Risk and innovation in project delivery method selection for complex highway projects

The selection of a project delivery method (PDM) is a crucial decision that state highway agencies (SHAs) must make during the pre-procurement stage of infrastructure projects. The chosen PDM will determine the project's stakeholders, contract structure, final design, and construction. However, the PDM selection process remains challenging due to uncertainties stemming from low project scope definition during evaluation and the evolution of PDMs over the last 20 years. When first implemented, design-build (DB) was seen as a way to transfer risk to contractors and improve cost and schedule performance through early integration and overlap of design and construction. However, recent studies have questioned the effectiveness of DB contracts in terms of cost performance and unnecessary risk transfer. As such, SHAs must adjust their PDM selection processes to account for these factors. This dissertation aims to provide comprehensive guidance for efficient PDM selection for complex highway projects, with input from the private sector (Industry), the Texas Department of Transportation (TxDOT), and the Federal Highway Administration (FHWA). The first chapter addresses the gap in defining innovation and complexity for PDM selection, outlining six dimensions grouped by inherent project complexity and exogenous innovation opportunities. The second chapter presents empirical impact assessments for selection criteria to achieve cost- and schedule-related goals, emphasizing the tradeoff between DB and DBB selection and the importance of risk management and mitigation. The third chapter identifies factors that impact risk assessment and allocation in DB contracts. Building on these results, the dissertation’s final chapter outlines a deterministic and probabilistic PDM selection framework developed for TxDOT as an implementation case study. Overall, this dissertation contributes to PDM selection literature by providing a novel approach that defines innovation, incorporates uncertainty and risk management strategies, and is independent of project cost estimates. By providing comprehensive guidance for efficient PDM selection, this work can help SHAs make informed decisions to optimize project outcomes.