Advanced Technology and Future Directions for Supplier Selection
- DOI
- 10.2991/978-94-6463-098-5_4How to use a DOI?
- Keywords
- Supply chain; Supplier relationship management; Spend Analytic; Machine Learning; Artificial Intelligence
- Abstract
As the supply chain system matures, the supply chain organization spends a lot of resources and manpower on supplier selection and management through tendering and negotiation. This paper describes Multi-auction Mechanism and Verizon’s advanced technology VSRT to supplier screening to explore the logic of efficient, correct supplier management and the future direction of SRM based on related literature. The result shows that while both approaches offer capabilities not available in most SRMs on the market, they both provide strong data-level support for strategic decisions and help companies make decisions that are more beneficial to them. A disciplined, predictive online Supplier Relationship Management (SRM) is necessary to help companies manage supplier performance quickly and produce high-quality reports. It also provides a practical way of thinking about the future direction of SRM systems and supplier selection and technological innovation. Good updated technical support for future SRM system operation and iterative processes in enterprises.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Chen Chen PY - 2022 DA - 2022/12/27 TI - Advanced Technology and Future Directions for Supplier Selection BT - Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022) PB - Atlantis Press SP - 23 EP - 30 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-098-5_4 DO - 10.2991/978-94-6463-098-5_4 ID - Chen2022 ER -