| Title: | Navigating gender nuances : assessing the impact of AI on employee engagement in Slovenian entrepreneurship |
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| Authors: | ID Rožman, Maja (Author)
ID Tominc, Polona (Author) |
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| Files: |  https://www.mdpi.com/2079-8954/12/5/145
 Navigating_Gender_Nuances.pdf (617,48 KB)
MD5: 98328DA4F7E4B1D4873C53B0D7D538D0
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | EPF - Faculty of Business and Economics
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| Abstract: | Background: Our research delved into exploring various selected facets of AI-driven
employee engagement, from the gender perspective, among Slovenian entrepreneurs. Methods:
This research is based on a random sample of 326 large enterprises and SMEs in Slovenia, with an
entrepreneur completing a questionnaire in each enterprise. Results: Findings suggest that there
are no significant differences between male and female entrepreneurs in Slovenia regarding various
aspects of AI-supported entrepreneurial management practice including the following: AI-supported
entrepreneurial culture, AI-enhanced leadership, adopting AI to reduce employee workload, and
incorporating AI tools into work processes. The widespread integration of AI into entrepreneurship
marks a transition to a business landscape that values inclusivity and equity, measuring success
through creativity, strategic technology deployment, and leadership qualities, rather than relying on
gender-based advantages or limitations. Our research also focused on the identification of gender
differences in path coefficients regarding the impact of the four previously mentioned aspects of
AI on employee engagement. While both genders see the value in using AI to alleviate employee
workload, the path coefficients indicate that female entrepreneurs report higher effectiveness in
this area, suggesting differences in the implementation of AI-integrated strategies or tool selection.
Male entrepreneurs, on the other hand, appear to integrate AI tools into their work processes more
extensively, particularly in areas requiring predictive analytics and project scheduling. This suggests
a more technical application of AI in their enterprises. Conclusions: These findings contribute
to understanding gender-specific approaches to AI in enterprises and their subsequent effects on
employee engagement. |
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| Keywords: | entrepreneurship, artificial intelligence, AI-supported entrepreneurial culture, AI-enhanced leadership, adopting AI to reduce employee workload, incorporating AI tools into work processes, employee engagement |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 07.03.2024 |
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| Article acceptance date: | 23.04.2024 |
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| Publication date: | 24.04.2024 |
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| Publisher: | MDPI |
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| Year of publishing: | 2024 |
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| Number of pages: | str. 1-24 |
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| Numbering: | Vol. 12, no. 145 |
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| PID: | 20.500.12556/DKUM-92122  |
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| UDC: | 331.108 |
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| ISSN on article: | 2079-8954 |
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| COBISS.SI-ID: | 194907907 |
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| DOI: | 10.3390/systems12050145 |
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| Publication date in DKUM: | 01.07.2025 |
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| Views: | 145 |
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| Downloads: | 13 |
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| Metadata: |    |
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| Categories: | Misc.
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