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Do I Desire Chatbots to be like Humans? Exploring Factors for Adoption of Chatbots for Financial Services
Abstract
AI-powered chatbots are gaining traction across various industries, especially in the financial sector. Despite these implementations, chatbot adoption and usage among consumers is still low. Grounding on the unified theory of acceptance and use of technology 2 (UTAUT2) model and the Belief Desire Intentions (BDI) model, this study explores factors influencing the adoption of chatbots for financial sectors by emphasizing on the role of user desires in addition to human beliefs. Explicitly, the research hypothesizes the role of the humanness in chatbots influencing consumer adoption in the financial services sector. The suggested research model was tested via a sample of possible adopters from India, the USA, and Singapore. Results highlight the key role of consumer desires to make artificial machines indistinguishable from human beings. Implications for research and practice are also presented.
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“Both are expected to be positively associated with perceived usefulness, particularly in natural-language interfaces (Blut et al., 2022;Sugumar & Chandra, 2021;Venkatesh et al., 2003).”
From From search results to generative answers: A mixed-methods study of credibility assessment and trust formation in AI Overviews (2027) · cites this paper as Sugumar & Chandra, 2021
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“In the context of chatbots, anthropomorphism can be defined as the degree to which users perceive the human attributes in an artificial machine by instilling such non-human actors with human characteristics, behaviors, motives, and emotions (Epley et al., 2007; Wagner et al., 2019).”
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Sorted by citations
Salah, M., Abdelfattah, F., Alhalbusi, H., & Mukhaini, M. A. (2023) · doi:10.21203/rs.3.rs-3508563/v1 · Cited by 12
Casermeiro-Corpas, Y., Rejón-Guardia, F., Vallespín, M., & Molinillo, S. (2027) · Information Processing & Management · doi:10.1016/j.ipm.2026.105211
Metadata
- Authors
- Sugumar, M., & Chandra, S.
- Affiliations
- S P Jain School of Global Management
- Venue
- Journal of International Technology and Information Management
- Published
- 2021-01-01
- Volume
- 30
- Issue
- 3
- Pages
- 38-77
- ISSN
- 1941-6679
- Cited by
- 34
- References
- 15
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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