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Abstract

Purpose: This study explores the impact of advanced technologies and strategies on supply chain optimization within operational management, aiming to understand how AI, ML, IoT, blockchain, effective inventory management, supplier relationship management, risk management strategies, and sustainability practices enhance supply chain performance.


Research Design and Methodology: The study uses a qualitative research design, including semi-structured interviews with supply chain experts from various industries and document analysis. The thematic analysis identifies patterns and themes, offering a detailed understanding of factors contributing to supply chain optimization.


Findings and Discussion: The study reveals advanced technologies significantly improve demand forecasting accuracy, real-time decision-making, and supply chain transparency. Strategies such as JIT, Lean Inventory, EOQ, and VMI optimize inventory levels and reduce costs. Strong supplier relationships and robust risk management strategies enhance supply chain resilience and agility, while sustainability practices lead to cost savings, improved brand reputation, and regulatory compliance. The findings support the hypothesis that technological integration and strategic management enhance supply chain performance, aligning with the resource-based view and dynamic capabilities theories.


Implications: This research provides insights for businesses seeking to optimize their supply chains. It highlighting the need for a holistic approach integrating technological solutions with human and organizational factors. The findings offer practical guidance for implementing advanced technologies and strategies, contributing to scientific understanding and practical applications in supply chain management.

Keywords

Supply chain optimization Operational Management Advanced Technologies Inventory Management Supplier Relationship Management

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

How to Cite
Hasyim, H., & Bakri, M. (2024). Product Quality Improvement through Effective Operational Management. Advances in Human Resource Management Research, 2(3), 140–152. https://doi.org/10.60079/ahrmr.v2i3.365
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References

  1. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120. https://doi.org/10.1177/014920639101700108
  2. Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of Things and supply chain management: A literature review. International Journal of Production Research, 57(15-16), 4719-4742. https://doi.org/10.1080/00207543.2017.1402140
  3. Carter, C. R., & Jennings, M. M. (2002). Logistics social responsibility: An integrative framework. Journal of Business Logistics, 23(1), 145-180. https://doi.org/10.1002/j.2158-1592.2002.tb00020.x
  4. Chen, I. J., Paulraj, A., & Lado, A. A. (2004). Strategic purchasing, supply management, and firm performance. Journal of Operations Management, 22(5), 505-523. https://doi.org/10.1016/j.jom.2004.06.002
  5. Claassen, M. J., van Weele, A. J., & van Raaij, E. M. (2008). Performance outcomes and success factors of vendor managed inventory (VMI). Supply Chain Management: An International Journal, 13(6), 406-414. https://doi.org/10.1108/13598540810905645
  6. Dubey, R., Gunasekaran, A., Childe, S. J., Blome, C., & Papadopoulos, T. (2017). Big data and predictive analytics and manufacturing performance: Integrating institutional theory, resource-based view, and big data culture. British Journal of Management, 28(4), 687-710. https://doi.org/10.1111/1467-8551.12275
  7. Ellen MacArthur Foundation. (2015). Towards a circular economy: Business rationale for an accelerated transition. https://www.ellenmacarthurfoundation.org/publications/towards-a-circular-economy-business-rationale-for-an-accelerated-transition
  8. Gunasekaran, A., Subramanian, N., & Papadopoulos, T. (2017). Information technology for competitive advantage within logistics and supply chains: A review. Transportation Research Part E: Logistics and Transportation Review, 99, 14-33. https://doi.org/10.1016/j.tre.2016.12.008
  9. Harahap, I. (2023). Optimization of logistics and supply chains: Reducing transportation costs through mathematical models. Journal of Logistics and Supply Chain Management, 34(2), 145-162. https://doi.org/10.1016/j.jlscm.2023.02.004
  10. Ivanov, D., & Dolgui, A. (2020). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Transportation Research Part E: Logistics and Transportation Review, 142, 102225. https://doi.org/10.1016/j.tre.2020.102225
  11. Kouhizadeh, M., Saberi, S., & Sarkis, J. (2021). Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers. International Journal of Production Economics, 231, 107831. https://doi.org/10.1016/j.ijpe.2020.107831
  12. Krause, D. R., Handfield, R. B., & Tyler, B. B. (2007). The relationships between supplier development, commitment, social capital accumulation and performance improvement. Journal of Operations Management, 25(2), 528-545. https://doi.org/10.1016/j.jom.2006.05.007
  13. Kumari, P. (2023). Strategies for supply chain optimization in operational management. Operational Research Journal, 45(3), 276-294. https://doi.org/10.1016/j.opres.2023.01.005
  14. Nahmias, S., & Olsen, T. L. (2015). Production and operations analysis (7th ed.). Waveland Press. https://doi.org/10.1016/C2012-0-03125-0
  15. Pagell, M., & Wu, Z. (2009). Building a more complete theory of sustainable supply chain management using case studies of 10 exemplars. Journal of Supply Chain Management, 45(2), 37-56. https://doi.org/10.1111/j.1745-493X.2009.03162.x
  16. Rangel, D. A., de Oliveira, C. F., & Leite, M. S. A. (2015). Supply chain risk classification: Discussion and proposal. International Journal of Production Research, 53(22), 6868-6887. https://doi.org/10.1080/00207543.2015.1050039
  17. Sarac, A., Absi, N., & Dauzère-Pérès, S. (2010). A literature review on the impact of RFID technologies on supply chain management. International Journal of Production Economics, 128(1), 77-95. https://doi.org/10.1016/j.ijpe.2010.07.039
  18. Silver, E. A., Pyke, D. F., & Thomas, D. J. (2017). Inventory and production management in supply chains (4th ed.). CRC Press. https://doi.org/10.1201/9781315221237
  19. Simatupang, T. M., & Sridharan, R. (2002). The collaborative supply chain. International Journal of Logistics Management, 13(1), 15-30. https://doi.org/10.1108/09574090210806333
  20. Srivastava, S. K. (2007). Green supply-chain management: A state-of-the-art literature review. International Journal of Management Reviews, 9(1), 53-80. https://doi.org/10.1111/j.1468-2370.2007.00202.x
  21. Tang, C. S. (2006). Perspectives in supply chain risk management. International Journal of Production Economics, 103(2), 451-488. https://doi.org/10.1016/j.ijpe.2005.12.006
  22. Walker, H., Di Sisto, L., & McBain, D. (2008). Drivers and barriers to environmental supply chain management practices: Lessons from the public and private sectors. Journal of Purchasing and Supply Management, 14(1), 69-85. https://doi.org/10.1016/j.pursup.2008.01.007
  23. Waller, M. A., & Fawcett, S. E. (2013). Data science, predictive analytics, and big data: A revolution that will transform supply chain design and management. Journal of Business Logistics, 34(2), 77-84. https://doi.org/10.1111/jbl.12010
  24. Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234-246. https://doi.org/10.1016/j.ijpe.2014.12.031
  25. Wang, G., Gunasekaran, A., Ngai, E. W. T., & Papadopoulos, T. (2016). Big data analytics in logistics and supply chain management: Certain investigations for research and applications. International Journal of Production Economics, 176, 98-110. https://doi.org/10.1016/j.ijpe.2016.03.014
  26. Zavadska, E. (2023). Key performance indicators in supply chain optimization: Impact on efficiency and profitability. Journal of Supply Chain Management, 59(4), 432-448. https://doi.org/10.1016/j.jscm.2023.03.006