Saudi Cultural Missions Theses & Dissertations
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Item Restricted User engagement and satisfaction , Customer Satisfaction and Efficiency in Automated Last-Mile Delivery Systems: A Survey-Based Study.(Saudi Digital Library, 2025) Abu khamees, Rahaf; Rastani, SinaThis study aimed to examine the determinants of public acceptance of automated last-mile delivery (ALMD) technologies in the United Kingdom and Saudi Arabia. To address this aim, the study investigated how demographic characteristics (age and residential area), national context, and perceptions of risks and benefits (privacy, trust, safety, job loss, efficiency, and sustainability) shape willingness to adopt ALMD. A quantitative, cross-sectional survey was conducted with 203 participants, using quota-based sampling to enhance representativeness across both countries. Data were analysed using descriptive statistics, Mann–Whitney U tests, Kruskal–Wallis tests, and Spearman’s rank-order correlations in SPSS. Descriptive analysis indicated that participants were predominantly young, digitally literate, and experienced with traditional parcel delivery, with only a minority reporting prior use of automated methods. Cross-national comparisons revealed no significant differences between UK and Saudi respondents, suggesting convergence of public attitudes across contexts. Based on correlation analysis, the study identified that trust, efficiency, and emissions reduction were the strongest predictors of acceptance. By contrast, age, residential area, and concerns over safety, privacy, and job loss did not significantly reduce willingness to adopt ALMD. Notably, job-loss concern and privacy awareness were sometimes positively associated with openness to adoption, indicating that risks may coexist with acceptance rather than act as barriers. The findings highlight the importance of building trust, demonstrating efficiency gains, and communicating tangible environmental benefits to encourage adoption. This study leaves several gaps that future work should address through longitudinal and qualitative approaches, as well as broader cross-cultural sampling, to capture evolving public attitudes toward ALMD.4 0Item Restricted The Trust-Waqf Convergence: A Comparative Analysis of English Trusts and Saudi Waqfs(Saudi Digital Library, 2025) Alomair, Abdulrahman; Arun-Qayyum, ShamTwo recent UK Supreme Court decisions—Akers v Samba and Byers v Saudi National Bank—expose a practical risk: under lex situs, equitable interests may be treated as extinguished when trust assets pass into a non-trust jurisdiction. In Byers, the court recognised that extinguishment enabled fraudulent trustees to “route assets to third parties through jurisdictions where the law extinguishes equitable proprietary interests” per Lord Burrows. The extinguishment of beneficiary interests is nothing less than termination of the trust, an outcome equity cannot allow. Civil law jurisdictions have historically struggled to recognise the trust; in common law theory, trusts split ownership between legal and equitable ownership. This concept normatively clashes with civil law doctrine. The Hague Convention on the Law Applicable to Trusts and on their Recognition (the Hague Trust Convention of 1985) attempted to bridge the civil-common law gap, to limited success. As Saudi Arabia recognises an analogous institution of waqf (plural, awqaf) and is committed to Islamic Shariah, the question arises on whether awqaf are sufficiently analogous, or if the doctrinal challenge is greater than with civil law. This dissertation asks whether English family trusts and Saudi family awqaf can be mutually recognised notwithstanding formal divergence. It adopts a formal-functional method and distils a thin recognition test anchored in five structural “pillars”: asset segregation, fiduciary duty, purpose-binding, role-separation, and determinacy. Applied, the test shows that Saudi waqf and the English trust are functionally adjacent enough for courts to recognise each other’s arrangements and calibrate remedies without statutory transplantation. The analysis is illustrated with judge-facing hypotheticals and an integrated “trust–waqf” model, aimed at guiding academics, practitioners, and judges confronting cross-border family wealth structures. The upshot is doctrinally modest but operationally significant: recognition should track function and protections, not labels, unless a hard local rule intervenes.27 0Item Restricted Trust in Healthcare Public-Private Partnerships in Delhi NCR: A Systematic Review of Stakeholder Perceptions and Governance Challenges(Saudi Digital Library, 2025) Alsaqabi, Dimah; Bhardwaj, Simran; Sultana, Parveen; Albariqi, Yazeed; Chichani, Sushant; Alshrari, Zeyad; Preethi, JohnBackground: Trust is central to the success of healthcare public-private partnerships (PPPs) yet remains poorly understood in the Indian context. This review examines trust dynamics in PPPs within Delhi NCR, a region marked by complex governance and significant PPP activity. Objectives: To identify key trust factors and its dynamics discussed in the literature on healthcare PPPs across Delhi NCR; and to provide recommendations for building and sustaining trust in future healthcare PPPs. Methods: A systematic review was conducted following PRISMA 2020 guidelines. Searches were performed in PubMed, Scopus, Elsevier, institutional library repositories, and Google Scholar encompassing studies published between January 2000 – May 2025. Inclusion criteria targeted empirical studies, policy papers, and case reports on trust in Indian healthcare, particularly Delhi-NCR context. Data were thematically synthesised using Braun and Clarke’s Thematic Analysis method and analysed through McKnight’s and Institutional Trust frameworks. Case study analysis was conducted using Porter’s Value Chain. Results: Forty studies met inclusion criteria. Five interrelated trust factors were identified: transparency, accountability, stakeholder engagement, regulation, and payment. Transparency and accountability showed strong positive correlation (r = 0.72). A Delhi-based dialysis PPP case study validated thematic findings, highlighting systemic trust breakdowns. Limitations: This review's findings are limited by being sector specific, as trust dynamics in healthcare PPPs may not translate directly to other sectors. Geographic bias is evident, with limited representation of regions beyond Delhi NCR, reducing national applicability. Additionally, the cross-sectional nature of most studies restricts insight into how trust evolves over time. Conclusion: This review examined what builds and breaks trust in healthcare PPPs, with a focus on Delhi-NCR. Five interconnected trust factors: transparency, accountability, stakeholder engagement, regulation, and payment were consistently identified. Transparency emerged as the most foundational, enabling or disabling other trust mechanisms. Theoretical frameworks helped explain paradoxes, such as low trust in high-influence stakeholders. Ultimately, trust must be intentionally embedded into PPP design through inclusive, transparent, and accountable governance.19 0Item Restricted Adoption of AI Itinerary Planners by Young Adults: A UTAUT Study(Bournemouth University, 2025) Alshehri, Omar; Buhalis, DimitriosThe rapid integration of generative Artificial Intelligence (AI) into the tourism sector has created powerful new tools for travel planning. This study investigates the key determinants influencing the adoption of AI itinerary planners among young adults (aged 18-28), a critical demographic of digital natives. The research aim was to develop and empirically validate an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model, integrating the core theory with the constructs of trust, personalisation, and perceived risk. A quantitative, cross-sectional online survey was administered, yielding a final sample of 228 valid responses, which were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings reveal that Performance Expectancy is the most powerful predictor of behavioural intention, strongly affirming that perceived utility is the primary driver of adoption. Social Influence and Trust also emerged as significant positive determinants. Crucially, the model demonstrated that Perceived Personalisation is a key antecedent, strongly and positively influencing both Performance Expectancy and Trust. In contrast, Effort Expectancy and Facilitating Conditions were found to be non-significant, suggesting these are baseline expectations rather than drivers for this technologically fluent cohort. While Perceived Risk did not directly deter adoption intention, it significantly eroded user trust. The validated model demonstrated substantial explanatory power, accounting for 76.2% of the variance in behavioural intention. The study concludes that young adults' adoption of AI planners is a pragmatic decision driven by utility, social proof, and a foundation of trust cultivated through a personalised user experience. These findings recommend that industry practitioners focus on enhancing personalisation algorithms and transparency to build trust and leverage social influence in marketing efforts to encourage adoption.34 0Item Restricted Exploring the experiences and concerns about privacy and security in online teaching by students and teachers in the United Kingdom and Kingdom of Saudi Arabia(Saudi Digital Library, 2025) Almekhled, Basmah Fahad; Petrie, HelenThis research programme investigated experiences of online teaching and related privacy and security concerns before and since the pandemic among HEI students and teachers in the United Kingdom (UK) and the Kingdom of Saudi Arabia (KSA). As there is little cross-cultural research on these issues, five studies were conducted to explore them. Studies 1 and 2 were online surveys with students. UK students reported difficulties due to the pandemic with practical, interaction, and social isolation. In contrast, KSA students reported difficulties with focus, engagement, and technical issues. UK students used webcams selectively, whereas KSA students reported little use. Privacy and security concerns were low among UK students but moderate among KSA students. Studies 3 and 4 were online surveys with teachers. UK teachers struggled with students not using their webcams during online teaching, whereas KSA teachers faced communication and assessment issues. Both groups reported difficulties with student engagement. KSA teachers reported low webcam use, whereas UK teachers reported high use. Privacy and security concerns were low among UK teachers but moderate among KSA teachers. Study 5, a field study in a KSA HEI, found neither students nor teachers used webcams in teaching. Students cited flexibility, distractions, and privacy concerns, whereas teachers cited distractions and security concerns. Students reported high levels of privacy concerns about their institutions but only moderate concern about teachers and classmates. Complex relationships were found between students’ online privacy, security concerns and trust. Studies 6 and 7 were online surveys which explored KSA and UK HEI teachers experiences and attitudes in more detail. Both groups valued webcam use for engagement, but UK teachers felt self-conscious and struggled with students' webcams presence, while KSA teachers had privacy, security and cultural concerns. Both groups were uncertain about institutional webcam policies and expressed limited satisfaction with privacy and security guidelines. These findings highlight the need to address webcam use and privacy and security concerns in online teaching in relation to cultural and educational contexts.16 0Item Restricted Enhancing Trust Modelling for the Internet of Underwater Things(University of Nottingham, 2025) Almutairi, Abeer; Furnell, Steven; Carpent, XavierThe Internet of Underwater Things (IoUT) has gained growing interest from researchers and industry alike, due to its potential for advancing the development of smart cities and underwater intelligent systems. However, the harsh and unpredictable nature of underwater environments, coupled with the inherent limitations of existing technologies, presents significant challenges to establishing a sustainable IoUT. Furthermore, the open nature of such networks renders them highly susceptible to malicious attacks and security threats. Traditional security measures, which are widely implemented in conventional cyber systems, exhibit severe performance constraints in underwater networks, highlighting the urgent need for novel security solutions that meet the unique requirements of underwater networks. Trust modelling has been widely recognised as an effective soft security measure to mitigate the impact of internal attacks. It primarily achieves this by analysing behavioural characteristics between network entities, thereby introducing a layer of defence against malicious activities. In the context of underwater networks, trust establishment between nodes has the potential to significantly enhance overall network security. However, existing Trust Modelling and Management (TMM) often fail to address the complexities of underwater environments, which necessitate new TMM that are lightweight, accurate, and decentralised. In light of these limitations, this thesis investigates and enhances TMM to meet the application requirements of underwater networks while addressing the specific challenges inherent to IoUT. The central research question addressed in this thesis is: To what extent can existing TMM accommodate diverse network topologies within the IoUT and effectively mitigate potential attacks from both the communication and physical domains. In order to answer this question, a comprehensive understanding of the key challenges and potential application requirements for underwater networks is required. To facilitate this investigation, a simulated environment is constructed to analyse the effectiveness of TMM. This study critically evaluates the capabilities of current TMM in detecting malicious activities across various underwater network structures, identifying vulnerabilities, and exposing potential attack vectors. In response to these findings, this thesis proposes a distributed multi-dimensional TMM, referred to as the Mobility-Aware Trust Model (MATMU), designed to enhance the detection of malicious behaviour within the constraints of underwater environments. MATMU expands the metric domain to include mobility-aware metrics, allowing for the assessment of similarities and differences in node movement patterns. Additionally, the model employs a dynamic weighting strategy that integrates metrics from both the communication and physical domains. The performance of MATMU is evaluated through extensive simulations conducted across various underwater scenarios and attack models. The results demonstrate that MATMU effectively mitigates malicious behaviour, exhibiting notable improvements over benchmark models, particularly in terms of faster convergence and enhanced attack detection. These findings underscore the suitability of MATMU for strengthening secure and reliable communication in underwater networks. This thesis also tackles the critical issue of dishonest recommendations within TMM in the IoUT context, which is introduced by malicious entities, aiming to manipulate trust computations by providing false or misleading recommendations, thereby degrading the reliability and stability of the TMM. A novel recommendation evaluation method is introduced, combining filtering and weighting strategies to more effectively detect dishonest recommendations. The proposed model incorporates an outlier detection-based filtering technique and deviation analysis to evaluate recommendations based on both collective outcomes and individual experiences. Furthermore, a belief function is employed to refine recommendations by assigning weights based on criteria such as freshness, similarity, trustworthiness, and trust decay over time. This multi-dimensional approach demonstrates a marked improvement in recommendation evaluation, effectively capturing deceptive behaviours that exploit the complexities of IoUT. The effectiveness of the model is validated through extensive simulations and comparative analyses with existing trust evaluation methods, demonstrating consistently high performance across varying proportions of dishonest recommendations, with the highest accuracy improvement observed when dishonest recommendations constitute up to 45% of the total recommendations. These findings underscore the model’s potential to significantly enhance the reliability and security of IoUT networks.25 0Item Restricted Measuring Human’s Trust in Robots in Real-time During Human-Robot Interaction(Swansea University, 2025) Alzahrani, Abdullah Saad; Muneeb, Imtiaz AhmadThis thesis presents a novel, holistic framework for understanding, measuring, and optimising human trust in robots, integrating cultural factors, mathematical modelling, physiological indicators, and behavioural analysis to establish foundational methodologies for trust-aware robotic systems. Through this comprehensive approach, we address the critical challenge of trust calibration in human-robot interaction (HRI) across diverse contexts. Trust is essential for effective HRI, impacting user acceptance, safety, and overall task performance in both collaborative and competitive settings. This thesis investigated a multi-faceted approach to understanding, modelling, and optimising human trust in robots across various HRI contexts. First, we explored cultural and contextual differences in trust, conducting cross-cultural studies in Saudi Arabia and the United Kingdom. Findings showed that trust factors such as controllability, usability, and risk perception vary significantly across cultures and HRI scenarios, highlighting the need for flexible, adaptive trust models that can accommodate these dynamics. Building on these cultural insights as a critical dimension of our holistic trust framework, we developed a mathematical model that emulates the layered framework of trust (initial, situational, and learned) to estimate trust in real-time. Experimental validation through repeated interactions demonstrated the model's ability to dynamically calibrate trust with both trust perception scores (TPS) and interaction sessions serving as significant predictors. This model showed promise for adaptive HRI systems capable of responding to evolving trust states. To further enhance our comprehensive trust measurement approach, this thesis explored physiological behaviours (PBs) as objective indicators. By using electrodermal activity (EDA), blood volume pulse (BVP), heart rate (HR), skin temperature (SKT), eye blinking rate (BR), and blinking duration (BD), we showed that specific PBs (HR, SKT) vary between trust and distrust states and can effectively predict trust levels in real-time. Extending this approach, we compared PB data across competitive and collaborative contexts and employed incremental transfer learning to improve predictive accuracy across different interaction settings. Recognising the potential of less intrusive trust indicators, we also examined vocal and non-vocal cues—such as pitch, speech rate, facial expressions, and blend shapes—as complementary measures of trust. Results indicated that these cues can reliably assess current trust states in real-time and predict trust development in subsequent interactions, with trust-related behaviours evolving over time in repeated HRI sessions. Our comprehensive analysis demonstrated that integrating these expressive behaviours provides quantifiable measurements for capturing trust, establishing them as reliable metrics within real-time assessment frameworks. As the final component of our integrated trust framework, this thesis explored reinforcement learning (RL) for trust optimisation in simulated environments. Integrating our trust model into an RL framework, we demonstrated that dynamically calibrated trust can enhance task performance and reduce the risks of both under and over-reliance on robotic systems. Together, these multifaceted contributions advance a holistic understanding of trust measurement and calibration in HRI, encompassing cultural insights, mathematical modelling, physiological and expressive behaviour analysis, and adaptive control. This integrated approach establishes foundational methodologies for developing trust-aware robots capable of enhancing collaborative outcomes and fostering sustained user trust in real-world applications. The framework presented in this thesis represents a significant advancement in creating robotic systems that can dynamically adapt to human trust states across diverse contexts and interaction scenarios.21 0Item Restricted ACCEPTANCE OF BLOCKCHAIN TECHNOLOGY BY HIGHER EDUCATION INSTITUTIONS IN THE KINGDOM OF SAUDI ARABIA(Aston University, 2025) Alhumayzi, Mohammed; Batista, Luciano; Benson, VladlenaThe increasing adoption of new technologies in the Higher Education Institutions (HEIs) sector highlights the importance of exploring blockchain acceptance among employees. Adopting blockchain, as an emerging technology, is likely to encounter resistance among employees. This study explores this issue. Specifically, this study aims to determine the drivers and hindrances of blockchain acceptance among employees in the HEIs industry. To address this aim, this study proposes a framework that extends the unified theory of acceptance and use of technology (UTAUT) with individual characteristics. The framework represents factors that explain blockchain acceptance. The identified elements are performance expectancy (PE), effort expectancy (EX), social influence (SI), facilitating conditions (FC), trust, perceived security (SEC) and awareness (AW). The relationships among these factors were examined based on a quantitative approach, where an online questionnaire was employed to collect data from administrative and academic staff working for HEIs in the Kingdom of Saudi Arabia (KSA). Partial Least Squares Structural Equation Model (PLS-SEM) and Multi-group Analysis (MGA) techniques were employed to analyse 394 responses. The findings of this study revealed the direct drivers and hindrances of blockchain acceptance, i.e., PE, FC, SEC and AW. Additionally, this study demonstrated the moderating effects of AW between FC and blockchain acceptance. Furthermore, it determined specific indirect effects of the EX, trust and SEC on blockchain acceptance. Moreover, this research detected significant differences between categories’ subsamples and identified the significant factors of blockchain acceptance per subsample. Finally, this research identified where blockchain needs to be adopted most within the HEIs, i.e., financial exchange, certificate management, and students’ assessment areas. The HEIs industry in KSA could use these findings to develop concise strategies that encourage the adoption of blockchain. Scholars might also employ the proposed framework to investigate the adoption of blockchain.33 0Item Restricted Employing communication for building learned trust in autonomous vehicles, A qualitative pilot study.(Politecnico Di Milano, 2024) Alharbi, Eilaf; Borghetti, Fabio; Bianchini, BeatriceAs autonomous vehicles (AVs) advance towards full automation, trust between passengers and the automated systems becomes a critical factor to their existence. This research presents a pilot study on developing a design framework to help build and maintain a dynamic learned trust during interactions with fully autonomous vehicles by exploring various information types, structures, and communication modalities. The study draws on insights from previous research, semi-structured interviews with 6 users and 3 experts to identify key design elements that influence trust. Key findings suggest that minimizing driving-related information and instead focusing on journey-related details can prevent passengers from feeling the need to monitor the vehicle’s decisions, thereby fostering trust. The concept of "Information on Demand" emerged as a valuable approach to balance transparency and personalization, allowing passengers to request specific information whenever is needed. Additionally, "technical explanations" were identified as effective in restoring trust when errors occur, emphasizing the importance of timely and clear communication. The research also highlighted the limited impact of non-driving tasks, such as entertainment on trust. Furthermore, communication modalities should be tailored to the type of information being conveyed, taking into account various risks and the passengers’ ability to process different communication methods. This pilot study’s results lay the foundations for a larger scale study aiming to examine various factors that influence the dynamic learned trust during the interaction with the automated system in the vehicles.27 0Item Restricted Factors driving Mobile Shopping Apps Loyalty in the UK(University of East Anglia, 2024-08-22) Alkhairallah, Khulud; Alotaibi, DalalThe widespread adoption of digital technologies has substantially transformed many aspects of daily life, especially retail and consumer behaviour. A significant increase in online shopping through mobile applications is anticipated in the UK due to the growing popularity of smartphones, a trend known as mobile shopping (M-shopping) or mobile commerce (M-commerce). This dissertation investigates the factors influencing customer loyalty in M-shopping apps, an area that has not been extensively explored in existing literature. This study, which focuses on the UK market, looks at how user loyalty in mobile shopping applications is affected by four factors namely service quality, perceived usefulness, perceived ease of use, and trust. A questionnaire survey was conducted and 201 valid responses were received. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to analyse data and to test the research hypotheses. The analysis revealed that all four factors have significant direct influence on M-Shopping loyalty and they account for 61.1% of the variation in mobile shopping loyalty in the UK. The study offers practical insights for companies looking to increase customer loyalty in the ever-changing digital marketplace. It pinpoints strategies for improving these factors. The findings also advance our knowledge of how changing digital interactions and customer expectations affect loyalty in mobile shopping.38 0