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The Impact of Artificial Intelligence on Institutional Recruitment and Selection Processes
No full textThis thesis examines the importance of artificial intelligence (AI) in reducing negative human intervention in recruitment and selection processes. The study uses a sequential approach to analyse the impact of ICT, AI, and recruitment and selection components on recruitment and selection processes. Data were collected through questionnaires distributed to employees of specific categories in Sharjah Government institutions in the UAE, with 251 participants agreeing to answer. The aim of the study is to respond to the research questions and hypotheses, engage in discussions, make practical contributions, and formulate recommendations. The literature review highlights the practical value of AI in selecting competent candidates for job vacancies in institutions. The research sheds light on the significance of AI in recruitment and selection processes, providing insights into how it can improve the efficiency and accuracy of selection procedures while reducing human biases. The study uses various statistical techniques such as structural equation modelling (SEM) analysis, multiple linear regression (MLR), descriptive and inferential statistics, and confirmatory factor analysis to identify the impact of AI on recruitment and selection processes. The results indicate that the use of AI to filter the CVs of job seekers and select qualified candidates for vacancies was perceived positively at a high level of significance (p ≤ 0.05), leading to reduced human errors in the process. The participants believed that most HR operations management in the future could depend on AI without human intervention. The research participants’ responses to using technology to enhance recruitment and selection processes were at a high level of significance (p ≤ 0.05). The participants also perceived the negative impact of key members on recruitment and selection processes at a high level of significance (p ≤ 0.05). The research proposes a framework for AI-assisted recruitment and selection processes, aiming to reduce errors and improve the selection of qualified candidates. It emphasises the need for institutions to establish new employment standards based on the use of AI technology and outlines key elements required for successful implementation, including infrastructure, specialised partnerships, employment platforms, and policy and regulation amendments. Overall, this study highlights the increasing significance of AI in enterprise operations and the need for researchers and specialists to consider AI as a key element for supporting production and services. The research sheds light on the importance of AI in recruitment and selection processes, providing insights into how it can improve the efficiency and accuracy of selection procedures while reducing human biases. The study was conducted with 251 participants from Sharjah Government institutions in the UAE, and the data were analysed using Statistical Package for Social Sciences (SPSS) software version 23 and STATA/MP software version 13.0
Estimation of Virtual Trust on Driverless Cars using Type-1 Fuzzy logic
No full textThe public's interest in self-driving automobiles
is growing daily. Because they improve our daily life and also
how they help us in various ways. They are also referred to as
robotic automobiles. These cars utilize cutting-edge technology
to efficiently address human mobility needs. Using the most
advanced technological elements, this is a significant
advancement in the automobile manufacturing sector. Over a
wireless network, these vehicles talk to one another. These
vehicles use cameras and sensors to take note of their
surroundings. Their whereabouts are monitored by GPS radar,
navigational pathways, and other tracking devices. If the
existing path is altered, the cars' positions are adjusted using a
sophisticated control system. These vehicles boost confidence,
increase road capacity, and decrease traffic accident. The major
benefit is a decrease in traffic enforcement, plus self-driving cars
consume less fuel than other types of vehicles and don't require
auto insurance. On the other hand, problems with software like
data security and dependability must be resolved. The most
crucial factor relates to driving jobs, which are the most
hazardous for people. The calculation of Virtual Trust (VT) in
driverless cars utilizing fuzzy logic design is the subject of this
study. Verified findings and analyses from the Mamdani Fuzzy
Inference System's (MFIS) test of virtual confidence in
autonomous vehicles. Utilizing MATLAB simulation, results
have been confirmed
Illegitimate Tasks, Negative Affectivity, and Organizational Citizenship Behavior among Private School Teachers: AMediated–Moderated Model
No full textSocial sustainability has gained popularity over the last decade, with a growing body of
research calling for researchers to focus on the personal-level determinants of employee satisfaction
and well-being in the pursuit of social sustainability. By using negative affectivity as a mediating
mechanism and gender and passive leadership as moderators, this study examines a novel sequential
mediation–moderation model that explores the relationship between unreasonable tasks and teachers’
Organizational Citizenship Behavior (OCB). It employs the Conservation of Resources (COR) and
Stress as Offense to Self (SOS) paradigms as acomprehensivetheoretical framework for organizational
stressors and organizational behavior. A total of 415 matched questionnaire responses were collected
Citation: Shaya, N.; Mohebi, L.; Pillai,
R.; Abukhait, R. Illegitimate Tasks,
Negative Affectivity, and
Organizational Citizenship Behavior
among Private School Teachers: A
Mediated–Moderated Model.
Sustainability 2024, 16, 733. https://
doi.org/10.3390/su16020733
Academic Editors: Sandro Serpa
and Maria José Sá
Received: 10 September 2023
Revised: 27 November 2023
Accepted: 29 November 2023
Published: 15 January 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
from private school teachers in the UAE. Confirmatory factor analysis (CFA) is conducted using
AMOS 20, hierarchical linear modeling (HLM) is utilized to verify the causal and moderation
hypotheses, and the resulting moderated mediated conceptual model is evaluated by employing
Hayes PROCESS analysis. Results demonstrate the effects of illegitimate tasks on OCB are indirect
and statistically significant and are mediated through negative affectivity. The cumulative effect
of illegitimate tasks and negative affectivity on OCB is magnified by the moderating effects of
passive leadership
Estimating the Reliability of the Inspection System Employed for Detecting Defects in Rail Track Using Ultrasonic Guided Waves
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 work focuses on the implementation of a data-based method to determine the inspection system reliability in terms of detecting different types of damages in rail tracks using ultrasonic-guided Rayleigh waves and a probability of detection (POD) technique. In this study, the reliability is tested against a surface crack (SC) and sub-surface damage – a through-side thickness hole (TSTH). The guided Rayleigh waves are generated using a custom-designed sensor that excites Rayleigh surface waves in the specimen and the propagating waves are sensed on the rail track surface. The wedge shape design of the sensor helps to excite a specific ultrasonic mode in the sample thereby hindering the ultrasonic energy of other coupled guided waves that can propagate simultaneously and the wedge angle is determined according to Snell’s law relying on the wave velocity of Rayleigh wave and bulk longitudinal wave. The guided wave responses as a function of varying severity of defects are obtained through a simulation study after the verification of the obtained guided wave responses with the help of an experimental study. A damage index (DI) is defined depending on defect size that gives the trend of damage severity from the captured ultrasonic responses and for monitoring defects in the rail track. This DI is eventually fed into the POD model to determine the probability of defect detection which in turn helps determine the inspection system reliability. The POD method also helps to study the critical design parameters that could affect or improve crack detection results.
Purpose – To determine the reliability of inspection system deployed for interrogating health status of rail track.
Methodology – Employing the Probability of detection technique for determining how reliable the inspection system is in detecting the health status of the rail track specimen using the ultrasonic guided waves.
Findings – It has been found that the proposed inspection system is >90% reliable in detecting defects.
Implications – This methodology can help maintenance engineers to make an informed decision on their developed technique for investigating the health status of the rail track sample.
Originality/ value – 13%
The Impact of Parent–Teacher Communication on Student Behaviour and Social Development in a Semi-Government School in Fujairah
No full textIn the realm of contemporary education, proficient communication between parents and instructors assumes a crucial role in moulding student conduct and fostering social growth. This study investigates the influence of parent–teacher communication on student results at a semi-government school located in Fujairah, the United Arab Emirates. A total of ten parents were included in this research study, which utilised a mixed-methods approach that included both questionnaires and interviews. The study analyses the main difficulties and advantages that exist in the communication between parents and teachers in the specific educational environment. The participants shared their experiences, perceptions, and expectations about communication strategies through questionnaires and interviews. The data analysis reveals several aspects that impact the efficiency of communication, such as cultural norms, technology capabilities, and institutional backing. Evidence indicates that although the significance of communication between parents and teachers is acknowledged, many obstacles impede its effective execution. The obstacles encompass language difficulties, restricted technology infrastructure, and cultural disparities in communication preferences. Nevertheless, the participants also emphasised the advantages of robust parent–teacher contact, including enhanced student engagement, behaviour, and overall academic achievement. In addition, the study examines methods to improve parent–teacher communication, including the use of multilingual communication platforms, regular feedback systems, and culturally sensitive approaches. The Interviews provided valuable insights into the intricate factors that contribute to the development of meaningful partnerships between parents and instructors. This research has important implications for educational stakeholders, policymakers, and practitioners who want to improve student outcomes by encouraging effective collaboration between parents and teachers. By tackling the identified issues and capitalising on the chances for enhancement, schools can establish a suitable atmosphere for comprehensive student development. Ultimately, this study adds to the expanding collection of research on parent–teacher communication and its influence on student behaviour and social development. It emphasises the significance of cultivating cooperative partnerships between parents and teachers to bolster the educational progress of pupils in semi-government schools in Fujairah and other areas
The Impact of School Leaders and Teachers in Empowering Students Towards NWEA MAP Assessment Attainment: A Study in a Private School in Dubai
No full textThis study examines the impact of school leadership practices on student performance in NWEA MAP assessments at an American curriculum school in Dubai. It aims at identifying effective strategies that enhance student achievement in standardized external testing by leveraging different leadership styles and teacher empowerment. The main research question is: How do school leaders and teachers empower students to enhance their NWEA MAP performance? The study investigates Transformational and Instructional leadership theories along with Self-Determination Theory to assess their influence on educational outcomes. A mixed-methods approach was employed, collecting qualitative data through semi-structured interviews and quantitative data via surveys to gain comprehensive and holistic insights into the phenomena. Ten school leadership participants took part in the qualitative interviews, and fifty-seven teachers participated in the quantitative surveys. The findings indicate that transformational leadership fosters high student expectations and participation, while distributed leadership promotes shared decision-making among teachers, significantly influencing and boosting MAP results. Additionally, increased access to technology platforms also played a significant role and improved performance. Nevertheless, the study's limitation to one school indicates that further research across diverse educational settings is necessary for generalizability. In conclusion, effective leadership, in addition to teacher and student empowerment, is vital for enhancing student performance on MAP assessments
Deep Learning Speech-Text Chatbot for High School Advising
No full textHigh 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
Learning Organisation and Readiness for Change in Higher Education Institutions: The Intervening Role of Organizational and Individual Resilience
No full textHigher education institutions today face an increasingly complex and rapidly changing environment. To adapt and respond effectively, they must develop themselves as learning organizations that foster readiness for change. Developing resilience is critical at both levels the individual and organizational to this process, as it empowers higher education institutions to navigate through challenges effectively. However, research on the interrelationships between these constructs in higher education institutions is limited. Understanding these potential links is crucial for higher education institutions seeking to enhance their change readiness capabilities. Against this background, this thesis examines the mediating role of individual and organizational resilience on the relationship between learning organization and readiness for change in higher education institutions in the United Arab Emirates (UAE). A learning organization is an organization that encourages and facilitates continuous learning and development among its members to adapt and thrive in a rapidly changing environment. Its conceptual framework, rooted in the literature review, employs a model elucidating the interplay between a learning organization and organizational readiness, mediated by individual and organizational resilience. It relies on learning organization theory, readiness for change theory, and resilience theory to elucidate this process. The model is tested with a sample of 404 respondents collected from four higher education institutions in the UAE. Here, a quantitative approach using partial least squares structural equation modeling (WarpPLS-8.0 version) is employed. The results indicate that individual and organizational resilience mediate the positive relationship between learning organization and readiness for change. Specifically, learning organization has a strong positive effect on individual and organizational resilience, and both types of resilience positively affect readiness for change. However, the data indicates that, compared to organizational resilience, individual resilience has a stronger mediating impact on individual readiness for change. On the other hand, the results indicate that organizational resilience has a stronger mediating impact on organizational readiness for change. Moreover, the findings confirm that resilience at the individual and organizational levels is crucial for translating learning organization practices into improved readiness for change within higher education institutions. As learning organizations, UAE universities can enhance change readiness by deliberately building resilience capacities in their workforces. The thesis contributes to the literature by investigating the three key concepts and applying the model specifically in UAE higher education institutions. The findings have practical implications for UAE universities seeking to enhance their adaptability and responsiveness to change. As learning organizations, they can build resilience capacities among faculty and staff to strengthen organizational change readiness. Fostering individual resilience is critical, as this study shows it plays a more significant role in mediating the link between learning organization practices and readiness for change
Adaptive and Ambidextrous Differentiation: The Role of Digital Transformation and Strategic Orientations on UAE Enterprises Sustainability
No full textPrevious 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 Theor
Leveraging Deep Learning and Word Embeddings to Detect Dish Names in Consumer Reviews
No full textNamed Entity Recognition (NER) is crucial for extracting entities from unstructured text, offering significant insights for businesses through customer review analysis. This study fills a gap in recognizing dish names from customer reviews, as existing literature mainly addresses food entity recognition in recipe datasets and lacks annotated datasets for this specific NER task. Domain adaptation and deep learning approaches like BiGRUs and CNNs remain underexplored. The research proposes a deep learning NER framework to accurately identify dish names in customer reviews with efficient computational resource use. In addition to the existing dataset, MenuNER dataset, an annotated dataset, ReviewsDB, was created from Yelp reviews for evaluation. Initial experiments revealed a notable performance drop in domain adaptation from food names in recipe datasets to dish names in reviews, with the F1-score nearly 50% lower. A comparative analysis of 53 deep learning models using various word embeddings, including Glove, Word2Vec, and Bert variants, showed that a simple architecture with a single-layer Bidirectional Gated Recurrent Unit (BiGRU) and Conditional Random Field (CRF) layer achieved the best performance, with an F1-score of 93.07% using glove-twitter-100 embeddings in the MenuNER dataset. Additionally, a two-layer BiGRU with a CNN and CRF achieved an F1-score of 82.40% on the ReviewsDB dataset. The study attributes performance differences to variability in annotation lengths and the broader range of terms in ReviewsDB. In conclusion, the proposed NER framework, leveraging pre-trained embeddings, provides a valuable tool for the food industry to analyze customer feedback and enhance customer satisfaction