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Research on Supply Chain Optimization at Amazon
- 1 Case Western Reserve University
* Author to whom correspondence should be addressed.
Abstract
In today's era of globalization and digitization, supply chain management is critical to the success of globalized companies. Amazon, one of the world's largest e-commerce platforms, has a particularly complex and important supply chain management. Despite many studies on supply chain management, there is still a lack of research on how Amazon uses operations research and data analytics to optimize its supply chain. The purpose of this paper is to explore how Amazon can improve the efficiency of its supply chain through operations research and data analytics techniques (e.g., linear programming, inventory control, and transportation modeling) to cope with increasing market demand. Through literature analysis and case studies, this paper examines in detail the optimization practices and technology applications of Amazon's supply chain management. The study uses data collected from Amazon as well as relevant academic articles and industry reports. The results of the study show that Amazon effectively uses advanced operations research models, such as linear programming, inventory control, and transportation models, to optimize various aspects of its supply chain. These models help reduce costs, manage inventory levels, and improve delivery efficiency. The analysis shows significant improvements in supply chain performance metrics, confirming Amazon's strategic use of data-driven decision-making.
Keywords
Amazon, Supply Chain Management, Operations Research, Optimization
[1]. Neubert, G., Ouzrout, Y., & Bouras, A. (2004). Collaboration and integration through information technologies in supply chains. Int. J. Technol. Manag., 28, 259-273. https://doi.org/10.1504/IJTM.2004.005065.
[2]. Themistocleous, M., Irani, Z., & Love, P. (2004). Evaluating the integration of supply chain information systems: A case study. Eur. J. Oper. Res., 159, 393-405. https://doi.org/10.1016/j.ejor.2003.08.023.
[3]. Soosay, C., & Hyland, P. (2004). Driving Innovation in Logistics: Case Studies in Distribution Centres. Wiley-Blackwell: Creativity & Innovation Management. https://doi.org/10.1111/J.1467-8691.2004.00292.X.
[4]. Wirtz, H. (2011). Innovation Networks in Logistics-Management and Competitive Advantages. International Journal of Innovation Science, 3, 177-192. https://doi.org/10.1260/1757-2223.3.4.177.
[5]. Ross, D. (2015). Managing Supply Chain Inventories. , 309-356. https://doi.org/10.1007/978-1-4899-7578-2_7.
[6]. Esper, T. (2021). Supply Chain Management Amid the Coronavirus Pandemic. Journal of Public Policy & Marketing, 40, 101 - 102. https://doi.org/10.1177/0743915620932150.
[7]. Zhu, L. (2020). Optimization and Simulation for E-Commerce Supply Chain in the Internet of Things Environment. Complex., 2020, 8821128:1-8821128:11. https://doi.org/10.1155/2020/8821128.
[8]. Beheshtinia, M., Feizollahy, P., & Fathi, M. (2021). Supply Chain Optimization Considering Sustainability Aspects. Sustainability. https://doi.org/10.3390/su132111873.
[9]. Amodeo, L., Chen, H., & Hadji, A. (2009). Multi-objective Supply Chain Optimization: An Industrial Case Study. , 732-741. https://doi.org/10.1007/978-3-540-71805-5_79.
[10]. Silva, C., Sousa, J., Runkler, T., & Costa, J. (2009). Distributed supply chain management using ant colony optimization. Eur. J. Oper. Res., 199, 349-358. https://doi.org/10.1016/j.ejor.2008.11.021.
Cite this article
Chen,Y. (2024). Research on Supply Chain Optimization at Amazon. Advances in Economics, Management and Political Sciences,105,248-252.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 3rd International Conference on Financial Technology and Business Analysis
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