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.

Efficiency evaluation of the energy companies in CNX 500 Index of the NSE, India using data envelopment analysis

2016 ◽  
Vol 23 (1) ◽  
pp. 113-126 ◽  
Author(s):  
Punita Saxena ◽  
Ratnesh R. Saxena ◽  
Deepak Sehgal
Keyword(s):  
Data Envelopment Analysis ◽  
Stock Markets ◽  
Stock Exchange ◽  
Peer Group ◽  
Data Envelopment ◽  
Energy Index ◽  
Content Type ◽  
Indian Economy ◽  
Energy Companies ◽  
Non Parametric

Purpose – Data envelopment analysis (DEA) is a non-parametric technique of computing efficiencies of decision-making units using similar set of inputs to give similar set of outputs. The objective is to pick out inefficient units from a data set of similar units and thus analyse their performance amongst their peer group. Stock markets can be considered to be an economy’s barometer. Thus, evaluation of efficiency effectiveness of the companies operating at stock exchange is a valuable exercise. Further, if the inefficient units can be given a benchmark for improvement, they can increase their market value. The purpose of this paper is to evaluate the efficiencies of the Oil, Gas and Power (OGP) sector of India for the companies that form a part of the CNX Energy Index and CNX 500 Index of the National Stock Exchange of India. Design/methodology/approach – A group of 24 units has been included in the study. DEA was applied for ranking the units as per their efficiency levels by computing their technical, pure technical and scale efficiencies (SE). It was observed that only nine units are efficient and the remaining 15 were inefficient. It was observed that ONGC is the most efficient unit and CESC Ltd is the least efficient unit in this group. Also in this group there are ten units that show inefficiency due to their scales of operations. Further, benchmarking for the inefficient units has also been done in terms of inputs/outputs and the targets are suggested. It was observed that some of the Public Sector Companies like NTPC are using more inputs compared to the other units from the same group for achieving the same efficiency. Findings – The present study attempted a limited objective of establishing the technical, pure technical and scale inefficiencies of the companies operating in OGP sector in India and listed on National Stock Exchange with the help of the non-parametric technique of DEA and suggesting how they can strive to improve their performance. It is observed that 37.5 per cent are technically efficient as well as scale efficient, whereas 62.5 per cent are pure technically efficient. There are 42 per cent companies representing approximately half of the output and more than half of the input that have scale inefficiencies characterized by their PTE less than SE. Out of the efficient companies, ONGC appears to be the best whereas Essar Oil has a comparatively lower rank. Out of the inefficient companies, the worst performer is CESC Ltd. However, inspite of being the worst performer, this unit does not have the worst benchmarking targets. The units like Sterlite technologies and KSK energy ventures need to improve their profit by almost 1,000 per cent. These kind of targets are very difficult to attain. Hence these units need to improve their scale of operation. The managers of these units must take up this issue seriously and take measures to improve their productivity. The study also attempted benchmarking where various inefficient units have been suggested targets they need to scale to improve their efficiency. If addressed, they can have micro as well as macro benefits. Research limitations/implications – In the present paper, the analysis is restricted only to the OGP sector of Indian economy. The study can be further extended to various other sectors of Indian economy such as agriculture, telecommunications etc. This would help in the holistic analysis of the economy. The flag bearer efficient units would set up a benchmark for the improvement to the inefficient units that would help improve the developing economy of India. Originality/value – An increase in productivity is the most crucial management objective for any industry. Assessing the performance of companies listed and traded in stock market is imperative for investors and financial managers. Researchers have widely studied the performance evaluation of listed companies. Establishing efficiency of stock markets as a whole as well as of the constituent companies has been subject of wide research, but to the understanding no study has been done on evaluating the efficiencies of the OGP sector of India. In the present study the authors have concentrated on companies, out of the universe of energy companies operating in India, which form part of the CNX Energy Index and CNX 500 Index of the National Stock Exchange of India. The reason is that they represent the Indian energy market pretty well.

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 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.

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.

scholarly journals Analyzing the performance of the Major League Baseball Teams by using the Data Envelopment Analysis

2021 ◽  
pp. 1-13
Author(s):  
Yanzhi Bi
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Major League Baseball ◽  
Scale Effects ◽  
Competitive Environment ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Use Of Resources ◽  
Major League ◽  
Reasonable Use

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.

scholarly journals Evaluating Efficiency of Waqf Institutions: An Intermediation Approach Using Data Envelopment Analysis (DEA)

2019 ◽  
Vol 2 (2) ◽  
pp. 82-89
Author(s):  
Nor Tasik Misbahrudin
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Wealth Distribution ◽  
Scale Efficiency ◽  
Optimum Level ◽  
Data Envelopment ◽  
Input And Output ◽  
Distribution State ◽  
Using Data ◽  
Decision Making Units

Waqf is a voluntary charity that cannot be disposed of and the ownership cannot be transferred once it is declared as waqf assets. Waqf institutions play an important role in helping the development of Muslims ummah through wealth distribution. State Islamic Religious Councils (SIRCs) in Malaysia are the sole trustee that manage and develop waqf assets. Based on selected input and output, the intermediary approach assumes that cash waqf received as output while total expenditure of SIRCs as input. Under this approach SIRCs act as intermediary between waqif (giver) and beneficiaries. Thus, this paper attempts to analyze the efficiency of waqf institutions in Malaysia by using Data Envelopment Analysis (DEA) method under output-orientation using Variable Return to Scale (VRS) assumptions. Four SIRCs were selected as decision making units (DMU) for the period of 2011 to 2015. The result indicates that changes in average technical efficiency for every year is contributed by both pure technical and scale. However, inefficiency of Malaysian waqf institutions is mostly contributed by pure technical efficiency aspects rather than scale. 2012 showed the highest average technical efficiency with 73.9% as most of the institutions operated in optimum level of input to produce output. Thus, the result suggests that both technical and scale efficiency should be improved to achieve the most efficient and productive level of performance in order to fulfill objectives of the institutions as an intermediary between waqif and beneficiaries.

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.

EFFICIENCY OF SLELECTED FARM TYPES IN LUBLIN PROVINCE IN 2014-2016

2018 ◽  
Vol XX (5) ◽  
pp. 206-211 ◽  
Author(s):  
Alina Syp ◽  
Adam Kagan ◽  
Dariusz Osucha
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Average Efficiency ◽  
Field Crops ◽  
Pig Farms ◽  
Dea Models ◽  
Large Crop ◽  
Farm Types

The aim of the study was to present changes in the efficiency of farms specializing in crops and pigs production in the Lublin province. To perform the analysis the empirical data for large crop and pig farms collected in Polish FADN system in the years 2014-2016 were applied. The level of efficiency was determined using input oriented Data Envelopment Analysis (DEA) models. In the studied years, in the field crops farms ratios of technical efficiency and scale efficiency remained at the same level, whereas the value of pure technical efficiency slightly increased. In the pig holdings, all efficiency indices have deteriorated. Comparing the average efficiency results according to farm specialization it was found that filed crops farms were more efficient than crop farms.

Sign in / Sign up

Export Citation Format

Share Document