Problem statement: An environmentally conscious consumer’s perspective can shift as they look for things that are gentler on the planet. Conversely, businesses engage in greenwashing when they try to cover up their lacklustre environmental initiatives. The current research was used the theory of rational choice behaviour to examine a model that connects corporate green washing and consumers’ green purchase intentions via the mediating roles of perceived risk, green trust and green confusion about food and beverage brands in Saudi Arabia. Research motivation: Sustainable business practices have been developed and adopted by corporations in response to the growing interest in environmentally friendly lifestyles and green products. However, green washing has become increasingly common as a means for businesses to give off the impression that they care about the environment when they really don’t. Research methodology: The online survey was used to obtain data directly from consumers about their views on green washing by corporations. Primary data was analysed using appropriate statistical tools and techniques in SPSS, AMOS and SmartPLS software, such as Correlation, Regression, Structural Equation Modelling (SEM), etc. Results: In terms of perceived greenness and confusion, the results showed that green wash mediates the relationship between green purchasing intention and greenness. There is a two-way correlation between consumers’ intentions to buy environmentally friendly products and their levels of green perception, and green confusion. The findings of this study were broadening our understanding of the consequences of green washing. Conclusions: All things considered, the study was encouraging more research on the subject and be a useful tool for academics, corporate managers, and students interested in environmental sustainability, product innovation, and green branding. According to the results, businesses can improve their green purchasing intentions by cutting down on green washing and focusing instead on building a positive reputation for their brand and encouraging customer loyalty. Corporate performance and social environment sustainability can both benefit greatly from this paper’s expansion of knowledge regarding the processes of individual customer psychological effects after perceptions of corporate greenwashing behaviour.

Graphene oxide can be referred to as oxidized graphene. Similar to graphene, oxidized graphene possesses remarkable structural features, advantageous properties, and technical applications. Among polymeric matrices, conducting polymers have been categorized for p conjugated backbone and semiconducting features. In this context, doping, or nano-additive inclusion, has been found to enhance the electrical conduction features of conjugated polymers. Like other carbon nanostructures (fullerene, carbon nanotube, etc.), graphene has been used to reinforce the conjugated matrices. Graphene can be further modified into several derived forms, including graphene oxide, reduced graphene oxide, and functionalized graphene. Among these, graphene oxide has been identified as an important graphene derivative and nanofiller for conducting matrices. This overview covers essential aspects and progressions in the sector of conjugated polymers and graphene oxide derived nanomaterials. Since the importance of graphene oxide derived nanocomposites, this overview has been developed aiming at conductive polymer/graphene oxide nanocomposites. The novelty of this article relies on the originality and design of the outline, the review framework, and recent literature gathering compared with previous literature reviews. To the best of our knowledge, such an all-inclusive overview of conducting polymer/graphene oxide focusing on fundamentals and essential technical developments has not been seen in the literature before. Due to advantageous structural, morphological, conducting, and other specific properties, conductive polymer/graphene oxide nanomaterials have been applied for a range of technical applications such as supercapacitors, photovoltaics, corrosion resistance, etc. Future research on these high-performance nanocomposites may overcome the design and performance-related challenges facing industrial utilization.

In the rapidly expanding Chinese high-tech industry, high employee turnover poses a significant challenge. This study employs a mixed-methods approach to explore the association between transformational leadership and turnover intentions, utilizing both survey responses and detailed interviews. Findings from this investigation demonstrate a strong negative correlation between transformational leadership and turnover intentions. Increased job satisfaction and organizational commitment, crucial factors for employee retention, mediate this relationship. The study underscores the strategic significance for high-tech enterprises in China to nurture transformational leadership as a means to mitigate turnover, thereby fostering a more engaged and dedicated workforce, and sustaining a competitive advantage in this dynamic industry.

This work presents a review of Mexican Higher Education during the decade of education for sustainable development and how today it faces the commitments made for the Sustainable Development Agenda 2030. By portraying the agreements that support the UN’s Development Program in advising higher education institutions, the SDGs which can be served through universities and their by-products, the success stories of some universities are shown. This case study addresses the theoretical value of quality of life and harmony of the environment, remarking on how different universities in Mexico have approached this matter as a key part of their curricula, policy, and research. Showcasing a special emphasis given to the work carried out by the University of Sonora, specifically for their institutional practices for sustainability and the study of sustainability from the perspective of Environmental Psychology.

Brain tumors are a primary factor causing cancer-related deaths globally, and their classification remains a significant research challenge due to the variability in tumor intensity, size, and shape, as well as the similar appearances of different tumor types. Accurate differentiation is further complicated by these factors, making diagnosis difficult even with advanced imaging techniques such as magnetic resonance imaging (MRI). Recent techniques in artificial intelligence (AI), in particular deep learning (DL), have improved the speed and accuracy of medical image analysis, but they still face challenges like overfitting and the need for large annotated datasets. This study addresses these challenges by presenting two approaches for brain tumor classification using MRI images. The first approach involves fine-tuning transfer learning cutting-edge models, including SEResNet, ConvNeXtBase, and ResNet101V2, with global average pooling 2D and dropout layers to minimize overfitting and reduce the need for extensive preprocessing. The second approach leverages the Vision Transformer (ViT), optimized with the AdamW optimizer and extensive data augmentation. Experiments on the BT-Large-4C dataset demonstrate that SEResNet achieves the highest accuracy of 97.96%, surpassing ViT’s 95.4%. These results suggest that fine-tuning and transfer learning models are more effective at addressing the challenges of overfitting and dataset limitations, ultimately outperforming the Vision Transformer and existing state-of-the-art techniques in brain tumor classification.

Electoral contestation in recent Indonesian election periods is faced with the challenge of polarization linked to identity politics, where initially assigned identity is leveraged as tools for political competition. This is a qualitative research, using interviews, observations, and direct group discussion methods to collect data from five different regions in Indonesia. The research focused on the presence of governing regulations and how they develop in complex dynamics. The results showed that identity politics was prevalent in all regions due to mobilization through identity manipulation to gain electoral political advantage. Furthermore, electoral characteristics showed a growing tendency toward polarization, primarily in terms of religion and ethnicity, with some issues related to regionalism, gender, religious affiliations, and family history networks. It was also found that weak regulations on identity manipulation led to increasing permissiveness among political actors, the state, and voters. This made identity issues become natural electoral problems, despite weakening the developing democracy in Indonesia. In this context, future contests in Indonesia are expected to consistently intensify identity politics, with the lack of regulations, permissiveness, and social media serving as the main driving factors.