Examining FinTech Lending Adoption by Small and Medium Enterprises Using a Technology–Environment Framework with PLS-SEM Analysis

Abstract

Small and medium enterprises (SMEs) are still experiencing chronic credit shortages amid the fast-growing number of financial technology (FinTech) lending solutions. Despite potential of immense promise of FinTech lending in reducing the financing constraints of SMEs, the adoption levels are even lower in emerging and developing economies. This paper discusses the factors of FinTech lending uptake in SMEs using a Technology Environment (T-E) model based on the Technology Environment Organization (TOE) model, which has been modified to eliminate organisational variables and specifically concentrate on the technological and environmental aspects. The hypotheses were tested and developed out of seven hypotheses via Partial Least Squares Structural Equation Modelling (PLS-SEM) on the data gathered on 287 SME owners and managers in a cross-sectional survey. Technology factors (Perceived Usefulness, Perceived Ease of Use, Platform Security, and Compatibility) and environmental factors (Competitive Pressure, Trading Partner Readiness and Regulatory Support) were studied as predictors of FinTech Lending Adoption Intent. Findings show that the structural model accounts 52 percent of variance in adoption intent (R 2 = 0.52) with Perceived Usefulness (β = 0.41, p < 0.001) and Regulatory Support (0.38, p < 0.001) proving to be the most significant predictors. Each hypothesis was upheld with p < 0.05 with the exception of Trading Partner Readiness (β = 0.11, p = 0.087) that was not significantly different. Convergent and discriminant validity was confirmed by measurement model diagnostics. The research is valuable in that it presents a validated T-E framework specific to SME FinTech lending settings and presents practical implications to designers of platforms, SMEs, and financial regulators.