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Supplier evaluation and classification in a Colombian motorcycle assembly company using data envelopment analysis

Supplier evaluation and classification in a Colombian motorcycle assembly company using data... PurposeThe purpose of this paper is to present a case study in which data envelopment analysis (DEA) is used to evaluate and classify the suppliers of a Colombian motorcycle assembly company. This tool allows the integration of several attributes into single performance measures (cross-efficiency and diversity efficiency) and subsequent classification based on the values obtained for these two metrics.Design/methodology/approachThe classification uses a methodology based on two main tools. The first is an input-oriented cross-efficiency DEA model with ordinal variables to evaluate the suppliers’ performance, and the second is a classification of these into categories that identifies those with good performance for features that make them outstanding.FindingsThe assembly company segments its suppliers according to supply frequency. The results show that suppliers working under a just-in-time system achieve superior performance with respect to other suppliers.Practical implicationsThe application of this methodology in a real-world case illustrates how DEA can be a useful tool to support the evaluation and classification of suppliers (a process of increasing complexity given the current trend to include multiple strategic measures together with classical operational measures). Moreover, the methodology illustrated in the study can be adapted to other similar settings.Originality/valueThe main contributions of this paper are twofold. First, to the best of our knowledge, this is the first study to illustrate the use of DEA in a real case related to supplier evaluation. Second, the presence of ordinal variables (e.g. quality or environmental ratings) gives rise to DEA variants seldom used in this context. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Academia Revista Latinoamericana de Administración Emerald Publishing

Supplier evaluation and classification in a Colombian motorcycle assembly company using data envelopment analysis

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References (77)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1012-8255
DOI
10.1108/ARLA-04-2017-0107
Publisher site
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Abstract

PurposeThe purpose of this paper is to present a case study in which data envelopment analysis (DEA) is used to evaluate and classify the suppliers of a Colombian motorcycle assembly company. This tool allows the integration of several attributes into single performance measures (cross-efficiency and diversity efficiency) and subsequent classification based on the values obtained for these two metrics.Design/methodology/approachThe classification uses a methodology based on two main tools. The first is an input-oriented cross-efficiency DEA model with ordinal variables to evaluate the suppliers’ performance, and the second is a classification of these into categories that identifies those with good performance for features that make them outstanding.FindingsThe assembly company segments its suppliers according to supply frequency. The results show that suppliers working under a just-in-time system achieve superior performance with respect to other suppliers.Practical implicationsThe application of this methodology in a real-world case illustrates how DEA can be a useful tool to support the evaluation and classification of suppliers (a process of increasing complexity given the current trend to include multiple strategic measures together with classical operational measures). Moreover, the methodology illustrated in the study can be adapted to other similar settings.Originality/valueThe main contributions of this paper are twofold. First, to the best of our knowledge, this is the first study to illustrate the use of DEA in a real case related to supplier evaluation. Second, the presence of ordinal variables (e.g. quality or environmental ratings) gives rise to DEA variants seldom used in this context.

Journal

Academia Revista Latinoamericana de Administración – Emerald Publishing

Published: Jun 3, 2019

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