Identifying women’s entrepreneurial barriers and empowering female entrepreneurship worldwide: a fuzzy-set QCA approach

  • Juan Wu
  • Yaokuang LiEmail author
  • Daru Zhang


Barriers faced by women entrepreneurs have always been a hot topic in women’s entrepreneurship research. However, existing studies have often adopted either explanatory/descriptive approaches or conventional quantitative methods, thereby limiting our understanding of gender specificity and complexity in terms of women’s entrepreneurial barriers. The present work begins with the adoption of a post-structural feminist perspective to examine women’s entrepreneurial barriers, and it identifies four gender inequality barriers, namely motherhood, entrepreneurial cognitions, norms, and finance. Using fuzzy-set qualitative comparative analysis (fsQCA), this study first investigates how the four barriers combine to explain the low level of female entrepreneurship across 28 countries and thus confirm, rather than exaggerating, the real barriers faced by women entrepreneurs. We further take advantage of the asymmetric thinking of fsQCA to explore the causal recipes for achieving a high female entrepreneurial rate. On the one hand, the findings indicate that poor female entrepreneurial cognitions together with a high initial funding requirement constitute women’s entrepreneurial barriers, leading to the low level of female entrepreneurship. On the other hand, the findings provide four causal paths, including not only favorable but also unfavorable conditions, to achieving a high level of female entrepreneurship. Furthermore, the findings also emphasize a low initial funding requirement as a critical incentive for an increase in female entrepreneurship. These findings provide a series of implications at the academic level, as well as the policy level.


Barrier Female entrepreneurship Motherhood Cognitions Finance Fuzzy-set qualitative comparative analysis (fsQCA) 



This work was supported by the National Social Science Fund of China [award number: 16BGL025]; and the National Natural Science Foundation of China [award number: 71272056].


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Authors and Affiliations

  1. 1.School of ManagementHefei University of TechnologyHefeiChina

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