Algorithmic Symbiosis in the New Era of Interactive Marketing

Topic Information

Dear Colleagues,

Interactive marketing has evolved significantly from its origins in direct marketing, becoming defined as a process of bi-directional value creation achieved through active customer connection, engagement, and participation (Wang, 2021; Wang, 2024). This paradigm shifted the market from a broadcast medium to a dynamic forum for conversation between connected actors. Recent technologies are transcending their role as mere tools for facilitating communication and are emerging as active, agentic participants in the value co-creation process itself (De Freitas et al., 2025). AI now automates content creation, personalizes customer experiences in real time, and analyzes vast datasets to predict consumer behavior with unprecedented accuracy (Davenport et al., 2020).

This profound integration necessitates a conceptual leap from “interaction” to “symbiosis.” The relationship between consumers, brands, and AI is no longer a series of discrete, turn-based exchanges but a deeply intertwined and mutually dependent ecosystem (Valenzuela et al., 2025; Wang, 2024). Consumers’ data continuously refines algorithmic models, which in turn shape and personalize the consumer journey, creating a feedback loop where the boundaries between human input and machine output become increasingly blurred (Edelman & Abraham, 2022). This new paradigm of “Algorithmic Symbiosis” presents a duality of immense opportunity and significant risk. On one hand, it unlocks hyper-personalization at scale, enhances creative ideation, and optimizes marketing efficiency (De Freitas et al., 2025; Davenport et al., 2020). On the other hand, it introduces critical challenges, including the risk of “AI hallucinations”, that can damage brand reputation, the potential for algorithmic bias, and escalating consumer privacy concerns (De Bruyn et al., 2020).

This Topic calls upon scholars and practitioners to explore the multifaceted dimensions of this new symbiotic era. We invite research that moves beyond viewing AI as an instrument and instead investigates its role as a collaborator, a social actor, and a central force in the future of interactive marketing. By fostering a multidisciplinary dialogue, we aim to build a robust theoretical and practical framework to navigate the complexities and harness the full potential of this transformative age, ensuring that technological advancement fosters responsible and sustainable value for all stakeholders (Wang, 2025).  Suggested topics include (but are not limited to) the following:

1. The Psychology of Human–AI Collaboration in Marketing.
2. Ethical Frameworks for Generative AI in Advertising.
3. Algorithmic Bias and Fairness in Customer Segmentation.
4. The Future of Personalization: From Segments to Symbiosis.
5. Consumer Trust and Adoption of AI Marketing Agents.
6. Embodied AI and the In-Store Customer Experience.
7. AI-Driven Creativity: Augmentation vs. Automation.
8. Privacy Calculus in the Age of AI-Mediated Interactions.
9. The Role of AI in Shaping Consumer Identity and Choice.
10. Value Co-Creation with AI-Powered Prosumers.
11. Navigating AI Hallucinations and Misinformation in Branding.
12. The Impact of Social AI on Brand Communities.
13. Measuring ROI in an AI-Driven Marketing Ecosystem.
14. Regulatory Challenges for AI in Interactive Marketing.
15. The Evolution of the Customer Journey with AI Touchpoints.
16. Leveraging Data Science and Gen AI Technologies for Marketing.
17. Contributions of Biometrics and Multimodal Systems to Marketing Research.

References

Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24–42.

De Bruyn, A., Viswanathan, V., Beh, Y. S., Brock, J. K. U., & Von Wangenheim, F. (2020). Artificial intelligence and marketing: Pitfalls and opportunities. Journal of Interactive Marketing, 51(1), 91–105.

De Freitas, J., Nave, G., & Puntoni, S. (2025). Ideation with generative AI—in consumer research and beyond. Journal of Consumer Research, 52(1), 18–31.

Edelman, D. C., & Abraham, M. (2022). Customer Experience in the Age of AI. Harvard Business Review, 100(3–4), 116–125.

Valenzuela, A., Puntoni, S., Hoffman, D., Castelo, N., De Freitas, J., Dietvorst, B., ... & Wertenbroch, K. (2024). How artificial intelligence constrains the human experience. Journal of the Association for Consumer Research, 9(3), 241–256.

Wang, C. L. (2021). New frontiers and future directions in interactive marketing: inaugural Editorial. Journal of Research in Interactive Marketing, 15(1), 1–9.

Wang, C. L. (2024). Editorial–what is an interactive marketing perspective and what are emerging research areas? Journal of Research in Interactive Marketing, 18(2), 161–165.

Wang, C.L. (2025). Editorial: Demonstrating contributions through storytelling. Journal of Research in Interactive Marketing, Vol. 19 No. 1, pp. 1–4. https://doi.org/10.1108/JRIM-01-2025-455.

Prof. Dr. Chenglu Wang
Dr. Zhen Li
Dr. Xiaoling Li
Dr. Hongfei Liu
Dr. Morgan Yang
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Administrative Sciences admsci	3.9	6.6	2011	21.5 Days	CHF 1600	Submit
Algorithms algorithms	2.6	5.4	2008	17.6 Days	CHF 1800	Submit
Data data	2.4	5.4	2016	19.2 Days	CHF 1600	Submit
Informatics informatics	5.1	9.1	2014	32.7 Days	CHF 1800	Submit
Journal of Theoretical and Applied Electronic Commerce Research jtaer	4.5	7.1	2006	20.9 Days	CHF 1400	Submit

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Published Papers (3 papers)

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Open AccessArticle

Striking the Right Pitch: The Inverted U-Shaped Effect of AI Anchor Pitch Variability on Consumer Engagement

by Xiaochen Liu, Qiang Yang and Yushi Jiang

J. Theor. Appl. Electron. Commer. Res. 2026, 21(8), 273; https://doi.org/10.3390/jtaer21080273 - 14 Aug 2026

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Abstract

As artificial intelligence and digital human technologies become increasingly integrated into livestream commerce, AI anchors are becoming important marketing agents. Yet prior research has focused primarily on their visual characteristics, leaving dynamic vocal cues largely unexplored. Drawing on social response theory and perceived [...] Read more.

As artificial intelligence and digital human technologies become increasingly integrated into livestream commerce, AI anchors are becoming important marketing agents. Yet prior research has focused primarily on their visual characteristics, leaving dynamic vocal cues largely unexplored. Drawing on social response theory and perceived authenticity research, this study examines the nonlinear association between AI anchor pitch variability and consumer engagement, together with a proposed psychological pathway and boundary condition. Study 1 analyzes 4322 product-presentation segments nested within 330 AI-anchored livestreams and 85 independent accounts on Douyin. Negative binomial models, formal boundary-slope tests, and additional specifications using account and livestream-session fixed effects, a correlated-random-effects decomposition, and viewer-minutes exposure provide robust evidence of an inverted U-shaped association between pitch variability and real-time danmaku engagement. Evidence concerning appearance-realism moderation is conditional and specification-sensitive across alternative pitch operationalizations, exposure definitions, and within-account specifications. Study 2 uses a preregistered multi-stimulus mixed design with four AI anchors, four products, and three between-participants pitch-variability conditions. Correctly scaled planned contrasts show that moderate pitch variability produced greater perceived authenticity and engagement intentions than the average of the two endpoint conditions. A 2-1-1 multilevel analysis yielded an indirect-effect pattern consistent with the proposed role of perceived authenticity. Models allowing treatment effects to vary across the 16 included anchor-product combinations showed a positive average moderate-pitch advantage, although its magnitude varied across stimuli. These findings extend livestream-commerce research from human streamers to AI-mediated communication while indicating that appearance-realism moderation, stimulus-level generalization, and causal mediation require further replication. Full article

(This article belongs to the Topic Algorithmic Symbiosis in the New Era of Interactive Marketing)

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32 pages, 1332 KB  

Open AccessArticle

Strategic Disclosure of AI Curation: A Boundary Condition on Algorithm Aversion in Hedonic E-Commerce

by Tiannv Ma, Yuqi Du, Yong Wang and Liying Zhou

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 232; https://doi.org/10.3390/jtaer21070232 - 18 Jul 2026

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Abstract

Algorithm-aversion research predicts that consumers prefer human curators to algorithmic ones in subjective decision domains, including taste-based hedonic recommendation. Drawing on the algorithmic-symbiosis paradigm and on assortment-perception theory, this paper identifies a boundary condition on that prediction: disclosing that recommendations are AI-curated rather [...] Read more.

Algorithm-aversion research predicts that consumers prefer human curators to algorithmic ones in subjective decision domains, including taste-based hedonic recommendation. Drawing on the algorithmic-symbiosis paradigm and on assortment-perception theory, this paper identifies a boundary condition on that prediction: disclosing that recommendations are AI-curated rather than human-curated lifts purchase intention in hedonic e-commerce but not in utilitarian e-commerce. The mechanism is a search-side option-breadth inference—the consumer’s attribution about the size of the option pool the curator considered upstream—which is diagnostic in preference-formative consumption categories where consumers build, rather than match, a preference. Three online experiments deployed through a Chinese consumer panel test the framework. Study 1 ($N=228$) finds the predicted Disclosure × Product-type interaction (${\eta }_p^2=0.025$) with the AI-versus-human lift confined to the hedonic cell ($d=0.65$). Study 2 ($N=257$) isolates the option-breadth pathway against trust and competence as competing mediators. Study 3 ($N=519$) extends the design to a second hedonic category, decomposes option breadth into search-side and display-side subdimensions through an eight-item bi-factor scale, tests mentalizing alongside option breadth as a competing mediator, and brings the moderated-mediation test by consumer AI familiarity to conventional statistical power (index of moderated mediation $=+0.065$, 95% CI $[+0.014,+0.118]$). Implications for interactive-marketing practice and algorithmic-disclosure regulation are discussed. Full article

(This article belongs to the Topic Algorithmic Symbiosis in the New Era of Interactive Marketing)

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23 pages, 2657 KB  

Open AccessArticle

Consumer Reactions to Virtual Influencer Transgressions: How Anime-Looking and AI-Driven Influencers Are Less Vulnerable

by Wei Song, Siyuan Wei, Zinuo Li, Shengliang Deng and Yuqi Du

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 219; https://doi.org/10.3390/jtaer21070219 - 9 Jul 2026

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Abstract

Virtual influencers in diverse appearances emerged and gained popularity on virtual platforms. However, how the appearances of virtual influencers affect consumers’ attitudes and reactions remained largely unexplored. Through three experimental studies, this paper examines the psychological mechanism and boundary conditions for consumer reactions [...] Read more.

Virtual influencers in diverse appearances emerged and gained popularity on virtual platforms. However, how the appearances of virtual influencers affect consumers’ attitudes and reactions remained largely unexplored. Through three experimental studies, this paper examines the psychological mechanism and boundary conditions for consumer reactions to virtual influencer transgressions. The results show that consumers are less forgiving and more negative in their reactions to transgressions conducted by human-like virtual influencers compared to anime-like ones, regardless of the type of transgression or the gender of the virtual influencer (Studies 1 and 2). Additionally, the driving mechanism of the virtual influencers has a moderating effect. When consumers are informed that the virtual influencer transgression is driven by a real person rather than AI, the impact of appearance on the reactions to transgressions is aggravated (Study 3). The result shows that appearance and driving mechanism both influence consumer perceptions of the virtual influencers’ agency, thereby determining the degree of reaction to transgressions. Full article

(This article belongs to the Topic Algorithmic Symbiosis in the New Era of Interactive Marketing)

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