The purpose of this paper is to study online clothing consumers' behaviour and their visual attention mechanism to provide objective and quantitative evidences for the display and sales of online clothing.
Firstly, this paper conducted a Focus Group Methodology and questionnaire survey to obtain concern factors of online clothing. Secondly, the online clothing's bottom-up visual stimulation and consumer's top-down expectations were analysed, and proposed the hypotheses about significant stimulus of clothing and consumer's emotional experience. Thirdly, the online clothing consumer's visual attention rules and related qualitative results were discussed, and proposed visual attention law for online clothing. Finally, took the company's 84th quarter clothing design practices as research projects, all the hypotheses were demonstrated through eye movement physiology experiments, online clothing trial release and node sales data.
Online clothing has unique visual display ways compared with other online products such as online advertising, brands and food packaging. Clothing patterns of unfamiliar (fresh) font shapes are more attractive than the patterns of familiar fonts. The cause of the bottom-up visual attention bias is the contrast between clothing features, not the absolute stimulus intensity of the features themselves. Clothing factors can change their emotional experience from no difference to significant difference under the influence of other clothing factors.
Put forward hypotheses of online clothing consumer behaviour and its visual attention mechanism, provided objective and quantitative evidences through eye tracker.
Funding: This work is supported in part by the Guangzhou Science and Technology Project under Grant 201802020011, in part by the Guangdong Provincial Key Laboratory of Cyber-Physical Systems, and in part by the National and Local Joint Engineering Research Center of Intelligent Manufacturing Cyber-Physical Systems.
Mo, X., Sun, E. and Yang, X. (2021), "Consumer visual attention and behaviour of online clothing", International Journal of Clothing Science and Technology, Vol. 33 No. 3, pp. 305-320. https://doi.org/10.1108/IJCST-02-2020-0029
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