Be snobbish: the role of task goal deviation in error tolerance for collaborative robots

Purpose Collaborative robots are key enabling technologies within the framework of Industry 5.0. Inevitable robot errors may lead to negative attitudes toward robots and cause deviations from task goals. However, collaborative robots with high ability and performance can gain informal status in the human–robot collaborative team. Since status is a significant factor influencing interactions, it is crucial to explore how variations in the status of erring robots influence team members’ attitudes. Design/methodology/approach This study employs affective events theory (AET) with the experimental vignette methodology (EVM), engaging a total of 388 participants (N student = 216, N non-student = 172) in the experiment. Findings First, erring robot status positively influences error tolerance (lower punishment tendency and higher future collaboration tendency). Second, negative attitudes toward robots mediate the relationship between erring robot status and error tolerance. Third, task goal deviation moderates the relationship between erring robot status and negative attitudes toward robots. Fourth, the protective effect of erring robot status differs by prior robot experience. Research limitations/implications This study enriches theoretical research on robot status and expands the application of AET to the industrial human–robot interaction (iHRI) domain. Additionally, it offers critical guidance to enhance the effectiveness and error tolerance of human–robot collaboration in practical contexts. Originality/value These findings offer a mechanistic explanation for employee attitudes and reactions following robot errors and propose practical measures to mitigate the negative impacts of robot errors on human–robot collaboration.

Authors

Publication Details

Journal
Internet Research
Published
2025-05-20
DOI
https://doi.org/10.1108/intr-06-2024-0992
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Be snobbish: the role of task goal deviation in error tolerance for collaborative robots

S. Liao, Hairun Pei, Long Lin, Qin Chen et al.
1 links
Internet Research
Human-Automation Interaction and Safety
article

Be snobbish: the role of task goal deviation in error tolerance for collaborative robots

S. Liao, Hairun Pei, Long Lin, Qin Chen, Yanhong Yao
article en

Abstract

Purpose Collaborative robots are key enabling technologies within the framework of Industry 5.0. Inevitable robot errors may lead to negative attitudes toward robots and cause deviations from task goals. However, collaborative robots with high ability and performance can gain informal status in the human–robot collaborative team. Since status is a significant factor influencing interactions, it is crucial to explore how variations in the status of erring robots influence team members’ attitudes. Design/methodology/approach This study employs affective events theory (AET) with the experimental vignette methodology (EVM), engaging a total of 388 participants (N student = 216, N non-student = 172) in the experiment. Findings First, erring robot status positively influences error tolerance (lower punishment tendency and higher future collaboration tendency). Second, negative attitudes toward robots mediate the relationship between erring robot status and error tolerance. Third, task goal deviation moderates the relationship between erring robot status and negative attitudes toward robots. Fourth, the protective effect of erring robot status differs by prior robot experience. Research limitations/implications This study enriches theoretical research on robot status and expands the application of AET to the industrial human–robot interaction (iHRI) domain. Additionally, it offers critical guidance to enhance the effectiveness and error tolerance of human–robot collaboration in practical contexts. Originality/value These findings offer a mechanistic explanation for employee attitudes and reactions following robot errors and propose practical measures to mitigate the negative impacts of robot errors on human–robot collaboration.

Internet Research
Openalex Percentile: Top 88%
Human-Automation Interaction and Safety
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.