Influence of Visual Coding Based on Attraction Effect on Human–Computer Interface
Linlin Wang, Yujie Liu, Xinyi Tang, Chengqi Xue, Haiyan Wang
TL;DR
This paper explores how visual coding influences decision-making on human-computer interfaces through the attraction effect.
Contribution
It identifies how similarity-based attributes and coding modes affect the intensity of the attraction effect in digital interfaces.
Findings
Similarity-based attributes enhance the attraction effect, while difference-based attributes do not.
Color coding has the strongest attraction effect, followed by size and labels.
The relationship driven by coding modes has a weaker influence than coding attributes.
Abstract
Decision-making is often influenced by contextual information on the human–computer interface (HCI), with the attraction effect being a common situational effect in digital nudging. To address the role of visual cognition and coding in the HCI based on the attraction effect, this research takes online websites as experimental scenarios and demonstrates how the coding modes and attributes influence the attraction effect. The results show that similarity-based attributes enhance the attraction effect, whereas difference-based attributes do not modulate its intensity, suggesting that the influence of the relationship driven by coding modes is weaker than that of coding attributes. Additionally, variations in the strength of the attraction effect are observed across different coding modes under the coding attribute of similarity, with color coding having the strongest effect, followed by…
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Taxonomy
TopicsColor perception and design · Multisensory perception and integration · Consumer Behavior in Brand Consumption and Identification