臺灣博碩士論文加值系統

近年來各都市已將大眾運輸系統的發展列為重要目標，「高雄市區鐵路地下化計畫」緣起於政府鐵路捷運化政策，「高雄市區鐵路地下化計畫」預計於2018年8月正式營運通車，同時政府宣布完工後將拆除現有12座陸橋設施，屆時騰出來的地上空間可望提升都會區的土地使用效益。本研究以高雄市鐵路地下化完工後所拆除的陸橋設施對住宅大樓房價之影響為主要探討，採用2016年「內政部不動產交易實價查詢服務網」之住宅大樓成交資料為研究樣本，以最小平方迴歸與空間迴歸進行分析與比較，探討距離陸橋設施遠近與不同分量水準下對住宅大樓房價之影響，並加入相關住宅特徵因子探討不動產之定價。
根據最小平方迴歸模型之實證結果顯示建坪變數、屋齡變數、屋齡平方變數、總樓層變數、停車位數、房間數、廳數、衛浴數、虛擬變數距陸橋設施351-750公尺內和建坪與距離陸橋設施351-750公尺之交乘項對房價具有顯著之影響，其中建坪變數、屋齡平方變數、總樓層變數、停車位數、衛浴數和建坪與距離陸橋設施351-750公尺之交乘項有正向顯著的影響；而屋齡變數、房間數、廳數與距陸橋設施351-750公尺內的虛擬變數對住宅大樓房價對住宅大樓房價有負向的影響。根據空間迴歸模型中空間誤差模型實證結果顯示空間誤差係數呈顯著正相關，其它變數方面之顯著性也與最小平方迴歸相同。
不管在OLS模型或空間迴歸模型的結果都相同，比較各係數會發現空間模型中，建坪、屋齡、屋齡平方、廳數與衛浴數對房價的影響增加了，其中值得探討的是停車位數與衛浴數在加入空間要素後，係數的變化程度很大，代表停車位數在空間迴歸模型中對房價的影響程度較小，衛浴數對房價的影響程度較大。由此可見消費者於空間中對停車位數雖重視，但並非最主要影響房價之因素；相對影響房價之因素中，消費者對衛浴數更加重視。

關鍵字：鐵路地下化、預期效果、空間迴歸模型、鄰避設施

In recent years, the development of mass transit systems has been listed as an important target for cities. The railway underground project in Kaohsiung city originated from the government railway rapid transit policy. It is expected to be officially opened to traffic in August 2018. At the same time, the government announced that the existing 12 land bridge facilities will be dismantled. By the time, the vacated ground space is expected to enhance the land use efficiency of the metropolitan area. Therefore, this study investigates the impact on the housing price of residential buildings for the land bridge facilities demolished after the completion of the underground construction. The residential building transaction data of 「Ministry of the Interior real estate transaction price inquiry service network」in 2016 were adopted as research samples. Analysis and comparison with least squares regression and spatial regression, the impact of the distance from the land bridge facilities and the different component levels on the housing price of the residential building were investigated. Furthermore, we add relevant residential characteristics to explore the pricing of real estate.
According to the results of the least squares regression model, the floor space variables, the house age variables, the square of the house age, the total floor variables, the number of parking spaces, the number of rooms, the number of halls, the number of bathrooms, the virtual variables within 351-750 meters of the land bridge facilities and the cross-over on the floor space with 351-750 meters from the land bridge facilities have a significant impact on house prices. Among those variables, the floor space variables, the square of the house age, the total floor variables, the number of parking spaces, the number of bathrooms, and the cross-over on the floor space with 351-750 meters from the land bridge facilities have a positive impact on house prices. The rest of variables show the negative impact. In addition, according to the results of spatial error model in the spatial regression model, the spatial error coefficient shows a significant positive correlation, and the significance of other variables are also the same as those in the least squares regression.
The calculation results are the same whether in the OLS model or the spatial regression model. Comparing the coefficients, the influence of the floor space, the age of the house, the square of the house age, the number of halls bathrooms on the house price has increased. Among them, the coefficients of the number of parking spaces and bathrooms significantly vary after adding a spatial element. Moreover, in the spatial regression model, the results demonstrate that the number of parking spaces has less impact on house prices; however, the number of bathrooms has a greater impact on house prices. This shows that although consumers value the number of parking spaces, they are not the main factors affecting housing prices. In contrast, among the factors affecting housing prices, consumers pay more attention to the number of bathrooms.

Keywords: Railway Underground Project, Expected Effect, Spatial Regression Model, Not-In-My-Back-Yard Facilities

目錄
中文摘要 i
英文摘要 ii
誌謝 iv
目錄 v
表目錄 vii
圖目錄 viii
第一章　緒論 1
第一節　研究背景與動機 1
第二節　研究目的 3
第三節　研究流程與架構 4
第二章　文獻探討 6
第一節　鄰避設施 6
第二節　預期效果 8
第三節　空間相關理論探討 9
第四節　熱區分佈 12
第三章　研究設計與方法 14
第一節　研究資料說明 14
第二節　變數選取說明 17
第三節　實證模型與檢定 22
第四節　敘述性統計表 25

第四章　實證結果分析 28
第一節　最小平方迴歸模型 28
第二節　住宅大樓空間模型 31
第五章　結論與建議 35
第一節　結論 35
第二節　研究建議與未來方向 36
參考文獻 38


表目錄
表1-1 2014鄰避設施調查報告 2
表2-1 不同鄰避設施對不動產價格之影響 7
表3-1 各自變數在不同距離下之平均值說明表 20
表3-2 變數說明表 21
表3-3 樣本資料敘述統計表 25
表4-1 最小平方迴歸模型之係數估計表 30
表4-2 空間迴歸模型之檢驗表 31
表4-3 空間迴歸模型之係數估計表 33
表4-4 OLS與空間迴歸模型比較表 34


圖目錄
圖1-1 高雄市區鐵路地下化計畫 1
圖1-2 研究流程圖 4
圖3-1 住宅大樓樣本分佈圖 15
圖3-2 住宅大樓分佈熱區圖 16
圖3-3 住宅大樓的LISA分佈圖 16
圖3-4 空間迴歸模型分析流程圖 24

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