DOI
https://doi.org/10.25772/0ZAT-XW81
Author ORCID Identifier
https://orcid.org/0000-0002-2123-0302
Defense Date
2019
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Systems Modeling and Analysis
First Advisor
Jason R. W. Merrick
Second Advisor
Casey Lichentdahl
Third Advisor
Lance Saunders
Fourth Advisor
Paul Brooks
Fifth Advisor
David Edwards
Abstract
The present work explores improvements in group decision-making. It begins with a practical example using state-of-the-art techniques for a complex, high-risk decision. We show how these techniques can reveal a better alternative. Although we created an improved decision process, decision-makers were apt to protect their own organizations instead of the project. This tendency was reduced over the course of the decision-making process but inspired the first conceptual component of this work.
The first concept describes the “Cost of Conflict” that can arise in a group decision, using game theory to represent the non-cooperative approach and comparing the outcome to the cooperative approach. We demonstrate that it is possible for the group to settle on a non-Paretto Nash equilibrium. The sensitivity of the decision-maker weights is revealed which led to the second conceptual portion of this work.
The second concept applies social network theory to study the influence between decision-makers in a group decision. By examining the number and strength of connections between decision-makers, we build from intrinsically derived weights to extrinsically derived weights by adding the network influences from other decision-makers. The two conceptual approaches provide a descriptive view of non-cooperative decisions where decision-makers still influence each other. These concepts suggest a prescriptive approach to achieving a higher group utility.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
5-8-2019
Included in
Business Administration, Management, and Operations Commons, Management Sciences and Quantitative Methods Commons, Operations Research, Systems Engineering and Industrial Engineering Commons