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

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2015.

Bibliographic Details
Main Author: Markina-Khusid, Aleksandra
Other Authors: Donna Rhodes.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2015
Subjects:
Online Access:http://hdl.handle.net/1721.1/100390
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author Markina-Khusid, Aleksandra
author2 Donna Rhodes.
author_facet Donna Rhodes.
Markina-Khusid, Aleksandra
author_sort Markina-Khusid, Aleksandra
collection MIT
description Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2015.
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spelling mit-1721.1/1003902019-04-12T15:32:06Z Effect of learning on stakeholder negotiation outcomes : modeling and analysis of game-generated data Markina-Khusid, Aleksandra Donna Rhodes. System Design and Management Program. Massachusetts Institute of Technology. Engineering Systems Division. System Design and Management Program. Engineering Systems Division. System Design and Management Program. Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2015. Cataloged from PDF version of thesis. Includes bibliographical references (pages 75-81). 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. by Aleksandra Markina-Khusid. S.M. in Engineering and Management 2015-12-16T16:36:02Z 2015-12-16T16:36:02Z 2015 2015 Thesis http://hdl.handle.net/1721.1/100390 932127830 eng 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. http://dspace.mit.edu/handle/1721.1/7582 81 pages application/pdf Massachusetts Institute of Technology
spellingShingle Engineering Systems Division.
System Design and Management Program.
Markina-Khusid, Aleksandra
Effect of learning on stakeholder negotiation outcomes : modeling and analysis of game-generated data
title Effect of learning on stakeholder negotiation outcomes : modeling and analysis of game-generated data
title_full Effect of learning on stakeholder negotiation outcomes : modeling and analysis of game-generated data
title_fullStr Effect of learning on stakeholder negotiation outcomes : modeling and analysis of game-generated data
title_full_unstemmed Effect of learning on stakeholder negotiation outcomes : modeling and analysis of game-generated data
title_short Effect of learning on stakeholder negotiation outcomes : modeling and analysis of game-generated data
title_sort effect of learning on stakeholder negotiation outcomes modeling and analysis of game generated data
topic Engineering Systems Division.
System Design and Management Program.
url http://hdl.handle.net/1721.1/100390
work_keys_str_mv AT markinakhusidaleksandra effectoflearningonstakeholdernegotiationoutcomesmodelingandanalysisofgamegenerateddata