Strategic Innovation under Volatility: A Game-Theoretic Model of Innovation Traps in Stagnant Economies | 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 Research Article Strategic Innovation under Volatility: A Game-Theoretic Model of Innovation Traps in Stagnant Economies Nam Anh Quach This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9075856/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 Macroeconomic stagnation in emerging economies is frequently associated with persistent underinvestment in innovation despite the presence of high-return technological opportunities. This paper develops a stochastic evolutionary game-theoretic model showing how macroeconomic volatility can endogenously generate innovation traps, in which decentralized firm behavior converges to a stable equilibrium dominated by imitation despite positive aggregate returns to innovation. We model a large population of firms facing a strategic choice between high-risk innovative strategies and low-risk imitative behaviors. To capture the influence of global market uncertainty and supply-chain volatility, stochastic fluctuations are incorporated directly into the payoff structure of the innovation game. The evolution of strategic behavior is described using stochastic replicator dynamics driven by Brownian motion, where the state variable represents the proportion of firms adopting innovative strategies. Analytical results show that sufficiently high environmental volatility can alter the stability structure of the evolutionary system, causing the dynamics to converge toward a suboptimal equilibrium dominated by imitation. This equilibrium represents an innovation trap in which decentralized strategic incentives suppress innovation even when aggregate economic returns remain positive. We derive explicit volatility thresholds that determine the stability of innovative equilibria and identify parameter regions where targeted risk-mitigation policies can destabilize the stagnation state and induce a transition toward innovation-driven growth. The results provide a formal mechanism explaining how macroeconomic volatility can endogenously generate persistent innovation failure and demonstrate how strategic interventions can restore self-sustaining innovative equilibria. Evolutionary Game Theory Stochastic Replicator Dynamics Innovation Traps Macroeconomic Volatility Strategic Innovation Equilibrium Stability Full Text Additional Declarations No competing interests reported. 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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