Abstract
Smart technologies for aging-in-place address the desire of older adults to live at home independently. Concurrently, they can support the challenged healthcare systems in times of demographic change. Much has already been understood about which factors influence the technology acceptance by future users. Thereby, privacy concerns have been highlighted as a decisive barrier. However, less is yet known about how acceptance is influenced: the central workings of acceptance genesis, the weighing between barriers and benefits and resulting trade-offs have only been focused in very few studies. To gain a deeper understanding of the weighing and trade-offs between privacy barriers and security benefits, an Adaptive Choice-Based Conjoint analysis was carried out using the example of emergency detection technologies (n = 274). The results indicate that if smart technologies offer life-saving security benefits in situations of need, privacy concerns are outweighed. The most important factor for the acceptance decision is the reliability followed by the fall risk. Privacy-related aspects were less important for acceptance decisions. Additionally, the study reveals important data on preferences for system characteristics as well as acceptance thresholds—non-negotiable no-go’s or must-haves. This information helps to understand users’ desires in order to tailor smart technologies to their specific needs.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Eva-Maria Schomakers
Eva-Maria Schomakers is a PhD student and scientific assistant at the Human-Computer Interaction Center at RWTH Aachen University. Her research is focused on online privacy, the acceptance of e-health technologies as well as new mobility services from a user perspective.
Martina Ziefle
Martina Ziefle is a psychologist, full professor, and chair of Communication Science at RWTH Aachen University. Her research is concerned with interaction and communication of humans with technology addressing the human factor in different technology types and usage contexts, focusing on technology acceptance and risk perception.