台灣高鐵營運策略之分析

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題名:	台灣高鐵營運策略之分析
作者:	賴螢潔;Ying-Chieh Lai
貢獻者:	統計研究所
關鍵詞:	高速鐵路;邏輯斯;STP;行銷組合（4P）
日期:	2006-06-07
上傳時間:	2009-09-22 11:01:58 (UTC+8)
出版者:	國立中央大學圖書館
摘要:	興建高速鐵路（High Speed Rail；簡稱HSR）為台灣地區交通建設中之一大突破，由於台灣地狹人稠及運輸需求不斷增加，加上民眾經濟能力的提升，對於交通運輸的服務水準要求及對時間價值之重要性也隨之提高，因此具有高速度、高運量及高準點度之高速鐵路為民眾所期待。除了提供最佳的硬體設備及服務外，依高鐵觀點而言，旅運者即是消費者，因此瞭解消費者之特性為重要之行銷策略，如此才能使高鐵更具市場競爭力，並多元化發展，為營運策略中重要之一環。本研究資料來源取自於交通部民國94年之「高速鐵路通車前民眾使用高鐵意願調查」，第一部分為高鐵行車安全信心度之探討，建立多項邏輯斯迴歸模型，由配適後的最終模型可知民眾對行車安全信心度受到年齡、教育程度與職業之影響。第二部分為高鐵行銷策略之探討，是使用旅運者搭乘高鐵目的之資料，經過複選題分析，選出兩個區隔市場（S）「返鄉、探親或訪友」與「觀光、休閒及旅遊」，再分別建立二元邏輯斯迴歸模型，利用其預測機率找出目標市場（T），依其需求提出合適之產品或服務，並做市場定位（P），最後分別建議不同之行銷組合（4P）。上述之研究結果可供後續研究者及高鐵有關當局參考。 The High Speed Rail（HSR）is a big breakthrough of the transportation constructions in Taiwan. The population density in Taiwan is getting higher than the transit volume of transportations. Moreover, the people put more emphasis on the quality of living with higher and higher income. They not only need faster but also higher service-level transportations. Due to above reasons, the high speed, high transit volume and high on-time percentage High Speed Rail is deeply expected by the people in Taiwan. On the position of the Taiwan High Speed Rail Consortium (THSRC), passengers are customers. Besides just providing the best hardware and service, THSRC have to realize the activity of customers to formulate marketing strategies. Therefore, THSR can have more competitiveness and diversification in the transportation marketing. The data is from the Ministry of Transportation and Communication in 2005. The first part of the research is the discussion of safety confidence level by the passengers. Built the polytomous logistic regression model and compared the fitted models to find out the best one. From the final model, we know that the safety confidence level is affected by the age, the education and the occupation. The second part of the research is the discussion of THSR marketing strategy. According to the multiple response analysis of the travel purposes by the passengers, we selected two market segmentations (S), which are “for homecoming and visiting relatives or friends” and “for sightseeing, leisure time and traveling”. Built the binary logistic regression model by market segmentations and used its predicted probability to find out the targeting market (T). Provided appropriate products or service for the two targeting markets and set up their market positioning (P). Finally, provided the marketing mix (4P) for the two targeting markets. The above results could be a reference for the following researchers and THSRC.
顯示於類別:	[統計研究所] 博碩士論文

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