Delivery Management System based on Blockchain, Smart Contracts and NFT: A Case Study in Vietnam

Current traditional shipping models are increas-ingly revealing many shortcomings and affecting the interests of sellers and buyers due to having to depend on trusted third parties. For example, the Cash-on-Delivery (CoD) model must depend on the carrier/shipper, or the Letter-of-Credit (LoC) model depends on the place of the Letter certification (i.e., bank). There have been many examples demonstrating the riskiness of the two models above. Specifically, in developing countries (e.g., Vietnam), the demand for exporting goods and trading between sellers and buyers have not yet applied the benefits of current technology to improve traditional shipping models. Two typical examples in the last five years that have demonstrated the risks of both sellers and buyers when applying CoD and LoC models are the problem of keeping the money of the seller of GNN Expresses (2017) as well as risks in losing control of 4 containers of cashew nuts when exporting from Vietnam to Italy (2021). A series of studies have proposed solutions based on distributed storage, blockchain, and smart contracts to solve the above problems. However, the role of the shipper has not been considered in some approaches or is not suitable for deployment in a developed country (i.e., Vietnam). In this paper, we propose a combination model between the traditional CoD model and blockchain technology, smart contracts, and NFT to solve the above problems. Specifically, our contribution includes four aspects: a) proposing a shipping model based on blockchain technology and smart contracts; b) proposing a model for storing package information based on Ethereum's NFT technology (i.e. ERC721); c) implementing the proposed model by designing smart contracts that support the creation and transfer of NFTs between sellers and buyers; d) deploy smart contracts on four EVM-enabled platforms including BNB Smart chain, Fantom, Celo, and Polygon to find a suitable platform for the proposed model.