隨著金融科技和AI人工智慧的發展日新月異，各式各樣的理財機器人油然而生，為人們帶來更便利、更良好的理財方式。在加密貨幣的市場中，「加密貨幣交易機器人」是可以根據投資人的需求和條件，自動進行投資下單或賣出，替投資人省去了盯盤、分析的時間成本，也給予投資人更客觀的判斷，降低了投資風險。雖然加密交易機器人為投資人帶來許多益處，但其自動判斷進出場時機的特性，也使得投資人喪失自我決策的權力，這為加密交易機器人的能力和安全性增添了些許疑慮。又因這是一項新興科技，鮮少有關於其學術研究上之文獻資料，本研究希望透過此研究分析，提供學術面及實務面關於加密交易機器人發展上的建議。

本研究以派網Pionex加密交易機器人為例，採用推敲可能性模型作為基礎，結合信任轉移理論及交易成本理論，並加入不確定性，目的在於探討使用者會因為那些因素而影響其對加密交易機器人的使用意圖。根據研究結果發現，推敲可能性模型中的中央路徑受到「服務品質」構面的影響較深，而周邊路徑則以「聲譽」構面影響程度較大，且同時驗證信任轉移、交易成本理論在本研究中皆成立。

With the rapid development of financial technology and AI, various kinds of financial robots have emerged to bring people a more convenient and better way to manage their property. In the cryptocurrency market, “Cryptocurrency Trading Robots” can automatically trade according to investors’ needs and conditions, saving investors’ time and cost of order monitoring and analysis, and giving them more objective judgment to reduce investment risks. Although the trading robots bring many benefits to investors, but also take away the right which investors can decide by themselves. Because the crypto trading robots can make decision when to trade automatically, it also adds some doubt to the ability and safety of trading robots. Since this is a new technology, there is little academic research on it. Through this study, we hope to provide academic and practical suggestions on the development of crypto trading robots.

This study take the Pionex Trading Robot as an example, and adopts the Elaboration Likelihood Model as the basis, combining Trust Transfer Theory and Transaction Cost Theory with uncertainty, in order to investigate the factors that affect users' intention to use the crypto trading bot. According to the findings, the central path in the Elaboration Likelihood Model is more influenced by the 'System Quality' construct, while the peripheral path is more influenced by the 'Reputation' construct, and it is verified that both Trust Transfer and Transaction Cost Theories hold true in this study.

論文審定書 i
摘要 ii
Abstract iii
目 錄 iv
圖 次 vi
表 次 vii
第一章 緒論 1
第一節 研究背景 1
第二節 研究動機 2
第三節 研究問題與目的 4
第四節 研究方法與流程 5
第二章 文獻探討 6
第一節 加密交易機器人 (Crypto Trading Bot) 6
第二節 推敲可能性模型 (Elaboration Likelihood Model, ELM) 7
一、 中央路徑 (Central Route) 7
二、 周邊路徑 (Peripheral Route) 8
第三節 信任轉移理論 (Trust Transfer Theory, TTT) 8
第四節 不確定性 (Uncertainty) 10
第五節 交易成本理論 (Transaction Cost Theory, TCT) 11
第三章 研究方法 13
第一節 研究模型 13
第二節 研究假說 13
一、 使用意圖 (Usage Intention) 13
二、 交易成本 (Transaction Cost) 14
三、 不確定性 (Uncertainty) 14
四、 信任 (Trust) 15
五、 系統感知 (System Beliefs) 17
六、 YouTuber感知 (YouTuber Beliefs) 17
第三節 操作型定義 19
第四節 研究設計 20
一、 研究對象 20
二、 問卷設計 21
第四章 資料分析 27
第一節 樣本基本資料分析 27
第二節 衡量模型 30
一、 信度分析 (Reliability) 31
二、 收斂效度 (Convergent Validity) 32
三、 區別效度分析(Discriminant Validity) 36
四、 共線性分析(Multicollinearity) 39
五、 共同方法偏誤(Common Method Bias) 40
第三節 模型及假說驗證 43
第五章 結論與建議 47
第一節 研究結果與建議 47
一、 信任因素之探討 47
二、 信任轉移之發生 48
三、 信任影響不確定性之作用 48
四、 不確定性對交易成本之影響 49
五、 交易成本理論成立 49
第二節 理論及實務意涵 49
一、 理論面 49
二、 實務面 50
第三節 研究限制 51
第四節 未來研究方向 52
參考文獻 54
中文文獻 54
英文文獻 54
附錄–本研究正式問卷 59

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