Exploring privacy-personalization paradox: Facial recognition systems at business events

Abstract

The purpose of this study is to propose the theoretical model of artificial intelligence-based touchless technology adoption, in the context of facial recognition systems (FRSs) adoption by business event attendees. This research combines constructs of technology adoption and privacy-personalization paradox models with the construct derived from the contemporary context of perceived health risk at events. The study used a survey research design with a mental simulation that introduced an FRS to respondents via a video clip. The results of structural equation modeling based on 199 responses show that performance expectancy and trust in the system positively impact the intention to use FRSs at business events. While lacking direct effects on the adoption intention, effort expectancy demonstrates a significant influence on performance expectancy, and perceived personalization serves as a significant predictor of trust in the system. Perceived health risks of attending a business event did not reveal statistically significant effects on performance expectancy and intention to use FRSs. However, further investigation shows that perceived health risk moderates the effects of privacy concerns on trust and intention to use FRSs.