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Does digitalization sufficiently empower female entrepreneurs? Evidence from their online gender identities and crowdfunding performance

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Abstract

Drawing upon cyberfeminist theory with a socially constructed view of gender, this paper aims to objectively reveal the extent of digitalization in female entrepreneurs’ empowerment by examining the impacts of their online gender identities on crowdfunding performance. Leveraging a female-led sample of 3125 Kickstarter crowdfunding campaigns, we develop a measure of gender identity online using natural language processing analytic techniques to mine linguistic narratives, and empirically investigate our questions. The results reveal an inverted U-shaped relationship between the online displays of masculinity and crowdfunding performance for female entrepreneurs and no significant effect of femininity on crowdfunding performance. Regarding hybrid masculinity and femininity, we find those female entrepreneurs who display a masculine identity (i.e., high on masculinity and low on femininity) online perform better in crowdfunding. The results clearly demonstrate that the potential of crowdfunding for female entrepreneurs’ empowerment is overestimated in that embracing masculinity is reproduced online in addressing women’s financial constraints, thus providing objective and reliable evidence for informing the debate on the extent of digitalization in female entrepreneurs’ empowerment.

Plain English Summary

Does digitalization sufficiently empower female entrepreneurs? Evidence from examining the impacts of their online gender identities on crowdfunding performance. Drawing upon cyberfeminist theory with a socially constructed view of gender, this paper relies on a dataset of female entrepreneurs online in a crowdfunding domain to reexamine the extent of digitalization in their empowerment. Through an empirical investigation of how female entrepreneurs “doing” gender identity online affects crowdfunding performance, this study shows that the online displays of masculinity have an inverted U-shaped association with crowdfunding performance; femininity has no significant effect; and their hybrids—a masculine identity (i.e., high on masculinity and low on femininity)—are more advantageous than are feminine, androgynous, and undifferentiated identities. Our findings based on cyberfeminist theoretical analyses reveal that embracing masculinity is reproduced online in addressing women’s financial constraints, strongly demonstrating that the true potential of crowdfunding for female entrepreneurs’ empowerment is overestimated. This paper provides objective evidence for informing the debates on the digitalization potential for female entrepreneurs’ empowerment and sheds light on how to apply cyberfeminism in subsequent research. Female entrepreneurs can also use our findings to improve crowdfunding performance.

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Notes

  1. The API of genderize.io is a language independent module that tries to detect gender by looking at given first names. The automatic recognition algorithm returns the gender and a probability that a specific name-gender attribution (male or female) was correct; in the case, it cannot decide, the algorithm returns none.

  2. Specifically, we employed a random sample of 50 campaigns with images and videos to check the differences in the words that emphasized masculine and/or feminine identities online among text, images, and videos, among which 25 samples failed, and 25 succeeded. For speech transcription in the videos, we utilized transcription software from iFLYTEK, which can recognize English speech and output it in transcript text. Official data from iFLYTEK showed that the accuracy rate of the text transfer is up to 97.5% (www.iflyrec.com/). As for words in images, we used manual inspections to record the text. With regard to testing the new dictionaries of text, images, and videos, we applied the same preprocessing, sentence encoding, and similar-word-finding techniques outlined above. Finally, we extracted the top 10 most similar words matching each word on our initial lists from the test corpus constructed with 50 random samples. After comparing the test list of words with our original list of words built on text, we did not find any new, meaningful items.

  3. The subcategories mainly include 3D Printing, Apps, Camera Equipment, DIY Electronics, Fabrication Tools, Flight, Gadgets, Hardware, Makerspaces, Software, Sound, Space Exploration, Robots, Wearables, and Web. See https://www.kickstarter.com/discover/categories/technology for more details.

  4. See GLOBE websites (https://www.globeproject.com/results) for more details of relevant cultural clusters.

  5. The man on team variable refers to whether there is at least one male founder in the founding team of the project and is coded as ‘1’ if yes and ‘0’ otherwise.

  6. The team size variable is operationalized as a categorical variable and coded as ‘0’ if only a single female entrepreneur without a team behind the project, ‘1’ if the number of team members is greater than 0 and less than 5, and ‘2’ otherwise. 239 campaigns of the sample had teams but did not report the team size online; all of them were classified as code ‘1.’.

  7. The image_f variable refers to whether at least one female image is displayed in the campaign and is coded as ‘1’ if yes and ‘0’ otherwise.

  8. The video_f is operationalized as a categorical variable and coded as ‘0’ if none of the videos is used in the campaign, ‘1’ if at least one video showing female voices is used, and ‘2’ otherwise (i.e., the campaign using a video that did not include female voices).

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Acknowledgements

The authors would like to thank the financial support from projects 16BGL025 (National Social Science Fund of China) and Crowdfunding Net (www.Kickstarter.com) for supplying the data. In addition, the authors thank the anonymous reviewers for their guidance.

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Correspondence to Yaokuang Li.

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Wang, Y., Li, Y., Wu, J. et al. Does digitalization sufficiently empower female entrepreneurs? Evidence from their online gender identities and crowdfunding performance. Small Bus Econ 61, 325–348 (2023). https://doi.org/10.1007/s11187-022-00690-x

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