Construction and validation of an updated perfect automation schema (uPAS) scale

Gibson, Anthony; Capiola, August; Alarcon, Gene M.; Lee, Michael A.; Jessup, Sarah A.; Hamdan, Izz Aldin

doi:10.1080/1463922x.2022.2081375

Cited by 3 publications

(2 citation statements)

References 33 publications

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“…Data from the technology acceptance question and condition were part of a larger study, analyzed as part of a different research question (Gibson et al, 2022). As such, no hypothesis was made concerning these data.…”

Section: Task and Stimulimentioning

confidence: 99%

See 1 more Smart Citation

Extending the Affective Technology Acceptance Model to Human-Robot Interactions: A Multi-Method Perspective

Jessup,

Willis,

Alarcon

2023

Proceedings of the Annual Hawaii International Conference on System Sciences

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The current study sought to extend the Affective Technology Acceptance (ATA) model to human-robot interactions. We tested the direct relationship between affect and technology acceptance of a security robot. Affect was measured using a multi-method approach, which included a self-report survey, as well as sentiment analysis, and response length of written responses. Results revealed that participants who experienced positive affect were more likely to accept technology. However, the significance and direction of the relationship between negative affect and technology acceptance was measurement dependent. Additionally, positive and negative sentiment words accounted for unique variance in technology acceptance, after controlling for self-reported affect. This study demonstrates that affect is an important contributing factor in human-robot interaction research, and using a multi-method approach allows for a richer, more complete understanding of how human feelings influence robot acceptance.

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Section: Task and Stimulimentioning

confidence: 99%

“…As such, no hypothesis was made concerning these data. However, we have included these variables so we can control for condition in our hierarchical binomial logistic regression analysis, which is beyond the scope of Gibson et al (2022).…”

Section: Task and Stimulimentioning

confidence: 99%