Cited by 85AI in Service InteractionsCustomer Service Quality and LoyaltyDigital Marketing and Social Media

“How mAy I help you today?” The use of AI chatbots in small family businesses and the moderating role of customer affective commitment

Rizomyliotis, Ioannis, Kastanakis, Minas N., Giovanis, Apostolos, Konstantoulaki, Kleopatra, Kostopoulos, Ioannis·2022·Journal of Business Research

Integrity signals

Registry

Crossref · 10.1016/j.jbusres.2022.08.035

Cites

19 of 19 references verified0 citation errors · 0 not checkable

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Authors
Rizomyliotis, I., Kastanakis, M. N., Giovanis, A., Konstantoulaki, K., & Kostopoulos, I.
Affiliations
  • University of West Attica (GR)
  • ESCP Business School (GB)
  • Liverpool John Moores University (GB)
Corresponding author
Rizomyliotis, Ioannis
Venue
Journal of Business Research
Publisher
Elsevier BV
Published
2022-12
Volume
153
Pages
329-340
ISSN
0148-2963 (ISSN-L)
OpenAlex
W4293708047
Cited by
85
References
19
Citations by year
2026: 16 · 2025: 32 · 2024: 19 · 2023: 17 · 2022: 1
FWCI
5.67
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Business Research (publishedVersion)
  • Liverpool John Moores University (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
  • Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
Keywords
AI chatbots, small family businesses, customer experience, customer satisfaction, human-machine communication, moderating effect

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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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