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Utilising Artificial Intelligence to Enhance Firm Circular Economy Maturity: A Thematic Review via Machine Learning

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  • Donghao Huang
  • Yuanzhu Zhan
  • Chris Lonsdale

Abstract

Despite the environmental imperative of a transition to a circular economy (CE), the current literature finds that globally firms are being slow to engage with such a transition. In this context, our thematic review explores how artificial intelligence (AI) might accelerate firm CE transition. In a departure from the dominant approach that adopts the product life cycle as the unit of analysis, the authors contribute to the literature by framing the potential of AI in terms of how it might accelerate greater CE maturity on the part of firms. A maturity model is advanced, identifying four stages of firm CE maturity, and then, different AI techniques are applied to each of the stages, providing guidance to adopting the correct AI technique for each stage in the maturity journey. The paper makes a further contribution to the literature by utilising a novel literature review method, whereby the authors themselves utilise AI in the form of a machine learning algorithm that optimises manual classification outcomes. This method provides greater objectivity to a review of 601 papers and reveals its future research potential.

Suggested Citation

  • Donghao Huang & Yuanzhu Zhan & Chris Lonsdale, 2025. "Utilising Artificial Intelligence to Enhance Firm Circular Economy Maturity: A Thematic Review via Machine Learning," Business Strategy and the Environment, Wiley Blackwell, vol. 34(5), pages 6135-6158, July.
  • Handle: RePEc:bla:bstrat:v:34:y:2025:i:5:p:6135-6158
    DOI: 10.1002/bse.4291
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