Modeling Governance Transitions in Industrial Clusters: A Bayesian Markov Approach to Resilience and Policy Design

Modeling Governance Transitions in Industrial Clusters: A Bayesian Markov Approach to Resilience and Policy Design | 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 Modeling Governance Transitions in Industrial Clusters: A Bayesian Markov Approach to Resilience and Policy Design Mohamed Yasser BOUNNITE, Loubaba RAFI This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7390153/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 The competitiveness and resilience of industrial clusters depend not only on their sectoral specialization but also on the adaptability of their governance structures. This study develops a stochastic modeling framework, based on absorbing Markov chains with Bayesian estimation, to analyze governance transitions and their impact on cluster performance. Using longitudinal data from 12 European clusters over a 36-month period, we classify governance regimes into four types and estimate transition probabilities under varying institutional and sectoral conditions. Results show that hybrid governance regimes are 2.3 times more likely to sustain high-performance states compared to hierarchical or purely collegial forms, and that targeted interventions at identified bifurcation points can enhance organizational resilience by 18% to 42%. The findings highlight the existence of a “governance goldilocks zone” where institutional complexity yields optimal innovation and performance outcomes. Beyond methodological contributions, the study provides actionable insights for policymakers and cluster managers: supporting hybrid governance mechanisms, monitoring weak signals of institutional transition and tailoring support policies to sectoral contingencies. These results contribute to strategic planning and policy design aimed at fostering competitiveness and resilience in dynamic socio-economic environments. Econometrics Development Economics Industrial clusters Governance transitions Hybrid governance Resilience and performance Absorbing Markov chains Policy interventions Full Text Additional Declarations The authors declare no competing interests. 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. 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