A text analytics based study of indian consumer attitudes toward adoption of sustainable products for circular economy

Abstract

The adoption of circular economy strategies is only possible through proper education among young minds. However, to build an effective education model, it is necessary to consider knowledge gaps and current consumption patterns. The best option for daily-use products, around which the consumer-response analysis can provide useful insights. Mat is such a product used in every household in India. There are two variants of the mat, one made of natural fibre and the other of plastic, available in the market and on the e-commerce platform. In the current scenario, the digital market or e-commerce platform provides an avenue to simultaneously analyse consumer comments on both natural fibre-based and plastic products. The present study deployed a natural language processing approach to analyse consumer comments. The Bidirectional Encoder Representations from Transformers (BERT)-based rating or sentiment analysis, informed by practice-based theory (PBT), indicates that the main barrier to the adoption of circular products is not a lack of environmental awareness, but the misalignment between perceived product attributes and usage practices. This necessitates integrating sustainability literacy with material awareness into the educational curriculum.