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.
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The seventeen barriers are: (1) lack of industry experience of women; (2) Societal expectations that women’s primary role are child care and domestic household duties; (3) Unfavorable lifestyle choices that women make daily; (4) Fewer tendencies to invest in training and development of employees; (5) Discrimination; (6) Negative attitude against women; (7) Problems related to childcare; (8) Inadequate education and training; (9) Exploitation of women; (10) Ethnic or religious barriers; (11) Family commitments; (12) Lack of access to capital; (13) Lack of access to business information; (14) Lack of access to networks; (15) Lack of access to advice; (16) Lack of tendency to acquire quality business information; (17) Lack of entrepreneurial skills.
Their research work has been involved in different countries (e.g., the USA, the UK, Australia, Turkey, Poland, Nigeria, Northern Ireland, Korea, sub-Saharan Africa, Spain, and Fiji) (Loscocco and Robinson 1991; Fielden et al. 2003; Collins and Low 2010; Cetindamar et al. 2012; Bliss and Garratt 2001; Woldie and Adersua 2004; Mc Gowan et al. 2012; Lee et al. 2011; Amine and Staub 2009; Tur-Porcar et al. 2017; Noguera et al. 2013; Naidu and Chand 2017), sectors (e.g., fisheries, service, and retail) (Coleman 2007; Akehurst et al. 2012; Zhao et al. 2013), and women groups (e.g., migrant women entrepreneurs and ethnic minority women entrepreneurs) (Azmat 2013; Carter et al. 2015).
In symmetrical relationships, for example, low values of X associate with low values of Y, and high values of X associate with high values of Y; in other words, low values of X are both necessary and sufficient for low values of Y to occur, and high values of Y occur with high values of X (Woodside 2013).
In Guatemala, the ratio of necessity TEA females and TEA females is 45.1%. In Brazil and Argentina, this ratio is 47.7% and 40.1%, respectively.
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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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Wu, J., Li, Y. & Zhang, D. Identifying women’s entrepreneurial barriers and empowering female entrepreneurship worldwide: a fuzzy-set QCA approach. Int Entrep Manag J 15, 905–928 (2019). https://doi.org/10.1007/s11365-019-00570-z