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Open Access
Study on the Behavioral Intention to use Cryptocurrency Market among Non-State University Students in Sri Lanka
(SLIIT,Business School, 2022-06) Maduranga H.A.C.P; Bandara H.M.C; Nipuna Ravishka E.A; Ranjitha H.D.K; Dissanayake, L.D.A. D.
The rise of cryptocurrency in the modern digital economy is relatively new and evolving rapidly. Due to the intricate structure and insufficient knowledge about cryptocurrencies, it's use is limited to industrialized countries. The study consists of four independent variables: awareness, trust, ease of use, and risk. The dependent variable is cryptocurrency behavioral intention. A survey of 380 undergraduates is undertaken to get information on respondents' perceptions of cryptocurrency's attributes and their intention to invest in it in the future. Pearson Correlation analysis is being utilized to study the relationship between awareness, trust, ease of use, risk, and behavioral intention of cryptocurrencies as the major purpose. The dependent variable and Cryptocurrency Factors have a positive relationship, with a 0.01 level of significance for correlation. We adopted snowball sampling technique as the survey's sample design based on survey's results. Furthermore, the data is analyzed for reliability and validity using AMOS statistical software. Two of the four hypotheses were not supported while the other two were significantly supported. The study's findings enhance to undergraduates' potential investment opportunities in cryptocurrency and validate the level of accuracy of cryptocurrency knowledge among undergraduates in developing countries. By studying human behavior, researchers can better predict the prospects for future cryptocurrency adoption and success.
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Decrypting the Digital Vault by Understanding Cryptocurrency Adoption Challenges Among Gen Z: Case of Sri Lanka
(University of Nigeria Department of Mass Communication, 2025-01-01) Mallawaarachchi, S; Hemachandra, U; Jayakody, D; Wickramarathne, U; Lokeshwara, A.A; Bandara, G.C
Background: As digital natives, Gen Zs are at the forefront of embracing cryptocurrencies for technological innovation and financial empowerment. This study is part of a larger effort to understand the evolving trends in the world of cryptocurrency, highlighting the need for more research in this area. Objective: This study sought to explore the diverse challenges faced by Gen Zs while adapting to the usage of cryptocurrencies within the Sri Lankan context. Methodology: The researchers conducted this study using an inductive qualitative approach. Data were gathered through in-depth interviews with 24 participants, employing snowball sampling to recruit participants. The collected data were then analysed using thematic analysis, and the findings were presented in prose form. Results: The results of this study revealed three key themes that significantly impact the usage of cryptocurrency as a digital asset among Gen Zs in Sri Lanka: (i) Trust and security concerns, (ii) Market volatility and investment risks, (iii) Regulatory approach and cryptocurrency transactions. Conclusion: Although cryptocurrency has gained acceptance among Gen Zs, its usage is determined by factors that ensure that users harness its full benefits. Contribution: This study has revealed the diverse challenges that Gen Zs embraced when adopting cryptocurrencies. © 2025, University of Nigeria Department of Mass Communication. All rights reserved.
Open Access
Cryptocurrency Price Prediction: A Comparative Study using LSTM, GRU and Stacking Ensemble Algorithm for Time Series Forecasting
(SLIIT, 2022-02-11) Ashikul Islam, M. D
Technology has significantly reshaped how humans interact with their tangible and intangible surroundings. Cryptocurrency is considered to be one of the most recent technological inventions which revolutionized how we perceive currencies and their functionality. It has become popular because of its safety, security and anonymity. However, volatility remains one of the major issues with cryptocurrencies to this day. Therefore, the primary aim of this paper is to develop LSTM (Long ShortTerm Memory), GRU (Gated Recurrent Units) and a Stacking Ensemble Learning algorithm that efficiently predicts the price of a cryptocurrency for a given period of time. The predictions are then observed and analysed to determine the comparative performance of the said algorithms.

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