Purpose – A successful supply chain should ensure that all participating members benefit from the marketplace. To achieve this goal, the supply chain members need to improve their competences all the time, which requires a continuous learning process. Thus, mutual learning, through knowledge sharing between the different members, is a necessary approach to increase the competence of supply chain partners. To realise efficient and effective knowledge sharing in a supply chain, this paper aims to explore and formulate a model that supports an enterprise with its management of the supply chain members' knowledge resource sharing (herein referred to as “advanced practice” and includes two levels of knowledge – strategic and operational). The model is based on the theories of supply chain management (SCM) and case-based reasoning (CBR). Design/methodology/approach – This research follows a conductive and inductive cycle. Firstly, based on the learning expounded through an extensive literature survey regarding SCM and CBR, as well as available empirical applications, the conceptual model is designed. Then the primary stage evaluation will be discussed regarding the feasibility and refinement of the model towards its maturity. Findings – To share knowledge along the supply chain is theoretically sound, but a difficult task to realise in practice, due to the complexity of knowledge sharing between the different organizations. Research limitations/implications – This research explores one of the important topics in SCM – knowledge sharing within a supply chain, and the model also extends and explores a new tool for this knowledge-sharing process by applying CBR methodology. Practical implications – The designed model in this research will provide a practice-oriented vehicle allowing the supply chain members to share and apply their knowledge. Originality/value – This research applies CBR in the domain of SCM, it both enriches the available approaches to supply chain performance enhancement and enlarges the application domains of CBR methodology.