Year: 2020
Type: dissertation
Abstract: Forms for consent regarding the use of digital cookies are currently used by websites to convey the information about the use of digital cookies on the visited website. However, the design of these consent forms is not entirely right according to the directives of the General Data Protection Regulation and also not optimal seen from a user's perspective. They often lack options and the informational text is often too brief within the form. As a user, that might make it difficult to understand what it is you accept and what the consequences could be for your personal data. Based on the directives given for the digital cookie consent form, it becomes clear that many do not meet the requirements. The question therefore arise, which factors make a cookie consent form successful, concerning how well a user understands the content and is aware of his/her choice of action? To answer that question, a quantitative- and a qualitative study was conducted. The quantitative study examined people's current understanding and perception about digital cookie forms. The results of that study were then used in the qualitative study to develop prototypes producing new cookie consent forms which were then examined with a usability test. The study presents five factors that contribute to a cookie consent form to be considered successful from the user's perspective in understanding the content and making an active choice. These factors are text, options, full-page consent form, active choice and trustworthiness. These five factors can independently increase the user experience of a form, although, all should be accounted for for better results. The various factors together contribute to a form that complies with different directives and laws, but above all, helps users get a better experience of understanding what they approve of and the feeling of making an active choice.
Author: Louise Gröndahl
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3173296260