An integrated model of prosocial crowdfunding decision: Three utility components and three informational cues

• Published in: Electronic commerce research and applications 2023-01, Vol.57, p.101233, Article 101233
• Main Authors: Yoo, Jenny Jeongeun, Jhang, Jihoon, Song, Sangyoung, Shin, Hyun S.
• Format: Article
• Language: English
• Subjects: AI (artificial intelligence); Big data; Crowdfunding; Facial expression detection; Kiva; Prosocial behaviors
• ISSN: 1567-4223; 1873-7846
• DOI: 10.1016/j.elerap.2022.101233

•We proposed a conceptual framework that delineates the dynamic relationship between crowdfunding supporters’ three utilities and informational cues.•Four hypotheses were empirically tested with massive data (n = 142,578) from Kiva.•Borrowers’ facial expressions were detected and analyzed with Artificial Intelligence.•Funding success rate increases when a borrower in the picture smiles or the target loan amount is smaller.•Three-way interactions exist among smile, target loan amount, and social-tie words. Prosocial crowdfunding has contributed to tackling social problems by expanding financial access to social entrepreneurs. Despite the growing body of research, our understanding of prosocial crowdfunding decisions is still fragmented as few research has provided a comprehensive view of how various motives and informational cues interactively influence funding success. Drawing on a wide range of theories in economics and psychology, we proposed an integrated conceptual framework that delineates the dynamic relationships between potential supporters’ three utilities (i.e., financial, other-focused, and self-focused) and three informational cues (i.e., textual, pictorial, and numerical informational cues) embedded in the crowdfunding projects. Then we developed and empirically tested our hypotheses using massive data from Kiva (n = 142,578). The results of our study showed that funding success increases when borrowers smile (H1) or when the target loan amount is smaller (H2). Additionally, the negative relationship between funding success and the target loan amount is moderated by the intensity of smile only when more (vs fewer) social-tie words are mentioned (H3 & H4). Our findings not only shed light on how diverse motives dynamically interact with subtle cues to affect supporters’ funding decisions but also provide practical implications for social entrepreneurs who are eager to improve funding success rates.