Supporting Circular Economy Strategies in Electronics: Data Characterization for R-Strategy Decision Making

When an electronic product reaches the end of its use, several circular strategies may be considered (reuse, repair, refurbishment, remanufacturing, repurposing, component reuse, and recycling). Applying these strategies requires information about the product, but it is often unclear what information is needed, where it can be obtained, and how it should be used in the decision. This study identifies and characterizes the data required at each step of an end-of-use decision process for electronic products. A decision-tree framework is used to trace the information needed for product identification, market assessment, remaining useful life estimation, inspection, safety and functional testing, diagnosis, and evaluation of circular strategy options. The approach is illustrated using four end-of-use laptop adapters. For each step, the required data are identified, their role is explained, and their practical accessibility is assessed and contextualized with literature-based indicators of availability, importance, and sensitivity. Results show that identification and regulatory information are generally accessible, whereas usage history, maintenance records, lifetime information, and detailed testing and diagnostic data are often inaccessible in the case study. By linking data requirements to specific decisions, the study identifies critical information gaps and highlights how Digital Product Passports and collaborative data sharing could support circular decision-making.