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Advancing Circular Economy Through Digital Twin Adoption, Green Finance, and Innovation: Insights From China's Industrial Sector

Tingting LiuSchool of Accounting, Guizhou University of Commerce Guiyang Guizhou ChinaQi ChengSchool of Accounting and Auditing, Jilin Business and Technology College Changchun Jilin ChinaKim Mee ChongSchool of Accounting and Finance, Faculty of Business and Law Taylor's University Lakeside Campus Subang Jaya Selangor MalaysiaAnvar AbsamatovDepartment of Economics Termez University of Economics and Service Termiz Uzbekistan
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ABSTRACT The transformation of the circular economy and environmental sustainability has become a burning issue in the emerging industrial economies. This paper investigates the impacts of digital twin adoption (DTA), green finance (GF), and green innovation capability (GIC) on circular economy practices (CEP) and sustainable enterprise performance (SEP) in Chinese manufacturing and construction companies. Based on time‐lagged survey data of 387 managers and the model being analyzed with PLS‐SEM, the results indicated that DTA, GF, and GIC have a significant positive effect on CEP, which has a significant positive effect on SEP. The relationships between strategic capabilities and sustainable performance are partially mediated by the practices of a circular economy, which shows that digital and financial investments produce better results when implemented in the context of a circular operational framework. Moreover, green transformational leadership has a positive moderating effect on the correlation between CEP and SEP, which enhances the performance impact of circular initiatives. Based on the dynamic capabilities theory and transformational leadership theory, this research explains the capability‐transformation process by which technological, financial, and leadership resources are transformed into quantifiable sustainability results. The results provide management and policy implications to accelerate sustainability‐focused industrial transformation in the emerging economies.

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