VJBM,Vol 7 http://drr.vau.ac.lk/handle/123456789/1642 2026-04-05T21:29:32Z 2026-04-05T21:29:32Z Gowsalya, S. Ekanayaka, R. G. I. D. http://drr.vau.ac.lk/handle/123456789/1648 2026-01-08T21:30:18Z 2024-01-01T00:00:00Z

The Relationship between Ownership Structure and Dividend Policy: Evidence from Licenced Commercial Banks in Sri Lanka Gowsalya, S.; Ekanayaka, R. G. I. D. In today's dynamic business environment, ownership structure and dividend policy are increasingly recognized as critical financial concepts. This study aims to examine the impact of ownership structure on dividend policy in licensed commercial banks in Sri Lanka. The research considers Managerial Ownership, Institutional Ownership, and Foreign Ownership as independent variables, while Dividend Policy serves as the dependent variable, with Firm Size included as a control variable. The study utilizes annual data from 2019 to 2023, covering a sample of 20 licensed commercial banks. Data analysis was conducted through applying descriptive statistics, correlation analysis, and multiple regression analysis to assess the relationships among variables and the influence of ownership structure on dividend policy. The correlation analysis indicates a significant negative relationship between Institutional Ownership and Dividend Policy, while Foreign Ownership exhibits a significant positive relationship with Dividend Policy. Multiple regression results further confirm that Institutional Ownership negatively impacts Dividend Policy. However, the study finds no significant impact of Managerial Ownership, Foreign Ownership, or Firm Size on Dividend Policy. The findings of this study provide valuable insights for investors and companies, enabling them to make informed investment decisions. Understanding the relationship between ownership structure and dividend policy enhances investor performance and contributes to corporate governance practices.

2024-01-01T00:00:00Z Romsiya, R. Tharshiga, P. Rathiranee, Y. http://drr.vau.ac.lk/handle/123456789/1647 2026-01-08T21:30:27Z 2024-01-01T00:00:00Z

The Nexus Between Working Capital Management and Firm Performance: Leverage as a Moderator Romsiya, R.; Tharshiga, P.; Rathiranee, Y. This study seeks to investigate the impact of WCM on firm performance and the moderating role of leverage in this relationship. Employing a quantitative approach, the study analyzes secondary data from the annual reports of forty-two companies spanning the periods from 2018/19 to 2022/23. The methodology includes descriptive statistics, correlation analysis, unit root tests, and panel regression models to ensure a robust econometric evaluation. The findings indicate that higher liquidity, as reflected by the Current Ratio (CR), positively influences both ROA and ROE, while an efficient DSO significantly improves asset efficiency. Additionally, the research reveals that leverage moderates the relationship between DSO and ROA, suggesting that firms with elevated debt levels must prioritize rapid collection of receivables to mitigate liquidity risks. Conversely, DIO and DPO demonstrate a limited direct effect on firm performance within this sector. These results underscore the importance of tailored WCM strategies and offer valuable insights for policymakers aiming to develop supportive frameworks. Future research should consider broader samples, explore additional moderating variables, and incorporate qualitative methods to deepen the understanding of WCM dynamics in various contexts. This work contributes to both academic and professional literature by highlighting the essential role of effective WCM in enhancing firm performance, particularly in high leverage environments..

2024-01-01T00:00:00Z Abeykoon, B.B.D.S. Sirisena, A.B. http://drr.vau.ac.lk/handle/123456789/1646 2026-01-08T21:30:25Z 2024-01-01T00:00:00Z

Mapping the Landscape of Management Information Systems: A Bibliometric Approach Abeykoon, B.B.D.S.; Sirisena, A.B. The discipline of management information systems (MIS) has been profoundly impacted by a large volume of scientific works published in the last few years. In order to make a scholarly accomplishment, this investigation recognizes the contributions that have exerted the most significant influence on the field of MIS research. The study objectives are: (1) to reflect the contemporary state of the MIS research field, and (2) to identify the knowledge gaps that require more attention, and promote MIS. The study utilized bibliometrics, performance analysis, and science mapping, preceded by Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). The analysis was executed using the Scopus database, which consisted of 1253 journal articles from 324 sources produced between 2018 and 2022. The study carried out the descriptive analysis and main analysis pertaining primarily to sources, authors, counties, and keywords. Furthermore, the health sector was identified as a key element contributing to the MIS. The findings of the study contribute to the advancement of academic knowledge in MIS and provide insights into the emerging trends in the field while facilitating the expansion of MIS research.

2024-01-01T00:00:00Z Sathana, V. http://drr.vau.ac.lk/handle/123456789/1645 2026-01-08T21:30:30Z 2024-01-01T00:00:00Z

Exploring Challenges For Artificial Intelligence Readiness in SMEs in Sri Lanka Sathana, V. AI technology adoption looks pretty challenging for the SME sector. Studies explain the challenges and barriers; AI readiness is context-based, and there is limited context-specific research on how Sri Lanka’s socioeconomic and infrastructural conditions shape these issues. Existing global models of AI readiness often fail to capture these localised realities, making them less applicable in the Sri Lankan Context. The study aims to identify and analyse challenges to AI adoption in Sri Lankan SMEs and assess AI-readiness among SMEs in Sri Lanka. The researcher applied qualitative research methodology to analyse the key factors. A purposive sampling method was used to select the research respondents. An in-depth interview was conducted to collect primary data from the subject. The researcher utilised coding and thematic analysis to analyse the data. The findings revealed three key factors, namely AI knowledge, macro environment, and microenvironment, that influence the artificial intelligence readiness of SEMs. The challenge of AI knowledge consists of AI awareness, AI benefits, and AI technology implementation. Macro environmental factors include AI ethics, AI society, economic, political, legal (Regulation), competition, and technological factors. The micro environment includes organisational structure, culture, financial, human resources, and data strategy. The result of the study reveals that Small and Medium Enterprises (SMEs) in Sri Lanka face considerable challenges in adopting AI technology; most SMEs in Sri Lanka are not fully ready to embrace AI technology. In addition, the researcher found that AI applications vary for specific sectors, and most SMEs do not have explicit knowledge about AI applicationsThis finding emphasised the need for academic inquiry into the role of education and training programs to address gaps in AI knowledge and awareness, which are foundational for SMEs' successful adoption of AI technologies. Furthermore, the findings underscore the importance of studying external factors such as AI ethics, AI society, Economic, Political, and legal (Regulation) challenges, Data Strategy, Competition, and Technological challenges to understand better how macro-environmental conditions shape SMEs' AI strategies.

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