Risk Factors Assessment Considering Change Degree for Mega-projects

AbstractRecently, techniques in the construction industry have rapidly developed, and alongside these changes there have been demands for the complexification, advancement and enlargement of the technical level and size. Thus, the risks are becoming increasingly diverse in the process of progress on construction projects. It is necessary to minimize the impacts of negative factors on the projects through the investigation and management of risk factors before they occur. But, the investigation and analysis of impacts are difficult due to the interdependent relationships among risk factors, and mega projects, in terms of project units, are on the rise. It is necessary to investigate risk factors considering the relationship among many changes. Therefore, this study was conducted to investigate risk factors and to evaluate the importance among the risk factors of a construction project while simultaneously considering the risk impact and change impact. If, prior to the beginning of construction work, risk factors with great impacts are managed based on the analysis results, they are expectedly applied as index to support the successful execution of a construction project

Analysis of Fatal Accidents and Their Causes in the Korean Construction Industry

The construction industry is one of the most hazardous industries in many countries. Many studies have asserted that industrial accidents could be prevented by eliminating their root causes. However, given that accident occurrence processes are considerably complex and often invisible, it is difficult to identify and eliminate the root causes. Based on this recognition, this paper aims to analyze the causality of construction accidents on the basis of direct causes that are classified into unsafe actions (UA) and unsafe conditions (UC). A logistic regression is applied to examine associations between UAs and UCs and their significances in triggering construction accidents. Then, a Delphi method is applied to determine the relationships between direct and root causes of construction accidents. This study contributes to an improved understanding of the complex causal process of construction accidents, which is a necessary stepping-stone to prevent construction accidents. Meanwhile, only one-to-one combinations of UCs and UAs are considered in this paper. Thus, follow-up studies to examine the impact of one-to-many or many-to-many combinations are needed

Application of Association Rule Mining and Social Network Analysis for Understanding Causality of Construction Defects

A construction defect can cause schedule delay, cost overrun and quality deterioration. In order to minimize these negative impacts of construction defects, this paper aims to analyze the causality of construction defects. Specifically, association rule mining (ARM) is used to quantify the interrelationships between defect causes, and social network analysis (SNA) is utilized to find out the most influential causes triggering generation of construction defects. The suggested approach was applied to 2949 defect instances in finishing work. Through this application, it was confirmed that the proposed approach can systematically identify and quantify causality among defect causes