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Influence of Demand on Supplier Selection Using the Analytic Hierarchy Process: A Case Study Validation in the Textile Industry

Open Access
|Sep 2024

Abstract

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.

DOI: https://doi.org/10.2478/bsrj-2024-0009 | Journal eISSN: 1847-9375 | Journal ISSN: 1847-8344
Language: English
Page range: 178 - 200
Submitted on: May 6, 2024
Accepted on: May 20, 2024
Published on: Sep 26, 2024
Published by: IRENET - Society for Advancing Innovation and Research in Economy
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2024 Bruna Ramos, João Silva, António Vila-Chã, Henrique Azevedo, João Ramos, Ana Cristina Ferreira, published by IRENET - Society for Advancing Innovation and Research in Economy
This work is licensed under the Creative Commons Attribution 4.0 License.