Paper Info
Title
A new importance-performance analysis approach for customer satisfaction evaluation supporting PSS design
Abstract
Product-service system (PSS) design focuses on customer value and satisfaction more than traditional product or service design, and pays much attention to making improvement strategies due to the immaturity of engineering design methodology. Customer satisfaction evaluation attracts PSS providers' attentions in supporting PSS design. Importance-performance analysis (IPA) as an effective customer satisfaction evaluation tool is revised and used to identify PSS improvement strategies in this paper. The new IPA is proposed for three reasons. First, considering the fact that the attribute performance and importance are not independent variables and attribute performance has a nonlinear relationship with the overall satisfaction, Kano's model is integrated into IPA. Second, to overcome the drawbacks of statistic method and artificial neural network (ANN) in obtaining attribute importance implicitly, e.g. requiring sufficient and confident data, and overlooking the attribute original importance about attribute's contributing level to customer value realization, a set of adjustment models are proposed to revise the attributes original importance according to the Kano quality categories of attributes and the levels of attributes performance. Third, considering the mutual influence relationships among attributes, the proposed IPA takes these relationships into account by decision making trial and evaluation laboratory (DEMATEL). In addition, to deal with the uncertainty and vagueness in evaluation process, vague sets are employed in the revised IPA. A case study is carried out to demonstrate the effectiveness of the developed customer satisfaction evaluation approach.
Year
DOI
Venue
2012
10.1016/j.eswa.2011.08.038
Expert Syst. Appl.
Keywords
Field
DocType
customer satisfaction evaluation,evaluation process,developed customer satisfaction evaluation,new importance-performance analysis approach,pss design,attribute importance,evaluation laboratory,effective customer satisfaction evaluation,customer value,customer value realization,attribute original importance,attribute performance
Service design,Computer science,Knowledge management,Engineering design process,Variables,Artificial intelligence,Artificial neural network,Customer value,Customer satisfaction,Vagueness,Statistic,Operations research,Machine learning
Journal
Volume
Issue
ISSN
39
1
0957-4174
Citations 
PageRank 
References 
15
0.66
16
Authors
2
Name
Order
Citations
PageRank
Xiuli Geng1824.15
Xuening Chu223821.29