The importance of information literacy in today’s digital world is increasingly emphasized. This is particularly evident in the context of using digital financial services. This article aims to investigate whether there is a relationship between information literacy and online payment preferences among a student population and whether there are gender differences in online payment habits. An online survey was conducted among students in Osijek examining information literacy and the types of goods they purchase and pay for through online financial services. Of the 408 respondents, the majority were female (86.27%), who were more likely to buy and pay for clothing, while men were most likely to make payments for particular features of video games. Differences were also found in the tendency to make online payments. Because no obvious linear relationships were found between reported information literacy and other variables, a neural network model with a multilayer perceptron (NN) architecture was developed to classify participants according to their reported information literacy level. The best overall classification accuracy of the NN was 73.17%. The NN and its sensitivity analysis revealed some hidden patterns that can help educational institutions develop information literacy and digital financial literacy programs for their students.
In today’s world, where almost everything takes place in the virtual world, information and informatics, as well as financial literacy are becoming increasingly important. Although most of the university students are considered to be sufficiently information and informatics literate, the Covid-19 pandemic has confirmed how necessary it is to possess the skills and knowledge related to these literacies in order to maintain quality of life by using new financial technologies and be effective in various spheres of life. This study investigated whether there is connection between these two literacies and financial literacy of university students. Also, students’ demographic data, Internet use, agreement with statements concerning information and informatics literacy as well as the use of payment services before and after the Covid-19 pandemic was explored. In addition, the research aim was also to see if acceptable neural network model could be made for distinguishing students based on their reported financial literacy. Monte Carlo exact test showed that there is statistically significant association at the 0.05 level of significance between the self-reported informatics literacy and information literacy (p = .000, two-sided), age (p = .027, two-sided) and by making payments via digital wallets in 2021 (p = .007, two-sided) and 2020 year (p = .024, two-sided). Also, Monte Carlo exact test showed that there is statistically significant correlation at the 0.05 level of significance between respondents’ information literacy and their work experience (p = .005, two-sided) and who covers their life expenses (p=.019, two-sided). The Monte Carlo test also showed that both of these literacies have statistically significant relationship with financial literacy (p = .000, two-sided), but statistically significant relationship was not found between financial literacy and payments via digital wallets. Concerning the neural network approach, the obtained multilayer perceptron (MLP) neural network model gained overall efficiency of 97.5% in distinguishing students based on their level of financial literacy.
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