Competitive strategy for the proposed Texas High Speed Rail Project : a system dynamics/ CLIOS process approach
Name
1003289941-MIT.pdf
Description
Full printable version
Size
10.15 MB
Format
Adobe PDF
Checksum (MD5)
81dd5d095c288782554f9f433838f014
Author(s)
Hidema, Takafumi
Advisor(s)
Joseph M. Sussman.
Alternative Title
Competitive strategy for the proposed Texas HSR Project : a system dynamics/ Complex, large-scale, integrated, open systems process approach
Date Issued
2017
Publisher
Massachusetts Institute of Technology
Abstract
The Texas High-Speed Rail (HSR) is an unprecedented US project proposed by a private company. This project has many uncertainties because it will be funded only by the private sectors and it is the first US HSR project using foreign technology. The HSRs are huge and complex systems involving political, economic and sociotechnical issues that are affected by and affect various stakeholders. Therefore, it is necessary to grasp the "whole picture" of the project to plan effective strategies to make it successful. The objective of this thesis is to identify how we can improve the system performance and propose recommendations to guide the project toward success. The CLIOS Process is applied to identify the current circumstances surrounding the project. Comparative study of HSR with other transportation modes and market analysis are conducted to identify competitive advantages of the HSR system and how to utilize these advantages to compete with other transportation modes. After these qualitative analyses, pricing strategy, capacity management and accessibility management are identified as the three "key factors for success." Based on the results, the System Dynamics (SD) approach is applied. Conceptualization of the HSR system by causal loop diagrams (CLDs) clarifies several feedback interactions between key variables, such as ridership, load factor, total travel time and fares. Then, the numerical SD model is created to conduct quantitative analysis over time. Sensitivity analysis for each policy parameter suggests how the HSR operator could improve system performance by implementing different strategies in the short to long run.
Description
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2017.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 193-202).
Subjects
Institute for Data, Systems, and Society.
Engineering Systems Division.
Technology and Policy Program.
MIT Department
Massachusetts Institute of Technology. Engineering Systems Division
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Technology and Policy Program
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