This paper aims to understand the local authorities’ reaction to green environment activities towards clean cities in Malaysia and how they respond to cleanliness awareness among the community. Four (4) cities, such as Melaka, Ipoh, and Muar dan Kuala Terengganu, were selected, and this study embarks on a qualitative research approach involving a semi-structured interview with top personnel from four local authorities. From the reaction point of view, some local authorities reacted positively towards the green environment and cleanliness of the city. Four (4) themes have been produced, such as awareness, which focuses on the daily routine of local authorities. Secondly, enforcement from the local government, with some warning and advice, really contributes to the changes in society’s attitude. Thirdly, support by local authority efforts, including awareness campaigns from electronic and printed media, does have a good impact. Lastly, active involvement from the local authorities regulated many communities in residential areas and had direct links with local communities and NGOs that annually organized green program activities. This study urged the Local Government Act 1976, which the local authorities are responsible for the enforcement activities such as the 3Rs (Reduce, Reuse, Recycle) activities and so on. Local authorities, state governments, and local communities should also help monitor and maintain environmental issues towards a clean city in Malaysia.

The article examines the modern vectors of implementation of measures to achieve results in the field of Sustainable Development Goals (SDGs), both at the level of national priorities and at the level of Central Asian countries. The purpose of this study is a multidimensional analysis of actions that make it possible to develop solutions to stabilize the environmental situation in Central Asian countries based on global international trends. The scientific novelty of the research lies in the integrated use of thematic modeling methods, as well as sociological surveys used to improve the efficiency of business processes in the field of environmental protection. The methodological basis for conducting a comparative assessment of the impact of environmental policy instruments used on regional development is the concept of sustainable development. In conclusion, conclusions are drawn about the need to develop effective mechanisms for the implementation of environmental policy in the studied countries.

In recent years, an ‘international’ unanimity has been reached as to the importance of collective collaboration to avoid the negative effects of climate change. This requires rethinking the old or traditional development model based on economic growth as the exclusive indicator of wealth. Thus, humanity has an urgent need to adopt a new, more humane and fairer economic model that constitutes an alternative to the models of exponential growth that have dominated in the last two centuries. To do so, humanity is looking to the Degrowth model as a potential concept that aims to reduce wealth from pollutants, seeks more justice (as equity), and the improvement of the capabilities of those who are poor and disadvantaged (in the sense of Amartya Sen and Martha Nussbaum). The purpose of this article is to question this model and whether it actually does improve environmental quality. Additionally, if the response is positive, another question arises: How to finance degrowth especially when we seek other less polluting energy sources whose costs seem to be very high?

Purpose: This study investigates the mediating effect of Environmental Attachment (EA) among consumers in an emerging market, concentrating on the impact of two key factors: Green Environmental Awareness (GEA) and Sense of Responsibility (SOR) on Sustainable Product Consumption (SPC). Design/methodology/approach: A thorough online survey was carried out with Google Docs and distributed to 304 Pakistani consumers who now use or are considering purchasing sustainable or green products. Structural Equation Modeling (SEM) was used to rigorously test the suggested model utilizing a non-probability sampling technique, specifically the stratified purposive sampling approach. Findings: Green environmental awareness (GEA) and a sense of responsibility (SOR) have been shown to have a substantial impact on creating environmental attachment (EA) in both existing and potential customers of sustainable products. The findings of this study also revealed that environmental attachment (EA) plays an important role as a mediator in the links between green environmental awareness (GEA) and the consumption of sustainable goods (SPC), as well as between a sense of responsibility (SOR) and SPC. Despite this, it is crucial to note that the projected direct effect of GEA on SPC was shown to be statistically insignificant. This conclusion implies that additional factors outside the scope of this study may influence the relationship between GEA and SPC. Research limitations/implications: It is vital to highlight that the focus of this study is on an online sample of consumers near Punjab, Pakistan. Future studies should look at other parts of Pakistan to acquire a more complete picture of sustainable consumption trends. Furthermore, our findings suggest that characteristics impacting sustainable consumption, such as Green Environmental Awareness (GEA) and Sense of Responsibility (SOR), may differ among countries. As a result, performing a comparison analysis involving two or more countries could provide valuable insights into projecting sustainable product consumption among current and potential sustainable product customers. Originality/Value: This study contributes to the literature by investigating the factors of sustainable consumption using the lens of the Norm Activation Model theory (NAM), notably Green Environmental Awareness (GEA) and Sense of Responsibility (SOR), to predict sustainable product consumption. The findings are important for promoting long-term goals in Pakistan and provide a framework that can be applied in other emerging markets.

This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.