http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/5814 Sat, 25 Apr 2026 03:19:16 GMT 2026-04-25T03:19:16Z http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/8810 Corporate governance and carbon emission disclosures: evidence from Sri Lanka Randunu, M. P. M. P.; Herath, H.M.M.N.; Wijekoon, W.M.H.N. The purpose of this study is to investigate whether corporate governance attributes such as Board Size, Board Independence, Audit Committee Independence, and ESG Committee impact carbon emission voluntary disclosures of environmentally sensitive listed companies in Sri Lanka. The sample of the study consists of 29 listed companies of CSE industry groups over the 2016 to 2020 period. Carbon emission disclosures were measured using the carbon disclosure project index checklist developed by Choi et al. (2013). Later, the corporate governance attributes that influence carbon disclosures were examined using panel data regression models. The findings of the study suggested that entities with higher number of directors on their boards were more likely to disclose carbon emission information and Board Independence and Audit committee Independence did not have a significant impact on reporting carbon emission information. Additionally, existence of the ESG Committee in companies had a strong positive impact on the carbon emission reporting and the extent of such disclosures. This study provides valuable insight which would be useful for organizations and regulatory bodies. Such an understanding is crucial for specifying necessary policies that will provide emission reduction practices and policies for entities. Thu, 01 Dec 2022 00:00:00 GMT http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/8810 2022-12-01T00:00:00Z http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/8809 Quantifying behavioral biasness in investment decisions with special reference to Uttar Pradesh Agarwal, A.; Sushma Behavioral biases haven't gotten the attention they merit, especially in the Indian context. Despite the abundance of information on behavioural finance, only a few academic research has sought to examine behavioural biases across different demographic groups. This research tries to address this lacuna in the literature. The present research work aims to investigate and quantify the behavioural biases that influence individual investors' investment decisions. The primary data was collected through a structured questionnaire from five prominent cities in the most populated state of India, i.e., Uttar Pradesh. The data was collected from 487 individual investors with the help of their financial advisors and brokers. The empirical research work revealed that eight listed biases affect investment decisions by nearly 82%. The outcome as a formal bias assessment instrument was supported by exploratory factor analysis (EFA) encompassing eight behavioural biases measured via 47 statements. The present research contribution, provides a formal assessment tool and further helps the researchers to uncover behavioral biases and develop de-biasing strategies. Academicians, financial advisers, practitioners, and economic psychologists are invited to utilize the instrument in order to further confirm its efficacy. Thu, 01 Dec 2022 00:00:00 GMT http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/8809 2022-12-01T00:00:00Z http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/8808 Effect of covid -19 pandemic on the performance of Sri Lankan banks Harshana, K. R.; Wanniarachchige, M. K. The COVID-19 pandemic has created detrimental effects on the Sri Lankan economy even though several fiscal and monetary policy measures were initiated. Nevertheless, the severity of these effects on the banking system has not been adequately documented in the literature. Thus, this study examined the effect of the COVID-19 pandemic on the performance of Sri Lankan banks using a sample of 18 licensed commercial banks. The data was collected from annual reports published by relevant banks for the ten years from 2012 to 2021. Return on equity, net interest margin and non-performing loans were used as measures of bank performance. Further, the study used liquidity measured using loan-to-deposit ratio, interest rate spread and state of the economy measured using gross domestic product growth rate as control variables. The results of three fixed effects panel regression models suggest that the COVID-19 pandemic has introduced statistically significant adverse effects on bank performance. This indicates that even though policy measures were taken, the banks have remained vulnerable. This implies that developing countries like Sri Lanka need comprehensive policy measures implemented at the initial stage of global pandemic situations to mitigate their adverse effects on the banks. Thu, 01 Dec 2022 00:00:00 GMT http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/8808 2022-12-01T00:00:00Z http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/8807 Information selection in default prediction: Sri Lankan bankers’ perspectives Fernando, J. M. R.; Li, L.; Hou, G. This study aims to ascertain the perceptions of bankers in Sri Lanka of the different default predictor information and the prediction performances. In semi-structured interviews, twenty-three credit risk and corporate banking managers from 26 banks in Sri Lanka were surveyed on their perceptions towards the application of accounting, share market and corporate governance information in corporate default prediction. The study follows mixed research design and uses semi-structured interviews to collect information of default prediction. Thematic analysis and t-tests were used to analyse the data. All the previous studies on corporate default prediction adopted quantitative methods to examine the role of different predictor information. This study contributes to the literature on redefining and realigning the corporate default prediction models with empirical quantitative findings. The results indicate that bankers in Sri Lanka have a generally positive perception of accounting information. They perceive governance information as being critical for credit decisions. However, no decisions are made using governance information. The majority of the bankers voiced negative perceptions about applying market information to their default prediction models. Further, bankers limit their default prediction models by devaluing or misunderstanding the role of different predictor information when making corporate lending decisions. Thu, 01 Dec 2022 00:00:00 GMT http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/8807 2022-12-01T00:00:00Z