Research Publications Authored by SLIIT Staff
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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.
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Publication Embargo The digital bridge: how digital transformation mediates the innovative culture-resilience nexus in IT firms(Emerald Publishing, 2025) Kodithuwakku, T; Samaraweera, I; Mathew, M; Samarakkody, T; Thelijjagoda, S; Gamage, SPurpose – This study aims to identify the impact of innovative culture on organizational resilience in the Sri Lankan information technology (IT) sector, with a specific focus on the mediation role of digital transformation. Design/methodology/approach – Using a quantitative approach, data were collected from over 274 participants who were managerial or above-level employees in the IT industry via surveys. Partial least squares structural equation modeling was used to analyze the data and test the hypothesized relationships between variables. Findings – The findings of this study revealed that innovative culture has a significant positive impact on the adoption of digital transformation, as the innovative mindset that is ingrained encourages continuous growth, creativity and risk-taking, thereby strengthening digital transformation initiatives. Both innovative culture and digital transformation have a significant positive impact on organizational resilience. Digital transformation significantly mediates the effect of innovative culture on organizational resilience. Practical implications – The findings offer valuable guidance to industry leaders and policymakers for the strategic utilization of technology and the design of appropriate business models. Originality/value – This study emphasizes the importance of developing innovative culture and digital transformation in the IT industry to ensure sustainable business processes.Publication Open Access Framework to create opportunities to maximize the contribution of differently abled employees in the Sri Lankan garment industry(Springer Science and Business Media, 2025-04) Gurudasa, P; Lokeshwara, A; Weerarathna, R; Thelijjagoda, S; Weerasinghe, C; Fonseka, S; Dananjaya, SThe primary focus of this study was on Differently Abled Employees’ (DAEs) work performance within Sri Lanka’s garment industry. Prior research revealed inadequate awareness among organizations regarding the provision of employment opportunities for DAEs. Notably, DAEs constitute a substantial portion of the economically inactive working-age population in Sri Lanka. In this setting, the study aimed to identify the crucial factors influencing the contribution of DAEs in the Sri Lankan garment industry. In this setting, the study sought to measure their impact and develop a framework that supports both DAEs and the garment industry, fostering a mutually beneficial work environment. Utilizing a mixed approach, the study encompassed a sample population of 270 DAEs. Data collection involved semi-structured interviews and a Likert scale questionnaire. Convenience sampling was deployed to interview 14 DAEs, while a sample of 159 DAEs was selected through simple random sampling for the distribution of the questionnaire. Thematic analysis and multiple linear regression analysis were employed to analyze qualitative and quantitative data. The results underscored the significance of the examined factors affecting DAEs’ contributions. Based on regression analysis results, the researchers developed a framework, which underwent further refinement through reviews and discussions. The findings proposed supportive strategies to achieve the overarching objective of the study to maximize DAEs’ contributions in the workplace.Publication Embargo 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., 2023-07-12) 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 Can visual impairment impact your income potential?(PLoS ONE, 2023-04-20) Wickramaarachchi, C; Jayathilaka, R; Suraweera, T; Thelijjagoda, S; Kollure, LPeople’s quality of life (QOL) has been disrupted globally in the wake of the pandemic in recent times. This was mainly due to global economic crises fuelled by the coronavirus (COVID– 19) and other related factors. Sri Lanka, too, was facing major social and economic constraints in the period 2021–2022. Thus, all communities islandwide have been economically disturbed. Among others, people with Visual Impairment and Blindness (VIB) have been pushed to severely disadvantageous positions, financially and otherwise. A sample from three geographical locations in Sri Lanka; and eleven individuals representing diverse cadres in Sri Lankan society were purposively selected for the study based on the existence of the majority of the visually impaired community using a mixed approach. Descriptive statistics were utilised to analyse the identified socio-economic characteristics. Ordered probit regression was employed to determine the mediating effect of socio-economic status on income levels. Word Cloud illustrates the factors affecting the QOL. Most severely impaired individuals are more likely to earn a lower rate of income. This situation has degraded their lives and poor QOL. Participants’ responses elucidate that facilities, resources, education, opportunities, income, employment, and government activities would enhance their QOL. The study adds value to society by recognising VIB people, helping them gain financial independence and strengthening them without marginalising the impaired community. The proposed policies in this study would be valuable for these social groups to address their wealth concerns.Publication Embargo MiMi: Sinhala Language Speech Assistive Learning Bot to Support Children with Stuttering(IEEE, 2022-12-13) Vithana, K.C.D; Weerarathne, D.N.N; Krishan, H.A.S; Wijesiri, M.R.M; Thelijjagoda, S; Jayawickrama, J. A. D. T.This research paper presents “MiMi”, a Sinhala Language voice assistive gamified solution that is designed to address stuttering in children aged between three and fourteen. Speech disorders occur when the regular flow of communication is disrupted. Stuttering, Lisps, Dysarthria, and Apraxia are some variations of speech impairments. Stuttering can be caused by a variety of factors including physical weaknesses, inherited diseases, Autism, and accidents. The risk of continuing to stutter into adulthood is highest in children between the ages of three to fourteen. It is recognized that stuttering therapy activities were less effective in managing stuttering after this age. Stuttering treatments comprise speech therapy with speech-language therapists, which requires in-person sessions that can be challenging and expensive in some circumstances. A parent’s financial ability, their busy schedules, the state of the economy in the nation, and the feasibility of physically seeing therapists and enduring treatments are all factors that might encourage or demotivate participation in therapy sessions. The development in technology and technical approaches have revolutionized the medical field and several studies have been conducted regarding communication disorders in recent years. The application can be used to practice a child’s needed speech therapy virtually and can also be used to aid speech therapy sessions done by speech therapists. The main aim of the system is to provide a customized, engaging, and innovative therapeutic strategy for children to manage stuttering.Publication Embargo DevFlair: A Framework to Automate the Pre-screening Process of Software Engineering Job Candidates(IEEE, 2022-12-09) Jayasekara, R.T.R; Kudarachchi, K.A.N.D; Kariyawasam, K.G.S.S.K; Rajapaksha, D; Jayasinghe, S.L; Thelijjagoda, SThe HR department of a technology company receives hundreds of job applications for each Software Engineering related vacancy. Evaluating a candidate by looking at the curriculum vitae may appear to be easy during the pre-screening process. However, an automated pre-screening process using Natural Language Processing and Machine Learning methodologies would help the recruiter to obtain a more accurate and deeper understanding of the candidate. In this paper we propose “DevFlair”, a framework to automate pre-screening Software Engineering job candidates. DevFlair uses data from social media, GitHub, and open-ended questionnaires to predict the Big-Five personality traits, analyze technical skill expertise, and analyze the experience in using industry-related online platforms. After analysis, the candidates are ranked according to their personality and technical skill levels. We conduct the personality prediction experiments using a social media posts dataset annotated with gold-standard Big-Five personality labels. We train FastText classification models and compare their accuracy against other state of the art classification models. The comparisons conclude that the FastText classification models substantially outperform the state of the art classification models when predicting Openness, Conscientiousness, and Agreeableness personality traits.Publication Embargo Assistant Zone – Homeschooling Assistance System based on Natural Language Processing(IEEE, 2022-12-09) Premendran, K; Bopearachchi, S.B.D.D.; Senevirathna, S.D.M.; Giridaran, S; Archchana, K; Ganegoda, D; Thelijjagoda, SAs a developing country, most people give their highest priority to education. When focusing on building an e-learning platform to improve the knowledge of students and teacher-student interactivity, the pandemic season can be mentioned as the main blocker which highly impacted the education field. Not only by considering the pandemic situation but also by addressing the concerns when it comes to teacher and student evaluation and psychological levels of students who are undergoing different difficulties, the “Home Schooling Assistance System” (Assistant Zone) has been introduced as a solution. The Assistant Zone has been initiated with three unique features which are valuable for both students and teachers. This system analyzes the strengths, weaknesses and evaluates the student performance, suggests study materials to improve themselves, provides solutions to the problems faced by the students, teachers, and parents and measures the performance of teachers based on their students, and recommends learning materials for the low-performing teachers. The Assistant Zone fulfills the targeted problems and introduces the above-mentioned three unique features with the use of Natural Language Processing (NLP) such as the BERT algorithm and Machine Learning models such as the Recurrent Neural Network, Forward Neural Network, and Gaussian Model.Publication Embargo Impact of Critical Success Factors in Oracle EBS Enterprise Resource Planning Post Go Live Implementation:A Case Study on SriLankan Airlines(Institute of Electrical and Electronics Engineers, 2022-01-08) Dissanayake, I; Thelijjagoda, SIn today's business world, ERP does everything from recording transaction data, managing workflows, analyzing data to provide insights to decision makers for effective decision making. Selection of a right ERP, proper testing and post go live could be a major scale system implementation for any organization. Thus, it is extremely beneficial to evaluate and test the Critical Success Factors (CSFs) in order to ensure a successful ERP post go live implementation. The primary goal of this study is to determine the impact of Critical Success Factors that influence for a successful post go live ERP implementation in the context of the national airline of Sri Lanka which is SriLankan Airlines. Three critical success factors were identified through this study. This study aims on Adequate end user training, Business Process Management (BPM) and Top Management Support as CSFs. The findings have verified that the ERP implementation success is influenced by the Top Management Support, Business Process Management and adequate end user trainings. Out of the identified three CSFs, it is statistically proven that the adequate end user training takes a significantly prominent place for a successful post go live implementation while BPM and Top Management Support also equally contribute to drive an ERP implementation project with expected outcomes. This study could be a guidance for enterprises, be beneficial to ERP clienteles, ERP consultants and service providers, be added to the existing body of knowledge.Publication Embargo AppGuider: Feature Comparison System using Neural Network with FastText and Aspect-based Sentiment Analysis on Play Store User Reviews(Institute of Electrical and Electronics Engineers, 2022-10-22) Thelijjagoda, S; Oshadi, D.M.KNowadays, there's a rapid growth in the number of apps downloaded from the app stores. People nowadays use apps for even the most simple daily tasks. In this situation, people always tend to search for new apps for the new tasks they come across in daily life. User reviews have a high impact on the app downloads. When analysing user reviews, it's important to consider the aspect that has been discussed in reviews. In mobile app reviews, the discussed aspect is mostly a functionality or feature of the mobile app. Therefore, it's crucial to make use of this important data in a way that helps app seekers to easily find the best-suited app for their requirements and also helps app developers to identify their weak features that need to be improved. This research was conducted to provide a strategy that visualizes user review summaries in a form that is relevant to the end user with the intention of achieving a model that is not only lightweight but also highly accurate and effective in terms of its performance. The AppGuider system was implemented, mainly with two models for sentiment analysis and aspect extraction. The sentiment classification model was developed with a deep learning approach that included a two-layer neural network, while the aspect extraction model was built with an unsupervised machine learning approach using the LdaMulticore algorithm. FastApi was used for data visualization in Frontend. User reviews were vectorized with FastText prior to input into the model. The accuracy of the sentiment classification model is 91%, with an 85.97% f1 score, an 85.93% recall, and an 86.05% precision. The FastText model outperformed the Stanford CoreNLP library in the performance test. The integrated system was evaluated by 25 user reviews that were entered manually and sentiment classification model scored 92% while the aspect extraction model scored of 76% accuracy.Publication Unknown AI Solution to Assist Online Education Productivity via Personalizing Learning Strategies and Analyzing the Student Performance(Institute of Electrical and Electronics Engineers, 2022-10-29) Liyanage, M.L.A.P.; Hirimuthugoda, U.J; Liyanage, N.L.T.N.; Thammita, D.H.M.M.P; Koliya Harshanath Webadu Wedanage, D; Kugathasan, A; Thelijjagoda, SHigher productivity in online education can be attained by consistent student engagement and appropriate use of learning resources and methodologies in the form of audio, video, and text. Lower literacy rates, decreased popularity, and unsatisfactory end-user goals can result from unbalanced or inappropriate use of the aforementioned. Prior studies mainly focused on identifying and separating the elements affecting the quality of online education and pinpointing the students' preferred learning styles outside of in-person and online instruction. This has not been able to clearly show how to enhance and customize the online learning environment in order to benefit the aforementioned criteria. This case study will primarily concentrate on elements that can be personalized and optimized to improve the quality of online education. With the aid of various algorithms like logistic regression,Support Vector Machines (SVM), time series forecasting (ARIMA), deep neural networks, and Recurrent Neural Networks (RNN), which make use of machine learning and deep learning techniques, the ultimate result has been attained. To increase application and accuracy, the newly presented technique will then be presented as a web-based software application. Contrary to what is commonly believed, this applied research proposes a new all-in-one Learning Management System (LMS) for students and tutors that acts as a central hub of all the learning resources.