Visual Selective Attention Analysis for Elderly Friendly Fresh E-Commerce Product Interfaces

Visual selective attention is a cognitive process by which humans efficiently process critical visual information. It reflects the user’s authentic visual thinking and can be applied by designers in age-friendly design to enhance the user experience of elderly users, meeting their visual needs and attention characteristics. This has significant implications for the age-friendly design of fresh e-commerce product interfaces. This paper explores age-friendly design for fresh e-commerce product interfaces based on the theory of visual selective attention. Experimental data indicate that the optimized interface significantly enhances the user experience for elderly users, with task completion time reduced by 39.62% and satisfaction increased by 60%. First, qualitative research is conducted to uncover the visual selective attention mechanisms of elderly users. Combining this with the framework of fresh e-commerce products, an age-friendly design model is established, including page layout, brand colors, font size, and focal styles. Second, using eye-tracking, descriptive analysis, and correlation coefficient analysis, a comparative analysis of the visual selection behaviors of elderly and young users is conducted, yielding characteristics and principles for age-friendly interactive interface design. Finally, the feasibility and effectiveness of the proposed method are validated through design practice and evaluation. This research provides new insights and methods for the age-friendly design of fresh e-commerce product interfaces. It holds practical significance and value for constructing an elderly perspective in fresh e-commerce and expanding the private traffic of elderly users.

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Publication Details

Journal
Applied Sciences
Published
2025-04-18
DOI
https://doi.org/10.3390/app15084470
Citations
1
Primary Topic
Color perception and design
Type
article
Field-Weighted Citation Impact
2.44
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article

Visual Selective Attention Analysis for Elderly Friendly Fresh E-Commerce Product Interfaces

Junnan Ye, Chaoxiang Yang, Wenhao Li, Yueting Han
1 citations
Applied Sciences
Color perception and design
2.44
article

Visual Selective Attention Analysis for Elderly Friendly Fresh E-Commerce Product Interfaces

Junnan Ye, Chaoxiang Yang, Wenhao Li, Yueting Han
article en
1 citations

Abstract

Visual selective attention is a cognitive process by which humans efficiently process critical visual information. It reflects the user’s authentic visual thinking and can be applied by designers in age-friendly design to enhance the user experience of elderly users, meeting their visual needs and attention characteristics. This has significant implications for the age-friendly design of fresh e-commerce product interfaces. This paper explores age-friendly design for fresh e-commerce product interfaces based on the theory of visual selective attention. Experimental data indicate that the optimized interface significantly enhances the user experience for elderly users, with task completion time reduced by 39.62% and satisfaction increased by 60%. First, qualitative research is conducted to uncover the visual selective attention mechanisms of elderly users. Combining this with the framework of fresh e-commerce products, an age-friendly design model is established, including page layout, brand colors, font size, and focal styles. Second, using eye-tracking, descriptive analysis, and correlation coefficient analysis, a comparative analysis of the visual selection behaviors of elderly and young users is conducted, yielding characteristics and principles for age-friendly interactive interface design. Finally, the feasibility and effectiveness of the proposed method are validated through design practice and evaluation. This research provides new insights and methods for the age-friendly design of fresh e-commerce product interfaces. It holds practical significance and value for constructing an elderly perspective in fresh e-commerce and expanding the private traffic of elderly users.

Applied SciencesVol. 15(8)
East China University of Science and Technology (CN)
Openalex Percentile: Top 14%
Color perception and design
2.44
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