Abstract

In response to the booming prevalence of mobile phone usage, marketers are increasingly turning to digital advertising as a targeted communication tool. However, this shift has exposed consumers to a barrage of advertisements, potentially leading to heightened irritation and casting doubts on the overall efficacy of advertising efforts. The motivation behind this research stems from the need to understand how the value derived from digital advertising influences consumer perceptions and behaviors, particularly in the face of rising irritation levels. The existing landscape of digital advertising necessitates a nuanced exploration of these dynamics to aid marketers in refining their strategies. Addressing this concern, our study employs a moderated mediation model to delve into the intricate relationship between digital advertising value, consumer attitudes toward advertising, and purchase intention. Utilizing a deep learning framework and the advertising value model, our methodology involved collecting data from 300 individuals. We employed a multi-analytic approach, combining partial least squares structural equation modeling and necessary condition analysis (NCA) to comprehensively analyze the conceptual model. Our results reveal an insight - digital advertising value exerts a more potent impact on purchase intention compared to its influence on attitudes toward advertising. Furthermore, the study underscores the pivotal role of advertising irritation as a robust negative moderator, significantly diminishing the overall effectiveness of advertising endeavors. The necessary condition analysis (NCA) findings offer a nuanced perspective, highlighting varying degrees of predictor necessity in the examined relationships. This nuanced understanding of predictor necessity provides valuable insights for advertisers aiming to optimize their strategies and enhance the effectiveness of digital advertising campaigns.