2021/01/15 by Henry K. Dambanemuya, Emőke-Ágnes Horvát, Dambanemuya, Henry K. +1
Business, Management and Accounting · Decision Sciences · Economics, Econometrics and Finance · #FOS: Computer and information sciences #FinTech, Crowdfunding, Digital Finance #Human-Computer Interaction (cs.HC) #J.4 #Microfinance and Financial Inclusion #Technology Adoption and User Behaviour
paper · pdf · doi:10.48550/arxiv.2101.06315
openalex publication_date 2021/01/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The growing popularity of online fundraising (aka "crowdfunding") has\nattracted significant research on the subject. In contrast to previous studies\nthat attempt to predict the success of crowdfunded projects based on specific\ncharacteristics of the projects and their creators, we present a more general\napproach that focuses on crowd dynamics and is robust to the particularities of\ndifferent crowdfunding platforms. We rely on a multi-method analysis to\ninvestigate the correlates, predictive importance, and quasi-causal effects of\nfeatures that describe crowd dynamics in determining the success of crowdfunded\nprojects. By applying a multi-method analysis to a study of fundraising in\nthree different online markets, we uncover general crowd dynamics that\nultimately decide which projects will succeed. In all analyses and across the\nthree different platforms, we consistently find that funders' behavioural\nsignals (1) are significantly correlated with fundraising success; (2)\napproximate fundraising outcomes better than the characteristics of projects\nand their creators such as credit grade, company valuation, and subject domain;\nand (3) have significant quasi-causal effects on fundraising outcomes while\ncontrolling for potentially confounding project variables. By showing that\nuniversal features deduced from crowd behaviour are predictive of fundraising\nsuccess on different crowdfunding platforms, our work provides design-relevant\ninsights about novel types of collective decision-making online. This research\ninspires thus potential ways to leverage cues from the crowd and catalyses\nresearch into crowd-aware system design.\n