Big data analysis model for predicting operational risk in overseas construction projects

Abstract

In this study, a big data analysis model was developed to predict the risks associated with overseas projects and a big data analysis technique. The risk analysis model can estimate the probability-cost interval for a planned project’s final cost by forming a probability density function and project costs through comparative analysis of data for a planned project and data for a previous similar project. This study attempted to collect a vast amount of information from the web and social networking services (SNS) in order to verify whether this information is sufficient to support the use of the web data analysis method used in this model. To this end, it was assumed that regional traffic conditions would be indicated on the web and SNS. In addition, two regions with different traffic conditions were selected, and then traffic-related keywords and words to enable assessment of traffic conditions were examined. Text information including these words was collected and the proportions of positive and negative words were analyzed. Results confirmed that two regions with different traffic conditions also had different numbers of negative words exhibited on the web.

Keywords

• overseas construction projects
• big data
• risk management
• risk analysis model
• project risk