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Massachusetts Institute of Technology

Effect of learning on stakeholder negotiation outcomes : modeling and analysis of game-generated data

Abstract

dc:description.abstract

A design negotiation game based on a stakeholder salience framework was created by the APACE research team to explore negotiation dynamics between stakeholders with individual attributes and agendas. Experimental data was collected anonymously during games played by groups of human participants through a web interface. It was found that the negotiation process takes a non-zero number of iterations even under conditions that strongly favor agreement. A realistic scenario was created based on extensive interviews with the major stakeholders involved in a real negotiation of a plan for a new government information technology system. Solution space exploration of this scenario demonstrated that the experimentally obtained solutions lie far from the optimality frontier. Performance differed significantly in two groups of participants with dissimilar professional experience; games played by interns achieved higher scores than those played by senior staff. An agent-based model was built to simulate multi-stage design negotiation. Utility functions of individual players were based on their private agendas. Players voted for a design according to the relative attractiveness of the design as established by the individual utility function. The negotiation process helps players discover other players' agendas. It was hypothesized that knowledge of each other's private objectives would enable groups of players to achieve design solutions that are closer to optimal. Effects of learning were introduced into the model by adding a fraction of the sum of all players' utility function to each individual utility function. Simulated games with learning effects yielded solutions with higher total player scores than simulated games without learning did. Results of simulated games with a substantial level of learning effects were similar to average experimental results from groups of interns. Results of simulated games without learning were close to the average results of games played by senior staff.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Engineering Systems Division.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Markina-Khusid, Aleksandra
Advisor dc:contributor.advisor
  • Donna Rhodes.

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/100390
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/100390

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Markina-Khusid, Aleksandra. Effect of learning on stakeholder negotiation outcomes : modeling and analysis of game-generated data. Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100390