Management 4.0 in Smart Manufacturing: A Systematic Review, Gap Analysis, and Future Roadmap
DOI:
https://doi.org/10.55578/isgm.2605.006Keywords:
Management 4.0,, Smart Manufacturing, Industry 4.0, Digital Transformation, Artificial Intelligence, Corporate Governance, Organizational TransformationAbstract
Management 4.0, driven by digital transformation and Industry 4.0 technologies, is reshaping organizational structures, managerial paradigms, and value creation mechanisms in smart manufacturing systems. Enabled by the convergence of artificial intelligence, cyber-physical systems, advanced analytics, and interconnected digital infrastructures, manufacturing organizations are increasingly transitioning toward adaptive, autonomous, and data-driven management models that transform decision-making, coordination, and operational governance.
Despite growing scholarly attention, the Management 4.0 domain remains fragmented and under-theorized. Existing literature exhibits limited conceptual integration, inconsistent empirical validation, and a lack of scalable implementation frameworks. In particular, the socio-technical complexity of integrating intelligent systems with human decision-making across organizational transformation, workforce evolution, governance redesign, and sustainability (including ESG integration) remains insufficiently addressed.
To address these gaps, this study conducts a systematic review of more than 200 peer-reviewed publications (2011-2026), supported by structured gap analysis. Grounded in socio-technical systems theory and the dynamic capabilities perspective, it reframes Management 4.0 as an integrated organizational transformation paradigm rather than a set of isolated digital initiatives.
The synthesis develops a consolidated conceptual framework structured into four interdependent capability domains: technological infrastructure, organizational architecture, managerial and leadership capabilities, and governance systems. Three critical gaps are identified: absence of a unified theoretical foundation, limited empirical validation of transformation pathways, and insufficient understanding of human-AI socio-technical integration in smart manufacturing contexts.
Finally, a ten-step implementation roadmap is proposed, encompassing digital maturity assessment, strategic alignment, digital architecture design, capability development, process reengineering, governance and ethics, innovation and risk management, customer-centric transformation, performance measurement, and knowledge management integration.
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