"ETHICS DO NOT OUTWEIGH TECHNICAL FAILURES": ANALYZING FRICTIONS IN RESPONSIBLE CONSUMPTION VIA GENERATIVE AI

« L'ETHIQUE NE COMPENSE PAS LE BUG »: ANALYSE DES FRICTIONS DANS LA CONSOMMATION RESPONSABLE VIA L'IA GENERATIVE

Maxime David and Bruno Cardinale ()
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Maxime David: ULH - Université Le Havre Normandie - NU - Normandie Université, NIMEC - Normandie Innovation Marché Entreprise Consommation - UNICAEN - Université de Caen Normandie - NU - Normandie Université - ULH - Université Le Havre Normandie - NU - Normandie Université - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université - IRIHS - Institut de Recherche Interdisciplinaire Homme et Société - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université
Bruno Cardinale: ULH - Université Le Havre Normandie - NU - Normandie Université, NIMEC - Normandie Innovation Marché Entreprise Consommation - UNICAEN - Université de Caen Normandie - NU - Normandie Université - ULH - Université Le Havre Normandie - NU - Normandie Université - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université - IRIHS - Institut de Recherche Interdisciplinaire Homme et Société - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université

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Abstract: Amid the rise of responsible consumption apps, the ethical promise (anti-waste, short supply chains) confronts the reality of usage. This research investigates reputational risk mechanisms in this sector through an automated analysis of 2,544 negative reviews from seven major platforms (Too Good To Go, Phenix, etc.). Employing a Generative AI classification methodology (Zero-Shot LLM), the study reveals that the primary barrier to engagement is neither financial nor moral, but technological. Technical and ergonomic frictions (>20% of complaints) act as critical factors: the failure of the tool is perceived as a breach of contract, generating a 'hot anger' that the application's general interest mission fails to mitigate. These findings call for a rethinking of digital reputational risk: technical reliability emerges as the indispensable prerequisite for the credibility of responsible discourse.

Keywords: responsible consumption; negative eWOM; technical friction; reputation risk; artificial intelligence (LLM); mobile apps; applications mobiles; intelligence artificielle (LLM); risque de réputation; friction technique; eWOM négatif; consommation responsable (search for similar items in EconPapers)
Date: 2026-05-19
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Published in 42e Congrès international de l'AFM, Association Française de Marketing, May 2026, Angers (France), France

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05777653

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