@inproceedings{788e6a266d774b47b50c2ca12a654407,
title = "Exploring User Motivations Behind iOS App Tracking Transparency Decisions",
abstract = "Apple{\textquoteright}s App Tracking Transparency framework allows users to decide whether they want to allow their activity to be tracked for advertising purposes. In this work we examine the tracking decisions made by 312 participants and their associations with privacy concern and personality factors, and conduct a thematic analysis on participants{\textquoteright} reasons for choosing to accept or reject tracking requests. Despite 51% of participants reporting that they had rejected tracking for privacy reasons, higher privacy concern scores did not correlate with a lower rate of tracking acceptance. Additionally, 43% of participants held incorrect beliefs about what tracking does, including nearly a quarter who mistakenly believed that accepting a tracking request would share their location with the requesting app. We suggest explanations for these misconceptions and provide recommendations that may improve usability of both App Tracking Transparency and future Privacy Enhancing Technologies.",
keywords = "App Tracking Transparency, Apple, iOS, privacy, privacy calculus, privacy concern, privacy decision making, privacy paradox, privacy salience",
author = "Hannah Hutton and David Ellis",
note = "This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Centre for Doctoral Training in Trust, Identity, Privacy and Security in Large-scale Infrastructures [grant number EP/S022465/1]. ; 2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 ; Conference date: 23-04-2023 Through 28-04-2023",
year = "2023",
month = apr,
day = "19",
doi = "10.1145/3544548.3580654",
language = "English",
isbn = "9781450394215",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
pages = "1--12",
booktitle = "CHI '23",
address = "USA United States",
}