Summary Nowadays the whole world is striving to achieve energy security and sustainable development through sustainable utilization of cleaner energy resources. But due to the rapidly rising population caused by the unprecedented urban development, it has created imbalances of energy supply and demand. Hybrid energy systems have emerged as a promising source to augment existing energy infrastructure for sustainable energy supply and to reduce the impact of challenges posed by the energy scarcities. There have been continuous requests from the urban sector for additional energy resources, but the energy generation involves a complex phenomenon. In India also, there are abundances of rising energy demands from various sectors over the regions, and these demands cannot be fulfilled further due to the limitations of the energy generation grids. As a result, an approach is required to offer additional energy resources beyond the use of diesel generator (which increases environmental pollution). Recently due advancement in hybrid energy systems consisting of non‐renewable & renewable or renewable & renewable or non‐renewable & non‐renewable, it provides a scope to understand the various configuration of the hybrid energy system for past trends, present status and future scenarios. The investment in energy technologies is critical to be evaluated with techno‐economic feasibility analysis for resource efficiency optimization. Hence, the main objective of this work is to propose an optimal system configuration for urban residential standalone hybrid energy systems to fulfil the electrical energy requirement, which is technically and economically reliable & feasible. The current work accounts for scaling up the existing energy system with proper implementation. The simulations results show that expected average energy requirements of 5 kWh/day with a peak of 818 W for a typical household can be met with proposed configuration (with components like solar PV, wind turbine, power generator [diesel] and battery backup system). The data simulation and optimization technique for a monthly profile of wind, solar, and excess energy generation over HOMER simulation toolkit offer the potential to generate excess electricity of 19.3%. Techno‐economic assessment of the system shows that the proposed system offers more economical and performance benefits. This study also articulates the need to propose a better energy system structure with basic energy grid extension as a cost‐effective solution for sustainable development. Similar kind of assessment will offer a useful decision support system for tropical countries to guide future researchers in energy studies.

This paper pioneers the identification of artificial intelligence (AI) enablers like technology feasibility, sophistication, data integrity, interoperability and perceived benefits that can boost operational efficiency of firms in Indian food processing industry. With the food processing industry contributing significantly to domestic gross value added and generating an export earning of close to USD 40 billion from agricultural and processed food exports, the study examines the role of AI in overcoming the existing inefficiencies of firms, particularly the small and medium enterprises (SMEs) involved in food processing. For this, questionnaire was circulated to 500 respondents comprising of IT and supply chain professionals, managers of food processing companies and academicians working in this domain, of which 341 complete responses were received. These responses were then analysed using PLS-SEM modeling, through which the relationship between AI adoption and operational efficiency of firm was established. The study found a significant relationship between AI adoption and operational efficiency. The R square and Q square values substantiate the predictive power of the model used in the study. The research has significant implications for supply chain professionals as technology adoption would boost resilience, integration and transparency of these firms. The study is also relevant for addressing issues pertaining to food security, ________________________________ Vranda Jain -Assistant Professor.

No abstract

As global value chains (GVCs) account for 80% of global trade, the revival of protectionism, amidst the looming trade tensions between United States and other trading partners, particularly China will dampen the international input–output relations. By using a multi-regional and multi-sectoral dynamic computable general equilibrium model, this study analyses China driven GVCs. The study explores the impact of tariff change on China and its major trading partners on economic variables like consumption, investment, government expenditure, exports and imports and sectors like electronic goods, coal, crude oil and machine equipment for the five-year period, that is, 2021–2025. GTAP 10 database has been used. The findings of the study suggest that although China’s dominance may diminish, yet it would continue to be one of the prominent players in GVC. Further, based on the results, the global economy can look forward to fragmented and locally oriented supply chains. At the sectoral level, the shorter supply chains would lead a further disjoint global trade system with a wider range of suppliers for similar products and hence increased regionalisation of production. JEL Codes: F10, F17, F60, F16, D58

No abstract