User experience and acceptance of artificial intelligence – understanding the role of user's expectations and system performance.
While system performance and user expectations are known to shape user acceptance, their interplay in the context of artificial intelligence (AI) remains underexplored. This study adopts a holistic perspective to examine how user expectations and AI performance influence user experience and acceptan...
| Publicado en: | Behaviour & Information Technology Vol. 45; no. 13; pp. 3218 - 3240 |
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| Autores principales: | , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Aug2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=196237616&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 196237616 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0144929X B6Q jtl: Behaviour & Information Technology issn: 0144929X maglogo: Y pubinfo: dt: Aug2026 vid: 45 iid: 13 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 196237616 190952301 196237616 196237616 10.1080/0144929X.2026.2615032 196237616 ppf: 3218 ppct: 22 formats: tig: atl: User experience and acceptance of artificial intelligence – understanding the role of user's expectations and system performance. aug: au: Ebermann, Carolin Blümel, Daniel Brauer, Benjamin Weibelzahl, Stephan affil: Psychology, PFH Private University of Applied Science, Göttingen, Germany sug: subj: Artificial Intelligence Attitude to Computers Emotional Regulation Task Performance and Analysis Human Male Female Adult Middle Age Germany Structural Equation Modeling Factor Analysis Descriptive Statistics Scales Adult: 19-44 years Middle Aged: 45-64 years Male Female ab: While system performance and user expectations are known to shape user acceptance, their interplay in the context of artificial intelligence (AI) remains underexplored. This study adopts a holistic perspective to examine how user expectations and AI performance influence user experience and acceptance in a concrete interaction scenario. Drawing on the Components model of User Experience (CUE), we conducted a longitudinal experiment (N = 202) in which participants engaged with a mock AI system for emotion recognition, experiencing either high or low system performance. We measured expectations, user experience, and acceptance at three points using validated questionnaires. Results show that user expectations and pre-use attitudes significantly shape both cognitive experience and post-use acceptance. While AI performance enhances cognitive user experience, it has no direct impact on emotional experience or acceptance. These findings highlight the critical role of managing user expectations in the design and deployment of AI systems. Educational interventions and expectation-aligned system features may foster more positive user experience and higher acceptance – independent of actual performance. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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