Young-Hyo Ahn, Jin-Hee Ma, Dong-Hun Lee, Kwan-Ho Kim, Hokey Min
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Recommendation of the Best Trading Partner Region through Supplier-Buyer Matching Using Deep Learning
Currently, the way suppliers and buyers find the best business partners on the supply chain is not far from simply focusing on low costs. This study aims to present a way to explore the optimal business partner to construct the best supply chain in consideration of supply chain risks, hidden costs, and opportunities to create added value. More specifically, the probability that a company finds an best business partner between regions or within regions is calculated and presented. In this study, we present a method of developing an index called a transaction possibility score using an artificial intelligence (deep learning) model to find a business partner as an best supplier.
We hope that the results of this study will not only explore the best business partners of each local company, but also help reorganize the local industrial structure in Korea.