Vendor evaluation with performance variability: a max–min approach

The importance of incorporating multi-dimensional information into vendor evaluation is well established in the literature. Over the years, several multi-criteria techniques have been proposed for effective evaluation and selection of vendors. However, these models have not considered performance variability measures in evaluating alternative vendors. It is critical for the buyer to derive and incorporate such type of measures into the evaluation process because it provides for a more accurate portrayal of vendor's performance. This paper fills this gap by proposing a max–min productivity based approach that derives vendor performance variability measures, which are then utilized in a non-parametric statistical technique in identifying vendor groups for effective selection. The primary advantage of this technique is that it provides the buyer with effective alternative choices within a vendor group. Thus, allowing the buyer to base the final decision on other intangible factors that could not be incorporated into the analysis. The model application is demonstrated through a previously reported dataset from a pharmaceutical company.