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Cited by 306AI in Service InteractionsCustomer Service Quality and LoyaltyTechnology Adoption and User Behaviour

The DOI matches its Crossref record; 127 of the 128 references it cites were found in a registry or an index.

Can AI chatbots help retain customers? Impact of AI service quality on customer loyalty

Chen, Qian, Lu, Yaobin, Gong, Yeming, Xiong, Jie·2023·Internet Research
DOI 10.1108/intr-09-2021-0686
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Abstract

Purpose: This study investigates whether and how the service quality of artificial intelligence (AI) chatbots affects customer loyalty to an organization. Design/methodology/approach: Based on the sequential chain model of service quality loyalty, this study first classifies AI chatbot service quality into nine attributes and then develops a research model to explore the internal mechanism of how AI chatbot service quality affects customer loyalty. The analysis of survey data from 459 respondents provided insights into the interrelationships among AI chatbot service quality attributes, perceived value, cognitive and affective trust, satisfaction and customer loyalty. Findings: The results show that AI chatbot service quality positively affects customer loyalty through perceived value, cognitive trust, affective trust and satisfaction. Originality/value: This study captures the attributes of the service quality of AI chatbots and reveals the significant influence of service quality on customer loyalty. This study develops research on service quality in the information system (IS) field and extends the sequential chain model of quality loyalty to the context of AI services. The findings not only help an organization find a way to improve customers' perceived value, trust, satisfaction and loyalty but also provide guidance in the development, adoption, and post-adoption stages of AI chatbots.

Overview

Integrity signals

Registry

Crossref · 10.1108/intr-09-2021-0686

Cites

127 of 127 references verified0 citation errors · 0 not checkable

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Verification

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Citations

Cites

Research works printed but not linked: 7

  1. 2002, An integrative approach to the assessment of e-commerce quality, Journal of Electronic Commerce Research, 3, 114
  2. 2020, Exploring oppositional loyalty and satisfaction in firm-hosted communities in China: effects of social capital and e-quality, Internet Research, 30, 487
  3. 1994, Qualitative Data Analysis
  4. 1997, Satisfaction: A Behavioural Perspective on the Consumer
  5. 2015, SmartPLS 3
  6. 2000, Should we delight the customer?, Journal of the Academy of Marketing Science, 28, 6
  7. 2001, Developing a scale to measure the perceived quality of an internet shopping site (SITEQUAL), Quarterly Journal of Electronic Commerce, 2, 31

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Metadata

Authors
Chen, Q., Lu, Y., Gong, Y., & Xiong, J.
Affiliations
  • Huazhong Agricultural University (CN)
  • Huazhong University of Science and Technology (CN)
  • École de management de Lyon (FR)
  • ESSCA School of Management (FR)
ORCID
Venue
Internet Research
Publisher
Emerald
Published
2023-01-17
Volume
33
Issue
6
Pages
2205-2243
ISSN
1066-2243 (ISSN-L)
DOI
10.1108/intr-09-2021-0686
OpenAlex
W4316468117
Semantic Scholar
94eded573134ce189a6362aed40b62d3f26b60b8
Cited by
260
References
128
Citations by year
2026: 60 · 2025: 109 · 2024: 70 · 2023: 21
FWCI
24.51
Type
journal article
Language
en
Open access
closed
Licence
www.emerald.com/insight/site-policies (tdm)
Locations
Internet Research (publishedVersion)
Topics
  • Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
  • Social Sciences › Business, Management and Accounting › Marketing › Customer Service Quality and Loyalty
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Keywords
AI chatbots, service quality, customer loyalty, perceived value, cognitive trust, affective trust, customer satisfaction, AI services, customer retention

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