Cited by 55AI in Service InteractionsCustomer Service Quality and LoyaltyDigital Marketing and Social Media

Enhancing service recovery satisfaction with chatbots: The role of humor and informal language

Shams, Ghazal, Kim, Kawon Kathy, Kim, Kaeun·2024·International Journal of Hospitality Management

Integrity signals

Registry

Crossref · 10.1016/j.ijhm.2024.103782

Cites

70 of 70 references verified0 citation errors · 0 not checkable

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Cites

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Authors
Shams, G., Kim, K. K., & Kim, K.
Affiliations
University of South Carolina (US)
Corresponding author
Kim, Kawon Kathy
Venue
International Journal of Hospitality Management
Publisher
Elsevier BV
Published
2024-07
Volume
120
Pages
103782
ISSN
0278-4319 (ISSN-L)
OpenAlex
W4396852295
Cited by
55
References
71
Citations by year
2026: 25 · 2025: 24 · 2024: 6
FWCI
7.12
Type
journal article
Language
en
Open access
closed
Locations
International Journal of Hospitality Management (publishedVersion)
Funders
Dong-A University
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
chatbots, humor, colloquial language, service failure, brand equity, failure severity, customer service, text-based chatbots, customer satisfaction

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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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