Examining the Social Influence on Information Technology Sustained Use in a Community Health System: A Hierarchical Bayesian Learning Method Analysis

Abstract

This paper develops a hierarchical Bayesian learning model to investigate the social influence on sustained use of technology in healthcare. First, this post-adoption Bayesian learning model study makes a contribution to the limited literature on sustained technology use. Second, in the post-adoption stage, our sustained use Bayesian learning model shows that the difference between peer effects and opinion leader effects are not significant. This finding differs from those found in the existing literature examining social influence on technology adoption. This phenomenon reveals the technology user's psychological changes in response to social influence at different stages of technology adoption and use. Therefore, this brings up a practical policy implication regarding how to leverage this change and what type of social influence should be considered to leverage during the technology implementation stage, for promoting early adoption or for encouraging sustained use.