<p>Digital twins have emerged as a transformative paradigm within Industry 4.0, enabling real-time monitoring, predictive analytics, and data-driven decision-making across diverse sectors. Yet, fragmented conceptualizations and inconsistent implementations continue to constrain their scalability and effectiveness. To address this, the present study proposes a unified, theory-driven framework for digital twin development that incorporates both technical and non-technical dimensions. We conducted a systematic literature review of 56 peer-reviewed articles published between 2016 and 2022, applying Strauss and Corbin’s grounded theory methodology and using NVivo software for qualitative analysis. Six core categories were identified: technological, organizational, managerial, process-related, environmental, and strategic factors. Together, these categories constitute the foundation of the proposed framework. Our findings indicate that the absence of unified models and definitional consensus remains a critical barrier to widespread adoption. The proposed model helps overcome this limitation by offering an adaptable structure to support strategic planning, operational optimization, and policy simulation in virtual environments. The unique contribution of this study lies in advancing a comprehensive, grounded theory–based framework that integrates cross-disciplinary factors and reduces the fragmentation prevalent in the existing digital twin literature.</p>