Decision Making and Supply Chain Risk Management for Construction Contractors

Xiao Shan

Abstract

The construction industry faces particularly complex supply chain risks and construction companies are under increasing pressure to manage and mitigate them effectively. Especially nowadays, as Singapore government promoting new construction techniques. new construction methods bring both benefits and risks. For example. new construction techniques promoted by the government towards productivity improvement such as the use of prefabricated prefinished volumetric construction (PPVC) methods require coordination of many third parties and suppliers of raw materials. These are vulnerable to risks of disruption if not managed properly. Thus, it is crucial for main contractor to take cautious on risk measures to improve their market competitiveness.

However, no study has addressed those risk factors and their impact on project time and cost properly. Thus, main contractors who is willing to invest in risk measures that does not necessarily bring the expected effectiveness or assurance of the achievement of project objective. The reason is that they are lack the of self-risk assessment skills and invest in the measures that does not able to provide optimal results. In order to reduce the unforeseen factors and invest the measures that can mitigate the risks effectively, it is crucial to develop models or framework to help main contractor identify the risk factors and quantify the impact, hence grasp the methods to select optimal solutions before investment.

This study is aimed at helping main contractors gain the skills of self-assessment of risk factors they faced at any stages of the project by building a series model that they can apply and use. Moreover, they are expected to apply and use the framework at any other decision-making problem. Not only on risk measurements selection, but also any other issues with multi-criteria factors that require decision making.

This study initiates by identifying the various typical risk issues of main contractor faced in a broad perspective with fishbone diagram tool. To ensure the validity of the risk information, it is carried out among the team who are experienced in construction works. The available approaches are also listed down at this stage. Then, developing an Analytic model to quantify those risk factors in terms of their impact on the objective, which is project success completion in this study, rank the approaches according to their effectiveness with respect to the risk factors. After that, a cash flow analysis is conducted for each approach. Follow with a Monte Carlo Simulation (@ Risk) for cost analysis under different uncertainties. Further with extreme case scenario analysis to identify the critical factors and impact. After obtaining the effectiveness and expected cost of alternatives, a linear programming model is built to help decision maker select the optimal alternative(s). The objective function is to maximize the effectiveness (weights) of the alternatives while subject to constraints such as budget limits, control cost variances. For an overall view, a sensitivity analysis is carry out to generate a table result that shows different solution under different budget constraints. A PYTHON program is written to solve the model. The code allows decision maker to input in the requirements and generate the optimal result.