A full investigation of the directional congestion in data envelopment analysis


One of interesting subjects in Data Envelopment Analysis (DEA) is estimation of congestion of Decision Making Units (DMUs). Congestion is evidenced when decreases (increases) in some inputs result in increases (decreases) in some outputs without worsening (improving) any other input/output. Most of the existing methods for measuring the congestion of DMUs utilize the traditional definition of congestion and assume that inputs and outputs change with the same proportion. Therefore, the important question that arises is whether congestion will occur or not if the decision maker (DM) increases or decreases the inputs dis-proportionally. This means that, the traditional definition of congestion in DEA may be unable to measure the congestion of units with multiple inputs and outputs. This paper focuses on the directional congestion and proposes methods for recognizing the directional congestion using DEA models. To do this, we consider two different scenarios: (i) just the input direction is available. (ii) none of the input and output directions are available. For each scenario, we propose a method consists in systems of inequalities or linear programming problems for estimation of the directional congestion. The validity of the proposed methods are demonstrated utilizing two numerical examples.

Publication DOI: https://doi.org/10.1051/ro/2019092
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > Aston Business School
Additional Information: © EDP Sciences, ROADEF, SMAI 2021.
Uncontrolled Keywords: Data envelopment analysis (DEA),Decision making units,Directional congestion,Theoretical Computer Science,Computer Science Applications,Management Science and Operations Research
Publication ISSN: 1290-3868
Last Modified: 08 Jul 2024 16:22
Date Deposited: 11 Oct 2019 12:59
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.rai ... 1051/ro/2019092 (Publisher URL)
PURE Output Type: Article
Published Date: 2021-03-02
Accepted Date: 2019-09-18
Authors: Khezri, Somayeh
Dehnokhalaji, Akram (ORCID Profile 0000-0002-2751-0719)
Hosseinzadeh Lotfi, Farhad



Version: Accepted Version

Access Restriction: Restricted to Registered users only


Version: Published Version

| Preview

Export / Share Citation


Additional statistics for this record