Read the latest and most impactful research on future states and emerging technologies for innovating research methods here. All the research listed comes from the ARF or one of its subsidiaries: The Journal of Advertising Research (JAR), the Marketing Science Institute (MSI) or the Coalition for Innovative Media Measurement (CIMM). Feel free to bookmark this page, as it will be updated periodically.
This research explores the downstream and upstream effects of consumer-to-consumer (C2C) gift subscriptions compared to personal subscriptions in the context of live streaming. It reveals that C2C subscriptions significantly enhance customer lifetime value by encouraging more tips and comments and highlights the importance of creator performance quality in driving subscription behaviors.
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This study explores the potential of large language models (LLMs) to revolutionize marketing research. By partnering with a Fortune 500 food company, the authors replicated qualitative and quantitative studies using GPT-4. The findings indicate that LLMs can effectively generate synthetic respondents, moderate in-depth interviews and perform data analysis tasks, matching or even surpassing human performance in certain aspects. The study highlights the benefits of a Human-LLM hybrid approach, where LLMs assist in various stages of the research process, from study design to data analysis. This approach not only enhances efficiency but also uncovers new insights that might be overlooked by human researchers alone.
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This study evaluates the reasoning depth of large language models (LLMs) using the 11-20 Money Request Game, an experimental game designed to test level-k reasoning. Level-k reasoning is a theoretical framework in game theory where individuals operate at varying levels of strategic thinking. The findings of the study reveal significant differences between the responses of LLMs and human participants, highlighting the limitations of using LLMs as human surrogates in behavioral experiments. This research emphasizes the need for caution when interpreting LLM behavior as human-like, as the models often exhibit inconsistent and non-human-like reasoning patterns. The study suggests that while LLMs can provide valuable insights, they should not be relied upon as accurate simulations of human behavior.
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In the rapidly evolving digital content landscape, media firms and news publishers require automated and efficient methods to enhance user engagement. This study introduces the LLM-Assisted Online Learning Algorithm (LOLA), a novel framework that integrates Large Language Models (LLMs) with adaptive experimentation to optimize content delivery. Leveraging a large-scale dataset from Upworthy, which includes 17,681 headline A/B tests, the study investigates three pure-LLM approaches and finds that prompt-based methods perform poorly, while embedding-based classification models and fine-tuned open-source LLMs achieve higher accuracy.
LOLA combines the best pure-LLM approach with the Upper Confidence Bound (UCB) algorithm to allocate traffic and maximize clicks adaptively. Numerical experiments on data from the website Upworthy show that LOLA outperforms the standard A/B test method, pure bandit algorithms and pure-LLM approaches, particularly in scenarios with limited experimental traffic. This scalable approach is applicable to content experiments across various settings where firms seek to optimize user engagement, including digital advertising and social media recommendations.
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Immersive technologies, including augmented reality (AR), virtual reality (VR) and mixed realities (MR), are expected to become increasingly important in advertising. These technologies create extended realities (XR) that enhance consumer engagement and provide new opportunities for marketers. While the fully immersive “metaverse” is still in development, platforms like Fortnite, Roblox and Zepeto already provide touchpoints where consumers connect physical and virtual realities.
Despite the potential of immersive technologies to transform advertising, there are challenges in effectively deploying them within communication strategies. Limited knowledge on how to use specific technologies or combinations of technologies to achieve different promotional objectives, siloed research on AR and VR applications, and the infancy of these research areas are some of the key challenges. This special issue of the Journal of Advertising Research addresses these challenges and provides insights into the future of immersive technologies in advertising.
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Immersive advertising leverages technologies like virtual reality, augmented reality and the metaverse to create engaging and multisensory experiences for users. This study explores how these technologies can enhance customer engagement and drive purchase intentions by providing vivid mental imagery and interactive experiences. By integrating physical and virtual realms, businesses can create seamless customer journeys and maximize value creation.
The study highlights the effectiveness of immersive advertising in the visitor economy, using examples from the Coachella festival and Emirates Airline. These case studies demonstrate how immersive technologies can attract and engage audiences, ultimately converting virtual interactions into real-world purchases.
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Explore the implications of informed privacy consent on behavior-based pricing (BBP) with this new MSI working paper. It highlights how privacy regulations requiring consumer consent before data collection impact pricing strategies and consumer surplus. The research finds that while informed consent empowers consumers, it paradoxically reduces overall consumer surplus by reducing the potential benefits of customized offers.
The study also reveals that firms can achieve higher profits by offering rewards for privacy consent, despite the associated costs. This underscores the complexity of privacy regulations and their unintended consequences on market dynamics and consumer welfare.
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The study explores the relationship between consumers' AI literacy and their receptivity to this emerging technology. What is AI literacy you ask? This refers to a person's degree of objective knowledge about AI, while receptivity refers to the extent to which a consumer is interested in having AI complete tasks. The study finds that contrary to popular belief, people with lower AI literacy exhibit greater receptivity towards AI-based products and services. What’s more, this relationship persists across a broad range of receptivity measures.
The research offers both theoretical and practical contributions. Theoretically, it contributes to the growing literature on psychological responses to AI, by focusing on understanding whether systematic differences across individuals predict differences in AI receptivity. Practically, the results suggest that attempts to increase the adoption of AI-based products and services through targeting consumers with greater AI literacy or increasing knowledge of AI may not be the most effective.
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Before the resurgence in interest in AI, virtual reality was the technology everyone was excited about. Despite the hype, advertisers have been slow to adopt VR environments. Why is this? This study, which was recently made available early online on the Journal of Advertising Research’s website, explores the potential and challenges of VR environments for advertising in its current state.
Widespread adoption has stalled, the study finds, due to obstacles such as limited reach, anticipated lack of ROI, lack of technical expertise and poor interoperability. However, the metaverse offers unique opportunities for advertisers, leaving a sort of resonating impact that other media cannot convey, because they do not engage the user in as immersive an experience as VR offers.
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Virtual influencers are computer-generated personas that engage with audiences on social media and in the metaverse. This study explores whether virtual influencers are more effective in advertising when they include real-world elements, such as interacting with real humans or endorsing real-world products. The research is grounded in the Computers Are Social Actors (CASA) framework and investigates how social cues and product types influence consumer perceptions of authenticity and attitudes toward both the influencer and the brand.
The findings suggest that virtual influencers are perceived as more authentic and favorable when they are shown alongside real humans and endorse real-world products. This perceived authenticity positively impacts consumer attitudes toward the virtual influencer and the brand, providing valuable insights for advertisers looking to leverage virtual influencers in their marketing strategies.
More analysis and the full study is available to ARF members.
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