BSpace

The British University in Dubai (BUiD) Digital Repository

Welcome to BSpace, the online institutional repository of the British University in Dubai. BSpace provides access to the Dissertations, Thesis, Research projects, Faculty publications and archives of BUiD.

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Recent Submissions

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    The Project Manager Competencies Towards Effective Performance of AI Projects in the UAE Banking Sector
    (The British University in Dubai, 2024-12) ALZAABI, ALYA HASSAN ALI IBRHIM; Dr Khan, Muhammed Waris
    The use of artificial intelligence (AI) in the UAE banking sectors has created an urgent demand for project managers with specialised skills to lead these complex initiatives effectively. While AI adoption accelerates across UAE banks, a limited understanding of the specific skills and capabilities required for successful project implementation remains. The current research aims to investigate the relationship between defining project manager competencies and AI project success in UAE banking. The research employed a quantitative cross-sectional design, collecting data from 76 project managers across UAE banks through a structured questionnaire. Statistical analysis revealed strong relationships between project manager competencies and AI project success. Leadership abilities emerged as the strongest predictor (d = 0.782, p < 0.001), followed by technical skills (d = 0.724) and communication competencies (d = 0.698). Competencies explained 71.2% of the variance in stakeholder success (R² = 0.712). Organisational size significantly moderated competency-success relationships, with stronger effects in larger banks (effect size = 0.456). All hypothesised relationships demonstrated significant positive effects with good model fit indices (CFI = 0.942, RMSEA = 0.058). The study provides empirical evidence that project manager competencies significantly influence AI project outcomes in UAE banking. The key recommendations incorporate developing integrated competency frameworks, contextualising training programs based on organisational characteristics, implementing comprehensive assessment centres, and establishing mentoring programs. These findings have critical implications for banking institutions in selecting, developing, and supporting project managers leading AI initiatives. Keywords: project management, artificial intelligence, banking sector, UAE, competencies, project success
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    A Dynamic Model Integrating Passenger Satisfaction Analytics and Pedestrian Simulation for Optimizing Metro Station Performance and Enhancing Passenger Experience
    (The British University in Dubai (BUiD), 2025-12) ALSALEEM, MOAMIN HAMEED; Prof Abu-Hijileh, Bassam
    This study develops a fully dynamic model to systematically assess metro station performance and passenger satisfaction, integrating the American Customer Satisfaction Index (ACSI) model with Structural Equation Modelling (SEM), Partial Least Squares (PLS) regression, and agent-based pedestrian simulation. A conceptual framework, consisting of 28 key indicators for SEM, refines passenger satisfaction indicators (PSI) through PLS regression to explore relationships between satisfaction drivers and metro performance. Importance-Performance Analysis (IPA) is also employed to identify key satisfaction factors. The research uniquely integrates SEM-PLS results with pedestrian simulation. ACSI SEM-PLS provides insights into passenger satisfaction, which are then used in ped simulation to predict the impact of projected ridership growth (3%, 5%, and 7% from 2030-2040) on station key performance indicators (KPIs). This combined approach offers a full understanding of passenger perceptions and operational dynamics. The study finds that current infrastructure will not support the anticipated ridership increase, leading to declines in station KPIs in efficiency (Space Density SD) and passenger experience (Passenger Density PS, Passenger Speed PS, Travel Time TT and Passenger Dissatisfaction Level PDL). To address these gapes, the study presents URBM model, which integrates improvements like expanded ticketing, improved circulation, and other strategies. These enhancements lead to significant gains across various KPIs metrics: SD improves by 44-56%, PD increases by 70-80%, PS rises by 53-70%, TT decreases by 11-16%, and PDL is reduced by 37-41%. The research contributes to knowledge by developing a KPI-driven framework that synthesizes satisfaction analytics with simulation modelling, thereby advancing methodological approaches in metro station design.
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    Exploring User Experience (UX) Design organizational maturity
    (The British University in Dubai, 2018-12) ALSAWALQA, MOHAMMED; Dr Ncube, Cornelius
    Designing for the best user experience when people are interacting with the digital world had been evolving through the years as many different methods emerged helping users interact in the most pleasurable, efficient, useful, and meaningful way. Many organizations suffer from low profits and become largely unsuccessful due to neglecting user’s needs and in the competitive online platforms novel technologies are driving the user experience to new heights and with-it high gains in short periods of time. The developed markets have had UX methods well-established for a while and billion-dollar brands that is user-driven are evidence for the value UX design could add to the bottom line. In the aim to understand the roots of UX design and what backgrounds UX practitioners need to have, this research brings a brief account of the different disciplines that contributed to modern UX design methods and practices from ergonomics, human computer interaction, cognitive psychology, any many more. The main goal was to explore the UX profession which depends mainly on the designers and the construction of specialized UX teams in organizations. Labeling any organization as UX-mature drove the research to analyze the available UX maturity models and develop a tailor-made model based on the data gathered through two questionnaires and interviews with UX experts and several case studies showing the value of good UX design.
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    Enhancing Cash Flow and Payment Certainty in UAE Construction: The Role of Project Bank Accounts in Mitigating Disputes
    (The British University in Dubai, 2025-11) ASHOUR, AMR IZEDDIN; Dr Al Eisaei, Hamad
    The foundation of construction as a business falls in its commercial nature, whether by exchanging a service, a product, or both for money. Therefore, nonpayment or delayed payment can and will affect transactions and the industry overall. Given that the construction industry occupies a big portion of the economy in the UAE and globally, negative implications extend beyond the industry itself to influence the broader economy. Therefore, solving payment issues is essential rather than a mere improvement. This dissertation evaluates the feasibility of implementing “Project Bank Accounts” (“PBAs”) to enhance payment certainty and cash flow within the UAE’s construction industry. First, the research analyses existing key payment legal frameworks and industry practices in the UAE and compares them with common law jurisdictions such as the United Kingdom, Australia, and New Zealand. Then, PBAs are introduced as a practical mechanism to close the identified payment security gaps in the construction sector in the UAE. PBAs are found to offer operational, legal, and administrative benefits to the industry due to their trust nature. PBA adoption can pave the way for future statutory adjudication introduction within the UAE legal framework. Also, PBAs can be merged with modern technologies such as blockchain to further advance efficiency, transparency, and accountability. Lastly, this dissertation provides findings and recommendations by ways of introducing PBAs through dedicated law reform within the UAE legal framework. It is found that this implementation would strengthen industry, support the economy, and back the UAE’s vision for innovation and a sustainable economy. Keywords: Construction, payment delay, payment certainty, dispute, project bank account, cash flow, legal framework, transparency, simultaneous, contractor, employer, subcontractor, statutory, policy, legal, efficiency.
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    Leveraging Retrieval-Augmented Language Models for Early Diagnosis in Resource-Constrained Healthcare
    (The British University in Dubai (BUiD), 2025-01) ZOHAIR, LUBNA MAHMOUD ABU; Prof Abdallah, Sherief
    Large language models (LLMs) encounter notable challenges when applied to sensitive domains such as healthcare, particularly where data is limited, highly confidential, and subject to strict regulatory frameworks. These challenges are especially pronounced in the context of rare disease diagnosis, where current approaches often rely on decoder-based models that are proprietary and prone to hallucinations and generation of inaccurate or misleading outputs. Additionally, the substantial computational demands of LLMs further limit their feasibility in resource-constrained or low-income settings. To address these challenges, this research proposes a framework that maximizes the diagnostic utility of small and early collected clinical datasets while leveraging the power of open-source pre-trained medical language models. The framework introduces Retrieval-Augmented Encoding (RAE), a technique designed to enhance the diagnostic performance of affordable language models with classification heads by retrieving similar clinical notes to enrich the encoding of input data and support inference in diagnostic tasks. It also employs Retrieval-Augmented Generation (RAG) to expand the training dataset through paraphrasing for fine-tuning. A case study on appendicitis diagnosis was conducted using 2,400 unstructured abdominal disease notes, focusing on the exploration of the diagnostic sufficiency of early-stage clinical notes such as the History of Present Illness (HPI). Results show that the proposed framework achieved diagnostic accuracy and precision rates exceeding 93.3% with the HPI notes alone, highlighting their potential for early and efficient diagnosis without reliance on additional unstructured notes, like Physical Examination. This research highlights how locally deployable language models can be used effectively in resource-constrained healthcare environments to support early and accurate diagnoses, particularly for rare diseases and critical clinical decisions. Keywords: large language models, small dataset, appendicitis, diagnosis, retrieval augmented generation, data augmentation, clinical notes, history of present illnesses, BERT models, rare disease, healthcare informatics