The concept of circular economy (CE) has proven its worth due to the scarcity of natural resources and huge amounts of wastage which impacts the environment. Thus, the adoption of the CE concept in the supply chain becomes critical. However, due to the complex nature of processes/activities in the circular supply chain (CSC), managing risk has become a priority to avoid disruption. In current literature, no discussion has been conducted on how to analyse the risks in the context of CSC. Therefore, to fill this literature gap, this study concentrates on identifying and analysing the risks to promote effective circular initiatives in supply chains in the context of the manufacturing industry, thus minimising the negative environmental impact. A total of 31 risks were identified through an extensive literature review and discussions with experts. A grey‐based decision‐making trial and evaluation laboratory (DEMATEL) method is applied by incorporating the experts' knowledge to compute prominence and cause/effect scores to develop an interrelationship map. Finally, a vulnerability matrix for risk categories is developed using the average of prominence and cause/effect scores of risks. The results show that transparent process is the most prominent risk and branding is the least significant risk. By using the average prominence and cause/effect score, a risk category, namely, financial risk, is identified as most vulnerable to CSC. These findings will help industry managers not only to prepare business strategies in the adoption of CE initiatives in supply chains by eliminating risks but also in minimising negative environmental impact.

A robust traceability system would help organizations in inventory optimization reduce lead time and improve customer service and quality which further enables the organizations to be a leader in their industry sector. This research study analyzes the challenges faced by the automotive industry in its supply chain operations. Further, the traceability issues and waiting time at different nodes of the supply chain are considered to be priority issues that affect the overall supply chain efficiency in the automotive supply chain. After studying the existing blockchain architectures and their implementation methodology, this study proposes a new blockchain-based architecture to improve traceability and reduce waiting time for the automotive supply chain. A hyper ledger fabric-based blockchain architecture is developed to track the ownership transfers in inbound and outbound logistics. The simulation results of the proposed hyper ledger fabric-based blockchain architecture show that there is an improvement in the traceability of items at different nodes of the supply chain that enhances the Inventory Quality Ratio (IQR) and the mean waiting time is reduced at the factory, wholesaler, and retailer, which thereby improves the overall supply chain efficiency. The blockchain embedded supply chain is more capable to eliminate the risks and uncertainties associated with the automotive supply chain. The benefits of adopting blockchain technology in the automotive supply chain are also described. The developed blockchain-based framework is capable to get more visibility into goods movement and inventory status in automotive supply chains.

As the supply chains are growing and becoming more interdependent, the vulnerability and the chances of supply chain failure also increases. The supply chain industry is severely affected due to the COVID-19 outbreak and industry practitioners are focusing on minimizing the ripple effect of the disruption made to the economy. Considering the unprecedented situation, the research is motivated to analyse the ripple effect in a multi-echelon supply chain and investigate the performance at various nodes to understand the capability of the supply chain to withstand the disruptions at different levels. Using discrete event simulation, this study analyses the ripple effect in the copper industry by an agent-based simulation software anyLogistix , considering various key performance indexes (KPIs) to gauge the magnitude. From the results of the simulation, it is evident that the lack of safety stocks and multi-sourcing of copper facilitate as major causes for the disruptions. The simulation helps to understand the disruption levels and make the supply chain more resilient and robust for any future disruption. Further, the study proposes resilient project management solutions to recover from the cascading ripple effect in the copper supply chain. The scientific contribution of the research is to provide supply chain managers with simulation techniques to understand the ripple effect on the copper supply chain. It helps the stakeholders to understand the importance of project management tools to reduce the cascading ripple effect in a copper supply chain. Further, the findings of this study will support contemporary managers, supply chain allies, project managers, and stakeholders to formulate strategies for recovering from the supply chain disruptions caused due to natural disasters, pandemics such as COVID-19.

Organizations have been facing quite a few challenges, including a growing global competitive market, shorter time to market, rising product variants, and adjustments in production because of fluctuation in demand. To handle these challenges, industries need to connect engineering technology with enterprise systems to transform their practices toward industry 4.0 requirements. The supply chain sector is targeting stakeholders to enhance their product competitiveness by leveraging innovative digital technologies such as artificial intelligence, the internet of things (IoT), and blockchain to make effective decisions instantaneously. This article will help in contextualizing emerging adaptive intelligence technology to drive connected intelligence and achieve supply chain operational excellence. A real-time case study in the manufacturing industry will be discussed. Subsequently, how adaptive intelligence can help quality management in real-time will be explored to manage the production quality, which is measured by rejections, scraps, and cost savings. Additionally, this article discusses how technology-embedded enterprise systems help the organization to manage the daily production, which is measured by production rate, quality, and yield. For the case organization, the IoT architecture is proposed and the performance metric framework for the supply chain is described. Furthermore, the article discusses how materials can be reused to extract economic benefits with collaborated diverse industries. This influences the eco-friendly environment across the supply chain with the focus on reducing the carbon footage.

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