| 题名 |
台灣地區各城市房屋住宅消費力探討 |
| 并列篇名 |
Study of Consumption Power of Residential Houses in Cities in Taiwan |
| DOI |
10.6338/JDA.201312_8(6).0003 |
| 作者 |
邱美甄(Mei-Chen Chiu)；鄧家駒(Gia-khy Tang)；張光昭(Kuang-Chao Chang)；邱俊誠(Chun-Cheng Chiu) |
| 关键词 |
消費力 ； 資料採礦 ； 房屋住宅消費力 ； 線性迴歸 ； 決策樹 ； 類神經網路 ； 群集 ； The ability of purchase ； Data Mining ； Consumption Power of Residential Houses ； Regression ； Decision Tree ； Artificial Neural Network ； Clustering |
| 期刊名称 |
Journal of Data Analysis |
| 卷期/出版年月 |
8卷6期（2013 / 12 / 01） |
| 页次 |
41 - 72 |
| 内容语文 |
繁體中文 |
| 中文摘要 |
消費即牽制著國家整體性的發展與速度，滿足大眾物質需求就是消費，致使本研究想去深入研究現今台灣地區，由於直接採用全國性的消費相關數據，容易掩蓋各城市區域之間的差異性，同時各城巿的民眾平均消費數據，也容易掩蓋各收入等級之間分群消費者的消費行為及能力，因此，本研究以消費經濟面為主軸，即來探討各城鎮對於房屋住宅的消費力的程度為何以及其影響因素之分析，房屋住宅消費力研究更是反應整體的經濟社會景氣具有重要的意義，亦可看出資產活化及各城市於房市的交易熱程度。鑒於人們消費對整體經濟環境變動日趨重要，本研究將深入各城市鄉里間的差異性及其區隔性，進而去探討台灣各城市區域居民對於房屋住宅的消費力，以資料採礦的各種方法技術找出其中相關變數後並利用迴歸方法、決策樹等方法建模後，再比較最佳模型進行預測；並期望其構建之指數後，展現該研究指數於各城市鄉里的差異特性，並藉以各種消費者角度以提供居民的住宅消費標的及瞭解到各城市鄉里的房屋消費力的高低起伏，還有房產仲介業之行銷房屋物件之參考，以及一些企業廠商的營運行銷決策之參考。 |
| 英文摘要 |
Consumption that is to contain the country's overall development and speed to meet the material needs is public consumption, resulting in this study wanted to go in-depth study in Taiwan today, due to the direct use of national consumption-related data, easy to cover all the differences between urban areas, while the population of the city average consumption data, it tends to cover up the income scale clustering between consumer behavior and ability, therefore, this study as the main consumer economy faces, namely to explore the various towns for housing and residential consumption to what extent and its influencing factors analysis, consumption of residential housing is the overall economic and social prosperity reaction is significant, and the city can be seen that the activation asset transactions in the housing market hot degree.Given the overall economic environment, people are spending more and more important changes, this study will further the differences between each city village and its compartmentalized, and then to various cities in Taiwan area residents for housing and residential spending power to the various methods of data mining techniques after which the relevant variables to identify and use regression methods, such as decision tree modeling method, and then compare the best model to predict; and expect it to build the index, the index shows the study the differences in the characteristics of each urban village and order a variety of consumer point of consumption in order to provide a resident's home and learned that the subject of the spending power of urban village houses ups and downs, as well as real estate brokerage industry marketing house object reference, as well as some marketing companies operating decision maker's reference. |
| 主题分类 |
基礎與應用科學 >
資訊科學 基礎與應用科學 > 統計 社會科學 > 管理學 |
| 参考文献 |
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