ABSTRACT
Project success is a major challenge to the sustenance of crowdfunding platforms constituted for donation. While previous studies have recognized the importance of source reputation, establishing a credible reputation remains a formidable task for project founders. This study proposes a novel idea of achieving credibility through bundling, in which crowdfunding campaigns collaborate with similar projects (project bundling) or external entities (ideological bundling). This study examines how these two bundling strategies affect crowdfunding outcomes. Further, the study explores how sources of reputation and size establish boundaries of bundling. Using data from Mchanga.com, our analysis reveals a diverse effect of collaborative fundraising on the success of donation crowdfunding. Specifically, our findings indicate that project bundling positively impacts campaign success, whereas ideological bundling has a negative effect. The study contributes to the literature on bundling, credible reputation, and collaborative fundraising on digital platforms. This research also provides insights for practitioners to successfully manage donation-based crowdfunding campaigns.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Supplementary Material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/10864415.2024.2332049
Correction Statement
This article was originally published with errors, which have now been corrected in the online version. Please see Correction (http://dx.doi.org/10.1080/10864415.2024.2341585)
Additional information
Notes on contributors
Bright Frimpong
Bright Frimpong ([email protected]) is an assistant professor at Washington and Lee University. He received his Ph.D. in information systems from the University of Texas Rio Grande Valley. Dr. Frimpong’s research interests include digital entrepreneurship, decoloniality, consumer behavior, data analytics, and cybersecurity. His work has appeared in Journal of Manufacturing Technology Management and the proceedings of such conferences as the Hawaii International Conference on System Sciences (HICSS), Americas Conferences in Information Systems (AMCIS), Production and Operations Management Society (POMS), and American Marketing Association Summer Conference (AMA).
Emmanuel Ayaburi
Emmanuel W. Ayaburi ([email protected]) is currently an assistant professor of information systems at Cleveland State University. He received his Ph.D. in information systems from the University of Texas at San Antonio. Dr. Ayaburi’s research interests include behavioral information systems security and privacy, economics of information systems, and knowledge sharing. His work has been published in European Journal of Information Systems, Information Technology & People, Information Systems Frontiers, International Journal of Information Management, Computers in Human Behavior, and other journals, and was published in proceedings of several conferences, including the International Conference on Information Systems (ICIS), Hawaii International Conference on System Sciences (HICSS), and Americas Conferences in Information Systems (AMCIS).
Francis Kofi Andoh-Baidoo
Francis Kofi Andoh-Baidoo ([email protected]; corresponding author) is a professor in the Department of Information Systems, Robert C. Vackar College of Business and Entrepreneurship, University of Texas Rio Grande Valley. He received his Ph,D. in information systems from the Virginia Commonwealth University. Dr. Andoh-Baidoo’s research interests are in business analytics, ICT for development, and information security and privacy. His research has appeared in such journals such as European Journal of Information Systems, Information and Management, Communications of the Association for Information Systems, Information Systems Frontiers, The DATABASE for Advances in Information Systems, and others. He serves on the editorial boards of Information Systems Frontiers and Information Technology for Development.
Xuan Wang
Xuan Wang ([email protected]) is an assistant professor of information systems at the Robert C. Vackar College of Business & Entrepreneurship, the University of Texas Rio Grande Valley. She received her Ph.D. in information systems and decision science from the E. J. Ourso College of Business, Louisiana State University. Dr. Wang’s interests include causal inference, big data analytics, and artificial intelligence in the area of virtual communities. Her research has been published in Information Systems Frontiers, Internet Research, Information Technology & People, and AIS Transactions on Human–Computer Interaction.
Nan Xiao
Nan Xiao ([email protected]) is an associate professor in the Department of Information Systems at the University of Texas Rio Grande Valley. He holds a Ph.D. in MIS from the State University of New York at Buffalo. Dr. Xiao’s research interests include crowdfunding, healthcare information systems, and information security. His work has been published in Information Systems Research, Decision Support Systems, Information & Management, and ACM Transactions on Management Information Systems.