Chatbots’ effectiveness in service recovery

Publication typeJournal Article
Publication date2024-06-01
scimago Q1
wos Q1
SJR6.260
CiteScore54.9
Impact factor27.0
ISSN02684012, 18734707
Library and Information Sciences
Information Systems
Computer Networks and Communications
Abstract
Leveraging the computers are social actors theory, in this study, we explore traits of artificial intelligence-based chatbots that make them perceived as trustworthy, drive consumers to forgive the firm for service failure, and reduce their propensity to spread negative word-of-mouth against the firm. Across two scenario-based studies with UK consumers: one in a utilitarian product category (n = 586) and another in a hedonic product category (n = 508), and a qualitative study, our findings suggest that the perceived safety of chatbots enhances consumers' perceived ability and empathy, and anthropomorphism enhances the benevolence and integrity of chatbots, i.e., three traits of chatbots affect components of trustworthiness differently. Further, these traits have a positive influence on customer forgiveness and a negative influence on negative word-of-mouth.
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GOST |
Cite this
GOST Copy
Agnihotri A. et al. Chatbots’ effectiveness in service recovery // International Journal of Information Management. 2024. Vol. 76. p. 102679.
GOST all authors (up to 50) Copy
Agnihotri A., Bhattacharya S. Chatbots’ effectiveness in service recovery // International Journal of Information Management. 2024. Vol. 76. p. 102679.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1016/j.ijinfomgt.2023.102679
UR - https://linkinghub.elsevier.com/retrieve/pii/S0268401223000609
TI - Chatbots’ effectiveness in service recovery
T2 - International Journal of Information Management
AU - Agnihotri, Arpita
AU - Bhattacharya, Saurabh
PY - 2024
DA - 2024/06/01
PB - Elsevier
SP - 102679
VL - 76
SN - 0268-4012
SN - 1873-4707
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2024_Agnihotri,
author = {Arpita Agnihotri and Saurabh Bhattacharya},
title = {Chatbots’ effectiveness in service recovery},
journal = {International Journal of Information Management},
year = {2024},
volume = {76},
publisher = {Elsevier},
month = {jun},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0268401223000609},
pages = {102679},
doi = {10.1016/j.ijinfomgt.2023.102679}
}