Fu Xianping’s research while affiliated with Dalian Maritime University and other places

In recent times, the rapid growth of e-learning has brought about increased concerns regarding cybersecurity risks within digital learning environments. Despite the growing importance of cybersecurity awareness among e-learning students, there is limited research on the factors that influence students' understanding and adherence to cyber safety practices. This study investigates the relationship between e-learning engagement, cybersecurity awareness, and cyber safety practices, with a focus on the moderating roles of gender and e-learning experience. The research emphasizes the need to consider demographic factors such as gender and experience level when designing cybersecurity interventions for online learners. The investigation uses structural equation modeling to analyze how engagement in e-learning platforms influences students' cybersecurity awareness and their adherence to security protocols. Among the key findings from SEM, the study reveals that e-learning engagement positively impacts cybersecurity awareness, with gender and experience level acting as significant moderators. However, the study also found that experienced learners may initially face challenges in applying security protocols effectively, though their understanding improves over time with continued engagement. In addition, the research found that students with higher e-learning engagement are more likely to adopt cyber safety practices and comply with information security policies. Interestingly, the results suggest that educational institutions should tailor cybersecurity programs to address the unique needs of students based on their gender and experience levels. Furthermore, our research can inform future policies and interventions aimed at promoting cybersecurity awareness among e-learning students, ultimately contributing to safer and more secure digital learning environments.

This study aims to investigate the role of digital learning platforms (DLP) as a mediator in the relationship between the social media capability (SMC) and academic performance (AP). It explores the individual impacts of SMC and DLP on academic performance. The study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the reflective and structural models, aiming to find the correlations among various variables. The adoption of the structural model is supported by evidence of convergent, discriminant, and convergent validity among the constructs. The structural model’s findings suggest a positive association between students’ use of social media and both Digital Learning Platforms (DLP) and academic performance. Moreover, it identifies DLP as a mediating factor in these relationships, indicating that students are more likely to leverage and harness the benefits of social media when they have control over digital learning platform resources. Consequently, SMC and DLP collectively contribute to improved academic performance. This study highlights the applicability of Partial Least Squares Structural Equation Modeling in understanding the dynamics of social media and digital learning platforms in the context of enhancing academic performance. The results also emphasize the significance of integrating digital learning platforms into educational institutions. Finally, the study discusses implications and provides practical recommendations based on its findings.

Implementation of Cyber Security Awareness (CSA) can inspire both large and small manufacturing companies to change their internal business processes for improved performance. However, CSA is still relatively novel in developing countries like Kenya. Thus, small and medium-sized manufacturing firms in particular require a proper understanding of CSA. This study focused at how Management Capabilities (MC) affect CSA and Manufacturing Firm Performance (MFP) as well as the mediating role of CSA in the relationship between MC and MFP. A sample of thirty-three manufacturing enterprises participated in the survey, and out of 110 responses that were received, 97 were confirmed to be valid. Moreover, Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for the measurement model to assess the constructs for convergent and discriminant validity. In addition, for the structural model, path coefficients and their corresponding t-values, R2 were used. To obtain cross-validated redundancy measures for each endogenous construct, the study examined predictive relevance (Q2) using the blindfolding procedure. The results indicate that MFP and MC require the mediating support of CSA. The results demonstrate that both MFP and MC necessitate the intermediary support provided by CSA. Furthermore, this research presents empirical evidence highlighting the direct positive impact of cybersecurity awareness on the performance of manufacturing firms. This underscores the critical importance of cultivating a culture of cybersecurity awareness within an organization, elucidating its constructive influence on various dimensions of firm performance.