Advancing vendor management models to maximize economic value in global supply chains
1 Independent Researcher, TX, USA.
2 Bowling Green State University, Ohio USA.
3 Independent Researcher, USA.
4 Independent Researcher, UK.
5 Independent Researcher, Canada.
Review
International Journal of Frontline Research in Science and Technology, 2023, 02(02), 042–050.
Article DOI: 10.56355/ijfrst.2023.2.2.0057
Publication history:
Received on 16 October 2023; revised on 29 November 2023; accepted on 02 December 2023
Abstract:
Effective vendor management is critical to successful global supply chains, significantly contributing to cost savings, quality enhancement, and operational efficiency. This paper explores the theoretical foundations of vendor management, identifies challenges and opportunities within global supply chains, and examines innovative strategies to enhance vendor management practices. Reviewing existing models and theoretical frameworks, we emphasize the importance of strategic alignment, collaboration, and transparency between businesses and their vendors. We discuss the major challenges such as geopolitical risks, cultural differences, and logistical complexities, while highlighting the transformative potential of technology and globalization. Advanced techniques such as multi-criteria decision analysis (MCDA), vendor scorecards, and e-sourcing platforms, coupled with supplier development programs, are presented as effective tools for vendor evaluation and relationship building. The integration of data analytics, artificial intelligence (AI), blockchain, and cloud-based solutions is underscored for optimizing vendor management processes. Finally, practical recommendations are provided to help businesses maximize economic value through strategic and technologically-driven vendor management practices, fostering stronger partnerships and ensuring sustainability.
Keywords:
Vendor Management; Global Supply Chains; Multi-Criteria Decision Analysis (MCDA); Data Analytics; Blockchain Technology; Supplier Development Programs
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0