Constructed wetlands have emerged as a sustainable alternative for decentralized wastewater treatment in developing countries which face challenges with urbanization and deteriorating infrastructure. This paper discusses the key factors affecting the implementation of constructed wetlands in developing countries. A case study research design was adopted, which focused on Bulawayo, Zimbabwe. A mixed-method approach was adopted for the study. Spatial analysis was conducted to identify potential sites for constructed wetlands in the city of Bulawayo. Semi structured interviews were conducted, with relevant stakeholders, such as town planners, civil engineers, NGO representatives, community leaders, and quantity surveyors. The findings reveal that political reforms, public acceptance, land availability, and funding are crucial for the successful implementation of constructed wetlands. Additionally, four sites were identified as the most favorable preliminary locations for these systems. The paper captures all the key factors relevant to the implementation of constructed wetlands (CWs) with a closer look at policy and the role it plays in the adoption of decentralized wastewater treatment systems. Formulating policy around the decentralized sanitation systems was considered imperative to the success of the systems whether in implementation or in operation. The paper adds to knowledge in the subject of sustainable wastewater treatment alternatives for developing countries. However, further research can be conducted with a different methodology to ascertain the applicability of the systems in developing urban cities considering other important aspects in the implementation of wastewater treatment systems.

Purpose—In the business sector, reliable and timely data are crucial for business management to formulate a company’s strategy and enhance supply chain efficiency. The main goal of this study is to examine how strong brand strength affects shareholder value with a new Supplier Relationship Management System (SRMS) and to find the specific system qualities that are linked to SRMS adoption. This leads to higher brand strength and stronger shareholder value. Design/Methodology/Approach—This study employed a cross-sectional design with an explanatory survey as a deductive technique to form hypotheses. The primary method of data collection used a drop-off questionnaire that was self-administered to the UAE-based healthcare suppliers. Of the 787 questionnaires sent to the healthcare suppliers, 602 were usable, yielding a response rate of 76.5%. To analyze the data gathered, the study used Partial Least Squares Structural Equation modelling (PLS-SEM) and artificial neural network (ANN) techniques. Findings—The study’s data proved that SRMS adoption and brand strength positively affected and improved healthcare suppliers’ shareholder value. Additionally, it demonstrates that user satisfaction is the most significant predictor of SRMS adoption, while the results show that the mediating role of brand strength is the most significant predictor of shareholder value. The results demonstrated that internally derived constructs were better explained by the ANN technique than by the PLS-SEM approach. Originality/Value—This study demonstrates its practical value by offering decision-makers in the healthcare supplier industry a reference on what to avoid and what elements to take into account when creating plans and implementing strategies and policies.

The UN agenda of Sustainable Development Goals (SDGs) 2015–2030 is a holistic approach. Universities play an important role in dissemination of quality knowledge, developing the skills and attitudes of a large number of youth across the world. Though the emphasis on Education for Sustainable Development (ESD) started as early as 1992, yet Universities adopted the concept of Green Campus integrating the environmental, social and economic aspects of sustainability quite recently. In developing countries including Pakistan, the Green Campus Initiatives (GCI) have not been implemented in the majority of the Universities. Northern Pakistan comprising Azad Jammu & Kashmir (AJ&K) and Gilgit Baltistan (GB) faces multiple challenges including Climate Impacts at the top. The fragile ecosystem of the region requires more sustainable initiatives at the University and community levels. In this research, the readiness of the seven universities located in Northern Pakistan have been assessed for GCI on the basis scanning of the websites and questionnaire survey of the relevant stakeholders. The results have shown that there is little commitment of resources for sustainability from senior management, lack of awareness in faculty & staff and less research focus on the related themes of green campus. The co-curricular activities in universities are not linked with sustainability and there are no incentives for faculty, staff and students to this end. It has been recommended that Green Campus Framework may be developed for Pakistani Mountain Universities, with commitment from leaders of the universities and allocation of sufficient resources for development of sustainable campuses. The Higher Education Commission of Pakistan (HEC) needs to allocate special funds for promoting GCI across universities in Pakistan.

This study investigates the impact of the metaverse on English language teaching, focusing on the perspectives of students from the University of Boyacá. The use of the metaverse was compared with the Moodle platform in a virtual educational environment. A mixed-method approach combining quantitative and qualitative methods was employed. The sample consisted of 30 university students enrolled in English courses, randomly assigned to two groups: one using the metaverse and the other using Moodle. Students’ grades on different activities and assessments throughout the course were collected, and semi-structured interviews were conducted to explore students’ perceptions of the educational platforms. Results revealed that while students recognize the potential of the metaverse to enhance interactivity and learning experience, they also identified technical and accessibility challenges. Although no significant differences in grades were found between the groups, less variability in grades was observed in the metaverse group. The mixed design allowed for a more comprehensive understanding of the impact of the metaverse on English language teaching, while providing a variety of student perspectives on their experience with educational technology. This research contributes to understanding the role of the metaverse in English language teaching and highlights key areas for future research and developments in the field of virtual education.

Border areas can play a crucial role in market integration and infrastructure development between Central Asian countries, thus creating favorable economic growth and regional cooperation conditions. This study aims to assess the economic impact of border areas between Kazakhstan and Uzbekistan, focusing on their role in enhancing market integration and infrastructure development to foster regional growth and cooperation.  Focusing on labor and capital as essential production drivers, this study employs a sophisticated panel data regression model to explore the Cobb-Douglas production function’s application in these border territories. The research findings indicate that regions’ elasticity towards capital and labor inputs vary, necessitating differentiated economic strategies. For capital-intensive areas, we recommend prioritizing investments in infrastructure and technology to boost production outputs. Conversely, in regions where labor significantly influences production, the emphasis should be on human capital development through education, training, and improved labor market conditions. The study’s insights into the evolving trade relations between the two countries underscore the need for flexible economic policies to enhance regional integration and cooperation. This research not only fills a crucial knowledge gap but also offers a blueprint for leveraging the diverse economic landscapes of Central Asia’s border areas in future policy-making and regional economic strategy.

This study uses a Time-Varying Parameter Stochastic Volatility Vector Autoregression (TVP-SV-VAR) model to conduct an empirical analysis of the dynamic effects of China’s stock market volatility on the agricultural loan market and its channels. The results show that the relationship between stock market and agricultural loan market volatility is time varying and is always positive. The investor sentiment is a major conduit through which the effect takes place. This time-varying effect and transmission mechanism are most apparent between 2011 and 2017 and have since waned and stabilized. These have significant implications for the stable and orderly development of the agricultural loan market, highlighting the importance of the sound financial market system and timely policy, better market monitoring and early warning system and the formation of a mature and sound agricultural credit mechanism.