Browsing by Author "Rathnayake, R.M.K.T."

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Effectiveness of Machine Learning Algorithms on Battling Counterfeit Items in E-commerce Marketplaces
(Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka, 2023) Gunawardhana, Kalinga; Kumara, B.T.G.S.; Rathnayake, R.M.K.T.; Jayaweera, Prasad M.
For e-commerce marketplaces, counterfeit goods are a major issue since they endanger public safety in addition to causing customer unhappiness and revenue loss. Traditional techniques to identify fake goods in online marketplaces take too long and have a narrow reach, hence they are ineffective. Machine learning algorithms have become a potential tool for swiftly and precisely identifying counterfeit goods in recent years. The usefulness of two machine learning algorithms in identifying fake goods in online marketplaces is examined in this research. The study assesses the performance using a sizable dataset of descriptions, title, prices and seller names from many well-known e-commerce platforms. The study's findings show that machine learning algorithms significantly affect the detection of fake goods in online marketplaces.
The Impact of Soft Productivity Factors on Employee Turnover in IT Industry; A Case Study in Sri Lanka
(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Perera, B.A.A.; Rathnayake, R.M.K.T.
Employee turnover has become one of major issues in IT industry in Sri Lanka. Employee turnover is deeply related with the productivity of an organization. Therefore the major purpose of this study is to examine how some selected soft productivity factors affect employee turnover in IT sector and introduce recommendations to reduce turnover rate. Eleven soft productivity factors were considered in the study and they were grouped as workplace environment and employees' capabilities and experience. The major data collection method used in the study was questionnaire survey and descriptive statistics were employed as well. Pilot testing was conducted before data collection and reliability of questionnaire was tested in order to filter the most valid questionnaire. The target population was IT employees who were employed in IT companies at the time. According to the results most employees were totally satisfied with the working place (73.3%) when there were good collaboration with team members (70.4%), no heavy workloads (75.3%), training and development programs (54.2%), when employees were provided with appropriate tools and development resources (70%) and encouraged to rest and refresh (60.9%). Good blend of different characteristic employees had been a motivation to retain in the organization (72.3%). It is concluded that good relationships and collaboration among employees and good blend of different characteristic team members are critical factors which support employee retention. Physical separation of team members has no significant effect on employee turnover if there are sufficient and efficient telecommunication facilities. Comfortable working conditions make employees less stressed and workload does not matter in such environments. When employees’ experience level, skills, and capabilities are higher, they tend to leave organizations for better opportunities.