Optimizing incentives for systems with heterogeneous agents

Author

Chen Chen, New Jersey Institute of TechnologyFollow

Document Type

Dissertation

Date of Award

8-31-2022

Degree Name

Doctor of Philosophy in Industrial Engineering - (Ph.D.)

Department

Mechanical and Industrial Engineering

First Advisor

Wenbo Cai

Second Advisor

Ismet Esra Buyuktahtakin-Toy

Third Advisor

Layek Abdel-Malek

Fourth Advisor

Sanchoy K. Das

Fifth Advisor

Yi Chen

Sixth Advisor

Junmin Shi

Abstract

This dissertation explores new models and applications based on the game theory of incentives. This exploration starts with controlling an invasive insect problem to address one of the most significant challenges facing our forests, the invasion of the Emerald ash borer (EAB), a non-native, wood-boring insect that threatens to kill most ash trees in North America, through designing two new cost-sharing programs between the landowners and local governments. Ash trees are one of North America’s most widely distributed tree genera and a vital part of the green infrastructure of cities, where they provide residents with numerous social, economic, and ecological benefits.

Current strategies to slow ash mortality due to the EAB infestation include surveillance of ash tree health coupled with insecticide treatment and/or removal of infested trees. Most ash trees grow on private land, and the growing spread of EAB infestation is largely due to the lack of a private-public partnership in its control. Local governments need programs to induce landowners to undertake actions to slow ash mortality.

A principal-agent modeling framework is presented to design two new programs in which a local government offers reimbursements to landowners to cover a portion of their management costs. Two mathematical models are designed for each program: one in which the reimbursement is based on the number of infested trees and another in which reimbursement is based on the number of treated trees. The numerical analysis shows that neither the optimal treatment decision nor the reimbursement in both programs is in general monotonic concerning the initial infestation level; rather, they depend on treatment effectiveness and the likelihood of the new infestations. Compared to the infestation-based reimbursement program, the treatment-based reimbursement program induces the landowner to treat more trees through a higher reimbursement and provides a higher overall benefit. The approach shown in this dissertation is expected to inspire other private-public partnerships to solve various environmental and societal spatio-temp oral problems through better resource sharing, such as the management of water, land, and wildfire.

Given the required reimbursement assigned to private lands, the government needs to address the problem of budget allocation among public and private sites. An integrated game theory-mixed integer framework is designed to allocate resources to the management decisions on both public and private sites over space and time to maximize the profit of the government. The attack rate of EAB of this integrated model is validated by predicting the real attack rate based on the real infestation EAB data.

The dissertation then focuses on studying the implications of emissions policies in a Carbon Capture and Storage (CCS) system. The excessive emission of CO₂ is supercharging the natural greenhouse effect, which causes the rise of temperature, further affects climate and sea levels, and even increases extreme weather and natural disasters. In order to induce emitters to capture as much as possible CO₂, the principal-agent framework is designed between the CCS operator and emitters.

Specifically, the principal (CCS operator) offers a menu of contracts to agents (emitters) whose demand may follow different distributions, and the government may or may not introduce the cap-and-trade policy (free allocated allowances given to emitters) into the market. Two scenarios are examined: 1) the cap-and-trade policy is lunched, and 2) the cap-and-trade policy is not lunched. The principal-agent framework is presented to design optimal contracts for emitters by the CCS operator. The principal prefers to offer efficient quantities to the agents regardless of the demand levels when there is only one type of agent with no carbon allowance assigned by the government; however, emitters are induced to capture all their emissions when the cap-and-trade policy is launched. When there are two different types of agents, mostly the emitters are induced to capture all their emissions with the allowance assigned by the government; however, they always do not have enough incentive to capture all emissions when the cap-and-trade policy is not implemented on the market.

Recommended Citation

Chen, Chen, "Optimizing incentives for systems with heterogeneous agents" (2022). Dissertations. 1617.
https://digitalcommons.njit.edu/dissertations/1617