Artificial intelligence-driven supply chain resilience in Vietnamese manufacturing small- and medium-sized enterprises

Prasanta Dey, Soumyadeb Chowdhury, Amelie Abadie, Emilia Vann Yaroson, Sobhan Sarkar

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


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. To bridge these gaps, we integrate resource orchestration and knowledge-based view theoretical perspectives to develop a novel structural model examining antecedents to SCR and AI adoption, considering AI adoption as a pivot for facilitating SCR. The structural equation modelling technique was employed on the data collected from 280 Vietnamese manufacturing SMEs’ operations managers. Our results demonstrate that leadership will drive AI adoption by creating a data-driven, digital and conducive culture, and strengthening employee skills and competencies. Furthermore, AI adoption positively influences CE practices, SC agility and risk management, which will help to achieve SCR. For managers, the importance of internal organisational employee-centric mechanisms to create value from AI adoption without impeding business value is highlighted. We reveal the enablers that will help in transforming SMEs to become resilient by deriving appropriate responses to unprecedented disruptions through data-driven decision-making leveraging AI adoption.

Original languageEnglish
JournalInternational Journal of Production Research
Early online date23 Mar 2023
Publication statusE-pub ahead of print - 23 Mar 2023


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