scholarly journals Applying DEA in Analysing the Efficiency of Top Manufacturing Companies in Pakistan

2011 ◽  
Vol 1 (2) ◽  
pp. 225
Author(s):  
Izah Mohd Tahir ◽  
Mehran Ali Memon
Keyword(s):  
Technical Efficiency ◽  
Returns To Scale ◽  
International Markets ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Manufacturing Companies ◽  
Critical Elements ◽  
Input Variables ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

The efficiency of manufacturing companies is one of the critical elements for its competitiveness in the domestic as well as international markets. Previous research on efficiency measurement usually adopts Data Envelopment Analysis (DEA) approach. Therefore this paper is aimed to analyse the efficiency of 14 top manufacturing companies in Pakistan for a five year period from 2006 to 2010. Data of top 14 manufacturing companies are gathered from OSIRIS database. DEA method is applied using both the Constant Returns to Scale (CCR) and Variable Returns to Scale (BCC) models to find the overall efficiency, technical efficiency and scale efficiency. In this paper we use two input variables (total expenses and total assets) and two output variables (sales and profit before tax). The results under CCR method show that only one company is considered technically efficient while the average overall technical efficiency varies from 0.64 to 0.99. Company number 5 (NRL) demonstrates the best performance for all years under study.

scholarly journals Application of Window Malmquist Index for Examination of Efficiency Change of Czech Commercial Banks

2017 ◽  
Vol 8 (3) ◽  
pp. 173-190
Author(s):  
Iveta Palecková
Keyword(s):  
Commercial Banks ◽  
Returns To Scale ◽  
Malmquist Index ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Efficiency Change ◽  
Average Efficiency ◽  
Index Approach ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

Abstract The aim of the paper is to apply the Window Malmquist index approach to examine the efficiency change of Czech commercial banks within the period 2004-2013. We used the Data Envelopment Analysis and theWindow Malmquist index approaches to estimate the efficiency change of Czech commercial banks. The average efficiency computed under the assumption of constant returns to scale was 73% and under the assumption of variable returns to scale the value was 83%. We estimated the average positive efficiency growth of Czech commercial banks during the period 2004-2013. We found that average scale efficiency was 88%, which means that Czech commercial banks were of an inappropriate size, especially the largest banks.

Measuring the financial efficiencies and performances of Turkish funds

2010 ◽  
Vol 60 (3) ◽  
pp. 295-320 ◽  
Author(s):  
F. Gökgöz
Keyword(s):  
Mutual Funds ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Portfolio Performance ◽  
Data Envelopment ◽  
Performance Indices ◽  
Programming Technique ◽  
Dea Models ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

Measuring the financial efficiencies of mutual funds in emerging markets has played an important role in finance literature. Charnes et al. (1978) advocated Data Envelopment Analysis (DEA), a valuable mathematical programming technique, which is used to measure the technical, pure and scale efficiencies of decision making units. The general form of DEA is the CCR model that depends on the assumption of constant returns to scale. Subsequently, Banker et al. (1984) developed an alternative DEA model which includes a variable returns to scale approach. The aim of this study is to measure and compare the financial efficiencies of Turkish securities and pension funds in the 2006–2007 period. In this respect, 36 securities mutual funds (SMFs) and 41 pension mutual funds (PMFs) have been evaluated comparatively according to classical portfolio performance measures and DEA models. Results from performance indices and DEA models reveal that PMFs have higher portfolio performances and financial efficiencies than SMFs in the 2006–2007 period. However, SMFs and PMFs have shown considerable increases in efficiency in the 2006–2007 period according to CCR and BCC models. Of the 77 funds studied, 23 funds in 2007 and 20 funds in 2006 demonstrated scale efficiency. Furthermore, the input ratios should be considerably improved for 2006 and 2007. But, mostly the output values of the funds were found to have remained unchanged in the case of PMFs and SMFs in 2007. The output ratios for 2006 should be considerably improved, especially in the case of SMFs. Finally, the DEA method is evaluated as a substantial quantitative tool for investors in analysing the financial efficiencies of funds in the capital markets.

scholarly journals DATA ENVELOPMENT ANALYSIS (DEA) APPROACH FOR ASSESSING TECHNICAL, ECONOMIC AND SCALE EFFICIENCY OF BROILER FARMS

2021 ◽  
Vol 52 (2) ◽  
pp. 291-300
Author(s):  
Fardos A.M. Hassan
Keyword(s):  
Returns To Scale ◽  
Sampling Technique ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Policy Makers ◽  
Education Experience ◽  
Level Of Training ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

This study was surveyed and evaluated technical, economic and scale efficiency of broiler farms in Egypt using DEA technique. So as to accomplish the specified aim, stratified random sampling technique was utilized to gather information from 150 broiler farms. The results showed that mean technical efficiencies of broiler farms were 0.915 and 0.985 under constant returns to scale (CRS) and variable returns to scale (VRS) respectively, implying that on average the farms could reduce input utilization by 8.5% and 1.5% for production level of output to be technically efficient. Notably, 48.7% of the farms were estimated fully technical efficient under VRS-model. The mean allocative and economic efficiency of the farms were assessed as 0.941 and 0.918 respectively, with only 2% of the farms were fully allocative and economic efficient. Furthermore, the average scale efficiency was 0.929 with the majority of broiler farms (82%) were operating with increasing returns to scale. The estimated Tobit regression showed that farmer's age, education, experience, access to extension services, and level of training were the most significant variables contributing to the disparities in efficiency of broiler farms. Such results are useful for extension workers and policy makers so as to guide policies towards expanding efficiency. 

scholarly journals Efficiency Analysis of East Asian Zinc Smelters and the Effects of Capacity and Bonus Zinc on Efficiency

2019 ◽  
Vol 5 (1) ◽  
pp. 4 ◽  
Author(s):  
Ha Park ◽  
Daecheol Kim
Keyword(s):  
Returns To Scale ◽  
Labor Cost ◽  
Efficiency Analysis ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Iron Aluminum ◽  
Tobit Regression Analysis ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

Non-ferrous metals are widely used as basic materials in various industrial fields, and zinc is a metal that is produced and used next to iron, aluminum, and copper. In this study, DEA (data envelopment analysis) was applied to measure the efficiency of 43 zinc smelters in three countries in East Asia: Korea, China, and Japan. The constant returns to scale (CRS) and the variable returns to scale (VRS) models, and the slack-based measure (SBM) were used for the analysis. As a result of the efficiency analysis, there were three efficient zinc smelters in the CRS model, 14 in the VRS model and 14 in the SBM. The average efficiency was 0.458 based on the SBM, which indicates that there is room for improvement in efficiency. In addition, the average scale efficiency value was 0.689, showing the scale to be inefficient. Therefore, it can be seen that the labor cost and the energy cost must be brought to an appropriate level. The Tobit regression analysis was used to analyze the causes of efficiency. The greater the capacity and the larger amount of bonus Zn of the refinery, the higher the efficiency of the refinery.

Data envelopment analysis of technical efficiency and productivity growth in the US Pacific Northwest sawmill industry

2008 ◽  
Vol 38 (10) ◽  
pp. 2553-2565 ◽  
Author(s):  
Ted L. Helvoigt ◽  
Darius M. Adams
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Pacific Northwest ◽  
Productivity Growth ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Efficiency Change ◽  
Constant Returns To Scale ◽  
Sawmilling Industry

This paper uses data envelopment analysis (DEA) to characterize the changing production frontier (technical efficiency, productivity growth, technical and efficiency change, and returns to scale) of the sawmilling industry in the Pacific Northwest (PNW) US using geographical panel data for the period 1968–2002. Unlike past DEA studies, we develop confidence intervals for all estimates using an improved bootstrapping method. The results indicate that the gap between the least and most efficient regions in PNW has grown and the least efficient regions are falling further behind the most efficient regions. For the Oregon regions, the null hypothesis of constant returns to scale (CRS) could not be rejected for any year. For the Washington regions, returns to scale varied year by year, although only two of the five regions showed strong tendencies away from CRS. For PNW as a whole, mean productivity growth was 0.5% per year between 1968 and 1992. Between 1992 and 2002, the regional mean was 1.3%, although with wide variation across regions. DEA results indicate that the vast majority of productivity growth in the PNW sawmilling industry between 1968 and 2002 was due to technical change. Improvements in scale efficiency played a very small role, and efficiency change was zero or negative.

Efficiency of Gulf Cooperation Council Banks

2016 ◽  
Vol 26 (1) ◽  
pp. 118-136 ◽  
Author(s):  
Peter A Aghimien ◽  
Fakarudin Kamarudin ◽  
Mohamad Hamid ◽  
Bany Noordin
Keyword(s):  
Technical Efficiency ◽  
Parametric Method ◽  
Returns To Scale ◽  
Gulf Cooperation Council ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Content Type ◽  
Use Of Resources ◽  
Potential Factors ◽  
Constant Returns To Scale

Purpose – This paper aims to investigate the efficiency level of Gulf Cooperation Council (GCC) banks on technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE). Both PTE and SE represent the potential factors that influence the efficiency of the GCC banks. In total, 43 GCC banks were observed in this study over the period from 2007 until 2011. Design/methodology/approach – The Data Envelopment Analysis, a non-parametric method using variable returns to scale under Banker, Charnes and Cooper model, was used with assets and deposit (as input) and loan and income (as output). Findings – On average, the results show that many GCC banks are operating within an optimal scale of efficiency. Nevertheless, the results also show managerial inefficiency in the use of resources. Furthermore, the results indicate that, while the larger banks (the 22 largest) tend to operate at constant returns to scale (CRS) or decreasing returns to scale, the smaller banks (the 21 smallest) are susceptible to operate at either CRS or increasing returns to scale. Research limitations/implications – Because of the chosen research method, the results may lack generalisation. Therefore, researchers are encouraged to test the propositions further. An additional implication of the results is that it was able to identify some banks that may become potential targets for outside acquisition. Practical implications – The findings should be useful to banks in the GCC in increasing their efficiencies and recognizing those with a potential for outside acquisition. Originality/value – The findings are valuable because they will facilitate the maintenance of efficient banks in the GCC. This is necessary to enable the countries to maintain a healthy and sustainable economy.

scholarly journals The Evolution of Efficiency in Costa Rican Banking System 2005-2015: Evidence from Data Envelopment Analysis

2016 ◽  
Vol 34 (2) ◽  
pp. 47-58
Author(s):  
Andrés Salas-Alvarado
Keyword(s):  
Data Envelopment Analysis ◽  
Returns To Scale ◽  
Banking System ◽  
Costa Rican ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Net Use ◽  
Private Banks ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

In this study the technical and scale efficiency of Costa Rican banking system is estimated for the 2005-2015 period, through the Data Envelopment Analysis (DEA). The estimations are within the approach of variable returns to scale with slacks developed by Banker, Charnes, and Cooper (1984) and the constant returns to scale approach developed by Charnes, Cooper, and Rhodes (1978). Efficiency scores were estimated annually for each bank to get the average for state banks, private banks, and the whole system. The inputs and outputs considered in the DEA model were defined through the intermediation approach. Through the application of DEA was concluded that a) for the whole system there are no clear efficiency improvements during the period analyzed, b) the most efficient banks were Banco BCT and Banco General, c) private banks were on average more efficient than state banks and d) the goods of net use were, on average, the input with bigger slack.

scholarly journals The cost of banking services and the technical efficiency of a South African bank

2008 ◽  
Vol 4 (2) ◽  
Author(s):  
Gert J Van der WSesthuizen ◽  
Chris Van Heerden
Keyword(s):  
South Africa ◽  
South African ◽  
Technical Efficiency ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Banking Services ◽  
Input And Output ◽  
The Cost ◽  
Variable Returns To Scale

Does the performance of one of the four largest banks in South Africa justify the customers’ complaints about the higher bank fees? Data Envelopment Analysis (DEA) was used to estimate the technical efficiency and returns to scale of one of the largest banks in South Africa. The intermediation approach was applied to classify the inputs and outputs and the analyses were conducted with both input- and output- orientation under variable returns to scale. Returns to scale efficiency and technical efficiency for 37 districts over a period of 22 months were estimated. The analyses indicated that 19 districts out of the 37 districts were never fully technically efficient during the 22 months (input- and output-orientated). It appears that customers’ complaints about high service fees are justified.

Efficiency in the Indian iron and steel industry – an application of data envelopment analysis

2014 ◽  
Vol 11 (1) ◽  
pp. 4-19 ◽  
Author(s):  
Roma Mitra Debnath ◽  
V.J. Sebastian
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Steel Industry ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Annual Income ◽  
Content Type ◽  
Steel Manufacturing ◽  
Constant Returns To Scale

Purpose – The purpose of this paper applies to Indian steel manufacturing industries to evaluate the technical and scale efficiency (SE). Design/methodology/approach – Data envelopment analysis (DEA) has been employed to calculate the relative efficiency of the steel manufacturing units. The selection criteria for the inclusion of a steel manufacturing unit in the analysis has been annual income of more than 50 crores and units manufacturing pig iron, steel and sponge iron. Within the DEA framework, the output-oriented model with constant returns to scale and variable returns to scale were studied. Four input variables, namely, gross fixed assets, total energy cost, total number of employees and currents assets were considered. Among the output variables, the four variables considered are income, sales, PBIT and PAT. Findings – The result of the efficiency scores have been categorized into three parts. The pure technical efficiency represents local efficiency and the reason of inefficiency is due to inefficient operations. Technical efficiency indicates that the respective decision-making units are globally efficient in case the efficiency is 100 per cent. The SE explains that the inefficiency is caused by disadvantageous conditions. As the result shows, that public sector undertaking (PSUs) are operating under disadvantageous conditions as compared to private manufacturing units. One of the possible reasons of location disadvantage condition is manufacturing units for PSUs are scattered throughout India. Some of the units are located in such places where, the raw material, supply chain could be difficult. It has been found that 45 per cent of the private manufacturing units are technically as well as scale inefficient units. Practical implications – The result of the study would benefit the steel industry to develop a performance benchmarking as steel companies must be profitable in the long term to ensure sustainable achievements. Originality/value – This is an original study to apply DEA to get insights on productivity efficiency of the steel manufacturing units in India. Though the manufacturing units were selected on the basis of annual income, the analysis of productivity does not reflect any impact of income on the efficiency of the manufacturing firms.

scholarly journals Does Farm Size and Specialization Matter for Productive Efficiency? Results from Kansas

2011 ◽  
Vol 43 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Amin W. Mugera ◽  
Michael R. Langemeier
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Production Technology ◽  
Returns To Scale ◽  
Productive Efficiency ◽  
Farm Size ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Sample Period ◽  
Analysis Techniques

In this article, we used bootstrap data envelopment analysis techniques to examine technical and scale efficiency scores for a balanced panel of 564 farms in Kansas for the period 1993–2007. The production technology is estimated under three different assumptions of returns to scale and the results are compared. Technical and scale efficiency is disaggregated by farm size and specialization. Our results suggest that farms are both scale and technically inefficient. On average, technical efficiency has deteriorated over the sample period. Technical efficiency varies directly by farm size and the differences are significant. Differences across farm specializations are not significant.

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