Cited by 20AI in Service InteractionsTechnology Adoption and User BehaviourCustomer Service Quality and Loyalty

A Study on the Factors That Influence Consumers’ Continuance Intention to Use Artificial Intelligence Chatbots in a Pharmaceutical e-Commerce Context

Jia, Jing, Chen, Lu, Zhang, Luwen, Xiao, Manling, Wu, Chengzhen·2025·The Electronic Library

Abstract

Purpose This study aims to explore the antecedent factors affecting consumers’ intention to continue using artificial intelligence (AI) chatbots in pharmaceutical e-commerce. This study aims to provide a comprehensive understanding of how technical characteristics and user satisfaction influence continuance intention, offering insights for enhancing AI chatbot systems and customer service strategies. Design/methodology/approach This study adopts both online and offline data collection methods and uses structural equation modelling with AMOS 26.0 to investigate the factors influencing consumers’ continuance intention to use AI chatbots in the pharmaceutical e-commerce context. The research model integrates technical characteristics of AI chatbots, service expectation confirmation, emotional satisfaction, cognitive satisfaction and e-health literacy. Findings The results of this study indicate that perceived flexibility, accuracy, reliability and convenience of AI chatbots positively influence service expectation confirmation, while anthropomorphism does not have a significant impact. Both emotional and cognitive satisfaction positively influence consumers’ continuance intention. This study highlights the importance of optimizing AI chatbot systems to improve service efficiency and consumer satisfaction. Originality/value This study uniquely integrates the pharmaceutical e-commerce context into AI chatbots research, addressing an existing gap in context-specific studies. This s…

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Registry

Crossref · 10.1108/el-09-2024-0275

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  • Studies focusing on intention usually follow extended TAM/ECT/TPB logic, in which quality/usefulness and confirmation lead to higher satisfaction and/or attitudes, which then predict continued use, purchase intention, or loyalty.

    “Studies that focus on intention usually follow the extended TAM/ECT/TPB logic, which says that quality/usefulness and confirmation lead to higher satisfaction and/or attitudes, which then predict outcomes like continued use, purchase intention, or loyalty”
  • Beliefs about one's ability (such as perceived task-solving competence) strengthen the usefulness and trust routes; delegation is more likely when the agent is seen as competent for the task.

    “First, beliefs about one's ability (such as perceived task-solving competence) strengthen the usefulness and trust routes stronger.Delegation is more likely when the agent is seen as competent for the task [51,52,69].”
  • Systems designed to minimize friction augment perceived utility and user satisfaction, thereby reinforcing trust and subsequent intention outcomes.

    “Systems designed to minimize friction (e.g., expedited information access, simplified input, structured guidance, enhanced navigation) augment perceived utility and user satisfaction, thereby reinforcing trust and subsequent intention outcomes (e.g., retention, purchase intention, reliance-oriented metrics) [6,44,45,48,50,52,67,69].”
  • The net-positive pattern is evident in dominant satisfaction/continuance pathways according to numerous studies.

    “According to numerous studies [44,46,48,50,69], this pattern is evident in dominant satisfaction/continuance pathways.”
  • In the main empirical cluster (Autonomy-1, recommendation/support scope), positive outcomes usually follow a utility/assurance chain: performance cues and interaction quality make people feel more useful and satisfied, which builds trust and leads to downstream adoption/continuance or purchase-intent outcomes.

    “In the main empirical cluster (Autonomy-1, recommendation/support scope), positive outcomes usually follow a utility/assurance chain: performance cues and interaction quality make people feel more useful and satisfied, which builds trust and leads to downstream adoption/continuance or purchase-intent outcomes (e.g., [44,46,48,50,69]).”

Authors
Jia, J., Chen, L., Zhang, L., Xiao, M., & Wu, C.
Affiliations
  • Changzhou University (CN)
  • Changzhou University School of Business, , Changzhou,
  • Tsinghua University (CN)
  • Konkuk University (KR)
  • Hanyang University (KR)
Venue
The Electronic Library
Publisher
Emerald
Published
2025-02-26
Volume
43
Issue
3
Pages
303-321
ISSN
  • 0264-0473 (ISSN-L)
  • 1758-616X
OpenAlex
W4407983528
Cited by
20
References
0
Citations by year
2026: 15 · 2025: 5
FWCI
8.02
Type
journal article
Language
en
Open access
closed
Locations
The Electronic Library (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
Keywords
AI chatbots, continuance intention, pharmaceutical e-commerce, user satisfaction, emotional satisfaction, cognitive satisfaction, digital health literacy, anthropomorphism, perceived flexibility, perceived accuracy, perceived reliability, perceived convenience, customer relationship management

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