Fuzzy sets as a basis for a theory of possibility
Fuzzy Sets and Systems
Interaction Design: Beyond Human Computer Interaction
Interaction Design: Beyond Human Computer Interaction
Incorporating affective customer needs for luxuriousness into product design attributes
Human Factors in Ergonomics & Manufacturing
Fuzzy approaches to quality function deployment for new product design
Fuzzy Sets and Systems
A fuzzy extension of Saaty's priority theory
Fuzzy Sets and Systems
A fuzzy integrated methodology for evaluating conceptual bridge design
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Scoring products from reviews through application of fuzzy techniques
Expert Systems with Applications: An International Journal
Calibrated fuzzy AHP for current bank account selection
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Often customers make their purchase decision based on price, quality and functionality of the product. Sometimes the decision is influenced by the perceived value, which is always subjective and emotion-driven. In order to ensure successful launch of a product, it is extremely important to predict the perceived value of design alternatives systematically based on the common language understood by both target users and designers. However, the index for communicating and evaluating such value from emotional perspective is not available in the literature. Therefore, the objective of this research is to extract key indexes of perceived value from emotional perspectives and develop an effective algorithm to evaluate products. First, through literature review and the interview of participants, many scenarios of purchase decision were collected. A focus group was invited to identify the essential elements that influence the perceived value of products. Followed by a large scale questionnaire survey and factor analysis, four indexes were extracted. These indexes, named as FASE Index in brief, included features, association, social-esteem, and engagement. Second, by combining the fuzzy mathematics and the pairwise comparison method, an evaluation model was developed. Third, the perception differences of sample products were conducted to verify the validity of FASE index. The findings of this study demonstrated that FASE index was effective for decision making in product design.