A review of the literature on DEA models under common set of weights
Journal of Modelling in Management
ISSN: 1746-5664
Article publication date: 20 February 2020
Issue publication date: 13 November 2020
Abstract
Purpose
Data envelopment analysis (DEA) is a mathematical method for the evaluation of the relative efficiency of a set of alternatives, which produces multiple outputs by consuming multiple inputs. Each unit is evaluated on the basis of the weighted output over the weighted input ratio with a free selection of weights and is allowed to select its own weighting scheme for both inputs and outputs so that the individual evaluation is optimized. However, several situations can be found in which the variability between weighting profiles is unsuitable. In those cases, it seems more appropriate to consider a common vector of weights. The purpose of this paper is to include a systematic revision of the existing literature regarding the procedures to determine a common set of weights (CSW) in the DEA context. The contributions are classified with respect to the methodology and to the main aim of the procedure. The discussion and findings of this paper provide insights into future research on the topic.
Design/methodology/approach
This paper includes a systematic revision of the existing literature about the procedures to determine a CSW in the DEA context. The contributions are classified with respect to the methodology and to the main aim of the procedure.
Findings
The discussion and findings of the literature review might insights into future research on the topic.
Originality/value
This papers revise the state of the art on the topic of models with CSW in DEA methodology and propose a systematic classification of the contributions with respect to several criteria. The paper would be useful for both theoretical and practical future research on the topic.
Keywords
Citation
Contreras, I. (2020), "A review of the literature on DEA models under common set of weights", Journal of Modelling in Management, Vol. 15 No. 4, pp. 1277-1300. https://doi.org/10.1108/JM2-02-2019-0043
Publisher
:Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited