The Analysis of Trainset Fleet Size for Taiwan High Speed Rail

碩士 === 國立交通大學 === 管理學院高階主管管理碩士學程 === 102 === The trainset is one of the most expensive components in railway operations . The investment is substantial and the cost is usually over 10 billion NTdollars per trainset. It also has the characteristics of a sunk cost and long payback period. Additionally...

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Bibliographic Details
Main Authors: Wen, Yu-Ming, 温裕明
Other Authors: Jen,William
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/4947d3
Description
Summary:碩士 === 國立交通大學 === 管理學院高階主管管理碩士學程 === 102 === The trainset is one of the most expensive components in railway operations . The investment is substantial and the cost is usually over 10 billion NTdollars per trainset. It also has the characteristics of a sunk cost and long payback period. Additionally, trainset procurement usually has a long lead time from ordering to delivery. Therefore, while making decisions on trainset procurement it is an important issue for railway operators to estimate their fleet size based on operational needs, and future train service plans. Taiwan High Speed Rail (THSR) has inaugurated to commercial operations in 2007. At the beginning the train service was 133 trains per week and has increased to 954 trains per week at present (2014). As operation services grew, train dispatching has become increasingly difficult. Moreover, four new stations coming online, Nangang, Miaoli, Changhua and Yunlin, will gradually increase the ridership as well as the round trip time. As a result, it is necessary to forecast the future fleet size in advance for a trainset procurement decision to prevent service quality to deteriorate and to arrange a long term financial plan. This research has proposed two suggestions for future study. (1) Besides trainset requirement assessment, financial analysis, trainset modeling, equipment replacement and so on should be considered together. (2) Due to future uncertainty, long term operation planning should consider sensitive analysis.