When does data envelopment analysis outperform a naïve efficiency measurement model?
This paper compares the results from data envelopment analysis (DEA) to a naïve efficiency measurement model, which generates a scalar efficiency score by averaging all output-input ratios. Random data and real-life data are used to test the relative performance of the naïve model against various DEA models. The results suggest that the proposed the naïve model replicates DEA efficiency scores almost perfectly for constant return-to-scales and low heterogeneity in output-input data. It is therefore concluded that heterogeneity in output-input data is important to take advantage of the capability of DEA. It is also shown that heterogeneity is more relevant to efficiency measurement than the number of dimensions.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
- Miller, Amy & Cioffi, Jennifer, 2004. "Measuring Marketing Effectiveness and Value: The Unisys Marketing Dashboard," Journal of Advertising Research, Cambridge University Press, vol. 44(03), pages 237-243, September.
- Simar, L. & Wilson, P.W., 1999.
"Statistical Inference in Nonparametric Frontier Models: the State of the Art,"
9904, Catholique de Louvain - Institut de statistique.
- Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
- Mickael Lothgren, 2000. "Specification and estimation of stochastic multiple-output production and technical inefficiency," Applied Economics, Taylor & Francis Journals, vol. 32(12), pages 1533-1540.
- Zhu, Joe, 1998. "Data envelopment analysis vs. principal component analysis: An illustrative study of economic performance of Chinese cities," European Journal of Operational Research, Elsevier, vol. 111(1), pages 50-61, November.
- Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
- Cooper, W. W. & Tone, K., 1997. "Measures of inefficiency in data envelopment analysis and stochastic frontier estimation," European Journal of Operational Research, Elsevier, vol. 99(1), pages 72-88, May.
- R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
- Tim Coelli & Sergio Perelman, 2000. "Technical efficiency of European railways: a distance function approach," Applied Economics, Taylor & Francis Journals, vol. 32(15), pages 1967-1976.
- Dan Horsky & Paul Nelson, 1996. "Evaluation of Salesforce Size and Productivity Through Efficient Frontier Benchmarking," Marketing Science, INFORMS, vol. 15(4), pages 301-320.
- Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
- Drake, Leigh & Simper, R., 2003. "The measurement of English and Welsh police force efficiency: A comparison of distance function models," European Journal of Operational Research, Elsevier, vol. 147(1), pages 165-186, May.
- Luo, Xueming & Donthu, Naveen, 2005. "Assessing advertising media spending inefficiencies in generating sales," Journal of Business Research, Elsevier, vol. 58(1), pages 28-36, January.
- Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
- Laurens Cherchye & Thierry Post, 2003. "Methodological Advances in DEA: A survey and an application for the Dutch electricity sector," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 57(4), pages 410-438.
- Jenkins, Larry & Anderson, Murray, 2003. "A multivariate statistical approach to reducing the number of variables in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 147(1), pages 51-61, May.
- Abdul Wadud & Ben White, 2000. "Farm household efficiency in Bangladesh: a comparison of stochastic frontier and DEA methods," Applied Economics, Taylor & Francis Journals, vol. 32(13), pages 1665-1673.
- William W. Cooper & Kyung Sam Park & Gang Yu, 1999. "IDEA and AR-IDEA: Models for Dealing with Imprecise Data in DEA," Management Science, INFORMS, vol. 45(4), pages 597-607, April.
- Rolf Färe & Shawna Grosskopf, 2000. "Theory and Application of Directional Distance Functions," Journal of Productivity Analysis, Springer, vol. 13(2), pages 93-103, March.
- Doyle, J. R. & Green, R. H. & Cook, W. D., 1995. "Upper and Lower Bound Evaluation of Multiattribute Objects: Comparison Models Using Linear Programming," Organizational Behavior and Human Decision Processes, Elsevier, vol. 64(3), pages 261-273, December.
When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:192:y:2009:i:2:p:647-657. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
If references are entirely missing, you can add them using this form.