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Reducing privacy concerns in personalized advertising: The role of social-self information in recommendation labels

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  • Lv, Linxiang
  • Chen, Siyun
  • Gong, Zhuoneng
  • Liu, Gus Guanrong
  • Qin, Huanyu
  • Zhang, Hao

Abstract

In the age of artificial intelligence (AI), it is crucial to address consumer privacy concerns in personalized advertising. However, the specific types of self-information that advertisers should prioritize to effectively alleviate these concerns in personalized advertisements remain unclear, even though personal information is a critical factor. This paper explores the literature on the concept of the “self,” highlighting that the social self—emerging from one’s integration into social groups—is perceived as less private and more shareable than the personal self, which is rooted in interpersonal comparisons and unique personal traits. Through a field study on Facebook and several experimental studies, we demonstrate that using recommendation labels with social-self information (vs. personal-self information) in personalized advertising reduces consumers’ ad avoidance. This reduction is attributed to the lower perception of threat severity, thereby diminishing privacy concerns.

Suggested Citation

  • Lv, Linxiang & Chen, Siyun & Gong, Zhuoneng & Liu, Gus Guanrong & Qin, Huanyu & Zhang, Hao, 2025. "Reducing privacy concerns in personalized advertising: The role of social-self information in recommendation labels," Journal of Business Research, Elsevier, vol. 201(C).
    • Handle: RePEc:eee:jbrese:v:201:y:2025:i:c:s0148296325005454
    DOI: 10.1016/j.jbusres.2025.115722
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    References listed on IDEAS

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