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Integrating IS success model with cybersecurity factors for e-government implementation in the Kingdom of Saudi Arabia

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 5 (2020)

DOI
10.11591/ijece.v10i5.pp4937-4955
ISSN
2722-2578, 2088-8708
Published
2020-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

The electronic government (E-Gov) Systems are currently getting recognized as an authentic strategically tool in delivering E-services. Considering the development of information system (IS) as well as the expanding of the internet-based applications in KSA, E-Gov has always been a significant aspect in delivering governmental services. This research has adopted the (IS) success model by both DeLone and McLean (D&M), moreover, it adopted technology acceptance model (TAM) with cybersecurity factors, both models were implemented to discover the status of the IS success then investigate cybersecurity aspects that impact the service efficiency and effectiveness in KSA. Consequently, this research aims to create a model to investigate the IS success model along with cybersecurity factors that influence E-Gov services effectiveness and usage. Therefore, a survey has been applied as the major data gathering approach; the survey has been distributed among 211 users of E-Gov services consistently. Moreover, all research findings were attained through a quantitative method using the structural equation modelling (SEM). Findings revealed that the constructs fundamental of the (IS) success model are strongly influencing users' satisfaction (US) of the E-Gov services; correspondingly, the fundamental constructs factors of cybersecurity with TAM appear to have a strong impacts on perceived risk (PR), in addition, both which affect the E-Gov services towards usage and effectiveness.

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Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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