This paper aims to apply a hybrid method of supplier selection to a well-known Turkish company operating in the appliance industry. The data envelopment analytic hierarchy process (DEAHP) methodology developed by Ramanathan, R., (Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process. Computers and Operations Research, 2006 Ramanathan, R. 2006. Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process. Comput. Oper. Res., 33: 1289–1307. [Crossref], [Web of Science ®] , [Google Scholar], 33, 1289–1307) was chosen as the survey method. In this method, the data envelopment analysis (DEA) approach is embedded into analytic hierarchy process (AHP) methodology. This research concluded that the DEAHP method outperforms the AHP method for supplier selection despite the findings that the AHP model suggested supplier 1 to be the best supplier, contradicting the suggestion made by the DEAHP model and the real action taken by BEKO in selecting supplier 2. These findings imply that DEAHP criteria reflect closer to the real optimum of the decision made. Drawing on a real case our study has supported Ramanathan's (2006 Ramanathan, R. 2006. Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process. Comput. Oper. Res., 33: 1289–1307. [Crossref], [Web of Science ®] , [Google Scholar]) work confirming the view that the DEAHP method provides a better decision than the AHP method for supplier selection. Because the DEAHP model is relatively more cumbersome to apply, its application will be more appropriate for high-value components where stringent purchasing criteria are required. In contrast, AHP would remain to be an appropriate approach for relatively lower value components (C class). The novelty of this research lies in the application of a hybrid approach to a real industry case–the DEAHP method for supplier selection, where little has been done on this subject. This study has dealt with one of the most important subjects in supply chain management providing a better decision for supplier selection using appropriate quantitative approaches.
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