When Humans Still Matter: Consumers’ Responses to Automation in Loyalty Program Preferential Treatment

The recent introduction of automated complimentary upgrades reflects the emerging role of artificial intelligence (AI) in making symbolically meaningful decisions in tourism. We explore consumers’ responses using a thematic analysis of online comments and open-ended survey responses, followed by a quantitative survey to validate findings. Paradoxically, the qualitative analysis reveals that both unbiased decisions and personalization are valued. The quantitative study further shows that lay beliefs about AI are associated with preferences, through procedural and interactional fairness. Only procedural fairness fully mediates the lay beliefs’ association with intention to negotiate out of dissatisfying upgrade decisions. Moreover, desire to be treated as a unique customer weakens the lay beliefs’ association with interactional fairness and the indirect association with preferences. We contribute by revealing how consumers respond when automated agents make symbolically meaningful decisions in the automated preferential treatment context. Firms should prioritize the procedural legitimacy and symbolic framing of automated decisions.

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Publication Details

Journal
Journal of Travel Research
Published
2026-10-29
DOI
https://doi.org/10.1177/00472875261499728
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00

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article

When Humans Still Matter: Consumers’ Responses to Automation in Loyalty Program Preferential Treatment

Wei Wu, Jinzhu Song, Lixian Qian, Youlin Huang
1 links
Journal of Travel Research
AI in Service Interactions
article

When Humans Still Matter: Consumers’ Responses to Automation in Loyalty Program Preferential Treatment

Wei Wu, Jinzhu Song, Lixian Qian, Youlin Huang
article en

Abstract

The recent introduction of automated complimentary upgrades reflects the emerging role of artificial intelligence (AI) in making symbolically meaningful decisions in tourism. We explore consumers’ responses using a thematic analysis of online comments and open-ended survey responses, followed by a quantitative survey to validate findings. Paradoxically, the qualitative analysis reveals that both unbiased decisions and personalization are valued. The quantitative study further shows that lay beliefs about AI are associated with preferences, through procedural and interactional fairness. Only procedural fairness fully mediates the lay beliefs’ association with intention to negotiate out of dissatisfying upgrade decisions. Moreover, desire to be treated as a unique customer weakens the lay beliefs’ association with interactional fairness and the indirect association with preferences. We contribute by revealing how consumers respond when automated agents make symbolically meaningful decisions in the automated preferential treatment context. Firms should prioritize the procedural legitimacy and symbolic framing of automated decisions.

Journal of Travel Research
Xi’an Jiaotong-Liverpool University (CN), Zhejiang Gongshang University (CN), South China University of Technology (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 14%
AI in Service Interactions
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