Ontology-Based Integration of Enterprise Architecture and Project Management: A Systems Thinking Approach for Project-Based Organizations in the Architecture, Engineering, and Construction Sector

Construction projects are becoming increasingly complex due to their dynamic nature, the integration of multiple disciplines, and the need for strategic alignment between organizational processes and project management. However, traditional project management approaches often fail to address this complexity effectively. This study presents the application of IModel, a web-based semantic model grounded in systems thinking, designed to integrate enterprise architecture and project management. Through a case study conducted in a multinational AEC company, IModel was evaluated for its ability to enhance system interoperability, optimize processes, and support strategic decision-making. The methodology combined web semantic modeling with expert interviews and organizational data analysis. Findings indicate that IModel provides a comprehensive framework for knowledge management, reduces uncertainty, and improves decision-making in dynamic project environments. However, challenges related to model adoption, including the need for training in systems thinking and ontological modeling, were identified. This study contributes to the literature on innovation in construction project management, highlighting the potential of systems thinking and semantic tools to address complex problems in dynamic and evolving environments.

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Publication Details

Journal
Systems
Published
2025-06-16
DOI
https://doi.org/10.3390/systems13060477
Citations
5
Primary Topic
Business Process Modeling and Analysis
Type
article
Field-Weighted Citation Impact
11.42
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article

Ontology-Based Integration of Enterprise Architecture and Project Management: A Systems Thinking Approach for Project-Based Organizations in the Architecture, Engineering, and Construction Sector

Mauro Mancini, Edison Atencio, Guillermo Bustos
5 citations
Systems
Business Process Modeling and Analysis
11.42
article

Ontology-Based Integration of Enterprise Architecture and Project Management: A Systems Thinking Approach for Project-Based Organizations in the Architecture, Engineering, and Construction Sector

Mauro Mancini, Edison Atencio, Guillermo Bustos
article en
5 citations

Abstract

Construction projects are becoming increasingly complex due to their dynamic nature, the integration of multiple disciplines, and the need for strategic alignment between organizational processes and project management. However, traditional project management approaches often fail to address this complexity effectively. This study presents the application of IModel, a web-based semantic model grounded in systems thinking, designed to integrate enterprise architecture and project management. Through a case study conducted in a multinational AEC company, IModel was evaluated for its ability to enhance system interoperability, optimize processes, and support strategic decision-making. The methodology combined web semantic modeling with expert interviews and organizational data analysis. Findings indicate that IModel provides a comprehensive framework for knowledge management, reduces uncertainty, and improves decision-making in dynamic project environments. However, challenges related to model adoption, including the need for training in systems thinking and ontological modeling, were identified. This study contributes to the literature on innovation in construction project management, highlighting the potential of systems thinking and semantic tools to address complex problems in dynamic and evolving environments.

SystemsVol. 13(6)
Pontificia Universidad Católica de Valparaíso (CL), Politecnico di Milano (IT)
Openalex Percentile: Top 2%
Business Process Modeling and Analysis
11.42
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Ontology-Based Integration of Enterprise Architecture and Project Management: A Systems Thinking Approach for Project-Based Organizations in the Architecture, Engineering, and Construction Sector — Mauro Mancini, Edison Atencio, et al. · Systems (2025) | TGRS Research Map | TGRS