Stochastic Transitions in African Entrepreneurship: A Markov Chain Analysis of Ecosystem Dynamics and Policy Levers

Abstract In the context of the rapidly evolving innovation ecosystems across Africa, this study investigates the advanced application of Markov chains as a robust analytical framework for modeling probabilistic transitions between various stages of entrepreneurial development. By integrating empirical data enriched with contextual variables, such as technological adoption, access to financing, and the influence of public policies, the research offers a dynamic and systemic perspective on the trajectories of African startups. The proposed approach identifies critical stages within the entrepreneurial lifecycleand outlines strategic levers aimed at guiding both institutional and private actors in enhancing support mechanisms for innovation.