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Are AI Recommendations Less Green? The Effects of AI Recommendation Sources and Green Product Attribute Framing on Consumer Responses
- Truvace record
- TRV-2026-2646raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Controlled or validated comparison
- Sources
- 1 sourcePeer-reviewed
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ABSTRACT Extant research has reported mixed evidence regarding the effectiveness of artificial intelligence (AI) recommendations in promoting green products, leaving it unclear under which conditions such recommendations are more (or less) effective. Drawing on Self‐Determination Theory (SDT), this research addresses this ambiguity by proposing a congruence effect between AI recommendation sources (substitute versus augmented AI) and green product attribute framing (utility‐based versus sustainability‐based). Us…
The problem
In four online experiments with 1,114 participants, substitute AI recommendations were less effective than augmented AI recommendations for sustainability-framed green products, and more effective only for utility-framed ones.
What this doesn’t fix
The findings come from scenario-based online experiments rather than observed purchases in real shopping settings.
Sources
1 on file- Journal of Consumer Behaviourdoi:10.1002/cb.70253
Cite this record
v1Truvace Impact Record TRV-2026-2646, v1: “Are AI Recommendations Less Green? The Effects of AI Recommendation Sources and Green Product Attribute Framing on Consumer Responses.” Truvace, 2026-11-12. /record/TRV-2026-2646 (accessed on the day you copy it). sha256 83a69d80041be8fb…
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