Privacy-Aware Decision Making: The Effect of Privacy Nudges on Privacy Awareness and the Monetary Assessment of Personal Information

被引:0
|
作者
Schmitt, Vera [1 ]
Nicholson, James [2 ]
Moeller, Sebastian [1 ]
机构
[1] Tech Univ Berlin, Qual & Usabil Lab, Berlin, Germany
[2] Northumbria Univ, Dept Comp & Informat Sci, Newcastle, England
关键词
Privacy protection; privacy policy analysis; GDPR; willingness to pay; privacy awareness; USERS;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Nowadays, smartphones are equipped with various sensors collecting a huge amount of sensitive personal information about their users. However, for smartphone users, it remains hidden, and sensitive information is accessed by used applications and data requesters. Moreover, governmental institutions have no means to verify if applications requesting sensitive information are compliant with the General Data Protection Directive (GDPR), as it is infeasible to check the technical details and data requested by applications that are on the market. Thus, this research aims to shed light on the compliance analysis of applications with the GDPR. Therefore, a multidimensional analysis is applied to analyzing the permission requests of applications and empirically test if the information provided about potentially dangerous permissions influences the privacy awareness and their willingness to pay or sell personal data of users. The use case of Google Maps has been chosen to examine privacy awareness and the monetary assessment of data in a concrete scenario. The information about the multidimensional analysis of the permission requests of Google Maps and the privacy consent form is used to design privacy nudges to inform users about potentially harmful permission requests that are not in line with the GDPR. The privacy nudges are evaluated in two crowdsourcing experiments with overall 426 participants, showing that information about harmful data collection practices increases privacy awareness and also the willingness to pay for the protection of personal data.
引用
收藏
页码:17 / 26
页数:10
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