AI Powered Supplier Selection: Finding the Perfect Fit in Supply Chain Management
Lakshmi Narasimha Raju Mudunuri
Vol. 7, Issue 1, Jan-Dec 2021
Page Number: 211 - 231
Abstract:
Research experts and industry executives emphasize that competition today extends beyond individual enterprises to entire supply chains. The synergy and collaboration among supply chain members can significantly enhance the value delivered to end customers and provide a competitive edge. Such interconnections foster mutually beneficial relationships among all participants in the supply chain. Therefore, selecting the right supply chain partners, including suppliers, is crucial in supply chain management.
References
- Chen, Y., Ma, S., & Sun, L. (2019). Artificial intelligence in supply chain management: Insights from bibliometric analysis. IEEE Access, 7, 168791- 168802.
- Chen, H., Wang, S., Xiang, H., & Huang, X. (2019). Artificial Intelligence in Supply Chain Management: Insights from an Industry Study. International Journal of Production Economics, 210, 204-216.
- Giannakis, M., & Papadopoulos, T. (2016). Supply chain sustainability: A risk management approach. International Journal of Production Economics, 171, 455–470.
- Kannan, P. K., & Telang, R. (2020). AI and Supply Chain Management. Journal of Operations Management, 66(4), 353-360.
- Kocabasoglu-Hillmer, C., & Dallery, Y. (2020). Artificial Intelligence in Supply Chain Management: Insights from a Delphi Study. International Journal of Production Research, 58(6), 1651-1671.
- Kabir, M. S., Gammack, J., & Kerr, D. (2020). Artificial intelligence in supply chain management: A comprehensive literature review and future research directions. International Journal of Logistics Research and Applications, 23(2), 117-142.
- Mourtzis, D., Doukas, M., & Giannikas, V. (2020). Artificial Intelligence in Supply Chain Management: A Comprehensive Literature Review. Expert Systems with Applications, 160, 113661.
- Min, H. (2010). Artificial intelligence in supply chain management: Theory and applications. International Journal of Logistics Research and Applications, 13, 13–39.
- Ngai, E. W. T., Peng, S., Alexander, P., & Moon, K. K. L. (2014). Decision support and intelligent systems in the textile and apparel supply chain: An academic review of research articles. Expert Systems with Applications, 41, 81–91.
- Ni, D., Xiao, Z., & Lim, M. K. (2020). A systematic review of the research trends of machine learning in supply chain management. International Journal of Machine Learning and Cybernetics, 11, 1463–1482.
- Pereira, P., & Christopher, M. (2020). Artificial intelligence in supply chain management: A framework for research and applications. International Journal of Physical Distribution & Logistics Management, 50(8), 776-805.
- Pan, Y., Wu, S., Zhu, Q., & Zhang, L. (2020). Artificial Intelligence in Supply Chain Management: A State-of-the-Art Review. International Journal of Production Research, 58(7), 2063-2080.
- Ramanathan, U., Subramanian, N., & Parrott, G. (2018). Role of Artificial Intelligence, Big Data and Blockchains in Transforming Supply Chain Operations. International Journal of Production Research, 56(8), 2764-2776.
- Ross, D. F. (2018). Introduction to Supply Chain Management Technologies (2nd ed.). CRC Press.
- Tayur, S., Ganeshan, R., & Magazine, M. (2012). Quantitative Models for Supply Chain Management. Springer Science & Business Media.
- Wang, F., Wan, Z., Yuan, Y., & Zhang, X. (2019). Artificial intelligence in supply chain management: A systematic literature review and future research agenda. International Journal of Production Research, 57(7), 2161-2184.
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