4.5 Article

Application of AHP and Taguchi loss functions in supply chain

Journal

INDUSTRIAL MANAGEMENT & DATA SYSTEMS
Volume 110, Issue 8-9, Pages 1251-1269

Publisher

EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/02635571011077861

Keywords

Supplier evaluation; Taguchi methods; Outsourcing; Decision making

Ask authors/readers for more resources

Purpose - The purpose of this paper is to develop a decision model to help decision makers with selection of the appropriate supplier. Design/methodology/approach - Supplier selection is a multi-criteria decision-making process encompassing various tangible and intangible factors. Both risks and benefits of using a vendor in supply chain are identified for inclusion in the evaluation process. Since these factors can be objective and subjective, a hybrid approach that applies to both quantitative and qualitative factors is used in the development of the model. Taguchi loss functions are used to measure performance of each supplier candidate with respect to the risks and benefits. Analytical hierarchy process (AHP) is used to determine the relative importance of these factors to the decision maker. The weighted loss scores are then calculated for each supplier by using the relative importance as the weights. The composite weighted loss scores are used for ranking of the suppliers. The supplier with the smallest loss score is recommended for selection. Findings - Inclusion of both risk and benefit categories in the evaluation process provides a comprehensive decision tool. Practical implications - The proposed model provides guidelines for supply chain managers to make an informed decision regarding supplier selection. Originality/value - Combining Taguchi loss function and AHP provides a novel approach for ranking of potential suppliers for outsourcing purposes.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available