Increasing flexibility and responsiveness are the opportunities that smart logistics offers to companies. With the development of the supply chain network (SCN) and big data processing, a simple view at above two technologies separately has become unadvisable. This work deals with the traceability and supply chain risk management of containers during shipping expeditions using real-time Data. The main objective of this article is to analyse proposed solutions to improve the efficiency of the supply chain by acting on risk management in containers transport. A future approach to improve the real-time management of shipments by taking into account random events is mentioned.

Knowledge is essential for organizations’ growth as it allows them to solve problems, make decisions, innovate, and stay competitive. Within organizations, there is, on the one hand, explicit knowledge that is easy to capture, represent, and share. On the other hand, there is tacit knowledge possessed and acquired by individuals during their activities. Unlike explicit knowledge, tacit knowledge is difficult to capture and formalize. Organizations have granted more interest and efforts in representing, sharing, and reasoning from explicit knowledge. However, for tacit personal knowledge, they rely on methods such as meetings, mentoring, questions answering, or interviews which are limited in capitalizing on personal knowledge. This study elaborates on the construction of interpersonal activity graphs for representing, sharing, and reasoning on organizations’ tacit knowledge possessed by individuals. The established graph is based on an extended activity theory framework and an ontology for common semantics. The proposed representation captures tacit knowledge in a graph form, making it shareable while offering means to reason and query it.