Factors that Influence Cookie Acceptance - Characteristics of Cookie Notices that Users Perceive to Affect their Decisions

Julia-Cassandra Giese, Martin Stabauer

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Especially in e-commerce and associated online marketing, web cookies play an essential role as they provide information that is key, for instance, to improving website functionality and customization. With the 2019 ruling of the Court of Justice of the European Union, cookie notices became mandatory in the EU. Companies seek to measure and improve cookie opt-in rates to avoid large data losses relevant for online marketing. We tested in an experiment the most common cookie variants – the binary-choice cookie notice and the category-choice cookie notice – for their acceptance rates. The results showed that the former achieved a slightly, but statistically significantly, higher opt-in rate, and the highest opt-in rate was found among users browsing on mobile devices. The decision to accept or reject cookies when presented with a cookie notice is made within seconds and can be influenced by various external factors, which we sought to identify and examine in this study with the use of a survey following the experiment. None of the external influencing factors examined were perceived as influential by more than half of the participants. Simplicity of use, the speed with which the cookie notice is dismissed and time pressure when browsing were the most frequently mentioned external influencing factors. However, all factors examined had some effect on users’ attitudes to cookie notices.
Original languageEnglish
Title of host publicationHCI in Business, Government and Organizations - 9th International Conference, HCIBGO 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Proceedings
EditorsFiona Fui-Hoon Nah, Keng Siau
Place of PublicationCham
PublisherSpringer
Pages272-285
Number of pages14
Volume13327
ISBN (Print)9783031055430
DOIs
Publication statusPublished - 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13327 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Fields of science

  • 502007 E-commerce
  • 505002 Data protection
  • 502050 Business informatics
  • 509001 Action research

JKU Focus areas

  • Digital Transformation

Cite this