Applying 2-Tuple Multigranularity Linguistic Variables to Determine the Supply Performance in Dynamic Environment Based on Product-Oriented Strategy

Supply performance assessment is not only the core mechanism for supplier management, but also the major task for enterprises in implementing supply chain management. Consequently, supply chain system implementation should rely on the results of supply performance assessments to supervise suppliers. However, supply performance assessment is always concerned with numerous supply behaviors, and the information obtained from these supply behaviors often varies during the measurement timeframe. Because of uncertainty and inaccuracy, the numerical data are not appropriate for demonstrating dynamic information. This study employs 2-tuple multigranularity linguistic variables to deal with dynamic information appropriately and assess supply performance, and even permits decision makers to introduce different linguistic terms (linguistic scale) based on consideration of supply behavior characteristics. The 2-tuple multigranularity linguistic variables present the information via linguistic and numeric results, both where the linguistic result could express the variation of dynamic information appropriately, and where the numerical result could further reflect the difference based on the same linguistic result to improve the sensitivity. Additionally, this study also employs a fuzzy linguistic quantifier to simulate the decision criteria based on the product strategy to further obtain the modified linguistic ordered weighted averaging operator with maximum entropy that will be exercised to aggregate the 2-tuple linguistic information. This investigation provides decision makers with rapid access to complete, and integrated information on the practical supply performance of suppliers as appropriate.