A readiness-based benchmarking framework for digital twin adoption for sustainability in the RMG sector

Purpose This study proposes a readiness benchmarking model for digital twin (DT) adoption in the ready-made garments (RMG) sector of emerging economies and analyzes its implications for sustainability. Design/methodology/approach This study uses the Delphi method and a proposed nominal group technique (NGT)-spherical fuzzy DEMATEL framework to analyze and reveal the causal relationship among the factors. Later, sensitivity and comparative analyses were conducted to assess the robustness of the analysis. Findings 22 influencing factors were identified from the existing literature and expert feedback, and 17 were finalized for analysis using the Delphi method. Among the 17 factors, “long-term sustainability planning” and “DT literacy” have the greatest influence. In contrast, “top management's readiness and support” and “collaboration with research institutions” are the top causes. Sensitivity analysis showed little or no variation across scenarios. Practical implications This cause-and-effect analysis could provide policymakers with a robust, reliable tool to address these influencing factors and inform strategy formulation in the context of technology adoption. Organizations can prioritize and analyze their areas for improvement and identify the critical factors when adopting costly, entirely new technology for business success. Moreover, this proactive approach could significantly reduce resource waste, downtime and challenges in implementing advanced technology. Originality/value Delphi integrated NGT-Spherical Fuzzy DEMATEL is a novel cause–effect analysis model that handles data uncertainty and ambiguity by capturing both fuzziness and hesitancy, while maintaining simplicity and robustness. This study's originality lies in the new paradigm of factor analysis for the digital twin adoption in the RMG sector of emerging economies.