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Trust dynamics in human interaction with an industrial robot

Bibliographic Data

ID21451885
AuthorsBasel Alhaji (0000-0002-8778-1713, University of Duisburg-Essen), Sebastian Büttner (0000-0002-8136-6228, University of Duisburg-Essen, corresponding author), Shushanth Sanjay Kumar (Clausthal University of Technology), Michael Prilla (0000-0002-6095-6114, University of Duisburg-Essen)
Year2025
Volume44
Issue2
Pages266-288
Publication date2025-01-20
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBehaviour and Information Technology (JOURNAL)
Journal identifiersISSN: 0144-929X • E-ISSN: 1362-3001
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/0144929x.2024.2316284
OpenAlexW4391884258
LanguageEN
Citations received5
References cited97

Trust is important for collaboration.In hybrid teams of humans and robots, trust enables smooth collaboration and reduces risks.Just as collaboration between humans and robots differs from interpersonal collaboration, so does the nature of trust in human-robot interaction (HRI).Therefore, further investigations on trust formation and dissolution in HRI, factors affecting it, and means for keeping trust on an appropriate level are needed.However, our knowledge of interpersonal trust and trust in autonomous agents cannot be transferred directly to HRI.In this paper, we present a study with 32 participants on trust formation and dissolution as well as forecasting to influence trust in an industry robot.Results show differences in dynamics and factors of trust formation and dissolution.Additionally, we find that the effect of forecasting on trust depends on task success.These findings support the design of trustful human-robot interaction and corresponding robotic team members

Dynamics (music) · Human–computer interaction · Human–robot interaction · Robot · Artificial Intelligence · Computer Science · Engineering · Healthcare Technology and Patient Monitoring · Human-Automation Interaction and Safety · Psychology · Robot Manipulation and Learning

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Unique citing works5
Citations per year5
Citation span2025 - 2026 (2)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 5

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