Enabling supply chain viability through digital transformation: Analysis of barriers in Industry 4.0 context
Abstract
The rapidly evolving digital economy is reshaping global value chains and creating new data driven models that improves resilience, viability and sustainability of supply chains. The adoption of Industry 4.0 (I4.0) technologies help in digital transformation and creates new opportunities in developing economies to improve their competitiveness, strength, and environmental performance. However, their adoption remains limited due to barriers (infrastructural, skills, finance) and contextual challenges such as regulatory gaps and institutional readiness. In line with these insights, the present study builds on the key issues that undermine the sustainability of supply chains in an I4.0 environment, particularly in less developed economies where the implementation of digital technologies remains limited. An Interpretive structural modelling approach (ISM) with Decision making trial and evaluation laboratory (DEMATEL) is used to identify the hierarchical structure and inter-relationship among the barriers. The findings show that workforce adaptation, high initial capital investment, digital adoption and integration are important barriers. These results are consistent with broader digital transformation literature, as they suggest that the potential of I4.0 can be unlocked through targeted investments in human capital, infrastructure and policy support. The study provides the strategic guidance for practitioners and policymakers on how to improve the use of digital technologies and promote sustainable supply chain development in a more inclusive digital environment. The study also explains about the causal interrelationship among the barriers in emerging economies. Based on the discussion the study provides few actionable insights for decision makers to prioritize investments in skills, digital infrastructure and regulatory facilitation to make supply chain more resilient and sustainable in the long term.
Fields of Study & Subjects
Digital Transformation in Industry
Big Data and Business Intelligence
Quality and Supply Management
Publication details
- Journal / source
- Journal of Digital Economy
- Publisher
- Elsevier BV
- Volume
- 5
- Pages
- 31–48
- Publication date
- 1 January 2026
- Language
- EN