Chatbots as brand agents: how brand concepts shape consumer engagement

Yuanyuan Cai et al.

Journal of Research in Interactive Marketing2026https://doi.org/10.1108/jrim-05-2025-0280article
AJG 1ABDC B
Weight
0.50

What the paper says

Purpose The rapid evolution of technology has ushered in a new epoch in consumer–brand interaction, with chatbots playing an important role. Despite the widely recognized potential of chatbots to reduce costs and increase productivity, their impacts on consumer experiences vary. This research examines how to enhance consumer engagement with chatbots by adopting a new perspective of brand concepts based on human values. Design/methodology/approach Four experiments were conducted to examine how brand concepts (self-transcendence vs. self-enhancement) and service agent types (human vs. chatbot) influence consumer engagement, with perceived fit serving as a mediator and chatbot conversation style (warm vs. competent) as a moderator. Findings Consumers are more engaged with self-transcendence brands when human agents are used, compared to chatbots. In contrast, for self-enhancement brands, agent types (human vs. chatbot) do not significantly impact engagement. Notably, perceived fit mediates the interaction effect on engagement for self-transcendence brands. Additionally, a warm (rather than competent) conversation style in chatbots enhances consumers' willingness to engage with self-transcendence brands. Originality/value This study advances interactive marketing research by proposing a new perspective of brand concepts to explore how to enhance consumer engagement with chatbots. It extends knowledge on brand management and AI-enabled marketing by deepening the understanding of brand–AI congruence, thereby offering a novel perspective to academic research for interactive marketing.

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https://doi.org/https://doi.org/10.1108/jrim-05-2025-0280

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@article{yuanyuan2026,
  title        = {{Chatbots as brand agents: how brand concepts shape consumer engagement}},
  author       = {Yuanyuan Cai et al.},
  journal      = {Journal of Research in Interactive Marketing},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/jrim-05-2025-0280},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.