AI‐Driven Circular Transformation: Unlocking Sustainable Startup Success Through Co‐Creation Dynamics in Circular Economy Ecosystems

Bang‐Ning Hwang, Pittinun Puntha and Siriprapha Jitanugoon

Sustainable Development, 2025, vol. 33, issue S1, 245-274

Abstract: This study investigates how artificial intelligence (AI) enables circular economy (CE) adoption in resource‐constrained startups through socio‐technical mechanisms of co‐creation. Grounded in dynamic capabilities theory and socio‐technical systems theory, we conceptualize AI‐driven circular transformation (AICT) as the strategic application of AI technologies to advance sustainability‐oriented innovation. Employing a mixed‐methods design, we examine how AICT enhances startup resilience and innovation via two mediators: collaborative intelligence and knowledge integration. Results from Partial Least Squares Structural Equation Modeling (PLS‐SEM), supported by qualitative insights, show that AICT indirectly improves adaptive performance and circular innovation by fostering ecosystem collaboration and organizational learning. The findings deepen understanding of how digital technologies interact with human and institutional capabilities to generate sustainable outcomes. This study offers practical guidance for startups and policymakers seeking to implement regenerative business models, with direct implications for achieving SDG 9, SDG 12, and SDG 13.

Date: 2025
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https://doi.org/10.1002/sd.70001

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Persistent link: https://EconPapers.repec.org/RePEc:wly:sustdv:v:33:y:2025:i:s1:p:245-274

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