Abstract: To deal with the subjectivity in determining the importance weights of Customer Requirements (CRs) using experts decision and Analytic Hierarchy Process (AHP),according to the product-service requirement attribute and overall satisfaction degree data of different configurations,a new approach based on feature selection technique of conditional probability was proposed to identify the key CRs,determine the basic importance degree of CRs and analyze CRs'Kano attributes to modify importance degree.The current approaches for determining competitive priority ratings of CRs were based on comparison among companies,which was ignored the real CRs'performance of the researched company and had lower accuracy.By combining with maximal deviation approach and CRs'real performance,the competitive priority ratings of CRs were calculated,and were modified based on CRs'Kano attributes.Weighted arithmetic mean approach was used to determine the final importance ratings of CRs by combining the basic importance ratings and modified competitive priority ratings.A case study of CRs'importance weights determination in excavator product-service concept development was presented to illustrate the effectiveness of the proposed approach.

Key words: importance weights of customer requirements, feature selection, conditional probability, competitive analysis, maximal deviation approach

摘要： 针对专家决策和层次分析法等方法计算顾客需求重要度具有的主观性,根据不同配置的产品服务组合方案需求属性及整体满意度数据,采用基于条件概率的特征选择技术识别关键顾客需求,计算其基本重要度,并基于规则分析需求的Kano属性用于重要度调整。顾客需求竞争性重要度分析通常基于企业间的相对比较,忽视了本企业顾客需求的实际表现,其准确性较差。结合最大偏差方法和需求的实际表现计算顾客需求的竞争性重要度,依据顾客需求的Kano属性予以调整,采用加权算术平均方法整合顾客需求基本重要度和调整后的竞争性重要度来计算最终重要度。以挖掘机产品服务组合方案开发过程中顾客需求重要度的计算为例,验证了所提方法的有效性。

关键词: 顾客需求重要度, 特征选择, 条件概率, 竞争分析, 最大偏差方法