Enhancing Transparency and Fairness in Digital Lucky Draws Using Smart Contracts
Abstract
Traditional lucky draw systems often face trust issues due to a lack of transparency and potential for manipulation. This study addresses these challenges by developing and evaluating a blockchain-based lucky draw prototype named "LuckyDraw." A mixed-method approach was employed, combining an applied research method with the Agile Scrum framework for system development, and a quantitative survey to evaluate user acceptance. The quantitative analysis, using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique on data from 100 respondents, confirmed the instrument's validity and reliability. The results showed that Perceived Usefulness (PU) was the strongest predictor of Behavioral Intention (BIU), followed by Trust (TRT). Furthermore, Perceived Ease of Use (PEOU) had a significant positive effect on PU. These findings indicate that a transparent, trustworthy, and easy-to-use system is highly accepted by users, offering a viable solution to the shortcomings of traditional systems.
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DOI: http://dx.doi.org/10.36448/jsit.v16i2.4547
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