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Robo-advisor acceptance: Do gender and generation matter?
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 t...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9242437/ https://www.ncbi.nlm.nih.gov/pubmed/35767541 http://dx.doi.org/10.1371/journal.pone.0269454 |
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author | Figà-Talamanca, Gianna Tanzi, Paola Musile D’Urzo, Eleonora |
author_facet | Figà-Talamanca, Gianna Tanzi, Paola Musile D’Urzo, Eleonora |
author_sort | Figà-Talamanca, Gianna |
collection | PubMed |
description | 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(+), 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. |
format | Online Article Text |
id | pubmed-9242437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-92424372022-06-30 Robo-advisor acceptance: Do gender and generation matter? Figà-Talamanca, Gianna Tanzi, Paola Musile D’Urzo, Eleonora PLoS One Research Article 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(+), 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. Public Library of Science 2022-06-29 /pmc/articles/PMC9242437/ /pubmed/35767541 http://dx.doi.org/10.1371/journal.pone.0269454 Text en © 2022 Figà-Talamanca et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Figà-Talamanca, Gianna Tanzi, Paola Musile D’Urzo, Eleonora Robo-advisor acceptance: Do gender and generation matter? |
title | Robo-advisor acceptance: Do gender and generation matter? |
title_full | Robo-advisor acceptance: Do gender and generation matter? |
title_fullStr | Robo-advisor acceptance: Do gender and generation matter? |
title_full_unstemmed | Robo-advisor acceptance: Do gender and generation matter? |
title_short | Robo-advisor acceptance: Do gender and generation matter? |
title_sort | robo-advisor acceptance: do gender and generation matter? |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9242437/ https://www.ncbi.nlm.nih.gov/pubmed/35767541 http://dx.doi.org/10.1371/journal.pone.0269454 |
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