Cross-sectional time series models for identifying the most important factors of e-government growth in Arab countries

The goal of this study was to determine the key elements driving the expansion of e-government in Arab nations. One of the econometric models—the cross-sectional time series model (panel)—was employed to accomplish the intended outcome. The following techniques were used to estimate the models: fixed effects model, random effects model, and linear panel data regression analysis. The results revealed that e-government is negatively affected by political stability and the absence of terrorism and violence (PV), positively affected by government effectiveness (GE), positively affected by regulatory quality (RQ), and positively affected by the rule of law (RL).

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Publication Details

Journal
Iraqi Journal for Computers and Informatics
Published
2025-04-12
DOI
https://doi.org/10.25195/ijci.v51i1.541
Primary Topic
Innovation Diffusion and Forecasting
Type
article
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article

Cross-sectional time series models for identifying the most important factors of e-government growth in Arab countries

Ban Qasim Al nidawy
Iraqi Journal for Computers and Informatics
Innovation Diffusion and Forecasting
article

Cross-sectional time series models for identifying the most important factors of e-government growth in Arab countries

Ban Qasim Al nidawy
article en

Abstract

The goal of this study was to determine the key elements driving the expansion of e-government in Arab nations. One of the econometric models—the cross-sectional time series model (panel)—was employed to accomplish the intended outcome. The following techniques were used to estimate the models: fixed effects model, random effects model, and linear panel data regression analysis. The results revealed that e-government is negatively affected by political stability and the absence of terrorism and violence (PV), positively affected by government effectiveness (GE), positively affected by regulatory quality (RQ), and positively affected by the rule of law (RL).

Iraqi Journal for Computers and InformaticsVol. 51(1)
University of Information Technology and Communications (IQ)
Openalex Percentile: Top 92%
Innovation Diffusion and Forecasting
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