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

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.

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246559
Author(s):  
Kiddus Yitbarek ◽  
Gelila Abraham ◽  
Melkamu Berhane ◽  
Sarah Hurlburt ◽  
Carlyn Mann ◽  
...  

Background Although much has been documented about the performance of the health extension program, there is a lack of information on how efficiently the program is running. Furthermore, the rising cost of health services and the absence of competition among publicly owned health facilities demands strong follow up of efficiency. Therefore, this study aimed to assess the technical efficiency of the health posts and determinants in Southwestern Ethiopia. Methods and materials We used data for one Ethiopian fiscal year (from July 2016 to June 2017) to estimate the technical efficiency of health posts. A total of 66 health posts were included in the analysis. We employed a two-stage data envelopment analysis to estimate technical efficiency. At the first stage, technical efficiency scores were calculated using data envelopment analysis program version 2.1. Predictors of technical efficiency were then identified at the second stage using Tobit regression, with STATA version 14. Results The findings revealed that 21.2% were technically efficient with a mean technical efficiency score of 0.6 (± 0.3), indicating that health posts could increase their service volume by 36% with no change made to the inputs they received. On the other hand, health posts had an average scale efficiency score of 0.8 (± 0.2) implying that the facilities have the potential to increase service volume by 16% with the existing resources. The regression model has indicated average waiting time for service has negatively affected technical efficiency. Conclusion More than three-quarters of health posts were found inefficient. The technical efficiency score of more than one-third of the health posts is even less than 50%. Community mobilization to enhance the uptake of health services at the health posts coupled with a possible reallocation of resources in less efficient health posts is a possible approach to improve the efficiency of the program.


Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4902
Author(s):  
Biswaranjita Mahapatra ◽  
Chandan Bhar ◽  
Sandeep Mondal

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.


2020 ◽  
Vol 12 (3) ◽  
pp. 121
Author(s):  
Abdullah M. Alsabah ◽  
Hassan Haghparast-Bidgoli ◽  
Jolene Skordis

The recent drop in oil prices has challenged public sector financing in Kuwait. Technical and scale efficiency scores for fifteen public hospitals in Kuwait from 2010 to 2014 were estimated using a two-stage data envelopment analysis (DEA). Technical efficiency scores were regressed against institutional characteristics using Tobit regression to investigate the determinants of efficiency differences in hospitals. Semi-structured interviews were also carried out with fourteen public and private hospital managers to qualitatively explore their perceptions and experience about about factors affecting hospital efficiency. The mean technical efficiency score for all hospitals was 85.8%, an improvement of 2% since 2010. The mean pure technical efficiency score was 79.6%, improving from 75% in 2010 to 81.2% in 2014. The mean scale efficiency score was 91.8%, improving from 87.6% in 2010 to 94.2% in 2014. Only three hospitals were constantly technically and scale efficient. Tobit regression showed that hospital efficiency was significantly associated with the average length of patient stay. Hospitals with more than 400 beds were potentially more technically and scale efficient. The qualitative study revealed that external factors affecting efficiency commonly included implemention of legislative changes and decreasing bureaucracy, while internal factors included increasing bed capacity and improving qualifications and training of human resources. Most public hospitals in Kuwait were not technically and scale efficient, but improvements were observed. Potential factors that affected the efficiency of hospitals in Kuwait were identified. These findings are useful to decision-makers in Kuwait for developing strategies to improve public hospital efficiency.


Author(s):  
Surakiat Parichatnon ◽  
Kamonthip Maichum ◽  
Ke-Chung Peng

<div><p><em>The purpose of this paper is to investigate and measure the technical efficiency of durian production in each province of Thailand using the data envelopment analysis (DEA) during the period 2012-2016. The findings indicate that the technical efficiency of Thai durian production revealed favorable results from 2012 to 2016 but still needs to be improved since the technical efficiency score is not close to 1.000. On the other hand, Chanthaburi province had the highest mean efficiency score and was recognized as the best province for Thai durian production. Moreover, the study found that Phuket province had lowest mean technical efficiency score of Thai durian production, which therefore should be increased the quantity of the outputs and inputs. Therefore, the results of this study can provide important information to farmers, agricultural planners and government agencies to help increase the technical efficiency levels of durian production in Thailand.</em></p></div>


2021 ◽  
Vol 50 (7) ◽  
pp. 2095-2107
Author(s):  
Noorasiah Sulaiman ◽  
Rahmah Ismail

This study measures the technical efficiency score of the manufacturing sector of the palm oil products-based subsector in Malaysia and investigates the major determinants that influence efficiency. Based on the Industrial Manufacturing Survey, this study explores the data from 2000 to 2015 over sixteen years, with a total of eleven subsectors of palm oil products-based. The first stage of the study is carried out with a data envelopment analysis (DEA) to calculate the technical efficiency score, which is considered a dependent variable. The second stage of the study uses a panel regression model to examine the determinants of efficiency comprise the variable capital-labour ratio, research and development, information communication technology, training, and skilled labour. The study findings show that most of the palm oil products-based subsectors are not operating efficiently. Skilled labour, technical and supervisory, and professional is one of the main determinants contributing to the efficiency level. The variable capital-labour ratio though significant, but harms the efficiency level. The moderating effects show that skilled technical and supervisory workers relatively affect the food industry’s efficiency larger than the non-food industry. Therefore, the industry still has room to improve efficiency by utilising input efficiently. Moreover, the efforts involve organisational management, equipped appropriate technology and related factors that will improve efficiency, increase productivity and competitiveness of palm oil products-based industries.


2015 ◽  
Vol 65 (s2) ◽  
pp. 101-113 ◽  
Author(s):  
Ling Jiang ◽  
Yunyu Jiang ◽  
Zhijun Wu ◽  
Dongsheng Liao ◽  
Runfa Xu

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.


2011 ◽  
Vol 43 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Amin W. Mugera ◽  
Michael R. Langemeier

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.


2019 ◽  
Vol 14 (2) ◽  
pp. 362-378 ◽  
Author(s):  
Vikas Vikas ◽  
Rohit Bansal

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.


2017 ◽  
Vol 1 (2) ◽  
pp. 067
Author(s):  
Abi Pratiwa Siregar ◽  
Jamhari Jamhari ◽  
Lestari Rahayu Waluyati

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.


2021 ◽  
pp. 1-13
Author(s):  
Yanzhi Bi

Abstract Professional teams are commercial and recreational organizations, and team managers always set their goals to be playing well and benefitting more in a highly competitive environment. In order to measure the ability of the professional teams to make reasonable use of resources and create various outputs, this study employs the Data Envelopment Analysis (DEA) model to measure the efficiencies of 30 Major League Baseball (MLB) teams. The results showed that the inefficiencies were due to pure technical inefficiencies rather than scale effects, and the scale efficiency on average is more higher than the other efficiencies, applying the managers in the Major League Baseball Teams have higher ability of controlling the scale change. Keywords: Major League Baseball, Data Envelopment Analysis, Technical efficiency, Pure technical efficiency, Scale efficiency.


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