Supplier Recommendation in Online Procurement
This addresses the need for competitive supplier selection in business supply chains, but it is incremental as it applies existing recommender system techniques to a new domain.
The paper tackles the problem of supplier discovery in online procurement for road freight by proposing a personalized recommender system, with preliminary results on real-world data showing promise.
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.