Partner or burden? The dual pathways linking perceived attributes of intelligent cockpits to human–machine collaboration willingness via cognitive load

Intelligent cockpits are transforming from passive control interfaces into proactive collaborative partners in connected vehicles. While industry practice emphasizes high instrumentality, entertainment value, and anthropomorphic features, whether these design attributes reduce users' psychological burden and promote collaboration willingness in cognitively demanding driving tasks remains unclear. Drawing on Technology Affordance Theory, this study investigates how three perceived attributes (instrumentality, entertainment, anthropomorphism) are associated with human–machine collaboration willingness through cognitive load as mediating mechanism. Structural equation modeling analysis of 503 Chinese licensed drivers reveals divergent pathway effects. Perceived instrumentality and entertainment enhance collaboration willingness by significantly reducing cognitive load (partial mediation). However, perceived anthropomorphism exhibits a paradoxical pattern: it directly promotes collaboration willingness through affective channels while showing null effects on cognitive load reduction. This challenges the assumption that anthropomorphism equates to usability, revealing an affordance conflict wherein social cognitive processing demands offset interaction convenience in multitasking contexts. The findings establish boundary conditions for anthropomorphic design effectiveness and suggest context-adaptive strategies prioritizing cognitive resource optimization in safety–critical environments.

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Publication Details

Journal
BMC Psychology
Published
2026-02-04
DOI
https://doi.org/10.1186/s40359-026-04074-8
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

Partner or burden? The dual pathways linking perceived attributes of intelligent cockpits to human–machine collaboration willingness via cognitive load

Silian Li
BMC Psychology
Human-Automation Interaction and Safety
article

Partner or burden? The dual pathways linking perceived attributes of intelligent cockpits to human–machine collaboration willingness via cognitive load

Silian Li
article en

Abstract

Intelligent cockpits are transforming from passive control interfaces into proactive collaborative partners in connected vehicles. While industry practice emphasizes high instrumentality, entertainment value, and anthropomorphic features, whether these design attributes reduce users' psychological burden and promote collaboration willingness in cognitively demanding driving tasks remains unclear. Drawing on Technology Affordance Theory, this study investigates how three perceived attributes (instrumentality, entertainment, anthropomorphism) are associated with human–machine collaboration willingness through cognitive load as mediating mechanism. Structural equation modeling analysis of 503 Chinese licensed drivers reveals divergent pathway effects. Perceived instrumentality and entertainment enhance collaboration willingness by significantly reducing cognitive load (partial mediation). However, perceived anthropomorphism exhibits a paradoxical pattern: it directly promotes collaboration willingness through affective channels while showing null effects on cognitive load reduction. This challenges the assumption that anthropomorphism equates to usability, revealing an affordance conflict wherein social cognitive processing demands offset interaction convenience in multitasking contexts. The findings establish boundary conditions for anthropomorphic design effectiveness and suggest context-adaptive strategies prioritizing cognitive resource optimization in safety–critical environments.

BMC PsychologyVol. 14(1)
South China University of Technology (CN)
Openalex Percentile: Top 72%
Human-Automation Interaction and Safety
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Partner or burden? The dual pathways linking perceived attributes of intelligent cockpits to human–machine collaboration willingness via cognitive load — Silian Li · BMC Psychology (2026) | TGRS Research Map | TGRS