知識是由許多資訊累積鏈結起來，並能透過有效的方法驗證與實際應用，進而協助進行有效地決策。一直以來在台灣，由於教育體制的系統性問題與資訊取得過於便利，潛意識中扭曲了一般社會大眾對於知識價值的認知。甚至有許多人認為知識應該是公共資源，而不願意花心思或實質的金錢在有價值的知識上。反觀社會文化對應用知識充滿迷思，典型如電視上的股市老師所分享的內容或是媒體對公共政策的報導，充斥著類知識的陷阱，反而會讓一般大眾對知識的價值與應用認知更加混淆。往往一般人在面對比較複雜的問題時，面臨著知識不足或是不知如何應用知識做分析與決策的情況。
網際網路科技日新月異，然而即使有維基百科提供了豐富的知識，卻沒有教導人如何應用。要解決以上問題，未來一定會有知識科技與知識應用服務的產業興起。改變一般社會大眾對知識的認知與提升使用知識應用服務的興趣，才會讓台灣有機會真正發展知識經濟。本研究中透過一個名為The Wall的創新知識應用服務系統，以系統視覺與功能設計之問卷的形式調查使用者在使用此服務的想法與是否願意付費的觀點，藉由分類與迴歸樹(CART)的統計方法試圖找出使用者願意實際投入資源(時間與金錢)取得知識與應用知識的潛在重要關鍵。希冀本研究能夠透過客戶導向的研究提供未來各式知識應用服務系統在研發初期資源有限的情況下，能以最有效的方式進行開發人機互動界面與知識庫內容結構設計之市場導向參考模式，進而逐漸形塑知識科技工業發展流程。

Knowledge is linked and formed systematically by information and can be verified and applied for effective decision-making. Due to the systematic problem in our educational system and the convenience for general public to obtain information, the value of knowledge has been distorted subconsciously. Even some people consider knowledge more of public property that valuable knowledge should be free of charge. In the mean time people are having certain myth about applying knowledge. Take investment consulting companies and public policy report as example, the information shared has filled with quasi knowledge trap, which would confuse people at the value of knowledge and knowledge applications. When people are facing complicated problems, either they do not have enough knowledge or they do not know how to use knowledge to make decisions.
Wikipedia provides rich knowledge but does not teach people how to apply them. To solve the problems mentioned above, knowledge technology and knowledge application service industry would have a great chance to rise in the future. By changing consumer’s perspective to knowledge and raising their interest of using knowledge application services, Taiwan would have great opportunities to develop knowledge economy. Through a survey of an innovative knowledge application service system, The Wall, we use Classification and Regression Tree (CART) to analyze survey data. We are trying to figure out the key factors of what drive consumers to be willing to put resources (time and money) to obtain knowledge. Hope this research will provide outside-in suggestions from the field with ideas of human-machine interactive feature and reference structure of knowledge base for developing a knowledge application system in the early R&D stage with limited resources and shaping the development procedure of knowledge technology industry.

大前研一. (2009). 形塑生活者大國：大前流心理經濟學.

毛國楠. (2011). 單一整合型計畫:互動式創新金融教育課程之研發，教學實驗與成效評估之研究. 國科會第二期高瞻計劃

周鴻謀. (2005). 視覺教具(圖片)在國小五年級英語閱讀理解成效之研究. 國立臺北教育大學兒童英語教育研究所學位論文.

洪珮瑜. (2009). IDEO圖卡應用於設計概念發想之研究. 國立台北教育大學數位科技設計學習(玩具與遊戲設計碩士班)碩士論文.

許素娜. (2011). 零售業潛在顧客篩選模式之建構. 臺北科技大學商業自動化與管理研究所學位論文.

曾永清, 李麗香. (2012). 情境式理財課程影響國中生理財素養之研究. 中等教育.

溫文玲. (2006). 透過圖像化學習提升國小學童語文閱讀理解能力之行動研究. 國立台東大學教育研究所碩士論文.

鄭振和, 張傳章, 陳李綢, 林正昌, 王克陸＆鐘惠民. (2009). 理財教育之三大關鍵落差.

謝易庭. (2008). 探討糖尿病患服藥前後影響因素---利用決策樹分類評估. 嘉南藥理科技大學醫療資訊管理研究所碩士論文.

Abiad, A. G., Detragiache, E. & Tressel, T., (2008). A New Database of Financial Reforms. IMF Working Paper No. 08/266.

Brieman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and regression trees. Belmont, CA: Wadsworth.

Edwards, R. & Jamieson, A. (2010). Five-year-olds to be given compulsory lessons on money, savings and debt. The Telegraph.

Felfernig, A. & Kiener, A., (2005). Knowledge-based Interactive Selling of Financial Services with FSAdvisor. 17th Innovative Applications of Artificial Intelligence Conference IAAI 05 Pittsburgh, Pennsylvania.

Gilpin, E., Olshen, R., Hennang, H. & Ross, J., Jr. (1983). Risk prediction after myocardial infarction: comparison of three multivariate methodies. Cardiology, 70: 73-84.

Hess, K. R., Abbruzzese, M.C., Lenzi, R., Raber, M. N. & Abbruzzese, J. L. (1999). Classification and Regression Tree Analysis of 1000 Consecutive Patients with Unknown Primary Carcinoma1. Clinical Cancer Research.

Huang, Y. P., Hsu, C. C. & Wang, S. H., (2007). Pattern recognition in time series database: A case study on financial database. Expert Systems with Applications.

Henning, H., Gilpin, E. A., Covell, J. W., Swan, E. A., O’Rourke, R. A. & Ross, J., Jr. (1976). Progonosis after acute myocardial infarction: multivariate analysis of mortality and survival. Circulation, 59: 1124-1136.

Lemon, S. C., Roy, J., Clark, M. A., Friedmann, P. D. & Rakowski, W. (2003). Classification and regression tree analysis in public health: Methodological review and comparison with logistic regression, Volume 26, Number 3, 172-181.

Lochner, L. C. & Schwartz, A. A. (2009). Warren Buffett to Teach Kids About Finance in Cartoon. Bloomberg.

Markoff, J. (2006). Entrepreneurs see a web guided by common sense. The New York Times.

Soon, C. S., Brass, M., Heinze, H. J., & Haynes, J. D. (2008). Unconscious determinants of free decisions in the human brain. Nature Neuroscience, 11, 543 – 545.