An agile enterprise architecture driven approach to enhance communication in geographically distributed agile development

University of Technology Sydney. Faculty of Engineering and Information Technology.Agile development is a highly collaborative environment, which requires active communication among stakeholders. This active communication helps in producing high quality working software systems in short releases and iterations. Due to the ever-increasing competition, there is an increasing interest among practitioners and researchers in contemporary geographically distributed agile development (GDAD). GDAD claims to offer several benefits over co-located agile development such as lower production cost, around the clock development, faster time to market, and the liberty of involving the most talented developers across the globe. However, in the GDAD environment, active communication is difficult to achieve due to many challenges such as differences in geographical locations and time. Literature has reported that agile enterprise architecture (EA) could help enhancing GDAD communication and performance. However, little empirical evidence is known to support this claim. Furthermore, it is not clear how to effectively achieve and study active communication construct in GDAD in terms of its dimensions, determinants and effects on performance? As a result, there is a lack of understanding about how GDAD organisations can establish and maintain active communication among distributed teams. This dissertation contributes to this research gap, first, by developing a research model based on an extensive systematic literature review on the GDAD communication challenges, techniques and strategies to mitigate these challenges, and the impact of communication on GDAD software performance. This study provides important insights about GDAD communication by identifying and empirically examining the relationships among the two dimensions of active communication (communication efficiency and communication effectiveness), one antecedent that can be controlled (agile enterprise architecture (EA)), and four aspects of GDAD performance (on-time completion, on-budget completion, software functionality, and software quality). The study then validates the research model using an integrated research approach that combines quantitative and qualitative data analyses. The quantitative data are collected using a survey technique from 160 responses and analysed using Partial Least Squares (PLS) analyses. The qualitative data are collected using interview techniques through 10 post hoc case studies and analysed using content analysis technique. This study reports that agile EA has positive impacts on communication efficiency and communication effectiveness, and on GDAD performance. It has also been found that communication efficiency and communication effectiveness have significant differential impacts on GDAD performance aspects. While communication efficiency is, generally, related to on-time and on-budget completions, communication effectiveness is, generally, related to functionality and quality aspects. While the prior GDAD literature offers little guidance for GDAD communication issue, this research contributes to both theory and practice, and offers a number of useful insights and agile EA driven GDAD model. From theory perspective, insights and model are theoretically based on and empirically tested about the value and positive impact of agile EA on active communication dimensions and GDAD performance, and the impact of communication efficiency and communication effectiveness on GDAD performance in the GDAD environment. Moreover, from practice perspective, this study indicates that agile EA, communication efficiency, and communication effectiveness together increase the GDAD performance and thus, facilitate a better GDAD performance than in GDAD that does not employ agile EA. Despite the above-mentioned contributions, like any other studies, this study has also some limitations such as sample size, time and potential analysis bias of applied qualitative and quantitative research methods. A number of steps were taken to mitigate or minimise the effects of these limitations. Thus, findings of this work should be considered with its limitations when interpreting it in the relevant theoretical and practical context

Fog computing security and privacy issues, open challenges, and blockchain solution: An overview

Due to the expansion growth of the IoT devices, Fog computing was proposed to enhance the low latency IoT applications and meet the distribution nature of these devices. However, Fog computing was criticized for several privacy and security vulnerabilities. This paper aims to identify and discuss the security challenges for Fog computing. It also discusses blockchain technology as a complementary mechanism associated with Fog computing to mitigate the impact of these issues. The findings of this paper reveal that blockchain can meet the privacy and security requirements of fog computing; however, there are several limitations of blockchain that should be further investigated in the context of Fog computing

Investigating internet of things impact on e-Learning system: An overview

e-Learning systems have reached their peak with the revolution of smart technologies. In the past few years, the Internet of Things (IoT) has become one of the most advanced and popular technologies, affecting many different areas. Using IoT in an e-learning system is a fantastic technology that improves the e-learning system and makes it more inventive and cutting-edge. The key challenge addressed in this study is the acceptance of IoT usage in e-learning systems as well as how to improve it so that it can be utilized properly. This research concentrates on how IoT can benefit e-learning systems and how it might benefit users of e-learning systems. A comprehensive literature review was conducted to get acquainted with the important research related to IoT technology and e-learning systems through online research databases and reliable scientific journals. The first research finding is that e-learning systems need such modern techniques as IoT to enable interconnection, increase reliability, and enhance the enjoyment of the educational process. The second result is that research related to the development of new technologies like the IoT has a significant impact on enhancing the performance of new systems and bringing about positive change. This study highlights the value of IoT, particularly in e-learning systems. It aids in the development of new strategies that will improve the efficacy of e-learning systems and stimulate researchers to develop advanced technology

Analysis of the role of servant leadership on employee’s job satisfaction mediated by leader-member exchange style among employees in the private higher education sector in Kuwait

A growing body of literature explores the underlying mechanisms and processes that enable servant leadership to impact organizational performance, engagement, and outcomes positively. This research assesses the mediation role of leader-member exchange between servant leadership and job satisfaction among employees in Kuwait's universities. The study utilized a closed-ended survey that was distributed to 240 workers, with 205 valid responses received from employees working in two private higher education sectors in Kuwait. using Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used for data analysis. The outcomes of the study demonstrated strong backing for the beneficial influence of servant leadership on leader-member exchange and job satisfaction. Furthermore, a positive correlation was established between leader-member exchange and job satisfaction among employees employed in Kuwait's private higher education sector. Moreover, the results partially validated the mediating effect of leader-member exchange in the relationship between servant leadership and employee job satisfaction. These results underscore the significance of integrating servant leadership principles into leadership approaches within this sector to improve employee satisfaction and overall organizational achievement

Machine Learning-Based Text Classification Comparison: Turkish Language Context

The growth in textual data associated with the increased usage of online services and the simplicity of having access to these data has resulted in a rise in the number of text classification research papers. Text classification has a significant influence on several domains such as news categorization, the detection of spam content, and sentiment analysis. The classification of Turkish text is the focus of this work since only a few studies have been conducted in this context. We utilize data obtained from customers’ inquiries that come to an institution to evaluate the proposed techniques. Classes are assigned to such inquiries specified in the institution’s internal procedures. The Support Vector Machine, Naïve Bayes, Long Term-Short Memory, Random Forest, and Logistic Regression algorithms were used to classify the data. The performance of the various techniques was then analyzed after and before data preparation, and the results were compared. The Long Term-Short Memory technique demonstrated superior effectiveness in terms of accuracy, achieving an 84% accuracy rate, surpassing the best accuracy record of traditional techniques, which was 78% accuracy for the Support Vector Machine technique. The techniques performed better once the number of categories in the dataset was reduced. Moreover, the findings show that data preparation and coherence between the classes’ number and the number of training sets are significant variables influencing the techniques’ performance. The findings of this study and the text classification technique utilized may be applied to data in dialects other than Turkish

Internet of Things and Blockchain Integration: Security, Privacy, Technical, and Design Challenges

The Internet of things model enables a world in which all of our everyday devices can be integrated and communicate with each other and their surroundings to gather and share data and simplify task implementation. Such an Internet of things environment would require seamless authentication, data protection, stability, attack resistance, ease of deployment, and self-maintenance, among other things. Blockchain, a technology that was born with the cryptocurrency Bitcoin, may fulfill Internet of things requirements. However, due to the characteristics of both Internet of things devices and Blockchain technology, integrating Blockchain and the Internet of things can cause several challenges. Despite a large number of papers that have been published in the field of Blockchain and the Internet of things, the problems of this combination remain unclear and scattered. Accordingly, this paper aims to provide a comprehensive survey of the challenges related to Blockchain–Internet of things integration by evaluating the related peer-reviewed literature. The paper also discusses some of the recommendations for reducing the effects of these challenges. Moreover, the paper discusses some of the unsolved concerns that must be addressed before the next generation of integrated Blockchain–Internet of things applications can be deployed. Lastly, future trends in the context of Blockchain–Internet of things integration are discussed

Cybersecurity Enterprises Policies: A Comparative Study

Cybersecurity is a critical issue that must be prioritized not just by enterprises of all kinds, but also by national security. To safeguard an organization’s cyberenvironments, information, and communication technologies, many enterprises are investing substantially in cybersecurity these days. One part of the cyberdefense mechanism is building an enterprises’ security policies library, for consistent implementation of security controls. Significant and common cybersecurity policies of various enterprises are compared and explored in this study to provide robust and comprehensive cybersecurity knowledge that can be used in various enterprises. Several significant common security policies were identified and discussed in this comprehensive study. This study identified 10 common cybersecurity policy aspects in five enterprises: healthcare, finance, education, aviation, and e-commerce. We aimed to build a strong infrastructure in each business, and investigate the security laws and policies that apply to all businesses in each sector. Furthermore, the findings of this study reveal that the importance of cybersecurity requirements differ across multiple organizations. The choice and applicability of cybersecurity policies are determined by the type of information under control and the security requirements of organizations in relation to these policies

The impact of diversity on job performance: evidence from private universities in Egypt

Employees from diverse backgrounds have been claimed to perform better; nevertheless, this link has been studied sparingly in the Egyptian setting. This paper addresses this gap by experimentally analyzing the link between employee performance and gender, educational background, and ethnic background. To investigate this link, a usable model was created, and data was collected from 269 academic staff members at private Egyptian institutions. PLS analysis was used, and the result revealed that educational and ethnic backgrounds have a positive effect on employees’ job performance whereas, the impact of gender background on employee’s job performance was found to be insignificant. Furthermore, the research findings disclose that the education and ethnic background of the employees mediates the relationship between employees’ job performance and gender diversity. Future research is yet to validate these results

A Probabilistic Data Fusion Modeling Approach for Extracting True Values from Uncertain and Conflicting Attributes

Real-world data obtained from integrating heterogeneous data sources are often multi-valued, uncertain, imprecise, error-prone, outdated, and have different degrees of accuracy and correctness. It is critical to resolve data uncertainty and conflicts to present quality data that reflect actual world values. This task is called data fusion. In this paper, we deal with the problem of data fusion based on probabilistic entity linkage and uncertainty management in conflict data. Data fusion has been widely explored in the research community. However, concerns such as explicit uncertainty management and on-demand data fusion, which can cope with dynamic data sources, have not been studied well. This paper proposes a new probabilistic data fusion modeling approach that attempts to find true data values under conditions of uncertain or conflicted multi-valued attributes. These attributes are generated from the probabilistic linkage and merging alternatives of multi-corresponding entities. Consequently, the paper identifies and formulates several data fusion cases and sample spaces that require further conditional computation using our computational fusion method. The identification is established to fit with a real-world data fusion problem. In the real world, there is always the possibility of heterogeneous data sources, the integration of probabilistic entities, single or multiple truth values for certain attributes, and different combinations of attribute values as alternatives for each generated entity. We validate our probabilistic data fusion approach through mathematical representation based on three data sources with different reliability scores. The validity of the approach was assessed via implementation into our probabilistic integration system to show how it can manage and resolve different cases of data conflicts and inconsistencies. The outcome showed improved accuracy in identifying true values due to the association of constructive evidence