Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/89607
標題: 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
A Study on Factors Affecting the Surrounding Dwelling Price of Science Park: The Case of Hsinchu Science Park
作者: You-Ting Ji
紀侑廷
關鍵字: 特徵價格;新竹科學園區;住宅房價;Hedonic Price;Hsinchu Science Park;Dwelling Price
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摘要: 
科學園區的設置對周邊鄰近房地產價格具有拉抬的效應已獲國內外實證研究的肯定。1996年,遠見雜誌評選出新竹縣、市是全台灣(北高二市除外)最理想居所。另天下雜誌公布2008年幸福城市排行榜,新竹市再度蟬連冠亞軍,是台灣最幸福的城市之一。為瞭解科學園區周邊房市需求的實質屬性,本研究應用特徵價格理論實證竹科周遭區域房價的影響因素,將房屋外部及內含特徵屬性細分為個別、區位及可及性三類,再依所取得2010至2012年之台灣不動產交易中心之實際成交公報資料進行實證研究。分別以傳統迴歸線性模式及半對數線性模式建構新竹市、竹北市的房價特徵模型,從而再挑出最適當模式作為房價評價模型,並加以進行特徵邊際價格分析,以提供有買賣、投資需求的民眾或營建業者參考。

實證結果顯示,以半對數線性模式所建構之住宅房價特徵模型對新竹市、竹北市的房價皆具有高度解釋能力(R2分別為0.782及0.888)。影響新竹市住宅房價的主要特徵為:使用樓層、住宅類型、車位型態、區位、距竹科距離。而影響竹北市住宅房價的主因亦同於新竹市外,尚有廳數、衛數。無論於新竹市或竹北市,距離竹科愈近住宅房價愈高,竹科的設置確實有顯著帶動周邊房價的效果。此外,住宅所在的區位不同會造就房價價差,尤其以位居具備便利生活機能的區位價差最大,最受購屋者的青睞。

It has been empirically confirmed that the establishment of a science park can boost the real estate prices for its neighboring area. Global Views Monthly Magazine selected Hsinchu City and Hsinchu County as the best place to live after Taipei City and Kaohsiung City in 1996. In 2008, Happy city rank published by Global Views Monthly Magazine, Hsinchu City was again the second and one of the happiest cities in Taiwan. In order to understand the actual features for real estate needs around a science park, this study applied hedonic price theory to empirically verify the factors affecting of real estate prices for areas around Hsinchu Science Park. External and internal house features were divided into three types: individual features, location features and accessibility. The actual trading prices from 2010 to 2013 released by Taiwan's Real Estate Portal were then used in the empirical analysis. The traditional linear regression model and semi-log linear model were applied to build hedonic models for dwelling prices in Hsinchu City and Zhubei City. The most appropriate model was then selected from them as the evaluation model for dwelling prices, and provide public or builder as a reference by helonic marginal price analysis.

Our empirical results indicate that the explanatory ability for our models based on semi-log linear model for dwelling price in Hsinchu City and Zhubei City is high (R2= 0.782 and 0.888 respectively.) The major features influencing dwelling price in Hsinchu City were floor number, type of house, type of parking, location and distance from Hsinchu Science Park. For Zhubei City, the major features were the same as those of Hsinchu City in addition to number of rooms and bathrooms. For both cites, the closer the houses to Hsinchu Science Park the more expensive they are. Therefore, the setup of Hsinchu Science Park indeed significantly boosted the housing price for its neighboring areas. Besides, location contributed to the difference in price. In particular, convenient locations were what buyers like the most.
URI: http://hdl.handle.net/11455/89607
其他識別: U0005-2401201417322000
Rights: 同意授權瀏覽/列印電子全文服務,2014-01-28起公開。
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