文献类型：期刊文献

英文题名：Research on product color design decision driven by brand image

作者：Zhang, Xinxin[1,4];Yang, Minggang[1];Su, Jianning[2,3];Yang, Wenjin[3];Qiu, Kai[3]

机构：[1]East China Univ Sci & Technol, Sch Art Design & Media, M Box 286,130,Meilong Rd, Shanghai 200237, Peoples R China;[2]Lanzhou Univ Technol, Sch Design Art, Lanzhou, Peoples R China;[3]Lanzhou Univ Technol, Sch Mech & Elect Engn, Lanzhou, Peoples R China;[4]Hebei Univ Technol, Sch Architecture & Art Design, Tianjin 300401, Peoples R China

年份：2020

卷号：45

期号：6

起止页码：1202

外文期刊名：COLOR RESEARCH AND APPLICATION

收录：;EI(收录号：20203008970124);WOS:【SSCI(收录号:WOS:000550449400001)，SCI-EXPANDED(收录号:WOS:000550449400001)】；

语种：英文

外文关键词：color brand image; gray theory; Kansei engineering; trend prediction; user's emotional demands

摘要：As one of the most important visual characteristics in a product system, color can arouse the user's emotional demands quickly. Due to the complexity of the user's emotional needs mining process, it can be expressed by color image adjectives. Meanwhile, product color trends that meet the user's emotional demands may help decision makers to anticipate a new market positioning and reduce the blindness in the product color design. In this study, the Gray theory combined with the Kansei engineering was used to mine the macro and microscopic factors in product color design decision process based on the product color brand image. The results showed that the constructed method could be used to guide the product color design that was to meet the user's emotional needs comprehensively and quickly. The method solved the problems that exist in the current product color trend prediction research and improved the accuracy of the correlation mining between product color design elements and brand image. Lastly, the color design of the mid-range sedan was taken as an example to prove the feasibility of the research approach. This is a new attempt to guide product color design decisions in two aspects, one is known from the results of product color trends quantitative prediction, and the other one comes from the correlation calculation between product color design elements and brand image.