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.
Submit your dissertation/thesis by completing the registration using your BUiD email.
Review the submission guidelines before you submit the final version
Communities in BSpace
Select a community to browse its collections.
- This community includes the articles, book chapters, conference and working papers published by BUiD staff members.
- This community includes the Theses and Dissertations submitted by Faculty of Business and Law students
- This community includes the Theses and Dissertations submitted by Faculty of Education students
- This community includes the Theses and Dissertations submitted by Faculty of Engineering and IT students
- The Journal is run by the Faculty of Education, The British University in Dubai (BUiD).
- This community includes the Newsletters published by the BUiD library
- This community includes the BUiD conference papers, newsletters and magazines.
Recent Submissions
The Impact of Time and Cost Management Practices on Labour Productivity in the UAE Construction Industry
(The British University in Dubai (BUiD), 2024-10) MABROUK, ZAKKARIA; Dr Muhammed Waris Khan
The purpose of this study is to identify the impact of time and cost management on the productivity of labour within UAE construction firms. Construction companies like Emaar and Arms Construction have focused on time and budget optimisation activities in terms of executing construction activities in the UAE. The optimisation of time and cost ensures the projection of the highest utilisation of the financial and human resources, which results in achieving the highest labour productivity with lower investment. Technology tools like BIM, 3D printing, and project management software are used for optimising the cost and time usage that delivers the highest efficiency of financial and human resources in terms of the construction of buildings.
In this study, the data collection is primary and it is done with managers, engineers, supervisors, etc., with the process of analysis carried out through the help of SPSS. The findings suggest that the major factors that are required to be improved by construction managers constitute the proper estimation of costs, project scheduling, and the proper allocation of resources. It is also linked with the right kind of control for risks and proper communication with quality parameters. It was also found that BIM integration, 3D modelling, and software linked with project management help in improving the process of managing construction projects. The integration of BIM, 3D printing, and project management software has made work easier in the construction sector in terms of designing unique and innovative building designs, and the application of software tools has made the completion of projects easier with fewer mistakes.
Keywords: Technology tools, Time and cost management, Optimisation, Resource usage
Adaptive and Ambidextrous Differentiation: The Role of Digital Transformation and Strategic Orientations on UAE Enterprises Sustainability
(The British University in Dubai (BUiD), 2024-10) AL JABRI, MADHAD ALI SAID; Dr Lahrech, Abdelmounaim
Previous research has highlighted the importance of firms building up their resources continuously to gain competitive advantage and remain viable in the fast changing and dynamic market. This is achieved by resources renewal enabling unique innovative products offerings and operational excellence resulting from all kind of strategic capabilities. However, firms’ ability to maximise opportunities realisation and balance their exploration and exploitations varies due to various contextual and organisational challenges such as digital maturity and strategic orientations which plays a crucial role in the evolving digital ecosystem. To improve our understanding on how firms can achieve sustainable competitive advantage and what strategies (outside-in or inside-out) need to be followed while uncovering whether strategy should be static, dynamic, adaptive or ambidextrous, this empirical research study examines how adaptive marketing capability influence firm's long-term survival and sustainability in the marketplace. This investigation is done considering the joint effect of market ambidexterity mediation and the moderation of both strategic orientations and digital transformation. This assessment is made using a deductive, quantitative method as the researcher philosophy is more positivism where a survey is a technique adopted and a Likert questionnaire is designed to collect data from ICT, IT and Telecom digital services enterprises in the UAE context where digital transformation is given a focus during and post the COVID-19 Pandemic and EXPO2020 event. Previous published literature was used to adopt validated scale where 224 responses were tested using IBM-SPSS 26.0, Smart PLS 4.0, and IBM- Amos 26.0. Data were analysed using variance based structural equation modelling (SEM) due to the model complexity and sample size as well as the non-uniform distribution of the sample data. The results suggest that adaptive marketing capability is statistically positively related to sustainable competitive advantage through market ambidexterity and the joint effect of digital transformation and strategic orientation is significant as mediation-moderation on this relationship. However, the impact of adaptive marketing capability found in-significant as a direct relationship and on a similar manner while digital transformation is moderating this direct relationship. Also it was found that firms with strategic orientations are more likely to leverage the ambidexterity capability leading to sustainable competitive advantage. This study contributes to literature on providing more insights on how marketing and strategic management interact to provide long-term competitive advantages in extremely volatile digital environment with global open ecosystem. It also enlightens the market ambidexterity body of knowledge during digital transformation and strategic orientations cultural shift programs. It also provides better understanding on the intersect between Resource Advantage theory, dynamic capability theory, organisational ambidexterity and adaptive marketing capability views. In addition, it proposes a converged (strategic and marketing management convergence in digital era) theoretical framework for future research. It offers executives practical insights on how to utilize the digital transformation and ambidexterity programs for building strategic ambidextrous capabilities that balancing the tensions between the exploration and exploitation activities and developing strategic orientations that is risk taking and with a culture of positive engagement to enable higher organisational success.
Keywords: Adaptive Marketing Capability, Sustainable Competitive Advantage, Market Ambidexterity, Strategic Orientations, Digital Transformation, Dynamic Capability Theory, R-A Theory
Deep Learning Speech-Text Chatbot for High School Advising
(The British University in Dubai (BUiD), 2024-11) Assayed, Suha Khalil; Dr Manar AlKhatib
High school is a crucial stage for students as they begin to shape their future. During this time, students need to identify their strengths and interests, choose the right curriculum, and prepare for university applications, including admission tests and selecting majors. However, not all high schools can afford college-career advisers to assist students with these important decisions, leaving some students less prepared for their future compared to those who receive guidance. This thesis addresses the challenges faced by both students and advisers in schools, proposing a novel, affordable bilingual speech-text chatbot designed to provide equal support to all high school students, including those in underprivileged schools. We explored various deep neural network models to determine the most effective model for this task. The proposed architecture integrates an encoder-encoder framework with different layers of deep recurrent neural networks (RNN), such as LSTM, BiLSTM, and stacked LSTM layers. Additionally, automatic speech recognition (ASR) is incorporated to convert spoken inquiries into text, allowing the chatbot to generate effective responses. Evaluation using the ROUGE metric showed that the BiLSTM layer achieved the highest performance, particularly in precision. A qualitative study comparing our chatbot (HSGAdviser) with ChatGPT revealed that students preferred our chatbot, especially for Yes/No questions, demonstrating its potential to provide equal, accessible advising for all students.
Sustainable Vs. Conventional Villa A Case Study of Sheikh Zayed Housing Programme, Al Seyouh-Sharjah
(The British University in Dubai (BUiD), 2024-03) AL HOSANI, RASHID; Professor Bassam Abu-Hijleh
The Gulf Region has witnessed rapid economic growth and infrastructural development beginning in the 21st century. The United Arab Emirates has emerged as one of the region's major economic and technological hubs due to its distinct commercial infrastructure, thereby growing its reputation. Against this backdrop, this paper's primary concern lies within the country’s housing infrastructure for its citizens.
As the country is undertaking massive housing projects as part of its ongoing infrastructure progress, the paper seeks to inform the government about cost reduction techniques to alleviate the government and its citizens’ pockets in the housing sector while enhancing sustainability. These techniques are critical considerations for reducing utility costs with optimized efficiency.
The four critical proposed parameters in this respect are HVAC, lighting parameters, building envelope, and solar water heaters. The study has found that HVAC systems with a higher coefficient of performance upgraded from the current 3.4 to 3.6 and 4.1 provide a potential 2.3 to 7.0% energy savings and simultaneously enhance sustainability. The study has also found that optimizing lighting parameters with the proposed Lighting Power Density Scenarios achieves energy savings ranging from 10.4% to 13.9% in villas.
Furthermore, the study discovered that utilizing a more optimized range of U-Values in building envelopes can save housing utility energy, lowering annual costs for inhabitants by at least 10.9%. Finally, the report found that switching from conventional power to solar water heaters results in a 7.1% savings. Overall, the study discovered that applying all the above-mentioned parameters can result in total average energy savings ranging from 26% to 30%.
Deep Learning for the Extraction of Aspects in Textual Opinions
(The British University in Dubai (BUiD), 2023-07) ALSEREIDI, MOHAMED SOHAIL
This study aimed to explore the effectiveness of deep learning models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformer-based models, and Graph Neural Networks (GNNs), in aspect-based sentiment analysis (ABSA) of textual opinions. The research conducted a comprehensive literature review to analyse existing studies and articles in the field, focusing on comparing the performance of deep learning models with traditional rule-based or lexicon-based approaches. The findings indicated that deep learning models demonstrated promising results and surpassed the performance of traditional methods in ABSA. CNN-based models, in particular, achieved remarkable outcomes on benchmark datasets. Transformer-based models, such as BERT and RoBERTa, also exhibited strong performance across various natural language processing tasks, including sentiment analysis. Additionally, GNNs showcased potential in leveraging text structure to improve aspect and sentiment extraction. The research identified a research gap, emphasizing the need for further exploration and advancements in the utilization of deep learning models for ABSA. This study contributes to the understanding of the potential of deep learning in ABSA and provides insights for future research in this field.