Dutta, Surjadeep, Chowdhury, Pritam, Sinha, Anindita, Biswas, Tisha and Ema, Uma Padmini ORCID: https://orcid.org/0000-0003-0780-0417 (2026) AI and MIST in Circular Economy and Resource Recovery: A Comparative Analysis of Ecommerce Industries. International Business & Economics Studies, 8 (1).

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Abstract

The rapid expansion of e-commerce has altered retail, but it has also exacerbated environmental issues such as packaging waste, product returns and product recovery, and resource depletion. This research evaluates the implementation of Artificial Intelligence (AI) and Modern Information Systems and Technologies (MIST) to achieve Circular Economy (CE) development and resource recovery in the context of e-commerce above the major e-commerce platforms of the United States, United Kingdom and Indian markets—Amazon, ASOS, IKEA Online, Big Basket, and Nykaa. This study used a quantitative research design and Power BI analysis to compare the extent to which these firms utilize AI and MIST to retrieve circularity, reduce carbon emissions, and improve operational efficiency. The findings revealed a clear relationship between high levels of AI and MIST relative to operations—such as predictive analytics, IoT-enabled tracking, blockchain transparency, and cloud-based logistics—and significant improvements in resource efficiency, waste reduction, and customer satisfaction. The e-commerce platforms with the greatest levels of CE performance were Amazon and IKEA Online platform, although emerging firms like Big Basket and Nykaa were beginning to adopt these models. In conclusion, both AI and MIST drive sustainable development, create customer trust, and increase competitive advantages, suggesting that their role in e-commerce is a key focus for digital transformation for sustainable e-commerce.

Item Type:	Article
Status:	Published
DOI:	10.22158/ibes.v8n1p45
Subjects:	H Social Sciences > HC Economic History and Conditions H Social Sciences > HF Commerce
School/Department:	London Campus
URI:	https://ray.yorksj.ac.uk/id/eprint/13941

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