Siyu Fan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Siyu Fan has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Dongyu Liu
Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
1 shared publication - Haibo Yang
Academy of Psychology and Behavior, Faculty of Psychology, Tianjin Normal University, Tianjin, 300387, China
1 shared publication - Te Ran
Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
1 shared publication - Yawen Guo
Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
1 shared publication
Latest Publications
- Open Access
- 19 March 2026
- Published by MDPI AG in Behavioral Sciences
- Vol. 16 (3) , 454
The Impact of Multidimensional Warning Messages on Payment Security Behavior Across Different Scenarios
To ensure the security of mobile payments, anti-fraud warning messages serve as a critical defensive interface between users and potential risks. The effectiveness of their design directly influences users’ risk perceptions and security-related behaviors. The present study employed eye-tracking technology to examine the effectiveness of warning messages in mobile payment transfer scenarios and the impact of specific warning design features on user decision-making. Experiment 1 utilized a 2 (warning message: present vs. absent) × 3 (potential risk level: high, medium, low) within-subject design to test the fundamental role of warning message presence. Results indicated that the presence of warning messages significantly prolonged participants’ reaction times when selecting the transfer option, suggesting a more cautious decision-making process. Building on Experiment 1, Experiment 2 employed a 2 (warning color: red vs. blue) × 2 (warning semantic type: imperative vs. reminder) × 3 (potential risk level: high, medium, low) within-subject design and incorporated eye-tracking technology to investigate the effects of these design variables and underlying attentional mechanisms. Red warnings and imperative semantics were both found to significantly increase the likelihood of transfer rejection, with these design advantages being particularly pronounced in high-risk contexts. These findings provide empirical evidence to guide mobile payment platforms in optimizing dynamically adaptive, context-sensitive anti-fraud warning designs.
- 19 March 2026
- Published by MDPI AG in Behavioral Sciences
- Vol. 16 (3) , 454
Open AccessThe Impact of Multidimensional Warning Messages on Payment Security Behavior Across Different Scenarios
To ensure the security of mobile payments, anti-fraud warning messages serve as a critical defensive interface between users and potential risks. The effectiveness of their design directly influences users’ risk perceptions and security-related behaviors. The present study employed eye-tracking technology to examine the effectiveness of warning messages in mobile payment transfer scenarios and the impact of specific warning design features on user decision-making. Experiment 1 utilized a 2 (warning message: present vs. absent) × 3 (potential risk level: high, medium, low) within-subject design to test the fundamental role of warning message presence. Results indicated that the presence of warning messages significantly prolonged participants’ reaction times when selecting the transfer option, suggesting a more cautious decision-making process. Building on Experiment 1, Experiment 2 employed a 2 (warning color: red vs. blue) × 2 (warning semantic type: imperative vs. reminder) × 3 (potential risk level: high, medium, low) within-subject design and incorporated eye-tracking technology to investigate the effects of these design variables and underlying attentional mechanisms. Red warnings and imperative semantics were both found to significantly increase the likelihood of transfer rejection, with these design advantages being particularly pronounced in high-risk contexts. These findings provide empirical evidence to guide mobile payment platforms in optimizing dynamically adaptive, context-sensitive anti-fraud warning designs.