Understanding the adoption intention of financial data retrieval services: An empirical analysis of my data

Abstract

This study empirically analyzed the variables affecting the adoption intention of a financial data retrieval service (i.e. My Data) through the convergence of the stimulus-organism-response (S-O-R) model, the value-based adoption model (VAM), and the unified theory of acceptance and use of technology (UTAUT1). This approach examined the causal relationships where the characteristics of My Data services (stimulus) influence users' perceived benefit and sacrifice (proposed by VAM), as well as performance expectancy, effort expectancy, social influence, and facilitating conditions (proposed by UTAUT1) (organism), which in turn impact adoption intention (response). The results indicate that the three sub-factors of My Data service characteristics—system quality, information quality, and service quality have significant effects on perceived benefit, perceived sacrifice, performance expectancy, effort expectancy, social influence, facilitating conditions, and adoption intention. These findings provide both theoretical and practical insights for the development, diffusion, and activation strategies of My Data, while simultaneously validating the convergence model's effectiveness.