Unraveling user perception of peer-to-peer lending platforms: a triangulated mixed-methods approach

Abstract This study investigates user perceptions of European peer-to-peer lending platforms through a post-positivist lens, guided by abductive reasoning. We aimed to explore user themes expressed in reviews, quantify user preferences, and interpret the underlying social constructs shaping platform engagement. Drawing on 2,480 user reviews from 66 platforms (2012–2023), we used natural language processing to identify key concerns and affective responses. A choice-based conjoint experiment ( n = 197) modeled how users evaluate trade-offs between five platform attributes. To deepen these findings, we conducted a qualitative analysis of user forum discussions, capturing how trust, risk perception, motivation, and social influence guide user behavior. By triangulating computational, experimental, and interpretive approaches, we provide a multidimensional understanding of user expectations, concerns, and decision-making processes. The study contributes to research on user behavior in digital finance and offers theoretical implications and practical design implications for user-centered peer-to-peer lending services in Europe.