A periodical analysis of e-government maturity in Saudi Arabia

Purpose Governments of the developing countries must be ready to embrace the evolution of information technology. However, the growth in demand for online services and expectations for convenient access to government resources are placing governments under pressure to deliver outstanding e-services. Despite the successful attempts of the Saudi Government to deliver e-government services, the literature still needs to be advanced with evidence to demonstrate the current status of government websites. Additionally, the growth of e-government services should be periodically monitored and evaluated. Design/methodology/approach This study aims to revisit e-government websites previously surveyed (2006-2012). in Saudi Arabia and examine growth based on the five-stage maturity model. This study supports the approach with a review of the United Nations data and links this assessment with the five-stage maturity model. Findings The results revealed remarkable improvements in the maturity level of online services provided by the government websites of Saudi Arabia. Practical implications The relationship between e-government use and investment decisions appears to be bidirectional, as greater levels of investment seem to offer more opportunities for service improvement. Originality/value The outcomes are expected to assist executive authorities in understanding the current situation of e-government and plan appropriate strategic suggestions and development.

A Mixed-Method Approach to Examining the Drivers and Outcomes of Citizens Trust towards e-government

This study investigates the antecedents and consequences of trust in e-government websites in Saudi Arabia. FSQCA and Structural equation modelling were used to analyse data collected from 504 participants. The findings indicate that our unified framework possesses some predictive ability regarding citizens' intentions to use e-government services, which was superior to existing theories. The findings indicate that (1) there is no sole factor that sufficiently motivates citizens to use e-government services; (2) three distinct settings of citizens' intention drivers are probable to lead in a significant level of citizens intending to use e-government services; and (3) Uncertainty avoidance has a moderating effect on citizens’, intention to use e-government services. The theoretical and practical implications were demonstrated.

Communicating Heat-Health Information to the Public: Assessing Municipal Government Extreme Heat Event Website Content

Extreme heat events pose a threat to human health. Forecasting and warning strategies have been developed to mitigate heat-health hazards. Yet, studies have found that the public lacks knowledge about their heat-health risks and preventive actions to take to reduce risks. Local governmental websites are an important means to communicate preparedness to the public. The purpose of this study is to examine information provided to the public on municipal government webpages of the 10 most populous U.S. cities. A two-level document and content analyses were conducted. A direct content analysis was conducted using federal government websites and documents to create the Extreme Heat Event Public Response Rubric. The Rubric contains two broad categories of populations and actions that are further specified. The Rubric was then used to examine local government extreme heat event websites for the 10 most populous cities in the U.S. The examination of the local government sites found that information included on the websites failed to identify the breadth of populations at greater risk for adverse heat-health outcomes and omitted some recommended actions designed to prevent adverse heat-health events. Local governments often communicated concrete and simple content to the public but more complex information was not included on their websites.

Enhanced Collaborative Filtering for Personalized E-Government Recommendation

The problems with the information overload of e-government websites have been a big obstacle for users to make decisions. One promising approach to solve this problem is to deploy an intelligent recommendation system on e-government platforms. Collaborative filtering (CF) has shown its superiority by characterizing both items and users by the latent features inferred from the user–item interaction matrix. A fundamental challenge is to enhance the expression of the user or/and item embedding latent features from the implicit feedback. This problem negatively affected the performance of the recommendation system in e-government. In this paper, we firstly propose to learn positive items’ latent features by leveraging both the negative item information and the original embedding features. We present the negative items mixed collaborative filtering (NMCF) method to enhance the CF-based recommender system. Such mixing information is beneficial for extending the expressiveness of the latent features. Comprehensive experimentation on a real-world e-government dataset showed that our approach improved the performance significantly compared with the state-of-the-art baseline algorithms.

Synthesis of health promotion concepts in children's palliative care

Background: Palliative care improves the health of children with a life-limiting condition and appears to draw implicitly on concepts shared with a model of health promotion. However, to date there has been no scrutiny about how this relationship may shape understanding about children's palliative care. Aim: To explore the influence of health promoting concepts on children's palliative care models, policies and guidelines. Data sources: Health and social care databases were searched for policies, models and guidelines published between 2000–2018. Additional searches of professional national and international healthcare websites, children's palliative care charities and UK and Ireland government websites were conducted. Methods: A best fit framework synthesis was used. Findings: A total of 55 policies and guidelines were reviewed for the framework synthesis. Eight themes were generated: (1) health promoting children's palliative care policy and guidelines; (2) planning ahead; (3) creating a supportive environment; (4) enabling coping and independence; (5) reorienting children's palliative care sectors; (6) the lengthening trajectory of need for support; (7) strengthening community engagement in children's palliative care; and (8) quality of life and value-based ideologies. Conclusion: The best fit framework synthesis confirmed a conceptual relationship between children's palliative care and health promotion. This is captured in a new model that will extend professionals' understanding.

Formulating a Health Sustainable Development Policy: How the Actors Handling the COVID-19 in Indonesia

This article aims to analyze the role of actors in COVID-19 control in Indonesia and identify sustainable development policies in the health sector. The significant impact of COVID-19 occurs in the health sector, so the critical primary role of the government is to formulate policies in the health sector to control COVID-19. This research used a descriptive qualitative method by analyzing the policies made and the role of actors in covid-19 control in the field of health. This research data uses secondary data from national and international journal articles, government websites, and national online media news during the COVID-19 pandemic. The technique of analyzing research data uses Vosviewer and Nvivo 12 plus software so that data visualization can be presented as a basis for formulating health development policies and how the role of actors in controlling COVID-19. This study indicates, 1) the pattern of health development policies in controlling COVID-19 still needs improvement in effectiveness and efficiency so that policies are right on target. 2) policies made in controlling COVID-19 in Indonesia are still not optimal, especially in integrating technology and other resources. 3) the government is not ready to control COVID-19; the role of other actors is still low in intensity in controlling COVID-19. Based on the research analysis it is important to formulate policies to control COVID-19 and identify its role. Thus, this research can provide a reference in formulating sustainable policies in controlling COVID-19 in the health sector.

Review on Phishing Attack Detection using Recurrent Neural Network

Phishing is a crime that involves the theft of personal information from users. Individuals, corporations, cloud storage, and government websites are all targets for the phishing websites. Anti-phishing technologies based on hardware are commonly utilised, while software-based options are preferred due to cost and operational considerations. Current phishing detection systems have no solution for problems like zero-day phishing assaults. To address these issues, a three-phase attack detection system called the Phishing Attack Detector based on Web Crawler was suggested, which uses a recurrent neural network to precisely detect phishing incidents. Based on the classification of phishing and non-phishing pages, it covers the input features Web traffic, web content, and Uniform Resource Locator (URL). Keywords: Attack detection, Recurrent Neural Network, Deep Learning.