Controversial information technologies, such as biometrics and radio frequency identification, are perceived as having the potential to both benefit and undermine the well-being of the user. Given the type and/or amount of information these technologies have the capability to capture, there have been some concerns among users and potential users. However, prominent technology adoption models tend to focus on only the positive utilities associated with technology use. This research leverages net valence theories, which incorporate both positive and negative utilities, and context of use literature to propose a general framework that can be used for understanding consumer acceptance of controversial information technologies. The framework also highlights the importance of incorporating contextual factors that reflect the nuances of the controversial technologies and their specific context of use. We apply the framework to consumer acceptance of biometric identity authentication for banking transactions through automated teller machines. To that end, we contextualize the core construct of perceived benefits and concerns to this domain in a qualitative study of 402 participants, determine the appropriate contextual factors that are antecedents of the contextualized core constructs by examining relevant past research, and then develop and validate a contextualized research model in a quantitative study of 437 participants. Findings support the validity of our framework, with the model explaining 77.6% of the variance in consumers’ attitudes toward using biometrics for identity authentication at automated teller machines.
The online appendix is available at https://doi.org/10.1287/isre.2017.0706 .