Cited by 30AI in Service InteractionsCustomer Service Quality and LoyaltyTechnology Adoption and User Behaviour

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Research on Artificial Intelligence Customer Service on Consumer Attitude and Its Impact during Online Shopping

Open access
Li, Chenzhuoer, Pan, Runjie, Xin, Huiyu, Deng, Zhiwen·2020·Journal of Physics: Conference Series

Abstract

Currently, AI customer service is gaining popularity at a high rate, with over 92% of online shoppers having experience with AI customer service. The question is: what attitudes do consumers have towards AI customer service? A randomly selected sample of 670 consumers was surveyed and the study found that 71.5% of consumers accept or at least do not resist AI customer service. The main reasons AI customer service is so popular are that it is fulltime responsive, absolutely neutral, more objective, and represents a future trend. Nevertheless, 28.5% of consumers are still resistant to AI chatbot, mainly because they are not as relevant, effective, and smooth as a human customer service agent. Besides, there are prevalent obstacles to seamlessly bridge AI chatbots with human agents. In terms of explicitly specified AI chatbots versus concealed AI chatbots, merchants should have them specified since consumers have strong antipathy with AI chatbots disguising as human agents. Furthermore, there are differences in attitudes towards AI customer service across age and educational background. Accordingly, we recommend that, in the context of the overall improvement of service quality, to slow down the pace of AI replacing human agents, to do so in a step-by-step and orderly manner, and to give consumers adequate choice for human agents versus AI chatbots. Finally, to fully promote AI customer service, it is an essential measure to increase its media coverage and publicity.

Overview

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Crossref · 10.1088/1742-6596/1575/1/012192

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1 of 1 references verified0 citation errors · 0 not checkable

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Citations

Cites

Show all 1 references

Research works printed but not linked: 4

  1. Su, 2020, The rapid development of artificial intelligence customer service and “lack of human touch” bottleneck to breakthrough, New Industrial Economy, 01, 2095
  2. Wang, 2018, Key technologies of AI in customer service systems, Telecommunication Science, 12, 1000
  3. Hildebrand, 2019, AI-Driven Sales Automation: Using Chatbots to Boost Sales. [J], NIM Marketing Intelligence Review, 11, 36, 10.2478/nimmir-2019-0014 · DOI
  4. Kurachi, 2018, Ai chatbot to realize sophistication of customer contact points, Fujitsu Scientific & Technical Journal, 54, 2

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Metadata

Authors
Li, C., Pan, R., Xin, H., & Deng, Z.
Affiliations
  • Virginia Tech (US)
  • Inner Mongolia Agricultural University (CN)
  • Sichuan University (CN)
Venue
Journal of Physics: Conference Series
Published
2020-06-01
Volume
1575
Issue
1
Pages
012192
ISSN
  • 1742-6588 (ISSN-L)
  • 1742-6596
OpenAlex
W3042946886
Cited by
30
References
1
Citations by year
2026: 2 · 2025: 12 · 2024: 8 · 2023: 4 · 2022: 2 · 2021: 2
FWCI
0.76
Type
conference paper
Language
en
Open access
Locations
Journal of Physics Conference Series (publishedVersion, cc-by)
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 in customer service, chatbots, consumer attitudes, online shopping, human-agent interaction, AI transparency, service quality

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