In the current global economy, supply chain transparency plays a pivotal role in ensuring this security by enabling companies to monitor supplier performance and fostering accountability and responsibility. Despite the advancements in supply chain relationship datasets like Bloomberg and FactSet, supply chain transparency remains a significant challenge in emerging economies due to issues such as information asymmetry and institutional gaps in regulation. This study proposes a novel approach to enhance supply chain transparency in emerging economies by leveraging online content and large language models (LLMs). We develop a Supply Chain Knowledge Graph Mining System that integrates advanced LLMs with web crawler technology to automatically collect and analyze supply chain information. The system's effectiveness is validated through a case study focusing on the semiconductor supply chain, a domain that has recently gained significant attention due to supply chain risks. Our results demonstrate that the proposed system provides greater applicability for emerging economies, such as mainland China, complementing the data gaps in existing datasets. However, challenges including the accurate estimation of monetary and material flows, the handling of time series data, synonyms disambiguation, and mitigating biases from online contents still remains. Future research should focus on addressing these issues to further enhance the system's capabilities and broaden its application to other emerging economies and industries.

Modern supply chains have reached an unprecedented and rather extraordinary level of complexity. The increasing digitization of the physical world, in conjunction with the innovation of IoT technology and sophisticated personality-based targeted marketing techniques, has created an ecosystem where consumer markets are instantaneously accessible, adaptable, and trackable. While there is an enormous potential for profit on the side of businesses, increases in demand have made the maintenance of a linearly structured supply chain unfeasible, especially when it is no longer strictly defined by its transition from raw material to final product. Moreover, consumers, businesses and suppliers now form a multi-dimensional conglomerate that ranges beyond specific industry-domains, population demographics, and national borders. These dynamics have outlined the vulnerability of our existing supply chains.

A new approach to traceability uses blockchain, artificial intelligence (AI) and the internet of things (IoT) to help provide transparency, efficiency and safety across the entire food supply chain. "The system can be used in feed mills, farms, hatcheries, broiler farms, slaughterhouses and for the processing," Sharmeen Khan, chief marketing officer, OpsSmart Global, said during the Virtual Poultry Tech Summit 2020. Blockchain, AI and IoT are three forms of digital technology poised to help the poultry industry solve a variety of current and future challenges, ranging from food safety, workforce challenges, interruptions to the supply chain and more. In this case, the three technologies work together to create a traceable and transparent ledger that permanently records each transaction along the supply chain.\ The approach could offer many benefits, including increased market share, improvement to brand loyalty and operational efficiency, an enhanced product quality, reduced IT expenditure and more efficient and seamless audits.

"New ways to improve the supply chain: Artificial Intelligence, IoT, Big Data, Augmented Reality, Blockchain, Drones, Machine Learning." "Blockchain is a key technology in the digital supply chain." "Is blockchain just another buzzword or is it the future of the digital supply chain." "Be a supply chain innovator.