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Seeing What Others Miss: A Study of Women Entrepreneurs in High-Growth Startups

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  • Neill Stern
  • Metcalf Lynn
  • York Jonathan L.

    (Orfalea College of Business, California Polytechnic State University, 1 Grand Ave, San Luis Obispo, CA 93407, USA)

Abstract

A pressing question in entrepreneurial research is where opportunities come from. Prior research indicates that some opportunities stem from known parameters and outcomes; some are discovered through engagement with unknown but knowable factors; and others are unknowable until brought into being through a creative process. This paper explores the second and more prevailing view in entrepreneurial research – that individuals discover business opportunity – and examines how high-growth entrepreneurs perceive opportunity through engagement with the world. Survey results, based on responses from 165 women entrepreneurs in high-growth startups, indicate that individuals with a strong discover mindset act and think in ways that support opportunity perception. Coupled with a belief in her abilities, the entrepreneur is more likely to move from opportunity perception to new venture creation. Results from semi-structured interviews with women from the same population elucidate the survey findings and yield implications for entrepreneurial theory and practice.

Suggested Citation

  • Neill Stern & Metcalf Lynn & York Jonathan L., 2015. "Seeing What Others Miss: A Study of Women Entrepreneurs in High-Growth Startups," Entrepreneurship Research Journal, De Gruyter, vol. 5(4), pages 293-322, October.
    • Handle: RePEc:bpj:erjour:v:5:y:2015:i:4:p:293-322:n:1
    DOI: 10.1515/erj-2014-0009
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    References listed on IDEAS

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    2. Paola Demartini, 2019. "Why and How Women in Business Can Make Innovations in Light of the Sustainable Development Goals," Administrative Sciences, MDPI, vol. 9(3), pages 1-8, August.
    3. Sara Sassetti & Giacomo Marzi & Vincenzo Cavaliere & Cristiano Ciappei, 2018. "Entrepreneurial cognition and socially situated approach: a systematic and bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1675-1718, September.

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