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A Fuzzy Decision Model for Evaluating Centralized Purchasing Process Performance
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DOI：10.3390/logistics10060141.png)
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Abstract
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Background: Evaluating centralized purchasing performance is a complex multi-criteria decision-making problem involving uncertainty, linguistic assessments, and subjective judgments from internal clients. Existing approaches provide limited support for handling these characteristics simultaneously. Methods: This study proposes a Mamdani fuzzy inference model integrating four criteria: Service Quality, Responsiveness, Compliance, and Collaboration. The fuzzy rule base was developed using expert knowledge and organizational evaluation practices. The model was applied to a real industrial case study based on an annual evaluation conducted collaboratively by four internal evaluators. Results: The model transformed qualitative assessments into an interpretable performance score while capturing interactions among evaluation criteria and handling uncertainty in the evaluation process. Conclusions: The proposed approach provides a structured decision-support framework for evaluating centralized purchasing performance. It enables the integration of linguistic assessments and expert knowledge, offering a flexible and coherent evaluation tool for industrial environments.
Keywords:
fuzzy logic
decision-making
purchasing process
performance evaluation
multicriteria evaluation
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