  The growing popularity of online fundraising (aka "crowdfunding") has
attracted significant research on the subject. In contrast to previous studies
that attempt to predict the success of crowdfunded projects based on specific
characteristics of the projects and their creators, we present a more general
approach that focuses on crowd dynamics and is robust to the particularities of
different crowdfunding platforms. We rely on a multi-method analysis to
investigate the correlates, predictive importance, and quasi-causal effects of
features that describe crowd dynamics in determining the success of crowdfunded
projects. By applying a multi-method analysis to a study of fundraising in
three different online markets, we uncover general crowd dynamics that
ultimately decide which projects will succeed. In all analyses and across the
three different platforms, we consistently find that funders' behavioural
signals (1) are significantly correlated with fundraising success; (2)
approximate fundraising outcomes better than the characteristics of projects
and their creators such as credit grade, company valuation, and subject domain;
and (3) have significant quasi-causal effects on fundraising outcomes while
controlling for potentially confounding project variables. By showing that
universal features deduced from crowd behaviour are predictive of fundraising
success on different crowdfunding platforms, our work provides design-relevant
insights about novel types of collective decision-making online. This research
inspires thus potential ways to leverage cues from the crowd and catalyses
research into crowd-aware system design.
