SUPPLIER SEGMENTATION: A CASE STUDY OF MOZAMBICAN CASSAVA FARMERS

Authors

  • Ntebaleng S Matshabaphala Department of Industrial Engineering, Stellenbosch University, South Africa
  • Jacomine Grobler Department of Industrial Engineering, Stellenbosch University, South Africa https://orcid.org/0000-0002-1868-0759

DOI:

https://doi.org/10.7166/32-1-2459

Keywords:

Clustering, Cassava, Supplier segmentation

Abstract

Over 3 000 Mozambican smallholder farmers supply cassava to Company XYZ. XYZ needs an effective supplier segmentation method to gain insight into how it should direct its resources for the greatest impact. This paper describes the application of the k-means algorithm, agglomerative hierarchical clustering, and a self-organising map with ward clustering to segment these cassava suppliers. The insights gained from the cluster analysis are then used to provide recommendations and suggest suitable intervention strategies to manage each segment of suppliers. The proposed method offers users the basis of a supplier segmentation system that is more robust than commonly used qualitative supplier segmentation models.

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Author Biographies

Ntebaleng S Matshabaphala, Department of Industrial Engineering, Stellenbosch University, South Africa

Ntebaleng is a M Eng (Industrial Engineering) student at Stellenbosch University.

Jacomine Grobler, Department of Industrial Engineering, Stellenbosch University, South Africa

Jacomine Grobler is an Associate Professor at Stellenbosch University.

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Published

2021-05-28

How to Cite

Matshabaphala, N. S., & Grobler, J. (2021). SUPPLIER SEGMENTATION: A CASE STUDY OF MOZAMBICAN CASSAVA FARMERS. The South African Journal of Industrial Engineering, 32(1), 196–209. https://doi.org/10.7166/32-1-2459

Issue

Vol. 32 No. 1 (2021)

Section

Case Studies

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