Abstract
Prior research has predominantly examined visual complexity in laboratory controlled settings. This study shifts to the context of online prosocial crowdfunding, where information is abundant yet attention is scarce, to systematically investigate the real-world effects of visual complexity. We analyze how two dimensions of visual complexity—feature complexity (pixel-level) and design complexity (object-level)—relate to fundraising performance. Grounded in dual-process theory, we propose that feature complexity positively correlates with fundraising performance while design complexity negatively correlates with performance. We further posit that greater platform competition amplifies the positive effect of feature complexity while attenuating the negative effect of design complexity. Using 1868,701 valid projects from Kiva, we empirically validate these predictions. Our study deepens the understanding of visual complexity effects in attention-scarce environments and provides practical guidance for borrowers to optimize cover image design.
| Original language | English |
|---|---|
| Article number | 103106 |
| Journal | International Journal of Information Management |
| Volume | 91 |
| DOIs | |
| State | Published - Dec 2026 |
| Externally published | Yes |
Keywords
- Competition
- Deep learning
- Image analytics
- Prosocial crowdfunding
- Visual complexity
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