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Purpose – The purpose of this research is to determine the effect of perceived ease, intensity of behavior, and user satisfaction in using the e-filing system, especially in the city of Lhokseumawe.

Design/Methodology/Approach – Analysis of the data in this study was done using multiple linear regression. The sample collection method used in this study was convenience sampling with a total sample of 96 people.

Findings – The results showed that (Aditya, 2011) perceived ease had a positive significant effect on the use of e-filing (Ajzen, 1980), intensity behavior positive significant effect had a on the use of e-filing (Darussalam, 2007), and user satisfaction had a positive significant effect on the use of e-filing (Davis, 1989).

Research Limitations/Implications – The implication of this research is the effect of user satisfaction against use of e-filing.

Practical Implications – Use of e-filing can simplify the reporting process overall by taxes and easy to use e-filing.

Originality/Value – Perceived ease, intensity behavior, and user satisfaction affect the use of e-filing.

Accompanying the development of economy, multinational enterprises (MNEs), as a role of promoting economic development, may also lead to environmental pollution of host countries. China has become one of the most significant countries in terms of introducing foreign direct investment (FDI), along with which the pollution problem has become serious. Whether the MNEs affect the environment and whether the MNEs in China perform worse than local enterprises attracts more attention. To understand more about it, we creatively build a model of vertical product differentiation, and the result indicates that the environmental performance of MNEs is better than that of local enterprises.

The need to reduce traffic congestion is becoming increasingly important. The means of achieving this aim involves optimising parameters such as traffic signal green-times, road prices and public transport fares. This paper will describe a new bilevel method of optimising traffic signals and prices. The method uses the steepest descent direction together with projections in order to define a descent direction which will reduce the objective function subject to the overriding necessity to be in equilibrium.

The paper will provide a description of the bilevel method together with results on two simple problems. Optimisation is performed on two functions simultaneously; the equilibrium function E (which must have value zero for equilibrium) and the objective function Z which is minimised subject to the constraint that E is zero. For most traffic problems equilibrium is not mathematically well behaved and therefore the method approaches equilibrium in stages, at each stage it minimises Z whilst avoiding the difficult equilibrium region.

The growing implementation of electronic health (e-health) systems has raised the importance of analyzing how these systems have been implemented in diverse regions. By employing a contextual sensitive approach and social mechanism theory, this study aims to better understand the reasons for the success and failure of e-health initiatives in the ex-Yugoslav region and derive useful insights for policymakers.

We employ a narrative review process grounded in the social mechanism theory, extended with field experts’ review, to acquire state-of-the-art information.

Findings indicate that different e-health systems coexist and evolve in different contexts in different countries, with varying levels of success. The contextual differences shape the broader environment, affecting the level of preparedness and capability for e-health implementation. Top-down approaches dominate e-health implementation in most countries when it comes to design process features, and more developed countries do not rely on strong social mechanisms for implementing e-health due to the openness of their culture towards e-health innovations.

Analyzing the milestones, challenges and functionalities of e-health systems in the region of interest can assist policymakers, academics and practitioners in making informed decisions and recommendations to enhance future e-health implementation.

No known studies evaluated e-health initiatives in the former ex-Yugoslav countries holistically and evolutionarily in the form of a comprehensive regional study. Further, our research endeavor is contextually specific since the health systems of these countries in the past were tied together under the federative umbrella health system and then diverged in terms of e-health development.

E-learning has demonstrated its value as a powerful tool for enhancing students' educational experience. This paper uses a quantitative approach to examine the impact of students' cognitive problem-solving skills on their e-learning management ability. In addition, it investigates the parallel mediation role of student psychological motivation and peer collaboration. Moreover, the moderating role of gender was examined to identify the difference in e-learning management ability among male and female students.

Data were collected from 214 Malaysian business students using an online survey. For the analysis, the researcher utilized both SPSS and a SMART PLS software.

The results show that cognitive problem-solving skills directly impact student e-learning management. Moreover, psychological motivation and peer collaboration mediate the relationship between cognitive problem-solving and student e-learning management. The study's results reported that female students' psychological motivation is higher than males in managing their e-learning environment. The study found that an e-learning environment helps students develop cognitive problem-solving skills, and students can manage their e-learning independently.

The COVID-19 pandemic in 2020 worldwide has shifted the educational system from a traditional approach to an online context. There is a lack of studies examining students' cognitive problem-solving skills, their ability to manage e-learning and investigating gender differences. The findings reported here are novel in the context of Malaysia. Little evidence exists about the impact of problem-solving among business students on e-learning management ability while providing insight into gender differences.

This study aims to investigate the mediating effect of concern for information privacy between e-HRM and job stress that eventually develops a turnover intention among employees.

A survey questionnaire was used on working professionals employed in the service and manufacturing sectors. A total of 178 usable responses were collected adopting a convenient snowball sampling technique. PLS-SEM was used to analyze and investigate the hypothesized relationships.

The study found that higher perceptions of e-HRM strength led to less concern for information privacy breaches. Further, concern for information privacy was positively associated with employee job stress and turnover intention. A positive relationship between job stress and turnover intention among employees was also established. Moreover, perceived concern for information privacy fully mediated the relationship between e-HRM and job stress and, eventually, turnover intention among employees.

Organizations should focus on ensuring considerable e-HRM strength while adopting and implementing e-HRM practices; failing may lead to concerns for employee privacy, job stress and eventually turnover intention among employees.

To the best of the authors’ knowledge, the study is among the first few studies to identify perceived concern for information privacy as a consequence of e-HRM reflecting the dark side of e-HRM.

The purpose of this systematic literature review is to catalog, explore and disseminate knowledge developed related to the affordances, constraints and collaborative practices of e-mentoring in order to offer recommendations for mentoring programs.

After identifying studies utilizing inclusion and exclusion criteria and a variety of relevant databases, chosen studies were organized into three categories based on e-mentoring practices.

Results reflect chat-room-based e-mentoring and e-mentoring with a video component both to have various affordances and collaborative features. These forms of e-mentoring can potentially be relevant to new teachers’ needs, may promote community and are disconnected from mentees’ school systems. A third form of e-mentoring, virtual reality e-mentoring, however, has the potential for accessibility issues and lack of relevancy to the mentoring process.

Chat-room-based e-mentoring and e-mentoring with a video component may benefit new teachers who do not have access to in-person mentors. However, these forms of e-mentoring may necessitate a component that ensures mentors and mentees alike remain consistently engaged in the e-mentoring process.

The study examined the relationship between e-learning usage, creativity, e-learning utility and academic performance among undergraduate (UG) and postgraduate (PG) students at Banaras Hindu University (BHU), India.

The data from 480 students were collected using a cross-sectional survey design. Pearson correlation analysis was performed in order to investigate the association between the variables.

The results revealed a significant positive correlation between time of use and academic performance (r = 0.294, p < 0.01). However, there was no significant correlation between time of use and the usability of e-learning in the attainment of learning outcomes. Furthermore, there was a negative correlation between time of use and creativity (r = −0.170, p < 0.01).

The results indicate that educators ought to promote consistent utilization of e-learning platforms to enhance scholarly achievements. However, learners should exercise prudence in their usage, as an over-reliance on these platforms may impede their creativity.

This study contributes to the existing body of knowledge regarding the impacts of e-learning on students' academic performance and creativity. Additionally, it offers instructing professionals and students who make use of e-learning platforms information that might be helpful to them.

An efficient e-waste management system is developed, aided by deep learning techniques. Here, a smart bin system using Internet of things (IoT) sensors is generated. The sensors detect the level of waste in the dustbin. The data collected by the IoT sensor is stored in the blockchain. Here, an adaptive deep Markov random field (ADMRF) method is implemented to determine the weight of the wastes. The performance of the ADMRF is boosted by optimizing its parameters with the help of the improved corona virus herd immunity optimization algorithm (ICVHIOA). Here, the main objective of the developed ADMRF-based waste weight prediction is to minimize the root mean square error (RMSE) and mean absolute error (MAE) rate at the time of testing. If the weight of the bins is more than 80%, then an alert message will be sent to the waste collector directly. Optimal route selection is carried out using the developed ICVHIOA for efficient collection of wastes from the smart bin. Here, the main objectives of the optimal route selection are to reduce the distance and time to minimize the operational cost and the environmental impacts. The collected waste is then considered for recycling. The performance of the implemented IoT and blockchain-based smart dustbin is evaluated by comparing it with other existing smart dustbins for e-waste management.

The developed e-waste management system is used to collect the waste and to avoid certain diseases caused by the dumped waste. Disposal and recycling of the e-waste is necessary to decrease pollution and to manufacture new products from the waste.

The RMSE of the implemented framework was 33.65% better than convolutional neural network (CNN), 27.12% increased than recurrent neural network (RNN), 22.27% advanced than Resnet and 9.99% superior to long short-term memory (LSTM).

The proposed E-waste management system has given an enhanced performance rate in weight prediction and also in optimal route selection when compared with other conventional methods.