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Despite efforts to reduce environmental pollution and wasteful fossil fuel use, electric vehicles (EVs) are still rare on the road. Why is it so challenging to get widespread EV adoption? One significant factor on which it heavily depends is one's awareness and understanding of EVs. However, due to an absolute lack of knowledge on the part of the populace, this factor becomes a huge impediment to the uptake of EVs. A systematic review of the electronic database Scopus for the years 2003–2022 was carried out on ‘EV awareness and adoption of EV’ while considering the ‘Preferred Reporting Items for Systematic Reviews and Meta-analysis’ (PRISMA) standards. A three-step identification process resulted in the ultimate detection of 41 papers, which were then thoroughly examined. A conceptual framework that encompasses the three key awareness aspects that influence EV adoption is developed. To encourage greater uniformity among EV researchers, this study's conclusions serve as a foundation for operationalising upcoming research efforts within a predetermined framework. The authors must therefore be optimistic that lingering technological, legislative, cultural, behavioural and business-model barriers may be overcome over time through widespread dissemination of knowledge and awareness related to EVs, making it possible for everyone to switch to greener, more economical and more efficient transportation solutions.

The present study intends to study the role of green transformational leadership in promoting green employee behaviour via green employee creativity. The study will draw its foundation from resource-based view and social exchange theory, thereby providing theoretical underpinning to explore the relationship between leadership, creativity and green behaviour.

A survey questionnaire was prepared to collect data to examine the relationship among the variables. Responses of 82 human resource (HR) managers and 488 employees of Indian Information Technology/Information Technology Enabled Services (IT/ITES) firms were used for the study. A 2-1-1 multi-level structural equation modelling (ML-SEM) was performed using Mplus version 8.6 software.

The study reveals significant and positive association for first three hypotheses, i.e. the direct relationship between green transformational leadership, green employee creativity and green employee behaviour. However, the fourth hypothesis is partially supported. Green employee creativity partially mediates the direct relationship between green transformational leadership and green employee behaviour.

By examining how green transformational leadership influences green employee behaviour through the interaction of creativity, the research offers a novel contribution to the field of sustainable organizational practices, enhancing the understanding of leadership, creativity and environmental commitment. The present research addresses pressing societal issues, contributes to more environmentally responsible practices and enhances the understanding of leadership and creativity in today's socially conscious world. Such a holistic examination of these interconnected factors can lead to actionable strategies for organizations to navigate the challenges of environmental responsibility in a rapidly changing world.

Spam emails classification using data mining and machine learning approaches has enticed the researchers' attention duo to its obvious positive impact in protecting internet users. Several features can be used for creating data mining and machine learning based spam classification models. Yet, spammers know that the longer they will use the same set of features for tricking email users the more probably the anti-spam parties might develop tools for combating this kind of annoying email messages. Spammers, so, adapt by continuously reforming the group of features utilized for composing spam emails. For that reason, even though traditional classification methods possess sound classification results, they were ineffective for lifelong classification of spam emails duo to the fact that they might be prone to the so-called “Concept Drift”. In the current study, an enhanced model is proposed for ensuring lifelong spam classification model. For the evaluation purposes, the overall performance of the suggested model is contrasted against various other stream mining classification techniques. The results proved the success of the suggested model as a lifelong spam emails classification method.