Skip navigation

DSpace

機構典藏 DSpace 系統致力於保存各式數位資料(如:文字、圖片、PDF)並使其易於取用。

點此認識 DSpace
DSpace logo
English
中文
  • 瀏覽論文
    • 校院系所
    • 出版年
    • 作者
    • 標題
    • 關鍵字
    • 指導教授
  • 搜尋 TDR
  • 授權 Q&A
    • 我的頁面
    • 接受 E-mail 通知
    • 編輯個人資料
  1. NTU Theses and Dissertations Repository
  2. 工學院
  3. 土木工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98572
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor許聿廷zh_TW
dc.contributor.advisorYu-Ting Hsuen
dc.contributor.author張肇杰zh_TW
dc.contributor.authorChao-Chieh Changen
dc.date.accessioned2025-08-18T00:55:30Z-
dc.date.available2025-08-18-
dc.date.copyright2025-08-15-
dc.date.issued2025-
dc.date.submitted2025-08-05-
dc.identifier.citation林楨家、施亭伃(2007)。大眾運輸導向發展之建成環境對捷運運量之影響:臺北捷運系統之實證研究。《運輸計劃季刊》,36(4),451–476。
何煖軒(2010)。高鐵車站聯外軌道運輸系統之規劃。《全球管理與經濟》,6(2),85–104。
謝澤星(2018)。高速鐵路站區的就業縉紳化。國立臺灣大學工學院建築與城鄉研究所碩士論文。
簡博秀(2015)。第三波的仕紳化與再層域競爭的國家政權—臺南中國城更新計畫。《城市學學刊》,6(1),63–92。
楊家欣(2012)。高速鐵路對臺灣交通可及性的影響。國立交通大學碩士論文。
游舒涵(2019)。以仕紳化地圖觀點探討臺北市1999至2018年自辦重建都市更新案之空間現象。國立成功大學碩士論文。
張維修(2012)。都市更新不曾發生:台北市的上流化政策分析。《國立台灣大學建築與城鄉研究學報》,20,63–92。
李承嘉、戴政新、廖麗敏、廖本全、林欣雨(2010)。鄉村仕紳化—以宜蘭縣三星鄉三個村為例。《台灣土地研究》,13(2),101–147。
胡志平(2010)。台灣高鐵通車營運對住宅價格之衝擊影響分析-以新竹車站為例。《建築與規劃學報》,11(2),77–88。
鍾若晴(2015)。捷運對仕紳化的影響。國立臺灣大學地理環境資源學系碩士論文。
胡凱傑(2020)。高雄鐵路地下化對住宅價格之影響。國立中山大學碩士論文。
賴奕翔(2023)。台灣的學歷貶值與教育策略。《台灣社會學刊》,70,1–40。
黃佳鈴、張金鶚(2005)。從房地價格分離探討地價指數之建立。《台灣土地研究》,8(2),73–106。
梁仁旭(2010)。不動產價值逆折舊之比較研究。《地政學報》,110,1–26。
交通部鐵道局(2019)。全國高快速鐵路網整體規劃及前瞻基礎建設計畫。
國家發展委員會(2017)。前瞻基礎建設計畫總體規劃報告。
新竹市政府(2013、2022)。新竹市政府統計資料。
臺南市政府(2013、2022)。臺南市政府公開資料。
內政部不動產資訊平臺(2013、2017、2022)。房屋交易及住宅價格指數(HPI)資料。
Glass, R. (1960). London: Aspects of change. MacGibbon & Kee.
Lees, L., Slater, T., & Wyly, E. (2008). Gentrification. Routledge.
Zuk, M., Bierbaum, A. H., Chapple, K., Gorska, K., & Loukaitou-Sideris, A. (2017). Gentrification, Displacement, and the Role of Public Investment. Journal of Planning Literature, 33(1), 31–44.
Smith, N. (1996). The new urban frontier: Gentrification and the revanchist city. Routledge.
Lin, J. J., Yai, T., & Chen, C. H. (2022). Temporal changes of transit-induced gentrification: A forty-year experience in Tokyo, Japan. Annals of the American Association of Geographers, 112(1), 247–265. https://doi.org/10.1080/24694452.2021.1910478
Lin, J. J., & Chung, J. C. (2017). Metro-induced gentrification: A 17-year experience in Taipei. Cities, 67, 53–62. https://doi.org/10.1016/j.cities.2017.04.019
Higgins, C. D., & Kanaroglou, P. S. (2016). Forty years of modelling rapid transit’s land value uplift in North America: Moving beyond the tip of the iceberg. Transport Reviews, 36(5), 610–634. https://doi.org/10.1080/01441647.2016.1174748
Loumeau, G., & Russo, A. (2022). Second-hand gentrification: Theory and evidence from high-speed rail extensions. CESifo Working Paper, No. 9992, 1–62. https://ssrn.com/abstract=4250022
Walks, R. A., & Maaranen, R. (2013). Gentrification, social mix, and social polarization: Testing the linkages in large Canadian cities. Urban Geography, 29(4), 293–326. https://doi.org/10.2747/0272-3638.29.4.293
Hackworth, J., & Smith, N. (2001). The changing state of gentrification. Tijdschrift voor Economische en Sociale Geografie, 92(4), 464–477. https://doi.org/10.1111/1467-9663.00172
Smith, N. (2002). New globalism, new urbanism: Gentrification as global urban strategy. Antipode, 34(3), 427–450. https://doi.org/10.1111/1467-8330.00249
Miwa, N., Bhatt, A., & Kato, H. (2022). High-speed rail development and regional inequalities: Evidence from Japan. Transportation Research Record: Journal of the Transportation Research Board, 2676(1), 1–12. https://doi.org/10.1177/03611981221078566
Wang, L., Jiang, M., Miwa, T., Bardaka, E., & Morikawa, T. (2020). Preliminary study on transit-induced residential gentrification in Nagoya, Japan. Asian Transport Studies, 6, 100022. https://doi.org/10.1016/j.eastsj.2020.100022
Du, Q., Huang, Y., Zhou, Y., Guo, X., & Bai, L. (2023). Impacts of a new urban rail transit line and its interactions with land use on the ridership of existing stations. Cities, 134, 104506. https://doi.org/10.1016/j.cities.2023.104506
Lin, J.-J., Tedong, P. A., & Wang, H.-Y. (2024). Association of proximity to transit stations with early-stage gentrification in a railway upgrade context: Evidence from Kuala Lumpur, Malaysia. Journal of Urban Planning and Development, 150(1). https://doi.org/10.1061/JUPDDM.UPENG-4322
Ahlfeldt, G. M. (2019). If we build it, will they pay? Predicting property price effects of transport innovations. Regional Science and Urban Economics, 77, 249–265. https://doi.org/10.1068/a4542
Guillen, J. (2023). Financial support failure and health results: The Peruvian case. PLoS One, 18(2), e0277327. https://doi.org/10.1371/journal.pone.0277327
Diao, M., Li, Q., Sing, T. F., & Zhan, C. (2023). Disamenities of living close to transit tracks: Evidence from Singapore's MRT system. Regional Science and Urban Economics, 103894. https://doi.org/10.1016/j.regsciurbeco.2023.103894
Gibbons, S., & Machin, S. (2005). Valuing rail access using transport innovations. Journal of Urban Economics, 57(1), 148–169. https://doi.org/10.1016/j.jue.2004.10.002
Pope, J. C. (2008). Buyer information and the hedonic: The impact of a seller disclosure on the implicit price for airport noise. Journal of Urban Economics, 63(2), 498–516. https://doi.org/10.1016/j.jue.2007.03.003
Baker, D. M., López Ochoa, E., & Greenlee, A. (2021). Transit development and housing displacement: The case of the Chicago Red Line Extension. Cities, 115, 103212. https://doi.org/10.1016/j.cities.2021.103212
Rosen, S. (1974). Hedonic prices and implicit markets: Product differentiation in pure competition. Journal of Political Economy, 82(1), 34–55. https://www.jstor.org/stable/1830899
Chau, K. W., & Chin, T. L. (2003). A critical review of literature on the hedonic price model. International Journal for Housing Science and Its Applications, 27(2), 145–165.
Angrist, J. D., & Pischke, J.-S. (2009). Mostly harmless econometrics: An empiricist’s companion. Princeton University Press. https://doi.org/10.2307/j.ctvcm4j72
Bertrand, M., Duflo, E., & Mullainathan, S. (2004). How much should we trust differences-in-differences estimates? The Quarterly Journal of Economics, 119(1), 249–275. https://www.jstor.org/stable/25098683
Anselin, L. (1988). Spatial econometrics: Methods and models. Springer. https://doi.org/10.1007/978-94-015-7799-1
LeSage, J., & Pace, R. K. (2009). Introduction to Spatial Econometrics. Chapman and Hall/CRC. https://doi.org/10.1201/9781420064254
Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN 978-0-471-49616-8.
Kiani, B., Lau, C., Sartorius, B., & Bergquist, R. (2024). Mastering geographically weighted regression: Key considerations for building a robust model. Geospatial Health, 19(1). https://doi.org/10.4081/gh.2024.1271
Rabiner, L. R. (1989). A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2), 257–286. https://doi.org/10.1109/5.18626
Damiano, L., Peterson, B., & Weylandt, M. (2017). A tutorial on hidden Markov models using Stan. Manuscript, Universidad Nacional de Rosario, University of Washington, Rice University. https://arxiv.org/abs/1712.08104
Bardaka, E., Delgado, M. S., & Florax, R. J. G. M. (2018). Causal identification of transit-induced gentrification and spatial spillover effects: The case of the Denver light rail. Journal of Transport Geography, 71, 15–31. https://doi.org/10.1016/j.jtrangeo.2018.06.010
Zuk, M., Bierbaum, A. H., Chapple, K., Gorska, K., & Loukaitou-Sideris, A. (2018). Gentrification, displacement, and the role of public investment. Journal of Planning Literature, 33(1), 31–44. https://doi.org/10.1177/0885412217716439
Hulten, C. R., & Wykoff, F. C. (1981). The measurement of economic depreciation. In Depreciation, inflation, and the taxation of income from capital (pp. 81–125).
Shilling, J. D., Sirmans, C. F., & Dombrow, J. F. (1991). Measuring depreciation in single-family rental and owner-occupied housing. Journal of Housing Economics, 1(4), 368–383. https://doi.org/10.1016/S1051-1377(05)80018-X
Malpezzi, S., Ozanne, L., & Thibodeau, T. G. (1987). Microeconomic estimates of housing depreciation. Land Economics, 63(4), 372–385. https://doi.org/10.2307/3146294
Goodman, A. C., & Thibodeau, T. G. (1995). Age-related heteroskedasticity in hedonic house price equations. Journal of Housing Research, 6(1), 25–42. https://www.jstor.org/stable/24825889
Goodman, A. C., & Thibodeau, T. G. (1997). Dwelling-age-related heteroskedasticity in hedonic house price equations: An extension. Journal of Housing Research, 8(2), 299–317. http://www.jstor.org/stable/24833644
Wilhelmsson, M. (2008). House price depreciation rates and level of maintenance. Journal of Housing Economics, 17(1), 88–101. https://doi.org/10.1016/j.jhe.2007.09.001
Sorensen, A. (2004). The making of urban Japan: Cities and planning from Edo to the twenty-first century. Routledge. ISBN 9780415354226.
Fraley, C., & Raftery, A. E. (2002). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association, 97(458), 611–631. https://doi.org/10.1198/016214502760047131
McLachlan, G., & Peel, D. (2000). Finite Mixture Models. John Wiley & Sons, Inc. http://dx.doi.org/10.1002/0471721182
Schwarz, G. (1978). Estimating the Dimension of a Model. The Annals of Statistics, 6(2), 461–464. http://www.jstor.org/stable/2958889
-
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98572-
dc.description.abstract本研究以臺鐵新竹六家線與臺南沙崙線為案例,結合量化模擬系統性分析鐵道支線延伸對新竹、臺南地區房地產價格與社區仕紳化現象的時空動態變化與影響。研究蒐集兩地區房屋交易資料,並整合村里層級社會經濟指標,從房價、教育程度、所得、人口結構等多面向進行實證檢驗。研究結果顯示鐵道支線延伸顯著提升車站周邊房價,並帶動高學歷、高所得人口進駐,產生明顯的仕紳化現象。新竹地區房價與仕紳化幅度高於臺南,且高鐵站、科學園區等設施周邊效果最為顯著。地理加權迴歸分析結果顯示,仕紳化與房價提升效應具高度空間異質性,且隨時間推進,正向影響逐漸由核心區外溢至鐵路沿線與外圍新興社區。臺南則以新興中產成長區為主,核心區老化與弱勢現象仍然存在。此外,隱藏式馬可夫模型結果證實顯示,大多數社區社會輪廓狀態高度穩定,僅少數邊緣化社區有機會因交通建設、人口遷入轉型為新興成長型聚落。臺南地區社區流動性較新竹為低,階層分化現象更為持久。本研究成果除補足臺灣鐵道支線與仕紳化議題的實證缺口,並顯示鐵道建設效益會隨空間結構與發展階段產生不同差異。因而政策規劃應因地制宜,兼顧區域均衡、環境品質與社會公平,以促進都市永續發展。zh_TW
dc.description.abstractThis study aims to explore the temporal and spatial dynamics of real estate prices and community gentrification in an extension line of Taiwan Railway from high speed rail stations in Hsinchu Liujia and Tainan Shalun, respectively. A comprehensive methodological framework is adopted, combining Difference-in-Differences (DiD), Spatial Error Model (SEM), Geographically Weighted Regression (GWR), and Hidden Markov Model (HMM) to systematically analyze the impacts of branch railway lines. Real estate transaction data from both regions are collected and integrated with village-level socioeconomic indicators. The empirical analysis examines multiple dimensions, including housing prices, education levels, income, and demographic structures. The results reveal that the extension of railway branch lines significantly increases housing prices near stations and attracts a higher proportion of highly educated and high-income residents, leading to pronounced gentrification effects. The extent of price increases and gentrification is comparatively higher in Hsinchu than in Tainan, with the most substantial impacts observed around the high-speed rail station and science parks. GWR analysis further highlights strong spatial heterogeneity in both gentrification and housing price effects. Over time, these positive effects gradually spill over from urban cores to areas along the railway and emerging suburban communities. In contrast, Tainan is characterized by emerging middle-class growth zones, while aging and social vulnerability remain in the urban central area. HMM results confirm that most community types are highly stable over time, with only a few marginalized communities showing potential for transformation into emerging growth clusters through transportation development and population in-migration. Compared to Hsinchu, community mobility in Tainan is lower, with more persistent social stratification. Results of this study fill a critical empirical gap in the research on railway branch lines and gentrification in Taiwan. It is also implicitly shown that impacts of railway development vary by spatial structure and stage of regional development. Policy planning should therefore be context-sensitive, balancing regional equity, environmental quality, and social fairness to promote sustainable urban development.en
dc.description.provenanceSubmitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-08-18T00:55:29Z
No. of bitstreams: 0
en
dc.description.provenanceMade available in DSpace on 2025-08-18T00:55:30Z (GMT). No. of bitstreams: 0en
dc.description.tableofcontents致謝 i
摘要 iii
Abstract v
目次 vii
圖次 xi
表次 xiii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 4
1.3 研究內容與流程 5
第二章 文獻回顧與評析 7
2.1 運輸及城鄉發展 7
2.2 仕紳化定義及演變 8
2.3 鐵道系統對房價與仕紳化之影響 11
2.4 綜合評析 14
第三章 研究方法與架構 17
3.1 假設提研 17
3.2 驗證方法 18
3.2.1 特徵價格法 (Hedonic Price Method) 19
3.2.2 差異中的差異法 (Difference-in-Differences) 19
3.2.2.1 平行趨勢假設 (Parallel Trend Assumption) 21
3.2.3 空間差異中的差異法 (Spatial DiD) 22
3.2.3.1 空間誤差模型 (SEM) 23
3.2.3.2 空間滯後模型 (SLM) 23
3.2.3.3 空間自迴歸組合模型 (SAC) 24
3.2.4 地理加權迴歸 (GWR) 25
3.2.5 隱藏式馬可夫模型 (HMM) 26
第四章 資料收集與分析 29
4.1 研究範圍 29
4.1.1 新竹六家線 29
4.1.2 臺南沙崙線 32
4.2 資料蒐集及處裡 34
4.3 資料變數定義 36
4.4 定義區域範圍 40
4.5 平行趨勢假設 43
第五章 研究結果與討論 47
5.1 不動產房產價格影響 47
5.1.1 不動產 DiD 模型 47
5.1.2 不動產 Spatial DiD 模型 50
5.2 村里層級仕紳化影響 54
5.2.1 村里 DiD 模型 54
5.2.2 村里 Spatial DiD 模型 56
5.2.3 地理加權迴歸模型 61
5.2.4 隱藏式馬可夫模型 66
5.3 分析結果相關討論 70
第六章 結論與建議 77
6.1 結論 77
6.2 研究限制 78
6.3 建議 79
參考文獻 81
-
dc.language.isozh_TW-
dc.subject鐵道支線zh_TW
dc.subject仕紳化zh_TW
dc.subject空間外溢zh_TW
dc.subject差異中差異分析法zh_TW
dc.subject隱藏式馬可夫模型zh_TW
dc.subjectHidden Markov Modelen
dc.subjectRailway branch lineen
dc.subjectGentrificationen
dc.subjectSpatial spilloveren
dc.subjectDifference-in-Differences analysisen
dc.title高鐵聯外支線對車站周邊仕紳化影響之研究zh_TW
dc.titleThe Impact of Railway Branch Lines Connecting High-Speed Rail on Gentrification of Station Nearby Areasen
dc.typeThesis-
dc.date.schoolyear113-2-
dc.description.degree碩士-
dc.contributor.coadvisor張學孔zh_TW
dc.contributor.coadvisorS K Jason Changen
dc.contributor.oralexamcommittee林楨家zh_TW
dc.contributor.oralexamcommitteeJen-Jia Linen
dc.subject.keyword鐵道支線,仕紳化,空間外溢,差異中差異分析法,隱藏式馬可夫模型,zh_TW
dc.subject.keywordRailway branch line,Gentrification,Spatial spillover,Difference-in-Differences analysis,Hidden Markov Model,en
dc.relation.page87-
dc.identifier.doi10.6342/NTU202503971-
dc.rights.note同意授權(全球公開)-
dc.date.accepted2025-08-11-
dc.contributor.author-college工學院-
dc.contributor.author-dept土木工程學系-
dc.date.embargo-lift2025-08-18-
顯示於系所單位:土木工程學系

文件中的檔案:
檔案 大小格式 
ntu-113-2.pdf7.36 MBAdobe PDF檢視/開啟
顯示文件簡單紀錄


系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。

社群連結
聯絡資訊
10617臺北市大安區羅斯福路四段1號
No.1 Sec.4, Roosevelt Rd., Taipei, Taiwan, R.O.C. 106
Tel: (02)33662353
Email: ntuetds@ntu.edu.tw
意見箱
相關連結
館藏目錄
國內圖書館整合查詢 MetaCat
臺大學術典藏 NTU Scholars
臺大圖書館數位典藏館
本站聲明
© NTU Library All Rights Reserved