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February 8, 2026Automation0 citationsOpen Access

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

AOAdetayo OnososenIMInnocent Musonda

Key Points

  • The study aims to identify and analyze barriers to human-robot collaboration in construction using interpretive structural modelling.
  • Synthesized previous research using the PRISMA method.
  • Applied interpretive structural modelling (ISM) to establish relationships among barriers.
  • Identified eight barrier categories related to human-robot collaboration.
  • Revealed regulatory and communication barriers as key upstream drivers.
  • Demonstrated downstream effects on safety, training, organizational, and technological outcomes.
  • Provided a systems-level framework for prioritizing interventions.

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.

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Cite This Study

Onososen et al. (2026) studied this question.

synapsesocial.com/papers/698827a20fc35cd7a884670bhttps://doi.org/10.3390/automation7010028
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