Institutional-Repository, University of Moratuwa
Welcome to the University of Moratuwa Digital Repository, which houses postgraduate theses and dissertations, research articles presented at conferences by faculties and departments, university-published journal articles and research publications authored by academic staff. This online repository stores, preserves and distributes the University's scholarly work. This service allows University members to share their research with a larger audience.
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Recent Submissions
item: Thesis-Full-text
Factors affecting the adoption of AI-driven automation within DevOps practices among IT professionals in Sri Lanka
(2025) Wijedasa, TH; Karunarathne, B
This research explores the factors influencing the adoption of AI-driven automation within DevOps practices among IT professionals in Sri Lanka. Drawing on a conceptual framework that integrates technical, strategic, and organizational dimensions, the study examines how four key constructs—technical Enablers (access to AI tools and efficiency gains), Future Focus (strategic orientation toward AI expansion), Barriers (cost, skills, integration complexity), and Organizational Readiness (culture and change-management support)—relate to the degree of AI adoption in CI/CD pipelines, automated testing, and real-time monitoring. A quantitative survey was administered online to a stratified sample of 384 respondents across job roles (developers, DevOps engineers, QA Engineers, project managers) and organization sizes. Items were measured on five-point Likert scales and organized into five sections: Demographics, Enablers, Future Focus, Barriers, and Organizational Readiness, plus a direct measure of Adoption Level. Data were analyzed using IBM SPSS: reliability testing (Cronbach’s alpha) confirmed internal consistency; exploratory factor analysis validated the measurement structure; Pearson correlation assessed bivariate relationships; and Hayes’ PROCESS macro tested mediation (Future Focus) and moderation (Organizational Readiness) hypotheses. By combining robust statistical methods with a multi-dimensional conceptual model, this study provides insights into the mechanisms through which AI capabilities, strategic planning, and organizational context drive or inhibit the integration of AI into DevOps workflows in emerging-economy settings.
item: Thesis-Full-text
Evaluate the impact of challenges of distributed software development teams in Sri Lankan context
(2025) Udugama, UKDHT; Hettiarachchi , C
The growth of the software industry worldwide has created a phenomenal increase in distributed software development (DSD) teams, as they provide flexibility, cost benefits, and proximity to diversified talent pools. The change to distributed models is accompanied by a unique set of issues that negatively affect team performance and project success. In this study, we try to analyze critically the effects of such issues in the backdrop of Sri Lankan software development organizations. The research mainly identifies and investigates major problems encountered by distributed teams, such as communication gap, time zone difference, cross-cultural diversity, and extensive use of virtual collaboration tools. Special focus is on the impact of these problems on the vital project parameters like software quality, on-time delivery, and cost-effectiveness. The study explores the connection of these issues with team performance in a set of hypotheses. It also looks at to what extent the use of agile project management methodologies and the application of contemporary collaboration software can alleviate these adverse effects and enhance productivity. Data is gathered from a cross-section sample of Sri Lankan software companies working in distributed setups. The analysis gives insight into prevailing strategies, tools, and frameworks employed to combat operational inefficacies and achieve successful collaboration. Results reflect both the failures and successes of current practices in optimizing trust, transparency, and coordination in remote environments. According to the findings, the thesis provides practical recommendations specific to the Sri Lankan context. They are the embracing of hybrid collaboration models, developing cross-cultural competency, investing in synchronous and asynchronous communications solutions, and imparting agile practices amenable to distributed teams. The study adds to the body of literature on remote software engineering and provides hands-on guidance for organizations to streamline distributed software development performance amidst special challenges faced in Sri Lanka.
item: Thesis-Abstract
Evaluating the role of AI in predictive incident management in IT organizations in Sri Lanka
(2025) Thomas, AP; Ambegoda, TD
The recent development of Artificial Intelligence (AI) has transformed Information Technology (IT) operations, particularly predictive incident management. This study explores the implementation of AI in predictive incident management systems in IT organizations in Sri Lanka. The traditional incident management systems are reactive by nature, fixing issues after they have happened, causing downtime and operational inefficiency. On the other hand, predictive incident management systems powered by AI utilize machine learning, data analytics, and anomaly detection to predict potential IT incidents in advance so that preemptive action can be taken. The research looks into the impact of AI adoption on machine learning, user satisfaction, and organizational trust in AI systems. The research adopts quantitative research design, gathering data from 340 IT professionals through a structured survey. Key determinants examined include AI awareness, data quality, system integration, training, and transparency of AI decision-making. The findings suggest that AI awareness and system integration are significant drivers of predictive incident management performance improvement, while organizational culture, data privacy, and transparency of AI decision-making are critical to trust development. Additionally, data quality issues, integration with current legacy systems, and resistance to AI adoption are emphasized. The study highlights the imperative need to surmount these hindrances for successful implementation of AI in predictive incident management. The research contributes to the current knowledge of AI application in emerging economies and provides actionable suggestions to Sri Lankan IT organizations that aim to improve their incident management systems.
item: Thesis-Full-text
The Impact of digitalization on fraud prevention and detection in the Sri Lankan banking industry
(2025) Suja, M; Rathnayake, RMS
The banking industry in Sri Lanka has been rapidly digitalized and this has completely revolutionized the way through which financial services are delivered and at the same time introduced new unprecedented fraud risks, which have not been equally met by the older strategies of preventing them. The study researches the effects of digitalization on the effectiveness of fraud prevention and detection in Sri Lankan commercial banks via identification of vulnerabilities and formulation of strategic recommendations regarding improved security capabilities. With quantitative research methodology, the study gathered data of 518 customers with digital banks and 300 working with the banking sector in major commercial banks using structured surveys. This study employed the Technology-Organization-Environment (TOE) model to review the complex relationships between digital transformation programs and fraud prevention efficiency through lenses of technology capacity, organization preparedness, and an environment. The important findings explain that there is an urgent gap between the rate of digital banking adoption and the ability to protect it, and it means that even traditional rule-based fraud detection systems are only 45 percent effective against modern threats and have a false positive rate of 15 percent. The study also sees considerable room to be improved with improved technologies, as the artificial intelligence and machine learning systems performed 85 percent better in terms of detection as well as biometric authentication can prevent account takeover fraud by 99.9 percent. The research has concluded that the organizational elements, such as staff training and customer education, are rather important factors of successful fraud prevention, and well- trained institutions achieve better results than institutions found only on technological afterthoughts by 50 percent better. When done with privacy protection and an optimal user experience, 94 percent of customers accept increased security precaution. Research recommendations suggest the following: multi-factor authentication and AI-enabled detection systems should be implemented right away, medium-step installation of end-to-end biometric-based authentication and predictive analytics systems, and long-term implementation of the capability to share information across banks in a cross-bank environment. The presented three-phased implementation framework will systematically guide the process of improving fraud prevention by ensuring the efficiency of operations and customer satisfaction. This study will add practical evidence-based solutions that can be adopted in Sri Lankan banks in order to face the fraud prevention issue and keep on with the digital development and achieve the competitive edge in the new financial services scene
item: Thesis-Full-text
Strategic decision making in post-merge and acquisition in the software industry : the role of AI-powered business intelligence
(2025) Malkanthi, VS; Karunarathne, B
This study investigates the complex challenges faced by leadership during post-merger and acquisition (M&A) integration within the software industry and explores how AIpowered Business Intelligence (BI) tools can support strategic decision-making, operational efficiency, quality maintenance, and process improvements. Additionally, it examines the ethical implications of using such tools in organizational decision-making. Using quantitative research design, multiple linear regression and independent samples t-tests were applied to assess the impact of three main independent variable groups which are M&A integration factors, AI-powered BI tool capabilities, and ethical considerations on key organizational performance outcomes. The findings reveal that cultural challenges are the most significant barriers to successful integration, consistently affecting decision-making effectiveness, quality consistency, and operational efficiency. Conversely, BI capabilities such as data consolidation, real-time insights, and communication support were found to significantly enhance organizational performance post-M&A. Ethical factors, particularly data transparency and clear governance, also contributed meaningfully to effective strategic decision-making and quality outcomes. The research concludes that while M&A integration challenges can undermine organizational success, their impact can be mitigated through targeted use of AI-powered BI tools and adherence to ethical practices. The study offers actionable recommendations for integrating BI systems and ethical governance into M&A strategies, contributing both to academic understanding and real-world application in the context of digital transformation.