Influence of demand on supplier selection using the analytic hierarchy process: A case study validation in the textile industry

Background Supplier selection has emerged as an important activity regarding strategic purchasing with implications for the operational efficiency of both organisations and supply chains. Given the need to evaluate both qualitative and quantitative criteria for different supply alternatives, the decision-making process became more complex. Objectives In the present work, an adapted Analytic Hierarchy Process model is proposed for supplier selection, which is being validated within the context of a textile company. The multi-criteria decision support model was coded in Python and encompasses criteria, cost, quality, delivery time, sustainability, and history. Methods/Approach This model allocates weights to individual suppliers based on the diverse criteria considered. Four alternatives were considered as the chemical fabric dyeing pigment suppliers. Two different scenarios were considered to understand the influence of demand on the supplier selection problem. Results The cost is the most valued criterion in the supplier selection (0.493 for Scenario 1 and 0.426 for Scenario 2). The second most important criterion for regular demand is quality (0.224), whereas, for the increased demand scenario, delivery time (0.301) is the second most impactful criterion. Conclusions The application of the AHP for both tested scenarios resulted in a different priority, highlighting the adjustment capacity of the implemented model to different search parameterisations.