Ad Avoidance in Digital Advertising: The Impact of Privacy Disruption and Perceived Intrusiveness

Purpose: Technological intervention in all domains has changed the world, and data has become major input for building strategies. This technology intervention has paved the way for digital marketers to collect data for developing marketing strategies destroying consumer privacy. Digital marketing strategies include social media ads, which are a private space for every user. This article presents empirical inferential data to determine the impact of privacy risk, privacy concern, and privacy control on ad-avoidance behaviour. A structured questionnaire was adopted in this study to collect data among digital natives and digital immigrants. N=100 was bootstrapped to 5000 subsamples. The model developed to test the impact is a reflective Structural Equation Model (SEM); hence the present data was analyzed through SmartPLS software, Version 3. The SEM model depicted the estimates of the interrelationship between the major constructs in the dataset. Findings showed a positive relationship between privacy risk and perceived intrusiveness. Similarly, perceived intrusiveness was strongly related to ad avoidance. Marketers need to concentrate on balancing the intrusive digital ads on social media platforms. The current research contributes to the advertising intrusiveness literature by developing a conceptual framework that provides an understanding of variables leading to ad avoidance.