2828 research outputs found
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The Environmental and Economic Impacts of the Use of Recycled Asphalt During the Preventive Maintenance of Roadways in the UAE
No full textThis open access book presents contributions on a wide range of scientific areas originating from the BUiD Doctoral Research Conference (BDRC 2023)This article studies the environmental and economic benefits expected from using recycled asphalt pavement in roadway maintenance by comparing the life cost analysis of conventional and recycled pavement. When comparing recycled and conventional asphalt, it turns out that the recycled asphalt cost is 28,060,400 Dhs compared to conventional asphalt's cost of 40,207,900 Dhs. Consequently, utilizing recycled asphalts will save around 12,147,500 Dhs, which is about 70% of the expense divided between the two pavements. This is because the duration of each maintenance process is different recycled asphalt requires 9 steps, which is the same as 33 days, compared to 12 steps for conventional asphalt, which requires 85 days. Calculating the waste from Dibba-Masafi Road is 23,104 m with the conventional pavement shows that managing this construction area’s waste is a challenge within its given rising volume of waste. However, by using recycled asphalt 3040 m of waste will be consumed which is a good amount to start a change in the roadway maintenance processes. Moreover, the assets that should be included in the roadway components, the norms and requirements set forth by the relevant authorities, and the minimal construction cost determined by quantity surveying are taken into account which resulted in the findings of this research demonstrating recycled asphalt as a long-term fix
The Challenges of Implementing the Emirates Standardized Test as a Proficiency Test in the UAE: An Exploratory Study
No full textThis open access book presents contributions on a wide range of scientific areas originating from the BUiD Doctoral Research Conference (BDRC 2023)This study investigated teachers’ and educational leaders’ perspectives regarding the challenges that EFL twelfth graders encounter in relation to the Emirates Standardized Test (EmSAT). The study context was a private school in the UAE that follows the Ministry of Education curriculum. The present qualitative study adopted the phenomenological interpretive research approach. Data were collected using semi-structured interviews with four English teachers and four educational leaders. Data were also analysed using thematic analysis that led to the creation of relevant themes. The findings revealed a number of challenges related to the EmSAT exam and recommendations to overcome these barriers. These included issues related to time constraints, anxiety, stress, lack of teaching resources, and learners’ low e-maturity level. The study had some implications for teachers, educational leaders, school administrations and policymakers
The Impact of Organisational Structure on Project Performance in the Energy Sector
No full textPurpose – The objective is to explore the impact of organisational structure on project performance and current research topics regarding organisational structure theories, types, and aspects in terms of challenges, culture, communication, organisational dynamics, and drivers.
Methodology – The adopted methodology employs two integrated approaches. First, use a systematic mapping approach to explore the existing research studies on organisational structure’s impact. Second, correlate the research studies to existing case studies in the energy sector, record findings, and propose recommendations on the way forward.
Findings – The study results concluded that most oil producers are a mix of functional and matrix organisations with diversified thoughts on centralizing project management teams.
Implications/limitations – It is essential to conduct follow-up research validating the potential for using the findings of this study to establish frameworks for the organisational transformation approach in meeting cultural variance and market conditions.
Originality/value – The proposed case studies and relevant theories present the most effective organisational structure model to improve project-based operations performance, thus enabling oil and gas organisations to manage their business mandates effectively
Grey Literature (GL): Access and Use Potentials for Healthcare Education Professionals in Developing Context: Ghana as a Case
No full textThe growing interest in grey literature (GL) is attributed to the fact that it constitutes a significant part of scientific production. The proliferation of alternative/complementary approaches to professional practice as well as new modes of delivery that bring in new forms of knowledge and usage have made GL more essential to inform practice and theory. Similarly, the rise of advanced and sophisticated technologies for storing, retrieving and sharing of information have also improved and encouraged the use of GL by practitioners across different practice sectors. However, majority of the research and papers on GL is cast within the context of literature review for the purposes of research and library practice (management – obtaining, storing, sharing etc). In addition, there is limited focus on how practitioners access and use GL to inform their practice. In developing contexts such as in Africa, the importance of GL has been highlighted but the main issues are that it is not adequately documented, as well as limited national and regional databases and access issues. These issues have negatively affected the use of GL in many developing contexts. This research paper assesses access and potential use of GL by healthcare education professionals in a developing context through a critical analysis of the characteristics of online repositories from 5 selected public higher education institutions in Ghana. The finding shows that the case institutions’ online repositories hold large databases of GL with many items relevant to healthcare education. It also indicates that many of the repositories are accessible online and have appropriate search engines that facilitate access and retrieval of documents. These characteristics post positive potential for access and use of grey literature by professionals. However, the finding highlights issues with intermittent access to internet in some of the repositories; lack of organised access and retrieval of GL materials. The paper provides a few recommendations which include provision of modern IT systems and stable internet connectivity to institutions holding large GL databases
The Impact of Integrating Artificial Intelligence on Students’ Learning: Teachers’ Approach and Perspectives from Selected Private Schools in Al Ain
No full textDetermining whether the integration of artificial intelligence in education is a promising technology to develop students’ metacognition or a threat to the human mind leading to unintended consequences has proven to be a problem. Comprising of 132 participants, this study aims to examine the impact of integrating artificial intelligence in education with respect to the teachers’ perspective and approach in private schools within Al Ain, UAE. The main research question targets teachers’ attitudes and perspectives on the impact of AI integration on students’ learning. The goal is to determine a framework which aligns the use of artificial intelligence with existing learning theories. This research delves into the body of related literature, consulting theories such as the three paradigmatic shifts and self-determination theory A purposeful mixed-methods approach is conducted to investigate and analyse educators’ perception, readiness, practice, and potential impact on students’ learning. The key findings identify the need for continuous specialised training programmes, the teachers’ inclusive role in urgently restructuring the automated curriculum, and intelligent learning platforms. The implications of this study provide insights to the educational system in the UAE as it introduces AI into its schools. To conclude, teachers’ perceptions and practice towards AI are fundamental to determine how the integration is implemented into the educational sector, while establishing guidelines with an ethical framework of regulations and creating individualised learning opportunities. Further studies are encouraged to expand wider among educational organisations and institutions in the future
Arabic Dialect Speech-Text Recognition Using Deep Learning
No full textRecently, the dominant utilization of media networking has emphasised the importance of precisely identifying users’ feelings, covering a spectrum from contentment to dissatisfaction, in the domain of online communications. The dissertation addresses the challenges of accurately transcribing Arabic speech due to the language’s complexity, limited audio resources, and diverse regional variations. Traditional speech recognition models struggle in this domain, prompting an exploration of deep learning approaches, specifically the TestRCNN and Hybrid TestRCNN-CNN Models. The research begins with a comprehensive preprocessing process, which involves loading audio data, extracting features using Mel-Frequency Cepstral Coefficients (MFCCs), and encoding labels. Both models are trained and evaluated on a curated dataset of Arabic speech samples, capturing the spatial and temporal features. The TestRCNN Model combines convolutional layers for local feature extraction and recurrent layers to capture temporal dependencies. It achieves an accuracy of 93% and a word error rate (WER) of 0.0986, but faces difficulties in distinguishing closely related phonetic sounds. To address these limitations, a hybrid approach is proposed, combining the TestRCNN and CNN architectures. This hybrid model leverages the CNN’s ability to extract detailed spatial features and the TestRCNN’s proficiency in capturing long-term dependencies. The Hybrid TestRCNN-CNN Model outperforms the TestRCNN, achieving an accuracy of 94% and significantly reducing the (WER) to 0.0460. The dissertation provides a detailed comparison of these models’ operational features, hyperparameters, and outcomes. Through extensive experimentation, the study highlights the hybrid approach’s advantages in accurately transcribing Arabic speech and contributes valuable insights to the field of Arabic speech recognition research
How Dynamic Capabilities in Maintenance Enable Metal Plants in the UAE Via Big Data Analytic Capabilities Towards Digital Twins Adoption? A Mediation and Moderation Analysis
No full textThe research employed a standardised survey to explore how Dynamic Capabilities (DCs) are influencing the adoption of Digital Twins (DTs) through Big Data Analytics Capabilities (BDAC) as a mediator variable. Furthermore, it also inspects the influence of Digital Leadership (DL) as a moderator variable in above relationship in terms of maintenance in metal plants in United Arab Emirates (UAE). This research reveals a correlation between above indicated variables based on practical responses from maintenance. Results will definitely support the improvement of maintenance performance in metal plants. Mediation and moderation analyses were conducted using SmartPLS4 to test four hypotheses based on data collected from 183 respondents, comprising managers, engineers and technicians from maintenance departments in various metal plants in UAE. As hypothesised, research findings suggest that BDAC plays a mediating role in relationship between DCs including seizing (SEZ) and transforming (TRF) and adoption of DTs. However, sensing (SEN) has neither a direct nor an indirect relationship with DTs. Additionally, low DL significantly strengthens moderation effect in terms of positive relationship between BDAC and adoption of DTs. These findings confirm need of this research's key predictor variable - DCs, BDAC and moderator variable DL - in driving organisational readiness toward digital transformation. The research is limited and should not be generalised given that it has only focused on analysing collected data from one sector - metal plants industry in the UAE. Future research should focus on analysing how applicable this framework is across other industries while investigating factors for adoption of DTs
Highlighting the Impacts of Parents’ Beliefs on Students’ Education
No full textThis open access book presents contributions on a wide range of scientific areas originating from the BUiD Doctoral Research Conference (BDRC 2023)Purpose- To highlight the impacts of parents’ beliefs on students’ education due to the dearth of such studies in the field of education.
Methodology- A sequential mixed-method approach was utilised, where quantitative data were collected and analysed, and then triangulated with qualitative data. The study employed a questionnaire and semi-structured interviews completed by 51 and nine parents, respectively. Convenience sampling was used.
Findings- The obtained data showed that parents’ beliefs play a key role in students’ education, as these beliefs are associated with parents’ expectations regarding their children. Moreover, parents’ beliefs function as a guide for their children’s efforts and endeavours.
Implications- This study recommends that increasing parental awareness regarding their role in their children’s education would be an effective strategy that would provide students with an enhanced learning environment.
Originality/value- This study is considered of great value as it urges policy makers and leaders to increase investment in the parents’ role in students’ education
Success Factors in Adopting AI in HRM: Perspective From the Private Sector in UAE
No full textArtificial intelligence (AI) is emerging as a transformative force in technological advancement, impacting the success of diverse business sectors. However, research on the specific success factors in AI adoption, especially in human resource management (HRM), remains limited. Previous studies have predominantly focused on AI techniques and applications within IT and industrial sectors rather than the HR context and primarily address applications like recruitment rather than exploring broader HR functions. This study aims to address these gaps by identifying key success factors for AI integration in HR across various applications, with a specific focus on the private sector in the United Arab Emirates (UAE), an area largely unexplored in existing literature. This research uses the Technology, Organisation, and Environment (TOE) framework combined with the Diffusion of Innovation (DOI) theory to investigate how these success factors influence AI adoption in HRM. Adopting a quantitative methodology, surveys were administered across UAE private firms to examine variables including factors under the Innovation feature of AI such as compatibility, relative advantage, complexity, trialability, and observability. Internal factors, such as top management support, organizational readiness and technical capability, and managerial capabilities along with external factors like government regulations and pressure, competitive pressure, Market status, and vendor partnerships, were also considered. Data analysis was conducted using SPSS and AMOS, employing tests such as Common Method Bias (CMB), Exploratory and Confirmatory Factor Analysis (EFA and CFA), and Structural Equation Modelling (SEM). This study provides insights into effective resource allocation for HR leaders considering AI adoption, offering implications for both theory and practice. The findings address key research questions, outline practical recommendations, and suggest avenues for future research to bridge existing literature gaps. Ultimately, this research will offer HR leaders in UAE private firms a framework to better understand and overcome AI adoption challenges, enabling informed decision-making and enhancing the strategic use of AI across HR functions and practices.
Keywords: AI adoption, human resource management, Diffusion of Innovation Theory (DOI), Technology Organization and Environment Theory (TOE), Success factors, UAE private sector, Innovation feature of AI, Internal effect, External effect, and SPSS AMOS
The Impact of Effective Talent Management Practices on Market Capitalizing Agility, Agile Innovation and Agile Creativity: a Quantitative Study in Knowledge-based Organizations
No full textTalent Management practices conceptualization captured considerable attention in the literature since the evolvement of the concept in the early 1990s, however, less attention has been given to empirical studies on the impact of Talent Management practices on organizational competitiveness. This empirical study considers the impact of effective talent management practices on competitive organizational agility (market capitalizing agility, agile innovation, and agile creativity) directly and through the mediating effects of operational adjustment capacity and absorptive capacity. The research population is knowledge-based organizations in the private sector. The findings presented are based on a deductive quantitative research design utilizing a positivist approach through deploying a cross-sectional survey. Responses to the survey were collected at an organizational level. Organizations in the UK were targeted with a sample size of 314. Data were analyzed through a Partial Least Square approach to Structural Equation Modeling (PLS-SEM) using smartPLS version 4. The present study addresses multiple gaps existing in the literature. The findings indicate a statistically significant positive relationship between effective talent management practices and agile innovation, agile creativity, operational adjustment capacity, and absorptive capacity. Also, the findings indicate that the relationship between effective talent management practices and market capitalizing agility, agile innovation, and agile creativity is mediated through absorptive capacity. Furthermore, the relationship between effective talent management practices and market capitalizing agility and agile creativity is mediated through operational adjustment capacity. To the best of the researcher’s knowledge, this is one of the first studies that attempted to quantitatively investigate these relationships