Integrating Kano Model, AHP, and QFD Methods for New Product Development Based on Text Mining, Intuitionistic Fuzzy Sets, and Customers Satisfaction

Ming Li · Jie Zhang

42 citations0/0 files storedMathematical Problems in Engineering

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Quality Function Deployment in Product Design Multi-Criteria Decision Making Color perception and design

Abstract

Online reviews are crucial to any online business that wants to increase sales on the Internet. Customer reviews have information about product attributes, customer requirements (CRs), and shopping experience; mining reviews provide the direction of decision-making for new product development and design (NPDD). Besides, the information of customer preference has vagueness and uncertainty, and the accuracy of decision-making information directly affects the success of NPDD. This paper proposed a methodology that integrates the Kano model (KM), analytic hierarchy process (AHP), and quality function deployment (QFD) methods with intuitionistic fuzzy set (IFS) to solve decision-making problems in NPDD. By the new method, the web crawler technology was first applied to e-commerce web sites to collect raw data, and the representative CRs were extracted through combining LDA model with Apriori algorithm. Second, the intuitionistic fuzzy Kano model (IFKM) is proposed to evaluate adjustment coefficient of CRs and Kano categories via customer preference membership functions. Thirdly, overall weights which contained emotional needs (ENs) and functional needs (FNs) are obtained via intuitionistic fuzzy analytic hierarchy process (IFAHP); thus, the adjusted weights are calculated from IFKM and IFAHP. Next, the intuitionistic fuzzy quality function deployment (IFQFD) is proposed to acquire engineering characteristics (ECs) of weights through combining competition benchmarks and based on technical benchmarks to make goals for a company’s NPDD. Finally, the method was applied to study vertical-configured air conditioner (VAC) as an example. The results showed that the application of text mining and IFS to improve CS is both reliable and scientific.

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References

1986Intuitionistic fuzzy sets 1984Attractive Quality and Must-Be Quality 1983A fuzzy extension of Saaty's priority theory 2007Intuitionistic Fuzzy Aggregation Operators 1999Intuitionistic Fuzzy Sets 1992Fuzzy Multiple Attribute Decision Making 2000Strengthening the Satisfaction-Profit Chain 1995Kansei Engineering: A new ergonomic consumer-oriented technology for product development

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