| Summary: | High-speed rail (HSR) is renowned for its efficiency and environmental advantages, reducing fuel consumption, generating employment, boosting tourism, and mitigating congestion. The Texas HSR project aims to connect Dallas and Houston using Japanese-origin HSR technology. Despite securing regulatory approvals, it faces significant challenges. This thesis examines the project's characteristics, identifies its challenges, and prioritizes future considerations.
The research begins with an overview of the project, exploring common reasons for the failure of large-scale projects, with a focus on demand estimation and organizational design. It then analyzes future demand for Texas HSR using two data sources: the Longitudinal Employer-Household Dynamics program’s Origin-Destination Employment Statistics (LODES) and the Next Generation National Household Travel Survey (NextGen NHTS). LODES data offers insights into workers’ transportation patterns and potential ridership, supporting current estimates but indicating areas for refinement. NextGen NHTS data aids in more precise travel demand modeling. The thesis recommends integrating multiple updated data sources for robust forecasting.
Applying the ARIES framework, the thesis examines the Texas HSR project's enterprise architecture through landscape mapping, stakeholder analysis, and SWOT analysis. Findings suggest that a collaborative Japanese-U.S. system, sharing critical information and expertise, can leverage strengths and opportunities. However, this requires significant effort and coordination due to limited experience and multiple entities, with workforce uncertainty as a risk. Effective collaboration and talent retention are crucial. To address these issues, a survey is conducted, followed by the envisioned future capturing. Then, the thesis proposes three alternative architectures. Alternative 3, which consolidates key entities for better resource management, is preferred among them. It also explores extreme scenarios and recommends a phased implementation plan to ensure smooth transitions and mitigate resistance to change. The thesis concludes with a summary of findings and a discussion of limitations and future work.
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