Applying social network analysis to identify the most effective persons according to their potential in causing accidents in construction projects

Abstract

Human errors are one of the main causes of accidents in the construction industry. Controlling all persons involved in a project with respect to safety issues are time-consuming and costly. It is clear that in each working group there is a person who affects others because of his experience, knowledge and etc. Therefore, improving the safety of an effective person's behaviour can lead to the safety of other people's behaviours. This study presents a new framework to detect effective persons by using social network analysis. To do this, firstly the most frequent accidents are identified and next, for each accident according to their activities and working groups the most influential person is identified. Finally, the influential level of each person in different accidents is combined with a new decision-making method to find the most influential person. The proposed framework was implemented in one of the construction projects in Iran.