Gas Distribution in Italy: A Non Parametric Analysis of Companies Operational Efficiency

2013 ◽  
Vol 838-841 ◽  
pp. 1972-1978 ◽  
Author(s):  
Corrado lo Storto
Keyword(s):  
Technical Efficiency ◽  
Returns To Scale ◽  
Scale Economies ◽  
Graphical Analysis ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Gas Industry ◽  
Density Measurements ◽  
Sample Average ◽  
Natural Gas Industry

This paper investigates the levels of technical efficiency in the distribution segment of the natural gas industry in Italy. An empirical analysis is conducted on a sample of 32 gas distributors, while Data Envelopment Analysis (DEA) is performed to calculate efficiency scores. Technical and scale efficiency, and density measurements are also used. Results show that the sample average technical efficiency is about at 75.58%, with a standard deviation of 31.24%. Scale economies are also relevant in the industry as scale efficiency is only 49.28%, with the bulk of companies showing decreasing returns to scale. Furthermore, from graphical analysis apparently no association between technical, scale efficiency and density measurements emerges, indicating that there is no one optimal way to improve efficiency of gas distributing companies.

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.

The evidence on the existence of economies Of scale in local government units

2017 ◽  
Vol 1 (2) ◽  
pp. 379 ◽  
Author(s):  
Primož Pevcin
Keyword(s):  
Local Government ◽  
Economies Of Scale ◽  
Returns To Scale ◽  
Scale Economies ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Administrative Costs ◽  
Government Operation ◽  
Major Reform ◽  
Limited Scale

<p>The purpose of this paper is to empirically verify if the possible existence of scale economies actually supports the argument that municipal consolidation is needed in Slovenia. The major reform of local self-government in Slovenia was implemented in 1994, when the transformation of existing 58 »communal« municipalities was envisaged. From 1995 onwards, the number of municipalities increased to the current number of 212 municipalities. Consequently, the necessity to implement structural reforms of local self-government in Slovenia has been stressed. The arguments favoring municipal amalgamations stressed that country has become too fragmented and municipal amalgamation would enable the reduction of (administrative) costs, and increase efficiency as well as quality of services provided, indicating that technical aspects of local government operation are targeted. Following, technical efficiency of Slovenian municipalities is estimated with the Data Envelopment Analysis (DEA) method, in order to determine if (and which) municipalities are experiencing increasing returns to scale (i.e., scale economies). The results indicate that there is important scale efficiency component, and predominantly very small municipalities are experiencing economies of scale, but their number is relatively low. Therefore, one of the classical arguments for municipal amalgamation, achieving economies of scale, can only be applied at a limited scale. This does not imply that more extensive amalgamation is not warranted, but it demands that other arguments justifying municipal amalgamation should be presented.  </p>

Efficiency of glass firms in India: an application of data envelopment analysis

2016 ◽  
Vol 13 (1) ◽  
Author(s):  
Mini Kundi ◽  
Seema Sharma
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Design Methodology ◽  
Large Scale ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Efficiency Measures ◽  
Target Values ◽  
Practical Implications

Purpose The purpose of the present study is to evaluate the efficiency of glass firms in India. Design/methodology/approach Data envelopment analysis (DEA) has been employed to study the technical, scale and super efficiency measures of glass firms in India. Findings Major findings of DEA analysis show that 65 percent firms are found to be technically efficient. Returns to scale analysis indicate that five firms are operating at decreasing returns to scale and two firms are exhibiting increasing returns to scale. Further, results show that small– and medium–scale firms are more efficient than large–scale firms. Old firms are more efficient compared to the young firms and foreign-owned firms are technically more efficient compared to the domestic firms. Practical implications The results of this study would help the managers to assess their relative efficiency and take corrective measures to efficiently use their resources. Originality/value This seems to be the first study to apply DEA to analyze the efficiency of glass firms in India. No previous study on glass industry seems to have decomposed the measure of overall technical efficiency into its components, namely pure technical efficiency and scale efficiency and no study seems to have examined whether ownership, age and size of a firm are significant for its efficiency. In addition, no earlier study seems to have ranked the glass firms based on their efficiency values. Further, target values of inputs and outputs are demonstrated in this study. Stability of efficiency scores is also checked.

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.

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.

PRODUCTIVITY GROWTH, TECHNICAL EFFICIENCY, AND RETURNS TO SCALE IN THE WASHINGTON STATE SAWMILL INDUSTRY

2005 ◽  
Vol 04 (03) ◽  
pp. 477-490 ◽  
Author(s):  
TED L. HELVOIGT ◽  
SHAWNA GROSSKOPF
Keyword(s):  
Technical Efficiency ◽  
Productivity Growth ◽  
Technical Change ◽  
Returns To Scale ◽  
Washington State ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Sawmill Industry ◽  
Annual Decline

We employed data envelopment analysis (DEA) to examine the technical and scale efficiency of the sawmill industry of Washington State. We found that there is regional variation in the rate of technical efficiency and that for most years the industry in aggregate operated at a point of modest scale inefficiency. In addition, we examined the industry's rate of productivity growth and technical change between the early 1970s and late 1990s using the Malmquist input-oriented productivity index. We found that the industry experienced a modest average annual decline in productivity and technical change during the 1970s, but experienced strong productivity growth and technical change during the 1980s and 1990s.

scholarly journals Decomposition of the technical efficiency of the banking system

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Sanderson Abel ◽  
Alex Bara ◽  
Pierre Le Roux
Keyword(s):  
Technical Efficiency ◽  
Commercial Banks ◽  
Returns To Scale ◽  
Banking System ◽  
Efficiency Score ◽  
Foreign Banks ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Analysis Method ◽  
Technical Inefficiency

The study investigated the technical efficiency of the commercial banks in Zimbabwe during the period 2009–2015. The study entailed the decomposition of the technical efficiency into pure technical and scale efficiency to understand the sources of the technical inefficiency in the commercial banks in Zimbabwe. To accomplish the task, the study sampled 11 commercial banks of which 6 are domestic and the other 5 are foreign banks. The study used the data envelopment analysis method. The results of the study revealed that commercial banks in Zimbabwe are technically inefficient with an efficiency score of 82.9%. The average pure technical and scale efficiency scores were 96.6% and 85.6%, respectively. The results imply that technical inefficiency of the Zimbabwean commercial banks is mainly a result of scale inefficiency emanating from decreasing returns to scale. The deduction is that commercial banks in Zimbabwe are operating at below their optimum capacity and hence have scope to increase their operations in order to improve on technical efficiency.

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.

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