Role of Enabler Technologies (IoT and Machine Learning) in Supply Chain Management

The convergence of enabler technologies such as Internet of Things (IoT) and Machine Learning (ML) algorithms has unparalleled prospects for real-time data gathering, analysis and decision-making in supply chain management (SCM) process. The paper explores the role of IoT and ML technologies poised to reshape the future of SCM and illustrates how these technologies jointly influence supply chain management in the upcoming future. A comprehensive bibliometric analysis of the potential use of IoT and an in-depth comparison of various ML algorithms are presented in the paper to revolutionize SCM. A bibliometric analysis study of IoT utilization in SCM clearly shows extensive growth and adoption of IoT in SCM over the past years. The study concludes that IoT has become an indispensable component of modern SCM. Furthermore, the paper sheds light on the versatility of ML algorithms in optimizing supply chain operations. The performance of multiple ML algorithms is analyzed on the parameter of exchange rate prediction, out of which support vector machine(SVM) outperforms other algorithms. The paper provides a roadmap for companies seeking to improve the efficiency, visibility, and sustainability of their supply chain processes by incorporating enabler technologies such as IoT and Machine Learning algorithms.