The relationship between robotisation and work characteristics: a systematic literature review

Abstract Although the prevalence of robots in the workplace is growing at a considerable speed, findings on their relationship with employees’ work experiences remain scarce. This poses a challenge for managers attempting to implement robots, as the few existing studies often report contradictory findings. This systematic literature review aims to solve this issue by identifying relationship tendencies between robotisation and work characteristics and the potential moderator variables in this relationship, creating a basis for future research. Findings reflect the important role of robotisation as an antecedent to the extended Work Design Model (Humphrey et al. 2007). They reveal mixed tendencies when it comes to the relationship between robotisation and both task and contextual characteristics, with a positive tendency for knowledge characteristics and a negative tendency for social characteristics being most likely. Potential moderator variables include implementation strategy, type of job, and type of robot. We conclude the review with managerial and theoretical recommendations and outline opportunities for future research.

Authors

Institutions

Publication Details

Journal
Management Review Quarterly
Published
2025-02-03
DOI
https://doi.org/10.1007/s11301-025-00488-7
Citations
2
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
2.48

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The relationship between robotisation and work characteristics: a systematic literature review

José María Peiró Silla, Vicente González‐Romá, Nina Jonczyk, Theresa Schweizer
2 citations
Management Review Quarterly
Digital Transformation in Industry
2.48
article

The relationship between robotisation and work characteristics: a systematic literature review

José María Peiró Silla, Vicente González‐Romá, Nina Jonczyk, Theresa Schweizer
article en
2 citations

Abstract

Abstract Although the prevalence of robots in the workplace is growing at a considerable speed, findings on their relationship with employees’ work experiences remain scarce. This poses a challenge for managers attempting to implement robots, as the few existing studies often report contradictory findings. This systematic literature review aims to solve this issue by identifying relationship tendencies between robotisation and work characteristics and the potential moderator variables in this relationship, creating a basis for future research. Findings reflect the important role of robotisation as an antecedent to the extended Work Design Model (Humphrey et al. 2007). They reveal mixed tendencies when it comes to the relationship between robotisation and both task and contextual characteristics, with a positive tendency for knowledge characteristics and a negative tendency for social characteristics being most likely. Potential moderator variables include implementation strategy, type of job, and type of robot. We conclude the review with managerial and theoretical recommendations and outline opportunities for future research.

Management Review QuarterlyVol. 76(1)
Universitat de València (ES)
Generalitat Valenciana, Conselleria de Cultura, Educación y Ciencia, Generalitat Valenciana
Openalex Percentile: Top 12%
Digital Transformation in Industry
2.48
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.

The relationship between robotisation and work characteristics: a systematic literature review — José María Peiró Silla, Vicente González‐Romá, et al. · Management Review Quarterly (2025) | TGRS Research Map | TGRS