Evaluating the Effectiveness of Digital Government in Supporting Female Entrepreneurial Performance in Saudi Arabia

Jawaher Abdulrahman Alomar

International Journal of Electronic Government Research2025https://doi.org/10.4018/ijegr.375427article
ABDC C
Weight
0.41

What the paper says

Female entrepreneurship is a key driver of economic growth, job creation, and social empowerment. Despite their importance, female entrepreneurs continue to face significant challenges. Previous research has looked into the factors that influence the success of female entrepreneurs, but there are few studies on how these factors interact, especially with digital government support. This study aims to bridge this gap by using total interpretive structural modelling (TISM) to investigate the role of digital government in increasing female entrepreneurship in Saudi Arabia. A literature review identified eight critical success factors (CSFs): digital government, family background, entrepreneurial attitude, start-up intent, social networks, self-efficacy, dynamic capabilities, and digital innovation. The study contributes to entrepreneurial self-efficacy, social capital, and institutional theories by incorporating these CSFs into a strategic framework. The findings have significant policy implications, particularly for Saudi Vision 2030, which aims to promote digital government assistance and sustainable female entrepreneurship.

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https://doi.org/https://doi.org/10.4018/ijegr.375427

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@article{jawaher2025,
  title        = {{Evaluating the Effectiveness of Digital Government in Supporting Female Entrepreneurial Performance in Saudi Arabia}},
  author       = {Jawaher Abdulrahman Alomar},
  journal      = {International Journal of Electronic Government Research},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.4018/ijegr.375427},
}

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.