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International Journal of Science, Strategic Management and Technology

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A STUDY ON OPTIMIZING END-TO-END SUPPLY CHAIN OPERATIONS THROUGH DIGITAL TRANSFORMATION AND INDUSTRY 4.0 TECHNOLOGIES

AUTHORS:
Dhanush J
Mentor
Dr. S. Bharathi
Affiliation
II MBA, Dhanalakshmi Srinivasan University, Tiruchirappalli,Tamil Nadu-621112.
DOI: 10.55041/ijsmt.v2i5.484
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract

The global supply chain landscape is undergoing a profound transformation driven by digital technologies and Industry 4.0 innovations such as the Internet of Things (IoT), Artificial Intelligence (AI), Big Data analytics, Blockchain, and Cloud Computing. This research paper examines how digital transformation optimizes end-to-end supply chain operations by enhancing visibility, agility, cost-efficiency, and resilience. The study investigates the effect of digital and automation technologies on key supply chain performance metrics including lead time, operational cost, and service quality.


A descriptive and analytical research design has been adopted, using secondary data sourced from industry reports, peer-reviewed journals, and case studies covering the years 2020 to 2025. Analytical tools such as trend analysis, correlation analysis, and regression analysis are applied to determine the relationship between digital adoption level and supply chain performance outcomes.


Keywords: Supply Chain Optimization, Digital Transformation, Industry 4.0, IoT, AI, Blockchain, Automation, Smart Manufacturing, Logistics Efficiency, Predictive Analytics, Supply Chain Resilience.

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Article Information
PUBLICATION DETAILS
Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 05
Review Rounds:
2
Article Type:
Research Article
Publication Date:
May 29 2026
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J, D. (2026). A Study on Optimizing End-To-End Supply Chain Operations Through Digital Transformation and Industry 4.0 Technologies. International Journal of Science, Strategic Management and Technology, 02(05). https://doi.org/10.55041/ijsmt.v2i5.484

J, Dhanush. "A Study on Optimizing End-To-End Supply Chain Operations Through Digital Transformation and Industry 4.0 Technologies." International Journal of Science, Strategic Management and Technology, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i5.484.

J, Dhanush. "A Study on Optimizing End-To-End Supply Chain Operations Through Digital Transformation and Industry 4.0 Technologies." International Journal of Science, Strategic Management and Technology 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i5.484.

References
1.Bharathi, S., Kalaiselvan, R., & Vanhaltren, C. J. (2024). Measuring training effectiveness: A systematic literature review. International Journal of Cultural Studies and Social Science, 20(2), 162.

2.Christopher, M. (2016). Logistics and Supply Chain Management (5th ed.). Pearson Education.

3.Porter, M. E., & Heppelmann, J. E. (2017). "Why Every Organization Needs an Augmented Digital Strategy." Harvard Business Review.

4.Kamble, S. S., Gunasekaran, A., & Sharma, R. (2020). “Modeling the Impact of Industry 4.0 on Supply Chain Sustainability.” Resources, Conservation and Recycling, 153, 104 - 559.

5.(2020). The Digital Supply Network Playbook: Building Intelligent Supply Chains in the Age of Data.

6.McKinsey & Co. (2021). Digital Transformation in Operations: Unlocking $1.5 Trillion in Supply Chain Value.

7.Bharathi, S., & Dhanush, J. (2026). Modes of transport - Road, rail, air, sea & multimodal. In Logistics and Supply Chain Management (p. 15).

8.Ivanov, D., & Dolgui, A. (2020). “A Digital Supply Chain Twin for Resilient Planning.” International Journal of Production Research, 58(16), 4860–4870.

9.Kagermann, H., Wahlster, W., & Helbig, J. (2013). Recommendations for Implementing Industry 4.0. Acatech Report.

10.Waller, M. A., & Fawcett, S. E. (2013). “Data Science, Predictive Analytics, and Big Data: A Revolution for Supply Chain Design and Management.” Journal of Business Logistics, 34(2), 77–84.
Ethics and Compliance
✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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