Purpose: The level of the environment is gradually declining, especially with regard to the serious problem of solid waste. Solid waste segregation-at-source is seen as the most essential approach to helping the natural environment minimize the amount of waste generated before being transferred to waste disposal sites and landfills in many rapidly growing towns and cities in developing countries. However, a number of previous environmental-based research have focused only on the general scope of recycling, sustainable development, and the purchase intention for sustainable food products. This situation has led to useful and relevant information on the research scope of households’ intention to segregate solid waste at source, which remains largely unanswered. The aim of this paper is, therefore, to provide a literature review to develop a novel theoretical framework in understanding the determinants of households’ intention to practise solid waste segregation-at-source. Theoretical framework: The study provides a detailed explanation of the application of the Theory of Reasoned Action, the Fietkau-Kessel Model, the Focus Theory of Normative Conduct, and the Value-Basis Theory to predict the relationship between attitude, subjective norms, environmental concerns, and environmental knowledge of households on intention to practise solid waste segregation-at-source. Design/methodology/approach: This research is descriptive in nature. Findings: A better understanding of the potential mediator and moderator is needed to contribute to the body of knowledge on the causal relationship between the studied variables. In conclusion, the researchers discuss how the framework can be used to address future research implications as more evidence emerges. Research, practical and social implications: The current study is expected to broaden previous research in order to improve general understanding of attitudes and subjective norms towards the specific research scope of solid waste segregation-at-source.

This research attempts to investigate the effect of audit quality on firm value in the high corporate governance context. In addition, this study seeks to examine the role of institutional shareholders as a moderating variable on the relationship between audit quality and firm value. Dataset includes the 95 (out of 575) Thai listed companies which fully and completely implement the Corporate Governance Code (CG Code) voluntary disclosure recommended by OECD (Organisation for Economic Co-operation and Development) in 2021. Multiple linear regression and Hayes’s regression-based analysis are done using market capitalization as the dependent variable. The research results illustrate that audit quality relates to firm value in a negative way, while profitability and institutional shareholders relate to firm value in a positive manner. Moreover, the interaction effect between audit quality and institutional shareholders wields a significant negative impact on the association between audit quality and firm value, which indicates that the negative effect of audit quality on firm value is stronger when more firm shares are owned by institutional shareholders. The results of this study would potentially be very useful to managers, financial advisors, and policymakers to observe the nature and vagaries of audit quality in high corporate governance environment, especially when institutional shareholders hold a significant proportion of firm shares. The study offers practical suggestions and recommendations for audit quality and institutional shareholders, which are essential for overall operating efficiency and firm value. The outcomes can help improve corporate governance practices, which in turn enhance the share price and profits.

Recently, Agile project management has received significant academic and industry attention from due to its advantages, such as decreased costs and time, increased effectiveness, and adaptiveness towards challenging business environments. This study primarily aims to investigate the relationship between the success factors and Agile project management methodology adoption and examine the moderating effect of perceived compatibility. The technology-organization-environment (TOE) framework and technology acceptance theories (UTAUT, IDT, and TAM) were applied as the theoretical foundation of the current study. A survey questionnaire method was employed to achieve the study objectives, while quantitative primary data were gathered using a carefully designed methodological approach focusing on Omani oil and gas industry. The PLS-SEM technique and SmartPLS software were used for hypotheses testing and data analysis. Resultantly, readiness, technology utilization, organizational factors, and perceived compatibility were the significant factors that promoted Agile methodology adoption in the oil and gas industry. Perceived compatibility moderated the relationship between success factors and Agile methodology. The findings suggested that people, technology, and organizational factors facilitate the Agile methodology under the technology acceptance theories and frameworks. Relevant stakeholders should adopt the study outcomes to improve Agile methodology adoption.

Indonesia ranks as the second-largest source of plastic garbage in marine areas, behind China. This is a critical problem that emphasises the need for synergistic endeavors to safeguard the long-term viability of marine ecosystems. The objective of this work is to examine the implementation of the Penta Helix model in the management of marine plastic trash. For this purpose, a Systematic Literature Review (SLR) was carried out, utilizing scholarly papers sourced from the Science Direct, Scopus, and Web of Science databases. The analysis centred on evaluating the Penta Helix model as a cooperative framework for tackling plastic waste management in the marine environments of Indonesia and China. The results suggest that the Penta Helix methodology successfully enables the amalgamation of many interests and resources, making a valuable contribution to the mitigation of plastic pollution in the waters of both nations. In order to advance a more comprehensive and sustainable approach to plastic waste management, this multidisciplinary plan brings together stakeholders from government, academia, business, civil society, and the media. Under this framework, the government is responsible for formulating laws, guidelines, and programs to decrease the use of disposable plastics and improve waste management infrastructure, all while guaranteeing adherence to environmental constraints. Simultaneously, the industrial and academic sectors are responsible for creating sustainable technology and pioneering business strategies, while civil society, in collaboration with the media, has a crucial role in increasing public consciousness regarding the destructive effects of plastic trash. This comprehensive strategy emphasizes the need of synergistic endeavors in tackling the intricate issues of marine plastic contamination.

This study is aimed at exploring the degree of association between workforce diversity dimensions and the academic performance of four universities in Ethiopia. The diversity management attributes were diversity, climate, values, and organizational justice; identity, schemas, and communication adapted to the contexts of higher education institutions. The universities were selected purposively, and stratified and systematic sampling techniques were further used to identify respondents. Quantitative and qualitative data were collected to achieve the purpose of the study. Correlation and regression analyses were used to analyze the data. Results from correlation analysis revealed that there are statistically significant positive relations between the dimensions of workforce diversity and academic performance. This implies that the organizational performance of higher education institutions can be significantly influenced by existing diversity. The freedom to express one’s own identity in the university workforce landscape was also observed to be limited in the universities studied, and this has to be improved. A democratic work environment is critical for the productivity of the staff, and an effort has to be geared towards the goal of creating such an environment. The regression analysis indicated that diversity, climate, organizational justice, identity, schema, and communication have statistically significant effects on the academic performance of higher educational institutions in Ethiopia. Finally, academic leaders are advised to apply the transformational leadership style, as it moderates the relationship between diversity management and academic performance.

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.