隨著目前特別是在人工智能 (AI) 領域發展，金融市場對於自動化投資理財顧問,稱作智能投資顧問 (robo-advisory services),產生了大量的需求。由於越來越多的公司開始投資自動化投資理財顧問，使得這項服務變得很熱門。儘管智能投資顧問越來越受歡迎，但與大多數新興技術一樣，採用率仍然很低。本研究探討了三個與人工智能相關的重要指標(透明度、信心水平和可靠度)，以及它們如何影響認知信任和情感信任的。此外，本研究將對受訪者進行簡單的風險評估。此項評估主要用於確認:受訪者的風險水平是否會影響其兩種信任結構(認知信任和情感信任)與未來使用意願之間的關係。共有 243 名受訪者參與了這個 2x2x2 實驗，並使用變異數分析(ANOVA)和偏最小平方法的結構方程模型(PLS-SEM)對於實驗數據進行解析。本研究發現: 透明度和信心水平對於認知信任、情感信任以及未來使用意願有顯著影響，而可靠度則只對未來的使用意願有顯著影響。本研究還發現: 情感信任對於未來的使用意願有相當程度的影響(這項結果與之前的研究相反)，而風險水平則對於認知信任、情感信任以及未來使用意願並沒有太大影響。對於希望改進其在金融市場上的自動化投資理財顧問或計劃推出此項新服務的公司，本研究結果提供些有趣的啟示和建議。

With the recent developments in technology, specifically in field of artificial intelligence (AI), there has been an emerging market for robo-advisory services in the finance market. Robo-advisory has been growing in popularity year over year as more and more companies are starting to offer their services for investments. Despite the growth in popularity, adoption rate has still been pretty low, as is the case with most emerging technologies. This research explores the three key factors related to artificial intelligence-based recommendations, transparency, confidence level, and accountability and how it affects two constructs of trust, cognitive trust and emotional trust. A simple risk level assessment will also be conducted on the experiment respondents and will be used to check whether the risk level of the participants play a moderating role on its relationship between the two types of trust and future usage intention. A total of 243 respondents participated in this 2x2x2 experiment, manipulating the three key factors, and will be analyzed using ANOVA and PLS-SEM. This research discovered that transparency and confidence level have a significant effect on cognitive trust, emotional trust, and future usage intention. However, accountability only has a significant effect on future usage intention. It also founded that emotional trust plays a more significant role in future usage intention, contrasting previous research. Furthermore, risk level did not have a moderating role between the two types of trust and future usage intentions. These findings provide interesting implications and recommendation for companies who are looking to improve their robo-advisory service in the finance market or are planning to release this new feature.

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