Digital transformation (DT) and supply chain intelligence

The gap

Evidence profile

Sourced from the abstract and inline gaps and future-work section of the source papers, classified as general, drawn from work published between 2023 and 2026, spanning 4 journals.

Supporting evidence — 4 representative gaps

• Necessary conditions for supply chain resilience and viability: the roles of digital transformation and intelligence integration in emerging markets (2026) · Business Process Management Journal · doi

  While digital transformation (DT) and supply chain intelligence integration have been recognized as important capabilities for strengthening supply chains, limited research has examined how they jointly contribute to resilience and long-term viability, or which conditions are indispensable for achieving these outcomes.

  generalabstractevidence 5/5
  Keywords: supply digital transformation chain intelligence integration recognized important capabilities strengthening chains limited examined jointly contribute
• Artificial intelligence-driven supply chain resilience in Vietnamese manufacturing small- and medium-sized enterprises (2023) · International Journal of Production Research · doi

  Despite the exponential growth of artificial intelligence (AI) research in operations, supply chain, and productions management literature, empirical insights on how organisational behavioural mechanisms at the human–technology interface will facilitate AI adoption in small- and medium-sized enterprises (SMEs), and subsequent impact of the adoption on sustainable practices and supply chain resilience (SCR) is under-researched.

  generalabstractevidence 5/5
  Keywords: supply chain adoption despite exponential growth artificial intelligence operations productions management literature empirical insights organisational
• Developing AI-enabled sustainable supply chain quality capability: Scale development, validation, and its role in enhancing supply chain resilience and performance (2026) · Radiant Journal of Business & Sustainability · doi

  By conceptualizing and validating AISSQC as a multidimensional organizational capability, the study addresses an important gap in the literature and provides a stronger explanation of how AI investments are translated into resilient and sustainable supply chain outcomes (Barney, 1991; Teece, 2007). The findings indicate that AI Capability alone is insufficient to strengthen resilience and sustainable performance; instead, organizational value emerges when AI is embedded within coordinated routines that integrate quality management, sustainability, collaboration, continuous improvement, and responsible governance.

  generalinline gapsevidence 5/5
  Keywords: organizational capability sustainable conceptualizing validating aissqc multidimensional addresses important literature provides stronger explanation investments translated
• Artificial Intelligence Applications in Supply Chain Management: A Systematic Review of Empirical Evidence and Future Research Directions (2026) · Journal of Business and Management Studies · doi

  Future research should focus on the development of more advanced AI technologies that can address the complex challenges in supply chains. Future studies should investigate the impact of AI on different types of supply chains and industries. Future research should explore the role of organizational learning and capability development in building internal competencies related to data analytics and AI management.

  generalfuture-work sectionevidence 5/5
  Keywords: future research focus development advanced technologies address complex

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