Investors’ willingness to use robo-advisors: Extrapolating influencing factors based on the fiduciary duty of investment advisors

Robo-advisors are increasingly seen as a solution for the growing demand for timely and actionable financial advice. However, systematic barriers to their deployment and use persist. Understanding the factors that influence investors' willingness to consult with robo-advisors is key to their wi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International review of economics & finance 2024-07, Vol.94, p.1-14, Article 103411
Hauptverfasser: Luo, Haohan, Liu, Xin, Lv, Xingyang, Hu, Yubei, Ahmad, Ali J.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Robo-advisors are increasingly seen as a solution for the growing demand for timely and actionable financial advice. However, systematic barriers to their deployment and use persist. Understanding the factors that influence investors' willingness to consult with robo-advisors is key to their wide-scale adoption. This research aims to isolate the factors influencing the willingness to adopt robo-advisors by investment advisory services. We focus on three adoption drivers: (1) performance of robo-advisors, (2) human-computer interaction, and (3) the reputation of software suppliers. Results indicate that ‘performance efficacy’, ‘perceived ease of use’, ‘customer education’, and ‘corporate reputation’ positively influence the perceived value, leading to higher adoption intention. Additionally, ‘performance efficacy’, ‘perceived privacy protection’ and ‘corporate reputation’ positively contributes to the building of trust, which in turn leads to higher adoption intention and asset allocation ratio. We found that low-experience investors were “value-driven”, while highly experienced investors were “trust-driven” when it came to adoption intent. The research highlights the potential of artificial intelligence-based applications for user behavior research and suggests design considerations for robo-advisor developers to influence positive adoption in financial advisory services.
ISSN:1059-0560
DOI:10.1016/j.iref.2024.103411