Comparative Performance Measurement: A Primer on Data Envelopment Analysis

Nyhan, Ronald C.; Martin, Lawrence L.

doi:10.2307/3380708

Cited by 59 publications

(29 citation statements)

References 22 publications

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“…Power and Novarum, and annual financial reports of each company. According to Nyhan and Martin [46], the appropriate number of input factors are limited by DEA while the appropriate number of output factors are limited by the DMU. This is because an increase in the number of input and output factors in the DEA results in an increase in efficient DMUs.…”

Section: Efficiency Analysis Resultsmentioning

confidence: 99%

Driving Sustainable Competitive Advantage in the Mobile Industry: Evidence from U.S. Wireless Carriers

Kim¹,

Kim²,

Kang³

2016

Sustainability

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Abstract:In light of the growing importance of data network quality in the wireless industry, this study analyzes and compares efficiencies in management, service quality, network quality, and market in the 4G Long Term Evolution (LTE) wireless industry. For this purpose, a bootstrap data envelopment analysis (DEA) model using representative U.S. wireless carriers as decision making units (DMUs) was designed and conducted, with further verification through the Mann-Whitney U and Wilcoxon W test, to examine the differences in efficiency distribution. The results indicate that, in terms of efficiency distribution, network quality efficiency and market efficiency belongs to the same group as that which has high management efficiency. Based on these results, this paper suggests implications and strategic guidelines for wireless carriers for improvement in management efficiency.

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Section: Efficiency Analysis Resultsmentioning

confidence: 99%

Driving Sustainable Competitive Advantage in the Mobile Industry: Evidence from U.S. Wireless Carriers

Kim¹,

Kim²,

Kang³

2016

Sustainability

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“…The lower the score, the greater the relatively inefficiency DEA has been used extensively in this country as well as in the Commonwealth of Australia and the United Kingdom to make relative efficiency comparisons between multiple service providers in such service areas as: health care, schools, the courts, police systems and higher education (Cruise & Nyhan, 2000;Nyhan & Martin, 1999a;Stough & Dinc, 1997;Thanassoulis, Boussofiane & Dyson, 1995;Callen, 1991;Fare, Grosskope & Weber, 1989;Lewin, Morey & Cook, 1982). Some limited application of DEA has also been made in the human services (Nyhan & Martin, 1999b;Byrnes, Freeman & Kauffman, 1997;Ozcan & Cotter, 1994). The Commonwealth of Australia and the United Kingdom, both of which have a longer history of using and analyzing performance measurement data than does the United States, have also both recommended that DEA be used as a primary tool in assessing the relative efficiency of government programs including human service programs (Steering Committee for the Review of Commonwealth/State Service Provision, 1997; Public Sector Productivity Panel, n.d.).…”

Section: Data Envelopment Analysis (Dea)mentioning

confidence: 99%

Comparing the Performance of Multiple Human Service Providers Using Data Envelopment Analysis

Martin

2002

Administration in Social Work

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With an abundance of performance measurement data now being collected, administrators and researchers have the opportunity to begin comparing the performance of multiple human service providers. Using performance data from the Oregon Department of Human Services, this paper illustrates how data envelopment analysis (DEA) can be used to make such comparisons using a "best practices" approach. The paper argues that DEA has numerous features that make it a particularly useful statistical tool for such applications.

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“…Such rankings do not, however, take contextual factors into account. The identification of best practices when policies and context are taken into account, in case of a large N, can be done by using statistical analysis based on multiple regression and residueanalysis (see Hatry and Fisk, 1992;Nyhan and Martin, 1999). Multivariate regression analysis allows for the development of adapted performance measures when a large number of cases is involved.…”

Section: Relating Performance Measures To Policies and Contextmentioning

confidence: 99%

“…The technique is disputed because it is based on a standard of average performance -the points on the regression line represent the average performance given the background factors. According to Nyhan and Martin (1999), benchmarking should be conducted by comparing actual performance to optimal instead of average performance. This is, however, not entirely on point.…”

Section: Reflectionsmentioning

confidence: 99%

Performance measurement and the search for best practices

Vries

2010

International Review of Administrative Sciences

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Current performance measurement methods are a-contextual and unable to measure the effectiveness of policies. They usually result in rankings that measure the extent of the policy problem, but they fail to reveal anything substantive about the quality of policies, and they are equally unhelpful in the search for best practices. The goal of this article is to further develop and validate a mixed method of performance measurement -a combination of statistical analysis, residue analysis and case study approach -which considers the policy context, relates the outcomes to the policies, and provides guidance in the systematic search for best practices. In this article, this approach will be tested against one of the problems mentioned in the Millennium Development Goals, e.g. literacy rates. Points for practitionersMany practitioners struggle with the question how to determine whether their performance is above or below expectations. Classic performance measures can give a distorted view on this question. Using the method introduced in this article might give a better picture of the robustness and effectiveness of performance than the traditional performance measures. It adapts to the adversity of the context and circumstances in which policies come about.

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Comparative Performance Measurement: A Primer on Data Envelopment Analysis

Cited by 59 publications

References 22 publications

Driving Sustainable Competitive Advantage in the Mobile Industry: Evidence from U.S. Wireless Carriers

Driving Sustainable Competitive Advantage in the Mobile Industry: Evidence from U.S. Wireless Carriers

Comparing the Performance of Multiple Human Service Providers Using Data Envelopment Analysis

Performance measurement and the search for best practices

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