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	3.1	5.6	2011	27.7 Days	CHF 1600	Submit
Informatics informatics	2.8	8.4	2014	34.9 Days	CHF 1800	Submit
Journal of Theoretical and Applied Electronic Commerce Research jtaer	4.6	11.7	2006	33.1 Days	CHF 1400	Submit
Algorithms algorithms	2.1	4.5	2008	17.8 Days	CHF 1800	Submit
Data data	2.0	5.0	2016	25.2 Days	CHF 1600	Submit

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