Measurement of Returns to Scale Using Non-Radial DEA Models
There are some specific features of the non-radial DEA (data envelopment analysis) models which cause some problems under the returns to scale measurement. In the scientific literature on DEA, some methods were suggested to deal with the returns to scale measurement in the non-radial DEA models. These methods are based on using Strong Complementary Slackness Conditions in the optimization theory. However, our investigation and computational experiments show that such methods increase computational complexity significantly and may generate “strange” results. In this paper, we propose and substantiate a direct method for the returns to scale measurement in the non-radial DEA models. Our computational experiments documented that the proposed method works reliably and efficiently on the real-life data sets.
|Date of creation:||07 Nov 2012|
|Date of revision:|
|Publication status:||Published as Krivonozhko, Vladimir E., Finn R. Førsund and Andrey V. Lychev, 'Measurement of Returns to Scale Using Non-Radial DEA Models' in european journal of operational research, 2014, pages 664-670.|
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"Returns-to-scale properties in DEA models: the fundamental role of interior points,"
Journal of Productivity Analysis,
Springer, vol. 38(2), pages 121-130, October.
- Krivonozhko, Vladimir & Førsund, Finn R., 2009. "Returms-to-scale Properties in DEA Models: The Fundamental Role of Interior Points," Memorandum 15/2009, Oslo University, Department of Economics.
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