Collaboration in Constructing Human–Robot Teams: Interpretive Structural Modelling (ISM) Approach to Identifying Barriers and Strategies for Enhancing Implementation

Human–robot collaboration (HRC) offers a significant potential to improve productivity, safety, and performance in construction, yet its adoption remains constrained by interrelated barriers. The existing studies largely identify these barriers in isolation, with limited insight into their systemic interactions. This study addresses this gap by synthesising prior research using PRISMA and applying interpretive structural modelling (ISM) to examine the hierarchical and causal relationships among barriers to HRC in construction. Eight barrier categories are identified: financial, safety, communication, robot technology-related, organisational, legal/regulatory, education/training, and social and human factors. The ISM–MICMAC results reveal regulatory and communication barriers as key upstream drivers shaping downstream safety, training, organisational, and technological outcomes. By moving beyond descriptive listings, the study provides a systems-level framework that supports the strategic prioritisation of interventions and informed decision-making. The findings advance the theoretical understanding of HRC as a socio-technical system and offer an evidence-informed foundation for context-sensitive implementation strategies in construction.

Authors

Institutions

Publication Details

Journal
Automation
Published
2026-02-05
DOI
https://doi.org/10.3390/automation7010028
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Collaboration in Constructing Human–Robot Teams: Interpretive Structural Modelling (ISM) Approach to Identifying Barriers and Strategies for Enhancing Implementation

Adetayo Onososen, Innocent Musonda
Automation
Occupational Health and Safety Research
article

Collaboration in Constructing Human–Robot Teams: Interpretive Structural Modelling (ISM) Approach to Identifying Barriers and Strategies for Enhancing Implementation

Adetayo Onososen, Innocent Musonda
article en

Abstract

Human–robot collaboration (HRC) offers a significant potential to improve productivity, safety, and performance in construction, yet its adoption remains constrained by interrelated barriers. The existing studies largely identify these barriers in isolation, with limited insight into their systemic interactions. This study addresses this gap by synthesising prior research using PRISMA and applying interpretive structural modelling (ISM) to examine the hierarchical and causal relationships among barriers to HRC in construction. Eight barrier categories are identified: financial, safety, communication, robot technology-related, organisational, legal/regulatory, education/training, and social and human factors. The ISM–MICMAC results reveal regulatory and communication barriers as key upstream drivers shaping downstream safety, training, organisational, and technological outcomes. By moving beyond descriptive listings, the study provides a systems-level framework that supports the strategic prioritisation of interventions and informed decision-making. The findings advance the theoretical understanding of HRC as a socio-technical system and offer an evidence-informed foundation for context-sensitive implementation strategies in construction.

AutomationVol. 7(1)
University of Johannesburg (ZA)
Decent work and economic growth
Openalex Percentile: Top 67%
Occupational Health and Safety Research
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.