A Multicriteria Customer Classification Method in Supply Chain Management
Since Kraljic’s strategic matrix was applied to supply chain management, classification of items, suppliers, and customers has become of increasing interest to research and companies. The aim of this research is to develop an easily interpretable multicriteria classification matrix method and validate it in real-world scenarios with a robustness analysis. This method assigns alternatives to one of four classes defined by critical dimensions that integrate several evaluation criteria. Initially, a global search pre-classifies the alternatives using the PROMETHEE net flows. Then, two local searches are carried out that make use of the discriminant properties of the net flow signs to improve the quality of the assignments. This approach is specifically applied to pre-classified alternatives near the boundary between two or more categories. The method has been validated by segmenting thousands of customers. Four customer segments were identified: strategic, collaborative, transactional, and non-preferred. A comparison was made between the results and those derived from an alternative method. Through an extensive sensitivity analysis, the proposed method was shown to be robust to parameter variation, highlighting its reliability in real dynamic contexts. The method provides valuable, easily interpretable information, which constitutes the basis for developing personalised strategies to enhance customer relationship management.
Authors
- Concepción Maroto (ORCID: https://orcid.org/0000-0001-8512-3197)
- Marina Segura (ORCID: https://orcid.org/0000-0002-6068-960X)
- Felipe Barrera (ORCID: https://orcid.org/0000-0003-3236-6966)
Institutions
- Universidad Complutense de Madrid (ES)
- Universitat Politècnica de València (ES)
- Universidad Pontificia Comillas (ES)
Publication Details
- Journal
- Mathematics
- Published
- 2024-10-31
- DOI
- https://doi.org/10.3390/math12213427
- Citations
- 2
- Primary Topic
- Customer churn and segmentation
- Type
- article
- Field-Weighted Citation Impact
- 0.88