Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/139258
|
| Title: | 桃園市公共自行車場站對鄰近住宅價格之影響
The Impact of Public Bike Station on Residential Housing Values Nearby in Taoyuan City |
| Authors: | 林子蕙
Lin, Tzu-Hui |
| Contributors: | 江穎慧
JIANG, YING-HUI
林子蕙
Lin, Tzu-Hui |
| Keywords: | 住宅價格
公共自行車系統
空間計量
Spline 迴歸
Housing price
Public bike system
Spatial econometrics
Spline regression |
| Date: | 2022 |
| Issue Date: | 2022-03-01 17:46:24 (UTC+8) |
| Abstract: | 近年來台灣公共自行車系統已趨向穩定,除了最早設立公共自行車系統的台北市及新北市兩大行政區外,桃園市公共自行車的發展更是日漸純熟,目前桃園市已建置 387 個站點,累積 5000 萬以上使用人次,公共自行車作為轉乘以及通勤的交通運具,不僅能帶動周邊商圈繁榮,尚具有休憩觀光等功能。過去文獻中多支持公共自行車對於周邊住宅價格存在價格溢價及資本化的影響,本文試圖釐清公共自行車系統對周邊住宅價格的影響為何。
本研究選取 2017 年至 2020 年不動產實價登錄交易資料作為研究對象,並運用公共自行車系統共 337 個站點之座標資料,運用特徵價格理論與迴歸模型進行公共自行車場站設站後對於周圍住宅價格之影響。本文統計說明桃園市公共自行車設站多設立於公園及公共場所附近,實證結果顯示公共自行車場站設立對於住宅價格有正向的影響,不同住宅類型影響公共自行車場站設站距離不同,對於鄰近的住宅價格有明顯的提升。
In recent years, Taiwan`s public bike system has become more stable. Apart from the two administrative districts of Taipei City and New Taipei City, which were the first to establish public bicycle systems, the development of public bikes in Taoyuan City is becoming more and more proficient. At present, Taoyuan City has built 387 stations, of bike sharing system in Taipei with over 50 million citizens that have used it.Sharing bike not only does it expand the service area of mass rapid transit system, but also promotes the development of locations or shopping areas near bike stations. In the past, many reports supported the impact of public bikes on the price of surrounding housing prices and capitalization. Therefore, this paper attempts to clarify the impact of bike sharing system on housing prices.
The real estate sales information in Taoyuan City from 2017 to 2020 along with 337 locations of bike stations is adapted in this study. Through the use of hedonic price theory and regression model to conduct a public bike station. The statistics show that Taoyuan City’s bike stations are mostly located near parks and public places. The empirical results show that the establishment of public bike stations has a positive impact on housing prices. Different residential types affect the distance between public bike stations, residential prices have risen significantly. |
| Reference: | 參考文獻
中文參考文獻：
江穎慧、莊喻婷、張金鶚，2017，「臺北市公共自行車場站對鄰近住宅價格之影響」，『運輸計畫季刊』，第 46 卷，第 4 期，399~428 頁。
朱健銘，2000，「土地利用空間型態之研究」，台灣大學地理學研究所碩士論文：臺北市。
李春長、梁志民、林豐文，2017，「捷運系統對鄰近住宅價格之影響 以差異中之差異法估計」，『台灣土地研究期刊』，第 20 卷，第 2 期，31~58 頁。
李泓見、張金鶚、花敬群，2006，「台北都會區不同住宅類型價差之研究」，台灣土地研究，9(1)，63-87。
林祖嘉、馬毓駿，2007，「特徵方程式大量估價法在臺灣不動產市場之應用」，住宅學報，16(2)，1-22。
林楨家、馮正民、黃麟淇，2005，「台灣高速鐵路系統對於地方發展之影響預測」，『運輸計劃季刊』，34(3): 391-412。
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』，第 11 卷，第 2 期，77~88 頁。
紀侑廷，2014，「科技園區周邊住宅房價影響因素之研究-以新竹科學園區為例」，國立中山大學學位論文。
許侶馨，1989，「捷運系統對沿線地區地價影響之研究」，交通大學運輸研究所碩士論文。
莊喻婷，2016，「臺北市公共自行車場站對鄰近住宅價格之影響」，國立政治大學地政學系碩士論文。
陳奕真，2018，「高速鐵路對於住宅價格之影響分析—臺灣實證研究」，國立政治大學地政學系碩士論文。
張金鶚、楊宗憲、洪御仁，2008，「中古屋及預售屋房價指數之建立、評估與整合－台北市之實證分析」，『住宅學報』，第 17 卷第 2 期，13~34 頁。
張怡文、江穎慧、張金鶚，2009，「分量迴歸在大量估價模型之應用--非典型住宅估價之改進」，『都市與計劃期刊』，36(3)，281-304。
洪得洋、林祖嘉，1999，「台北市捷運系統與道路寬度對房屋價格影響之研究」，『住宅學報』，第 8 期，47~67 頁。
彭建文、楊宗憲、楊詩韻，2009，「捷運系統對不同區位房價影響分析─以營運階段為例」，『運輸計畫季刊』，第 38 卷，第 3 期，275~296頁。
鄒克萬、鄭皓騰、郭幸福、楊宗名，2013，「應用空間特徵價格模型評估高速鐵路對土地價格影響之時空特性－以臺灣高鐵為例」，『建築與規劃學報』，第14 卷，第一期，47~66 頁。
馮正民、曾平毅、王冠斐，1994，「捷運系統對車站地區房價之影響」，『都市與計劃期刊』，第二十一卷第一期， 25-45 頁。
楊宗憲，1995，住宅價格指數之研究，國立政治大學地政學系碩士論文。
臺北市交通局交通統計查詢系統，2020, http://dotstat.taipei.gov.tw/。
廖四郎和陳靜宜，2013，「高速鐵路的時空效應對房屋價格的影響—以高雄為例」，『住宅學報』，第 22 卷，第 1 期，25~54 頁。
賴櫻芳，2019，高速鐵路車站對住宅價格影響，國立臺灣大學建築與城鄉研究所學位論文。
戴國正，2012，大眾捷運系統對房價影響效果之再檢視，國立政治大學地政學系碩士論文。
外文參考文獻：
Bin, G., Haijun, B., & Ying, L. (2015). “A study of the effect of a high-speed rail station on spatial variations in housing price based on the hedonic model”, Habitat International, Volume 49, pp.333-339.
Chad, C. Mary, E.G. (1998). “Railroad Development and Land Value”, Journal of Real Estate Finance and Economics, 16(2), pp.191-204.
Cliff, A. D. & Ord, J. K. (1982). Spatial Processes. Models and Applications. Paris, France: Institut National d`Etudes Démographiques.
Dziauddin, M. F. (2019), An Investigation of Condominium Property Value Uplift around Light Rail Transit Stations Using a Hedonic Pricing Model, Earth and environmental science, Volume 286, pp.1-12.
Fotheringham, A. S., Brunsdon, C., & Chaelton, M. (2003). Geographically Weighted Regression: Oxford, United Kingdom: Geographical Analysis.
Haizhen, W., Zaiyuan, G., Chuanhao, T., Yue X., & Li, F. (2018). “Subway Opening, Traffic Accessibility, and Housing Prices: A Quantile Hedonic Analysis in Hangzhou”, China, Sustainability, 10, 2254, pp.1-23.
Houthakker, H. S. (1952), The Review of Economic Studies. Oxford, United Kingdom: Oxford University Press.
Hui, S., Yuning, W., & Qingbo L. (2016). “The Impact of Subway Lines on Residential Property Values in Tianjin: An Empirical Study Based on Hedonic Pricing Model”, Discrete Dynamics in Nature and Society, Volume 2016, pp.164-173.
Jinghong, L. (2019). Will Dockless Bike Sharing System Alter the Subway Price Premium in Rental Market? Evidence from Beijing, MIT, Department of Urban Studies and Planning, MA.
Junhong, C., Yige, D., Xianling, Y., & Li, W. (2020). “The Last Mile Matters: Impact of Dockless Bike Sharing on Subway Housing Price Premium”, Management Science Articles in Advance, pp.1-20.
Michael, D. (2011). “The Impact of Transit-oriented Development on Housing Prices in San Diego, CA”, Urban studies, Volume 48(1), pp.101-127.
Midgley, P. (2011). Bicycle-sharing Schemes: Enhancing Sustainable Mobility in Urban Areas. New York, America: UN Department of Economic and Social Affairs.
Minmeng, T., & Deb, N. (2021), “How Does Air Pollution Influence Housing Prices in the Bay Area? ”, International Journal of Environmental Research and Public Health, Volume 18, pp.1-13.
Morito, T., & Hajime, S. (2008). “Measuring the impact of large-scale transportation projects on land price using spatial statistical models”, Papers in Regional Science,
Volume 87 Number 3, pp.385-401.
Richard, F. M. (1966), Household Production and Consumer Demand Functions, Econometrica, Volume. 34, No. 3, pp.699-708.
Rong, W., Li, Y., & Liwen, C. (2019). “The Impact of High-Speed Rail on Housing Prices: Evidence from China’s Prefecture-Level Cities”, Sustainability, 11, 3681, pp.2-18.
Rosen, S. (1974). “Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition”, The Journal of Political Economy, 82: 34-55.
Siqi, Z., Yangfei, X., Xiaonan, Z. & Rui W. (2016). “Transit development, consumer amenities and home values: Evidence from Beijing’s subway neighborhoods”, Journal of Housing Economics 33, pp.22–33.
Speyrer, J. F. & Ragas, W. R. (1911). “Housing Prices and Flood Risk: An Examination Using Spline Regression”, Journal of Real Estate Finance and Economics, Volume 4, pp.395-407.
Stacy, G. S., David, A. M. & Emily, N. Z. (2005). “The Composition of Hedonic Pricing Models”, Journal of Real Estate Literature, Volume 13, Iss. 1, pp.3-43.
Tobler, W. R. (1970). “A Computer Movie Simulating Urban Growth in the Detrpit Region”, Economic Geography, Volume 46, pp.234-240.
Upton, G, Fingleton, B.,1985, “Spatial Data Analysis by Example”, Willy New York.
Wen-Chi, L., & Xizhu, W. (2012). “Hedonic house prices and spatial quantile regression”, Journal of Housing Economics, Volume 21, pp.16-27.
William J. S. (1975). “Community Environment, Zoning, And The Market Value Of Single-Family Homes”, The Journal of Law & Economics, Volume 18, No. 2, pp.535-557.
Zhengyi, Z. & Anming, Z. (2021). “High-speed rail and industrial developments: Evidence from house prices and city-level GDP in China”, Transportation Research Part A,149, pp.98-113. |
| Description: | 碩士
國立政治大學
地政學系
108257001 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0108257001 |
| Data Type: | thesis |
| DOI: | 10.6814/NCCU202200289 |
| Appears in Collections: | [地政學系] 學位論文
|
Files in This Item:
| File |
Description |
Size | Format | |
|---|
| 700101.pdf | | 1541Kb | Adobe PDF2 | 0 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
