Location

Hilton Waikoloa Village, Hawaii

Event Website

https://hicss.hawaii.edu/

Start Date

7-1-2025 12:00 AM

End Date

10-1-2025 12:00 AM

Description

Promoting women ’s empowerment through ICTs is an essential driver for achieving gender equality (SDG5) goals. While an increasing number of women and girls are enjoying equal opportunities to access technologies and STEM education, how the academic world of Information Systems (IS) emphasizes gender equality remains less known. This bibliometric study addresses this gap by examining the landscape of SDG5 publications within the IS discipline and assessing the impact of these studies. In addition, we highlight the role of leading authors’ gender (female) in driving SDG5 research. To empirically conduct this study, we self-trained an LSTM machine learning model to effectively identify authors’ gender by their names. Our empirical analysis reveals that the IS discipline is less attentive on SDG5 topics. In addition, female scholars tend to publish more SDG5 studies but exert less impact on academic society compared to their male counterparts. We further discuss our findings and propose future research directions.

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Jan 7th, 12:00 AM Jan 10th, 12:00 AM

The United Nations’ Sustainable Development Goal 5 (SDG5) Research and Impact from a Gender Perspective: A Bibliometric Analysis in the IS Discipline

Hilton Waikoloa Village, Hawaii

Promoting women ’s empowerment through ICTs is an essential driver for achieving gender equality (SDG5) goals. While an increasing number of women and girls are enjoying equal opportunities to access technologies and STEM education, how the academic world of Information Systems (IS) emphasizes gender equality remains less known. This bibliometric study addresses this gap by examining the landscape of SDG5 publications within the IS discipline and assessing the impact of these studies. In addition, we highlight the role of leading authors’ gender (female) in driving SDG5 research. To empirically conduct this study, we self-trained an LSTM machine learning model to effectively identify authors’ gender by their names. Our empirical analysis reveals that the IS discipline is less attentive on SDG5 topics. In addition, female scholars tend to publish more SDG5 studies but exert less impact on academic society compared to their male counterparts. We further discuss our findings and propose future research directions.

https://aisel.aisnet.org/hicss-58/sj/digital_divide/2