Risk allocation model for price escalations in construction projects: Integrating bargaining game theory and probabilistic Bayesian modeling

Economic market uncertainties, like those witnessed during pandemics and supply chain-related challenges, introduce complexity in ascertaining precise price estimates for construction materials. Despite some studies on risk allocation in construction projects utilizing quantitative and qualitative approaches, these studies fail to explain the underlying process of risk allocation due to a lack of theoretical support, indicating a need for a more structured and theoretically grounded approach to understanding risk allocation, specifically under volatile market conditions. To bridge this knowledge gap, this study proposes a novel game-theoretical model integrating Bayesian statistics and bargaining game theory dynamics, offering a robust framework for optimal risk allocation and strategic decision-making in the face of material price fluctuations. Applied and validated in a bridge replacement project in Ohio, the model considers asphalt, nonreinforced concrete, steel reinforcement, and aggregates materials. The research findings provide insights into the influence of different considerations, such as the patience factor, on the optimal risk allocation proportion between the owner and contractor. Also, the findings show that the contracting parties can ensure an advantage in risk allocation during the negotiations by adapting their patience level. The model developed in this research could be potentially adapted to other contexts (geographic regions and construction project types) and can be expanded beyond two-player (contractor and project owner) bargaining scenarios.