negotiation behaviors in agent-based negotiation support systems

Abstract

Prior research on negotiation support systems (NSS) has paid limited attention to the information content in the observed bid sequences of negotiators as well as on the cognitive limitations of individual negotiators and their impacts on negotiation performance. In this paper, we assess the performance of human subjects in the context of agent-based NSS, and the accuracy of an exponential functional form in representing observed human bid sequences. We then predict the reservation values of negotiators based on their observed bids. Finally, we study the impact of negotiation support systems in helping users realize superior negotiation outcomes. Results indicate that an exponential function is a good model for observed bids. Based on the negotiation behaviors of human subjects, we find that accurate estimates of opponent reservation values for the negotiation issue that is most important to subjects, improves negotiation outcomes when an agreement is reached. Results also show that bids are correlated with reservation values, and that automated negotiations using NSS can lead to superior negotiation outcomes compared to human subjects.