Network Model and Analysis of Construction Project Safety Risk and Stakeholder Based on SNA
- 10.2991/assehr.k.211216.047How to use a DOI?
- SNA; Construction project; Stakeholder; Security risks; 2-mode network
In this article, the WBS-RBS risk identification method was used, combined with the case analysis, to identify the main stakeholders and safety risks involved in the construction project. Based on SNA, a 2-mode network model of stakeholders and security risks was constructed, and the network relationship between them was visualized by UCINET, and the network density, node strength and position of core-edge roles were analyzed. The results show that, stakeholders of construction projects are closely related to safety risks, and four core stakeholders, namely the construction unit, the construction unit, the supervision unit and the operation personnel are identified. There are 10 core risk factors, which respectively are illegal approval process, ignorance of risk warning, lack of safety education, bad construction site environment, failure to use personal protective equipment, imperfect management system, the dangerous parts without a warning sign, poor government regulation，bad construction site management, weak risk identification ability, weakening the key construction project risk governance and the governance body. This article provides a certain reference for making and promoting safety management measures of construction projects.
- © 2021 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - Qinqin Zhang AU - Ying Song AU - Junwei Shi PY - 2021 DA - 2021/12/17 TI - Network Model and Analysis of Construction Project Safety Risk and Stakeholder Based on SNA BT - Proceedings of the 2021 International Conference on Social Sciences and Big Data Application (ICSSBDA 2021) PB - Atlantis Press SP - 249 EP - 260 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.211216.047 DO - 10.2991/assehr.k.211216.047 ID - Zhang2021 ER -