Applying the Linguistic Strategy-Oriented Aggregation Approach to Determine the Supplier Performance with Ordinal and Cardinal Data Forms

Supply chain management is a new and evolving paradigm for enterprises to cope with international competition and to improve global logistics efficiency. The suppliers’ performances affect not only supply chain execution results but also the profit capability and business survivability. However, suppliers’ performance assessment always involves a large dimension of supplier behaviors. Information on supplier behaviors is often difficult to be accurately demonstrated as quantitative data. For this reason, the study employs a 2-tuple linguistic variable to perform the initial evaluation and final assessment while keeping track of both linguistic information and data, which can avoid a tied result. Additionally, the modified linguistic ordered weighted averaging (M-LOWA) operator with maximum entropy is used to derive the maximum aggregation value under the current business strategy to reflect on the criteria. The focal company can then rapidly rely on the assessment results to represent the performance of suppliers and provide integrated information to decision makers. This study draws the complete framework for the issue of supplier performance assessment without limitations on categories of variables and scales.