Strategic interactions in modern elections and markets

This thesis examines strategic interactions in democratic and economic institutions against the backdrop of technological advancements which fuel new strategic capabilities. I investigate four interconnected domains: manipulation of redistricting fairness through strategic campaigning (termed here as 'Votemandering'), computational complexity and optimal strategies in Ranked Choice Voting (RCV), large-scale empirical validation of RCV's mechanism design, and AI-driven strategic behavior in oligopolistic markets. My overarching aim is to identify strategic gaps and guide institutional design in technology-mediated environments, which I do by developing theoretical and algorithmic frameworks through computational modeling, optimization techniques, as well as comprehensive empirical analysis. The findings contribute toward strengthening mechanism design in both electoral and market contexts. In redistricting, I demonstrate that fairness measures can exhibit vulnerability to strategic voter-data manipulation, though efficient regulatory frameworks and non-partisan constraints can enhance robustness. For RCV, I develop efficient algorithms that circumvent computational complexity barriers to uncover its strategic incentives. A large-scale analysis of over 100 diverse real-world elections shows that despite theoretical vulnerabilities, actual strategic dynamics are straightforward and transparent, and allow significant improvements in democratic benefits over prior plurality elections. In market contexts, I find that large language models demonstrate sophisticated strategic capabilities but exhibit autonomous, tacit collusion, sustaining prices up to 200\% of competitive levels. However, targeted regulation of major firms can effectively restore competitive pricing. Together, these contributions provide computational frameworks for understanding technology-mediated strategic behavior while offering practical tools for preserving institutional integrity in democratic governance and competitive markets.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Industrial Engineering

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Deshpande, Sanyukta

Contributors dc:contributor

• Jacobson, Sheldon H.
• Sreenivas, Ramavarapu S.
• Wang, Qiong
• Garg, Nikhil

• Strategic Behavior
• Mechanism Design
• Fairness
• Rank Choice Voting
• Game Theory
• Electoral Institutions

Statement dc:rights

• Copyright 2025 Sanyukta Deshpande

Language dc:language

en

Handle dc:identifier

https://hdl.handle.net/2142/132617

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/132617