Whether to trust chatbots: Applying the event-related approach to understand consumers’ emotional experiences in interactions with chatbots in e-commerce
Abstract
Chatbots can be used in marketing services to substantially improve the consumer experience. Based on cognitive appraisal theory, this study applied an event-related potential (ERP) approach to investigate consumers’ emotional experiences and consumer trust in passive interaction with chatbots versus humans, taking into account objective or subjective tasks in e-commerce. The results showed that chatbot (vs. human) service interactions automatically drew more consumer attention at the subconscious stage (i.e., a larger P2); consumers purposefully allocated more resources to regulate the negative emotions elicited by chatbots at the conscious stage (i.e., a larger LPP); and there was a lower trust in chatbots than in humans. Moreover, under subjective tasks, the differences between chatbots and human agents in emotional experience (as reflected by LPP) and trust were amplified. The findings will encourage e-retailers to improve the emotional service experience of their chatbots and prioritize the application of chatbots for objective tasks in customer service.
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For AR-assisted CBT, acceptance might fluctuate as undergraduate students become more habituated to the hardware or as their anxiety levels change throughout the semester.
“For AR-assisted CBT, acceptance might fluctuate as the undergraduate students become more habituated to the hardware or as their anxiety levels change throughout the semester [117].”
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The Transformative Role of Artificial Intelligence in the Event Management Industry
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Gender effect in human–machine communication: a neurophysiological study
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The power of emojis: Enhancing the willingness to adopt chatbot recommendations
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Do cute language style chatbots make consumers more unethical?
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Chatbot integration for online shopping: a bibliometric review and future research agenda
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“Prior studies have demonstrated that variations in chatbot design—such as language style, anthropomorphic cues, and emoticon use—evoke different consumer responses (Li and Shin, 2023; Li and Wang, 2023; Lu et al., 2024).”
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“Therefore, a 1000 ms time window is reasonable and consistent with the standard practices of previous ERP research [60], which has been widely accepted and validated as effective in the field.”
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“Unlike human agents, chatbots operate continuously without fatigue, provide consistent responses, and remain unaffected by negative interactions, making them a valuable resource in managing such situations (Sidlausk-iene et al., 2023; Wang et al., 2023).”
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Bibliometric analysis of research on ChatGPT: using VOSviewer
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“Consumers also exhibit lower trust in chatbots compared to humans [15].”
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Why human mistakes hurt more? Emotional responses in human-AI errors
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“…method (explicit and implicit) and product type (similar and related) (Shang et al., 2024), as well as service type (chatbots and humans) and task type (subjective and objective) (Wang et al., 2023 ), influence con - sumers’ decision-making processes and neuropsychology mechanisms through ERP.”
InfluentialThe Impact of AI Trust Violation on Trustworthiness: An Empirical Study Based on AI Chatbots
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“…expressive modalities of interactive interfaces shape user trust; when virtual teachers present highly anthro-pomorphized images and cues, they can trigger a "social presence heuristic, " creating a sense of real human presence that enhances learners’ trust and perceived needs (Wang et al., 2023).”
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“Wang Various references to chatbots highlight their role in enhancing service quality in various sectors, particularly in customer service, education, and the business sector.”
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“An AI-chatbot system is an AI-based application (Marjerison, Zhang, and Zheng 2022) or an automated computer programmer that has been developed to communicate with customers without any human involvement (Wang et al. 2023).”
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Novel Cognitive Trust Model in Travel Chatbots
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“Second, given the critical role of perceived desire in trust formation, chatbots should be programmed to explicitly communicate their commitment to helping users through phrases such as “I’m here to help you plan the perfect trip” or “Let me find the best options for you”.”
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Matching embodied conversational agent appearance to message emotion enhances persuasion in eHealth
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“Existing literature suggests that chatbot interactions tend to reduce consumers’ emotional experiences [79].”
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“Key factors impacting consumer interactions with AI include the perceived credibility and humanness of the agents (J. Kim & Im, 2023; Soderlund et al., 2021), as well as the valence of experiential responses evoked through verbal and non-verbal cues (Wang et al., 2023).”
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“This may be due to the prior evidence supporting that much online shopping platform integrates a generic mechanism of trust, resulting in positive attitude of customers and use behavior where conversational agents are enabled [44].”
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ONE-DAY WORKSHOP MEMBANGUN NILAI TRUST TERHADAP PRODUK LAYANAN PADA GENERASI Z DI METRO-LAMPUNG
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Chatbot Service: An Integrated Framework of the Customer Journey and Experiential QualityPreprint
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Ethical Dynamics and Organizational Climate in Enhancing AI-based HRM Decision MakingPreprint
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- Authors
- Wang, C., Li, Y., Fu, W., & Jin, J.
- Affiliations
- Hefei University of Technology (CN)
- Shanghai International Studies University (CN)
- Corresponding author
- Fu, Weizhong
- Jin, Jia
- Venue
- Journal of Retailing and Consumer Services
- Publisher
- Elsevier BV
- Published
- 2023-07
- Volume
- 73
- Pages
- 103325
- ISSN
- 0969-6989 (ISSN-L)
- OpenAlex
- W4323671075
- Cited by
- 126
- References
- 84
- Citations by year
- 2026: 35 · 2025: 46 · 2024: 28 · 2023: 17
- FWCI
- 11.15
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Retailing and Consumer Services (publishedVersion)
- Funders
- Humanities and Social Science Fund of Ministry of Education of the People's Republic of China (20YJAZH098)
- National Natural Science Foundation of China (72271166, 2022KFKT003)
- Ministry of Education of the People's Republic of China
- Fundamental Research Funds for the Central Universities (JS2020HGXJ0032)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Keywords
- chatbots, consumer trust, emotional experience, event-related potentials, appraisal theory, P2 component, e-commerce customer service, emotion regulation, e-retailers
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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