Evaluation and Selection of Manufacturing Suppliers in B2B E-Commerce Environment

Abstract

The evaluation and selection of manufacturing suppliers in B2B e-commerce environment is summed up as a multiple-attribute decision-making problem. In B2B E-commerce environment, some performance indicators of manufacturing suppliers present uncertainty and could not be expressed with precise numeric values. Linguistic terms, preference orderings, or interval numbers are commonly used to express the performances of the suppliers accurately instead of crisp values when the available information is uncertain or incomplete. This paper proposes an approach to the selection of manufacturing suppliers in B2B E-commerce environment, where the attribute values in decision matrix are expressed with linguistic terms, preference orderings, and interval numbers. Firstly, the hybrid decision matrix is normalized by calculating the grey correlation coefficients of attribute values with the ideal values of attributes. Secondly, a deviation maximization model is proposed to determine the attribute weights, which is combined with those derived from the entropy method. Thirdly, the overall values of suppliers are calculated and their rankings are obtained. Finally, an example is used to illustrate the proposed approach.