With the global emphasis on environmental sustainability, particularly in the context of industrial manufacturing, and the need to comply with government regulations, organizations have been compelled to adopt sustainable manufacturing processes and report their current sustainability levels and strategic goals. The organizations are using multicriteria decision-making frameworks to assess their current sustainability performance and prioritize key elements for strategic decision-making. However, the current sustainability assessment frameworks involve complex and laborious procedures, starting with the collection of data from organizational databases and then computing their sustainability level. In this regard, the study presents a structured application for calculating the organizational sustainability index (SI). The developed application utilizes the Analytical Hierarchy Process (AHP) and an aggregation method to calculate the overall sustainability index. The integration of the application with the organizational database enables seamless calculation throughout the entire process. The application provides a better understanding of sustainability performance and enhances organizational strategic decision-making by prioritizing the most influential sustainability indicators.

Supply chain interruptions impact all sizes of organizations, but small and medium-sized enterprises (SMEs) are particularly susceptible since they have fewer resources and less negotiating leverage than larger corporations. Environmental disruptions such as climate change, resource scarcity, and natural disasters lead to operational delays, higher costs, and revenue loss. SMEs can mitigate these disruptions by collaborating with their supply chain partners. This study presents a framework for how modeling simulation and artificial intelligence can aid in collaboration to support SMEs in mitigating the operational impacts of environmental supply chain disruptions. It indicates that partnerships can assist SMEs in creating contingency plans, sharing resources, and building resilience. It identifies key benefits of collaboration for SMEs and different strategies that SMEs can use to mitigate the disruptions due to environmental issues. The paper concludes by calling for more research on developing a decision-making framework to overcome collaboration barriers faced by SMEs.

This literature review examines recent studies on the application of artificial intelligence (AI) in public administration, incorporating real-life examples to demonstrate the impact of AI on various aspects of public administration. The review is organised into the following sections: AI for decision-making, AI for public service delivery, AI for policy analysis, AI for public engagement, and AI for public sector efficiency. The paper concludes by identifying potential challenges and future research directions.