in DEA applications with a large number of DMUs in different situations, where some of them enjoyed the good environmental conditions, while others suffered from bad conditions. Therefore, a better assessment of real performance can be obtained. Originality/value – The paper proposed a hybrid algorithm combination of fuzzy C-means clustering method with classic DEA models for the first time.

Measuring operational efficiency of isolation hospitals during COVID-19 pandemic using data envelopment analysis: a case of Egypt

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahmoud Abdelrahman Kamel ◽  
Mohamed El-Sayed Mousa
Keyword(s):  
Data Envelopment Analysis ◽  
Design Methodology ◽  
Operational Efficiency ◽  
Data Envelopment ◽  
Allocation Of Resources ◽  
Tobit Regression ◽  
Health Crisis ◽  
Content Type ◽  
Dea Analysis ◽  
Using Data

PurposeThis study used Data Envelopment Analysis (DEA) to measure and evaluate the operational efficiency of 26 isolation hospitals in Egypt during the COVID-19 pandemic, as well as identifying the most important inputs affecting their efficiency.Design/methodology/approachTo measure the operational efficiency of isolation hospitals, this paper combined three interrelated methodologies including DEA, sensitivity analysis and Tobit regression, as well as three inputs (number of physicians, number of nurses and number of beds) and three outputs (number of infections, number of recoveries and number of deaths). Available data were analyzed through R v.4.0.1 software to achieve the study purpose.FindingsBased on DEA analysis, out of 26 isolation hospitals, only 4 were found efficient according to CCR model and 12 out of 26 hospitals achieved efficiency under the BCC model, Tobit regression results confirmed that the number of nurses and the number of beds are common factors impacted the operational efficiency of isolation hospitals, while the number of physicians had no significant effect on efficiency.Research limitations/implicationsThe limits of this study related to measuring the operational efficiency of isolation hospitals in Egypt considering the available data for the period from February to August 2020. DEA analysis can also be an important benchmarking tool for measuring the operational efficiency of isolation hospitals, for identifying their ability to utilize and allocate their resources in an optimal manner (Demand vs Capacity Dilemma), which in turn, encountering this pandemic and protect citizens' health.Originality/valueDespite the intensity of studies that dealt with measuring hospital efficiency, this study to the best of our knowledge is one of the first attempts to measure the efficiency of hospitals in Egypt in times of health' crisis, especially, during the COVID-19 pandemic, to identify the best allocation of resources to achieve the highest level of efficiency during this pandemic.

scholarly journals Performance of Malaysian Insurance Companies Using Data Envelopment Analysis

2018 ◽  
Vol 11 (3) ◽  
pp. 1147 ◽  
Author(s):  
Ng Jia Bao ◽  
Rohaizan Ramlan ◽  
Fazeeda Mohamad ◽  
Azlina Md Yassin
Keyword(s):  
Data Envelopment Analysis ◽  
Insurance Industry ◽  
Secondary Data ◽  
Efficiency Score ◽  
Equity Capital ◽  
Insurance Companies ◽  
Data Envelopment ◽  
Insurance Company ◽  
Policy Makers ◽  
Using Data

The purpose of this study is to evaluate the performance of the local insurance in Malaysia for the period 2014-2015. The major challenge in the insurance industry is increasing competition in this market. Besides that, problematic in performance measurement to evaluate performance is another challenge in insurance industry. 24 local insurance companies involved in this study using quantitative method of Data Envelopment Analysis (DEA) output-orientation CCR model. This study utilizes three inputs and three outputs; operating expenses, equity capital and commission as well as net premium, net investment income, and net incurred claim. The secondary data sources were derived from official data of local insurance companies’ annual report respectively. The DEA-Solver-LV version 8 tools were used to analyze the data that have been collected to evaluate the performance of local insurance company. This DEA model allows integration of the performance for the insurance companies and provides management overall performance evaluation. The results showed that there are 8 efficient companies in 2014 and 9 efficient companies in 2015. The average efficiency score in 2014 was increased from 78.9% to 79.1% in 2015. The findings from this study will benefit the insurance associations in Malaysia, management of insurances companies and policy makers.

scholarly journals Selection and Analysis of Input-Output Variables using Data Envelopment Analysis of Decision Making Units - Indian Private Sector Banks

2021 ◽  
Vol 10 (5) ◽  
pp. 119-127
Author(s):  
B. Vittal ◽  
Raju Nellutla ◽  
M. Krishna Reddy
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Banking System ◽  
Efficiency Score ◽  
Data Envelopment ◽  
Input Output ◽  
Key Factor ◽  
And Performance ◽  
Using Data ◽  
Decision Making Units

In banking system the evaluation of productivity and performance is the key factor among the fundamental concepts in management. For identify the potential performance of a bank efficiency is the parameter to evaluate effective banking system. To measure the efficiency of a bank selection of appropriate input-output variables is one of the most vital issues. The suitable identification of input-output variables helps to create and identify model in order to evaluate the efficiency and analysis. The Data Envelopment Analysis (DEA) is a mathematical approach used to measure the efficiency of identified Decision Making Units (DMUs). The DEA is a methodology for evaluating the relative efficiency of peer decision making units of identified input/output variables for the financial year 2018-19. In this study the basic DEA CCR, BCC models used for measure the efficiency of DMUs. In addition to these models for minimize the input excess and output shortfall Slack Based Measure (SBM) efficiency used. The SBM is a scalar measure which directly deals with slacks of input, output variables which help in obtain improved efficiency score compare with previous model. The result from the analysis is

scholarly journals A COMPARATIVE STUDY OF BANKING EFFICIENCY IN ASEAN-5: THE DATA ENVELOPMENT ANALYSIS (DEA) APPROACH

2018 ◽  
Vol 33 (2) ◽  
pp. 168
Author(s):  
Setyo Tri Wahyudi ◽  
Azizah Azizah
Keyword(s):  
Data Envelopment Analysis ◽  
High Efficiency ◽  
Efficiency Score ◽  
The Philippines ◽  
Data Envelopment ◽  
Banking Efficiency ◽  
Output Efficiency ◽  
Input Variables ◽  
Using Data ◽  
Second Period

As an intermediary institution, a bank is required to operate efficiently due to the increased competition among banks, both domestic and international. However, not all banks are able to optimize their owned resources to reach a certain efficiency level. Thus, efficiency plays an important role in this era of more globalized banking competiti on. The objective of this study is to calculate the banking efficiency score for the ASEAN-5 countries, consisting of Indonesia, Malaysia, the Philippines, Singapore, and Thailand. Using Data Envelopment Analysis (DEA), the input variables comprised of employees’ benefits, fixed assets, and deposits; while the output variables were total income and loans. The results show the relatively high efficiency levels of every bank in each country. The achievement of an input-output efficiency variable in the first period (2006-2009) tended to increase, but the second period (2010-2013) showed a declining trend. The performance of the banks in Singapore during the first period was very good, while in the second period, the banks in the Philippines showed a respectable performance.

scholarly journals Penggunaan Data Envelopment Analysis (DEA) dalam Pengukuran Efisiensi Bank Umum Syari'ah di Indonesia

2018 ◽  
Vol 5 (2) ◽  
pp. 293
Author(s):  
Anita Puspitasari ◽  
Didit Purnomo ◽  
Triyono Triyono
Keyword(s):  
Data Envelopment Analysis ◽  
Commercial Bank ◽  
Secondary Data ◽  
Efficiency Score ◽  
Financial Statement ◽  
Data Envelopment ◽  
Output Variable ◽  
Period Data ◽  
The Difference ◽  
Using Data

The purpose of the research is to analayze efficiency level of Sharia Commercial Bank in Indonesia (Bank Mega Syariah, Bank Muamalat Indonesia, Bank Panin Dubai Syariah, Bank BNI Syariah, Bank BRI Syariah, and Bank Syariah Mandiri) 2014-2015 period. Data used in this research is secondary data taken from Financial Statement Publication issued by Otoritas Jasa Keuangan (OJK). This research uses input-output variable with Data Envelopment Analysis (DEA) Method.The result shows the difference of efficiency score for each Sharia Commercial Bank. Based on the calculacy using Data Envelopment Analysis (DEA) Method on BUSN Foreign Exchange of Sharia Commercial Bank in Indonesia only Bank Panin Dubai Syariah that has been succeeded with 100 percent of continuously efficiency during the research. The highest efficiency is experienced by Bank BNI Syariah and BRI Syariah because during the research they experienced inefficiency. During the research Bank Mega Syariah experienced efficiency three times on quarter March 2014, March 2015, and June 2015. Bank Muamalat Indonesia only experienced efficiency twice on quarter March 2014 and March 2015, beside that Bank Muamalat Indonesia experienced inefficiency. Bank Syariah Mandiri experienced efficiency twice on quarter March 2015 and quarter December 2015.

scholarly journals Competitive Environment Analysis in Global Retail Companies Operation Strategy: A Data Envelopment Analysis (DEA) Based Approach

2020 ◽  
Vol 5 (1) ◽  
pp. 16
Author(s):  
Zainal Putra ◽  
Muzakir Muzakir
Keyword(s):  
Data Envelopment Analysis ◽  
Efficiency Score ◽  
Global Market ◽  
Data Envelopment ◽  
Operation Strategy ◽  
Environment Analysis ◽  
Return On Equity ◽  
Asset Turnover ◽  
Using Data ◽  
Retail Company

<em>This research aims to  find out the most competitive retail company operating in current global market based on the perspective of efficiency. A well-performed company is the company that is efficient in its operations. By using Data Envelopment Analysis (DEA) approach, this research differs from prior research because we used multivariable inputs, namely: asset, operational expense and the number of employees. The output variables used in this research are: total revenue, net profit, return on equity (ROE), return on assets (ROA), return on investment (ROI), dividend yield ratio and asset turnover ratio. The analysis results shows that six retail companies are “efficient” in its operation (efficiency score of 1.00), namely: Carrefour, Costco, Kroger Company, Home Depot Inc, JD.com Inc Adr and Alibaba Group Holdings Ltd ADR. Therefore, these companies are considered the most competitive in its operation strategy in the current global market, whereas there are four retail companies falls into category of “inefficient” (efficiency score &lt; 1.00), namely: Walmart, Amazon.com Inc, Tesco PLC and Walgreens Boots Alliance Inc.</em>

scholarly journals Evaluation of the efficiency of logistics activities using Data Envelopment Analysis (DEA)

2020 ◽  
Vol 27 (1) ◽  
Author(s):  
Alessandro Lepchak ◽  
Simone Bernardes Voese
Keyword(s):  
Data Envelopment Analysis ◽  
Efficiency Score ◽  
Air Transport ◽  
Maximum Efficiency ◽  
Data Envelopment ◽  
Analysis Model ◽  
Lower Efficiency ◽  
Cargo Handling ◽  
Multimodal Analysis ◽  
Using Data

Abstract This study aimed to analyze the efficiency of activities related to logistics modes, transport and cargo handling in Brazil. The theoretical framework was composed of the logistics efficiency and of the discussion of the characteristics of modes of transport and of variables related to efficiency. The study was classified as descriptive and quantitative, using the technique of data envelopment analysis. As main results, the ancillary activities to air transport stand out as efficient, which reached scores of 100% in the analyzed periods, except in 2010, in which they obtained 91.58%. It is worth noting that the activities cabotage and long-haul and ancillary activities to land transport achieved three maximum efficiency scores. In addition to evaluating the benchmark for the activities of lower efficiency score, the study also included improvements needed for other activities to achieve maximum efficiency. Finally, the central contribution of the article lies in the proposition of a multimodal analysis model.

Municipal Efficiency and Economies of Scale in Bosnia and Herzegovina

2018 ◽  
Vol 16 (4) ◽  
pp. 715-734 ◽  
Author(s):  
Aida Soko ◽  
Jelena Zorič
Keyword(s):  
Data Envelopment Analysis ◽  
Bosnia And Herzegovina ◽  
Economic Efficiency ◽  
Economies Of Scale ◽  
Positive Impact ◽  
Returns To Scale ◽  
Efficiency Score ◽  
Full Scale ◽  
Scale Efficiency ◽  
Data Envelopment

This study estimates municipal efficiency and economies of scale of municipalities in Bosnia and Herzegovina by employing data envelopment analysis (DEA) with variable (VRS) and constant (CRS) returns to scale. The results indicate low overall municipal efficiency, with economies of scale reached in very few municipalities. The average municipal efficiency score is 0.7115 under DEA VRS assumption, where only 16% of municipalities are found efficient. The average scale efficiency is 0.7458 with full scale efficiency reached by only 11% of municipalities in Bosnia and Herzegovina. Furthermore, the analysis shows strong positive impact of number of inhabitants on overall municipal efficiency. Politically motivated fragmentation of municipalities, aiming to bring peace and stability to the country, did not go hand in hand with improved economic efficiency.

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