We offer a retrospective on interactive advertising research by first examining the topics addressed in the Journal of Interactive Advertising (JIA) in three respects: (1) how these topics align with the journal’s editorial mission; (2) how different they are from adjacent journals; and (3) how they mirror key evolutions in advertising practice. We screened the focal research topics of 1380 articles published since 2000 in three journals: Journal of Interactive Advertising, Journal of Research in Interactive Marketing, and Journal of Interactive Marketing. Additionally, we discuss how publication characteristics in JIA evolved during the past decade, highlighting notable patterns. To that end, we screened the 173 articles published in the 10 most recent JIA volumes on the following characteristics: research topics; theoretical lenses; methods (types of samples, countries in which the studies were conducted, research designs and analytical approaches, realism and ecological validity in research designs); and the quality of the managerial implications offered and quality of the further research suggestions. Finally, we provide methodological recommendations and an extensive further research agenda for four interactive advertising categories, encompassing: (1) innovation and technology: real-time hyper-personalization, immersive experiences, personalized search technology, and location-based advertising, (2) consumer responses: user-generated content, ad avoidance, (3) integration strategies: integration of tools and channels, integration across societal groups, and (4) ethics and sustainability: consumer data empowerment, and ad carbon footprint and consumer digital impact.

Artificial intelligence (AI) technology is widely used in social media to offer personalized experiences and shape user engagement, but questions persist about AI’s potential. Due to the nascency of the technologies, little understanding exists about how these systems impact our societies. This study establishes an approach that integrates moral foundations theory and AI-mediated communication (AI-MC) using in-context learning to appeal to Black Americans on social media. We empirically compare the AI-MC with the human-authored copy on user engagement results from Facebook advertising messages, with self-reported measures of engagement using a two-part, 2 × 3 factorially designed study. The results indicated that AI-MC and positive perceptions toward AI can lead to higher engagement with messaging targeting Black Americans. The AI effect was most pronounced on the loyalty/betrayal moral frame, which had the least linguistic similarity to the human-authored stimuli but was most effective at engaging the audience. Engagement patterns were also inconsistent between the behavioral outcomes reported by Facebook and the engagement that was self-reported by respondents, suggesting differences between perceived engagement and what occurs naturally on social media.

Drawing upon uses and gratifications theory (UGT) and self-determination theory (SDT), this research examined how social interaction with other users and brand engagement in metaverse stores influence consumer satisfaction and purchase intentions, with media enjoyment serving as a mediator. To assess these relationships, we employed a 2 (social interaction: present vs. absent) × 2 (brand engagement: high vs. low) factorial experiment across two studies with young consumers, utilizing a controlled video simulation of a metaverse store (Study 1) and an immersive metaverse platform (Study 2). Study 1 revealed that social interaction had a direct effect on both brand store satisfaction and purchase intentions, whereas brand engagement directly influenced only brand store satisfaction; however, both factors exerted indirect effects on outcomes through enjoyment. Study 2 confirmed the direct and indirect effects of social interaction on brand store satisfaction and purchase intentions, whereas brand engagement influenced these outcomes solely through the mediating role of media enjoyment. Theoretical and practical implications are discussed.

This paper revisits and builds on Taylor’s (2009) framework of the six principles of digital advertising. The basic tenet of the framework is that six factors—privacy, trust, relevance, interactivity, entertainment, and brand-building—are associated with enhancing the effectiveness of digital advertising. Initially proposed as isolated factors, this analysis highlights the interconnected nature of these principles, offering a holistic perspective that underscores their collective impact on digital advertising effectiveness. In addition, the ways in which advances in recent technological advances, including generative artificial intelligence, artificial reality, virtual reality, gamification, and the presence of the metaverse have affected implementation of these principles by practitioners is discussed. By reexamining these foundational principles, this paper offers valuable insights for scholars and practitioners in gaining a deeper understanding of the complexities of interactive and immersive digital advertising.

Interactive advertising has transformed the relation between consumers and advertisers, with data collection and processing now at its core. Dataveillance—the automated tracking and analysis of large volumes of digital traces—plays a crucial role in enhancing personalization in interactive advertising. However, the increasing reliance on dataveillance raises significant concerns, including impacts on privacy, individual autonomy, ethical considerations, and societal inequalities. This article examines the role of dataveillance across the interactive advertising process, highlighting its implications for the interactions between consumers and advertisers, and its resulting challenges. By mapping these challenges, this article advances theoretical understanding of the interplay between interactive advertising and dataveillance and offers a research agenda to guide future investigations. The research agenda focuses on the impact of dataveillance on advertising effectiveness, consumer interactions, and advertising research.

Artificial intelligence (AI) has the potential to revolutionize the advertising industry by transforming how advertisements are created, delivered, and analyzed. This paper provides a comprehensive overview of 20 years of advertising research on the use of AI, based on a systematic literature review of 83 publications from leading advertising journals. The review reveals four major topics: AI agents, AI-driven insights, AI-powered ad delivery, and AI-assisted content creation, with AI-assisted content creation being the least explored. Building on current research trends, this paper expands previous studies by focusing on this underexplored area and discusses five types of AI-generated advertising—curated personas, timeless storytelling, artistic craftsmanship, product imagination, and personalized personas—and their connection to AI aversion. Based on the review and current discussion, we propose a research agenda for future advertising research on AI, focusing on three areas: (1) co-creation and interactivity; (2) leveraging diverse AI roles to mitigate AI aversion; and (3) productivity versus ethics.

Despite the prevalence of diversity of endorsers in interactive advertising, most previous research has concentrated on diversity in traditional advertising formats. This paper, therefore, explores the phenomenon of diversity within interactive advertising, analyzing its unique characteristics, prevalence, and impact. It reviews the limited existing research on diversity in interactive advertising and discusses the distinctive features of this advertising type—such as user participation, personalization, Big Data, multimodality, technology, and shared control—and how each contributes to the prevalence, representation, and effects of diversity. User participation allows consumers to influence how diversity is (re-)presented. Personalization and targeting enable tailored diversity content, which enhances relevance but carries the risk of discrimination. Big Data provides more nuanced insights into diversity portrayals and can connect it to consumer engagement. Multimodality, through the use of visuals, enhances engagement but may also reinforce stereotypes. Technological advancements facilitate more diverse portrayals. Shared control emphasizes authenticity in diversity, although backlash can occur if content is perceived as insincere. The paper suggests research propositions for each feature that provide ideas and directions for future research on diversity in interactive advertising, followed by several managerial takeaways.

In an effort to sell, advertisers track our needs, preferences, and online behaviors. The continuous collection of big volumes of data results in the so-called dataveillance. Guided by the transparency-awareness-control framework and privacy management theory, the current study aims to provide insights into consumers’ thought processes as they determine if, when, and what types of dataveillance are appropriate. We analyzed 22 in-depth interviews and explored consumer perceptions of appropriate dataveillance in the context of advertising. Our findings show that interviewees held pre-existing expectations of dataveillance that helped determine whether specific circumstances were appropriate. Interviewees desired awareness of and control over dataveillance for advertising purposes, and these two factors often intertwined with their expectations. Additionally, interviewees expressed privacy cynicism, or a feeling that they lacked control over the collection and use of their personal information. Consumer perceptions of appropriate dataveillance in advertising provides important implications to advertisers on how to navigate data collection and usage for advertising to prevent backlash.

With the start of generative potential of artificial intelligence (AI) to create ads at scale, is the industry in danger of creating ineffective content efficiently, or AI can help achieve both efficiency and effectiveness? The adoption of generative AI in advertising is a function of not only efficiency but also effectiveness gains. This study looks beyond efficiency to consider consumer responses. It explores the productivity of AI-powered ads, in which generative AI tools assist in specific creative tasks under human supervision. This study introduces a new measure of artificial intelligence advertising productivity (AAP). This measure employs data envelopment analysis (DEA) to examine the balance of generative AI advertising specific inputs to consumer response outputs. To understand consumer responses, this study uses topic modeling (BERTopic) and sentiment analysis (Google Natural Language AI) to analyze 10,378 consumer comments on the generative AI-powered ads and their comparable human-created ads. The results are fed into DEA to calculate AAP. The AAP measure provides marketers a suggested metric to evaluate the value gained from their AI advertising initiatives. It provides brands with a benchmark to assess their AI advertising performance against other brands. The results show a majority of generative AI-powered ads in the sample were identified as productive and consumers generally perceive these ads positive.

As brands increasingly integrate autonomous sensory meridian response (ASMR) marketing into advertising strategies, understanding its underlying persuasive mechanisms remains a critical research gap. Building on the entertainment overcoming resistance model (EORM) and extending its framework, this study develops the advertising consumers’ resistance-overcoming sensory satisfaction (ACROSS) model, identifying the psychological pathways through which ASMR advertisements facilitate persuasion. Across two experimental studies (Study 1: N = 578; Study 2: N = 588), a serial–parallel mediation model was tested. Results showed that sensory modalities of ASMR—particularly auditory stimulation—enhanced key entertainment-based psychological processes, including voice credibility, sensory gratification, interest, transportation, parasocial interaction, identification, and endorser liking. These entertainment features, in turn, weakened message resistance factors (i.e., reactance, counterarguing, intrusiveness), ultimately inducing more favorable attitudes and behavioral intentions. By adding ASMR marketing to the broader entertainment–persuasion literature, this study extends existing models of media-based persuasion, offering theoretical and practical insights for scholars and practitioners in advertising, marketing, and consumer psychology.