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.

The digital transformation of businesses is creating new products, processes, and services. But to provide these new offerings, companies must share information and assets with each other in ways that were previously off-limits. For example, digitized services may require competitors to share physical assets such as warehouse space. This, in turn, means that companies will need to change the way they forge and manage relationships with other entities in the supply chain to facilitate new types of alliances and agreements. It will require managers responsible for developing supply chain relationships, such as account managers or supply managers, to adopt a boundary-spanning mindset in order to facilitate collaboration, experimentation, and trust across organizational boundaries.

Elsevier, the global information analytics business specializing in science and health, is pleased to announce the winner of the 2018 Semantic Web Challenge (SWC). The winner was recently announced at the 17th International Semantic Web Conference held in Monterey County, California, USA. The challenge and allocated prize were sponsored by Elsevier. The Semantic Web Challenge is a highly-prestigious, and the longest-running, competition fostering scientific progress in the field of artificial intelligence on the web. The semantic web and the use of linked data extends the current human-readable web by encoding some of the semantics of resources in a machine-readable form.