Saudi Cultural Missions Theses & Dissertations
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Item Restricted The Role of Artificial Intelligence in Personalising the Recruitment Process in Saudi Arabia: A Systematic Literature Review(Swansea University, 2024-09-29) Alotaibi, Mohammed; Balaussa, ShaimakhanovaArtificial intelligence (AI) has revolutionised various industry sectors, including human re- sources (HR),by enhancing decision-making, automating tasks, and improving efficiency. In the Kingdom of Saudi Arabia, the adoption of AI in HR is increasing, particularly in recruitment processes. This study explores how AI is transforming recruitment in Saudi Arabian organisations, highlighting the benefits and challenges associated with its im- plementation. AI-driven recruitment tools can streamline candidate screening, improve decision-making by analysing large datasets, and enhance the overall candidate experi- ence through personalisation. However, the study also identifies significant challenges, such as the need for AI systems to align with local cultural norms, legal requirements, and data privacy regulations. Moreover, the limited availability of skilled professionals to manage AI technologies and concerns about bias in AI-driven decisions are notable barriers. The research emphasises the importance of understanding employees’ and HR professionals’ perceptions of AI, particularly in terms of trust, acceptance, and effec- tiveness. By applying frameworks such as the technology acceptance model (TAM) and employee engagement theory, this study aims to assess AI’s impact on recruitment, fo- cusing on personalised onboarding experiences and strategic workforce planning in Saudi Arabia. The findings suggest that despite existing challenges, AI holds significant po- tential to optimise HR operations and contribute to organisational success, aligning with Saudi Arabia’s Vision 2030 goals. Future research should address the ethical implications, long-term impacts, and cultural adaptations necessary for successful AI integration in re- cruitment.By bridging these gaps, AI can play a pivotal role in modernising recruitment practices, enhancing efficiency, and driving competitive advantage in the evolving Saudi employment market.7 0Item Restricted Towards Intelligent Self-Reconfiguration of Manufacturing Systems(Cranfield University, 2024) Alotaibi, Mohammed; Patsavella, John; Syed, Jelena MilisavljevicGlobal market demand is undergoing significant and rapid changes, creating an unprecedented challenge for conventional manufacturing systems such as mass production. As the demand for highly customized products surges, these traditional methods struggle to handle the dynamic market demands. However, a promising solution may lie in Reconfigurable Manufacturing Systems (RMS), developed in the late 1990s. RMS have the potential to address the current demand fluctuations effectively. Despite their promise, many manufacturers worldwide encountered challenges when attempting to adopt the concept of Reconfigurable Manufacturing Systems, particularly concerning the integration and modularity aspects. This research’s goal is to close this gap by providing a comprehensive framework that addresses these challenges and elevates the effectiveness of RMS to new heights. Extensive data were collected from relevant literature and expert interviews to develop the framework. Utilizing the collected data, a conceptual framework was formulated, serving as a blueprint to overcome the identified issues and enhance the performance of RMS. To ensure the validity and practicality of the proposed framework, a second round of interviews was conducted, seeking validation from industry experts. By offering a robust and validated framework, this research seeks to contribute to the manufacturing landscape by empowering industries to embrace Reconfigurable Manufacturing Systems confidently. This transformation has the potential to unlock unparalleled flexibility and responsiveness, enabling manufacturers to meet the ever-changing demands of the global market efficiently. As a result, this paper lays the foundation for a more adaptive and competitive manufacturing ecosystem for the future.17 0