Identifying necessary conditions to deep-tech entrepreneurship

Abstract

Purpose – Our research aimed to address which resources provided by an entrepreneurial ecosystem (EE) are necessary for deep technology entrepreneurship. Design/methodology/approach – We employ a novel approach known as necessary condition analysis (NCA) to data on EEs and deep-tech startups from 132 countries, collected in a global innovation index and Crunchbase datasets. The NCA makes it possible to identify whether an EEs resource is a necessary condition that enables entrepreneurship. Findings – Necessary conditions are related to political and business environment; education, research and development; general infrastructure; credit; trade; diversification and market size; and knowledge absorption capacity. Research implications – Our results show that business and political environments are the most necessary conditions to drive deep-tech entrepreneurship. Practical implications – Policymakers could prioritize conditions that maximize entrepreneurial output levels rather than focusing on less necessary elements. Social implications – Some resources require less performance than others. So, policymakers should consider allocating policy efforts to strengthen resources that maximize output levels. Originality/value – Studies on deep-tech entrepreneurship are scarce. This study provides a bottleneck analysis that can guide the formulation of policies to support deep-tech entrepreneurship, since it allows to identify priority areas for resource allocation

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