Abstract
Given the highly visible nature, transportation infrastructure construction projects are often exposed to numerous unexpected events, compared to other types of construction projects. Despite the importance of predicting financial losses caused by risk, it is still difficult to determine which risk factors are generally critical and when these risks tend to occur, without benchmarkable references. Most of existing methods are prediction-focused, project type-specific, while ignoring the timing aspect of risk. This study filled these knowledge gaps by developing a neural network-driven machine-learning classification model that can categorize causes of financial losses depending on insurance claim payout proportions and risk occurrence timing, drawing on 625 transportation infrastructure construction projects including bridges, roads, and tunnels. The developed network model showed acceptable classification accuracy of 74.1%, 69.4%, and 71.8% in training, cross-validation, and test sets, respectively. This study is the first of its kind by providing benchmarkable classification references of economic damage trends in transportation infrastructure projects. The proposed holistic approach will help construction practitioners consider the uncertainty of project management and the potential impact of natural hazards proactively, with the risk occurrence timing trends. This study will also assist insurance companies with developing sustainable financial management plans for transportation infrastructure projects.
Highlights
The third-party liability insurance has been commonly adopted by the owners of largescale construction projects, in order to cover economic damages caused by construction operation, project management, or other external risks [1]
With the highest classification accuracy, NN 9-70-3 was selected as the final model to classify financial loss clusters by claim payout ratios and risk occurrence timing in bridge, road, and tunnel construction projects
The third-party liability insurance has been commonly adopted by the owners of large-scale construction projects, in order to cover economic damages caused by construction operation, project management, and other external risks
Summary
It is pivotal to use proper risk assessment methods and to contribute to improving sustainability in project management. Given the significance of sustainable risk management, many research efforts were made by estimating economic damages in broad ranges of construction projects [1,6,7,8,9,10,11,12,13,14,15,16]. Transportation infrastructure is well known as a key built asset to facilitate sustainable economic growth [17,18,19,20]. As essential social and economic assets, transportation infrastructure systems (e.g., roads, bridges, tunnels) construct space, enhance the productivity of a nation by increasing the mobility and Sustainability 2021, 13, 6376.
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