Keywords: MESO, simulation, negotiation, e-learning  

Background and Motivation: 

Effective negotiation requires providing and receiving the right kind of information. Providing information about relative priorities across issues and their magnitude using Multiple and Equivalent Simultaneous Offers (MESO) leads to optimal joint outcomes [1]. However, in the context of an academic environment, instructors often have limited control over the kind of information students share during role plays, leading to suboptimal agreements or no agreements at all. To address this, we created a software program that teaches students how to provide and interpret priority-related information using MESO, leading to mutually beneficial agreements. 

Methodology: 

The software program uses a case-based approach to develop and assess students’ competencies in MESO negotiations, specifically with negotiating the purchase of a car. Students create MESOs and receive counter-MESOs to learn how to give and receive the right kind of information during negotiation. The software includes features that allow students to adjust their offers based on the counteroffers received and provides feedback on the joint outcome of the negotiation. 

Results: 

The study involved 374 students who negotiated over the purchase of a car using the software program. For distributive issues that are mutually exclusive where there is a win-lose scenario: the most frequently selected car was priced at $50,000 and had a 1-week delivery date. For integrative issues that are non-mutually exclusive potentially creating a win-win scenario: the most frequently selected car had a 30-month warranty, was at 2% financing, and had audiophile audio installed. For compatible issues that are non-mutually exclusive where the parties desire the same outcome: the most frequently selected car had airbags on all sides with a shut-off switch and had a yellow colour. The average buyer's utility was 15,589 with a standard deviation of 3,213.10. We found that initially, students seemed to propose offers that would maximize their points in the simulation. However, over 25 attempts, they converged closer to a Pareto frontier for the optimal number of points available in the simulation of 13,200, indicating that they were learning to negotiate for mutually beneficial outcomes [2]. Furthermore, student feedback showed liking the instantaneous responses that the simulator provided while also complimenting being able to practice negotiation skills in an environment where emotions are not a factor. These results demonstrate the effectiveness of the software program in teaching negotiation skills and promoting mutually beneficial agreements. 

Conclusion: 

Providing and receiving the right kind of information during negotiation is crucial to achieving optimal joint outcomes. The software program developed in this study effectively teaches students how to use MESO to provide and interpret priority-related information, leading to mutually beneficial agreements. This program can be used as a tool for instructors to teach negotiation skills and for students to practice negotiation in a controlled environment. Future studies can explore the program's effectiveness in different negotiation contexts and with different populations. 

References: 

[1] G. J. Leonardelli, J. Gu, G. McRuer, V. H. Medvec, and A. D. Galinsky, “Multiple equivalent simultaneous offers (mesos) reduce the negotiator dilemma: How a choice of first offers increases economic and relational outcomes,” Organizational Behavior and Human Decision Processes, vol. 152, pp. 64–83, May 2019.  

[2] M. J. Prietula and L. R. Weingart, “Negotiation offers and the search for agreement,” Negotiation and Conflict Management Research, vol. 4, no. 2, pp. 77–109, Mar. 2011.