Paper Number
ECIS2026-1994
Paper Type
CRP
Abstract
Online services increasingly collect personal data, yet traditional text-based privacy policies fail to facilitate informed consent due to their length and complexity. In response, supplementary privacy assurance mechanisms have emerged, including privacy labels and AI-powered privacy assistant chatbots. Drawing on justice theory, we conducted a between-subjects online experiment (N = 240) situated in the finance domain to compare three treatments: standalone text-based privacy policies, policies supplemented with privacy labels, and privacy policies supplemented with privacy assistant chatbots. Our results demonstrate that both supplementary privacy assurance mechanisms outperform a standalone text-based privacy policy on trust, with the chatbot additionally reducing privacy concerns. Privacy labels enhanced trust through procedural justice, while the privacy assistant chatbot increased trust through interactional justice and directly reduced privacy concerns. Our findings contribute to a more nuanced understanding of how different privacy assurance mechanisms influence user justice perceptions and outcomes, offering guidance for future research and practice.
Recommended Citation
Konopka, Björn; Thatcher, Jason B.; and Wiesche, Manuel, "Beyond The Wall Of Text: A Comparative Empirical Study Of Privacy Assurance Mechanisms" (2026). ECIS 2026 Proceedings. 12.
https://aisel.aisnet.org/ecis2026/security/security/12
Beyond The Wall Of Text: A Comparative Empirical Study Of Privacy Assurance Mechanisms
Online services increasingly collect personal data, yet traditional text-based privacy policies fail to facilitate informed consent due to their length and complexity. In response, supplementary privacy assurance mechanisms have emerged, including privacy labels and AI-powered privacy assistant chatbots. Drawing on justice theory, we conducted a between-subjects online experiment (N = 240) situated in the finance domain to compare three treatments: standalone text-based privacy policies, policies supplemented with privacy labels, and privacy policies supplemented with privacy assistant chatbots. Our results demonstrate that both supplementary privacy assurance mechanisms outperform a standalone text-based privacy policy on trust, with the chatbot additionally reducing privacy concerns. Privacy labels enhanced trust through procedural justice, while the privacy assistant chatbot increased trust through interactional justice and directly reduced privacy concerns. Our findings contribute to a more nuanced understanding of how different privacy assurance mechanisms influence user justice perceptions and outcomes, offering guidance for future research and practice.
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