This study investigates the adoption of Green Construction Finance (GCF) and its determinants within Kenya’s construction industry. Utilizing a quantitative approach, data were collected from 55 registered property developers and analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings reveal a nascent GCF landscape characterized by a stark paradox: while 98% of developers express a conceptual willingness to adopt green practices, actual uptake is restricted to a mere 1.03%. The structural model indicates that the eight theorized determinants, awareness, accessibility, institutional, financial, environmental, technical, risk, and socio-cultural factors, collectively explain only 5.95% (R²=0.0595) of the variance in adoption. Critically, the analysis identifies a "barrier bundle" effect, where a lack of discriminant validity and high multicollinearity among constructs suggest that stakeholders perceive regulatory, financial, and risk-related hurdles as a single monolithic obstacle. Notably, environmental factors exhibit a negative path coefficient (-0.6313), implying they are currently viewed as cost burdens rather than value drivers. The study concludes that piecemeal interventions are insufficient; a holistic, systemic strategy is required to de-risk the sector and move beyond the current state of statistical fragility toward meaningful, sustainable construction uptake.

Tribal heritage in Jharkhand holds immense potential not just as a cultural asset but as a foundation for sustainable, community-led entrepreneurship. This paper examines the major issues that can help the tribal societies transform their cultural heritage into legitimate business enterprises. Based on the domain, the study makes use of the Best-Worst Method (BWM) to rank significant enablers. It applies Interpretive Structural Modelling (ISM) and MICMAC analysis to discover the structural relationship between them. It is indicated that although the availability of natural resources, indigenous knowledge, and governmental support serve as the foundations of tribal enterprise, psychological preparedness and market access are the key factors in the long-term development. Interestingly, cultural values and education are also discovered as highly ingrained factors that determine an entrepreneurial intent and sustainability. The paper illuminates the multifaceted nature of the problems tribal entrepreneurs have to encounter, such as geographical remoteness and the changing demands of consumers, but also shows the opportunity to interfere by making specific changes. Through mapping of these enablers and their linkage, this study will provide a practical framework to be used by policymakers, NGOs, and local stakeholders to enable and expand tribal entrepreneurship in Jharkhand. Finally, it promotes the model of development in which cultural pride and economic empowerment must go hand in hand.

Tribal heritage in Jharkhand holds immense potential not just as a cultural asset but as a foundation for sustainable, community-led entrepreneurship. This paper examines the major issues that can help the tribal societies transform their cultural heritage into legitimate business enterprises. Based on the domain, the study makes use of the Best-Worst Method (BWM) to rank significant enablers. It applies Interpretive Structural Modelling (ISM) and MICMAC analysis to discover the structural relationship between them. It is indicated that although the availability of natural resources, indigenous knowledge, and governmental support serve as the foundations of tribal enterprise, psychological preparedness and market access are the key factors in the long-term development. Interestingly, cultural values and education are also discovered as highly ingrained factors that determine an entrepreneurial intent and sustainability. The paper illuminates the multifaceted nature of the problems tribal entrepreneurs have to encounter, such as geographical remoteness and the changing demands of consumers, but also shows the opportunity to interfere by making specific changes. Through mapping of these enablers and their linkage, this study will provide a practical framework to be used by policymakers, NGOs, and local stakeholders to enable and expand tribal entrepreneurship in Jharkhand. Finally, it promotes the model of development in which cultural pride and economic empowerment must go hand in hand.

This article provides a detailed analysis of the fast fashion (FF) supply chain, focusing on emerging trends and significant challenges. It aims to define fast fashion, identify current supply chain trends, and clarify sustainability issues across environmental, social, and economic areas. Using a systematic literature review, the study examines relevant research published from 2020 to 2025, drawing from various electronic sources. The findings highlight key trends, including increased transparency and traceability enabled by technologies such as blockchain and RFID, sustainable sourcing practices, and greater digitalization and collaboration among stakeholders. However, it also underscores urgent environmental issues, such as water contamination and carbon emissions, as well as social concerns, like worker exploitation, and economic issues, such as overproduction. Technological challenges, such as infrastructure upgrades and resistance to change, are also addressed. The paper recommends that future research explore innovative business models, such as ultra-fast fashion, to better align with consumer preferences and address overproduction. While offering extensive insights into fast-fashion trends and sustainability issues, the study acknowledges some limitations in the scope of innovative business ideas. Practical implications underscore the importance of advanced technologies to improve supply chain transparency and reduce environmental impacts, advocating strategic shifts toward sustainable sourcing and circular-economy principles. Overall, this systematic review consolidates key data on the fast-fashion industry's supply chain, providing valuable insights for stakeholders seeking to adopt more sustainable and fairer practices.

Digital Twin (DT) technology combined with the Internet of Things (IoT) can be used to provide new solutions to real-time monitoring and management of agriculture. This paper introduces an IoT-based digital twin platform that will help in streamlining agricultural operations by incorporating different sensor technologies to monitor vital soil and crop conditions, such as moisture, temperature, pH, and nitrogen concentrations. The system offers predictive analytics to inform irrigation control, pest control, and fertilizer application, to help in making agricultural activities more sustainable. The effectiveness of the model is tested based on real time data integration and predictive modeling with 92% accuracy in monitoring soil moisture and an 87 percent accuracy in predicting crop yields. Although the system shows a high potential in terms of resource optimization and productivity, issues like sensor calibration, network connectivity and scalability to bigger operations exist. The future direction must be aimed at making sensors more reliable, more scalable, and adding AI and automation to make the system even more efficient and applicable in precision farming.

Transportation is one of the most important functions of logistics management because of its impact on both the level of customer service provision and the organization’s cost structure. The study explores the transportation cost optimization strategies and how they affect the supply chain performance of Shea nuts in the Agro-processing industries in Ghana. The quantitative study design was adopted and utilized to solicit data. With a sample size of 204 respondents. Data was analyzed using multiple linear regression in Statistical Package for Social Sciences (SPSS v20). The results revealed interesting findings in the supply chain within the institution as it seeks to assert that transportation is seen to be effective and contribute highly to firms output when Agro companies use outsourcing and pooling as means of transport. From the results, the supply chain correlated positively and significantly with outsourcing and pooling as transport optimization practices in Agro firms supply chain. This paper adds to the existing literature on the supply chain systems of Agro processing firms but departs from previous studies which seek to concentrate not on the transport optimization of the Agro processing firms but rather on the challenges, production, and profit maximization of these firms. Our study is unique unlike any otheIn this research, a heterogeneous tricomposite catalyst was developed to facilitate biodiesel synthesis reaction. The Musa ABB (Kachkal) banana trunk was explored as the biowaste for the preparation of the catalyst. The trunk of the plant was cut into pieces, dried and burnt into ashes, and underwent heat treatment at 550 ℃ for 2 h. The calcined trunk was treated with potassium carbonate and CuO and the final composite was named a calcined banana trunk-K2CO3-CuO (CTKC) catalyst. The CTKC catalyst was employed in the production of rice bran pongamia oil methyl ester (RPOME) from rice bran and Pongamia pinnata (RP) oil blend in 1:1 ratio. The CTKC catalyst was characterized via XRD, and FT-IR analytical tools. Similarly, FT-IR and 1H NMR were employed to examine RP oil blend and RPOME. Under the optimized condition of 7 wt.% catalyst amount, 9:1 methanol to oil molar ratio (MTOMR), and 65 ℃ reaction temperature, the highest biodiesel yield was found to be 94.07 %. The density of RPOME was found to be 0.8811 g/cm3 which fits into the specified limit of EN 14214 and the kinematic viscosity of RPOME was found to be 3.5403 mm2/s which falls under both ASTM D6751 and EN 14214 standards. In brief, the CTKC catalyst functions as an effective heterogeneous catalyst for the synthesis of biodiesel from a binary blend of edible oil (rice bran) and non-edible oil (Pongamia pinnata). This represents an innovative strategy to tackle the rising pollution caused by diesel and petroleum-derived from fossil fuels used in vehicles. r research previously authored as it seeks to reveal the option of transport optimization that is cost effective and efficiently productive for Agro processing firms to adopt.

Sustainability is getting preference now-a-days in most of the countries in the world. This implies industrial and other developments for economic growth, and of course civilization, but certainly not at the cost of environmental degradation. Environmental conservation is a must. One of the major components of industrial sectors is their electrical energy inputs through electrical substation. Numerous research addresses the issue of energy pollution, cantering on fossil fuel. A very few research can be found which address the issue of pollution generated from electrical energy. This research addresses this issue, with special attention to electrical substations. In the last two or three decades, several electrical equipment manufacturers have started producing this equipment in Bangladesh, which were previously import-oriented. This equipment use various types of oils, acids, zinc and other metals, which are all environmentally hazardous. Thus, any industrial company, buying such equipment from substation manufacturers, should consider green aspects. As such, now it is of prime importance to select green suppliers of substation equipment. Since selection of right or green supplier involves multi-criteria evaluation, Multi-criteria Decision Making (MCDM) technique is essential. Additionally, both qualitative and quantitative criteria require fuzzy analysis to make it more precise and realistic. This research addressed the issue of environmental pollution, its sources, nature and severity, and their mitigation through selecting green suppliers.

Cities throughout the world are facing significant issues in terms of expanding urbanization. One of the key challenges is the increased amount of generated garbage and pollution due to the high demand for food and other necessities. Public waste bins are filling up faster than ever, and many of them overflow before being collected, resulting in blocked streets and unpleasant smells, as well as detrimental health and environmental effects. Overflowing garbage is a public nuisance and an eyesore, in addition to causing other health and environmental problems. Everyone desires to live in and visit places that are clean, fresh, and healthy. A smelly city with waterborne diseases and garbage all over the place does not attract visitors or investors. As a result of inefficient garbage management and recycling, cities continue to lose money and lose out on revenue advantages and job opportunities. Because of the uncertainty and complexity of garbage disposal and minimization of the environmental effect, a multi-attribute decision-making method based on a dynamic spherical fuzzy weighted average and uncertain dynamic spherical fuzzy weighted average aggregation operators are proposed to evaluate the site selection scheme of garbage disposal plant, and support for decision-making of garbage disposal site selection. In this study, firstly, spherical fuzzy information based dynamic and uncertain dynamic aggregation operators are integrated. Meanwhile, some interesting properties of the proposed operators are analyzed. Then, a multi-attribute decision-making method is established using proposed dynamic and uncertain dynamic aggregation operators under a spherical fuzzy environment. After that, a practical case on evaluating the garbage disposal site selection scheme is given to verify the effectiveness of the proposed method. The results show that this method boasts more expansive space for information representation, more flexible adaptation to the evaluation environment, and stronger robustness of the evaluation results.

Water security is a significant challenge in India due to its rapidly growing population, increasing demand for water, and frequent droughts and floods. The country has also been facing issues related to water pollution, inefficient water management practices, and limited access to safe drinking water. Ensuring water security in India requires a comprehensive approach that involves the integration of technology, policy, and community engagement to address the complex challenges associated with water management. This research paper identifies eight major challenges of water security in India, including population growth, climate change, water resource management, anthropogenic factors, technological factors, socio economic issues, geopolitical factors, and virtual water trade. Using the Analytical Hierarchy Process (AHP) method, this study ranks these challenges based on their relative importance. The findings suggest that population growth and climate change are the most critical challenges, followed by poor water resource management, anthropogenic factors, technological factors, socio economic issues, geopolitical factors, and virtual water trade. The study highlights the need for integrated and holistic approaches to address these challenges and ensure sustainable water management in India.

Sustainable crop production depends on data-driven decision-making to optimize agricultural policies. The present research evaluates the possibility of growing maize and apples in Onondaga County, New York, using a land suitability analysis based on the Analytical Hierarchical Process (AHP). The expected potential of land and empirical farmed land utilization differ significantly, according to our analysis of high-resolution soil, land use, and climate information. According to the current investigation, less than 5% of the county’s land is now under cultivation. In fact, sufficient portions appropriate for agriculture such as 44.97% suited for apple orchards and 28.66% for maize. The main obstacles to agriculture are zoning laws that restrict agricultural growth, and land use restrictions and significant forest cover. The current research stipulates modifying zoning laws and providing financial subsidies to farmers. Further, investing in infrastructure development to increase agricultural production to maximize use of agricultural land and to promote awareness for sustainable agriculture practices. The outcomes of the study highlight evidence-based strategies which help in minimizing the gap between agriculture potential and land utilization. It also promotes steady growth of agriculture by offering particular land usage administrators, agriculture scientists, and administrators with beneficial guidelines.