This study conducts an original, data-driven bibliometric investigation into the evolution of construction risk management (CRM) research between 2002 and 2024. Drawing on a dataset of 778 peer-reviewed publications retrieved from the Web of Science Core Collection, the study utilizes VOSviewer and Biblioshiny to empirically map publication trends, thematic clusters, and regional distributions. A key contribution of the research is the development of a four-phase thematic evolution model that illustrates the transition from conventional risk classification approaches to integrated frameworks incorporating advanced technologies such as Artificial Intelligence (AI), Building Information Modelling (BIM), and Environmental, Social, and Governance (ESG) principles. The analysis reveals three dominant thematic axes: methodological innovations in risk assessment, technological advancement in digital integration, and socio-political dynamics in stakeholder governance. Despite the increasing academic emphasis on data-driven approaches, persistent regional disparities and implementation gaps remain, particularly in underrepresented regions such as Sub-Saharan Africa and South Asia. The study also uncovers the fragmented integration of ESG dimensions across literature, suggesting the need for more coherent and context-sensitive risk models. By offering a longitudinal and spatial synthesis of global knowledge production, this research enhances our understanding of how CRM has evolved and where critical research gaps persist. The findings aim to inform future efforts toward inclusive, resilient, and adaptable risk management strategies in the construction sector.
ESG integration Risk perception Thematic mapping Regional disparities Stakeholder governance Construction sector
Ethics committee approval was not required for this study because of there was no study on animals or humans.
I would like to thank Fatma KÜRÜM VAROLGÜNEŞ for her valuable support.
This study conducts an original, data-driven bibliometric investigation into the evolution of construction risk management (CRM) research between 2002 and 2024. Drawing on a dataset of 778 peer-reviewed publications retrieved from the Web of Science Core Collection, the study utilizes VOSviewer and Biblioshiny to empirically map publication trends, thematic clusters, and regional distributions. A key contribution of the research is the development of a four-phase thematic evolution model that illustrates the transition from conventional risk classification approaches to integrated frameworks incorporating advanced technologies such as Artificial Intelligence (AI), Building Information Modelling (BIM), and Environmental, Social, and Governance (ESG) principles. The analysis reveals three dominant thematic axes: methodological innovations in risk assessment, technological advancement in digital integration, and socio-political dynamics in stakeholder governance. Despite the increasing academic emphasis on data-driven approaches, persistent regional disparities and implementation gaps remain, particularly in underrepresented regions such as Sub-Saharan Africa and South Asia. The study also uncovers the fragmented integration of ESG dimensions across literature, suggesting the need for more coherent and context-sensitive risk models. By offering a longitudinal and spatial synthesis of global knowledge production, this research enhances our understanding of how CRM has evolved and where critical research gaps persist. The findings aim to inform future efforts toward inclusive, resilient, and adaptable risk management strategies in the construction sector.
ESG integration Risk perception Thematic mapping Regional disparities Stakeholder governance Construction sector
Ethics committee approval was not required for this study because of there was no study on animals or humans.
I would like to thank Fatma KÜRÜM VAROLGÜNEŞ for her valuable support.
| Birincil Dil | İngilizce |
|---|---|
| Konular | Risk Analizi, Altyapı Mühendisliği ve Varlık Yönetimi, İnşaat Mühendisliğinde Sayısal Modelleme, İnşaat Mühendisliğinde Sistem Tanımlama, İnşaat Yapım Mühendisliği |
| Bölüm | Research Articles |
| Yazarlar | |
| Erken Görünüm Tarihi | 12 Kasım 2025 |
| Yayımlanma Tarihi | 15 Kasım 2025 |
| Gönderilme Tarihi | 3 Temmuz 2025 |
| Kabul Tarihi | 27 Ekim 2025 |
| Yayımlandığı Sayı | Yıl 2025 Cilt: 8 Sayı: 6 |