In this study, we drew from the existing online trust model to develop a specific model of online lending platform trust from the perspectives of cognition-based trust and affect-based trust. Trust between lenders and borrowers have been discussed a lot but there are no empirical studies focusing on trust toward lending platforms. The dearth of the relevant studies on this aspect indicates the great need for the present study. This study aims to incorporate the Technology Acceptance Model with additionally context-specific factors to propose a research model. Perceived platform trust is divided into three dimensions: technology expectancy, cognition-based trust and affected-based trust. To test the model, we collected data from 300 users with different educational levels on p2p lending platforms in China. The structure of demographic features of our samples is analogous to that of the overall p2p market in China at the end of 2012. The finding suggested that positive reputation and social influence had few impacts on trust toward lending platforms and perceived institutional risks. The finding of this research provided a theoretical foundation for future academic studies as well as practical guidance for both borrowers and lenders lending on p2p platforms.
Wang, Meng; Wang, Tao; Kang, Minghui; and Sun, Shuang, "UNDERSTANDING PERCEIVED PLATFORM TRUST AND INSTITUTIONAL RISK IN PEER-TO-PEER LENDING PLATFORMS FROM COGNITION-BASED AND AFFECT-BASED PERSPECTIVES" (2014). PACIS 2014 Proceedings. 208.