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TRUVACE RECORD VERSION
record: TRV-2026-2646
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T16:56:21.826992Z
status: published
lens: p_space
sector: business
headline: Are AI Recommendations Less Green? The Effects of AI Recommendation Sources and Green Product Attribute Framing on Consumer Responses
dek: 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…
gain_title: (none)
problem_title: 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.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: 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.
problem_evidence: substitute (augmented) AI recommendations are more effective for utility‐framed (sustainability‐framed) green products
quick_read: Researchers ran four scenario-based online experiments with 1,114 participants in total to test when AI recommendations help promote green products. They compared substitute AI with augmented AI and utility-based with sustainability-based product framing.

The recommendation source and the framing worked as a match. Substitute AI recommendations worked better for utility-framed green products, and augmented AI recommendations worked better for sustainability-framed ones.

Consumers' sense of control helped explain the pattern. Attribute-based explanations after the recommendation removed substitute AI's disadvantage under sustainability framing, which the authors say businesses could use to raise the market share of green products.
limitation: The findings come from scenario-based online experiments rather than observed purchases in real shopping settings.
tag: Evidence-backed problem
key_points: The research used four scenario-based online experiments with 1,114 participants in total. | The experiments included one product choice task, one preference evaluation, and two studies measuring purchase intention and willingness to pay. | Substitute AI recommendations were more effective for utility-framed green products. | Augmented AI recommendations were more effective for sustainability-framed green products. | Consumers' sense of control mediated the match between AI source and framing. | Attribute-based post hoc explanations eliminated substitute AI's disadvantage under sustainability framing.
rundown: Earlier research gave mixed evidence on whether AI recommendations promote green products. This study, drawing on Self-Determination Theory, tested whether the answer depends on the AI's role and on how the green product is framed.

Participants completed a product choice task, a preference evaluation, and two studies measuring purchase intention and willingness to pay. Together these covered 1,114 people. Substitute and augmented AI recommendations were compared across utility-based and sustainability-based framings.

The effect ran through consumers' sense of control. Giving attribute-based explanations after the recommendation shifted responses toward sustainability-framed green products when substitute AI made the recommendation.
sources:
- peer_reviewed | Journal of Consumer Behaviour | https://doi.org/10.1002/cb.70253 | 2026-10-13
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