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Saudi Arabia (SA) is amongst the few countries with a significant foreign workforce who are employed in the higher education sector. More specifically, 39% of SA's academic staff members are foreign nationals and 63% of that proportion occupy professorial positions. Drawing from a workforce localisation perspective, the study was framed as an exploration of equity and social justice amongst Saudi nationals and foreign nationals in a university work setting. The authors employ the lens of how human resource development (HRD) opportunities are administered.

Following the choice of an exploratory qualitative study, the authors employed a multi-case study approach where each of the six universities represented a unit of analysis.

The authors found that nationality differences influenced access to HRD opportunities. These differences are reinforced by practices associated with procedural processes, managerial discretion and selective restrictions in accessing HRD opportunities.

The findings have both practical and social implications, specifically for the SA government's strategic vision of developing local human capabilities.

The workforce localisation agenda within the higher education sector has both a compounding effect on local human capital and supports SA's 2030 Vision and human capital target. Nonetheless, perceived inequity and injustice in accessing HRD opportunities by foreign nationals potentially undermine morale, academic quality standards and research performance, which impacts the development of future human capital and the ‘Saudization’ goals.

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.

This study aims to explore the effect of Saudi Vision 2030 and its government initiatives on macroeconomic variables related to housing.

This exploratory study used an empirical–analytical approach. Based on secondary data, a set of hypotheses was contrasted to verify whether there has been any change in the trends of macroeconomic variables related to housing after Saudi Vision 2030 entered into force.

The results show that the trend of percentage of housing ownership went from a continuous decrease to accelerated growth since the implementation of Saudi Vision 2030. However, the effect of these advances is not observed in non-oil gross domestic product (GDP) or in the economic activities of the construction, real estate and financial services sectors.

This study notes that despite successful housing outcomes, it appears that Saudi Vision 2030 does not have a positive impact on non-oil GDP. Consequently, government entities should review the degree to which other economic activities contribute to non-oil GDP. A limitation of the study was that the GDP of housing construction and marketing and that of granting mortgage loans were not specifically available, nor were data on public and private investment made for implementing government initiatives.

To the best of the authors’ knowledge, this is the first study to explore the effect of Saudi Vision 2030 on housing and its contribution to the economy.

Traditional level inverter technology has drawbacks in the aspect of Total harmonic distortion (THD) and switching losses for higher frequencies. Due to these drawbacks, two-level inverters have become unprofitable for high-power applications. Multilevel inverters (MLIs) are used to enhance the output waveform characteristics (i.e. low THD) and to offer various inverter topologies and switching methods.

MLIs are upgraded versions of two-level inverters that offer more output levels in current and voltage waveforms while lowering the dv/dt and di/dt ratios. This paper aims to review and compare the different topologies of MLI used in high-power applications. Single and multisource MLI's working principal and switching states for each topology are demonstrated and compared. A Simulink model system integrated using detailed circuit simulations in developed in MATLAB®–Simulink program. In this system, a constant voltage source connected to MLI to feed asynchronous motor with squirrel cage rotor type is used to demonstrate the efficacy of the MLI under different varying speed and torque conditions.

MLI has presented better control and good range of system parameters than two-level inverter. It is suggested that the MLIs like cascade-five-level and NPC-five-level have shown low current harmonics of around 0.43% and 1.87%, respectively, compared to two-level inverter showing 5.82%.

This study is the first of its kind comparing the different topologies of single and multisource MLIs. This study suggests that the MLIs are more suitable for high-power applications.

Switching power converters for photovoltaic (PV) applications with high gain are rapidly expanding. To obtain better voltage gain, low switch stress, low ripple and cost-effective converters, researchers are developing several topologies.

It was decided to use the particle swarm optimization approach for this system in order to compute the precise PI controller gain parameters under steady state and dynamic changing circumstances. A high-gain q- ZS boost converter is used as an intermittent converter between a PV and brushless direct current (BLDC) motor to attain maximum power point tracking, which also reduces the torque ripples. A MATLAB/Simulink environment has been used to build and test the positive output quadratic boost high gain converters (PQBHGC)-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. The simulation results show that the PQBHGC-3 topology is effective in comparison with other HG cell DC–DC converters in terms of efficiency, reduced ripples, etc. which is most suitable for PV-driven BLDC applications.

The simulation results have showed that the PQBHGC-3 gives better performance with minimum voltage ripple of 2V and current ripple of 0.4A which eventually reduces the ripples in the torque in a BLDC motor. Also, the efficiency for the suggested PQBHGC-3 for PV-based BLDC applications is the best with 99%.

This study is the first of its kind comparing the different topologies of PQBHGC-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. This study suggests that the PQBHGC-3 topology is most suitable in PV-driven BLDC applications.

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.

This study aims to empirically investigate the impact of oil prices, political instability and changes in stability on the bank diversification of the two types of banking systems in the Middle East and North African (MENA) countries.

The study uses bank diversification, stability measurement of probability of default and Zscore by adopting the generalised method of moment for the data between 2007 and 2021. The authors estimate short- and long-run dynamic panel analysis and a robustness test.

The findings reveal that Islamic banks are slightly lower in diversification and stability than conventional peers in the region. Diversification increases with a positive increase in GDP growth, law and order, political stability, bank size, asset quality, oil price, return on equity, profitability and change in banking asset-based stability. The authors found consistency in the two stability measurements in both short- and long-run situations.

Despite the change in banking stability and economic growth and oil prices improved diversification, banks in the region are not diversifying during the crisis period and political instability. Therefore, policymakers should improve mechanisms to monitor the crisis and political unrest to avoid the systemic risk that adversely affects the system through macro-financial linkages in the region.

This study uses change dual stability measurements and oil prices to predict MENA region bank diversification. The authors extended the banking literature by estimating the relationship between crisis periods, political and banking stability, oil prices and other institutional indicators of banking diversification. This study uncovers the effect of the global crisis period on banking diversification and the impact of banking stability changes and validates the models through robustness tests.

This study aims to uncover the main predictors of financial distress in the Gulf Cooperation Council (GCC) countries using a wide range of global factors and asset classes.

This study uses novel approaches that take into account extreme events as well as the nonlinear behavior of time series over various time intervals (i.e. short, medium and long term) and during boom and bust episodes. This study primarily uses the conditional value at risk (CoVaR), the quantile multivariate causality test and the partial wavelet coherence method. The data collection period ranges from March 2014 to September 2022.

US T-bills and gold are the primary factors that can increase financial stability in the GCC region, according to VaRs and CoVaRs. More proof of the predictive value of the oil, gold and wheat markets, as well as geopolitical tensions, uncertainty over US policy and volatility in the oil and US equities markets, is provided by the multivariate causality test. When low extreme quantiles or cross extreme quantiles are taken into account, these results are substantial and sturdy. Lastly, after adjusting for the effect of crude oil prices, this study’s wavelet coherence results indicate diminished long-run connections between the GCC stock market and the chosen global determinants.

Despite the implications of the author’s research for decision makers, there are some limitations mainly related to the selection of Morgan Stanley Capital International (MSCI) GCC ex-Saudi Arabia. Considering the economic importance of the Kingdom of Saudi Arabia (KSA) in the region, the author believes that it would be better to include this country in the data to obtain more robust results. In addition, there is evidence in the literature of the existence of heterogeneous responses to global shocks; some markets are more vulnerable than others. This is another limitation of this study, as this study considers the GCC as a bloc rather than each country individually. These limitations could open up further research opportunities.

These findings are important for investors seeking to manage their portfolios under extreme market conditions. They are also important for government policies aimed at mitigating the impact of external shocks.

This study aims to empirically investigate the impact of political instability on the banking stability of the dual banking system in the Middle East and North African (MENA) countries.

The study measures banking stability with probability of default (PD) and Zscore by employing the generalised method of moment (GMM) between 2007 and 2021 on the dual banking system in the region. The authors further estimate short-long-run situations coupled with a robustness test using a generalised least square (GLS) model.

The authors' findings indicate that institutional factors of political stability, crisis period, high-crisis countries, law and order and macroeconomic indicators influence the two types of banking stability in the region. The authors found the consistency of the factors explaining stability in the region in both short-and long-run situations. Consequently, the study also reveals the adverse effects of crisis periods and high-crisis countries on banking stability.

The results of this study explicitly identify the critical need for sustaining political stability and abiding by laws and order to achieve dual banking stability in the region. Therefore, policymakers may consider allowing the region's banks to operate beyond retail banking since diversification enhances banking stability.

The authors' study balances by employing dual stability measurement in predicting the impact of political instability, law and order and other indicators on the MENA region's two banking models. This study uncovers the effect of the global crisis period on banking stability and high-crisis countries in the region and verifies the models' robustness.

This paper aims to empirically investigate the asymmetrical relationship between changes in oil price and the banking stability of the conventional and Islamic banks in the Middle East and North African (MENA) countries.

This paper measures banking stability with Z-score and probability of default using the Generalized Method of Moment. This paper selects a sample of conventional and Islamic banks operating within the MENA oil-producing states between 2008 and 2016.

The result of this paper reveals that the banking stability of the two types of banks responds to positive and negative shocks in oil prices. Thus, the stability of conventional banks is slightly better than that of Islamic banks in the region. Consequently, this paper also reveals that bank capitalization improves with the banking stability of the two banking systems in the region.

The findings of this paper will help the banks in the MENA oil-producing countries with strategies for improving banking stability during the oil price fluctuations and provide the policymakers with possible time for bank capital reform.

This paper explores the impact of the international oil price shocks on Islamic and conventional banks in one of the essential global oil-producing regions. As such, this paper extends the banking stability literature by accounting for the role of oil shock prices on banking distance and the probability of default. To the best of the authors’ knowledge, this is the first investigation of different transmission channels of oil price fluctuations in the region while considering the dual banking system in the hub of Islamic banks.