Vol. 13 No. 3 (2025): Business & Management Studies: An International Journal
Articles

Profile analysis of the business life difficulties of women working in the IT field using the clustering method

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  • Kevser Şahinbaş
Kevser Şahinbaş
Assist. Prof. Dr., Istanbul Beykent University, Istanbul, Turkiye

Published 2025-09-25

Keywords

  • Gender Inequalities, Information Technology Sector, Challenges, Women in Technology
  • Cinsiyet Eşitsizlikleri, Bilişim Sektörü, Engeller, Teknolojide Kadınlar

How to Cite

Profile analysis of the business life difficulties of women working in the IT field using the clustering method. (2025). Business & Management Studies: An International Journal, 13(3), 1132-1160. https://doi.org/10.15295/bmij.v13i3.2612

Copyright (c) 2025 Kevser Şahinbaş

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Profile analysis of the business life difficulties of women working in the IT field using the clustering method. (2025). Business & Management Studies: An International Journal, 13(3), 1132-1160. https://doi.org/10.15295/bmij.v13i3.2612

Abstract

Despite women's increasing interest in various career opportunities in the IT sector and their active participation in training and recruitment policies aimed at improving the number of women in the industry, there is evidence that gender-based discrimination persists in perceptions about the sector. This study aims to analyse the difficulties women face in the IT sector in Türkiye by associating them with demographic variables. The survey study asked questions about discrimination in a male-dominated industry, challenges encountered in managerial advancement, individuals' internal barriers, and difficulties related to accessing technology. To determine how demographic factors affect the difficulties, t-tests, ANOVA tests, correlation analysis for the relationship between variables, and employee profile analysis with K-Means clustering were conducted. It was determined that women face structural barriers in accessing managerial positions and difficulties in accessing technology. However, no significant difference was found in individuals' internal barrier perceptions based on gender. Additionally, K-Means cluster analysis was applied, and three distinct employee profiles were identified. The first cluster comprises female employees who perceive structural difficulties intensely; the second cluster represents individuals who have adapted to the sector and have a low perception of challenges; while the third cluster includes highly educated individuals who face internal obstacles and problems accessing technology.

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