Geodesic
Stochastic performance measurement in two-stage network processes: A data envelopment analysis approach
Kybernetika, Tome 58 (2022) no. 2, pp. 200-217.

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In classic data envelopment analysis models, two-stage network structures are studied in cases in which the input/output data set are deterministic. In many real applications, however, we face uncertainty. This paper proposes a two-stage network DEA model when the input/output data are stochastic. A stochastic two-stage network DEA model is formulated based on the chance-constrained programming. Linearization techniques and the assumption of single underlying factor of the data are used to construct the equivalent deterministic linear programming model. The relationship between the stochastic efficiency of each stage and stochastic centralized efficiency of the whole process, at different confidence levels, is discussed. To illustrate the real applicability of the proposed approach, a real case on 16 commercial banks in China is given.
DOI : 10.14736/kyb-2022-2-0200
Classification : 90B50, 90C05
Keywords: stochastic DEA; chance-constrained models; two-stage network systems; efficiency 
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Amirteimoori, Alireza; Mehdizadeh, Saber; Kordrostami, Sohrab. Stochastic performance measurement in two-stage network processes: A data envelopment analysis approach. Kybernetika, Tome 58 (2022) no. 2, pp. 200-217. doi : 10.14736/kyb-2022-2-0200. http://geodesic.mathdoc.fr/articles/10.14736/kyb-2022-2-0200/

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