An evaluation of vendor selection models from a total cost of ownership perspective

Abstract Many different vendor selection models have been published in the purchasing literature. However there has been no systematic approach to compare the relative efficiency of the systems. In this paper we propose to use the concept of Total Cost of Ownership as a basis for comparing vendor selection models. We illustrate the comparison with a real life data set of the purchasing problem of ball bearings at Cockerill Sambre, a Belgian multinational company in the steel industry. From a Total Cost of Ownership perspective mathematical programming models outperform rating models and multiple item models generate better results than single item models for this specific case study.

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