Saudi Cultural Missions Theses & Dissertations
Permanent URI for this communityhttps://drepo.sdl.edu.sa/handle/20.500.14154/10
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Item Restricted Barriers to The Participation of Women in Sports Leadership Roles: A Qualitative Design in Saudi Arabia(Loughborough University, 2024-09-17) Nahari, Shaden; Pullen, EmmaThis qualitative study investigates the barriers to women's participation in sports leadership roles in Saudi Arabia, focusing on the perceptions, beliefs, and lived experiences of women in leadership positions. Despite global progress in increasing opportunities for women in sports, their representation in leadership remains disproportionately low, particularly in Saudi Arabia. The study employs a social constructivist ontology, which acknowledges that the barriers to women's leadership are shaped by cultural, social, and individual factors. A qualitative design was chosen to explore these complex and nuanced experiences in depth. Five women currently or previously involved in sports leadership roles in Saudi Arabia were selected using purposive sampling. Data were gathered through semi-structured interviews, each lasting approximately 25 minutes. The interviews were transcribed verbatim and analysed using thematic analysis, which allowed for the identification and examination of key themes related to cultural, structural, and individual barriers to women's leadership. The study's findings highlight significant challenges, including work-family conflict, gender stereotypes, and the lack of mentorship and networking opportunities. These findings underscore the need for comprehensive policy reforms and targeted interventions to enhance gender diversity in Saudi sports leadership. The study provides valuable insights into the socio-cultural dynamics that limit women's leadership roles and offers recommendations for future research and policy development aimed at promoting gender equality in sports leadership.47 0Item Restricted Can diversity in the audit committee mitigate the risk of financial misconduct and corruption? An Overview of Saudi Arabia Regulations.(King's College University, 2024-09-01) Alkhathlan, Norah Rashed; Banerjee, NigelThis dissertation explores the impact of professional diversity within audit committees on mitigating financial misconduct and corruption, focusing mainly on Saudi Arabia's Regulation. Recognizing the critical role of maintaining financial integrity, this study investigates how diverse audit committee compositions might improve financial oversight and decrease unethical behaviors. The research methodology combines a review of past incidents of corporate misconduct with an analysis of the legal framework, complemented by an examination of annual reports from Saudi companies to analyze the expertise and backgrounds of audit committee members. The results indicate that a mix of financial, legal, and industrial expertise within audit committees strengthens their ability to detect and address risks associated with financial misconduct and corruption. The dissertation recommends restructuring audit committees to consist of five members: three with financial skills, one with legal qualifications, and one with industrial experience. This recommended configuration aim to enhance the committee's effectiveness in adhering to legal standards and protect financial integrity. However, acknowledging the varied nature of companies in Saudi Arabia, an exception is proposed for small companies.36 0Item Restricted How could HR practices be implemented in recruitment and selection to enable best practices towards diversity in organisations in Saudi Arabia?(Swansea University, 2024) Albalawi, Mohammed; Pritchard, KatrinaThis study explores the role of human resource (HR) practices in recruitment and selection to maximise diversity, including gender diversity, in organisations with a specific focus on Saudi Arabia. The research highlights the importance of diversity in enhancing innovation, creativity and organisational performance. It examines the formats in which cultural, legal, and organisational challenges impact the implementation of diversity strategies in the recruitment process. Drawing on theories such as Institutional Theory, Human Resource Management (HRM) Theory, and Diversity Management Theory, the research identifies the benefits of diverse workforces and the barriers posed by deeprooted cultural norms (e.g., gender roles and tribal affiliations). Through following systematic literature review methodology, this research included 60 studies. Key findings suggest that diversity promotes creativity and better decision-making; nevertheless, it indicated that achieving it in Saudi organisations requires overcoming societal bias and adapting global diversity practices to the local context. Moreover, the study explores the tension between merit-based and diversity-based recruitment, which has emphasised the need for HR managers to find a balance between fairness and inclusivity. Recommendations include adopting blind recruitment practices, creating inclusive job descriptions, providing diversity training for HR professionals and implementing targeted recruitment strategies. The research contributes to the existing literature by addressing the limited studies on diversity in recruitment and selection in Saudi Arabia, mainly in non-Western contexts. It identifies gaps in current practices and suggests areas for future research, like the exploration of other dimensions of diversity, as is the case in disability and age and the role of leadership in promoting inclusive HR practices. Thus, this study provides thoughts into the ways through which organisations could embrace recruitment and selection processes with diversity goals to create inclusive workplaces in Saudi Arabia.13 0Item Restricted Heterogeneous Machine Learning Ensembles for Predicting Train Delays(2023-06-07) Al Ghamdi, Mostafa; Wang, WenjiaTrain delays are a serious problem in the UK and other countries. Much research has gone into developing methods for predicting train delays. Most of these methods use only single models or homogeneous ensembles and their performance in terms of accuracy and consistency in general is unsatisfactory. We have therefore developed heterogeneous ensembles that use different types of regression models with an aim of improving their prediction performance. We first looked at a wide range of base-learner models, including the state-of-the-art methods, Random Forest and XGBoost. Overall, our ensembles were more accurate than any of these single models. We developed two methods for model selection when building the ensemble, the first uses accuracy and the second uses accuracy and diversity. We found that using accuracy resulted in the most accurate ensembles. We adapted the Coincident Failure Diversity measure for regression and compared its effectiveness with other diversity measures. While it proved the best, overall, we found no relationship between ensemble accuracy and diversity in the regression context. We also investigated the effect of ensemble size. We compared the performance of our ensembles with the deep learning methods CNN and Tabnet and found that our ensembles were more accurate. However, ensembles of deep learning models proved to be more accurate than those of single machine learning models. We tested our ensembles using a different set of train delay data and found that they produced more accurate and consistent results, indicating that our methods generalise well to new data.22 0