arbiter
JournalsPricingAccount

Transforming Entrepreneurship in Saudi Arabia

Jawaher Abdulrahman Alomar

International Journal of Electronic Government Research2026https://doi.org/10.4018/ijegr.405809article
ABDC C
Weight
0.50

What the paper says

Electronic government is critical for fostering innovation and entrepreneurship in rapidly evolving digital economies. Although prior research highlights the role of digital public services, the literature remains fragmented, offering limited insight into how digital government initiatives systematically enhance innovation performance. This study develops a strategic, multi-level framework of critical success factors influencing digital government capacity and performance, examining Saudi Arabia's Vision 2030 digital transformation using total interpretive structural modeling. Seven factors are identified: innovation capacity and performance, digital infrastructure, strategic partnerships, digital technology adoption, government digitalization efforts, entrepreneurial competence, and digital dynamic capabilities. Government digital transformation is the primary driver, while partnerships, infrastructure, institutional digitalization, and capacity building exert systemic effects.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.4018/ijegr.405809

Or copy a formatted citation

@article{jawaher2026,
  title        = {{Transforming Entrepreneurship in Saudi Arabia}},
  author       = {Jawaher Abdulrahman Alomar},
  journal      = {International Journal of Electronic Government Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.4018/ijegr.405809},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Transforming Entrepreneurship in Saudi Arabia

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

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

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
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.