Alternate Strategies for a Win-Win Seeking Agent in Agent-Human Negotiations

With the growth of e-commerce and e-markets, there is an increasing potential for the use of software agents to negotiate business tasks with human negotiators. Guided by design science methodology, this research prescribes and validates a win-win seeking negotiation agent using strategies of "simultaneous-equivalent offers" and "delayed acceptance" and compares their effects against the use of conventional sequential-single offer and immediate acceptance strategies. To evaluate the alternate strategies, a negotiation agent system was implemented and an experiment was conducted in which 110 agent-human dyads negotiated over a four-issue online purchase task. Our results indicate that the proposed agent strategies can enhance the economic performance of the negotiated outcome (counterpart agreement ratio, individual utility, joint utility, and the distance to Pareto-efficient frontier) and maintain the human counterparts' positive perceptions toward the outcome and the agent. The findings confirm the efficacy of the proposed design and showcase an innovative system to facilitate e-commerce transactions.