Department of Information Management
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Publication Embargo Renewable realities: Charting a greener course for the world's high-emitting nations through information technology insights(Wiley, 2024-11-14) Ranthilake, T; Caldera, Y; Senevirathna, D; Gunawardana, H; Jayathilaka, R; Peter, SCarbon dioxide (CO₂) is the most abundant gas among all greenhouse gas emissions,severely impacting global warming. This study examines the impact of Informationand Communication Technology (ICT), population dynamics, Per Capita GrossDomestic Product (PGDP), and Renewable Energy Consumption (REC) on CO₂ on aglobal scale, representing 38 countries selected using the Pareto principle. Resultsfrom the panel regression model indicate a significantly positive relationship betweenICT, PGDP, and population on CO₂ emissions. In contrast, REC exhibits a negativerelationship. The Multiple Linear Regression model shows that an increase in PGDPleads to higher CO₂ emissions, except in Uzbekistan. ICT increases emissions in theUnited States, Argentina, Australia, Canada, and Egypt. Population growth raisesemissions, except in the United States, France, Germany, and Russia. REC reducesCO₂ emissions in most countries. Policymakers in individual countries can gain a pre-cise understanding of how these variables impact CO₂ emissions, enabling them tomitigate the risks associated with global warmingPublication Open Access The interconnectedness of energy consumption with economic growth: A granger causality analysis(Elsevier Ltd, 2024-09-15) Perera, N; Dissanayake, H; Samson, D; Abeykoon, S; Jayathilaka, R; Jayasinghe, M; Yapa, SIn considering today's energy challenges, the link between the usage of renewable and non-renewable energy sources and economic growth has gained substantial policy attention. This research examines the complex relationship between these three variables to understand how non-renewable energy consumption and renewable energy consumption interact and what that means for economic growth. This study uses the Granger causality approach to explore the relationships between non-renewable energy consumption, renewable energy consumption, and economic development. It draws on a comprehensive dataset from the Word Bank database, including 152 nations from 1990 to 2019. The analysis is further disaggregated by four subgroups of countries; least developed, developed, transitional economies and developing countries. The result of this study provides valuable empirical evidence of uni-directional causality running from renewable energy consumption to economic growth and non-renewable energy consumption to economic growth in transitional economies. Furthermore, policymakers should focus on both variables when making decisions because the results show that energy consumption and economic growth are interconnected. Implementing global energy efficiency standards, reducing fossil fuel usage, and adopting regulatory measures are all viable policies for limiting adverse effects on the environment while encouraging economic development.Publication Open Access Security matters: Empowering e-commerce in Sri Lanka through customer insights(Springer Nature, 2024-12) Jayathilaka, R; Udara, IIn the fast-paced, post-COVID digital world, e-commerce presents promising prospects for significant advancement. However, customers often feel uncertain due to persistent concerns about the robustness of security measures safeguarding e-commerce platforms. The primary objective of our study was to identify factors affecting the security of e-commerce platforms based on the perceptions of Sri Lankan customers. This research was conducted using data collected from Sri Lankan e-commerce users via both online and offline surveys. An ordered probit regression model was utilised, demonstrating that transaction security, privacy, vendor system security, and platform quality positively impact the perceived security of e-commerce. The e-commerce industry in Sri Lanka is expected to see growth and an increased user penetration rate. The findings of this study are anticipated to assist e-commerce business owners and policymakers in addressing critical security issues, namely vulnerabilities in transactional security, low privacy, inadequate system security, and poor e-commerce platform quality. These improvements are expected to build trust and credibility among consumers, maximising e-commerce success.Publication Open Access Unveiling Sri Lanka’s brain drain and labour market pressure: A study of macroeconomic factors on migration(Public Library of Science, 2024-03) Kaluarachchi, S; Jayathilaka, RThe purpose of this study is to explore the impact of GDP per capita income (GDPPCI), unemployment, higher education (HE), and economic growth (EG) on migration in Sri Lanka. Numerous global and local studies have explored the influence of macroeconomic and socioeconomic factors on migration. In the Sri Lankan context, fewer studies have probed the impact of GDPPCI, unemployment, HE, and EG on migration, particularly concerning brain drain and domestic labour market pressure. An applied research methodology was adopted, utilising annual data from 1986 to 2022. The statistical data were sourced from reports by the Sri Lanka Bureau of Foreign Employment (SLBFE), the Central Bank of Sri Lanka (CBSL), Labor Force Survey Data from the Department of Census and Statistics (LFSDCS), and University Grants Commissions (UGC). This study utilised the Vector Error Correlation model (VECM), Vector Auto-regression (VAR), and Granger Causality test through STATA. The empirical findings of the VAR model highlighted that GDPPCI and EG negatively impact migration, whereas unemployment and HE positively affect migration. The study’s implications demonstrated that GDPPCI, unemployment, HE, and EG were the primary factors influencing the country’s migration decisions. These findings will hopefully inform and guide the Sri Lankan government and policymakers for more effective decision-making. © 2024 Kaluarachchi, Jayathilaka. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Publication Open Access Personal well-being index as a measure of quality of life of diverse groups of people with visual impairment and blindness(Springer Science and Business Media B.V., 2024-04) Jayathilaka, R; Dunuwila, V; Attale, D; De Seram, H; Sudusinghe, D; Abeyrathna, I; Suraweera, T; Thelijjagoda, SToday, the world adopts various assessment tools and indices to measure quality of life (QoL) of different persons. The Personal Well-being Index (PWI) is a popular and validated tool used by developed countries to assess the QoL of their citizens. The PWI consists of seven major domains that define people’s QoL. Thus, the main purpose of this study is to explore the application of PWI in measuring the QoL of the visually impaired and blind (VI and B) persons in Sri Lanka, and to identify how QoL varies with their demographic characteristics. Primary data revealed among 64 VI&B, 34 blind and 30 visually impaired people from Hambanthota, was analysed based on vision level, age, gender, marital status, and the level of education. Results indicated that visually impaired (VI) respondents had a higher PWI value than that of the blind. Accordingly, the age group of 40–59 contributes to a higher PWI value than that of others; while the results signify that the PWI values basically depend on the levels of education the participants received. It is significant that the blind and the partially sighted people are concerned about their future security to a greater extent compared to the other domains in the PWI. Also, QoL was perceived to deteriorate with age. Thus, it is evident that efforts to improve QoL of people with visual disabilities requires priority to secure a fruitful and secure future for them.Publication Open Access Examining the influence of global smoking prevalence on stroke mortality: insights from 27 countries across income strata(Springer link, 2024-03-19) Abeysekera, I; De Silva, R; Silva, D; Piumika, L; Jayathilaka, R; Rajamanthri, LBackground This study investigates the influence of Global Smoking Prevalence (GSP) on Stroke Death Rates (SDR) across 27 countries categorized into High-Income Countries (HIC), Upper Middle-Income Countries (UMIC), Lower Middle-Income Countries (LMIC), and Low-Income Countries (LIC). Methods Analysing data from two distinct periods (1990–1999 and 2010–2019), countries exhibiting an increased SDR were selected. The study uses a polynomial regression model, treating income groups as cross-sectional and years as time series data. Results Results from the regression model reveal that 17 countries observed a significant impact of GSP on SDR, with only Turkey, Solomon Islands, and Timor-Leste resulting in negative values. However, the study emphasises that out of all 27 countries, the highest occurrence of the impact of GSP on SDR has been reported in the LMIC stratum for the period under review. Conclusion It is evident that GSP affects the risk of incidence of stroke death, specifically in the LMIC stratum. Furthermore, it has been identified that GSP is a major preventable risk factor affecting global mortality. To mitigate the risk of stroke death attributable to smoking prevalence, necessary preventive steps should be adopted to encourage smoking cessation, and essential policies should be implemented to reduce the burden of SDR.Publication Open Access Towards a greener future: examining carbon emission dynamics in Asia amid gross domestic product, energy consumption, and trade openness(Springer Nature, 2024-02-10) Dharmapriya, N; Edirisinghe, S; Gunawardena, V; Methmini, D; Jayathilaka, R; Dharmasena, T; Wickramaarachchi, C; Rathnayake, NThe purpose of this study is to examine the impact of gross domestic product, energy consumption, and trade openness on carbon emission in Asia. Among the 48 countries in Asia, 42 were included in the analysis, spanning a period of 20 years. Given that Asia is the predominant contributor, accounting for 53% of global emissions as of 2019, a comprehensive examination at both continental and individual country levels becomes imperative. Such an approach aligns with local, regional, and global development agendas, contributing directly and indirectly to climate change mitigation. The analytical techniques employed in this study encompassed panel regression and multiple linear regression, illuminating the specifc contributions of each country to the study variables and their impact on carbon emissions. The fndings suggest that gross domestic product (13 out of 42 countries), energy consumption (21 out of 42 countries), and trade openness (eight out of 42 countries) have a highly signifcant impact (p<0.01) on carbon emissions in Asia. Energy consumption plays a vital role in increasing carbon emissions in Asia, driven by rising populations, urbanisation, and oil and gas production. Policymakers can take several actions such as adopting a carbon pricing system, using sustainable transportation, renewable energy development,and international cooperation within Asia to reach the goal of being carbon neutral by 2050.Publication Open Access Forecasting weekly dengue incidence in Sri Lanka: Modified Autoregressive Integrated Moving Average modeling approach(PLoS ONE, 2024-03-08) Karasinghe, N; Peiris, S; Jayathilaka, R; Dharmasena, TDengue poses a significant and multifaceted public health challenge in Sri Lanka, encompassing both preventive and curative aspects. Accurate dengue incidence forecasting is pivotal for effective surveillance and disease control. To address this, we developed an Autoregressive Integrated Moving Average (ARIMA) model tailored for predicting weekly dengue cases in the Colombo district. The modeling process drew on comprehensive weekly dengue fever data from the Weekly Epidemiological Reports (WER), spanning January 2015 to August 2020. Following rigorous model selection, the ARIMA (2,1,0) model, augmented with an autoregressive component (AR) of order 16, emerged as the best-fitted model. It underwent initial calibration and fine-tuning using data from January 2015 to August 2020, and was validated against independent 2000 data. Selection criteria included parameter significance, the Akaike Information Criterion (AIC), and Schwarz Bayesian Information Criterion (SBIC). Importantly, the residuals of the ARIMA model conformed to the assumptions of randomness, constant variance, and normality affirming its suitability. The forecasts closely matched observed dengue incidence, offering a valuable tool for public health decision-makers. However, an increased percentage error was noted in late 2020, likely attributed to factors including potential underreporting due to COVID-19-related disruptions amid rising dengue cases. This research contributes to the critical task of managing dengue outbreaks and underscores the dynamic challenges posed by external influences on disease surveillance.Publication Open Access Unveiling Sri Lanka’s brain drain and labour market pressure: A study of macroeconomic factors on migration(PLoS ONE, 2024-03-11) Kaluarachchi, S; Jayathilaka, RThe purpose of this study is to explore the impact of GDP per capita income (GDPPCI), unemployment, higher education (HE), and economic growth (EG) on migration in Sri Lanka. Numerous global and local studies have explored the influence of macroeconomic and socioeconomic factors on migration. In the Sri Lankan context, fewer studies have probed the impact of GDPPCI, unemployment, HE, and EG on migration, particularly concerning brain drain and domestic labour market pressure. An applied research methodology was adopted, utilising annual data from 1986 to 2022. The statistical data were sourced from reports by the Sri Lanka Bureau of Foreign Employment (SLBFE), the Central Bank of Sri Lanka (CBSL), Labor Force Survey Data from the Department of Census and Statistics (LFSDCS), and University Grants Commissions (UGC). This study utilised the Vector Error Correlation model (VECM), Vector Auto-regression (VAR), and Granger Causality test through STATA. The empirical findings of the VAR model highlighted that GDPPCI and EG negatively impact migration, whereas unemployment and HE positively affect migration. The study’s implications demonstrated that GDPPCI, unemployment, HE, and EG were the primary factors influencing the country’s migration decisions. These findings will hopefully inform and guide the Sri Lankan government and policymakers for more effective decision-making.