U SING SOCIAL NETWORK DATA TO PREDICT TECHNOLOGY ACCEPTANCE Research - in - Progress

In contrast to popular literature on technology acceptance, this research-in-progress paper does not intend to build an explanatory model of technology acceptance but a predictive model so as to predict whether a specific person is likely to accept some technology. We show that the constructs that were identified in the classic UTAUT (such as performance expectancy, effort expectancy and social influence) can be used in a predictive model but that better predictions of system use can be made using knowledge about social networks that exist between people. Both social influence and social selection data are valuable to make predictions. Our approach is tested in the context of a video system which is part of an online learning platform, using a sample of 133 interconnected students.