A Negotiation Optimization Strategy of Collaborative Procurement with Supply Chain Based on Multi-Agent System

Abstract

In the process of collaborative procurement, buyers and suppliers are prone to conflict in cooperation due to differences in needs and preferences. Negotiation is a crucial way to resolve the conflict. Aimed at ameliorating the situations of underdeveloped self-adaptive learning effect of current collaborative procurement negotiation, this paper constructs a negotiation model based on multi-agent system and proposes a negotiation optimization strategy combined with machine learning. It provides a novel perspective for the analysis of intelligent SCM. The experimental results suggest that the proposed strategy improves the success rate of self-adaptive learning and joint utility of agents compared with the strategy of single learning machine, and it achieves win-win cooperation between purchasing enterprise and supplier.

Procurement professionals' perceptions of skills and attributes of procurement negotiators: a cross-sectional survey in Tanzania

“…Conducted negotiations provide a means for suppliers and customers to maintain business relationships (Atkin and Rinehart, 2006;Meijers et al, 2014), are essential for project success (Hoezen and Volker, 2015), and help in resolving conflicts or misunderstandings (Vetschera, 2013). Furthermore, negotiations play an important role in supply chain coordination and cooperation (Chen and Xu, 2018) and reduce transaction costs (Meijers et al, 2014). Despite the relevance of negotiations, studies show that the success of negotiations is dependent on several factors, including the friendly negotiation environment (Khan, 2018), trust (Bakar and Peszynski, 2010), supplier quality (Delina et al, 2020), tactics (Geiger, 2017) and the characteristics of negotiators (Cichosz, 2016).…”