Saudi Cultural Missions Theses & Dissertations
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Item Restricted The Impact of Artificial Intelligence on Supply Chain Optimization in Saudi Arabia(Saudi Digital Library, 2025) AlQahtani, Abdullah Saeed; Khobzi, HamidThis dissertation examines the impact of Artificial Intelligence (AI) on supply chain optimization in Saudi Arabia, with particular emphasis on its alignment with the Kingdom’s Vision 2030 objectives. AI technologies such as machine learning, predictive analytics, robotic process automation, and the Internet of Things are increasingly recognized for their potential to enhance efficiency, resilience, and sustainability within supply chain operations. However, despite growing national interest, empirical research focusing on AI adoption in the Saudi supply chain context remains limited. The study adopts a qualitative, interpretivist approach based on multiple secondary case studies drawn from peer-reviewed literature published between 2020 and 2025. The analysis is guided by the Technology–Organization–Environment (TOE) framework, supported by the Supply Chain Operations Reference (SCOR) model, to examine both adoption drivers and process-level applications across key sectors, including telecommunications, healthcare, manufacturing, and national mega-projects. Findings indicate that AI adoption in Saudi supply chains is most advanced in planning, forecasting, and logistics delivery, while challenges persist in system integration, data quality, workforce readiness, and organizational resistance to change. Environmental factors such as Vision 2030 initiatives and government support act as strong enablers, although adoption remains concentrated among large organizations and flagship projects. The study concludes that while AI has significant potential to transform Saudi supply chains, its full benefits depend on improved digital integration, skills development, and supportive policy frameworks.32 0Item Restricted Employing Business Intelligence and Data Analysis Techniques in Evaluating Institutional Performance: An Applied Study of the Non-Profit Sector in Charitable Associations in Al-Jauf(Saudi Digital Library, 2025) AlBuniyah AlNusairi, Turki Hamdan Shafaq; AlShabool, Khaledهدفت الدراسة إلى التعرف على أثر توظيف تقنيات ذكاء الأعمال في تقييم الأداء المؤسسي بالقطاع غير الربحي في الجمعيات الخيرية بمنطقة الجوف. استخدمت الدراسة المنهج الوصفي التحليلي، وجمعت البيانات عبر الاستبانة الإلكترونية. وتمثل مجتمع الدراسة في عدد 11654 موظف ومتدرب في الجمعيات الخيرية، وتم الحصول على الاستجابات من عينة عشوائية قوامها 200 موظف وموظفة. ركزت الدراسة على أبعاد ذكاء الأعمال (أنظمة ذكاء الأعمال القائمة على السحابة، التحليلات المعرفية، معالجة اللغة الطبيعية، لوحات التحكم التفاعلية) كمتغير مستقل، وتقييم الأداء المؤسسي كمتغير تابع. أظهرت النتائج أن جميع أبعاد ذكاء الأعمال سجلت مستويات مرتفعة، وأن مستوى تقييم الأداء المؤسسي كان أيضًا مرتفعًا، مما يؤكد التأثير الإيجابي والواضح لتوظيف تقنيات ذكاء الأعمال على تقييم الأداء المؤسسي في القطاع غير الربحي. أوصت الدراسة بالاستثمار المستمر في تبني وتطوير هذه التقنيات، مع التركيز على تطوير القدرات البشرية، وبناء ثقافة تنظيمية داعمة للبيانات، وتشجيع استخدام لوحات التحكم التفاعلية، وتطوير أنظمة تقييم الأداء لتكون أكثر مرونة. كما تشدد على أهمية تعزيز التعاون وتبادل الخبرات بين الجمعيات، والاستفادة من التحليلات المعرفية ومعالجة اللغة الطبيعية لتقييم الجوانب النوعية للأداء A study was conducted to examine the impact of employing business intelligence techniques on institutional performance evaluation in the non-profit sector, specifically within charitable organizations in the Al-Jouf region. The study utilized a descriptive analytical approach, collecting data through an electronic questionnaire. The study population consisted of 11,654 employees and trainees in charitable organizations, with responses obtained from a random sample of 200 employees. The research focused on four dimensions of business intelligence (cloud-based business intelligence systems, cognitive analytics, natural language processing, and interactive dashboards) as the independent variable, and institutional performance evaluation as the dependent variable. The results indicated that all business intelligence dimensions were at a high level, and the level of institutional performance evaluation was also high, confirming the clear and positive impact of using business intelligence technologies on institutional performance evaluation in the non-profit sector. The study recommended continuous investment in adopting and developing these technologies, with an emphasis on developing human capabilities, building a data-supportive organizational culture, encouraging the use of interactive dashboards, and developing more flexible performance evaluation systems. It also stressed the importance of enhancing cooperation and knowledge exchange among organizations and utilizing cognitive analytics and natural language processing to evaluate qualitative aspects of performance.2 0Item Restricted Employee Readiness for AI Adoption in Riyadh’s Healthcare Sector: Perceptions and Organizational Support(Saudi Digital Library, 2025) Almutairi, Hadeel; Cui, QinquanArtificial intelligence (AI) is widely recognized as a significant driver of digital transformation across several domains, with the healthcare sector identified as one of the most influenced sectors. This research assesses employee readiness for AI among healthcare professionals in Riyadh, Saudi Arabia, with particular attention paid to perceptions (perceived usefulness and ease of use) and organizational support, including training and management support. This study employed a quantitative, cross-sectional, and correlational design. A survey was administered to evaluate employee readiness levels and potential predictors of AI readiness. A total of 120 employees participated with overall readiness (M = 4.20, Var=0.64). The regression explained 39.4% of the variance in readiness, with perceived usefulness (B = 0.44, p < 0.001) and training (B = 0.40, p < 0.001) contributing positively to readiness, while management support contributed negatively (B = -0.17, p = 0.011), and ease of use was not significant (B = 0.05, p = 0.574). Independent t-tests and ANOVA confirmed no significant differences in readiness by gender (p = 0.40), job type (p = 0.44), or years of experience (p = 0.56). The results showed that perceived usefulness and training were the strongest predictors of employee readiness for AI. While ease of use was not significant, organizational support had a negative effect. This study contributes to the literature on AI readiness in Saudi healthcare, highlighting perceived usefulness and training as key drivers for AI adoption, while questioning assumptions about the management support role in AI adoption. Healthcare leaders and policymakers should prioritize training, communicate the practical benefits of AI, and ensure that managerial commitment is supported by resources.14 0Item Restricted The Extent of Readiness to adopt and utilize Emerging Technologies in Private Sector Organizations in the Kingdom of Saudi Arabia(Saudi Digital Library, 2025) Ismail, Malik; O'dea, ChristinThis research aims to contribute to bridging the gap in the literature in the field of Managing Technological Change and Information Systems management, by exploring the state of readiness to adopt and utilize emerging technologies in organizations within the Private Sector of the Kingdom of Saudi Arabia. While literature has highlighted the success of the public sector, and factors affecting the adoption of specific technologies, this research contributes findings across different organizations in the Private Sector, with a general definition of Emerging Technologies. This research uses qualitative methodologies to explore context-specific contributors to readiness, which candidates reported in Semi-Structured interviews. Findings reveal that while technological awareness is high, organizational readiness is hindered by legacy IT systems, centralized decision-making, and skills gaps. SMEs exhibited agility in experimentation, while large firms struggled with procurement cycles and hierarchical cultures. The study contributes to existing research by contextualizing digital transformation in the Private Sector of Saudi Arabia, by providing practical insights for Business Leaders seeking to align readiness with national digitalization agendas, while also highlighting skill gaps relevant to educational policy and workforce development.11 0Item Open Access Onboarding New Employees in the Era of Digital Transformation(Saudi Digital Library, 2025) Alharbi, Safiah; Dasuki, Salihu; Abbott, Pamela; Lin, AngelaThis research responds to calls for more studies on the digitalisation of onboarding processes by exploring the impact of the adoption of digital onboarding in a Saudi telecoms company (STC). Adopting a qualitative methodology, it draws on 25 semi- structured interviews with HR professionals and new employees, national policy documents, and company annual reports, with the aim of identifying whether digital solutions can enhance onboarding practices and foster employee engagement effectively within the Saudi context. While previous studies have explored the general benefits and challenges of digital onboarding, little is known about how these processes unfold within specific socio-cultural environments, such as the Gulf States. This study addresses this gap by offering a context-specific examination of digital onboarding in Saudi Arabia, a country which combines a young, tech-savvy population with rapid digital transformation as part of its national development plan (Saudi Vision 2030) but which retains deeply-rooted cultural norms that prioritise interpersonal relations and face-to-face communication. By situating digital HR processes within the cultural and generational dynamics of Saudi society, this research highlights the nuances that are often overlooked in the universalised models of digital transformation. The findings show that digital onboarding, as practiced in a leading organisation within a transforming national context, is shaped by a confluence of strategic, technological, and human factors. They also indicate that, while digital tools can enhance organisational efficiency and employee engagement, their full potential will only be realised when a balanced, context-sensitive, and culturally-grounded approach to digital transformation is adopted. This study therefore concludes that digital onboarding practices must adapt not only to generational shifts but also to deeply ingrained social customs. In doing so, it contributes to the theoretical understanding of digital onboarding and provides valuable insights into how digital processes can be effectively designed and implemented in culturally-rich and evolving work environments.21 0Item Restricted Digital Transformation in Tourism : A Case Study of Holiday Inn Guildford(university of surrey, 2025) ALSULAIMANI, ALANOUD; TOM, LUNTThis study investigates the impact of digital transformation on luxury hotels, focusing on enhancing competitiveness, resilience, and customer experience. Using a qualitative approach, the research explores how digital technologies such as online booking platforms, mobile check-in, and smart services are adopted in the post pandemic hospitality sector. Data were collected through secondary sources, highlighting the strategies luxury hotels employ to maintain operational efficiency and improve guest satisfaction. Findings reveal that digital transformation not only enhances customer experience but also strengthens hotels’ adaptability and market competitiveness. The study provides practical insights for hotel managers aiming to implement effective digital strategies and offers a foundation for future research in hospitality digitalization30 0Item Restricted Artificial Intelligence (AI) Assimilation in the Public Sector:An Attention-Based Exploration of Decision Making, Leadership, and Communication in Saudi Arabia(Saudi Digital Library, 2025) Alshahrani, Albandari Fahad; Griva, Anastasia; Dennehy, DenisThe rapid development of Artificial Intelligence (AI) has opened new possibilities for public sector organisations to improve service delivery, strengthen decision-making processes, and enhance operational efficiency. However, successfully assimilating AI in government contexts presents distinct challenges that differ markedly from those faced by private sector organisations. Public institutions operate within complex frameworks shaped by multiple stakeholder expectations, stringent regulatory requirements, accountability obligations, and often risk-averse organisational cultures — all of which significantly influence technology assimilation outcomes. Despite growing interest in AI within government, there is still limited understanding of how organisational attention dynamics shape AI assimilation processes. This PhD thesis addresses this critical gap by applying the Attention-Based View (ABV) theory to explore how leadership attention allocation, communication practices, and institutional contexts influence AI integration in public sector organisations. This doctoral thesis, structured as an article-based PhD, comprises three interrelated studies that collectively advance understanding of AI assimilation through the lens of organisational attention. The research pursues five Research Objectives (ROs): identifying organisational and governance challenges in public sector AI assimilation through a systematic literature review (RO1); investigating leadership attention allocation mechanisms in AI initiatives (RO2); examining communication channels as attention management mechanisms in public sector AI integration (RO3); analysing how national policies and institutional contexts influence AI assimilation outcomes (RO4); and providing practical insights for AI-driven governance (RO5). Methodologically, the research combines a systematic literature review with qualitative case studies conducted in the Saudi Arabian public sector, focusing on organisations implementing AI under the Vision 2030 transformation agenda. The first study presents a systematic literature review of 61 peer-reviewed articles published between 2012 and 2023, mapping the current state of AI research in public administration. This review identifies seven major challenges including infrastructure limitations, data governance issues, workforce readiness gaps, regulatory complexities, cultural resistance, cybersecurity concerns, and resource constraints, and five primary benefits, such as enhanced decision-making, greater efficiency, cost optimisation, increased transparency, and improved citizen engagement. This study lays a foundational understanding of AI assimilation challenges and underscores the need for attention-based perspectives. The second study applies ABV theory to examine attention-related challenges in AI assimilation within Saudi public sector organisations. Using in-depth qualitative analysis of a single case study, the research identifies five core attention-based challenges, divided into internal (situated) and external (structural) categories. Internally, challenges include fragmented leadership attention, competing priorities, and resource conflicts; externally, they involve regulatory demands, stakeholder expectations, and institutional pressures. These findings highlight the importance of understanding how attention allocation shapes AI outcomes and underscore the central role of leadership focus in managing assimilation challenges. The third study extends this analysis by exploring how leadership practices and communication channels facilitate AI integration across multiple Saudi public sector organisations. The research shows that leaders coordinate organisational attention through structural frameworks (formal systems), situated practices (contextual engagement), and communication-mediated mechanisms (information flow management). The study introduces the concept of leaders as "attention architects" who design and manage attention structures to support digital transformation. Findings reveal how formal and informal communication channels function not only as conduits but as active mechanisms shaping attention, fostering alignment, and sustaining commitment to AI initiatives. Theoretically, this thesis advances ABV by applying the theory to public sector AI assimilation and developing communication channels as attention regulators. It offers the first thorough application of ABV in public sector AI assimilation, highlighting distinct dynamics compared to private sector contexts. The study also underscores the role of national transformation agendas in shaping attention allocation and assimilation trajectories, providing insights relevant to Global South and developing country contexts. Furthermore, this thesis establishes a novel theoretical framework that integrates organisational attention with institutional theory, demonstrating how cultural and political factors systematically influence attention allocation patterns in complex technological transformations (Ocasio et al., 2018; Taras et al., 2020). The thesis also contributes to communication theory by conceptualising formal and informal communication networks as co-equal drivers of attention distribution, challenging traditional hierarchical models of organisational attention and proposing a more dynamic, multi-channel approach to understanding attention flows in public sector contexts (Putnam & Mumby, 2014; Cornelissen et al., 2020). Practically, the findings provide actionable guidance for public sector leaders and policymakers. They suggest strategies for designing attention structures, managing competing demands, and leveraging communication channels to enable successful AI integration. The focus on Saudi Arabia's Vision 2030 offers valuable lessons for other governments pursuing digital transformation under complex institutional and cultural constraints. This thesis acknowledges limitations, including its focus on a single national context, the literature review's temporal scope (up to 2023), and the qualitative nature of empirical studies. These limitations present opportunities for future work, such as cross-country comparative studies, longitudinal analyses of attention dynamics, and quantitative validation of the developed frameworks. In sum, this thesis makes significant contributions to both theory and practice by demonstrating the critical role of organisational attention in public sector AI assimilation. It reveals that successful integration demands strategic attention management, effective communication systems, and leadership practices that align organisational focus with implementation goals. The findings offer a strong foundation for future studies on attention dynamics in technology assimilation and provide practical insights to support leaders and policymakers striving for AI-enabled governance transformation. By integrating theoretical depth with practical relevance, this PhD research advances academic understanding and offers concrete guidance for navigating public sector digital transformation.8 0Item Restricted An Investigation on the Influence of Digital Transformation on Organisational Project Management in Saudi Arabia's Tourism Sector(Saudi Digital Library, 2025) Albalawi, Amal; Tomasz, ArkadiuszThis research investigates the role of Digital Transformation(DT) on Organisational Project Management (OPM) within Saudi Arabia's tourism sector, a key area for Vision 2030 development. A significant gap exists in scholarly understanding of digital transformation's specific role and consequences for OPM in this context. The study aimed to address this gap by exploring key hindering and facilitating factors as well as the benefits and challenges of DT for OPM, ultimately offering recommendations for the enhancement of DT’s integration in OPM in Saudi Arabia’s tourism industry.55 0Item Restricted Digital Enterprise Architecture Maturity and Performance (DEAMP) Assessment Framework(Saudi Digital Library, 2025) Alsufyani, Nujud Mohammed J; Gill, Asif Q; Beydoun, GhassanOrganisations increasingly recognise the transformative potential of digitalisation. This phenomenon involves changes in organisational strategy, processes, knowledge, and the entire sociotechnical system. These changes have unpredictable impacts on organisational performance, posing challenges for decision-makers in assessing the feasibility of digitalisation and its intended performance outcomes. However, current research reveals a significant gap in understanding digital maturity (DM) levels and their link to organisational performance outcomes. Thus, this research aims to understand enterprise-architecture- driven DM levels, digitalisation performance outcomes, and their relationships to develop an assessment framework. A well-established DSR method has been employed to construct a theoretically robust framework for assessing digital enterprise architecture maturity and performance (DEAMP assessment framework). This framework comprises two components: the DEAMP model and the DEAMP process. It captures the interconnectivity between DM levels and organisational performance outcomes to provide decision-makers with valuable insights to enhance DM for organisational performance gains. This framework was evaluated using illustrative scenarios and an expert survey. The findings were utilised incrementally to iteratively develop and refine the framework and demonstrate the framework's suitability and effectiveness. The thesis research offers significant contributions to academic and practical knowledge in the field of enterprise architecture and a solid foundation for future directions.39 0Item Restricted A framework to adopt construction 4.0 in the Kingdom of Saudi Arabia: Impact of Institutional Pressures, Ambidexterity and Organizational Resources on Intention to Adopt(University of Newcastle, 2025) Alyami, Abdullah; Thayaparan, Gajendran; Marcus, Jefferies; Tanvi, NewazConstruction 4.0 is the construction industry’s response to Industry 4.0, a technological revolution to adopt innovative methodologies and modern technologies to boost productivity and efficiency in modern workplaces. Construction 4.0 is driven partly by an accelerated pace of urbanization, the resulting heightened demand within the construction industry, and the construction industry’s reputation for lack of modernization. It marks a paradigm shift characterised by the integration of digital technologies, automation, real-time data, and artificial intelligence across all stages of the construction lifecycle. The extant literature suggests that Construction 4.0 adoption is influenced by organizational resources (technology, people, process, and education), ambidexterity (exploration and exploitation), and institutional pressures (normative pressure, memetic pressure, and coercive pressure). The predominant discourse of existing studies on the implementation of Construction 4.0 have focused on its impact on work procedures, project completion times, quality, and safety measures, despite the significant influence of organizational resources, ambidexterity, and institutional pressures on the successful adoption of Construction 4.0. Less attention has been paid to how internal organisational factors and external institutional forces interact to shape the strategic intent to adopt Construction 4.0 technologies. This study addresses this gap by investigating the influence of three critical constructs: organisational resources (technology, people, processes, education and training), organisational ambidexterity (exploration and exploitation capabilities), and institutional pressures (coercive, normative, and mimetic) on the intention to adopt Construction 4.0 within the Saudi construction industry. Hence, this study investigates the influence of organizational resources, ambidexterity, and institutional pressures on the adoption of Construction 4.0 in the Kingdom of Saudi Arabia. Ultimately, the study has developed a framework for implementing Construction 4.0 in the Saudi construction industry. This research developed a theoretical model proposing eighteen (18) hypotheses, based on theories related to strategic resources (Resource-Based View), strategic flexibility (ambidexterity), and institutional pressures (institutional theory) to understand their impact on Construction 4.0 adoption. A comprehensive literature review was conducted, and a conceptual model was developed to measure the influencing factors. A quantitative research methodology was adopted, underpinned by a positivist paradigm. Data was collected through a questionnaire completed by 261 professionals in construction organizations in Saudi Arabia. Structural Equation Modelling (SEM) was adopted to test the hypotheses, examine the relationships between variables, and validate the conceptual model. The results of the SEM confirmed 13 of the 18 hypotheses, revealing that institutional pressures significantly influence exploration orientation. This orientation, in turn, positively impacts key organizational resources—particularly human capital, education and training, and processes—needed for the adoption of Construction 4.0. The intention to adopt C4.0 was found to be most strongly influenced by the development of these organizational resources. Moreover, the study identified five dominant adoption pathways that integrate external institutional forces and internal strategic capabilities. These pathways offer a nuanced understanding of how adoption dynamics unfold in practice, especially in contexts undergoing rapid socio-economic transformation. These findings offer theoretical and practical contributions. Theoretically, it advances the discourse on digital transformation in construction by integrating three organizational theories into a single explanatory model. The integration of organizational theories provides a deeper understanding of Construction 4.0 adoption dynamics. Empirically, it provides evidence-based insights specific to the Saudi Arabian context, an emerging market undergoing rapid reform aligned with Vision 2030. Practically, the study offers an empirically validated framework tailored to the Saudi construction context, which can inform decision-makers, policy developers, and construction professionals seeking to enhance productivity through digital transformation in alignment with national strategic ambitions.27 0