Working with robots: Trends and future directions

Robots are taking on a prominent role in driving organizational evolution toward industrial revolutions. While research on the role of robots in human resource management (robot-HRM) is proliferating, the literature falls short in providing a state-of-the-art overview of the progress and ways forward for the field. Hence, this study aims to review and consolidate the extant literature on robot-HRM into a unified framework and provide pragmatic ways forward. To do so, this study conducts a framework-based systematic literature review by adopting the SPAR-4-SLR protocol to guide its assembling, arranging, and assessing of theories, contexts, characteristics, and methods (TCCM) of robot-HRM studies identified and retrieved from Scopus and Web of Science. In doing so, this study contributes a seminal overview of the research trends and ways forward for robot-HRM, as well as the implications for professionals to manage the embedding of robots and the interaction with employees in the workplace. • Clarifies robot-HRM's advancing role. • Consolidates key robot-HRM studies. • Reveals pathways for robot-HRM's future. • Guides HR on robotic integration.

Authors

Institutions

Publication Details

Journal
Technological Forecasting and Social Change
Published
2024-12-11
DOI
https://doi.org/10.1016/j.techfore.2024.123648
Citations
14
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
4.86
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Working with robots: Trends and future directions

Xin‐Jean Lim, Jun‐Hwa Cheah, Weng Marc Lim, Siqi Wang
14 citations
Technological Forecasting and Social Change
AI in Service Interactions
4.86
article

Working with robots: Trends and future directions

Xin‐Jean Lim, Jun‐Hwa Cheah, Weng Marc Lim, Siqi Wang
article en
14 citations

Abstract

Robots are taking on a prominent role in driving organizational evolution toward industrial revolutions. While research on the role of robots in human resource management (robot-HRM) is proliferating, the literature falls short in providing a state-of-the-art overview of the progress and ways forward for the field. Hence, this study aims to review and consolidate the extant literature on robot-HRM into a unified framework and provide pragmatic ways forward. To do so, this study conducts a framework-based systematic literature review by adopting the SPAR-4-SLR protocol to guide its assembling, arranging, and assessing of theories, contexts, characteristics, and methods (TCCM) of robot-HRM studies identified and retrieved from Scopus and Web of Science. In doing so, this study contributes a seminal overview of the research trends and ways forward for robot-HRM, as well as the implications for professionals to manage the embedding of robots and the interaction with employees in the workplace. • Clarifies robot-HRM's advancing role. • Consolidates key robot-HRM studies. • Reveals pathways for robot-HRM's future. • Guides HR on robotic integration.

Technological Forecasting and Social ChangeVol. 212
Qingdao University (CN), University of East Anglia (GB), Universiti Putra Malaysia (MY), Sun Yat-sen University (CN), Sohar University (OM), Arizona State University (US), Swinburne University of Technology (AU), Sunway University (MY), Swinburne University of Technology Sarawak Campus (MY)
Openalex Percentile: Top 4%
AI in Service Interactions
4.86
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.