University of Illinois Urbana-Champaign

Strategic interactions in modern elections and markets

Deshpande, Sanyukta

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

Description

Title
Strategic interactions in modern elections and markets
Author(s)
Deshpande, Sanyukta
Issue Date
2025-09-02
Director of Research (if dissertation) or Advisor (if thesis)
Jacobson, Sheldon H.
Doctoral Committee Chair(s)
Jacobson, Sheldon H.
Committee Member(s)
  • Sreenivas, Ramavarapu S.
  • Wang, Qiong
  • Garg, Nikhil
Department of Study
Industrial&Enterprise Sys Eng
Discipline
Industrial Engineering
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
  • Strategic Behavior
  • Mechanism Design
  • Fairness
  • Rank Choice Voting
  • Game Theory
  • Electoral Institutions
Abstract
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.
Graduation Semester
2025-12
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/132617
Copyright and License Information
Copyright 2025 Sanyukta Deshpande

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Graduate Theses and Dissertations at Illinois