scholarly journals Measurement of Scale Efficiency in Dairy Farms: Data Envelopment Analysis (DEA) Approach

2013 ◽  
Vol 5 (9) ◽  
Author(s):  
Bassam Aldeseit
Keyword(s):  
Data Envelopment Analysis ◽  
Dairy Farms ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Dea Approach

Measurement of Technical and Scale Efficiency of Dairy Farms in Pune District of Maharashtra: Data Envelopment Analysis Approach

2021 ◽  
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Management Practices ◽  
Dairy Farms ◽  
Herd Size ◽  
Efficiency Score ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Resource Saving ◽  
Technical Efficiency Score

The present study intended to determine the technical and scale efficiency of sample dairy farms for evaluating their performance. Data Envelopment Analysis (DEA) technique was used to estimate the technical and scale efficiency of 80 each of member and nonmember dairy farms in the Pune district of Maharashtra state during 2019. Technical efficiency score further partitioned into pure technical efficiency and overall technical efficiency. The technical efficiency score was more for member dairy farms as compared to the non-members under the assumption of constant return to scale (CRS) and variable return to scale (VRS). It highlighted that the non-members of dairy cooperatives had more potential to reduce the input use without affecting the output level compared to the member group. It was also observed that the technical efficiency under the CRS assumption was more than VRS for both member and non-member groups. It revealed that the farms were scaled inefficient (SE<1) and not operating at optimal scale. The study further revealed a positive relationship between technical efficiency and herd size. It also revealed that the resource-saving potential due to the scale effect. So, it supported the policy of providing technical advice on the use of feed and fodder resources, better management practices, and increasing the herd size to increase the technical and scale efficiency.

scholarly journals The Efficiency Performance of Global Islamic Banks

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Norlina Kadri ◽  
Rossazana Abdul Rahim ◽  
Dyg Siti Zahrah Abg. Abdillah
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Banking Sector ◽  
Scale Efficiency ◽  
Islamic Banking ◽  
Data Envelopment ◽  
Islamic Banks ◽  
Technical Inefficiency ◽  
Efficiency Performance ◽  
Dea Approach

This paper examines the efficiency performance of the Islamic banks that consist of 14 countries namely Bahrain, Bangladesh, Iran, Jordan, Kuwait, Lebanon, Malaysia, Pakistan, Qatar, Saudi, Tunisia, Turkey, UAE, and Yemen during the period of 2004-2011 with 44 Islamic banks involved. The efficiency estimates of individual banks are evaluated using the Data Envelopment Analysis (DEA) approach. The empirical findings suggest that during the period of study, pure technical efficiency outweighs scale efficiency in the global Islamic banking sector implying that the Islamic banks have been managerially efficient in exploiting their resources to the fullest extent. The empirical findings seem to suggest that the global Islamic banks have exhibited high pure technical efficiency. During the period of study it is found that pure technical efficiency has greater influence in determining the total technical inefficiency of the Global Islamic banking sectors.

scholarly journals Technical Efficiency of Universities in Telangana State through Data Envelopment Analysis (DEA) Approach

2021 ◽  
Vol 2 (6) ◽  
pp. 30-39
Author(s):  
R. Nellutla ◽  
R. Ashok ◽  
M. Ramesh ◽  
V. V. Haragopal
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Research Paper ◽  
The State ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Reference Set ◽  
Telangana State ◽  
Dea Approach

In this present research paper we analyze the universities data by CCR, BCC models through Data Envelopment Analysis (DEA) approach for the State of Telangana. To know the Performance of student’s university wise in state of Telangana. University wise Performances is presented along with technical efficiency, Pure Technical Efficiency, Scale Efficiency, CRS, VRS, Reference set and Peers. Measuring the Technical Efficiency (TE) and Pure Technical Efficiency (PTE) of the universities by CCR, BCC Model through DEA approach.

scholarly journals The Measurement of Innovation Efficiency of Chinese High-tech Industry Using Data Envelopment Analysis

2015 ◽  
Vol 65 (s2) ◽  
pp. 101-113 ◽  
Author(s):  
Ling Jiang ◽  
Yunyu Jiang ◽  
Zhijun Wu ◽  
Dongsheng Liao ◽  
Runfa Xu
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Environmental Variables ◽  
Scale Efficiency ◽  
High Tech ◽  
Data Envelopment ◽  
High Tech Industry ◽  
Economic Competitiveness ◽  
Development Level ◽  
Using Data

In the era of knowledge economy, a country’s economic competitiveness depends largely on the development level of high-tech industry. This paper evaluates the efficiency of China’s high-tech industry in 31 provinces in 2012 with data envelopment analysis. The empirical results are summarized as following. Firstly, when the effects of exogenous environmental variables are not controlled, the comprehensive technical efficiency of 31 provinces will be overestimated, the pure technical efficiency will be underestimated, and the scale efficiency value will be overestimated. Secondly, after eliminating the environmental impact, the comprehensive technical efficiency of 31 provinces with the average of 0.395 is rather low, due to the low scale efficiency.

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.

Efficiency evaluation of Indian oil and gas sector: data envelopment analysis

2019 ◽  
Vol 14 (2) ◽  
pp. 362-378 ◽  
Author(s):  
Vikas Vikas ◽  
Rohit Bansal
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Capital Investment ◽  
Oil And Gas ◽  
Stock Exchange ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Content Type ◽  
Indian Economy ◽  
Oil And Gas Sector

Purpose Data envelopment analysis (DEA), a non-parametric technique is used to assess the efficiency of decision-making units which are producing identical set of outputs using identical set of inputs. The purpose of this paper is to find the technical efficiency (TE), pure technical efficiency and scale efficiency (SE) levels of Indian oil and gas sector companies and to provide benchmark targets to the inefficient companies in order to achieve efficiency level. Design/methodology/approach In the present study, a group of 22 oil and gas companies which are listed on the National Stock Exchange for which the data were available for the period 2013–2017 has been considered. DEA has been performed to compare the efficiency levels of all companies. To measure efficiency, three input variables, namely, combined materials consumed and manufacturing expenses, employee benefit expenses and capital investment and two output variables – operating revenues and profit after tax (PAT) have been considered. On the basis of performance for the financial year ending 2017, benchmark targets based on DEA–CCR (Charnes, Cooper and Rhodes) model have been provided to the inefficient companies that should be focused upon by them to attain the efficiency level. The performance of the companies for the past five years has been examined to check the fluctuations in the various efficiency scores of the companies considered in the study over the years. Findings From the results obtained, it is observed that 59 percent, i.e. 13 out of 22 companies are technically efficient. By considering DEA BCC (Banker, Charnes and Cooper) model, 16 companies are observed to be pure technically efficient. In terms of SE, there are 14 such companies. The inefficient units need to improve in terms of input and output variables and for this motive, specified targets are assigned to them. Some of these companies need to upgrade significantly and the managers must take the concern earnestly. The study has also thrown light on the performance of the companies over last five years which shows Oil India Ltd, Gujarat State Petronet Ltd, Petronet LNG Ltd, IGL Ltd, Mahanagar Gas, Chennai Petroleum Corporation Ltd and BPCL Ltd as consistently efficient companies. Research limitations/implications The present study has made an attempt to evaluate the efficiency of Indian oil and gas sector. The results of the study have significant inferences for the policy makers and managers of the companies operating in the sector. The results of the study provide benchmark target level to the companies of Oil and Gas sector which can help the managers of the relatively less efficient companies to focus on the ways to improve efficiency. The improvement in efficiency of a company would not only benefit the shareholders, but also the investors and other stakeholders of the company. Originality/value In the context of Indian economy, very limited number of studies have focused to measure the efficiency of oil and gas sector in the context of Indian economy. The present study aims to provide the latest insight to the efficiency of the companies especially operating in the Indian oil and gas sector. Further, as per our knowledge, this study is distinctive in terms of analyzing the efficiency of Indian oil and gas sector for a period of five years. The longitudinal study of the sector efficiency provides a bird eye view of the average efficiency level and changes in the efficiency levels of the companies over the years.

scholarly journals The Efficiency of Non-Bank Financial Intermediaries: Empirical Evidence from Malaysia

2008 ◽  
Author(s):  
Fadzlan Sufian
Keyword(s):  
Risk Factors ◽  
Data Envelopment Analysis ◽  
Empirical Evidence ◽  
Financial Institutions ◽  
Economies Of Scale ◽  
Financial Intermediaries ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Parametric Data ◽  
Dea Method

This paper investigates the performance of Malaysian non-bank financial institutions during the period of 2000-2004. Several efficiency estimates of individual NBFIs are evaluated using the non-parametric Data Envelopment Analysis (DEA) method. The findings suggest that during the period of study, scale inefficiency outweighs pure technical inefficiency in the Malaysian NBFI sector. We find that the merchant banks have exhibited a higher, technical efficiency compared to their peers. The empirical findings suggest that scale efficiency tends to be more sensitive to the exclusion of risk factors, implying that potential economies of scale may be overestimated when risk factors are excluded.  

scholarly journals Performance of Village Unit Co-Operatives in Yogyakarta Special Region: A Data Envelopment Analysis Approach

2017 ◽  
Vol 1 (2) ◽  
pp. 067
Author(s):  
Abi Pratiwa Siregar ◽  
Jamhari Jamhari ◽  
Lestari Rahayu Waluyati
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Best Practice ◽  
Negative Impact ◽  
Positive Impact ◽  
Three Dimensions ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Rice Milling ◽  
Special Region

This study assessed the performance of 32 village unit co-operatives (KUD) in Yogyakarta Special Region during 2011 to 2012. The efficiency level of the KUD were evaluated by employing the data envelopment analysis and multiple regression analysis using panel data to determine the factors affecting efficiency level. Efficiency analysis was decomposed into three dimensions to explore possible sources of inefficiency. According to Marwa and Aziakpono (2016), the first dimension was technical efficiency, which explored the overall effectiveness of transforming the productive inputs into desired outputs compared to the data-driven frontier of best practice. The second dimension was pure technical efficiency, which captured managerial efficiency in the intermediation process. The third dimension was scale efficiency, which explored whether KUD were operating in an optimal scale of operation or not. The results found that the average scores are 64%, 92%, and 68% for technical, pure technical, and scale efficiency respectively in 2011, while in 2012 the average scores are 57%, 94%, and 60% for technical, pure technical, and scale efficiency. Factors having significantly positive impact on several measures of efficiency are incentive and dummy variables (agriculture inputs and hand tractor). Accounts receivable only has positive relationship to pure technical efficiency. On the other hand, rice milling unit and electricity services have negative impact with several measures of efficiency.

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