Journal of Research in Interactive Marketing

Bui, Hien Thu

doi: 10.1108/jrim-02-2025-0066pmid: N/A

The integration of artificial intelligence (AI) into advertising has revolutionized how brands create and deliver marketing messages. The involvement of AI in ad creation introduces a critical question: if the AI origin of an advertisement is disclosed, how this transparency affects advertising value and purchase intentions. Grounded on the Persuasion Knowledge Model, this study investigates the effect of AI disclosure on these two key outcomes.Design/methodology/approachChatGPT and Stable Diffusion were employed to generate stimuli. 358 consumers recruited via Prolific were exposed to the stimuli. The data were analyzed using a combination of Hayes’ Process models, MANCOVA and ANCOVA.FindingsThe results reveal that AI disclosure diminishes advertising value and purchase intentions. The relationships are negatively mediated by advertising credibility and positively moderated by consumer attitudes towards AI.Originality/valueTheoretically, the research contributes to a more comprehensive picture of AI-generated advertising evaluation. Practically, the research offers actionable insights for businesses seeking to balance the advantages of AI with human psychology, ultimately optimizing advertising effectiveness in an increasingly AI-driven marketplace.

Cao, Yiqun; Aral, Sinan

doi: 10.1108/jrim-04-2024-0212pmid: N/A

Understanding video advertising effectiveness is essential, given advertisers’ substantial investment in the format and its ubiquitous presence in our daily lives. But understanding video ad feature effectiveness is challenging due to the limited availability of video ad data and the complexity of video features.Design/methodology/approachWe therefore collected video ad and performance data on more than 90,000 video ad campaigns, registering 1 trillion impressions, across more than 20 industry segments, on six popular social media platforms, including Facebook, YouTube, SnapChat, LinkedIn, Twitter and Pinterest. We establish a taxonomy of video ad features, based on the Elaboration Likelihood Model (ELM), using unsupervised clustering to explore how different features cluster across our sample. We then perform a feature importance analysis, using group Lasso and Random Forest models, and employ multilevel linear models of video feature effects on ad performance.FindingsWe find, for example, that the presence and early appearance of text in videos reduces view-related performance metrics, while the presence and early appearance of people improves view-related metrics. We also explore the heterogeneity of video ad feature performance effects across platforms, industries and campaign objectives. As predicted by ELM, for example, text reduces ad performance in the luxury industry and increases performance in professional services ads.Originality/valueTo our knowledge, ours is the largest analysis of video ad features and their performance implications to date. We hope to provide a foundation for future causal studies of video ad features and their performance effects.

Çi̇l, Ebru; Erkan, Ismail; Acikgoz, Fulya

doi: 10.1108/jrim-11-2024-0526pmid: N/A

Drawing on perspectives from Human-Computer Interaction and interactive marketing, this study examines how immersive technologies such as Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) shape virtual customer experiences (VCEs) as standalone digital offerings. It explores how these technologies deliver intrinsic experiential value across emotional, cognitive, and social dimensions, rather than merely supporting purchase decisions.Design/methodology/approachA systematic literature review was conducted using the Scopus and Web of Science databases, analyzing 78 peer-reviewed articles published in journals listed on the Australian Business Deans Council Quality List. The search included specific and broader terms (e.g. “virtual customer experience,” “immersive technology,” “consumer experience”) to capture interdisciplinary perspectives.FindingsThe review identifies immersive environments – such as virtual brand worlds, AR-based entertainment, and gamified VR scenarios – as sources of intrinsic consumer value, fostering sustained engagement, brand attachment, and satisfaction independently from traditional product sales. However, ethical and psychological concerns, including technostress, privacy, and cognitive fatigue, also emerged as significant factors shaping consumer interactions. These insights are structured into a conceptual framework outlining three stages of the VCE journey: pre-decision, phygital interaction, and post-intention engagement.Originality/valueThis review synthesizes previously fragmented insights, providing a holistic view encompassing both enjoyment-driven and practical aspects of immersive interactions, while emphasizing the importance of inclusive and ethically responsible design.

Kan, Tangchung; Ku, Edward C.S.

doi: 10.1108/jrim-03-2025-0107pmid: N/A

This study explores how perceived ChatGPT credibility, compatibility, and innovative digital marketing influence joint decision-making and process innovation capabilities through relational ties.Design/methodology/approachThe research model was analyzed using partial least squares structural equation modeling (PLS-SEM) based on 472 valid questionnaires from members of three well-known online travel communities who traveled with unfamiliar companions.FindingsResults showed that perceived ChatGPT credibility, compatibility, and innovative digital marketing significantly impacted relational ties, which, in turn, influenced joint decision-making and process innovation capabilities. Additionally, joint decision-making significantly affects process innovation capabilities.Originality/valueThis study offers three notable contributions to tourism marketing. Through empirical research, it analyzes the relationship between joint decision-making and the process innovation capabilities of OTCs. Specifically, the study provides a novel perspective on the Process Innovation model, encompassing antecedents, mediators, and moderators. Through analysis through PLS, this study clearly understands the causal relationship between joint decision-making and process innovation capabilities of OTCs.

Huang, Qing; Zhou, Yiting; Wu, Zongshu; Li, Xiaoling

doi: 10.1108/jrim-02-2025-0095pmid: N/A

Exploring factors beyond position rank that determine the sponsored search advertising performance is critical, which reduces sellers’ reliance on costly bidding price. In this study, we focus on keyword specificity and keyword popularity, and examine how they influence the click-through rate (CTR) and conversion rate (CR) of search advertising differently. We also examine how two types of advertising information (commercial and quality) vary the effects of each keyword attribute.Design/methodology/approachUsing a dataset collected from a leading e-commerce platform in China, we employed a seemingly unrelated regression model to test the hypotheses.FindingsOur results show that more specific keywords generate higher CR but lower CTR. On the contrary, more popular keywords generate higher CTR but lower CR. Their relative effects are influenced by advertising information. Commercial information is more conducive to improving the effects of keyword specificity, while quality information is more conducive to improving the effects of keyword popularity.Originality/valueThe current study explores the impacts of keyword specificity and keyword popularity on CTR and CR of sponsored search advertising, shifting prior research focus from single attribute to a comprehensive view of both internal and external aspects of keywords. Moreover, it enriches the literature on interactive marketing and ad copy design by introducing advertising information as sellers’ response to consumer search needs and demonstrating the importance of aligning advertising information types with keyword attributes.

Guo, Rui; Sun, Dongli; Luo, Yang; Zhou, Min; Tao, Lan

doi: 10.1108/jrim-01-2025-0008pmid: N/A

Amid growing environmental concerns, green demarketing (GD) has emerged as a strategy for encouraging sustainable consumption by discouraging excessive use. This study investigates how message sidedness (one-sided vs. two-sided) in GD communication influences consumer purchase intentions, and whether this effect is moderated by product attribute dominance (utilitarian vs. hedonic).Design/methodology/approachAcross five experiments (N = 1,153), including lab-based scenarios, field studies, and an eye-tracking experiment, participants were exposed to GD brand messages with varying sidedness and attribute emphasis. Perceived sincerity was examined as a mediating mechanism.FindingsResults show that two-sided GD messages, which acknowledge both benefits and limitations, tend to enhance purchase intentions, particularly for products emphasizing utilitarian attributes. In contrast, one-sided messages are more effective when products highlight hedonic features. Mediation analyses confirm that perceived sincerity explains the effect of message sidedness.Originality/valueThis research advances understanding of how message presentation and product positioning interact to shape consumer responses to sustainable branding. It offers actionable insights for marketers on leveraging message transparency and attribute framing in green demarketing strategies.

Bai, Shizhen; Yang, Yuan; Yu, Dingyao; Tan, Yongbo

doi: 10.1108/jrim-01-2025-0035pmid: N/A

This study investigates how the information and sentiment of content conveyed by AI agents on digital platforms influence user engagement with multimodal content. Analyzing data on 2,238 agents from the character AI system, we show how text and images activate distinct information-processing channels and jointly shape user interactions.Design/methodology/approachWe analyze multimodal data from AI agents using structural topic modeling (STM), VADER sentiment analysis, image information entropy and a ResNet-50 deep-learning model. Grounded in dual coding theory (DCT) and the elaboration likelihood model (ELM), we focus on two attributes – informational richness and sentiment polarity – for both text and images, and test their impacts on users’ online engagement behavior.FindingsText information shows an inverted-U relationship with user engagement. Image visual complexity moderates the effect of textual informational richness. Although aggregate sentiment does not significantly predict engagement, image sentiment amplifies the effect of text sentiment. Images with low emotional intensity create an “emotional vacuum” that increases engagement when paired with positive textual sentiment.Originality/valueBy integrating DCT and ELM, this study offers a new framework for explaining the behavioral effects of multimodal content. It also introduces a method for quantifying the informational and affective attributes of text–image pairs. The findings provide actionable guidance for optimizing digital marketing content and the design of AI-driven conversational agents.

Song, Xi; Liu, Matthew Tingchi; Lee, Voon-Hsien; Mo, Ziying

doi: 10.1108/jrim-02-2025-0106pmid: N/A

This paper elucidated how recommendation agents (RAs) in online retailing elicit a counteractive perception among consumers from a perspective of control, which results in their intent to avoid RA recommendations. For marketers who attempt to reduce consumers’ negative responses in the context of RAs, the paper examined whether an RA empowered by algorithmic transparency would confer an effective solution.Design/methodology/approachOne pilot test and two studies of scenario-based experiments were conducted to capture the proposed effect.FindingsThe findings support that sense of control (SOC) and avoidance intention (AV) are negatively related, where privacy concern (PC) mediates the relationship. Transparency empowerment exerts a detrimental effect on leveraging consumers’ SOC. The assertion that an increased SOC eliminates consumer avoidance is found to be substantially stronger in the absence of transparency.Research limitations/implicationsThe research consolidates the compensatory control theory (CCT) and adds a novel perspective on the relationship between one’s control and PC, which has yet to be adequately addressed. It enriches empowerment literature by revealing that algorithm transparency would not significantly influence consumers’ avoidance of RAs’ recommendations, whereas non-transparent RAs would attenuate such impact.Practical implicationsThis study entails significant implications for technicians and marketers, emphasizing the need to promote feelings of control through RAs while also highlighting the necessity to rethink the interpretability and transparency attributes in RAs.Originality/valueThis research contributes to the literature on human–technology interaction, documents key theoretical and managerial implications, and sheds light on the counterintuitive effects that span the literature on individual control and consumer empowerment.