Exploring the implications of corporate governance practices and frameworks for large-scale business organisations: A case study on the Kingdom of Saudi Arabia

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.In 2006 the Kingdom of Saudi Arabia (KSA) introduced new legislation related to corporate governance (CG). Initial evaluation by the World Bank three years later showed relatively modest implementation of the regulations. This thesis investigates the extent to which this has been adopted over the past ten years. Saudi business has become more globalized, and a more standardised approach to CG is naturally expected by international partners and investors who must themselves justify investment.. This research expands the existing literature on CG by examining the progress of countries with developing economies and relatively weak or new histories of regulated CG. This thesis explores the extent and form of the uptake of the newest generation of CG regulations, the existing roadblocks and the general current attitudes to corporate governance in KSA, examining the extent of KSA company compliance with KSA corporate governance regulations, the reasons for non-compliance when that exists, and any relevant deficits in the 2006 legislation with respect to international best practice. This is investigated through the use of a series of interviews and surveys with major Saudi organizations, as well as analysis of secondary information. The mixed method approach of quantitative and qualitative data analysis was selected as providing a means to generate both benchmarking data (i.e. quantitative) and further insight as to obstacles for further adoption (i.e. qualitative). As the basis for the investigation, questions are structured around four basic pillars of corporate governance: transparency; stakeholder value; responsibility; and fairness. This linkage of these factors with organisational structure, decision-making and the overall image of the firm within the industry is combined with an examination of how CG affects Saudi business expansion and investments, particularly in relation to how parties from other countries perceive the governance of a company. This perception of governance may condition their views concerning, for example, partnering with and investing in that company. The secondary data relates to The Saudi Arabian Monetary Agency (SAMA), Sanabil Investments and Saudi Arabia Basic Industries Corporation (SABIC). The qualitative data analysis was taken from interviews conducted from fifteen top managers of large-scale organisations. The quantitative data was collected from three organisations: Almarai, Saudi Aramco and Albaik. The overall results of the qualitative analysis and the secondary analysis showed that CG plays a vital role in business development. Quantitative analysis supported the idea that transparency, stakeholder value and corporate image are the main attributes of CG in a Saudi context, with statistical analysis indicating that both are essential to company access to private investment and market liquidity The overall findings indicate KSA’s need to improve its CG standards further, and taht whilst benchmarking of government-supported institutions such as SAMA and SABIC would be of assistance, the KSA government could play a pro-active role in encouraging businesses to expand best international corporate governance practices

Two-stage PCR assay for detection of human brucellosis in endemic areas

BACKGROUND: Brucellosis is a common zoonosis that can cause a severe febrile illness in humans. It constitutes a persistent health problem in many developing countries around the world. It is one of the most frequently reported diseases in Saudi Arabia and incidence is particularly high in the Central region, and around the city of Riyadh. The aim of this study was to evaluate a two-stage PCR assay for detection of human brucellosis particularly in endemic areas. METHODS: A total of 101 serum samples were collected from patients with acute febrile illness (AFI) of unknown cause from two different locations in the Western region of Saudi Arabia. The first location (Northern) is characterized by a nomadic rural population while the second (Central) is a modern urban city. All samples were subjected to DNA extraction and Brucella genus-specific PCR amplification using B4/B5 primers of the bcsp31 gene. Positive B4/B5 samples were subjected to multiplex species-specific Brucella PCR amplification. RESULTS: In the Northern location, 81.9% of the AFI samples were confirmed Brucella positive, while all the samples collected from the Central region proved to be Brucella negative. Samples positive for Brucella were subjected to multiplex species-specific Brucella amplification. B. abortus was detected in 10% and B. melitensis in 8% of the samples, while the majority (82%) of samples showed both B. abortus and B. melitensis. As expected, B. suis was not detected in any of the samples. CONCLUSIONS: This study concluded that a two-stage PCR assay could be useful as a rapid diagnostic tool to allow the consideration of brucellosis as a possible cause of AFI, particularly in non-urban locations. It also recommends the collection of epidemiological data for such patients to obtain further information that may help in rapid diagnosis

Diversity of fungi in bottled water in Jeddah, Saudi Arabia

The occurrence of fungi in drinking water systems has received increased attention over recent decades and fungi are now generally accepted as drinking water system contaminants. However, fungal contamination of bottled water has received little attention. Forty unopened bottled water samples, of different trademarks, were collected from various localities in Jeddah city, Saudi Arabia and analyzed for fungal contamination: 1) immediately after opening the bottles; and 2) after closing and storing them for 180 and 365 days. The fungal species were identified under a compound microscope followed by molecular sequencing. At least one fungal species were found in 58% of the bottles. In total, 18 fungal species belonging to 11 fungal genera were identified. Rhizopus nigricans and seven different species of Aspergillus were found to frequently contaminate the bottled water samples. Penicillium sp. were found in one sample. The 180 days storage of opened and reclosed bottles did not substantially affect the abundance of fungi or the species found. Some of the fungi identified may be pathogenic and the contamination of fungi in bottled water should be considered during the processing of water

An information security governance framework for the organisations in the kingdom of Saudi Arabia

Due to the ever-changing threats to the confidentiality, integrity and availability of information in an organisation, information security should be addressed from the highest level of the organisation and regarded as a governance challenge that needs effective direction and control. Consequently, information security governance has become essential for organisations to ensure objectives are achieved, risks are managed appropriately, and resources are used responsibly. Although organisations in the Kingdom of Saudi Arabia acknowledge the importance of governing information security for their ability to survive and thrive, there is inadequate implementation of information security governance in the majority of organisations. The absence of the crucial practices for the successful implementation of information security governance addresses the need to investigate the critical success factors for such implementation in the Saudi Arabian organisations. Therefore, this research has developed a framework to support the implementation of information security governance and the Kingdom of Saudi Arabia’s vision of a thriving economy for 2030. The factors in this framework were identified by reviewing the literature as well as industrial best practice frameworks. Based on the review conducted, the proposed framework was developed to understand the practices required to direct and control information security within the governance areas for the organisations to survive and thrive. Once the framework was developed, it was reviewed by interviewing 15 information security governance experts from the Kingdom of Saudi Arabia. After updating the framework according to their recommendations, the framework was confirmed by distributing a questionnaire to 33 practitioners from Saudi organisations. The findings revealed that the factors were statistically significant. Driving from the confirmed framework, an information security governance maturity assessment instrument was developed to measure the maturity level of information security governance implementation in organisations. The instrument was developed by using the Goal Question Metrics approach, after which the instrument content was validated by using the Content Validity Ratio. Subsequently, case studies were conducted in four Saudi organisations in order to evaluate the practicality of the developed instrument. The instrument was used to assess the maturity status of information security governance in Saudi organisations that have started governing their information security as a part of their corporate governance. Afterwards, the practicality of the instrument was evaluated through a questionnaire that was distributed to the committee members who used the instrument and through interviews with the Information Security directors. The findings validate a good level of practicality for the instrument in measuring the maturity of information security governance. This thesis presents a detailed discussion on the development and validation of the information security governance framework and the information security governance maturity assessment instrument

Bayesian and non-bayesian estimation of stress-strength model for Pareto type I distribution

Abstract This article examines statistical inference for where X and Y are independent but not identically distributed Pareto of the first kind (Pareto (I)) random variables with same scale parameter but different shape parameters. The Maximum likelihood, uniformly minimum variance unbiased and Bayes estimators with Gamma prior are used for this purpose. Simulation studies which compare the estimators are presented. Moreover, sensitivity of Bayes estimator to the prior parameters is considered

Urban foodprints (UF) – Establishing baseline scenarios for the sustainability assessment of high-yield urban agriculture

Allowing for significant water savings and year-round yields, Controlled-Environment Agriculture (CEA) is oftentimes portrayed as a sustainable alternative to conventional farming, and its practice in urban areas as a food, income and employment generator is expanding worldwide. Particularly in today's fast growing cities, where economic strength is buying food security through imports, a largescale implementation of such practices should be further investigated as potential contributors - not only to food security but also to self-sufficiency - for the production of horticultural crops. However, further than quantifying the potential for food self-sufficiency of cities through urban cultivation, there is a crucial need for assessing the extent to which such scenarios are effectively more sustainable than existing supply chains. For that purpose, this paper presents the Urban Foodprints (UF) methodology, a fundamental preliminary step in the sustainability assessment of high-yield urban agriculture, consisting of collecting and integrating data on the existing supply chain, to be used as a baseline scenario in the environmental performance analysis. Through the case of Riyadh, Saudi Arabia, where harsh climatic conditions, a heavy reliance on food imports and a growing population constitute major threats to food security, the UF method is described and applied to the top four consumed horticultural crops - watermelon, tomato, onion and carrot. The environmental sustainability of high-yield urban agriculture in Riyadh is subsequently assessed for tomato, as a comparison of the resulting city's current foodprint for the crop vs. a scenario of local production in CEA urban farms. Results show that urban production in high-yield greenhouses has the potential to reduce Global Warming Potential (GWP) by 9%. However, while water savings contribute greatly to reducing irrigation-related emissions and food miles are considerably reduced, the energy needs of the greenhouses are significantly higher than the baseline. This outcome may be improved by enhancing the envelope of the farms to reduce overheating. Keywords: baseline scenario; Controlled-Environment Agriculture (CEA); sustainability assessment; Urban Foodprint; urban food syste

Generative Adversarial Networks-Based Novel Approach for Fraud Detection for the European Cardholders 2013 Dataset

Credit card use poses a significant security issue on a global scale, with rule-based algorithms and traditional anomaly detection being two of the most often used methods. However, they are resource-intensive, time-consuming, and erroneous. Given fewer instances than legal payments, the dataset imbalance has become a serious issue. On the other hand, the generative technique is considered an effective way to rebalance the imbalanced class issue, as this technique balances both minority and majority classes before the training. In a more recent period, GAN is considered one of the most popular data generative techniques, as it is used in significant data settings. Hence, the research under study explores a classification system to detect fraudulent credit card transactions that are being trained using the European Cardholders 2013 dataset. It has 30 features, 28 of which are hidden due to sensitive information. Fraud activity accounts for less than 1% of the entire transaction volume of ${\$}$ 284807. Additionally, GANs is a generative model based on game theory, in which a generator G and a discriminator D compete with one another. The generator’s goal is to make the discriminator uncertain. Distinguishing between instances from the generator and those from the original dataset is the discriminator’s goal, and we can increase classifiers’ discriminating strength by training GANs on a set of fraudulent credit card transactions. According to the outcome, our model outperformed the earlier experiments with an AUC score of 0.999. Additionally, it creates artificial data using GANs, enabling the production of a sizable volume of high-quality data. In terms of innovation and performance, this technique substantially improves over earlier research