An integrated attitude model of self-service technologies: evidence from online stock trading systems brokers

This study develops an integrated causal path analysis, based on both category-based affect theory and the technology acceptance model (TAM), to identify the antecedents of consumers' attitudes toward self-service technologies. Using online stock trading systems as an example ( N = 267), this study employs structural equation modeling to confirm the research structure. The results reveal that consumers' attitudes toward self-service technologies depend on their attitude toward technologies and attitude toward self-services, in support of category-based affect theory. Further, computer self-efficacy and network information literacy positively influence attitude toward technologies, and both perceived ease of use and perceived usefulness positively influence attitude toward self-service technologies, which were proposed in the two theories, were also found. Therefore, this study suggests that integrated attitude model of the category-based affect and TAM can be applied to properly explain the attitude forming toward self-service technologies, and can be fruitful for future research on the diffusion of Internet-based technological systems.