Saudi Cultural Missions Theses & Dissertations
Permanent URI for this communityhttps://drepo.sdl.edu.sa/handle/20.500.14154/10
Browse
8 results
Search Results
Item Unknown EXAMINING PATIENT SAFETY CULTURE TRENDS IN U.S. HEALTHCARE THROUGH A MULTI-YEAR ANALYSIS(Saudi Digital Library, 2026) Alabdullah, Hassan; Karwowski, WaldemarPatient Safety Culture (PSC) is recognized as a cornerstone of healthcare quality and a key determinant of patient outcomes. Despite the Institute of Medicine’s early calls to establish safety-oriented systems, evidence on the long-term stability of PSC in U.S. hospitals has remained limited. This dissertation addresses this gap through a multi-year evaluation of PSC using the Hospital Survey on Patient Safety Culture (HSOPSC v1.0) and advanced statistical methods. Drawing on one of the largest national datasets—comprising over 993,000 healthcare providers from 1,601 U.S. hospitals across three survey cycles (2013–2020)—the study employed a longitudinal repeated cross-sectional design. Analyses combined descriptive statistics, second-order factor modeling, and Partial Least Squares Structural Equation Modeling (PLS-SEM) with multi-group analysis to capture temporal trends, determinants, and outcomes of PSC. Findings showed that overall PSC scores averaged 65% across years, with strengths in “Supervisor/Manager Expectations” and “Teamwork within Units,” and persistent weaknesses in “Nonpunitive Response to Error” and “Handoffs and Transitions.” PSC declined slightly over time, with regional and institutional variations: smaller, non-teaching, and Southern/Central hospitals reported higher PSC. Hospital size and region exerted inconsistent effects, while workforce factors—such as staff role, tenure, and patient contact—were stronger and more stable predictors of PSC outcomes. Importantly, PSC demonstrated robust predictive power, explaining 56.7% of the variance in overall safety perceptions and 23.2% in error reporting frequency. The dissertation provides rare longitudinal evidence confirming PSC as a dynamic, multidimensional construct. While PSC’s influence on safety outcomes has strengthened over time, sustaining improvements remains challenging, particularly in fostering blame-free reporting, ensuring adequate staffing, and improving care transitions. Practical implications highlight leadership commitment, nonpunitive systems, and workforce-centered strategies, alongside interprofessional education to embed safety in daily practice. Collectively, the findings offer actionable insights for policy, leadership, and training, while advancing methodological rigor in PSC research.23 0Item Unknown Investigating the Factors that Affect the Adoption of Cybersecurity Data Visualization Applications Within Organizational Context: An Application of the T-O-E Framework(Saudi Digital Library, 2025) Aljasir, Afnan; Chinazunwa, UwaomaCybersecurity visualization (VizSec) tools have emerged as critical enablers for organizations to detect, interpret, and respond to increasingly complex cyber threats. Despite their potential, the adoption and effective use of these tools remain inconsistent across industries. This dissertation examines the determinants of VizSec adoption through the application of the Technology-Organization-Environment (TOE) framework; and the effect of its adoption on organizational performance thereafter. Mixed-method approach was used in this study to provide an in-depth understanding of quantitative and qualitative results. During the quantitative step, a survey of 230 cybersecurity professionals and decision-makers in various industries was used to gather data and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The qualitative stage was based on 14 semi-structured interviews, conducted with the help of the six-phase thematic analysis of Braun and Clarke, in order to render the lived experiences and the practical knowledge of the participants. The results show that the most powerful drivers of adoption are technological determinants, especially ease of use, lesser complexity, and compatibility with the already existing infrastructure. Influencing factors include organizational aspects, comprising of top management support, financial and human resources, as well as the organizational ability to learn, without which the value of VizSec is constrained due to the lack of skilled professionals. Environmental factors were considered key determinants, whereas competitive pressure had a small influence. Notably, the research proved the mediating effects of Security Data Visualization (SDV) between factors of the TOE and organizational performance. Adoption of VizSec was found to have a high level of customer satisfaction, financial performance, innovation and agility within the organization. Theoretically, this research contributes by generalizing the use of the TOE framework in the space of cybersecurity visualization and introduces SDV as a mediating construct to redefine organizational and environmental variables in this sense. In practice, the study provides a roadmap on how organisations can get the best out of VizSec through strategic investments, enhancing compliance, developing skilled human capital, and establishing vendor relationships.12 0Item Unknown The Influence of Digital Technology Engagement on Academic Performance in Undergraduate Students in Saudi Arabia(Saudi Digital Library, 2025) Alruthaya, Ali Saleh; Khan, ShahadatThis thesis examines the influence of digital technology on student engagement and academic performance among undergraduate students in Saudi Arabia. Recognising the importance of digital transformation in education, this research addresses significant gaps in understanding how digital technologies affect educational outcomes broadly within Saudi higher education institutions. Employing a positivist paradigm and a quantitative research approach, this study utilises the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework. It evaluates the impact of seven key constructs, performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, habit, and learning value, on student engagement and subsequently assesses the direct relationship between student engagement and academic performance. Data was collected via questionnaires from a diverse sample of 527 undergraduate students across six Saudi public universities, and subsequently analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings indicate that performance expectancy, hedonic motivation, social influence, facilitating conditions, and learning value significantly enhance student engagement, which positively influences academic performance. Theoretically, this research extends the UTAUT2 model by incorporating academic performance as a critical outcome variable, offering original and nuanced insights specific to the Saudi educational context. Practically, the results provide valuable guidance for educators and policymakers aiming to utilise digital technologies effectively to boost student engagement and academic achievement. This study acknowledges limitations, including its cross-sectional design and reliance on self-reported data, which may limit external validity. However, the originality and value of this research lie in its pioneering application of the UTAUT2 framework within the unique socio-cultural and educational landscape of Saudi Arabia. This research provides foundational insights to inform strategic and operational educational reforms in Saudi Arabia and other similar regional contexts.38 0Item Unknown ASSESSMENT OF THE SAFETY CULTURE IN PETROCHEMICAL INDUSTRIES IN SAUDI ARABIA: A CROSS SECTIONAL STUDY(Saudi Digital Library, 2025) Alqarfi, Ahmed Mohammed; Karwowski, WaldemarGiven the inherently hazardous nature of petrochemical operations, an effective safety culture is critical. Following PRISMA 2020 guidelines, 29 peer-reviewed articles published in open access between 2014 and 2024 were selected to evaluate the status of safety culture dimensions employed in the petrochemical sector. This cross-sectional study assessed safety culture in the Saudi Arabian petrochemical industry and examined the relationships among safety culture dimensions, safety motivation (SM), and safety performance. Safety performance was operationalized as personal error behavior (PEB) and attitudes toward violations (ATV), with SM modeled as a mediating factor. After obtaining IRB approval, a total of 482 employees from the petroleum facilities in Jubail and Yanbu Industrial Cities completed an email-administered survey. Structural equation modeling (SEM) was applied using SmartPLS and SPSS. The results indicate that safety culture has a significant effect on SM, PEB, and ATV, and that SM significantly mediates the relationship between safety culture and safety performance. To enhance safety outcomes across the petrochemical sector, future studies should focus on longitudinal research to track safety culture trends and extend safety culture assessments to other high-risk environments, including oil exploration, drilling, and gas operations. Additionally, further studies could investigate the development of subcultures within broader safety frameworks, providing deeper insights into the specific safety dynamics at play in these critical sectors.35 0Item Restricted Determinants of project control system effectiveness in Saudi Arabian construction project delivery(Saudi Digital Library, 2025) Aloatibi, Rashed; Sohail, M.; Soetanto, Robby; Edum-Fotwe, FrancisConstruction projects in the Kingdom of Saudi Arabia (KSA) continue to face persistent challenges, including schedule delays, cost overruns, and uncontrolled scope deviations. Despite increasing emphasis on Project Control Systems (PCSs), research has yet to offer a comprehensive, empirically tested framework for assessing the determinants that shape PCS effectiveness. This study addresses that gap by developing a structured, multi-layered framework that evaluates how various Project Control System Determinants (PCSDs) influence project performance across cost, schedule, and scope dimensions. Data were collected through a cross-sectional survey of 222 completed construction projects in KSA, capturing variations in control practices and performance outcomes. A multi-stage analytical design was applied at both strategic and tactical levels using two approaches: a structural-based model and an indicator-based predictive approach, to address the research aim and objectives. At the strategic level, Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to test a structural model grounded in empirical evidence and informed by relevant theoretical perspectives, linking 13 PCSDs to project performance. Results showed that operational control determinants, including pre- and post-operational controls, as well as uncertainty controls, had significant direct and mediating effects. Organisational, human, and technological inputs influenced performance indirectly through their effects on operational controls, validating the study’s Input–Process–Output (IPO) modelling logic. As part of the structural modelling approach, tactical-level insights were derived using Importance–Performance Map Analysis (IPMA). This analysis identified priority areas for improvement, including leadership and team capacity, estimation accuracy, integrated stakeholder engagement, Project Management Office (PMO) involvement, audit frequency, knowledge management for continuous improvement, and schedule compression techniques. These elements were both high in importance but underperforming, marking them as critical leverage points for enhancing PCS effectiveness. In the indicator-based predictive approach, a combination of machine learning models, including random forest, gradient boosting, and ridge regression, was employed to rank the most influential determinants of cost, schedule, and scope outcomes. Project Planning and Scheduling (PPS), Corrective Actions (CA), and Change Control (CC) emerged as consistently strong predictors. Furthermore, Lasso and Elastic Net Regression were used to analyse 59 sub-indicators, offering granular insights into practices with the greatest impact, such as estimation precision, change control efficiency, earned value analysis (EVA), and resource optimisation. This research makes three key contributions. First, it offers theoretically significant contribution by introducing a novel, integrative PCS framework grounded in empirical evidence and structured across strategic and tactical levels. Second, it demonstrates methodological rigour through the use of multi-model triangulation, latent variable modelling, and machine learning. Third, it provides practical value by presenting a replicable, diagnostic roadmap for project managers and policymakers to evaluate and improve control systems in complex settings such as construction. These contributions have broader relevance to complex project environments and are particularly well suited to advancing the goals of Vision 2030 and strengthening project delivery in Saudi Arabia’s evolving construction sector.14 0Item Restricted Exploring the Impact of Talent Management Strategies on AI Adoption in Saudi Arabia’s Emerging Tech Startups: The Mediating Role of Knowledge Sharing(Saudi Digital Library, 2025) Abuhaimed, Mohammad Saad; Abdoulrahman Aljounaidi Mhd RamezSaudi Arabia's Vision 2030 emphasizes AI-driven digital transformation, yet tech startups struggle to scale AI beyond pilots. Purpose: This study examines how talent management (TM) strategies—attracting-selecting (AST), developing (DT), empowering (ET), retaining (RT), and career succession (CS)—shape AI adoption, and whether knowledge sharing (KS) mediates this relationship. Method: Using probability-based systematic random sampling of employees (n=337, N=2,308) across Saudi AI-adopting startups, the model was analyzed with PLS-SEM (SmartPLS 4). Findings: AST, DT, and ET positively affect AI adoption; RT shows no effect; CS exhibits a negative effect. KS partially mediates AST, DT, ET, and CS effects, indicating TM practices influence adoption primarily through knowledge institutionalization. Implications—Industrial: Startup leaders should integrate KS infrastructures with TM initiatives. Recommended practices: (1) cross-functional AI taskforces with rotating membership; (2) peer-learning sessions where early adopters mentor colleagues; (3) searchable repositories (wikis, Confluence) documenting implementation lessons and troubleshooting guides; (4) succession systems prioritizing collaborative knowledge transfer (mentoring, communities of practice) to prevent silos. Empirical evidence shows succession planning without KS scaffolding correlates negatively with adoption (β = -0.182, p < .01), highlighting knowledge-hoarding risks. Academic: The study extends technology-acceptance theory by integrating human-capital antecedents and positioning KS as the pivotal mediating mechanism in resource-constrained startups. Testing 16 structural paths across five TM dimensions addresses three gaps: (1) mechanistic under-specification, (2) construct aggregation bias, and (3) non-Western context neglect. The mediation framework—validated through bootstrapped indirect effects—provides a replicable blueprint for future research examining causality, moderators (industry velocity, founder literacy), and boundary conditions.59 0Item Restricted DOES AI INTEGRATION MODERATE THE RELATIONSHIP BETWEEN FIRM GROWTH AND PERFORMANCE IN SMES: THE INFLUENCE OF DECISION-MAKING AND OPERATIONAL PERFORMANCE(University of South Alabama, 2025-05) AlQahtani, Dalal T; Butler, Frank C; Gillis, William E; Hair Jr, Joe F; Scott, Justin TToday’s dynamic business environment requires small and medium-sized enterprises (SMEs) to keep up with technological advancements in order to remain competitive. Business growth creates more challenges for SMEs since they possess fewer available resources than big organizations. Since the introduction of artificial intelligence (AI), several SMEs have been able to compete more effectively and deliver better performance. As part of this research, I examine the possibility that AI integration (AII) will moderate the relationship between firm growth and both decision-making and operational performance, ultimately affecting the performance of SMEs. The aim of this research is to provide practical implications for AI as a strategic resource for improving decision-making capabilities, performance and growth by utilizing the resource-based view (RBV) and information processing theory (IPT). A partial least squares structural equation model (PLS-SEM) was used to analyze data from 338 SME business strategy decision-makers in the United States. In order to verify the measurement model’s reliability and validity, a Confirmatory Composite Analysis (CCA) was performed, followed by the evaluation of the structural model in order to test the hypotheses. In contrast to initial hypotheses, this study found that firm growth is positively related to both decision-making and operational performance. Nevertheless, the study results support the original hypothesis that both decision-making performance (DMP) and operational performance (OPP) positively affect a firm’s performance. Furthermore, AII significantly moderated the relationship between FG and OPP, while it did not significantly moderate the relationship between FG and DMP. This indicates the complexity of the role AI integration plays in SMEs. The paper concludes with recommendations for future research, as well as guidance for practitioners regarding how SMEs can improve their decision-making capabilities and performance using AI.37 0Item Restricted Analysing affective factors in relation to students’ achievement and behaviour in EFL in Saudi Arabia(Saudi Digital Library, 2023-11-22) Alnemari, Aeshah; Pons-Sanz, SaraThis study investigates the relationships between attitude, motivation and anxiety in relation to students’ effort and achievement in learning English as a foreign language (EFL). It examines the influence of affect on the foreign language learning of Saudi secondary students (years 10– 12, aged 16–18 years) to elucidate the obstacles that hinder successful English language learning in Saudi Arabia. The study uses a mixed-methods approach, which combines data from questionnaires and semi-structured interviews. One hundred and thirty-three students completed a questionnaire that was created with input from Gardner (2004) and Dörnyei (2001) to measure attitude, Noels (2003) and Aljasir (2016) to measure motivation, and Horwitz et al. (1986) to measure anxiety. Descriptive statistics and partial least squares structural equation modelling (PLS-SEM) were employed to analyse data collected from the questionnaire. In addition, 18 interviewees participated in this study and the data collected were analysed qualitatively. The analysis produced interesting results, which highlight the significant role of affective factors in language learning. All affective factors, albeit to varying degrees, predict students’ effort and achievement. Examining students’ effort in addition to their achievement helps to gain better insights into the relationships between the study variables. Moreover, the year of study and the education situation influence the relationship between affective factors and learning outcomes, resulting in increasing controlled motivation with age and increased anxiety for year 11 students. In addition, language attitude is more effective when it is related to the importance of learning the language for pragmatic values independent of the classroom experience. When attitude is related to learning English only as a school requirement, they will have less effect on the learning process. The findings highlight the significant role of teachers to enhance students’ autonomous motivation for more effective learning. Based on these results, the study has much to offer stakeholders in the Saudi context as regards developing language teaching and learning practices in Saudi Arabia.22 0