Improving supplier performance using a comprehensive scheme

Abstract

Improving and coordinating buyer and supplier efforts to increase productivity and competitive advantage in a supply chain is an important issue. Numerous studies have proposed models, principles and criteria for supplier evaluation and selection. Hence, evaluating and improving supplier performance are important when building long-term supply chain competitiveness. This study presents a novel and comprehensive framework that illustrates the linkages between evaluating supplier performance and planning improvements. The proposed framework comprises four parts: building an evaluation model, evaluating supplier performance based on the buyer perspective, evaluating supplier performance based on the supplier perspective and scheduling improvement tasks. This study applies a hybrid genetic algorithm to help suppliers schedule improvement tasks based on the evaluation findings. Finally, evaluation data of a light-emitting diode (LED) manufacturer in Taiwan is used to interpret the procedure and verify model effectiveness.

Keywords:

• supplier performance
• improvement planning
• genetic algorithm