TOO UNFAIR TO ACCEPT? INVESTIGATING THE EFFECTS OF BENEFITS, PRIVACY CONCERNS AND DISTRIBUTIVE JUSTICE ON THE ACCEPTANCE OF TRACKING

Online services increasingly collect behavioral data without users’ explicit awareness. While seemingly free, providers profit through personalized advertising based on behavioral insights and inferred preferences. As such profiling increases privacy risks, users often hesitate to accept tracking via consent options in cookie banners. In the context of free online services, fair data handling includes not only control but also a fair distribution of the value generated from personal data. Distributive justice refers to users’ perceptions of whether their outcomes are fair compared to the advertising profits gained by providers. Yet, it remains unclear how perceived privacy concerns, benefits, and distributive justice influence users’ acceptance of tracking. To address this gap, we conducted an experimental study examining two serial mediation paths. We find a suppression effect involving perceived benefits and distributive justice, indicating an ambivalent role of monetary rewards. Our findings inform the design of fair, data-driven business models and consent mechanisms.

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Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-06-18
Primary Topic
Privacy, Security, and Data Protection
Type
article
Field-Weighted Citation Impact
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article

TOO UNFAIR TO ACCEPT? INVESTIGATING THE EFFECTS OF BENEFITS, PRIVACY CONCERNS AND DISTRIBUTIVE JUSTICE ON THE ACCEPTANCE OF TRACKING

Journal of the Association for Information Systems
Privacy, Security, and Data Protection
article

TOO UNFAIR TO ACCEPT? INVESTIGATING THE EFFECTS OF BENEFITS, PRIVACY CONCERNS AND DISTRIBUTIVE JUSTICE ON THE ACCEPTANCE OF TRACKING

article en

Abstract

Online services increasingly collect behavioral data without users’ explicit awareness. While seemingly free, providers profit through personalized advertising based on behavioral insights and inferred preferences. As such profiling increases privacy risks, users often hesitate to accept tracking via consent options in cookie banners. In the context of free online services, fair data handling includes not only control but also a fair distribution of the value generated from personal data. Distributive justice refers to users’ perceptions of whether their outcomes are fair compared to the advertising profits gained by providers. Yet, it remains unclear how perceived privacy concerns, benefits, and distributive justice influence users’ acceptance of tracking. To address this gap, we conducted an experimental study examining two serial mediation paths. We find a suppression effect involving perceived benefits and distributive justice, indicating an ambivalent role of monetary rewards. Our findings inform the design of fair, data-driven business models and consent mechanisms.

Journal of the Association for Information Systems
Munich School of Philosophy (DE), LMU Klinikum (DE), Universität der Bundeswehr München (DE), Ludwig-Maximilians-Universität München (DE)
Peace, Justice and strong institutions
Openalex Percentile: Top 40%
Privacy, Security, and Data Protection
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