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 Measuring the Efficiency of Football Clubs Using Data Envelopment Analysis: Empirical Evidence From Spanish Professional Football

SAGE Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 215824402198925
Author(s):  
Isidoro Guzmán-Raja ◽  
Manuela Guzmán-Raja
Keyword(s):  
Data Envelopment Analysis ◽  
High Efficiency ◽  
Sport Performance ◽  
Data Envelopment ◽  
Professional Football ◽  
Efficiency Measure ◽  
Factors Affecting ◽  
Football Clubs ◽  
Main Factors ◽  
Using Data

Professional football clubs have a special characteristic not shared by other types of companies: their sport performance (on the field) is important, in addition to their financial performance (off the field). The aim of this paper is to calculate an efficiency measure using a model that combines performance (sport and economic) based on data envelopment analysis (DEA). The main factors affecting teams’ efficiency levels are investigated using cluster analysis. For a sample of Spanish football clubs, the findings indicate that clubs achieved a relatively high efficiency level for the period studied, and that the oldest teams with the most assets had the highest efficiency scores. These results could help club managers to improve the performance of their teams.

scholarly journals Evaluation of Car Performances Using Data Envelopment Analysis

2018 ◽  
Vol 22 ◽  
pp. 01051
Author(s):  
Yunus GÜRAL ◽  
Ayşe Turan BUĞATEKİN
Keyword(s):  
Data Envelopment Analysis ◽  
Maximum Speed ◽  
Data Envelopment ◽  
Automotive Sector ◽  
Nonparametric Method ◽  
Maximum Torque ◽  
Acceleration Time ◽  
Input Variables ◽  
Using Data ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a nonparametric method used to examine the relative efficiencies of Decision Making Units (DMUs) on conditions where there are multiple inputs and multiple outputs. As in all sectors, it is very important for the automotive sector to operate effectively. Therefore, it is also important to measure the efficiency and find the source of the inefficiency. In this study, the performances of the DMU of the automobiles will examine using Data Envelopment Analysis. In this direction, it is aimed to assist consumers in purchasing by calculating the relative efficiencies of automobile models, determining effective and ineffective DMUs according to the wishes of the consumers. Sales price and fuel consumption are determined as input variables; maximum speed, cylinder volume, horsepower, maximum torque, luggage volume, acceleration time from 0 to 100 km are determined as output variables.

scholarly journals Supporting Better Decision-Making: A Combined Grey Model and Data Envelopment Analysis for Efficiency Evaluation in E-Commerce Marketplaces

2020 ◽  
Vol 12 (24) ◽  
pp. 10385
Author(s):  
Chia-Nan Wang ◽  
Thanh-Tuan Dang ◽  
Ngoc-Ai-Thy Nguyen ◽  
Thi-Thu-Hong Le
Keyword(s):  
Data Envelopment Analysis ◽  
Business Performance ◽  
Technology Development ◽  
Technological Development ◽  
Hybrid Approach ◽  
Efficiency Score ◽  
Grey Model ◽  
Modern World ◽  
Data Envelopment ◽  
Input Variables

E-commerce has become an integral part of businesses for decades in the modern world, and this has been exceptionally speeded up during the coronavirus era. To help businesses understand their current and future performance, which can help them survive and thrive in the world of e-commerce, this paper proposes a hybrid approach that conducts performance prediction and evaluation of the e-commerce industry by combining the Grey model, i.e., GM (1, 1) and data envelopment analysis, i.e., the Malmquist-I-C model. For each e-commerce company, GM (1, 1) is applied to predict future values for the period 2020–2022 and Malmquist-I-C is applied to calculate the efficiency score based on output variables such as revenue and gross profit and input variables such as assets, liabilities, and equity. The top 10 e-commerce companies in the US market are used to demonstrate model effectiveness. For the entire research period of 2016–2022, the most productive e-commerce marketplace on average was eBay, followed by Best Buy and Lowe’s; meanwhile, Groupon was the worst-performing e-commerce business during the studied period. Moreover, as most e-commerce companies have progressed in technological development, the results show that the determinants for productivity growth are the technical efficiency change indexes. That means, although focusing on technology development is the key to e-commerce success, companies should make better efforts to maximize their resources such as labor, material and equipment supplies, and capital. This paper offers decision-makers significant material for evaluating and improving their business performance.

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.

scholarly journals EFFICIENT COMPARISON OF THE TOP 10 LARGEST COMMERCIAL BANKS IN INDONESIA: DEA (DATA ENVELOPMENT ANALYSIS)

2021 ◽  
Vol 11 (3) ◽  
pp. 427
Author(s):  
Ari Christianti
Keyword(s):  
Data Envelopment Analysis ◽  
Commercial Banks ◽  
Banking Industry ◽  
Maximum Efficiency ◽  
Data Envelopment ◽  
Labor Costs ◽  
Banking Efficiency ◽  
Parametric Data ◽  
Fixed Assets ◽  
Using Data

Banking efficiency is very important in supporting the success of macro policies specifically, maintaining the sustainability of development that affects economic growth and social welfare. This study discusses the efficiency of commercial banks for the 2015-2019 period using data from the 10 largest commercial banks in Indonesia. The methodology used is non-parametric, Data Envelopment Analysis, to analyze technical efficiency. The results showed that 7 banks had a maximum efficiency level consistently during the study period and there were still 3 banks that did not reach the maximum efficiency but during certain periods or periods. Based on the results of the DEA, inefficient banks in a certain period can achieve maximum efficiency by reducing inputs such as labor costs, net fixed assets, and the number of deposits. This might be attributed that the competition in the banking industry and because not all inputs could be controlled by management, some large banks cannot maintain their level of efficiency consistently.

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 Measuring Tourism Efficiency of European Countries by Using Data Envelopment Analysis

2017 ◽  
Vol 13 (10) ◽  
pp. 31 ◽  
Author(s):  
Halenur Soysal-Kurt
Keyword(s):  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Returns To Scale ◽  
Tourism Industry ◽  
European Countries ◽  
Data Envelopment ◽  
Micro Level ◽  
Input Variables ◽  
Using Data ◽  
Constant Returns To Scale

This study aims to measure relative efficiency of 29 European countries with the data of the year 2013 using input-oriented and constant returns to scale Data Envelopment Analysis and to offer improvement suggestions for the countries found inefficient based on their measured relative efficiency scores. Three input and three output variables are used to assess relative performances of the countries. In this study, tourism expenses, number of employees and number of beds are used as input variables; tourism receipts, tourist arrivals and number of nights spent are used as output variables. As the result of the analysis, 16 countries are found relatively efficient and 13 countries are found relatively inefficient. This study is one of the few publications within the scope of European countries based on data envelopment analysis. Unlike most researches evaluating the efficiency of tourism establishments at the micro level, this paper is thought to contribute to the related literature as it evaluates relative efficiency of the countries at the macro level for tourism industry. Considering the variables used in the analysis, it is expected to give ideas to relatively inefficient European countries on efficiency improvement.

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 Analysis of Sharia Banking Efficiency in Industry Revolution 4.0 Era

2020 ◽  
Vol 4 (4) ◽  
pp. 536
Author(s):  
Reny Fitriana Kaban ◽  
Novita Setyawati
Keyword(s):  
Financial Services ◽  
High Efficiency ◽  
Annual Report ◽  
Labor Cost ◽  
Third Party ◽  
Data Envelopment ◽  
Banking Efficiency ◽  
Operating Income ◽  
Use Of Technology ◽  
Input Variables

This research aimed to analyze the efficiency of Sharia Banking in Indonesia for the period of 2013-201, the era of industry revolution 4.0. The research method used Data Envelopment Analysis while the data was taken from the annual report of Sharia Banking Statistic issued by Indonesia Financial Services Authority for the intended years. The input variables were the third-party fund, labor cost, and other cost while the output variables were total financings and operating income. Both with CRS and VRS model input approach, Sharia Banking in Indonesia generally already had high-efficiency value either based on years or banks. The banks who had not been in high-efficiency criteria were highly recommended learning from the benchmark banks. The result showed in general the use of technology and the internet by Sharia Banking was already appropriate, which caused their operations running efficiently.

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