Enhancement for Artificial Intelligence Assistants: Expansion of UTAUT Model to Focus on Housing Modernization, Incorporating Elements of Acceptance, Usability, and Emotions
In the modernization of rental housing stock in Germany, the integration of AI virtual assistants (AIVAs) is being explored through the state-funded KIMM project. A significant aspect of this project is the application of the Usability-Valence-Arousal-UTAUT (UVA-UTAUT) model, an extension of the traditional Unified Theory of Acceptance and Use of Technology (UTAUT) [1].
The UVA-UTAUT model delves into the acceptance of AIVAs by renters, extending the UTAUT framework to include usability and emotional responses (valence and arousal) as critical factors for technology adoption. Within the KIMM project, this model investigates how users interact with AIVAs by combining explicit usability and acceptance measures with implicit emotion recognition techniques [1].
At its core, UVA-UTAUT incorporates:
- The traditional acceptance drivers from UTAUT (performance expectancy, effort expectancy, social influence, facilitating conditions),
- Usability, which directly relates to how easily and effectively users can utilize the AI assistant,
- Emotional dimensions:
- Valence (the positivity or negativity of the emotional response), and
- Arousal (the intensity of the emotional response).
By incorporating these emotional components, the model provides a richer, multidimensional understanding of factors that affect whether renters accept and use AIVAs for housing-related purposes, such as managing rental services or interacting with smart home technologies under the KIMM project [1].
The study's findings are anticipated to contribute to the understanding of users' interactions with AIVAs and encourage further exploration of the UVA-UTAUT model. Future research directions are outlined, with potential implications for the fields of Human-Computer Interaction (HCI), Affective Computing, and Psychology [1].
In essence, the UVA-UTAUT model aims to offer a deeper understanding of how emotional states and usability influence the acceptance of AIVAs, supporting the ongoing integration of AI into everyday rental housing management and modernization efforts within KIMM.
[1] Source: [Citation Pending]
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