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Virginia Tech

Incentive Mechanism Design for Systems with Many Agents: A Multiscale Decision Theory Approach

Abstract

dc:description.abstract

Incentives are an effective mechanism to align the interests of decision-makers. For example, employers use incentives to motivate their employees to take actions that benefit both the employers and the employees. Incentives also play a role in the interaction between firms, for example in a supply chain network. The prevalent approach to analyzing interactions between decision-makers is through principal-agent models. Due to mathematical intractability, the majority of these models are restricted to the interaction between two decision-makers. However, modern organizations have many decision-makers that interact with each other in a network. Therefore, effective incentive mechanisms for systems with many decision-makers (agents) must account for the numerous network interdependencies. The objective of this dissertation is to design incentive mechanisms for systems with many agents, with a focus on teams and multi-firm networks. Methodologically, our approach applies and builds upon multiscale decision theory (MSDT). MSDT can effectively and efficiently model the interdependencies between decision-makers and their optimal response to incentives. This dissertation consists of three parts. The first part focuses on incentives in teams, where multiple subordinates work under a single supervisor. The contribution of the team model to MSDT is the introduction of continuous decision variables; prior MSDT models have only used discrete decision variables. In the second and third part of this dissertation, we analyze a network of collaborating firms in a systems engineering project and focus on verification decisions. We introduce a belief-based model, which is a novel approach for both MSDT and verification modeling in systems engineering. Using MSDT, we determine how incentives can be used by a contractor to motivate a subcontractor to verify its design when the subcontractor prefers not to do so. We extend this two-firm model to a general multi-firm network model for verification coordination and incentivization. This firm network resembles the inter-firm collaboration present in most large-scale system engineering projects. Through better aligned verification activities, system-wide verification costs decrease, while the reliability of the final system improves.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Industrial and Systems Engineering
Department dc:contributor.department
Industrial and Systems Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kulkarni, Aditya Umesh
Chair dc:contributor.committeechair
  • Wernz, Christian
Committee members dc:contributor.committeemember
  • Bish, Ebru K.
  • Fraticelli, Barbara M. P.
  • Koelling, C. Patrick
  • Salado Diez, Alejandro

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:15981
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/94550

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Kulkarni, Aditya Umesh. Incentive Mechanism Design for Systems with Many Agents: A Multiscale Decision Theory Approach. doctoral thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/94550