EXPRESS: Investor Learning in Crowdfunded Supply Chain Finance Markets

Crowdfunded Supply Chain Finance (SCF) represents a novel market design that transforms financial flows within the SCF paradigm. It enables crowd investors to serve as financers, lending vital working capital to suppliers facing liquidity problems. A distinctive feature of this market is the mandatory involvement of loan guarantors, which facilitates repeated interactions between investors and fundraisers, potentially fostering investor learning. To understand how such learning dynamics shape investor decision-making, we develop a Bayesian learning model that conceptualizes investor perceptions of guarantor reliability as a subjective attitude underlying the perceived risk of a loan listing. The model posits that investors can learn about a guarantor’s reliability through a series of scheduled repayments involving the same guarantor over time. We consider investor decision-making a joint process comprising two interdependent components: (1) the incidence decision of whether to invest and (2) the amount decision of how much to invest. Our results reveal that investor perceptions of guarantor reliability play a crucial role in shaping both decisions, albeit in distinct ways. While perceived reliability exerts a positive, monotonic effect on amount decisions, its impact on incidence decisions follows an inverted U-shaped pattern. Furthermore, perceived reliability attenuates the positive effect of loan interest rates on both decisions, suggesting that the appeal of higher returns diminishes as investors’ reliability perceptions increase. A posterior analysis further shows that offering high interest rates may become counterproductive when perceived reliability is sufficiently high. These findings provide actionable implications for platform designers and participants in crowdfunded SCF markets.