The Roles of Financial Capability and Social Influence in the Uptake of Robo-advisors: A Latent Profile Approach
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Ali, Sara
Gilbert, Aaron
Kapitan, Sommer
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Elsevier BV
Abstract
Many individuals perceive investing as complex, but cannot access personalized investment advice. Robo-advisors offer cost-effective, automated financial advice with the potential to democratize investing for particularly underserved groups. However, global adoption remains low, hindered by barriers related to financial literacy, trust, and technology acceptance. This study investigates whether robo-advice serves as a substitute for financial capability, a multidimensional construct encompassing knowledge, behavior, and self-efficacy, thereby broadening access to investing. Using a nationally representative survey of 983 New Zealanders aged 18–83, we employ latent profile analysis to identify six distinct segments of robo-advisor adoption mindsets based on openness to new technology, financial capability, and financial product experience. Our findings suggest that greater financial capability supports the adoption of robo-advice, rather than robo-advice serving as a substitute for low financial capability. However, social influence, especially from traditional media, reviews, and social media, is significantly associated with psychological comfort and with greater consideration of robo-advice, especially among financially vulnerable groups. These insights highlight actionable opportunities for financial institutions to expand adoption and ultimately foster financial inclusion by leveraging social media influence.
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1502 Banking, Finance and Investment, 3502 Banking, finance and investment, 3801 Applied economics, Robo-advisor, financial capability, social influence, latent profile analysis, digital financial inclusion
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Journal of Behavioral and Experimental Finance, ISSN: 2214-6350 (Print); 2214-6369 (Online), Elsevier BV, 51, 101195-101195. doi: 10.1016/j.jbef.2026.101195
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© 2026 The Author(s). Published by Elsevier B.V. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.