DEA-based benchmarking models in supply chain management: an application-oriented literature review

October 21, 2017
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Data Envelopment Analysis (DEA) is a mathematical methodology for benchmarking a group of entities in a group. The inputs of a DEA model are the resources that the entity consumes, and the outputs of the outputs are the desired outcomes generated by the entity, by using the inputs. DEA returns important benchmarking metrics, including efficiency score, reference set, and projections. While DEA has been extensively applied in supply chain management (SCM) as well as a diverse range of other fields, it is not clear what has been done in the literature in the past, especially given the domain, the model details, and the country of application. Also, it is not clear what would be an acceptable number of DMUs in comparison to existing research. This paper follows a recipe-based approach, listing the main characteristics of the DEA models for supply chain management. This way, practitioners in the field can build their own models without having to perform detailed literature search. Further guidelines are also provided in the paper for practitioners, regarding the application of DEA in SCM benchmarking.

Ertek, G., Akyurt, N., Tillem, G., 2012, “Dea-based benchmarking models in supply chain management: an application-oriented literature review”, X. International Logistics and Supply Chain Congress 2012, November 8-9, Istanbul, Turkey.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

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