The 4th Wave Evolution of Digital Citizenship Concept? Proposing Digital Citizenship Concept for Malaysia Context

Online world demands new sets of characteristics to warrant the ability to cope with its constantly evolving challenges and risks. Digital citizenship, a concept introduced, focusing on new ways of learning and exploring in an online environment safely, securely, and appropriately. The evolution of digital citizenship could be seen along with the changes in technology used in education, and requires students to engage with technology longer hours than before. Thus, how can we approach the challenge of using technology actively and immersively, while maintaining sanity and wellness, and building resilience to potential online risk? Thus, this conceptual paper proposes a new concept of digital citizenship by bridging the notions of wellness and resilience from the psychology discipline into digital citizenship, for its feasibility in the Malaysian educational context. This paper argues the necessity and potential integration of the spiritual element that is lacking in the existing digital citizenship concept, which has proven its significance in enhancing wellness and resilience of adolescent in the literature. It is hoped this fourth wave of proposed digital citizenship concept would bring fruitful discussion and contribute to a better understanding of how one might better socialize online or participate with others in a positive and meaningful way. Thus, only then, digital resilience and digital wellness will be established and a better future online society will be formed.

How does Online Engagement Drive Consumers’ Webrooming Intention?

Based on the cognitive-motivational-relational (CMR) theory, this study empirically investigates the mechanisms through which consumers' online engagement impacts their channel switching intention. The present study examines the mediating effects of perceived value and the ways in which these mediating effects are moderated by online risk perception. Data were collected from 428 online Indian consumers using systematic random sampling. The results of the structural and process macro analyses indicated that consumer online engagement has a significant impact on consumer online search benefits which in turn leads to webrooming intention. Also, perceived value mediated the effects of online search benefits and offline purchase benefits on webrooming intention. The results advance the theory of CMR by explaining consumer channel switching behaviour and are expected to help multi-channel retailers to identify the key drivers that help engage consumers online.

Empirical investigation of factors affecting online shopping behavior

This study aims to examine advertising, online risk, perceived usefulness, and reliability as factors affecting online shopping behavior among subscribers of online stores in Nigeria. This research adopted a quantitative approach in which a self-administered questionnaire was used to collect data. The respondents consist of 375 subscribers of online stores who had prior online shopping experiences from an online store based in Nigeria. The study used Smart-PLS for data analysis. The findings revealed that advertising and perceived usefulness have a significant positive effect on online shopping behavior. On the other hand, online risk has a negative effect on online shopping behavior. Additionally, there is a positive relationship between reliability and online shopping behavior. This research could be a valuable guideline for online firms to make informed decisions on how to increase online sales. Additionally, this research could advance online shoppers’ knowledge, particularly Nigerians, regarding online shopping.

The Role of Self-Esteem and Perceived Parental Mediation in Cyberbullying

When access to information on the internet is expected to support the growth to adulthood, cyberbullying is instead becoming a threat to adolescents' psychological well-being. Parental mediation and self-esteem are considered as protective factors to youngsters from online risk. The present study examines whether self-esteem mediates the relationship between perceived parental mediation and cyberbullying. The study participants were 351 senior high school social students in Yogyakarta who are media and internet users. The data were collected using the Cyberbullying Scale (Cronbach’ α = 0.784), Self-Esteem Scale (Cronbach’ α = 0.766), and Perceived Parental Mediation Scale (Cronbach’ α = 0.656). Analysis using Structural Equation Modeling (SEM) showed that the proposed model was reached the goodness-of-fit ( = 53.711; df = 18; p = 0.001; RMSEA = 0.075; GFI= 0.964; CFI= 0.923). This study concluded that self-esteem partially mediated parental mediation and cyberbullying, with an indirect effect = -0.047 (p = 0.024; p<0.05). Self-esteem as the cognitive-personality factor and optimal parental mediation as environmental factors were considered to prevent adolescent cyberbullying. Therefore, we would recommend practitioners of educational, social, and clinical psychology to take the opportunity to involve self-esteem and parental mediation factors in intervention program design.

Online Risk-Averse Submodular Maximization

We present a polynomial-time online algorithm for maximizing the conditional value at risk (CVaR) of a monotone stochastic submodular function. Given T i.i.d. samples from an underlying distribution arriving online, our algorithm produces a sequence of solutions that converges to a (1−1/e)-approximate solution with a convergence rate of O(T −1/4 ) for monotone continuous DR-submodular functions. Compared with previous offline algorithms, which require Ω(T) space, our online algorithm only requires O( √ T) space. We extend our on- line algorithm to portfolio optimization for mono- tone submodular set functions under a matroid constraint. Experiments conducted on real-world datasets demonstrate that our algorithm can rapidly achieve CVaRs that are comparable to those obtained by existing offline algorithms.

Uncertainty Evaluation of Object Detection Algorithms for Autonomous Vehicles

The safety of the intended functionality (SOTIF) has become one of the hottest topics in the field of autonomous driving. However, no testing and evaluating system for SOTIF performance has been proposed yet. Therefore, this paper proposes a framework based on the advanced You Only Look Once (YOLO) algorithm and the mean Average Precision (mAP) method to evaluate the object detection performance of the camera under SOTIF-related scenarios. First, a dataset is established, which contains road images with extreme weather and adverse lighting conditions. Second, the Monte Carlo dropout (MCD) method is used to analyze the uncertainty of the algorithm and draw the uncertainty region of the predicted bounding box. Then, the confidence of the algorithm is calibrated based on uncertainty results so that the average confidence after calibration can better reflect the real accuracy. The uncertainty results and the calibrated confidence are proposed to be used for online risk identification. Finally, the confusion matrix is extended according to the several possible mistakes that the object detection algorithm may make, and then the mAP is calculated as an index for offline evaluation and comparison. This paper offers suggestions to apply the MCD method to complex object detection algorithms and to find the relationship between the uncertainty and the confidence of the algorithm. The experimental results verified by specific SOTIF scenarios proof the feasibility and effectiveness of the proposed uncertainty acquisition approach for object detection algorithm, which provides potential practical implementation chance to address perceptual related SOTIF risk for autonomous vehicles.