When AI Chatbots Ask for Donations: The Construal Level Contingency of AI Persuasion Effectiveness in Charity Human–Chatbot Interaction

As AI chatbots are increasingly used in digital fundraising, it remains unclear which communication strategies are more effective in enhancing consumer trust and donation behavior. Drawing on construal level theory and adopting a human-AI interaction perspective, this research examines how message framing in AI-mediated persuasive communication shapes trust and donation willingness. Across four studies, we find that when AI chatbots employ high-level construal (abstract) message framing, consumers perceive the information as less credible compared to when the same message is delivered by a human agent. This reduced message credibility weakens trust in the charitable organization through a trust transfer mechanism, ultimately lowering donation intention. Conversely, low-level construal (concrete) framing enhances both trust and donation willingness. Moreover, the negative impact of abstract message framing by AI chatbots is significantly attenuated when the chatbot features anthropomorphic visual cues, which increase perceived credibility and restore trust and donation willingness. These findings reveal potential risks in deploying AI chatbots for interactive fundraising marketing and offer practical insights for nonprofit organizations seeking to leverage AI in donor engagement.

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Publication Details

Journal
Journal of theoretical and applied electronic commerce research
Published
2025-12-03
DOI
https://doi.org/10.3390/jtaer20040341
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

When AI Chatbots Ask for Donations: The Construal Level Contingency of AI Persuasion Effectiveness in Charity Human–Chatbot Interaction

Jin Sun, Jia Si
Journal of theoretical and applied electronic commerce research
AI in Service Interactions
article

When AI Chatbots Ask for Donations: The Construal Level Contingency of AI Persuasion Effectiveness in Charity Human–Chatbot Interaction

Jin Sun, Jia Si
article en

Abstract

As AI chatbots are increasingly used in digital fundraising, it remains unclear which communication strategies are more effective in enhancing consumer trust and donation behavior. Drawing on construal level theory and adopting a human-AI interaction perspective, this research examines how message framing in AI-mediated persuasive communication shapes trust and donation willingness. Across four studies, we find that when AI chatbots employ high-level construal (abstract) message framing, consumers perceive the information as less credible compared to when the same message is delivered by a human agent. This reduced message credibility weakens trust in the charitable organization through a trust transfer mechanism, ultimately lowering donation intention. Conversely, low-level construal (concrete) framing enhances both trust and donation willingness. Moreover, the negative impact of abstract message framing by AI chatbots is significantly attenuated when the chatbot features anthropomorphic visual cues, which increase perceived credibility and restore trust and donation willingness. These findings reveal potential risks in deploying AI chatbots for interactive fundraising marketing and offer practical insights for nonprofit organizations seeking to leverage AI in donor engagement.

Journal of theoretical and applied electronic commerce researchVol. 20(4)
University of International Business and Economics (CN)
Openalex Percentile: Top 80%
AI in Service Interactions
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