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Robo-advisor acceptance: Do gender and generation matter?

Figà-Talamanca, Gianna ; Tanzi, Paola Musile ; D'Urzo, Eleonora Mahmoud, Ali B.

PloS one, 2022-06, Vol.17 (6), p.e0269454-e0269454 [Periódico revisado por pares]

San Francisco: Public Library of Science

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Título:
Robo-advisor acceptance: Do gender and generation matter?
Autor: Figà-Talamanca, Gianna ; Tanzi, Paola Musile ; D'Urzo, Eleonora
Mahmoud, Ali B.
Assuntos: Advisors ; Algorithms ; Analysis ; Artificial intelligence ; Attitudes ; Automation ; Bank technology ; Biology and Life Sciences ; Computer and Information Sciences ; Consultants ; Demographic aspects ; Evaluation ; Financial inclusion ; Financial management ; Financial planners ; Forecasts and trends ; Gender ; Gender aspects ; Gender differences ; Human error ; Hypotheses ; Influence ; Information systems ; Portfolio management ; Research and Analysis Methods ; Research methodology ; Robotics ; Sex differences ; Social Sciences ; Technology ; Technology Acceptance Model ; Technology adoption ; Technology utilization
É parte de: PloS one, 2022-06, Vol.17 (6), p.e0269454-e0269454
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Competing Interests: The authors have declared that no competing interests exist.
Descrição: Robo-advice technology refers to services offered by a virtual financial advisor based on artificial intelligence. Research on the application of robo-advice technology already highlights the potential benefit in terms of financial inclusion. We analyze the process for adopting robo-advice through the technology acceptance model (TAM), focusing on a highly educated sample and exploring generational and gender differences. We find no significant gender difference in the causality links with adoption, although some structural differences still arise between male and female groups. Further, we find evidence that generational cohorts affect the path to future adoption of robo-advice technology. Indeed, the ease of use is the factor which triggers the adoption by Generation Z and Generation Y, whereas the perceived usefulness of robo-advice technology is the key factor driving Generation X.sup.+, who need to understand the ultimate purpose of a robo-advice technology tool before adopting it. Overall, the above findings may reflect that, while gender differences are wiped out in a highly educated population, generation effects still matter in the adoption of a robo-advice technology tool.
Editor: San Francisco: Public Library of Science
Idioma: Inglês

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Robo-advisor acceptance: Do gender and generation matter?

Figà-Talamanca, Gianna ; Tanzi, Paola Musile ; D'Urzo, Eleonora Mahmoud, Ali B.

San Francisco: Public Library of Science

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