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The ongoing digitization and novel smart technologies can deliver enormous benefits to society and individuals. However, smart services often require the vast collection of data conflicting with users’ privacy. The integration of privacy concerns into acceptance research is needed to portray and predict user decisions in smart technologies. To allow a privacy-integrated prediction of users’ technology acceptance, we apply the privacy calculus theory to adoption behavior. We test the new model in three usage contexts, autonomous driving (transportation), activity trackers (fitness), and cardiac device remote monitoring (medical treatment). Using an online questionnaire, 624 German participants evaluated all three technologies. The model fits well in all contexts, although also context-related differences in the weighing of perceived benefits and privacy concerns showed. It is concluded that the trade-off between perceived benefits and privacy concerns is a central keystone not only for the willingness to disclose information but also for technology acceptance.
Schomakers et al. (Thu,) studied this question.