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Stochastic Transitions in African Entrepreneurship

A Markov Chain Analysis of Ecosystem Dynamics and Policy Levers

Bibliographic Data

ID21737652
AuthorsMohamed Yasser Bounnite (0009-0002-6221-9270, CERMACH Research Center, SUP’RH School of Management & Artificial Intelligence, Complexe Panorama, Casablanca, Morocco, corresponding author), Abdelillah Khalid (0009-0001-9673-5188, CERMACH Research Center, SUP’RH School of Management & Artificial Intelligence, Complexe Panorama, Casablanca, Morocco)
Year2026
Pages1-25
Publication date2026-04-23
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of African Business (JOURNAL)
Journal identifiersISSN: 1522-8916 • E-ISSN: 1522-9076
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/15228916.2026.2662038
OpenAlexW4413940552
LanguageEN
References cited29

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 lifecycle and outlines strategic levers aimed at guiding both institutional and private actors in enhancing support mechanisms for innovation

Biology · Economic geography · Economic system · Economics · Ecosystem · Entrepreneurship · Markov chain · Physics · Sociology · Statistical physics · Statistics · Stochastic dynamics · Firm Innovation and Growth · Mathematics · Ecology

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Highly citedNo

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