 Time-to-unicorn and digital entrepreneurial ecosystemsAna Venâncio, Winnie Picoto and Inês Pinto Technological Forecasting and Social Change, 2023, vol. 190, issue C Abstract: This study examines the influence of a digital entrepreneurial ecosystem in setting the pace of how fast a start-up becomes a unicorn (time-to-unicorn). We apply a fuzzy-set qualitative comparative analysis approach (fsQCA) in which we use factors such as supply and demand conditions, innovation and change, institutional environment, and digital trust to determine the configurations that lead to unicorn success, measured by time-to-unicorn. We draw on data on unicorns from CB Insights and use the digital evolution and digital trust scores from the Digital Intelligence Index to analyze 766 unicorns from 39 countries that achieved this status between 2014 and 2021. The results show that several combinations of conditions increase the average national speed that a start-up takes to become a unicorn. Institutions, resources, and infrastructures have a stronger effect on unicorn success than digital trust. These findings contribute to the ongoing debate on the role of digitalization and institutions in the performance of digital entrepreneurial ecosystems. Keywords: Entrepreneurship; Ecosystem; Unicorns; Digitalization; Time-to-unicorn; Institutional theory; fsQCA (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:190:y:2023:i:c:s0040162523001105 DOI: 10.1016/j.techfore.2023.122425 Access Statistics for this article Technological Forecasting and Social Change is currently edited by Fred Phillips More articles in Technological Forecasting and Social Change from Elsevier |
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