Multi-Dependent Criteria Supplier Selection with Uncertain Performance Evaluation

Abstract

One of the key to improve logistics efficiency of a firm is to select appropriate supplier. In order to select supplier, there are many criteria involved. Also supplier with greatest average performance does not confirm to be the most suitable one because of uncertainties. Therefore the objectives of this research are to develop decision matrix for selecting supplier based on mean-variance-skewness and identify influential criteria of supplier selection problem for Thai electronics industry. In this research, the set of criteria comprises of 6 main criteria with total of 13 sub-criteria. The data was collected via in-depth interview and questionnaire. The first three criteria which have highest important weight are lead time, follows by price, and continuous improvement ability with important weight equal to 0.0910, 0.0869 and 0.0806, respectively. To analyze skewness effect, it is found that skewness has effect on performance more than average and SD. Skewness can better distinguish between first and less priority supplier than considering only mean and SD. This result indicates that skewness really plays important role in supplier performance and should not be ignored when evaluating suppliers. Therefore, this research develops decision matrix for supplier selection including skewness, namely, Success Mode Skewness Analysis (SMSA). The validation of developed decision matrix shows that including skewness into consideration is more valid than considering only mean and SD. The findings have significant implication for both of suppliers and buyers in terms of improving logistics efficiency