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DGRA: Multi-sourcing and Supplier Classification through Dynamic Grey Relational Analysis Method

ABSTRACT

Most multiple criteria decision analysis methods do not guide decision-makers beyond supplier evaluation (by providing them with a ranking), and supplier selection and classification is effectively the decision-makers’ job. The relative difference between the performance of different suppliers is usually overlooked even though this fact is functionally important in real-life multi-sourcing decisions. The current study proposed a system that not only evaluates suppliers through the Dynamic Grey Relational Analysis (DGRA) model but also helps the decision-makers to distinguish the most reliable suppliers from the least reliable ones using a novel Rank Product Score (RPS), which allows the decision-makers to visualize the performance of each supplier on an exponential curve. Unlike the benchmark models, the normalization of input data is not mandatory in the proposed model, and uncertainty in input can be quantified even when it is not explicitly visible in the input. The new framework enables the procurement managers looking for strategic global multi-sourcing to select the suppliers from the top cluster on this curve. The proposed framework is tested on a practical case from a big engineering organization with diverse suppliers, demonstrating its validity. The comparative analyses on three dimensions confirm the effectiveness and efficiency of the proposed framework. The framework is of immediate practical use for building intelligent decision support systems in the purchasing environment.

Keywords: Decision Support System; Multiple Criteria Decision Analysis; Supplier Selection Problem; Uncertainty Analysis; Grey Model; Grey Relational Analysis

Read the full paper at Dynamic Grey Relational Analysis for Multiple Attribute Decision-Making