Oday Jarjies, Hülya Bayrak, Kübra Durukan

Using of fractional factorial design $ (r ^{k-p} )$ in data envelopment analysis to selection of outputs and inputs

Abstract Data envelopment analysis (DEA) is a linear programming based tech- nique for measuring the relative performance of organisational units where the presence of multiple inputs and outputs makes comparisons difficult. We used, Morita and Avkiran propose after it has been de- veloped an input-output selection method that uses fractional factorial design, which is a statistical approach to find an optimal combination. Energy efficiency and greenhouse gas emissions are closely linked in the last two decades. We demonstrate the proposed method using data that increase energy efficiency and heating gas emissions in the European Union (EU) countries.

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[1] Charnes, A., Cooper, W.W. and Rhodes, E. Measuring the efficiency of decision making units. European Journal of Operational Research Vol. 2, 429-441, 1978. 686
[2] Box, G.E., Hunter, J.S., Hunter, W.G. Statistics for Experimenters: Design, Innovation, and Discovery, 2nd Edition. Wiley, 2005.
[3] Jahanshahloo, G.R. and Hosseinzadeh, L.F. Introduction to Data Envelopment Analysis, (forth coming) 2004.
[4] Taguchi, G., Wu, Y. and Chowdhury, S. Mahalanobis-Taguchi System. McGraw-Hill Pro- fessional, 2000.
[5] Morita, H. and Haba, Y. Variable selection in data envelopment analysis based on external information. Proceedings of the eighth Czech-Japan Seminar 2005 on Data Analysis and Decision Making under Uncertainty, 181187, 2005.
[6] Morita, H. and Avrikan, N.K. Selecting Input and Output Variables in Data envelopment analysis by designing statictcal experiments. Journal of the Operations Research Society of Japan, 52(2), 163-173, 2009.
[7] Edirisinghe, N.C.P. and Zhang, X. Generalized DEA model of fundamental analysis and its application to portfolio optimization. Journal of Banking & Finance, 31, 33113335, 2007.
[8] Seiford, L.M. and Zhu, J. Context-dependent data envelopment analysis: measuring attrac- tiveness and progress. Omega, 31, 397408, 2003.
[9] Cooper, W.W, Seiford, L.M. and Tone, K. Data Envelopment Analysis. Kluwer Academic Publishers, 2000.
[10] http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/themes.
[11] http://www.eia.gov/countries/data.cfm.
[12] http://en.wikipedia.org/wiki/Mahalanobis_distance.

Hacettepe Journal of Mathematics and Statistics-Cover

Yayın Aralığı: Yılda 6 Sayı
Başlangıç: 2002
Yayıncı: Hacettepe Üniversitesi Fen Fakultesi

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