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.
 Research Publications |  Thesis & Dissertation |  E- Books |
 UoM Journal Publications |  UoM Conference Proceedings |  Articles published in Scimago's Q1 journals |  UoM Research Reports |  Other Articles authored by UoM staff |
Recent Submissions
item: Thesis-Full-text
Factors affecting high employee turnover in IT industry of Sri Lanka
(2024) Senarathne, SMACTN; Rathnayake, S
Among most promising sectors in Sri Lanka, the information technology sector has grown significantly since the country's post-war era. This sector is vital to Sri Lanka since it is currently one of the main ways the nation earns foreign exchange revenue. Despite its significance, the industry was seeing an increase in staff turnover, which may be extremely dangerous if it keeps up. This research was carried out based on four factors named work life balance, rewards, opportunities for career progression and the leadership style to determine the association between each element and employee turnover as well as which ones are most influencing the high turnover. The study's findings demonstrated that, among the four variables linked to employee turnover, reward has been the most important.
item: Thesis-Full-text
Technological advancements on selected accounting practices : a study on big data analytics, automation, and artificial intelligence in Sri Lanka
(2024) Madushanka, TKD; Wijayasiri , A
Technology has been shaping the world day by day with modern inventions. Individuals, organizations, and industries have changed according to developments. Big data analytics, automation, and artificial intelligence (AI) are in the process of changing accounting practices continuously and embracing the profession widely. Though there are higher interventions, the impact of these technologies on efficiency, accuracy, and productivity of accounting practices remains unclear. By identifying the level of impact, organizations can actively use these technological advancements in operations. Further, it helps to formulate strategies and maintains its competitive edge. Objectives are to identify the current integration of technological advancements in accounting practices, investigate the efficiency, accuracy, and productivity of these technologies, identify the challenges and barriers that arise when integrating these technologies, to come up with strategies to overcome challenges, and increase integration of technological advancements. Primarily integration of big data analytics tools and AI seems low with accounting practices. Main issues with lower integration are lack of skilled personnel and cost and resource constraints. Big data analytics tools are mainly used for data visualizations and AI use of predictive analytics for financial decisions. However, automation is widely used by accounting professionals. To investigate the efficiency, accuracy, and productivity of technological advancements, hypothesis was developed and tested. Outcomes show, integration of big data analytics tools significantly increases the efficiency of financial reporting, integration of automation significantly increases the accuracy of financial data and information, and integrated AI software significantly increases productivity of professionals. Therefore, organizations need to prepare their future and strategies to get the most from these advancements. Main challenges and barriers to integration of technological advancements are lack of technical skills and expertise, change management and user resistance, and data quality and standardization issues. To overcome those challenges. there must be training and developments, collaborations with industry professionals, partnering with technology vendors, and standardizing data and systems This study highlights the need for enhanced integration of Big Data Analytics, Automation, and AI in selected accounting practices. Addressing challenges like skill shortages, change management, user resistance, and data standardization can significantly boost integration. Organizations must invest in training and strategic partnerships to fully capitalize on these technological advancements.
item: Thesis-Abstract
Customer empowerment factors influencing the acceptance of artificial intelligence (AI) and machine learning (ML) in credit risk assessment in Sri Lankan banks and financial institutions
(2025) Anandapreman, GDB; Perera, I
This research is performed to investigate the critical customer empowerment factors that significantly influence the acceptance of Artificial Intelligence (AI), and Machine Learning (ML) based credit risk assessments in the banks and financial institutions in Sri Lanka who are engaged in the lending business. Banks and financial institutions are rapidly leveraging cutting-edge technologies like AI and ML in their banking operations to render various services to their customers in their respective market context. Therefore, it is vital to understand the customer perceptions and their sense of control in this context for successful implementation of AI and ML based tools in banks and financial institution of Sri Lanka.
The researcher aimed to study and investigated key customer empowerment factors such as customer awareness, customer trust and customer privacy concerns and how far they impact in the implementation of AI and ML integrated credit risk assessment tools in the lending landscape of Sri Lanka.
The research has been carried out with quantitative methods through a well- constructed questionnaire survey from the banking customers and financial institution representatives. Their responses were validated and analyzed through statistical tools to identify the relationships between the customer empowerment factors and Acceptance of AI and ML based credit risk assessment.
The final results and the respective outcomes from this research are aimed at being recommended as a part of the research objectives to the regulatory body, CBSL, Banks and Financial institutions that aim to deploy the AI and ML integrated credit risk assessment tools in their lending business.
This study determined whether the customer acceptance of this AI and ML integrated credit risk assessment tools is controlled by customer awareness, customer trust and customer privacy concerns.
item: Thesis-Full-text
Factors affecting Sri Lankan customers’ online purchase intentions during a crisis
(2025) Swarnasinghe, H; Wickramanayake, S
The rapid shift towards online shopping has transformed consumer behavior, particularly in times of crisis. This study examines the factors influencing Sri Lankan consumers' online purchase intentions during crises, with a focus on the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB). The study explores the impact of Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Structural Assurance (SA), and Social Influence (SI) on online Purchase Intentions.
The study collected data from a sample of 415 Sri Lankan consumers who engaged in online purchasing during the economic and pandemic crisis period between 2020 and 2023. Participants represented diverse demographic segments, including university students, professionals, and homemakers, ensuring a broad understanding of consumer behavior.
A quantitative research approach, the data was collected from various Sri Lankan consumers through a structured survey. Statistical analysis was conducted to assess the relationships between key variables, revealing that digital trust, platform security, and peer influence significantly shape consumer decision-making in uncertain environments. Findings suggest that consumers prioritize ease of access, transaction security, and social validation when making online purchases during crises.
The study contributes to the academic discourse on e-commerce adoption in crisis scenarios and provides insights for businesses, policymakers, and digital marketers. By addressing factors that drive online shopping behavior in uncertain times, this research offers practical recommendations for enhancing consumer confidence and optimizing digital retail strategies. Future studies are encouraged to explore long-term behavioral changes, cross-country comparisons, and the role of emerging technologies in shaping online consumer trends.
item: Thesis-Full-text
Investigating the adaptation of privacy by design in software aimed at Sri Lankan end users
(2025) Subhashani, WKAG; Sandareka, W; Abeysekara, T
Software across desktop, mobile, web, and Internet of Things (IoT) technologies have evolved into powerful tools for customization and understanding user preferences which in turn collect vast amounts of user data. Consequently, organizations and governments worldwide have emphasized the importance of safeguarding user privacy through legal frameworks and principles such as Privacy by Design (PbD). PbD is a proactive approach that integrates privacy considerations into systems and processes from the outset rather than as an afterthought. While several studies have explored the integration of PbD in software development across different countries, there is a lack of research examining how Sri Lanka’s software industry adapts these principles. With the recent enactment of Sri Lanka’s Personal Data Protection Act (PDPA), software development firms are increasingly required to incorporate privacy and data protection measures. However, achieving a comprehensive approach necessitates going beyond regulatory compliance. This study investigates how software companies in Sri Lanka integrate PbD principles into the Software Development Life Cycle (SDLC) to ensure customer data privacy. A qualitative research design was adopted to gain in-depth insights into privacy considerations in software development. Data were collected through semi-structured interviews with seven experienced professionals working in medium-to-large-scale software firms or leading their own companies. Thematic analysis was employed to identify key themes related to privacy, privacy regulation, privacy design, and privacy embedding within the SDLC. Findings indicate that Sri Lankan software developers possess a strong understanding of privacy and legal compliance, particularly in relation to the PDPA. However, opinions remain divided regarding the implementation of pseudonymization and data encryption due to the associated costs and complexities, despite legal recommendations. Privacy embedding was found to be influenced by PbD principles, though not all principles are universally applied across contexts. The most commonly implemented privacy protection measures include data minimization and access control mechanisms. Additionally, the study highlights a trade-off between privacy and software performance, where excessive privacy measures can impact system efficiency and usability. This research contributes to the global discourse on privacy-aware software development by providing the first empirical insights into how the Sri Lankan software industry adapts PbD principles. The findings offer practical implications for industry professionals and policymakers seeking to enhance privacy integration within software development practices in emerging markets