Assessing the Performance of Telecommunication Industry in India: A Data Envelopment Analysis

2010 ◽  
Vol 11 (2) ◽  
pp. 29-47
Author(s):  
Seema Sharma ◽  
Kirankumar Momaya ◽  
K. Manohar

Rapid growth of telecommunications in India has been creating opportunities for many players from Asia, Europe and other parts of world. Relative assessment of efficiencies can be used to enhance productivity and competitiveness. In this study an attempt is made to evaluate competitiveness of the telecom industry in India focusing on the efficiency. Input oriented data envelopment analysis is used to measure the relative technical and scale efficiencies of 10 service providers. Further, using output oriented model, the efficiency analysis is extended to 23 service circle areas. From the analysis performed on service providers the technically and scale efficient firms were identified. Technical and scale efficiency were assessed at circle level also. The findings confirm some assumptions and hint at several competitiveness implications for leadership in firms and government.

2018 ◽  
Vol 31 (4) ◽  
pp. 276-282 ◽  
Author(s):  
Mohammad Amin Bahrami ◽  
Sima Rafiei ◽  
Mahdieh Abedi ◽  
Roohollah Askari

Purpose As hospitals are the most costly service providers in every healthcare systems, special attention should be given to their performance in terms of resource allocation and consumption. The purpose of this paper is to evaluate technical, allocative and economic efficiency in intensive care units (ICUs) of hospitals affiliated by Yazd University of Medical Sciences (YUMS) in 2015. Design/methodology/approach This was a descriptive, analytical study conducted in ICUs of seven training hospitals affiliated by YUMS using data envelopment analysis (DEA) in 2015. The number of physicians, nurses, active beds and equipment were regarded as input variables and bed occupancy rate, the number of discharged patients, economic information such as bed price and physicians’ fees were mentioned as output variables of the study. Available data from study variables were retrospectively gathered and analyzed through the Deap 2.1 software using the variable returns to scale methodology. Findings The study findings revealed the average scores of allocative, economic, technical, managerial and scale efficiency to be relatively 0.956, 0.866, 0.883, 0.89 and 0.913. Regarding to latter three types of efficiency, five hospitals had desirable performance. Practical implications Given that additional costs due to an extra number of manpower or unnecessary capital resources impose economic pressure on hospitals also the fact that reduction of surplus production plays a major role in reducing such expenditures in hospitals, it is suggested that departments with low efficiency reduce their input surpluses to achieve the optimal level of performance. Originality/value The authors applied a DEA approach to measure allocative, economic, technical, managerial and scale efficiency of under-study hospitals. This is a helpful linear programming method which acts as a powerful and understandable approach for comparative performance assessment in healthcare settings and a guidance for healthcare managers to improve their departments’ performance.


The study has analyzed the technical efficiency of major cash crops' yield in Pakistanfrom 1948 till 2018. Cotton and sugarcane are the crops selected for analysis with an area ofthousand hectares. For carrying out the analysis, data is taken from the Ministry of Food andAgriculture (MINFA), Pakistan Bureau of Statistics, and economic surveys of Pakistan of differentyears. The technique employed in the study is the non-parametric Data Envelopment Analysis(DEA) technique. The result obtained after technical efficiency analysis reveal the suboptimal cashcrop yield in Pakistan throughout the analysis. The average technical efficiency of cotton andsugarcane crops from 1948 to 2018 are approximately 0.80 and 0.84 respectively. Furthermore,the result of scale efficiency analysis showed the monotonous performance of cash crops'production. The consistent variation in cotton and sugar cane crops' yield over the years reportedby the efficiency analysis, accounts for Constant Return to Scale (CRS) and Variable Return toScale (VRS) models, resulted in varying Return to Scale (RTS). The plausible reasons can beattributed to the Increasing Returns to Scale (IRS) or Decreasing Returns to Scale (DRS) in thecase of cotton and sugarcane production. An interesting finding is unveiled that out of 70 years,cotton and sugarcane crops achieved the optimal scale efficiencies for only one year. The bestpossible level of output of cotton and sugarcane crops in the future can be achieved by allocatinga lesser area under the cultivation of these crops in Pakistan. It is also imperative that farmers adoptand implement modern farm technologies. Increasing the area under crop production is not asolution, especially in the wake of alarming population growth and urbanization in Pakistan. Theformulation of policies encouraging farmers requires modern farm inputs to realize the optimalyield of cash crops in Pakistan. The government should educate the farmers regarding advancedfarming and efficient farm management techniques to help to augment the farm output withoutexpansion of the area for these crops


Author(s):  
Matthias Klumpp ◽  
Dominic Loske

Although resources are scarce and outputs incorporate the potential to save human lives, efficiency measurement endeavors with data envelopment analysis (DEA) methods are not yet commonplace in the research and practice of non-government organizations (NGO) and states involved in humanitarian logistics. We present a boot-strapped DEA window analysis and Malmquist index application as a methodological state of the art for a multi-input and multi-output efficiency analysis and discuss specific adaptions to typical core challenges in humanitarian logistics. A characteristic feature of humanitarian operations is the fact that a multitude of organizations are involved on at least two levels, national and supra-national, as well as in two sectors, private NGO and government agencies. This is modeled and implemented in an international empirical analysis: First, a comprehensive dataset from the 34 least developed countries in Africa from 2002 to 2015 is applied for the first time in such a DEA Malmquist index efficiency analysis setting regarding the national state actor level. Second, an analysis of different sections in a Rohingya refugee camp in Bangladesh is analyzed based on a bootstrapped DEA with window analysis application for 2017, 2018, and 2019 quarter data regarding the private NGO level of operations in humanitarian logistics.


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.


Sign in / Sign up

Export Citation Format

Share Document