Conversational agents in business: A systematic literature review and future research directions
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A substantial body of research relevant to chatbot use has been developed within broad domains such as health, education, and business, as well as more specific application domains such as polling, information search, libraries, and museums.
“A substantial body of research of relevance for chatbot use has been developed within broad domains such as health [105], education [84], and business [8], as well as more specific application domains such as polling [62], information search [73], libraries [92], and museums [64].”
From Future directions for chatbot research: An interdisciplinary research agenda (2021) · cites this paper as [8]
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“A substantial body of research of relevance for chatbot use has been developed within broad domains such as health [105], education [84], and business [8], as well as more specific application domains such as polling [62], information search [73], libraries [92], andmuseums [64].”
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- Authors
- Bavaresco, R., Silveira, D., Reis, E., Barbosa, J., Righi, R., Costa, C., Antunes, R., Gomes, M., Gatti, C., Vanzin, M., Junior, S. C., Silva, E., & Moreira, C.
- Affiliations
- Universidade do Vale do Rio dos Sinos (BR)
- Corresponding author
- Bavaresco, Rodrigo
- Venue
- Computer Science Review
- Publisher
- Elsevier BV
- Published
- 2020-05
- Volume
- 36
- Pages
- 100239
- ISSN
- 1574-0137 (ISSN-L)
- OpenAlex
- W3016125500
- Cited by
- 143
- References
- 99
- Citations by year
- 2026: 17 · 2025: 21 · 2024: 27 · 2023: 29 · 2022: 30 · 2021: 15 · 2020: 4
- FWCI
- 0.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computer Science Review (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- chatbots, business applications, machine learning, natural language processing, self-learning, personalization, response generation, service quality, market competitiveness, artificial intelligence in business
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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.
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