Too much information!? Examining the impact of different levels of transparency on consumers’ evaluations of targeted advertising

Abstract

Online behavioral advertising is widely employed across the Internet. To mitigate the lack of transparency in tailored advertising and increase the acceptance of behavioral advertising, numerous platforms have adopted transparency measures by, for example, providing short explanations to users. We examine to what degree different levels of transparency, operationalized as degrees of detail, delivered through advertising explanations impact consumers’ evaluations of behavioral targeted advertising and their trust in the platform presenting the ad. Empirically, we relied on an online experiment involving 174 Facebook users. Results showed that ad explanations with a medium level of detail led to more favorable advertising evaluations among users compared to ad explanations with a high level of detail.

Keywords:

• Algorithmic Curation
• Attitudes Toward Advertising
• Social Media Platforms
• Targeted Advertising
• Transparency

Data availability statement

The data described in this article are openly available in the Open Science Framework at https://osf.io/p5kb3

Open Scholarship

This article has earned the Center for Open science badges for Open Materials through Open Practices Disclosure. The materials are openly accessible at https://osf.io/p5kb3