Technology acceptance models such as TAM and UTAUT are widely used to explain why people adopt new technologies. They are robust, elegant, and easy to apply. But are they still reliable when technologies become more complex and interaction modes change?
In our new open-access paper, we systematically test the robustness of classic acceptance models across different interaction perspectives and comparable technologies. The core insight is simple but consequential:
acceptance is not only about usefulness and ease of use – it is also about how people perceive their role in using a technology.
Active vs. passive interaction matters
We show that acceptance relationships change depending on whether users experience a technology as something they actively control or passively observe. Under these conditions, classic models lose stability. Constructs that are usually considered robust behave differently across perspectives.
Introducing Usage Perception
To address this, we extend existing models with the construct Usage Perception (UP). UP captures how users cognitively frame their interaction with a technology. The result:
- more stable path relationships
- higher theoretical coherence
- improved explanatory power across technologies
Why this is relevant
For AI systems, autonomous technologies, XR, and emerging mobility concepts, acceptance cannot be fully explained without accounting for perception of use. This has implications for:
- acceptance research
- system design
- technology communication and rollout strategies
📄 Read the full open-access article here:
https://www.sciencedirect.com/science/article/pii/S2451958826000047
If you work on technology acceptance, human–technology interaction, or AI deployment, this perspective shift is worth considering.