本研究以T銀行的金融理財客戶為主要研究對象，探討智能投顧使用情形、金融素養、財務風險態度、社會人口統計和投資組合資料是否會影響投資者對傳統理財顧問所提供的投資理財建議的需求。本文採用便利抽樣方式進行抽樣，共計發出了320份問卷，回收了300份有效樣本，總計有效樣本回收率為93.75%。透過描述性統計分析、獨立樣本T檢定及單因子變異數分析及階層迴歸分析法進行統計分析，其主要研究結果如下：
1.	智能投顧使用者使用機器人諮詢服務與尋求傳統理財顧問建議與否存在顯著的負相關關係。
2.	金融素養與尋求傳統理財顧問建議與否無顯著的關聯性。
3.	財務風險態度與尋求傳統理財顧問建議與否無顯著的關聯性。
4.	擔心自己會成為投資詐騙的受害者與尋求傳統理財顧問建議與否存在顯著的負相關關係。
5.	女性尋求傳統理財顧問諮詢建議的傾向高於男性。
6.	自營商的受訪者其尋求傳統理財顧問諮詢建議的傾向較非自營商的受訪者低

The purpose of this thesis is to explore the relationships between using the robo-advisory services and seeking human financial advice, we use the T banks’ financial management customers as the main research object. Along with a set of control variables, including financial literacy, financial risk attitude, socio-demographics, and portfolio data. Convenience sampling is applied in the research, a total of 320 questionnaires were distributed, and 300 valid questionnaires were returned, resulting in a return rate of 93.75%. By illustrating the descriptive statistics analysis, T test & ANOVA, and hierarchy regression analysis, the main results of the study are presented as the following:
1.	There was a strong negative relationship between using robo-advisors and seeking human financial advice.
2.	There was no significant correlation between financial literacy and seeking advice from traditional financial advisers.
3.	There was no significant correlation between financial risk attitude and seeking advice from traditional financial advisers.
4.	There was a strong negative relationship between fear of investment fraud and seeking human financial advice
5.	Women are more likely than men to seek advice from traditional financial advisers.
6.	Self-employed respondents were less likely to seek advice from traditional financial advisers than non-self-employed respondents.

目錄
目錄	I
表目錄	III
圖目錄	IV
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	3
第二章 文獻探討	4
第一節 智能投顧概念與內涵	4
第二節 台灣智能投顧發展現況	5
第三節 台灣智能投顧學術研究現況	9
第四節 金融素養	14
第五節 信任	17
第六節 研究變項之間的關聯性	17
第三章 研究方法	21
第一節 研究架構	21
第二節 研究假設	21
第三節 研究變項操作性定義及衡量	21
第四節 研究對象及與樣本抽樣方式	22
第五節 資料統計分析方法	25
第四章 實證結果	26
第一節 樣本數據結構	26
第二節 差異性分析	29
第三節 羅吉斯迴歸分析	33
第五章 結論與建議	35
第一節 研究結論	35
第二節 主要研究發現	37
第三節 研究限制	38
第四節 研究建議	38
參考文獻	40
附錄：問卷設計	47

 
表目錄
表2-1台灣機器人理財服務	7
表2-2傳統理財服務與智能投顧服務主要區別及主要服務特徵	8
表2-3機器人理財顧問(智能投顧)的研究近況	10
表2-4機器人理財顧問(智能投顧)的研究近況(續)	11
表2-5機器人理財顧問(智能投顧)的研究近況(續)	13
表3 1金融素養與財務風險態度之定義與衡量	23
表3 2 受訪者之社會人口統計和投資組合資料	24
表4 1回收樣本描述性統計	26
表4 2 受訪者智能投顧知悉、選擇原因與使用情形之描述性統計	27
表4 3受訪者的月收入與投資組合資料描述性統計	28
表4 4受訪者金融素養程度之描述性統計	29
表4 5受訪者在金融素養每一道題目答對率之敘述性統計	29
表4 6受訪者各社會人口統計變項在各研究變項之差異情形	31
表4 7受訪者其投資組合資料在各研究變項之差異情形	32
表4 8智能投顧使用者與非使用者在各研究變項之差異情形	33
表4 9智能投顧使用者對尋求傳統理財顧問建議與否之羅吉斯迴歸分析表	34
表 5 1研究假說彙整表	35


圖目錄
圖3- 1研究架構圖	21

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