Incentive Mechanism Design for Systems with Many Agents: A Multiscale Decision Theory Approach
| dc.contributor.author | Kulkarni, Aditya Umesh | en |
| dc.contributor.committeechair | Wernz, Christian | en |
| dc.contributor.committeemember | Bish, Ebru K. | en |
| dc.contributor.committeemember | Fraticelli, Barbara M. P. | en |
| dc.contributor.committeemember | Koelling, C. Patrick | en |
| dc.contributor.committeemember | Salado Diez, Alejandro | en |
| dc.contributor.department | Industrial and Systems Engineering | en |
| dc.date.accessioned | 2019-10-11T06:00:35Z | en |
| dc.date.available | 2019-10-11T06:00:35Z | en |
| dc.date.issued | 2018-08-14 | en |
| 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. | en |
| dc.description.abstractgeneral | Incentives are often used to align the interests of decision-makers in modern organizations. 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 multiple firms, for example in a supply chain network. The prevalent approach to analyzing interactions between decision-makers is through the so-called 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 interdependencies that arise due to the organizational structure. 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 derive optimal organization-wide incentives. This dissertation consists of three parts. The first part focuses on incentives in teams, where multiple employees work under a single manager. 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 contractors in a systems engineering project and focus on design verification strategies. 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. | en |
| dc.description.degree | Ph. D. | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:15981 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/94550 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Incentives | en |
| dc.subject | multiscale decision theory | en |
| dc.subject | systems engineering | en |
| dc.subject | organizations | en |
| dc.title | Incentive Mechanism Design for Systems with Many Agents: A Multiscale Decision Theory Approach | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Industrial and Systems Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Ph. D. | en |
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