When Crowdfunding Meets InDemand: A Dynamic Analysis Using Hidden Markov Model

This study explores the dynamics of project persuasiveness within crowdfunding platforms, with a particular emphasis on the InDemand feature, which enables projects to continue raising funds after achieving their initial goals. By employing a Hidden Markov Model (HMM) with heterogeneity identification, our analysis identifies three distinct persuasiveness states and demonstrates their stickiness. Using data from Indiegogo, this paper analyzes how backer-initiated information (BII) and initiator-initiated information (III) influence the persuasiveness states of projects. The findings reveal that while the quantity of BII consistently enhances project persuasiveness across all states, III's impact is significant only in low and medium persuasiveness states. Moreover, our study highlights the contrasting effects of the initiator's information valence across low and high persuasiveness states. This research offers valuable insights into information management strategies for crowdfunding initiators.