Knowledge-Empowered Automated Negotiation System for B2B e-Commerce

This paper presents a knowledge empowered automated negotiation system for buyer-centric multi-bilateral multi-attribute e-Procurement. We propose two knowledge empowered models namely KERM and KACM. KERM is used for the buyer to determine a list of suppliers which are the best qualified candidates to negotiate with. KERM also allows the flexibility to assign appropriate weights, based on buyer´s interests, to each knowledge factor affecting the overall evaluation result of a quote. The resulted list of quotes of high rank is believed to produce satisfactory negotiation result for the buyer. KACM enables an automated concession process, while at the same time facilitates a flexible negotiation via the use of concept switch and tagged rules. KACM emphasizes the utilization of knowledge originated from the historical negotiation data in estimating and fine-tuning the negotiation parameters for improving the performance of automated negotiation. Our results show that the prototype makes significant improvement in the satisfaction level of negotiation results.