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The main purpose of this research is to produce the most accurate theoretical framework of the potential threat of cyberterrorism to the national security, compared to conventional terrorism. So it aims to identify the theoretical framework that best explains the threat of cyberterrorism and conventional terrorism to national security derived from empirical data, using grounded theory, and to validate the developed grounded theory statistically by quantitative data.

This paper presents the results of the quantitative study survey. It provides in the beginning basic information about the data. To purify the data, reliability and exploratory factor analysis, as well as confirmatory factor analysis (CFA), were performed. Then, structural equation modelling was utilised to test the final model of the theory and to assess the overall goodness-of-fit between the proposed model and the collected data set.

The first study, as a qualitative exploratory study, gives a rich data set that provides the foundation of the development of the second study, as a quantitative confirmatory study. In the researcher’s previous qualitative study, it provides a better theoretical understanding of the potential threat of cyber and conventional terrorism to Saudi national security. Also, it provides the development of the grounded theory of the study (Figure 1). It also has led to the development of the conceptual framework and the hypotheses for the second phase of the study (i.e. survey).

It is original study based on empirical data collected from Saudi military and security officials and experts in the critical infrastructures.

The purpose of this paper is to explore the people’s perceptions of sustainable housing in Saudi Arabia using Riyadh as a case study. Riyadh was chosen as a case study for two reasons: it is the capital city of Saudi Arabia and the largest city in the country; and there are no major differences between the characteristics of people in Riyadh and other major Saudi cities.

The questionnaire survey technique was used in this study to achieve the main purpose. The study used descriptive statistics (frequency, percentage) with the aid of the Statistical Package of Social Science Software (SPSS) to analyze the data.

The findings reveal that there is a lack of people’s awareness about the sustainable housing. However, it shows a positive response regarding people’s willingness to live in sustainable housing in the future as well as to adjust their current houses to be more environmentally friendly houses.

The thoughts of stakeholders who are involved in the housing field, including policymakers and real estate developers, are very significant, however, due to the time limitation it has not been explored in this study. Therefore, future research is recommended to investigate the opinions of different stakeholders to have better insights for delivering sustainable housing.

The study contributes to exploring the people’s perceptions of sustainable housing in Saudi Arabia using Riyadh as a case study. Only a few studies have discussed this issue, so this study was conducted to bridge this research gap and build upon the literature.

The purpose of this paper is to identify the obstacles to the availability of suitable housing units for various socioeconomic segments of society with an emphasis on single-family homes, which is the most preferred housing type in the Saudi society.

To achieve the aim of this paper, the Delphi method was used to explore the experts’ opinions on the most important obstacles.

The findings of the study underline 17 different obstacles affecting the availability of suitable housing units for various segments of the Saudi society. The most critical obstacle is the high cost of land followed by the low income of the families, high cost of construction, high interest rate of mortgages and shortage of suitable residential lands.

The study concludes with a number of proposed recommendations that can contribute to address the current shortage of suitable housing units.

The purpose of this paper is to discuss the housing delivery within the Saudi Vision 2030 through an in-depth reading of the Saudi Vision 2030 from the researcher’s point of view and to identify the most significant aspects that may affect housing delivery in the country.

In this study, the desktop study technique was followed to review the key related literature, collect the data and analyze secondary data. The content analysis technique was used for data analysis of gathered documents and secondary data.

The findings reveal that there are several commitments in the Saudi Vision 2030 from the Saudi Government to be an exemplary leading nation in all aspects, including the delivery of affordable housing. Housing shortage, housing cost, demographic changes and land scarcity are identified as significant reasons for the lack of providing affordable housing.

The opinions of policymakers is very important, but due to time limitation, it has not been addressed. Future research can assess the Saudi Vision 2030 based on the study of the policymakers, professionals and academics to have better insights.

The paper contributes to discussing the housing delivery within the Saudi Vision 2030 and identifying the most significant aspects that may affect the housing delivery from the researcher’s point of view. Only a few studies have discussed the housing issues within the Saudi Vision 2030.

The purpose of this paper is to formulate a number of housing policies to address these two issues and meet the needs of Saudi families, in accordance with their social and economic characteristics.

The paper first provides a review of the housing policies in Saudi Arabia, highlights some of the global experiences in the field of housing and reviews the best lessons learned from those experiences. Then, the paper analyses the reality of the housing sector in Dammam Metropolitan Area (DMA) and discusses the most important results reached.

Finally, and based on the main findings, the paper puts forward a set of policies and actions recommended to improve housing sector in DMA.

The paper analyses the reality of the housing in DMA.

The purpose of this study is to identify the preferred characteristics of buyers of single-family homes in Saudi Arabia with an emphasis on the city of Dammam.

Data were collected using face-to-face structured interviews conducted from November 2016 to May 2017 with 177 owners of single-family homes that were purchased between 2010 and the first quarter of 2017.

The findings indicate that homes can be divided into three types: villas, detached duplexes and semi-detached duplexes. Also, more than three-quarters of the respondents purchased their homes through mortgages from either lenders or the government. It seems we find that the advantages of the detached duplex, particularly its privacy level, over other types of single-family homes induce homebuyers to choose this home type.

In this study, the authors analyze housing preferences among various segments of the Saudi society, in the city of Dammam, to understand the housing supply in Saudi Arabia. Only a few studies have investigated the preferences of homebuyers in Saudi Arabia. Below the authors provide a literature review, discuss data and methods and results, as well as provide concluding remarks.

Buildings are major contributors to greenhouse gases (GHG) along the various stages of the building life cycle. A range of tools have been utilised for estimating building energy use and environmental impacts; these are time-consuming and require massive data that are not necessarily available during early design stages. Therefore, this study aimed to develop an Environmental Impacts Cost Assessment Model (EICAM) that quantifies both energy and environmental costs for residential buildings.

An Artificial Neural Network (ANN) was employed to develop the EICAM. The model consists of six input parameters, including wall type, roof type, glazing type, window to wall ratio (WWR), shading device and building orientation. In addition, the model calculates four measures: annual energy cost, operational carbon over 20 years, envelope embodied carbon and total carbon per square metre. The ANN architecture is 6:13:4:4, where the conjugate gradient algorithm was applied to train the model and minimise the mean squared error (MSE). Furthermore, regression analysis for the ANN prediction for each output was performed.

The MSE was minimised to 0.016 while training the model. Also, the correlation between each ANN output and the actual output was very strong, with an R² value for each output of almost 0.998. Moreover, validation was conducted for each output, with the error percentages calculated at 0.26%, 0.25%, 0.03% and 0.27% for the annual energy cost, operational carbon, envelope materials embodied carbon and total carbon per square metre, respectively. Accordingly, the EICAM contributes to enhancing design decision-making concerning energy consumption and carbon emissions in the early design stages.

This study provides theoretical implications to the domain of building environmental impact assessment through illustrating a systematic approach for developing an energy-based prediction model that generates four environmental-oriented outputs, namely energy cost, operational energy carbon, envelope embodied carbon, and total carbon. The model developed has practical implications for the architectural/engineering (A/E) industries by providing a useful tool to easily predict environmental impact costs during the early design phase. This would enable designers in Saudi Arabia to make effective design decisions that would increase sustainability in the building life cycle.

By providing a holistic predictive model entitled EICAM, this study endeavours to bridge the gap between energy costs and environmental impacts in a predictive model for Saudi residential units. The novelty of this model is that it is an alternative tool that quantifies both energy cost, as well as building’s environmental impact, in one model by using a machine learning approach. Besides, EICAM predicts its outcomes more quickly than conventional tools such as DesignBuilder and is reliable for predicting accurate environmental impact costs during early design stages.

The purpose of this paper is to identify the students’ attitudes towards private sector work during study.

This study used a comprehensive social survey (including questionnaire and interviewing) distributed to experts in departments and colleges in King Saud University and Princess Nora University.

This study found that students’ attitudes can be influenced by the financial and social security achieved through private work during study, and the personal development of job skills. Whereas society’s inferior view to private work, study and working hours’ conflicts, and the insufficient information about private work during study are some of the negative factors that influence their attitudes. It also emphasised the role of the private sector in influencing such attitudes by advertising job opportunities for students, giving them flexible work hours and providing training programmes. This study concludes with a proposal suggesting how to modify students’ attitudes towards private sector work during study.

This paper identifies the students’ attitudes towards private sector work during study and suggests a proposal that contributes to support students’ positive attitudes and adjust the negative ones; thus, helping to reduce the unemployment rate among young people.

Spam emails classification using data mining and machine learning approaches has enticed the researchers' attention duo to its obvious positive impact in protecting internet users. Several features can be used for creating data mining and machine learning based spam classification models. Yet, spammers know that the longer they will use the same set of features for tricking email users the more probably the anti-spam parties might develop tools for combating this kind of annoying email messages. Spammers, so, adapt by continuously reforming the group of features utilized for composing spam emails. For that reason, even though traditional classification methods possess sound classification results, they were ineffective for lifelong classification of spam emails duo to the fact that they might be prone to the so-called “Concept Drift”. In the current study, an enhanced model is proposed for ensuring lifelong spam classification model. For the evaluation purposes, the overall performance of the suggested model is contrasted against various other stream mining classification techniques. The results proved the success of the suggested model as a lifelong spam emails classification method.

Islamic finance has exhibited immense potential to transform the global financial landscape in the recent years. In reaction to the trend, Nigeria introduced Islamic banking system to cater to the need of the teeming population and promote financial inclusion, among other potential benefits. Unfortunately, the notable growth recorded by the banks since the inception of the Islamic banking system is slowing down because of religiously induced sentiments and criticisms championed by certain non-Muslim segments of the society. Interestingly, even with the impish hype and publicity, non-Muslims make a significant customer base of the Islamic banks. Therefore, the current paper aims to investigate the factors influencing the choice of Islamic banking among non-Muslim customers, using the theory of planned behaviour as a conceptual framework.

This research adopts a positivist approach and relies on facts and quantitative data in an objective manner. Positivism emphasizes on using scientific methods to derive factual and quantifiable results.

Based on the regression analysis, subjective norm was found to be the most significant factor influencing the choice of Islamic banking followed by perceived behavioural control and attitude. As a result, it is important for Islamic banking institutions and relevant regulatory agencies to take preemptive measures that may protect and enhance these factors in a bid to promote patronage and eventual success of Islamic banking in Nigeria, especially in the face of growing scepticism.

The existing literature focuses on the choices of either Muslims without due emphasis on the determinant of choice in the case of non-Muslim customers. The growing support of Islamic banking products, cutting across religious divides, compels research on the factors that influence the choice of Islamic banking among non-Muslim customers. Hence, this research seeks to bridge the gap in the existing literature by embarking on an investigation into the factors influencing the choice of Islamic banking among non-Muslim customers in the context of Nigeria.