A digital resilience hierarchy: orchestrating Industry 4.0 technologies in manufacturing

Purpose This paper examines how Industry 4.0 technologies contribute to organizational resilience through hierarchical digital orchestration. Specifically, it investigates how blockchain and IIoT function as foundational digital resources that enable the effective utilization of machine vision, robotics, and AI, and how these technologies collectively strengthen a firm's risk management infrastructure and resilience. Design/methodology/approach Drawing on resource orchestration theory as a theoretical lens, this study develops a Digital Resilience Hierarchy (DRH) that distinguishes between a digital veracity layer and a cognitive–physical layer. The proposed relationships are tested using structural equation modeling with survey data from 361 U.S. manufacturing firms. Findings The results provide strong support for the DRH. Blockchain and IIoT act as foundational enablers that facilitate the utilization of machine vision, robotics, and AI. These cognitive–physical technologies strengthen a firm's risk management infrastructure, which in turn enhances firm resilience. In addition, machine vision and AI exhibit direct positive effects on resilience, while robotics contributes primarily through risk management infrastructure. Research limitations/implications The study is based on cross-sectional survey data from U.S. manufacturing firms. Future research could employ longitudinal designs or examine other industries and emerging digital paradigms to further assess how digital orchestration shapes resilience over time. Practical implications The findings suggest that resilience benefits depend on integrated and aligned digital investment strategies. Managers should prioritize foundational digital technologies, such as blockchain and IIoT, that enable higher-order applications and support the development of robust risk management infrastructure. Originality/value This study advances manufacturing technology management theory by introducing and empirically testing the DRH, offering a systems-based explanation of how Industry 4.0 technologies collectively generate organizational resilience through differentiated and interdependent pathways.

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Publication Details

Journal
Journal of Manufacturing Technology Management
Published
2026-09-26
DOI
https://doi.org/10.1108/jmtm-01-2026-0091
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
0.00
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article

A digital resilience hierarchy: orchestrating Industry 4.0 technologies in manufacturing

Liu Yang, Pamela J. Zelbst, Gerald Kohers, Sandra Buzón
Journal of Manufacturing Technology Management
Supply Chain Resilience and Risk Management
article

A digital resilience hierarchy: orchestrating Industry 4.0 technologies in manufacturing

Liu Yang, Pamela J. Zelbst, Gerald Kohers, Sandra Buzón
article en

Abstract

Purpose This paper examines how Industry 4.0 technologies contribute to organizational resilience through hierarchical digital orchestration. Specifically, it investigates how blockchain and IIoT function as foundational digital resources that enable the effective utilization of machine vision, robotics, and AI, and how these technologies collectively strengthen a firm's risk management infrastructure and resilience. Design/methodology/approach Drawing on resource orchestration theory as a theoretical lens, this study develops a Digital Resilience Hierarchy (DRH) that distinguishes between a digital veracity layer and a cognitive–physical layer. The proposed relationships are tested using structural equation modeling with survey data from 361 U.S. manufacturing firms. Findings The results provide strong support for the DRH. Blockchain and IIoT act as foundational enablers that facilitate the utilization of machine vision, robotics, and AI. These cognitive–physical technologies strengthen a firm's risk management infrastructure, which in turn enhances firm resilience. In addition, machine vision and AI exhibit direct positive effects on resilience, while robotics contributes primarily through risk management infrastructure. Research limitations/implications The study is based on cross-sectional survey data from U.S. manufacturing firms. Future research could employ longitudinal designs or examine other industries and emerging digital paradigms to further assess how digital orchestration shapes resilience over time. Practical implications The findings suggest that resilience benefits depend on integrated and aligned digital investment strategies. Managers should prioritize foundational digital technologies, such as blockchain and IIoT, that enable higher-order applications and support the development of robust risk management infrastructure. Originality/value This study advances manufacturing technology management theory by introducing and empirically testing the DRH, offering a systems-based explanation of how Industry 4.0 technologies collectively generate organizational resilience through differentiated and interdependent pathways.

Journal of Manufacturing Technology Management
Sam Houston State University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 7%
Supply Chain Resilience and Risk Management
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