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.

中文翻译：

---

B2B电子商务环境中制造供应商的评估和选择

B2B电子商务环境中制造供应商的评估和选择被总结为一个多属性决策问题。在B2B电子商务环境中，制造业供应商的某些绩效指标存在不确定性，无法用精确的数值表示。当可用信息不确定或不完整时，通常使用语言术语，偏好顺序或间隔号来准确地表示供应商的绩效，而不是使用明晰的值。本文提出了一种在B2B电子商务环境中选择制造供应商的方法，其中决策矩阵中的属性值用语言术语，偏好顺序和区间数表示。首先，通过计算属性值的灰色相关系数和属性的理想值，对混合决策矩阵进行归一化。其次，提出了一个偏差最大化模型来确定属性权重，并将其与从熵方法得出的权重相结合。第三，计算供应商的总价值并获得其排名。最后，通过一个例子来说明所提出的方法。