From Digital Fragmentation to Digital State Capacity: Institutional, Regulatory, and Infrastructural Conditions for Digital Government Transformation in Libya
DOI:
https://doi.org/10.65420/sjphrt.v2i3.165Keywords:
Digital government, digital transformation, digital state capacity, e-government, Libya, TOE framework, public administrationAbstract
More contemporary research defines digital government not merely as the automation of administrative processes, but as a fundamental transformation in public sector governance. This paper investigates digital government development in Libya, a context characterized by institutional fragmentation, ambiguous regulatory environments, and infrastructural disparities. Adopting a PRISMA-based systematic review, this study integrates the Technology-Organization-Environment (TOE) framework with the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). We propose "Digital State Capacity" as a focal concept, identifying seven critical hierarchical domains: institutional coordination, regulatory preparedness, infrastructural resilience, skilled human capital, interoperable systems, cybersecurity, and public trust. The findings suggest that digital transformation in fragile states requires a sequential approach, where foundational governance and legislative clarity precede advanced service integration. This study provides a phased policy roadmap and an evaluation matrix to guide Libya’s transition from fragmented digital efforts to a cohesive, resilient digital state system.
References
[1] Alatresh, S. (2008). Design WAP-based to WEB-based patient emergency service system for Pusat Kesihatan Universiti (PKU) [Master’s thesis, Universiti Utara Malaysia].
[2] Alatresh, S. (2021). The adoption of cloud computing among private banks employees in Libya. International Journal of Mathematics and Computer Research, 11(9), 11-16.
[3] Alatresh, S., Atiya, M., & Moussa, S. (2022). The effect of technological factors on the adoption of cloud based e-banking among private banks employees in Libya. International Journal of Contemporary Management and Information Technology, 2(4), 11-16.
[4] AlSharaa, M. U., Alatresh, S., Mousa, M., & Negrat, K. (2026). The impact of digital transformation on the academic work of faculty members at Bani Waleed University. Journal of Scientific and Human Dimensions, 402-416.
[5] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340.
[6] Forti, Y. (2020). A New Model for eGovernment in Local Level Administrations in Libya [Doctoral dissertation, University of Gloucestershire].
[7] Hassan, M., Alsahaq, A., & Alatrash, S. (n.d.). A novel imputation-boosted technique to overcome the unrated items issue and improving the performance of collaborative filtering.
[8] Healy, P., Angus, S. D., Raschky, P., Ackermann, K., Lane, N., Li, W., & Huang, C. (2026). Digital State Capacity. arXiv preprint arXiv:2608.03221.
[9] OECD Publishing. (2020). The OECD digital government policy framework: Six dimensions of a digital government. Paris, France: OECD Publishing.
[10] Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372.
[11] Said, K. K., Rhaimi, C. B., & Alatresh, S. (2024). A review on melanoma skin cancer detection using deep learning. African Journal of Advanced Pure and Applied Sciences, 154-159.
[12] Said, K. K., Rhaimi, C. B., & Alatresh, S. (2024). Classification of skin cancer based on deep learning using convolutional neural networks–opportunities and vulnerabilities: A systematic review. Malaysian Journal of Industrial Technology, 8(3), 1-12.
[13] Said, K. K., Rhaimi, C. B., & Alatresh, S. (2024). Skin diseases discover based on artificial intelligence. Bani Walid University Journal of Human and Applied Sciences, 188-198.
[14] Shouran, Z., Khalifa, H. A., AlSharaa, M. U., Mousa, M., & Alatresh, S. (2025). AI-enhanced semantic IoT framework for smart city management information systems. Libyan Open University Journal of Applied Sciences, 01-07.
[15] Shouran, Z., Mousa, M., Alatresh, S., & AlSharaa, M. U. (2025). Security and privacy in the Internet of Things: Issues, challenges, and a deep learning-based intrusion detection framework. Bani Walid University Journal of Human and Applied Sciences, 10(4), 225-233.
[16] Shwehdy, A. B. (2025, May). Drivers and barriers in Libya’s e-government implementation: A case study. In Conference on Digital Government Research (Vol. 26).
[17] Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books.
[18] United Nations Department of Economic and Social Affairs. (2024). United Nations E-Government Survey 2024: Accelerating digital transformation for sustainable development—With the addendum on Artificial Intelligence. Stylus Publishing, LLC.
[19] United States Agency for International Development. (2022). Libya digital ecosystem country assessment (DECA). USAID. https://www.usaid.gov/libya
[20] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
[21] Wynn, M., Bakeer, A., & Forti, Y. (2021). E-government and digital transformation in Libyan local authorities. International Journal of Teaching and Case Studies, 12(2), 119-139.

