The present invention relates to a design esthetic evaluation system based on customized big data analysis for new product development, by investigating, analyzing, and evaluating the esthetics of a design for a developed product based on big data information, so that a product developer establishes a product strategy. And a technology for making design decisions more efficient. In order to achieve the above object, the 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 product information is input from the 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 predetermined brand and design information according to a preset condition; A survey information setting unit configured to set the content of survey information on product candidates included in the product category; A survey participant setting unit for setting a participant group by assigning survey participants to each product candidate group included in the product category; An information collection unit for collecting survey information for each product candidate group by providing survey information on a corresponding product candidate group to a group of survey participants set for each product candidate group through the online web; An analysis unit that acquires esthetic evaluation information for each product candidate group through a preset analysis program based on the collected product candidate group survey information; And an information providing unit for providing the applicant with esthetic evaluation information for each product candidate group obtained by the analysis unit through the online web. 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 tendency (measurement factor 3). , Brand reputation (measurement factor 4) and purchase intention (measurement factor 5), and the analysis program is characterized in that it is a Statistical Package for the Social Sciences (SSPS) regression analysis program.
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