Investor Learning in Crowdfunded Supply Chain Finance Markets

Abstract

Crowdfunded Supply Chain Finance (SCF) is an innovative market design that transforms financial flows, allowing individual investors to serve as funders under the SCF paradigm. Required by the crowdfunded SCF platform, the involvement of loan guarantors in the financing process alters how fundraisers and investors interact with each other, potentially giving rise to the behavior of investor learning. In this study, we develop a Bayesian learning model, wherein we conceptualize individual perception of guarantor reliability as a subjective attitude underlying the perceived risk of a loan listing. We consider that individual investors can learn about a guarantor’s reliability as they have more interactions with the same guarantor over time. We model investor decision-making as a process involving two separate yet interdependent stages: (1) the incidence decision of whether to invest and (2) the amount decision of how much to invest. Our results show that investors’ decision-making is governed by their perceptions of guarantor reliability, despite in two distinctive manners. Whereas the perceived guarantor reliability is found to have a monotonic, positive effect on amount decisions, its impact on incidence decisions is best described by a curvilinear (inverted U-shaped) relationship. Our results also show that perceived guarantor reliability moderates the positive main effect of interest rates on both decisions, implying that the effectiveness of promising greater returns to induce more funding diminishes as the reliability perception rises. A posterior analysis reveals that offering high interest rates will turn counterproductive when perceived guarantor reliability is high. Implications for platform managers are discussed.

Keywords: FinTech, supply chain finance, crowdfunding, platform design, learning models, Bayesian estimation