A design science research methodology for developing an integrated model supplier reduction and grouping parts using GT-based algorithm

Abstract

Purpose

This study aims to propose a quantitative approach to reduce the number of suppliers in an organization. This method is based on grouping, and different parts are grouped based on the capabilities they need and are allocated to suppliers who have these capabilities. In this regard, an integrated model for supplier reduction and grouping of parts using a group technology-based algorithm is proposed.

Design/methodology/approach

Design science research methodology was used in this study. The main problem under investigation is a large number of suppliers in an organization’s supply base. The proposed model was used to solve this problem in the electric motor industry.

Findings

The results of implementing the proposed model in the electric motor industry showed that reducing suppliers had a significant effect on reducing cost, increasing information sharing, increasing supplier innovation and technology, enhancing the relationship between buyers and sellers and reducing risks in the production process.

Practical implications

From a managerial point of view, reducing the number of suppliers plays an important role in the company’s overall strategy, and seems to be a prerequisite for building a strong supplier partnership and an effective supply chain, and will have many benefits for the focal company and suppliers.

Originality/value

To the best of the authors’ knowledge, grouping and formation of product families have never been performed based on the similarity of the operational capabilities required for producing parts, and it has not been addressed as a solution for reducing suppliers.

Citation

Dehghani, M., Akhavan, P. and Abbasi, M. (2023), "A design science research methodology for developing an integrated model supplier reduction and grouping parts using GT-based algorithm", Journal of Business & Industrial Marketing, Vol. 38 No. 9, pp. 1911-1926. https://doi.org/10.1108/JBIM-05-2022-0216