Determinants of Online Lending Adoption: A Structural Integration of the Technology Acceptance Model and Borrowers’ Economic Well-Being

This study investigates the psychological and economic determinants of online lending adoption by integrating the Technology Acceptance Model (TAM) with an economic well-being construct. We examine the effects of perceived ease of use (PEU), perceived usefulness (PU), perceived risk (PR), and economic well-being (ECO) on borrowers’ behavioral intention to use (BIU) and actual usage (AU) of digital lending platforms. While prior Indonesian studies have frequently applied TAM to explain digital lending uptake, evidence on the role of borrowers’ economic well-being remains inconclusive; accordingly, we explicitly model ECO as a determinant within the adoption process. A cross-sectional survey of 300 individuals with prior experience using online lending services was analyzed using partial least squares structural equation modeling (PLS-SEM) to estimate structural paths and test mediation. The results indicate that PU positively and most strongly predicts BIU, whereas PR and ECO exert significant negative effects on BIU; PEU shows no statistically significant association with BIU. Behavioral intention, in turn, significantly predicts AU. Mediation tests suggest that BIU acts as a complementary partial mediator of the PU to AU relationship and as a competitive partial mediator for the PR to AU and ECO to AU relationships. PEU exhibits neither a significant direct effect nor an indirect effect on AU via BIU. Overall, the findings highlight perceived usefulness, perceived risk, and economic well-being as salient drivers of intention and realized use of online lending services, while challenging the explanatory relevance of perceived ease of use in this context. By extending TAM with an economic well-being construct, the study refines theory on digital credit adoption and offers actionable implications for platform design, consumer protection, and financial inclusion policies in developing economies. Keywords: economic well-being; online lending; Technology Acceptance Model; behavioral intention; digital lending platforms. DOI： https://doi.org/10.35741/issn.0258-2724.60.5.1