Cognitive Preference Performance of In-Vehicle Human–Machine Interface Icons under Female New Energy Vehicles

Ya-Ying Li, Fang-Hao Song (), Yan Liu () and Yong Wang
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Ya-Ying Li: Shool of Mechanical Engineering, Shandong University, Jinan 250012, China
Fang-Hao Song: Shool of Mechanical Engineering, Shandong University, Jinan 250012, China
Yan Liu: Shool of Mechanical Engineering, Shandong University, Jinan 250012, China
Yong Wang: Shool of Mechanical Engineering, Shandong University, Jinan 250012, China

Sustainability, 2022, vol. 14, issue 22, 1-21

Abstract: With the advent of the “her economy” era, the new energy automobile market has also ushered in the “her era”, and female consumers have gradually become the main force of domestic and foreign vehicle consumption, thus contributing to the sustainable and rapid development of many female new energy automobile market segments. In this context, this study explores the icon cognitive preferences of female drivers based on gender differences in icon cognition by taking the human–machine interface icons in new energy automobiles as a case study. Firstly, we conducted behavioral response experiments and facial electromyography experiments on 20 male and female participants to analyze their cognitive preferences for icons by combining the four dimensions of “semantic dimension, conceptual dimension, contextual dimension and pragmatic dimension”. The results showed that the four−dimensional graphic deconstruction format had a significant effect on the improvement of icon recognition performance. At the same time, we designed 10 formats of icons as experimental stimulus materials and combined them with subjective scales to jointly explore the reasons for the bias of different gender participants towards icons. The results show that there are significant gender differences in icon perception on a four−dimensional basis, with males more likely to be disturbed by icon constituent elements (semantic dimension), while females are more likely to be disturbed by icon metaphors (semantic dimension) and usage environment and interface context (contextual dimension). This study helps to explore the best balance between studying women’s driving experiences in new energy vehicles and the sustainable product life cycle, and then improve the accuracy of women drivers’ decision−making behavior in new energy vehicles to ensure driving safety.

Keywords: female drivers; automotive human–machine interface; icon perception; gender differences; graphic dimensions (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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