在金融科技日益進步的現代，許多顧客在金融服務方面享受著科技帶來的便利。尤其是提供自動化投資和資產配置的理財機器人，為許多無法聘請理財專員或投資顧問的小資族群以及較為忙碌的上班族提供理財投資服務。理財機器人的服務提供商可根據顧客的風險態度來進行資產和投資項目的配置，提供其客製化的投資組合。以美國為例，選擇理財機器人作為投資理財工具的用戶逐年增加，除了幾家以此服務賣點的新創公司，也越來越多傳統的銀行提供機器人理財的領域。對於提供理財機器人服務的眾多競爭者而言，如何吸引顧客選擇該企業的理財機器人服務為一重要的課題。本研究的主要目的就是在探討不同族群的顧客(例如:年齡、年收入、風險態度、財務自我效能)採用理財機器人的關鍵服務因子，並比較不同族群間各個服務因子的重要程度。
本研究採用問卷調查法對251位潛在顧客進行資料蒐集，研究中根據文獻和參考各大理財機器人服務提供商的資料彙整出顧客在選擇理財機器人時偏好的服務屬性，採用基於選擇的聯合分析法建立數個選擇方案供受試者進行選擇，並以年齡、年收入、風險態度和財務自我效能作為顧客分群的依據，以此了解各客群的選擇偏好。
本研究結果支持提出的多項假說，總體而言，年費用率的提高對顧客選擇偏好有負向影響，促銷、基礎理財教育和人為的協助對顧客選擇偏好有正向影響。各顧客族群方面，高自我效能相較低自我效能族群偏好基礎理財教育和人為的協助，老年族群會更偏好促銷、基礎理財教育和人為的協助，保守型投資人會更偏好人為的協助，富有族群相較小康和貧困族群更偏好較低的年費用率、基礎理財知識和人為的協助。最後，根據研究結果實務方面的貢獻，可作為理財機器人服務提供商針對不同客群提供相對應服務方案上的參考依據。

In the modern era of advanced financial technology, many customers enjoy the convenience brought by technology in financial services. Robo-advisor provides automated investment and asset allocation, which offers financial investment services for many customers who cannot hire financial specialists or investment consultants. Robo-advisor can automatically configure assets and investment projects according to customers' characteristics and provide their customized investment portfolios. Taking the United States as an example, the number of users choosing Robo-advisor as investment and wealth management tools has increased year by year. Besides a few start-up companies that promote this service, more and more traditional investment banks enter the Robo-advisor fields. For the many competitors in offering Robo-advisor service, how to attract customers to choose their company’s Robo-advisor service is an important issue. The main purpose of this research is to discuss the key service factors of different customer groups, such as age and financial self-efficacy in adopting Robo-advisors. Furthermore, compare the importance of each service factor among different customer groups.
In this study, online questionnaires were used to collect data from 251 potential customers. According to the literature review and data collected from websites of major Robo-advisor service providers, the research summarized the key factors that customers prefer when choosing Robo-advisor. Based on the choice-based conjoint analysis method, several options were offered for the participants to choose from. The research then selects age, annual income, risk attitude, and financial self-efficacy as the basis for customer segmentation to understand the preferences of each customer group.
The results of this study support several hypotheses. Overall, the increase in the annual fee has a negative impact on customer choice preference, while promotion, the offer of general investing education, and additional human assistance have a positive effect on customer choice preference. In terms of customer groups, those with high financial self-efficacy prefer general investing education and additional human assistance more than those with lower self-efficacy. Elderly people prefer promotion, general investing education, and additional human assistance more. The wealthy group prefers lower annual fee, more general investing education, and additional human assistance compared to the middle-class and poverty group. Finally, based on the practical contribution of the research results, it can be used as a reference for Robo-advisor service providers to offer different schemes for each customer group.

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