Data di Pubblicazione:
2024
Abstract:
The fashion industry accounts for a relevant portion of the environmental impact of EU consumption. Moreover, the expansion of fast fashion raises further concerns about the well-being of the people and animals involved in its production. Increasing the purchase of green clothes (i.e., sustainable garments that have been produced by brands conforming to good ethical standards) is thus key to the reduction of fashion’s environmental and social footprint. In this paper, we investigate digital nudges to promote the selection of green clothes in online catalogs. For this purpose, we propose a recommender system that combines the personalized suggestion of new and second-hand garments with the presentation of sustainability and ethical standards data to favor item comparison and support responsible selection decisions. This is different from standard recommender systems, which suggest homogeneous products, either new or second-hand. Moreover, it is challenged by the bias toward buying new products that is observed in the literature about clothing consumption. In a user study involving 251 participants, we found that enhancing clothes recommendations with (i) sentences that promote second-hand garments and (ii) visual labels that summarize items’ sustainability and brands’ ethical standards, sensibly reduced this bias. Moreover, it induced some people to take the sustainability of products into account in their selection decisions. However, participants’ interest in brands’ ethical standards seemed to be secondary, especially regarding respect for animals. This finding reveals a need to enhance people’s awareness and sensitivity on this topic. Even though more work is needed to increase green, and especially ethical fashion consumption, our findings suggest the adoption of nudges in clothes recommender systems to enhance user awareness about items, their sustainability, and their social impact.
Tipologia CRIS:
03A-Articolo su Rivista
Keywords:
Clothing; Digital nudging; Ethics; Green products; Image color analysis; Recommender systems; recommender systems; Standards; Sustainable development; sustainable fashion consumption
Elenco autori:
Geninatti Cossatin A.; Mauro N.; Ardissono L.
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