Stochastic performance measurement in two-stage network processes: a data envelopment analysis approach

Title:

Stochastic performance measurement in two-stage network processes: a data envelopment analysis approach

Creator:

Amirteimoori, Alireza, Mehdizadeh, Saber, and Kordrostami, Sohrab

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:210a256c-2577-48a5-804f-f7b087037a6b
uuid:210a256c-2577-48a5-804f-f7b087037a6b
doi:10.14736/kyb-2022-2-0200

Subject:

stochastic DEA, chance-constrained models, two-stage network systems, and efficiency

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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.

Language:

English

Rights:

http://creativecommons.org/licenses/by-nc-sa/4.0/
policy:public

Coverage:

200-217

Source:

Kybernetika | 2022 Volume:58 | Number:2

Harvested from:

CDK

Metadata only:

false