For displaced people, migrating into Europe has highly complex information needs about the journey and destination. Each new need presents problems of where to seek information, how to trust or distrust information, and financial and other costs. The outcomes of receiving poor or false information can cause bodily harm or death, loss of family, or financial ruin. We aim to make two major contributions: First, provide rich insights into digital literacy, information needs, and strategies among Syrian and Iraqi refugees who entered Europe in 2015, a topic rarely dealt with in the literature. Second, we seek to change the dominant perspective on migrants and refugees as passive victims of international events and policies by showing their capacities and skills to navigate the complex landscape of information and border regimes en route to Europe. Building on research at Za’atari refugee camp (Jordan), we surveyed 83 Arab refugees in two centers in Berlin. Analyses address refugees’ temporal information worlds, focusing on the importance and difficulty in finding specific information, how migrants identify mis- and disinformation, and the roles of information and technology mediaries. Findings illustrate the digital capacities refugees employ during and after their journey to Europe; they show social support via social media and highlight the need for a radical shift in thinking about and researching migration in the digital age.

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This work aims to examine the impact of green training on green environmental performance through the mediating role of green competencies and motivation on the adoption of green human resource management. The convenience sampling technique was employed to collect data through an online survey undertaken at public and private universities in Malaysia. The analyses were conducted using the Statistical Package for the Social Sciences (SPSS) v.25 and Smart PLS v.3 software, with the aim of testing the predefined hypotheses. It was revealed that green training has a significant impact on green environmental performance, and all six dimensions of green competencies, namely, skills, abilities, knowledge, behavior, attitude and awareness, were also green motivations. Both green competencies and motivations positively and significantly mediated the relationship between green training and environmental performance.

Smart city is synchronized with digital environment and its transportation system is vitalized with RFID sensors, Internet of Things (IoT) and Artificial Intelligence. However, without user's behavioral assessment of technology, the ultimate usefulness of smart mobility cannot be achieved. This paper aims to formulate the research framework for prediction of antecedents of smart mobility by using SEM-Neural hybrid approach towards preliminary data analysis. This research undertook smart mobility service adoption in Malaysia as study perspective and applied the Technology Acceptance Model (TAM) as theoretical basis. An extended TAM model was hypothesized with five external factors (digital dexterity, IoT service quality, intrusiveness concerns, social electronic word of mouth and subjective norm). The data was collected through a pilot survey in Klang Valley, Malaysia. Then responses were analyzed for reliability, validity and accuracy of model. Finally, the causal relationship was explained by Structural Equation Modeling (SEM) and Artificial Neural Networking (ANN). The paper will share better understanding of road technology acceptance to all stakeholders to refine, revise and update their policies. The proposed framework will suggest a broader approach to investigate individual-level technology acceptance.