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Relationship between organisational culture and collective coping strategies in project teams: an exploratory quantitative study in the UAE construction industry
No full textconstruction project teams in the United Arab Emirates (UAE). Three collective coping strategies were
examined, including problem-focused, relationship-focused and emotion-focused coping strategies.
Design/methodology/approach– O’Reilly et al.’s (1991) organisational culture profile (OCP) assessed
organisational culture values. Data were collected through an online questionnaire from practitioners in the
United Arab Emirates (UAE) construction organisations.
Findings– The findings show a high correlation between competitiveness culture values and problem
focused teamcopingstrategy. Relationship-focused team coping strategy was found to have ahigh correlation
with emphasis on rewards and performance orientation values. Conversely, an emotion-focused team coping
strategy correlates highly with competitiveness, supportiveness and emphasis on rewards cultural values.
Research limitations/implications– The cross-sectional design of the survey and the UAE context may
present limits to the generalisability of findings.
Practicalimplications–Limitedattemptshavebeenmadetostudycollectivecopinginconstructionproject
teams. The study paves the path for exploring emergent socio-psychological concepts in construction
organisations, including the impact of organisational culture on team collective coping with adverse events.
Originality/value– Understanding the pivotal impact of culture on successful team coping provides
managers with valuable insights into managing situational adversity in construction project teams
A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques
No full textEvery year, phishing results in losses of billions of dollars and is a major threat to the Internet
economy. Phishing attacks are now most often carried out by email. To better comprehend the existing
research trend of phishing email detection, several review studies have been performed. However, it is
important to assess this issue from different perspectives. None of the surveys have ever comprehensively
studied the use of Natural Language Processing (NLP) techniques for detection of phishing except one that
shed light on the use of NLP techniques for classification and training purposes, while exploring a few
alternatives. To bridge the gap, this study aims to systematically review and synthesise research on the use
of NLP for detecting phishing emails. Based on specific predefined criteria, a total of 100 research articles
published between 2006 and 2022 were identified and analysed. We study the key research areas in phishing
email detection using NLP, machine learning algorithms used in phishing detection email, text features in
phishing emails, datasets and resources that have been used in phishing emails, and the evaluation criteria.
The findings include that the main research area in phishing detection studies is feature extraction and
selection, followed by methods for classifying and optimizing the detection of phishing emails. Amongst
the range of classification algorithms, support vector machines (SVMs) are heavily utilised for detecting
phishing emails. The most frequently used NLP techniques are found to be TF-IDF and word embeddings.
Furthermore, the most commonly used datasets for benchmarking phishing email detection methods is the
Nazario phishing corpus. Also, Python is the most commonly used one for phishing email detection. It is
expected that the findings of this paper can be helpful for the scientific community, especially in the field
of NLP application in cybersecurity problems. This survey also is unique in the sense that it relates works
to their openly available tools and resources. The analysis of the presented works revealed that not much
work had been performed on Arabic language phishing emails using NLP techniques. Therefore, many open
issues are associated with Arabic phishing email detection
Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning
No full textThis work is to apply sentiment analysis SA for Arabic movie reviews on social media. Automatically detecting attitude or sentiment in a text is often helpful. By classifying the data into positive, negative, or neutral emotions, SA aids in our understanding of the precise emotions that underlie the more broad feelings that are typically associated with behavior. By utilizing the power of multiple word representations and deep learning approaches, this work seeks to enhance categorization performance. Through the use of mobile apps, the internet, and social media portals, there has been a tremendous increase of data in recent years. People are now able to share their opinions about specific topics because to the rapid development of technologies and social media platforms. People all around the world use a number of these social media sites frequently to share their evaluations and opinions of movies. By evaluating prior evaluations, it has become simpler for individuals to identify movies that live up to their expectations thanks to technologies like machine learning (ML) and deep learning (DL). Massive data can be collected every day from social media network such as YouTube, twitter, Instagram, and many other platforms. The tools used for collecting data are Vicinitas for Twitter and IGCommentExport for Instagram. The testing datasets were collected from mainly from Instagram for two Arabic movies reviews. The two movies are Wahed Tani which translates to (someone else) and Amahom which translate to (their uncle), Three datasets were employed, and several categorization models were compared across them. Prior to performing sentiment analysis, it is necessary to prepare the data so that it may be used to train machine learning (ML) algorithms. In order to label the data that was gathered from a corpus collection for ML use, manual annotation was made. For sentiment analysis, pre-processing is a crucial step in the data preparation process. Data pre-processing is a crucial step in NLP activities to enhance dataset performance and guarantee the accuracy of the emotive analysis. We translated some of the most common emojis as per its meaning in Arabic. There are different types of Arabic and the three main are Classical Arabic (CA), Modern standard Arabic (MSA), and Dialect Arabic language (DA). In this paper we are focusing on DA Arabic since it is commonly used on social media The main dataset was the Arabic Sentiment Analysis Dataset (ASAD) which presented a novel large Twitter-based benchmark (Alharbi et al., 2020). The proposed CNN, RNN, CNN-RNN, and BERT models were used in conjunction with the three datasets. With the Bert model and in comparison, to the other examined models, two of these datasets were used. We test the CNN model first, then the LSTM, and finally the CNN-LSTM combo. After comparing these three modes, the best mode was chosen in order to compare it to the BERT model. The results of the hybrid CNN-LSTM model showed an accuracy of 90%. Finally, we compared CNN-LSTM with the BERT model Therefore, the BERT model outperformed all other classifiers in terms of accuracy (91%), recall (71%%), precision (83%), and F-measure (77%)
Sentiment Analysis for opinion leaders on Twitter: A Case Study of COVID-19
No full textThe coronavirus or COVID-19 is an ongoing global problem where a pandemic was implemented early in 2020 during the outbreak. Social media platforms were used during the pandemic to share views and exchange information. This study aims to provide a framework for sentiment analysis of opinion leaders on Twitter. The experiments were conducted by aiming COVID-19 specific tweets from four opinion leaders by applying machine learning models. The dataset collected uses covid hashtags and tweets posted in English. Sentiment analysis are then performed on these tweets for analysis. The tweets are then preprocessed to prepare it for evaluation. This research provides findings from these tweets using sentiment analysis on machine learning models where the logistic regression model provided the best accuracy results followed by the Multi-layer perceptron model, Support vector machine, Convolutional neural network, and Decision tree. As the tweets directly affect people’s thoughts, the purpose of these results was to know about the tweet’s sentiments from diverse public opinion leaders around the world during COVID-19
The transition of students with SEND from rehabilitation centers to mainstream schools in the UAE
Get PDFStudents with disabilities have had the opportunity to attend mainstream schools in recent years as a result of right-based policies and obligations. This has ensured equal access to education by meeting all of their needs and providing support to overcome their inherited barriers. However, due to a variety of complicating factors, some students are still left behind in special classrooms, such as rehabilitation centers (Abdat, 2020). Such centers were initially established to provide care and education to students with disabilities in order to prepare them to be socially and educationally integrated with their non-disabled peers. Many people have an impact on the transition from rehabilitation centers to mainstream schools, including educators, students, and parents. As a result, the purpose of this study was to investigate the factors that influence the transition of students with disabilities from rehabilitation centers to mainstream schools in the UAE. It covered three major topics: teaching practices in a rehabilitation center for transitioning students, challenges teachers face when transmitting to their students, and parents’ perceptions of inclusion and transition. The study was conducted using the qualitative method to provide descriptive data involving the feelings and thoughts of the participants. The data were collected using several approaches. Semi-structured interviews (10 parents), two focus groups (15 teachers), and four non-participant observations were used to collect data (4 teachers). Thematic analysis of parent interviews revealed the following issues: 1) difficulties with school enrollment, 2) a service gap, 3) anticipated threats, 4) the complexity of disabilities, 5) fears about the future. Furthermore, teachers revealed their difficulties in achieving a successful transition, which included 1) a curriculum hiatus, 2) inadequate compensation, 3) group collaboration, 4) the complexity of disabilities. Observations also revealed teaching methods used to prepare students for their transition. Finally, the study provides recommendations on the status of transition from rehabilitation centers to mainstream schools for students with disabilities
An Analysis of Thermal Comfort at the School Outdoor Spaces: A Case Study of the American School of Creative Science, Dubai, UAE
No full textOutdoor school spaces are significant spaces which, regardless of a child’s residential area, provide great opportunity for outdoor space exploration leading to overall enhancement to the students’ wellbeing. This paper analyzes the outdoor school spaces of a school in Dubai to optimize its outdoor school spaces and ensure their thermal comfort. To achieve this aim, and using mixed methodology approach of survey, field observation, workshops and ENVI-Met V5.3 software simulation, the initial school outdoor spaces were analyzed and then enhanced by means of several proposed heat mitigation strategies. The enhanced outcome was evaluated against the initial one, using PET (physiological equivalent temperature), revealing that shade separately had the highest impact on its corresponding location with a decrease of up to 16% in PET, but no decrease to the overall PET of the microclimate. Additionally, the addition of vegetation alone had an impact on the microclimate decreasing it by 5%. Thus, combining the strategies of vegetation, shade, green facades/roofs and small water features resulted in 5% to 25% reduction in PET depending on the corresponding location being analyzed. The enhancements also led to reduction in the building energy flux, by up to 5%. The results obtained provide insight and guidelines for school designers and school board members on how to evaluate and enhance the school outdoor spaces to ensure they are thermally comfortable
مكافأة الموظف كوسيط في العلاقة بين أسلوب القيادة التحويلية وتحفيز الموظفين في مؤسسات الإنشاء في دولة الإمارات العربية المتحدة
No full textThis study aims to investigate the moderating effects of extrinsic and intrinsic employee rewards on the relationship between transformational leadership style and employee motivation in construction organisations in the UAE. The data were collected through a questionnaire distributed among the employees of different construction organisations in UAE to investigate their opinions. The data collected from 144 employees were analysed using a combination of inferential and descriptive statistics. All of the statistical analyses were performed using IBM's SPSS 28 statistical package. The study findings revealed a significant positive relationship between intrinsic and extrinsic employee rewards and employee motivation for construction sector workers in UAE. Also, the study’s results suggest that there is not enough evidence supporting the notion that the presence or absence of intrinsic and extrinsic rewards affect the impact of transformational leadership style on employee motivation for construction employees in UAE. The study's findings were compared with those of previous research. The study's limitations and the theoretical and practical implications of the findings were acknowledged. Moreover, the study's findings are expected to help develop a comprehensive understanding of the relationship between employee rewards, transformational leadership style and the motivation of construction employees in UAE
The Analysis of Project Governance and Cultural Intelligence in the Successful Delivery of Complex Construction Projects: The Case of the UAE Construction Sector
No full textThe overarching aim of this research was to examine how project governance and cultural intelligence can influence successful complex construction project delivery. The research proposed a model that comprises project governance and cultural intelligence determinants that can be used to enhance successful complex construction project delivery in the UAE. The key variables of project governance, cultural intelligence and successful complex construction project delivery are significantly explicated in the literature review with the accompanying factors and references for each. To obtain the needed results, the study entailed the use of a quantitative research method. For this study, it was crucial to ensure that only the relevant respondents took part in each stage of the research.
A total sample of 404 respondents was used in the study. This number of respondents was considered sufficient in the context of this study and the realisation of the set goals aimed at understanding the complex building construction industry. The study adopted non-probability sampling and snowball sampling strategies. Data analysis comprised descriptive statistics, reliability test, correlation test and regression test. Validity and reliability were attained through the assessment of their plausibility in relation to the existing knowledge on the relationship between the aspects of project governance and cultural intelligence and their effects on successful complex construction project delivery. The verification occurred when the model had been formulated. Workshops and group discussions helped achieve this goal. The research rigour was attained by focusing on verification and validation, which include aspects of methodological coherence and data analysis. As specified below, the novelty of the research can be viewed from two perspectives:
There is a paucity of research studies that examine how project governance and cultural intelligence could influence successful complex construction project delivery, yet the topic is of significance in the construction sector. The research findings of the study are intended to add to the existing body of knowledge in the single area that explicates the relationship between complex area of cultural intelligence, project governance, and complex building construction projects.
The proposed model is intended to provide senior construction project practitioners in the UAE with approaches for managing the rising numbers of multicultural teams based on the aspects of project governance and cultural intelligence.
Keywords:
Project governance, Cultural intelligence, Complex building projects, Construction sector, United Arab Emirates, Project management
The Influence of Cognitive Bias Attributes on Decision-making Style of the Project Manager: The Moderating Role of Narcissistic and Voice Behaviour
No full textThis thesis investigates the influence of cognitive bias attributes (CBA) on the decision-making (DM) style of project managers (PJM): the moderating role of narcissistic behaviour (NB) and voice behaviour (VB) in Information Technology Software Development (ITSD) projects in Dubai. The research classified sources of bias under two families: (1) perception and behavioural bias, (2) belief and probability estimation bias; these families consist of six groups that contain 21 sources of bias.
The research followed a positivism philosophy using a deductive approach based on a quantitative analysis methodology and a survey instrument strategy to collect data; 381 responses were collected through an electronic survey. The study used confirmatory factor analysis to validate the constructive validity of the variables, Cronbach’s alpha to test the reliability of the variables, a pilot study conducted prior to survey distribution and multiple regression analysis through IBM SPSS statistics version 20 to test research hypotheses.
The results indicated that: 1) CBA influences the decision-making style of project managers, 2) the relationship between CBA and the experiential decision-making style of the project manager is significant, whereas the rational decision-making style of the project managers is less affected by CBA, 3) using the experiential style to make a decision under uncertain events has a relatively negative influence on the success of projects as it is connected to CBA, 4) using the rational style to make a decision under uncertain events has a relatively positive influence on the success of the projects as it is less connected to CBA, 5) voice behaviour negatively moderates the relationship between cognitive bias and the decision-making style of project managers; however, the relationship was weak, and 6) NB does not moderate the relationship between CBA and the DM style.
The researcher developed a de-biasing DM model which can be used to mitigate the influence of the biased decisions. The study enriched the body of knowledge of the CBA through extensively exploring various sources of bias and their impact on the DM process; and expands on the knowledge of the DM styles provided by CEST by exploring the negative influence posed by CBA. The study imparts elaborate information about the role of project managers’ NB and VB in the context of PM and provides a model that will help mitigate the risk of CBA on the decision-making process. The thesis recommends testing the group and social bias family, effect, and memory bias family in future research