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.