Targeted Position Games: A Framework for Strategic Rank Optimization in Competitive Environments

Targeted Position Games: A Framework for Strategic Rank Optimization in Competitive Environments | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Targeted Position Games: A Framework for Strategic Rank Optimization in Competitive Environments Esmaeil Farshi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7880175/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In contemporary competitive landscapes, such as digital marketplaces and online auctions, agents often prioritize achieving specific ranks over outright victory, challenging conventional game-theoretic paradigms focused on payoff maximization. This paper introduces Targeted Position Games (TPGs), a novel framework where players strategically aim for designated ranks, incorporating positional constraints inspired by exclusivity principles like the Pauli Exclusion Principle in quantum mechanics. We formalize TPGs, prove the existence of Nash equilibria under general conditions, and extend the model to accommodate avoidance strategies and overlapping target ranks— allowing multiple players to compete for the same position. Through rigorous mathematical analysis, including pure and mixed strategy equilibria, we demonstrate the framework’s robustness. Empirical insights from position auction data and computational simulations validate the model’s predictions. Applications span online advertising , e-commerce, AI decision-making, and interdisci-plinary analogies to quantum systems. By bridging theoretical game theory with practical and empirical domains, TPGs provide a versatile tool for modeling rank-centric competition, with implications for mechanism design and strategic optimization. Physical sciences/Mathematics and computing Physical sciences/Physics Targeted Position Games Game Theory Competitive Strategy Nash Equilibrium Position Auctions Artificial Intelligence Digital Economy Full Text Additional Declarations No competing interests reported. Supplementary Files TPGSupplementaryInformation.pdf TPGSuppData.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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