Human-AI collaboration: Unraveling the effects of user proficiency and AI agent capability in intelligent decision support systems
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The single-agent model proves insufficient as use cases increasingly demand context retention, task interdependence, and adaptability across dynamic environments.
“However, as use cases increasingly demand context retention, task interdependence, and adaptability across dynamic environments, the single-agent model proves insufficient [151], [152].”
From AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges (2025) · cites this paper as [151]
Cites
A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction
Hancock, P. A., Billings, D. R., Schaefer, K. E., Chen, J. Y. C., de Visser, E. J., & Parasuraman, R. (2011) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720811417254 · Cited by 2,051 · see citing works
Inkpen, K., Chappidi, S., Mallari, K., Nushi, B., Ramesh, D., Michelucci, P., Mandava, V., Vepřek, L. H., & Quinn, G. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3534561 · Cited by 132 · see citing works
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AI Agents vs. Agentic AI: A Conceptual taxonomy, applications and challenges
Sapkota, R., Roumeliotis, K. I., & Karkee, M. (2026) · Information Fusion · doi:10.1016/j.inffus.2025.103599 · Cited by 244 · see citing works
“However, as use cases increasingly demand context retention, task interdependence, and adaptability across dynamic environments, the single-agent model proves insufficient [149,150].”
AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges
Sapkota, R., Roumeliotis, K. I., & Karkee, M. (2025) · SuperIntelligence - Robotics - Safety & Alignment · doi:10.70777/si.v2i3.15161 · Cited by 186 · see citing works
Raees, M., Khan, V.-J., Lykourentzou, I., & Papangelis, K. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791467 · Cited by 5 · see citing works
- Authors
- Peng, L., Li, D., Zhang, Z., Zhang, T., Huang, A., Yang, S., & Hu, Y.
- Affiliations
- Nanjing Agricultural University (CN)
- Shenzhen University (CN)
- Corresponding author
- Li, Dailin
- Venue
- International Journal of Industrial Ergonomics
- Publisher
- Elsevier BV
- Published
- 2024-09
- Volume
- 103
- Pages
- 103629
- ISSN
- 0169-8141 (ISSN-L)
- OpenAlex
- W4401506519
- Cited by
- 59
- References
- 3
- Citations by year
- 2026: 30 · 2025: 27 · 2024: 2
- FWCI
- 22.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Journal of Industrial Ergonomics (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- human-AI collaboration, intelligent decision support system, user proficiency, AI reliance, user confidence, individual differences, gender differences, AI agent design
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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