2008
DOI: 10.1108/14635770810903141
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Performance benchmarking in gas distribution industry

Abstract: PurposeThe paper aims to research the capability of using the tools of domestic and international performance benchmarking for estimation of efficiency, determine its key factors and reveal the full reserves of inputs reduction and potential growth efficiency for gas distribution companies.Design/methodology/approachIn the research, three models of data envelopment analysis (DEA) and other tools of performance benchmarking are used to analyse the efficiency of gas distribution companies. Some factors are exami… Show more

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Cited by 39 publications
(24 citation statements)
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“…In the first stage, a conventional Data Envelopment Analysis (DEA) model was used to evaluate the water service operator efficiency, while in the second stage the influence of environmental factors on efficiency was investigated implementing a bootstrapped DEA procedure [42]. Since its introduction by Charnes et al [43], Data Envelopment Analysis as a non-parametric technique has been extensively used for measuring efficiency in the public utilities sector to identify and design policy measures (see, for instance [44][45][46][47][48][49][50].…”
Section: Methodsmentioning
confidence: 99%
“…In the first stage, a conventional Data Envelopment Analysis (DEA) model was used to evaluate the water service operator efficiency, while in the second stage the influence of environmental factors on efficiency was investigated implementing a bootstrapped DEA procedure [42]. Since its introduction by Charnes et al [43], Data Envelopment Analysis as a non-parametric technique has been extensively used for measuring efficiency in the public utilities sector to identify and design policy measures (see, for instance [44][45][46][47][48][49][50].…”
Section: Methodsmentioning
confidence: 99%
“…DEA has been widely used for measuring and benchmarking the relative efficiency of various entities. Selected DEA applications include assessing the efficiency of bank branches (Paradi et al, 2011), advertising (Pergelova et al, 2010), hospitals (Aksezer and Benneyan, 2010), suppliers (Joo et al, 2009), portfolios (Dia, 2009), hotels (Min et al, 2008), railway zones (George and Rangaraj, 2008), telecommunication service providers (Debnath and Ravi Shankar, 2008;Kwon et al, 2008), and utility companies (Goncharuk, 2008).…”
Section: Related Studiesmentioning
confidence: 99%
“…Results show that scale inefficiencies negatively affect the overall efficiency of gas operators, whereas technology shows increasing returns only for the smallest operators suggesting that efficiency improvement can be achieved by intensify the merging process and concentration that have characterized the early years of the 2000s. Goncharuk [16] developed three DEA models to calculate the efficiency in the gas industry distribution segment In Ukraine and US comparing 54 Ukrainian and 20 US operators. The author analyzed factors that have an impact on efficiency, e.g., scale, regional location, ownership, etc.…”
Section: Literature Reviewmentioning
confidence: 99%