EXPLORING SUCCESSFUL CAMPAIGN PROFILES ON CROWDFUNDING-BASED PROJECT FINANCING: A TREE-BASED COMPARATIVE ANALYSIS

Crowdfunding platforms have become a popular alternative for financing projects. However, campaigners in the platform witness several challenges that affect their success. This study aims to: (a) generate and explore profiles among the non-successful, successful, and very successful campaigns; (b) to interpret investment behaviour of the backers from the profiles. We employed a fresh approach of tree-based comparative analysis (TBCA) as an exploratory tool that augments qualitative comparative analysis (QCA) with data mining evaluation. Campaign profiles were drawn from four groups of 17 predictors, namely: ``campaign strategy,'' ``presentation strategy,'' ``campaigners'' track records, and ``temporal data.'' We analyzed 647 campaigns in Kickstarter and the analysis was divided into two timelines: before and on the first day of campaigns. The emerging profiles offer practical insights for campaigners to develop a coherent set of campaign decisions and to anticipate the possible outcome. The profiles also indicate that prior to the campaign, investment behaviour is mainly explained by ``signal theory:' Interestingly, for the first day of a campaign, the funding ratio performance has the most significant impact on very successful projects - that is, consistent with ``herding behaviour.''