Abstract
The outcomes from the previous chapters provide useful information from the literature of operations research and economics on measuring the performance of a set of homogenous firms with multiple input factors and multiple output factors as well as ranking and benchmarking firms. If firms are not homogenous, the situation is the same as when each factor has a different unit of measurement from one firm to another, and therefore, no meaningful discrimination can be expressed, unless the simple conditions of discrimination, which are represented in Sect. 2.3, are satisfied. In this chapter, the concepts introduced in the previous chapters are adapted with the literature and the philosophical background is discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261–1264.
Cooper, W. W., Seiford, L. M., & Zhu, J., (2011). Handbook on data envelopment analysis (International series in operations research & management science, 2nd ed.). New York: Springer.
Toloo, M., (2014). Data envelopment analysis with selected models and applications. Series on Advanced Economic Issues, Faculty of Economics, VŠB-TU, Ostrava.
Førsund, F. R., Lovell, C. K., & Schmidt, P. (1980). A survey of frontier production functions and of their relationship to efficiency measurement. Journal of econometrics, 13(1), 5–25.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429–444.
Charnes, A., Cooper, W. W., Golany, B., Seiford, L. M., & Stutz, J. (1985). Foundations of data envelopment analysis and Pareto-Koopmans empirical production functions. Journal of Econometrics, 30(1), 91–107.
Coelli, T. J., Rao, D. S. P., O'Donnell, C. J., & Battese, G. E. (2005). An introduction to efficiency and productivity analysis (2nd ed.). New York: Springer.
Debreu, G. (1951). The coefficient of resource utilization. Econometrica: Journal of the Econometric Society, 19, 273–292.
Färe, R., & Lovell, C. K. (1978). Measuring the technical efficiency of production. Journal of Economic theory, 19(1), 150–162.
Färe, R., Grosskopf, S., & Lovell, C. A. K. (1985). Measurement of efficiency of production. Boston: Kluwer-Nijhoff Publishing Co., Inc.
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 120, 253–290.
Førsund, F. R., & Hjalmarsson, L. (1974). On the measurement of productive efficiency. The Swedish Journal of Economics, 76, 141–154.
Khezrimotlagh, D. (2014). Profit efficiency by Kourosh and Arash model. Applied Mathematical Sciences, 8(24), 1165–1170.
Khezrimotlagh, D., Salleh, S., & Mohsenpour, Z. (2013). A new method for evaluating decision making units in DEA. Journal of the Operational Research Society, 65(1), 694–707.
Koopmans, T. C. (1951). Analysis of production as an efficient combination of activities. Activity analysis of production and allocation, 13, 33–37.
Pastor, J. T., Ruiz, J. L., & Sirvent, I. (1999). An enhanced DEA Russell graph efficiency measure. European Journal of Operational Research, 115(3), 596–607.
Sexton, T. R., Silkman, R. H., & Hogan, A. J. (1986). Data envelopment analysis: Critique and extensions. New Directions for Program Evaluation, 1986(32), 73–105.
Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European journal of operational research, 130(3), 498–509.
Tone, K. (2002). A strange case of the cost and allocative efficiencies in DEA. Journal of the Operational Research Society, 53, 1225–1231.
Zhu, J. (2014). Quantitative models for performance evaluation and benchmarking: data envelopment analysis with spreadsheets (Vol. 213). Cham: Springer.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Khezrimotlagh, D., Chen, Y. (2018). Data Envelopment Analysis. In: Decision Making and Performance Evaluation Using Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 269. Springer, Cham. https://doi.org/10.1007/978-3-319-76345-3_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-76345-3_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-76344-6
Online ISBN: 978-3-319-76345-3
eBook Packages: Business and ManagementBusiness and Management (R0)