Bridging the policy design and implementation gap in Nigeria’s startup ecosystem

Bibliographic Data

ID22428324
AuthorsAbubakar Sadiq Muhammad (0000-0001-6534-4988, Bavarian Research Institute for Digital Transformation), Labaran Isiaku (0000-0001-6386-770X, Cyprus International University), Abdulhaleem Salisu Shehu (Nasarawa State University)
Year2026
Volume20
Issue3
Pages899-924
Publication date2026-06-22
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueTransforming Government: People, Process and Policy (JOURNAL)
Journal identifiersISSN: 1750-6166 • E-ISSN: 1750-6166
PublisherEmerald (PUBLISHER)
DOI10.1108/tg-09-2025-0295
OpenAlexW7125493079
LanguageEN
References cited39

Purpose This study aims to identify and analyze the barriers hindering the effective implementation of the Nigeria Startup Act (2022) and to determine the causal relationships among them to provide actionable insights for policymakers. Design/methodology/approach The study uses a fuzzy Decision-Making Trial and Evaluation Laboratory (fuzzy DEMATEL) methodology. Data was collected from ten experts within the Nigerian innovation policy and startup ecosystem through a pairwise comparison questionnaire. The experts evaluated the influence of ten pre-identified barriers, which were subsequently analyzed using fuzzy set theory to map a cause–effect network. Findings The analysis identifies four key barriers as causal factors that drive the system: insufficient funding, bureaucratic bottlenecks, policy incoherence and low awareness of the Act. These root causes significantly influence six dependent barriers: lack of inter-agency coordination, inadequate technical capacity, low stakeholder engagement, resistance to change, data scarcity and limited monitoring and evaluation systems. Bureaucratic bottlenecks were found to be the most central and influential barrier within the network. Originality/value This study is among the first to apply the fuzzy DEMATEL method to analyze innovation policy implementation in Africa. It moves beyond descriptive barrier identification to provide an empirical model of their causal interdependencies, offering a novel and strategic perspective for overcoming the design-implementation gap in developing economies.

Bureaucracy · Fuzzy logic · Fuzzy set · Pairwise comparison · Qualitative comparative analysis · Scarcity · Stakeholder · Stakeholder analysis · Economic Growth and Development · Qualitative Comparative Analysis Research · University-Industry-Government Innovation Models

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