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.
Highlights
As market competition intensifies and product life cycles constantly get shorten, new product design and development (NPDD) methodology has become an effective way for enterprises to respond to market competition
We proposed that intuitionistic fuzzy Kano model (IFKM) can obtain customer requirements (CRs) preference, which includes affirmation, negation, hesitation, and priority, which effectively express voice of customer (VOC)
We proposed a new method for NPDD based on text mining, customer satisfaction (CS), and intuitionistic fuzzy set (IFS)
Summary
As market competition intensifies and product life cycles constantly get shorten, new product design and development (NPDD) methodology has become an effective way for enterprises to respond to market competition. Newman and Patel [3] mentioned three types of product attributes that are associated with customer requirements (CRs), namely, the attributes of basic function, the attributes of convenient function, and the attributes of psychological satisfaction. Both attributes of basic function and convenient function belong to customer functional requirements, and Mathematical Problems in Engineering the attributes of psychological satisfaction are the higher psychological response of customer experience; that is, the product forms will further promote CS after functions meet customer’s basic requirements, thereby resonating with the customer’s psychology. In today’s environment in which CRs are diversified and personalized, emotional needs (ENs) become increasingly important in customer decision-making to purchase products. is requires NPDD to fulfill the customers’ basic function needs (FNs) for products, and to satisfy customers ENs. erefore, enterprises should pay attention to both ENs and FNs in NPDD
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