Abstract

Design has been deemed as a new driving force of innovation beside of technology and market recently, How to help an enterprise to capture user preference through product meaning innovation has attracted a wide research interest. The design-driven innovation theory puts forward the theoretical framework of hermeneutics to guide the radical meaning innovation research, but it loses sight of incremental meaning innovation. While in traditional research paradigm on Utilitarian-Hedonic dual customer perceived value, the conclusions are inconsistent due to the complexity and uncertainty of interaction between technology and meaning innovation. This paper eliminated or weakened the effect of technological innovation, took gold jewelry design as research subject and proposed the algorithms and model for product innovation of meaning based on the assumption that the incremental and radical meaning innovations are complementary. It adopted the grey correlation and grey clustering algorithm to merge similar image vocabularies and determine a design image board for gold jewelry, applied a quantitative scoring conjoint analysis algorithm to calculate the relative importance weights of series requirement attributes for each population, utilized the questionnaire survey to obtain big data, learned the design image preference for each population on basis of clustering analysis, mean value comparison algorithm and virtual regression model analysis, and finally clarified the users’ characteristic factors that may influence product design image preference as well as their influencing degree. The distributed algorithms and model can verify each other, and the design practice cases also verify their robustness. The combination of the algorithms and the model can not only solve the innovation of meaning for design-dominated products such as ornaments, but also provide reference for the research of incremental or radical meaning innovation of other products.

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