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Original Articles

Using an Eye-Tracking Approach to Explore Gender Differences in Visual Attention and Shopping Attitudes in an Online Shopping Environment

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Pages 15-24 | Published online: 24 Apr 2017
 

ABSTRACT

Growth in online marketing has been unprecedented, and mainstream shopping is shifting from traditional stores to online shopping channels. However, many aspects of online consumer behavior remain unaddressed. In particular, the effects of gender differences in visual attention on shopping attitudes are a great challenge in online retailers’ attempts to understand consumers’ cognitive processing and strategies. This study was designed to investigate the effects of gender on visual attention to online shopping information and its influence on attitudes about the products displayed. Using an eye-tracking approach, the results identified significant gender differences in visual attention to online shopping information and shopping attitudes about the products presented. Female participants attended visually to most of the online shopping information areas to a greater degree than did males, and their attitudes about products were influenced to some degree by visual attention to the consumer opinion areas. Although males’ visual attention was lower than females’, their shopping attitudes were influenced extensively by visual attention to product information and consumer opinion areas.

Additional information

Notes on contributors

Yoon Min Hwang

Yoon Min Hwang, PhD, is a research professor at SKK Business School, Sungkyunkwan University in Seoul, Republic of Korea. His research interests focus on human–computer interaction, cognitive/emotional science, AI/IoT business model, and entrepreneurship/creativity.

Kun Chang Lee

Kun Chang Lee is a full professor at SKK Business School and SAIHST(Samsung Advanced Institute of Health Sciences & Technology), Sungkyunkwan University, Seoul 03063, Republic of Korea. He is now in charge of Creativity Science Research Institute. His research interests include creativity science, HCI, HRI, emotion science, physiological reasoning for problem-solving, and artificial intelligence techniques in DSS.

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