Going Back to the Roots: a Bibliometric and Thematic Analysis of Women Entrepreneurship

Fayaz, Naira; Khandai, Sujata; Zupic, Ivan and Kaur, Avneet. 2022. Going Back to the Roots: a Bibliometric and Thematic Analysis of Women Entrepreneurship. Dynamic Relationships Management Journal, 11(2), pp. 97-115. ISSN 2232-5867 [Article]

[img]
Preview
Text
Fayaz Khandai Zupic Kaur 2022 - Going back to the roots - a bibliometric analysis of women entrepreneurship.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (1MB) | Preview

Abstract or Description

We used bibliometric methods to examine studies related to women entrepreneurship. Specifically, we focused on understanding the recent trends, the most influential publications and journals, topics on which women entrepreneurship studies are conducted, and deciphering the future direction of women entrepreneurship studies. We used the Scopus database to extract 1,554 documents published from 1982 to 2022 and analyzed the scientific publications per year, the most cited articles, sources of publications, keyword co‐occurrence, thematic structure (topic modeling), and bibliographic coupling. We found that the scientific publications related to women entrepreneurship are increasing significantly each year, and the most consistent keyword is “gender.” Citation analysis identified Ahl (2006) as the most cited article, which demonstrates Ahl’s notable influence, as well as the success of the gender turn influenced by feminist theory. Co‐word analysis found seven clusters showing the thematic structure of women entrepreneurship research. Bibliographic coupling analysis found four clusters, encompassing various aspects associated with women entrepreneurship. The clusters are “Role of gender in an entrepreneur’s performance,” “Challenges and upcoming issues faced by women entrepreneurs,” “Impact of geographic location on women entrepreneurship,” and “Financial struggles of women entrepreneurs.” Topic modeling using the latent Dirchlet allocation algorithm (LDA) identified seven areas of interest in the women entrepreneurship literature. We conclude with implications and suggestions for future research.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.17708/DRMJ.2022.v11n02a07

Additional Information:

Articles published in DRMJ are licensed under a Creative Commons Attribution-NonCommercial 4.0 International Public License (CC BY-NC 4.0; http://creativecommons.org/licenses/by-nc/4.0/). Under this license, authors retain ownership of the copyright for their content, but allow anyone to download, reuse, reprint, modify, distribute and/or copy the content for NonCommercial purposes as long as the original authors and source are cited.

Keywords:

bibliographic coupling, bibliometric analysis, co‐word analysis, female entrepreneurship, topic modeling, women entrepreneurship

Departments, Centres and Research Units:

Institute of Management Studies

Dates:

DateEvent
9 September 2022Accepted
7 December 2022Published

Item ID:

32888

Date Deposited:

03 Jan 2023 10:24

Last Modified:

28 Mar 2023 10:42

Peer Reviewed:

Yes, this version has been peer-reviewed.

URI:

https://research.gold.ac.uk/id/eprint/32888

View statistics for this item...

Edit Record Edit Record (login required)