Overall efficiency of operational process with undesirable outputs containing both series and parallel processes: A SBM network DEA model

Abstract

This paper proposes a new slacks-based measure network data envelopment analysis (SBM-NDEA) model with undesirable outputs to evaluate the performance of production processes that have complex structure containing both series and parallel processes. We demonstrate the proposed approach by evaluating Chinese commercial banks during 2012-2016. The operational process of these banks could be divided into deposit producing and deposit utilizing processes connected serially, while deposit utilizing process is further divided into profit generating and deposit reserve interest earning processes, which are parallel. The overall efficiency is decomposed into deposit producing and deposit utilizing efficiency. Deposit utilizing efficiency is further decomposed into profit generating and deposit reserve interest earning efficiency, respectively. Our empirical results suggest that the overall inefficiency is mainly from the profit generating process. The results also estimate the adjustment of variables for the network process of an inefficient bank.

Publication DOI: https://doi.org/10.1016/j.eswa.2021.115062
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: © 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: Chinese commercial banks,Data Envelopment Analysis,SBM-NDEA model,Series and parallel network,General Engineering,Computer Science Applications,Artificial Intelligence
Publication ISSN: 1873-6793
Last Modified: 13 Dec 2024 08:22
Date Deposited: 22 Apr 2021 09:17
Full Text Link:
Related URLs: https://linking ... 957417421005030 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2021-09-15
Published Online Date: 2021-04-20
Accepted Date: 2021-04-16
Authors: Shi, Xiao
Emrouznejad, Ali (ORCID Profile 0000-0001-8094-4244)
Yu, Wenqi

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