Abstract :

The Emergence Of Industry 5.0 Represents A Paradigm Shift From Technology-centric Industrial Systems Toward Human-centric, Sustainable, And Resilient Manufacturing And Logistics Ecosystems. While Industry 4.0 Focused Primarily On Automation, Connectivity, And Data-driven Operations, Industry 5.0 Emphasizes Collaboration Between Humans And Intelligent Technologies To Create Value Through Enhanced Flexibility, Sustainability, And Resilience. Intelligent Logistics Has Become A Critical Enabler Of This Transformation By Integrating Artificial Intelligence (AI), Internet Of Things (IoT), Digital Twins, Collaborative Robots (cobots), Blockchain, Autonomous Vehicles, And Advanced Analytics Into Supply Chain Operations. This Paper Presents A Systematic Review And Conceptual Analysis Of Industry 5.0-driven Intelligent Logistics And Its Implications For Supply Chain Transformation. A PRISMA-based Review Methodology Was Employed To Analyze Recent Literature Published Between 2018 And 2026 From Leading Scopus And Web Of Science Indexed Journals. The Findings Indicate That Human-centric Automation Improves Operational Efficiency, Decision-making Quality, Supply Chain Visibility, And Sustainability Performance While Maintaining The Essential Role Of Human Expertise. The Study Identifies Key Challenges Including Cybersecurity Risks, Interoperability Issues, Workforce Skill Gaps, Ethical Concerns, And Investment Barriers. Furthermore, A Comprehensive Conceptual Framework Is Proposed To Illustrate The Relationship Between Industry 5.0 Technologies, Intelligent Logistics Capabilities, And Supply Chain Outcomes. The Paper Contributes To Existing Knowledge By Synthesizing Fragmented Research Streams And Proposing Future Research Directions Focused On Human-AI Collaboration, Sustainable Logistics, Digital Resilience, And Intelligent Decision Support Systems. The Findings Provide Valuable Insights For Academics, Policymakers, And Practitioners Seeking To Implement Industry 5.0 Principles In Logistics And Supply Chain Management

Published:

20-12-2024

Issue:

Vol. 24 No. 12 (2024)

Page Nos:

287-296

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite