The International Energy Agency (IEA) anticipates the global energy demand to grow by more than 25% by 2040, requiring more than $2 trillion a year of investment in new energy supply (IEA, 2018). With power needs increasing as populations grow and climate extremes become more routine, power companies seek to continually increase capacity, improve efficiency, and provide resilience to the power grid, such that they can meet the energy needs of the societies they serve, often while trying to minimize their carbon emissions. Despite significant research dedicated to planning for industrial projects, including power generation projects as well as the pipeline projects that enable power generation and distribute power, there are still endemic cost overruns and schedule delays in large scale power generation projects. This research explores root causes of these seemingly systemic project performance issues that plague power generation projects. Specifically, this work analyzes approximately 770 power and pipeline projects and identifies how project performance indicators (i.e., cost and schedule performance) as well as planning indicators, compare in two regulatory environments, namely nonregulated and regulated markets. This contributes explicit understanding of the relationship between project performance and regulatory environment, both quantitatively and qualitatively, to the pipeline and power project planning and construction bodies of knowledge. Following an understanding of nonregulated versus regulated markets, this research takes a deeper dive into one highly-regulated power sector, the nuclear power sector, and explores root causes for cost overruns and schedule delays. This work leverages gray literature (i.e., newspaper articles) as sources, in order to analyze projects individually (most academic literature presents data about an aggregated set of projects) and understand the public perception of risks associated with such projects. This work contributes an understanding of the risks associated with nuclear power plant construction to the nuclear power plant construction body of knowledge. Ultimately, the findings from this research support improved planning for power and pipeline projects, in turn leading to more predictable projects, in terms of cost and schedule performance, regardless of regulatory environment. This enables power providers to meet the capacity demands of a growing population within budget and schedule.

Alternative Project Delivery Methods (APDMs), namely Design Build (DB) and Construction Manager at Risk (CMAR), grew out of the need to find a more efficient project delivery approach than the traditional Design Bid Build (DBB) form of delivery. After decades of extensive APDM use, there have been many studies focused on the use of APDMs and project outcomes. Few of these studies have reached a level of statistical significance to make conclusive observations about APDMs. This research effort completes a comprehensive study for use in the horizontal transportation construction market, providing a better basis for decisions on project delivery method selection, improving understanding of best practices for APDM use, and reporting outcomes from the largest collection of APDM project data to date. The study is the result of an online survey of project owners and design teams from 17 states representing 83 projects nationally. Project data collected represents almost six billion US dollars. The study performs an analysis of the transportation APDM market and answers questions dealing with national APDM usage, motivators for APDM selection, the relation of APDM to pre-construction services, and the use of industry best practices. Top motivators for delivery method selection: the project schedule or the urgency of the project, the ability to predict and control cost, and finding the best method to allocate risk, as well as other factors were identified and analyzed. Analysis of project data was used to compare to commonly held assumptions about the project delivery methods, confirming some assumptions and refuting others. Project data showed that APDM projects had the lowest overall cost growth. DB projects had higher schedule growth. CMAR projects had low design schedule growth but high construction schedule growth. DBB showed very little schedule growth and the highest cost growth of the delivery methods studied. Best practices in project delivery were studied: team alignment, front end planning, and risk assessment were identified as practices most critical to project success. The study contributes and improves on existing research on APDM project selection and outcomes and fills many of the gaps in research identified by previous research efforts and industry leaders.

Front End Planning (FEP) is a critical process for uncovering project unknowns, while developing adequate scope definition following a structured approach for the project execution process. FEP for infrastructure projects assists in identifying and mitigating issues such as right-of-way concerns, utility adjustments, environmental hazards, logistic problems, and permitting requirements. This thesis describes a novel and effective risk management tool that has been developed by the Construction Industry Institute (CII) called the Project Definition Rating Index (PDRI) for infrastructure projects. Input from industry professionals from over 30 companies was used in the tool development which is specifically focused on FEP. Data from actual projects are given showing the efficacy of the tool. Critical success factors for FEP of infrastructure projects are shared. The research shows that a finite and specific list of issues related to scope definition of infrastructure projects can be developed. The thesis also concludes that the PDRI score indicates the current level of scope definition and corresponds to project performance. Infrastructure projects with low PDRI scores outperform projects with high PDRI scores.