A PLS-SEM analysis of people, management, and organisational culture influences on AI-driven hospital facilities management systems

Introduction As hospitals increasingly integrate artificial intelligence (AI) into facility and asset management, understanding the organisational and human factors influencing this transition has become essential. Despite growing interest in AI-driven facility management, there is limited empirical evidence on how organisational culture, management commitment, and staff-related factors shape AI adoption in hospital environments. Methods This study employed Partial Least Squares Structural Equation Modelling (PLS SEM) to analyse data from a diverse sample of built environment professionals with experience in hospital asset and facilities management. The model assessed the influence of organisational culture, managerial commitment and people-related factors on staff adaptability and AI integration. Results The structural model demonstrated strong explanatory power (R 2 = 0.901), confirming that organisational culture significantly influences both staff adaptability and AI integration within hospital facility management systems. Unexpectedly, hypotheses related to people factors (H1) and management commitment (H2) were not statistically significant. These results may be attributed to sample characteristics or potential measurement limitations. Discussion The findings highlight the dominant and necessary role of organisational culture in shaping AI adoption within hospital facility management—overshadowing individual-level and managerial influences. This suggests that fostering a conducive organisational culture may be more critical than isolated managerial directives or individual competencies when implementing AI-driven systems. The study provides actionable insights for hospital administrators and policymakers aiming to align AI implementation strategies with organisational readiness, thereby contributing to the emerging body of knowledge on AI adoption in healthcare facilities management.

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Publication Details

Journal
Frontiers in Built Environment
Published
2026-03-04
DOI
https://doi.org/10.3389/fbuil.2025.1717168
Primary Topic
Facilities and Workplace Management
Type
article
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article

A PLS-SEM analysis of people, management, and organisational culture influences on AI-driven hospital facilities management systems

Motheo Meta Tjebane, Molusiwa Stephan Ramabodu
Frontiers in Built Environment
Facilities and Workplace Management
article

A PLS-SEM analysis of people, management, and organisational culture influences on AI-driven hospital facilities management systems

Motheo Meta Tjebane, Molusiwa Stephan Ramabodu
article en

Abstract

Introduction As hospitals increasingly integrate artificial intelligence (AI) into facility and asset management, understanding the organisational and human factors influencing this transition has become essential. Despite growing interest in AI-driven facility management, there is limited empirical evidence on how organisational culture, management commitment, and staff-related factors shape AI adoption in hospital environments. Methods This study employed Partial Least Squares Structural Equation Modelling (PLS SEM) to analyse data from a diverse sample of built environment professionals with experience in hospital asset and facilities management. The model assessed the influence of organisational culture, managerial commitment and people-related factors on staff adaptability and AI integration. Results The structural model demonstrated strong explanatory power (R 2 = 0.901), confirming that organisational culture significantly influences both staff adaptability and AI integration within hospital facility management systems. Unexpectedly, hypotheses related to people factors (H1) and management commitment (H2) were not statistically significant. These results may be attributed to sample characteristics or potential measurement limitations. Discussion The findings highlight the dominant and necessary role of organisational culture in shaping AI adoption within hospital facility management—overshadowing individual-level and managerial influences. This suggests that fostering a conducive organisational culture may be more critical than isolated managerial directives or individual competencies when implementing AI-driven systems. The study provides actionable insights for hospital administrators and policymakers aiming to align AI implementation strategies with organisational readiness, thereby contributing to the emerging body of knowledge on AI adoption in healthcare facilities management.

Frontiers in Built EnvironmentVol. 11
Durban University of Technology (ZA)
Openalex Percentile: Top 43%
Facilities and Workplace Management
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A PLS-SEM analysis of people, management, and organisational culture influences on AI-driven hospital facilities management systems — Motheo Meta Tjebane, Molusiwa Stephan Ramabodu · Frontiers in Built Environment (2026) | TGRS Research Map | TGRS