Eye-tracking technology has emerged as a valuable tool for evaluating cognitive load in online learning environments. This study investigates the potential of AI-driven consumer behaviour prediction eye-tracking technology to improve the learning experience by monitoring students’ attention and delivering real-time feedback. In our study, we analysed two online lecture videos used in higher education from two institutions: Oxford Business College and Utrecht University. We conducted this analysis to assess cognitive demands in PowerPoint presentations, as this directly affects the effectiveness of knowledge dissemination and the learning process. We utilised a neuromarketing-research consumer behaviour eye-tracking AI prediction software called ‘Predict’, which employs an algorithm constructed on the largest neuroscience database (comprising previous studies conducted on live participants n = 180,000 with EEG and eye-tracking data). The analysis for this study was carried out using the programming language R, followed by a series of t-tests for each video and Pearson’s correlation tests to examine the relationship between ocus and cognitive demand. The findings suggest that AI-powered eye-tracking systems have the potential to transform online learning by providing educators with valuable insights into students’ cognitive processes and enabling them to optimise instructional materials for improved learning outcomes.

Impulsive buying is a growing problem in modern society with significant financial and psychological consequences, and it is necessary to examine the mechanisms underlying it. Understanding the mechanisms driving this behavior is crucial. Impulsive buying consists of two key aspects: a cognitive aspect, characterized by a lack of planning and reflection, and an affective aspect, involving emotional responses that can occur before, during, or after a purchase. This study aims to explore the relationship between personality traits, as measured by the HEXACO model, and tendencies toward impulsive buying. Specifically, it examines how the HEXACO traits differentially predict the cognitive and affective components of impulsive buying tendencies. Data were collected from a sample of 420 students, with 32 excluded due to incomplete responses, resulting in a final sample of 388 students (155 men, 233 women) with an average age of 22.8. Hierarchical regression analyses revealed that HEXACO personality domains significantly predicted overall impulsive buying tendencies. As expected, Honesty–Humility and Conscientiousness were negatively associated with impulsive buying, while Emotionality and Extraversion positively predicted impulsive buying tendencies. Moreover, Honesty–Humility, Conscientiousness, and Extraversion significantly predicted the cognitive component of impulsive buying, while Honesty–Humility and Emotionality were significant predictors of the affective component. These findings suggest the importance of educating individuals, from an early age, on the negative consequences of impulsive buying, effective money-saving strategies, and the principles of mental accounting.

In the realm of digital transformation, effective leadership and motivation are pivotal for organisations navigating the complexities of today’s systems. This study explores the intersection of intrinsic motivation and mental well-being among mature students—an analogy that sheds light on strategies applicable to organisational contexts. In developed nations like the UK, mental health for mature students is increasingly recognised as a crucial component of their educational journey. Mature students, who typically enrol in higher education after an educational gap and upon turning 21, often face specific challenges that can impact their mental well-being while pursuing academic goals. The primary objective of our study was to assess the relationship between intrinsic motivation and the mental well-being of mature students. The study included 248 full-time undergraduate mature students enrolled in private higher education institutions in the UK. These participants were 21 years and older. The research employed two measurement scales: the four-item Intrinsic Motivation Scale, adapted from Jaramillo, and the Warwick–Edinburgh Mental Well-Being Scale. Data collection utilised online Google Forms with multiple choice self-report formatted questions, and our analysis involved both descriptive and inferential statistics. Our research revealed a significant positive correlation between variables of intrinsic motivation and mental well-being. Confirmatory factor analysis (CFA) results confirmed the construct in the model. The results indicated that intrinsic motivation significantly predicts mental well-being among mature students (Cohen’s effect size value, f² = 0.54). Recognising and addressing the unique difficulties individuals encounter and providing appropriate support can enhance their well-being and contribute to the overall success of the higher education community.

This study aims to improve college magazines, making them more engaging and user-friendly. We combined eye-tracking technology with artificial intelligence to accurately predict consumer behaviours and preferences. Our analysis included three college magazines, both online and in PDF format. We evaluated user experience using neuromarketing eye-tracking AI prediction software, trained on a large consumer neuroscience dataset of eye-tracking recordings from 180,000 participants, using Tobii X2 30 equipment, encompassing over 100 billion data points and 15 consumer contexts. An analysis was conducted with R programming v. 2023.06.0+421 and advanced SPSS statistics v. 27, IBM. (ANOVA, Welch’s Two-Sample t-test, and Pearson’s correlation). Our research demonstrated the potential of modern eye-tracking AI technologies in providing insights into various types of attention, including focus, engagement, cognitive demand, and clarity. The scientific accuracy of our findings, at 97–99%, underscores the reliability and robustness of our research, instilling confidence in the audience. This study also emphasizes the potential for future research to explore automated datasets, enhancing reliability and applicability across various fields and inspiring hope for further advancements in the field.

Background: The transformation of business and the economy is a key business problem, and its importance was further heightened during the COVID-19 pandemic, with the increased pressure on enterprises. Hence, the digital readiness of their business will likely determine its future competitiveness in the field. Objectives: The paper addresses the issue of digital readiness for business, with the aim of examining similarities and differences in the digital readiness of European Union countries. The main focus is on identifying the changes during the first two years of the pandemic. Methods/Approach: We conducted a factor analysis and hierarchical cluster analysis based on selected indicators. The results revealed some significant differences. Results: While the countries that lead in digital readiness remained the same, there were relatively large differences in the classification of other EU countries. Some countries, such as Latvia or Slovenia, significantly improved in many aspects of digital readiness during the pandemic. On the other hand, Bulgaria and Romania are still included in the same cluster, representing an overall low digital readiness. Conclusion: Enterprises in more developed countries also have a higher level of digital readiness. Although COVID-19 had a positive impact on digital readiness in some less developed countries, the impact is only partial, indicating a need for stronger actions to bridge the digital divide at the EU level. These findings provide a hopeful outlook, suggesting that with the right actions, the digital divide in the EU can be effectively bridged.

This research investigates the impact of applying neuromarketing techniques to three practical examples of higher education (HE) branding: an official college website page, an official college Facebook page, and recorded online video lectures used for teaching at HE institutions. The study was conducted in three different HE institutions with a representative sample of 720 participants, with n = 529 used for testing the CARE college website, n = 59 for testing the HAZEF Facebook page, and n = 132 for testing the emotional response of students studying online. To assess the participants’ emotional responses, this study utilized automated facial coding through a webcam (15 Hz) and considered mood intensities. Additionally, a sentiment analysis was employed to verify the survey results and determine any discrepancies in the cognitive response. By analyzing gaze activity, movement patterns, and emotional responses, valuable insights were gained into students’ behaviors and preferences. This study recommends incorporating neuromarketing research into HE branding and online teaching to enhance students’ learning experiences. Overall, this study contributes to the understanding of human expectations and behaviors in response to online teaching and provides valuable insights for HE institutions in Europe.