Persistent Link:
http://hdl.handle.net/10150/289589
Title:
Conflict resolution under uncertainty
Author:
Lin, Chiahung Jessica, 1970-
Issue Date:
1997
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Rubinstein's alternating offer bargaining model is extended to uncertain situations. When the players do not have complete information on the feasible payoff set, the bargaining is based on the players' own estimations on the Pareto frontier. It has been proved that there always exists a unique stationary fictitious subgame perfect equilibrium (SPE) if the estimates of the Pareto frontier are close to each other. Monotonicity and convergence properties of the stationary subgame perfect equilibria (SPEs) are next examined. It has been shown that the convergence of the disagreement payoff vector and the break-down probabilities implies the convergence of the SPEs as well. The controllability of the resulting dynamic systems is examined and it is shown that by selecting an appropriate disagreement payoff vector and a break-down probability, any desired outcome or maximize payoffs can be reached. The bargaining processes with time-varying Pareto frontiers are also analyzed. Four examples are provided to illustrate how to use the general model to design optimal negotiation strategy. The results of the dissertation provide schemes that can be applied to design and conduct future negotiations.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Psychology, Behavioral.; Psychology, Social.; Economics, Theory.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Systems and Industrial Engineering
Degree Grantor:
University of Arizona
Advisor:
Szidarovszky, Ferenc

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleConflict resolution under uncertaintyen_US
dc.creatorLin, Chiahung Jessica, 1970-en_US
dc.contributor.authorLin, Chiahung Jessica, 1970-en_US
dc.date.issued1997en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractRubinstein's alternating offer bargaining model is extended to uncertain situations. When the players do not have complete information on the feasible payoff set, the bargaining is based on the players' own estimations on the Pareto frontier. It has been proved that there always exists a unique stationary fictitious subgame perfect equilibrium (SPE) if the estimates of the Pareto frontier are close to each other. Monotonicity and convergence properties of the stationary subgame perfect equilibria (SPEs) are next examined. It has been shown that the convergence of the disagreement payoff vector and the break-down probabilities implies the convergence of the SPEs as well. The controllability of the resulting dynamic systems is examined and it is shown that by selecting an appropriate disagreement payoff vector and a break-down probability, any desired outcome or maximize payoffs can be reached. The bargaining processes with time-varying Pareto frontiers are also analyzed. Four examples are provided to illustrate how to use the general model to design optimal negotiation strategy. The results of the dissertation provide schemes that can be applied to design and conduct future negotiations.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectPsychology, Behavioral.en_US
dc.subjectPsychology, Social.en_US
dc.subjectEconomics, Theory.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineSystems and Industrial Engineeringen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorSzidarovszky, Ferencen_US
dc.identifier.proquest9738962en_US
dc.identifier.bibrecord.b37474182en_US
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