The Dual-Edged Sword Effect of Human–Robot Collaboration on Migrant Workers’ Well-Being: Evidence from China

Migrant workers are a unique group under China's urban-rural dual system, and improving their well-being is an intrinsic requirement for achieving common prosperity. In recent years, human-robot collaboration has come forth as a novel work paradigm. Comprehending the influence of human-robot collaboration on the well-being of migrant workers is a vital yet insufficiently investigated matter. With the conservation of resources theory as an analytical framework, this study empirically analyzes data from a two-stage survey of 382 migrant workers in Chinese manufacturing enterprises. The findings suggest that perceived human-robot collaboration can positively influence migrant workers' well-being by facilitating perceived decent work, while also negatively affecting their well-being by increasing job replacement anxiety. Perceived organizational support plays a positive moderating role in two distinct aspects: on the one hand, the relationship between perceived human-robot collaboration and perceived decent work; on the other hand, the mediating effect through which perceived decent work connects perceived human-robot collaboration with the well-being of migrant workers. Conversely, perceived organizational support exerts a negative moderating effect on the association between perceived human-robot collaboration and job replacement anxiety, while job replacement anxiety functions as a mediator in the relationship linking perceived human-robot collaboration to migrant workers' well-being. This study helps understand how human-robot collaboration in manufacturing enterprises affects the well-being of migrant workers.

Authors

Institutions

Publication Details

Journal
Behavioral Sciences
Published
2026-04-01
DOI
https://doi.org/10.3390/bs16040526
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Dual-Edged Sword Effect of Human–Robot Collaboration on Migrant Workers’ Well-Being: Evidence from China

Ruonan Wang, Guangsheng Zhang
Behavioral Sciences
Social Robot Interaction and HRI
article

The Dual-Edged Sword Effect of Human–Robot Collaboration on Migrant Workers’ Well-Being: Evidence from China

Ruonan Wang, Guangsheng Zhang
article en

Abstract

Migrant workers are a unique group under China's urban-rural dual system, and improving their well-being is an intrinsic requirement for achieving common prosperity. In recent years, human-robot collaboration has come forth as a novel work paradigm. Comprehending the influence of human-robot collaboration on the well-being of migrant workers is a vital yet insufficiently investigated matter. With the conservation of resources theory as an analytical framework, this study empirically analyzes data from a two-stage survey of 382 migrant workers in Chinese manufacturing enterprises. The findings suggest that perceived human-robot collaboration can positively influence migrant workers' well-being by facilitating perceived decent work, while also negatively affecting their well-being by increasing job replacement anxiety. Perceived organizational support plays a positive moderating role in two distinct aspects: on the one hand, the relationship between perceived human-robot collaboration and perceived decent work; on the other hand, the mediating effect through which perceived decent work connects perceived human-robot collaboration with the well-being of migrant workers. Conversely, perceived organizational support exerts a negative moderating effect on the association between perceived human-robot collaboration and job replacement anxiety, while job replacement anxiety functions as a mediator in the relationship linking perceived human-robot collaboration to migrant workers' well-being. This study helps understand how human-robot collaboration in manufacturing enterprises affects the well-being of migrant workers.

Behavioral SciencesVol. 16(4)
Liaoning University (CN), Shenyang University (CN)
Reduced inequalities
Openalex Percentile: Top 32%
Social Robot Interaction and HRI
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.