Integrating fuzzy Kano model and fuzzy importance–performance analysis to analyse the attractive factors of new products. (May 2020)

• Record Type: Journal Article
• Authors: Xi, Le; Zhang, Hui; Li, Sunan; Cheng, Jianxin
• Is Part Of: International journal of distributed sensor networks. Volume 16:Number 5(2020)
• Publication Date: 2020-05
• Subjects: Attractive factor -- evaluation grid method -- fuzzy Kano model -- fuzzy importance–performance analysis -- product development; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147720920222
• Languages: English
• ISSNs: 1550-1329

Abstract

The sorting mechanism underlying the traditional evaluation grid method with attractive factors mainly represents the time or the paired comparison method. However, the current approach employed to identify abstract factors of attractiveness may not be comprehensive. The objective of this article is to propose a hybrid method with an integrated fuzzy Kano model and fuzzy importance–performance analysis to evaluate attractive factors. Fuzzy importance–performance analysis is a more accurate quantitative–qualitative method for two-dimensional analysis, and integrated fuzzy Kano model compensates for the low-resolution problem of the traditional Kano model. A combination of both models arrives at a more comprehensive and reliable evaluation grid method evaluation mechanism. The results indicate that the attractive factors sorted through integrated fuzzy Kano model–fuzzy importance–performance analysis have deconstructed abstract factors and feature factors of the customer service robot. Moreover, the key factors of the products sorted by through integrated fuzzy Kano model–fuzzy importance–performance analysis provide a better understanding of customer expectations associated with the products, which consequently enables developers and designers to accurately understand the design style and conceive new ideas.