Avoidance of AI-Empowered Digital Service Assistants in Fashion Shopping: The Negative Side of Personalized Recommendation of Chatbots
Abstract
While people often resist suggestions when their autonomy is challenged, the reluctance to use chatbot services due to perceived threats to freedom of choice remains unexplored. Based on psychological reactance theory, this study investigates the effects of personalized recommendations by AI chatbots, focusing on how they could lead to chatbot avoidance. An online survey collects data from 186 participants who had experience using chatbot services during online shopping. The results of bootstrapping analysis show that personalized recommendations by chatbots increase avoidance behavior, serially mediated by perceived threats to freedom and negative affect. The study also finds the interplay effect of the personalized recommendations of chatbots and fashion involvement on the threat to freedom. When consumers have low fashion involvement, personalized recommendations by a chatbot decrease the threat of freedom. However, when consumers have high fashion involvement, the personalized recommendations of chatbots increase their perceptions of the threat of freedom. This research contributes to the understanding of negative consumer responses to AI chatbots in retail, offering insights into how personalized recommendations can be perceived as intrusive and impact consumer acceptance negatively.
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Personalized chatbots pose a threat to freedom of choice as consumers react in the form of psychological reactance and avoidance, specifically when product involvement is high.
“According to Yoon et al. [23], personalized chatbots pose a threat to freedom of choice as consumers react in the form of psychological reactance and avoidance, specifically when product involvement is high.”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as Yoon et al. [23]
Perceived freedom threats are key mediators of avoidance.
“Yoon et al. [23] identify perceived freedom threats as key mediators of avoidance”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as Yoon et al. [23]
Personalized systems proposed by AI-driven chatbots stimulate reactance and avoidance, mediated by freedom-threat and negative affect.
“Yoon et al. [23] demonstrate that personalized systems proposed by AI-driven chatbots stimulate reactance and avoidance, mediated by freedom-threat and negative affect.”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as Yoon et al. [23]
Design elements that give agents more freedom or make them feel more personal can make people less likely to buy.
“Some studies show that design elements that give agents more freedom or make them feel more personal can make people less likely to buy [23,40]”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
In everyday shopping situations, executor-like behavior can stop people from adopting something by making them feel powerless and can make reactance worse when recommendations seem to be steering or limiting.
“In everyday shopping situations, executor-like behavior can stop people from adopting something by making them feel powerless [40] and can make reactance worse when recommendations seem to be steering or limiting [23].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
Personalized or heavily directed recommendations can provoke reactance and avoidance, especially in contexts of heightened involvement or when such recommendations are viewed as limiting choice.
“Personalized or heavily directed recommendations can provoke reactance and avoidance, especially in contexts of heightened involvement or when such recommendations are viewed as limiting choice [23].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
Negative reactions arise when autonomy cues suggest a loss of control (reactance/threat-to-freedom) or displacement (powerlessness); conversely, positive outcomes are observed when systems facilitate friction reduction while maintaining perceived authorship and recourse.
“Negative reactions arise when autonomy cues suggest a loss of control (reactance/threat-to-freedom) or displacement (powerlessness); conversely, positive outcomes are observed when systems facilitate friction reduction while maintaining perceived authorship and recourse [23,24,40].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
Particularly in regular, non-urgent shopping contexts, the user experience can shift toward helplessness and threat-to-freedom reactions, resulting in lower adoption intentions and higher avoidance.
“Particularly in regular, non-urgent shopping contexts, the user experience can shift in these situations toward helplessness and threat-to-freedom reactions, resulting in lower adoption intentions and higher avoidance [23,40].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
Feelings of powerlessness and psychological reactance occur when cues of autonomy or personalization are perceived as threats to freedom or displacement, leading to decreased acceptance and heightened avoidance.
“First, feelings of powerlessness and psychological reactance occur when cues of autonomy or personalization are perceived as threats to freedom or displacement, leading to decreased acceptance and heightened avoidance [23,24,40].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
Marketing lift depends on maintaining the user's sense of control, not just on improving capability cues.
“This demonstrates that marketing lift depends on maintaining the user's sense of control, not just on improving capability cues (e.g., [22,23,40]).”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
Negative pathways often come up through governance-related mediators, like powerlessness and reactance, which make adoption and delegation less likely even when benefits are clear.
“This is why negative pathways often come up through governance-related mediators, like powerlessness and reactance, which make adoption and delegation less likely even when the benefits are clear [23,40].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
Experiments confirm autonomy to powerlessness/reactance mechanisms and interface-driven reactance shifts, whereas surveys focus on usefulness/satisfaction/trust chains.
“This disparity is evident in both experimental and survey methodologies: experiments confirm autonomy → powerlessness/reactance mechanisms [23,40] and interface-driven reactance shifts [24], whereas surveys focus on usefulness/satisfaction/trust chains [42,44,69].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
Interface design is not superficial appearance; cues can shift agency perceptions and reactance, but the market importance of these cue pathways is still not well understood.
“This bridging logic follows the review's broader conclusion that interface design is not superficial appearance; cues can shift agency perceptions and reactance-but the market importance of these cue pathways is still not well understood [23,24].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
Personalization can cause avoidance through threat-to-freedom mechanisms, and high autonomy can decrease adoption through helplessness in routine contexts.
“This directly addresses findings that personalization can cause avoidance through threat-to-freedom mechanisms [23] and that high autonomy can decrease adoption through helplessness in routine contexts [40].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
Acceptance models usually assume that delegation is the action-level construct, and autonomy is the boundary condition that makes governance costs important.
“Acceptance models usually assume that delegation is the action-level construct, and autonomy is the boundary condition that makes governance costs important [23,24,40].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
The effects of manipulating autonomy frequently shift through governance mechanisms, such as perceived control and powerlessness/reactance.
“Second, the effects of manipulating autonomy frequently shift through governance mechanisms, such as perceived control and powerlessness/reactance, indicating that future research should treat governance and delegation as causal constructs rather than downstream correlates [23,24,46].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
Governance-related constructs (perceived control/agency, powerlessness/reactance, risk/privacy) consistently influence whether delegation is perceived as empowerment or displacement.
“In RQ2-RQ3, governance-related constructs (perceived control/agency, powerlessness/reactance, risk/privacy) consistently influence whether delegation is perceived as empowerment or displacement [23,24].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [23]
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“…they may exhibit greater sensitivity to any perceived threat to their control and freedom of choice when interacting with chatbots that offer personalized – yet limited – recommendations (Aljukhadar et al., 2017; De Kerviler et al., 2016); thus, they may express a greater degree of reactance.”
Kim, K. J., Park, E., & Shyam Sundar, S. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.02.009 · Cited by 234 · cited 1× · see citing works
“…has predominantly focused on consumer adoption in terms of anthropomorph-ism, likability, intelligence, and social presence (e.g. Huang & Rust, 2018; Kim et al., 2013, 2019; van Doorn et al., 2017), this study highlights consumers’ avoidance of chatbot service driven by psychological reactance.”
Testing the performance of online recommendation agents: A meta-analysis
Blut, M., Ghiassaleh, A., & Wang, C. (2023) · Journal of Retailing · doi:10.1016/j.jretai.2023.08.001 · Cited by 31 · see citing works
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Balaskas, S. (2026) · Information · doi:10.3390/info17030222 · Cited by 8 · see citing works
- Authors
- Yoon, N., Choi, D., & Lee, H. K.
- Affiliations
- Korea University (KR)
- Old Dominion University (US)
- Chungnam National University (KR)
- Corresponding author
- Lee, Ha Kyung
- Venue
- Journal of Global Fashion Marketing
- Publisher
- Informa UK Limited
- Published
- 2025-06-13
- Volume
- 16
- Issue
- 4
- Pages
- 423-442
- ISSN
- 2093-2685 (ISSN-L)
- 2325-4483
- OpenAlex
- W4411288207
- Cited by
- 11
- References
- 6
- Citations by year
- 2026: 8 · 2025: 3
- FWCI
- 4.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Global Fashion Marketing (publishedVersion)
- Funders
- Ministry of Education of the Republic of Korea
- National Research Foundation of Korea
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Keywords
- AI chatbots, personalized recommendation, reactance, negative affect, fashion involvement, online shopping, consumer acceptance of AI, fashion retail
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