Exploring Consumers’ Response to Text-Based Chatbots in e-Commerce: The Moderating Role of Task Complexity and Chatbot Disclosure
Open accessAbstract
Purpose: Artificial intelligence (AI)-based chatbots have brought unprecedented business potential. This study aims to explore consumers' trust and response to a text-based chatbot in e-commerce, involving the moderating effects of task complexity and chatbot identity disclosure. Design/methodology/approach: A survey method with 299 useable responses was conducted in this research. This study adopted the ordinary least squares regression to test the hypotheses. Findings: First, the consumers' perception of both the empathy and friendliness of the chatbot positively impacts their trust in it. Second, task complexity negatively moderates the relationship between friendliness and consumers' trust. Third, disclosure of the text-based chatbot negatively moderates the relationship between empathy and consumers' trust, while it positively moderates the relationship between friendliness and consumers' trust. Fourth, consumers' trust in the chatbot increases their reliance on the chatbot and decreases their resistance to the chatbot in future interactions. Research limitations/implications: Adopting the stimulus–organism–response (SOR) framework, this study provides important insights on consumers' perception and response to the text-based chatbot. The findings of this research also make suggestions that can increase consumers' positive responses to text-based chatbots. Originality/value: Extant studies have investigated the effects of automated bots' attributes on consumers' perceptions. However, the boundary conditions of these effects are largely ignored. This research is one of the first attempts to provide a deep understanding of consumers' responses to a chatbot.
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The empirical research on the effects of agentic commerce is still dispersed but suggests an interrelated set of commerce and psychological effects.
“The empirical research on the effects of agentic commerce is still dispersed but suggests an interrelated set of commerce and psychological effects”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [51]
The Introduction (p. 2) links attributes of AI-enabled systems to consumer perceptions, decisions, and purchase intentions, and says empirical evidence on chatbot pushback is limited. The Abstract (p. 1) reports relationships among empathy, friendliness, trust, reliance, and resistance in e-commerce. These passages support related psychological and consumer-response effects, but the paper does not characterize research on agentic commerce broadly as dispersed or establish a broader set of commerce effects. (LLM, conf=0.82)
Experimental — accuracy not yet measuredBeliefs 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].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [51]
Section 2.5 (p. 7) says consumers who trust a chatbot are more likely to rely on it to address problems or make decisions. Section 4.1 (p. 13) suggests that, for complex tasks, consumers may care more about the chatbot’s ability to solve problems than its attitude. The paper does not establish that perceived competence strengthens a usefulness route or that competence itself increases delegation; its tested chatbot attributes are empathy and friendliness. (LLM, conf=0.84)
Experimental — accuracy not yet measuredTask complexity and disclosure influence the translation of empathy and friendliness cues into trust.
“task complexity and disclosure influence the translation of empathy and friendliness cues into trust [51]”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [51]
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- Authors
- Cheng, X., Bao, Y., Zarifis, A., Gong, W., & Mou, J.
- Affiliations
- Renmin University of China (CN)
- University of International Business and Economics (CN)
- Loughborough University (GB)
- Beijing University of Chemical Technology (CN)
- Pusan National University (KR)
- Corresponding author
- Mou, Jian
- Venue
- Internet Research
- Publisher
- Emerald
- Published
- 2021-07-12
- Volume
- 32
- Issue
- 2
- Pages
- 496-517
- ISSN
- 1066-2243 (ISSN-L)
- OpenAlex
- W3179245706
- Cited by
- 300
- References
- 23
- Citations by year
- 2026: 70 · 2025: 96 · 2024: 58 · 2023: 54 · 2022: 20 · 2021: 2
- FWCI
- 11.84
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Internet Research (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion, cc-by)
- ePrints Soton (University of Southampton) (submittedVersion)
- arXiv (Cornell University) (cc-by)
- Funders
- University of International Business and Economics
- Renmin University of China (21XNO002)
- 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
- chatbots, text-based chatbots, consumer trust, task complexity, chatbot empathy, e-commerce, stimulus-organism-response model, moderating effect
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