Retail footprints and consumer voices: Sentiment analysis on decarbonisation, sustainability, and waste in online and offline shopping
小売りのフットプリントと消費者の声:オンラインとオフラインでの脱炭素、持続可能性、廃棄物に関する感情分析 (AI 翻訳)
Salil Seth, Mohd Irfan Pathan, Lokesh Tomar
🤖 gxceed AI 要約
日本語
本論文は、BERTモデルを用いて消費者のレビューやSNS投稿から、小売業における脱炭素・持続可能性・廃棄物管理に対する感情を分析する。オフラインでは廃棄物管理への批判が強い一方、オンラインでは脱炭素と持続可能性への肯定的な感情が高い。グリーンウォッシュや過剰な廃棄物戦略は否定的感情を引き起こすが、透明なコミュニケーションと消費者参加は肯定的感情を生む。小売業のエコ中心主義への示唆を与える。
English
This paper applies the BERT model to analyze consumer reviews and social media posts for sentiments on decarbonization, sustainability, and waste management in retail. Offline shoppers are more critical of waste practices, while online shoppers show higher positivity on sustainability and decarbonization. Greenwashing and excessive waste strategies trigger negative sentiments, whereas transparent communication and consumer engagement foster positive ones. The study offers actionable insights for eco-centric retail practices.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本ではSSBJ基準やサステナビリティ情報開示が進む中、小売業の消費者の声をAIで分析する本手法は、企業のグリーンウォッシュ懸念への対応やESGコミュニケーションの改善に役立つ。特にオンライン・オフラインの違いは日本企業のチャネル戦略に示唆を与える。
In the global GX context
Globally, with ISSB and CSRD requiring more detailed sustainability reporting, sentiment analysis of consumer perceptions offers a new data source for companies to validate their decarbonization claims and avoid greenwashing. The online-offline comparison is relevant for omnichannel retailers worldwide.
👥 読者別の含意
🔬研究者:Demonstrates BERT-based sentiment analysis for retail sustainability research, offering a replicable methodology for ESG text analytics.
🏢実務担当者:Retailers can use these insights to align online and offline sustainability communications and address consumer concerns about greenwashing.
🏛政策担当者:Policymakers can use the findings to understand consumer reactions to waste management and decarbonization efforts, informing future regulations on green marketing.
📄 Abstract(原文)
With climate change drawing global attention, grounded conceptualization about consumer perceptions of waste management, sustainability, and decarbonization in the retail sector becomes paramount. Also, the retail sector, comprising both online and offline counterparts, plays a crucial role in shaping ecological outcomes through its decarbonization tactics, waste minimization regimes, and sustainable practices. The objective of this paper is to decode consumer reviews (voices) for tracing retail carbon footprints in terms of decarbonization efforts, waste management practices, and sustainability principles by performing sentiment analysis using the Bidirectional Encoder Representations from Transformers (BERT) model for examining sentiment polarity. The consumer-generated content from social media posts and customer reviews on the review page of websites was analyzed. The sentiments were classified as positive, neutral, and negative after collecting the data, pre-processing it, and its subsequent analysis. The deep contextual embeddings of BERT have established themselves as an accurate tool for capturing the nuanced expressions about sustainability initiatives and retail practices. The results of the study reveal significant variations in the consumer sentiments between their online and offline shopping experiences. In offline contexts, waste management practices garner critical attention, whereas in online mode, both sustainability and decarbonization witness higher sentiment positivity. The findings also underscore that perceived greenwashing and superfluous waste management strategies trigger negative perceptions, whereas visible green practices, transparent communication, and consumer engagement evoke positive sentiments. Via integration of sentiment analytics and ecological impact themes, this paper heralds’ actionable insights for social advocacy of environmentalism and imbibitions of eco-centrism in the retail sector at large.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.65453/ajbmr.153.1514first seen 2026-07-02 07:45:27
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