## 1 Introduction
Examples include (a) Recycled Content Traceability (%)--the fraction of a product's material (by weight or item count) that can be traced back to prior product lives via the blockchain record; (b) Return/Reuse Audit Rate--the percentage of returned items for which the system successfully logs and verifies disposition (reused, recycled, or properly discarded); (c) Latency of Traceability Queries--the time to retrieve the full history of a product including manufacturing and post-use events; and (d) Cycle Closure Rate--the proportion of output that re-enters as input (a measure of circularity enabled, perhaps tracked through smart contract triggers). These metrics extend conventional supply chain KPIs by focusing on transparency of reuse/recycling processes, which is a novel contribution to evaluating supply chain sustainability. * Additional Simulation Experiments for Validation: To strengthen the evidence for our extended framework, we design new simulation experiments beyond those in the initial study. First, we implement a closed-loop apparel supply chain simulation where a certain percentage of sold garments are returned after use, sorted for recycling, and reintroduced as raw material in new production. We describe the methodology for simulating consumer returns, processing by a recycler entity, and injecting recycled material back into the manufacturing orders. The expected result is that the blockchain ledger successfully links each returned garment to a batch of recycled fiber and then to a new garment, demonstrating traceability across product generations. We will measure system performance (transaction load, smart contract execution time) and integrity of traceability (e.g., no lost links in the chain of custody). Second, we propose a cross-industry simulation: for example, modeling a furniture supply chain with a take-back program for used furniture, and comparing it to the apparel case. This will involve different asset types and a unique assembly structure. By running the WEave framework in both contexts, we can compare how the framework handles different throughput or data volume requirements. We anticipate that while the absolute performance may differ (apparel might generate more data per unit due to more components), the qualitative outcomes will be similar--i.e., successful end-to-end traceability and manageable overhead. * Alignment with Sustainability and Resilience Goals: Finally, we expand the discussion of sustainability, transparency, and resilience implications. The Special Issue's theme highlights that digital technologies in supply chains should not be just for efficiency, but also for making supply chains resilient to shocks and sustainable in the long term. Our extended framework contributes to sustainability by enabling circular supply chain management, which can reduce waste and virgin resource consumption (e.g., by tracking and increasing recycled inputs). It also contributes to resilience: improved traceability means that in the event of a disruption or quality failure, firms can quickly isolate affected batches and reroute supply (since the provenance of every part is known) [16]. Moreover, having a tamper-proof record of transactions can prevent fraud and ensure continuity of data if a particular intermediary is compromised. In summary, we articulate how the WEave extension is not just a technical upgrade, but a sociotechnical improvement aligning supply chains with broader goals of transparency, sustainability (through circular resource flows), and resilience. Several recent studies have explored using blockchain technology to support circular economy goals by improving product traceability, recycling verification, and supply chain transparency. For example, [PERSON] et al. [17] present a blockchain-based reverse logistics framework for agricultural pesticide packaging. Their system uses Ethereum smart contracts and QR-coded tokens to track pesticide containers from use to collection, rewarding farmers and waste handlers with digital coins for returning empty containers.