DESIGN AESTHETIC EVALUATION SYSTEM BASED ON CUSTOMIZED BIG DATA ANALYSIS FOR NEW PRODUCT DEVELOPMENT

摘要

The present invention relates to a customized big data analysis-based design aesthetic evaluation system for new product development. Based on big data information, the product developer establishes a product strategy by investigating, analyzing, and evaluating the aesthetics of the design for the developed product. and technology that allows design decisions to be made more efficiently. In order to achieve the above object, a customized big data analysis-based design aesthetic evaluation system for new product development according to the technical idea of the present invention provides an online web on the Internet, and inputs product information from an applicant through the online web receiving product information input unit; a product candidate group setting unit configured to search for brand information and design information related to the input product, and set a product category including at least two product candidate groups having certain brand and design information according to a preset condition; a survey information setting unit for setting survey information for a product candidate group included in the product category; a survey participant setting unit for setting a participant group by allocating survey participants to each candidate group included in the product category; an information collection unit configured to collect survey information for each product candidate group by providing the survey content for the corresponding product candidate group to the survey participant group set for each product candidate group through the online web; an analysis unit configured to obtain esthetic evaluation information for each product candidate group through a preset analysis program based on the collected survey information for each product candidate group; and an information providing unit for providing, to the applicant, esthetic evaluation information for each product candidate group obtained by the analysis unit through the online web; is configured, and the analysis unit is based on the collected survey information, but the survey information includes design aesthetics (measurement factor 1), perceived quality (measurement factor 2), consumer innovation propensity (measurement factor 3) , brand reputation (measurement factor 4) and purchase intention (measurement factor 5).