Supplier Recommendation in Online Procurement

TL;DR

This work proposes a recommender system to assist with supplier discovery in road freight online procurement, able to provide personalized supplier recommendations, taking into account customer needs and preferences.

Abstract

Supply chain optimization is key to a healthy and profitable business. Many companies use online procurement systems to agree contracts with suppliers. It is vital that the most competitive suppliers are invited to bid for such contracts. In this work, we propose a recommender system to assist with supplier discovery in road freight online procurement. Our system is able to provide personalized supplier recommendations, taking into account customer needs and preferences. This is a novel application of recommender systems, calling for design choices that fit the unique requirements of online procurement. Our preliminary results, using real-world data, are promising.

Figures (2)

• Figure 1: Mean precision, recall and NDCG for different values of $k$ for the FM recommender, the popularity baseline and the MF-like baseline.
• Figure 2: Recommendation in 3 Steps