arbiter
JournalsPricingAccount

Human-likeness perceptions in automated driving systems: exploring post-usage trust and continuance intention through TAM and automated social presence perspectives

Xu Wang et al.

Ergonomics2026https://doi.org/10.1080/00140139.2026.2621032article
AJG 3
Weight
0.50

What the paper says

Mind perception theory explains how people attribute human-like qualities to technology. Drawing on this theory, this study introduces perceived competence and warmth as key dimensions of human-likeness in automated driving systems (ADS). We propose a post-usage model for Level-3 ADS trust and adoption. It extends TAM by incorporating the two human-likeness dimensions, trust, and automated social presence (ASP; feeling of being socially accompanied by automation). We conducted a driving-simulator experiment to manipulate users' perceptions of competence and warmth. The proposed model was then validated using multilevel structural equation modelling with 280 experimental samples. Results show competence and warmth jointly enhance perceived ease of use, usefulness, and ASP, thereby promoting trust and continued usage. Notably, warmth receives greater user attention than competence. Moreover, post-usage trust exerts a stronger impact on continuance intention than original TAM pathways. Our findings inform the design of ADS that foster trust and continued adoption.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1080/00140139.2026.2621032

Or copy a formatted citation

@article{xu2026,
  title        = {{Human-likeness perceptions in automated driving systems: exploring post-usage trust and continuance intention through TAM and automated social presence perspectives}},
  author       = {Xu Wang et al.},
  journal      = {Ergonomics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/00140139.2026.2621032},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Human-likeness perceptions in automated driving systems: exploring post-usage trust and continuance intention through TAM and automated social presence perspectives

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.