More than just financial performance: Trusting investors in social trading

Social trading is a new form of online community in which investors can automatically, simultaneously, and unconditionally copy the investments of other traders whom they trust. Using data from the social trading network eToro, this study uses fuzzy-set qualitative comparative analysis to explore configurations of cognition-based and affect-based signals of trustworthiness that generate trust and prompt one investor to copy another. This study identifies two configurations that prompt trust and the decision to copy. Those configurations rely on both cognition-based and affect-based signals of trustworthiness. Furthermore, the study identifies six configurations in which weak cognition-based and affect-based signals of trustworthiness lead to parties failing to establish trust. These findings contribute to a better understanding of the establishment and non-establishment of trust in online communities and have implications for social trading platforms and their members.