Enhancing Transparency in Buyer-Driven Commodity Chains for Complex Products: Extending a Blockchain-Based Traceability Framework Towards the Circular Economy
This repository contains the chaincodes and scripts necessary to run the simulation discussed in Section 2 of the paper.
Read the paper»
Table of Contents
From the paper: This study extends our prior blockchain-based traceability framework, WEave, for application to a furniture supply chain scenario, while using the original multi-tier apparel supply chain as an anchoring use case. We integrate circular economy principles such as product reuse, recycling traceability, and full lifecycle transparency to bolster sustainability and resilience in supply chains by enabling data-driven accountability and tracking for closed-loop resource flows. The enhanced approach can track post-consumer returns, use of recycled materials, and second-life goods, all represented using a closed-loop supply chain topology. We describe the extended network architecture and smart contract logic needed to capture circular lifecycle events, while proposing new metrics for evaluating lifecycle traceability and reuse auditability. To validate the extended framework, we outline simulation experiments that incorporate circular flows and cross-industry scenarios. Results from these simulations indicate improved transparency on recycled content, audit trails for returned products, and acceptable performance overhead when scaling to different product domains. Finally, we offer conclusions and recommendations for implementing WEave functionality into real-world settings consistent with the goals of digital, resilient, and sustainable supply chains.
- Hyperledger Fabric version 2.5.9
- Go version 1.22.4
- jq version 1.6
- Docker Desktop
Please follow the detailed instructions on the Hyperledger Fabric website to install the necessary prerequisites (including those listed above) required to run a local Docker-based Fabric network based on your operating system:
- macOS
- Linux
- Windows
- For Windows: it is strongly recommended to use WSL2 (Windows Subsystem for Linux version 2) and thereon follow the Linux instructions
Optional: The earlier, linear forward-flow apparel supply chain WEave repository contains simulation scripts and chaincodes that offer complementary functionality to this repository and can be used for comparison.
In order to use this repository to simulate an apparel supply chain trace, one must:
- Clone this repository and navigate there to make it the working directory for the following steps
- Download the Fabric install script and make it (and all existing scripts) executable:
curl -sSLO https://raw.githubusercontent.com/hyperledger/fabric/main/scripts/install-fabric.sh && find . -type f -name "*.sh" -exec chmod +x {} \; - Use this newly installed script to download the v2.5.9 binaries:
If executed succesfully, this will create 2 directories within the working directory:
./install-fabric.sh --fabric-version 2.5.9 binarybin/andbuilders/ - Navigate to the admin-channel chaincode directory, i.e.,
chaincode/*admin-channel/, and create thevendor/directory:Then, do the same for the production-channel chaincode directory, i.e.,go mod vendorchaincode/*production-channel/. At the end of this step, both*admin-channel/and*production-channel/should contain avendordirectory.
Now that the prerequisites and go dependencies for the chaincode are installed, we can begin the simulation.
This script runs both apparel and furniture circular supply chain performance analyses and generates 6 CSV files total ([1]apparel_performance_500_units.csv - 500 garments, 5% return rate, [2] apparel_performance_2500_units.csv - 2500 garments, 10% return rate, [3] apparel_performance_5000_units.csv - 5000 garments, 15% return rate,[4] furniture_performance_500_units.csv - 500 tables, 5% return rate, [5]furniture_performance_2500_units.csv - 2500 tables, 10% return rate, and [6] furniture_performance_5000_units.csv - 5000 tables, 15% return rate) in test-network/performance_results
cd test-network
./runCompletePerformanceAnalysis.shTo help analyze the CSVs and generate plots accordingly
pip install -r requirements.txtThis script generates comprehensive plots in test-network/performance_results for quantitative analysis of circular supply chain performance based on the 6 CSV files outputted in step 1.
python generate_performance_plots.pyscalability_analysis.png shows how throughput scales with production volume (500→2500→5000 units) to demonstrate framework scalability across apparel vs furniture supply chains.
circular_economy_impact.png shows the performance impact of return rates and circular processes for cost-benefit analysis of circular economy integration.
traceability_performance.png shows query latency for different asset types (sold/returned/recycled/refurbished) to measure traceability complexity across circular supply chain stages.
comprehensive_dashboard.png shows multi-metric overview with summary table for a complete framework performance assessment.
Takkar, R., Birman, K., & Gao, H. O. (2025). Enhancing Transparency in Buyer-Driven Commodity Chains for Complex Products: Extending a Blockchain-Based Traceability Framework Towards the Circular Economy. Applied Sciences, 15(15), 8226. https://doi.org/10.3390/app15158226
@Article{app15158226,
AUTHOR = {Takkar, Ritwik and Birman, Ken and Gao, H. Oliver},
TITLE = {Enhancing Transparency in Buyer-Driven Commodity Chains for Complex Products: Extending a Blockchain-Based Traceability Framework Towards the Circular Economy},
JOURNAL = {Applied Sciences},
VOLUME = {15},
YEAR = {2025},
NUMBER = {15},
ARTICLE-NUMBER = {8226},
URL = {https://www.mdpi.com/2076-3417/15/15/8226},
ISSN = {2076-3417},
ABSTRACT = {This study extends our prior blockchain-based traceability framework, WEave, for application to a furniture supply chain scenario, while using the original multi-tier apparel supply chain as an anchoring use case. We integrate circular economy principles such as product reuse, recycling traceability, and full lifecycle transparency to bolster sustainability and resilience in supply chains by enabling data-driven accountability and tracking for closed-loop resource flows. The enhanced approach can track post-consumer returns, use of recycled materials, and second-life goods, all represented using a closed-loop supply chain topology. We describe the extended network architecture and smart contract logic needed to capture circular lifecycle events, while proposing new metrics for evaluating lifecycle traceability and reuse auditability. To validate the extended framework, we outline simulation experiments that incorporate circular flows and cross-industry scenarios. Results from these simulations indicate improved transparency on recycled content, audit trails for returned products, and acceptable performance overhead when scaling to different product domains. Finally, we offer conclusions and recommendations for implementing WEave functionality into real-world settings consistent with the goals of digital, resilient, and sustainable supply chains.},
DOI = {10.3390/app15158226}
}Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the Apache-2.0 license. See LICENSE.txt for more information.
Ritwik Takkar - rt398@cornell.edu
Project Link: https://github.com/ritwiktakkar/WEave_2.0