科技園區設置，會影響大環境之產業結構與經濟條件，故可歸類為影響房地產價格之區域因素。是故，本研究主要探討內湖科技園區設立十餘年間房屋價格變動因素，本文擬將科技園區視為一個環境資源，建立內科所在地方最適房屋迴歸價格模型，藉由房屋迴歸價格模型評估內科對房屋價格的影響。並蒐集影響不動產價格之相關文獻，以住宅特徵方面之相關統計資料，經觀察與歸納將整理出相關理論及內湖科技園區之發展現況，選出可能影響房屋價格的因子加以探討。
在實證方面，本研究採用內政部地政司之房地產交易資料進行實證分析，配合其他變數之蒐集，建構資料庫，再利用統計軟體SPSS將測量之變數進行敘述性及迴歸性分析，建立房屋迴歸價格模型，以此分析內科對鄰近地區住宅價格之影響。研究數值結果顯示，雙邊對數型函數為最適房屋迴歸價格模型，而以「用途類別」影響房屋總價最明顯。
The establishment of a technology park will affect the industrial structure and economic conditions of the general environment, so it can be classified as a regional factor that affects real estate prices. Therefore, this study mainly discusses the factors of house price changes during the establishment of Neihu Technology Park for more than ten years. This article intends to treat the technology park as an environmental resource, establish the most suitable house regression price model in the place where the internal medicine is located, and evaluate the internal The impact of house prices. It also collects relevant literature that affects the price of real estate. Based on the statistics of residential characteristics, the relevant theories and the development status of Neihu Technology Park will be sorted out through observation and summary, and factors that may affect house prices will be selected for discussion.
In terms of empirical research, this study uses real estate transaction data from the Department of Land Affairs of the Ministry of the Interior for empirical analysis, cooperates with the collection of other variables, constructs a database, and then uses statistical software SPSS to perform a descriptive and regression analysis of the measured variables to establish a housing regression price This model is used to analyze the influence of internal medicine on residential prices in neighboring areas. The numerical results of the study show that the bilateral logarithmic function is the most suitable housing regression price model, and the "use category" affects the total housing price most obviously.
