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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorHardman, Lynda
dc.contributor.authorBatogiannis, Konstantinos
dc.date.accessioned2023-07-25T00:01:52Z
dc.date.available2023-07-25T00:01:52Z
dc.date.issued2023
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/44300
dc.description.abstractThis study explores gender-biased drives within the Government sector and Commercial industries. By focusing on four specific drives, namely Dominance, Decision Making, Social Empathy, and Helping, the aim is to uncover the extent to which employees in these sectors conform to stereotypical male and female drives in order to aid Talent Motivation Analysis (TMA) foster gender equity and mitigate the effects of these biases. Through an analysis of data and visualization, significant disparities and deviations from gender stereotypes are identified within and between the sectors. The findings reveal that while there are subtle differences in drives between the Government sector and Commercial industries, the overall dissimilarities are relatively minimal. The study reveals distinct gender-based patterns within each sector, illustrating variances in Dominance, Decision Making, Social Empathy, and Helping. However, these differences have minimal practical significance, as indicated by their small or negligible effect sizes. The study acknowledges limitations, including missing data and the absence of certain variables, and provides recommendations to advance gender equality in decision-making and establish inclusive work environments. In summary, this research acts as a guide for TMA, emphasizing the importance of challenging gender stereotypes, promoting equal opportunities, and ensuring fair treatment for employees regardless of gender.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectThis study explores gender-biased drives within the Government sector and Commercial industries. By focusing on four specific drives, namely Dominance, Decision Making, Social Empathy, and Helping, the aim is to uncover the extent to which employees in these sectors conform to stereotypical male and female drives in order to aid Talent Motivation Analysis (TMA) foster gender equity and mitigate the effects of these biases. (EX20 TMA)
dc.titleExploring Gender-Based Stereotypical Employee Drives: A Comparative Study of Government and Commercial Sectors
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.courseuuApplied Data Science
dc.thesis.id20029


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