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Bridging the digital divide: how technological symmetry and collaboration fortify supply chain resilience

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  • Vu Minh Ngo

    (University of Economics Ho Chi Minh City)

  • Huan Huu Nguyen

    (University of Economics Ho Chi Minh City)

  • Long Hoang Nguyen

    (University of Economics Ho Chi Minh City, Vinh Long Campus)

Abstract

This study investigates how digital technologies contribute to supply chain resilience (SCR) under different risk conditions, addressing the overlooked question of whether technologies perform uniformly across contexts. Specifically, we examine the role of technological capability symmetry (TCS) and digital supply chain collaboration (DSCC), the distinct affordances of Artificial Intelligence (AI), Business Information Systems (BIS), and automation, and the influence of diverse risk types, including supply, operational, financial, demand, and technological risks, on technology–resilience dynamics. Using survey data from 879 importer–exporter firms in Vietnam and analyzed through Partial Least Squares Structural Equation Modeling with Multi-Group Analysis, the results show that TCS strengthens both DSCC and SCR, with DSCC mediating this effect. Risk severity promotes technological symmetry but simultaneously reduces the effectiveness of DSCC in enhancing supply chain resilience. Across technologies, AI enhances sensing under supply and financial risks, BIS enables seizing under supply and demand volatility, and automation supports transforming regarding technological risks. These findings advance dynamic capability theory by showing that digital technologies are not interchangeable but yield differentiated resilience benefits depending on risk context. For managers, we provide a practical decision matrix that links specific risks to the digital investments most likely to strengthen resilience.

Suggested Citation

  • Vu Minh Ngo & Huan Huu Nguyen & Long Hoang Nguyen, 2026. "Bridging the digital divide: how technological symmetry and collaboration fortify supply chain resilience," Operations Management Research, Springer, vol. 19(1), pages 1-26, March.
    • Handle: RePEc:spr:opmare:v:19:y:2026:i:1:d:10.1007_s12063-025-00572-x
    DOI: 10.1007/s12063-025-00572-x
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