Source-linked AI summary
Blockchain-enabled supply chain: An experimental study
Francesco Longo, Letizia Nicoletti, Antonio Padovano, Gianfranco d'Atri, Marco Forte
TL;DR
Supply-chain partners may avoid sharing sensitive data when trust is limited, while evidence on blockchain applications remains scarce. The paper connects an Ethereum-like blockchain to enterprise systems and a supply-chain simulation model, finding that blockchain can improve supply-chain performance, reduce information-asymmetry consequences, and discourage misconduct. However, blockchain verification does not prevent inaccurate or counterfeit data from being entered initially.
Problem
Limited trust discourages sensitive information sharing, and companies report little blockchain knowledge because the technology is novel and application studies are scarce.
Method
The study develops a software connector linking an Ethereum-like blockchain with enterprise systems and integrates it with a supply-chain simulation model for scenario analysis.
Results
Blockchain is reported as a convenient instrument for overcoming collaboration and trust issues, improving overall supply-chain performance, reducing information-asymmetry consequences, and discouraging misconduct.
Takeaways & Limitations
Blockchain can serve as a certification entity for shared supply-chain information and support more trustworthy collaboration within the studied setting.
Takeaways & Limitations
Blockchain does not prevent data from being inaccurate or counterfeit before companies submit it to the chain, so trust still depends on partner companies.
Abstract
from arXiv · showhide
Despite Information and Communication Technologies (ICT) have reduced the information asymmetry and increased the degree of interorganizational collaboration, the companies participating a supply chain are less inclined to share data when information is sensible and partners cannot be fully trusted. In such a context, Blockchain is a decentralized certificate authority that may provide economic and operational benefits but companies operating in a supply chain claim to have little knowledge about Blockchain due to its novelty and to the lack of use cases and application studies. In this work, a software connector has been designed and developed to connect an Ethereum-like blockchain with the enterprises' information systems to allow companies to share information with their partners with different levels of visibility and to check data authenticity, integrity and invariability over time through the blockchain, thus building trust. In order to explore the potential of deploying the blockchain in a supply chain, a simulation model has been developed to recreate the supply chain operations and integrated with the blockchain through the same software connector to carry out a scenario statistical analysis. Application results shows how blockchain technology is a convenient instrument to overcome collaboration and trust issues in a supply chain, to increase the supply chain overall performance, to minimize the negative consequences of information asymmetry over the echelons of a supply chain but also to discourage companies from any misconduct (e.g. counterfeiting data or low data accuracy).
1. Introduction
The introduction frames low trust and information asymmetry as barriers to accurate data sharing and supply-chain performance, motivating blockchain as a certification mechanism. The paper proposes and evaluates a blockchain-enabled supply chain to quantify operational and economic benefits.
- Problem: Inaccurate or counterfeit information can amplify information asymmetry and contribute to production variance, excess safety stock, logistics costs, and inefficient resource use.The described propagation through the supply chain is associated with the bullwhip effect.
- Problem: Low trust makes supply-chain partners reluctant to share information, especially when they perceive one another as competing entities.Building trust requires sustained accurate information sharing, while access to accurate enterprise data already depends on trust.
- Proposed approach: Blockchain is proposed as a certification entity that provides a shared state of truth for exchanged information and supports authenticity, integrity, and invariability checks.Hashes are public on the blockchain while original data remain off-chain and are exchanged through conventional methods.
- Study contribution: The study addresses limited supply-chain blockchain evidence by combining a blockchain with a supply-chain simulation model for quantitative what-if analysis.The contribution targets both literature and industrial practice through an application study of blockchain-enabled supply chains.
- Findings: Results indicate that blockchain can overcome collaboration and trust issues, improve overall supply-chain performance, reduce information-asymmetry consequences, and discourage misconduct.The reported misconduct examples include counterfeiting data and low data accuracy.
2. Materials and methods
The methodological framework integrates an Ethereum-like public blockchain, a supply-chain simulation model, and a software connector. Together, these components represent supply-chain information and operations while bridging the blockchain with enterprise information systems.
- Framework components: The framework consists of three components: an Ethereum-like public blockchain, a supply-chain simulation model, and a software connector.The connector bridges the blockchain with the simulation model or, in a real deployment, with enterprise information systems.
- Blockchain: The blockchain represents a decentralized ledger for demand forecasts and inventory levels.These data are stored as information associated with the supply-chain framework.
- Simulation model: The simulation model recreates the company network and the flow of goods and information among participating organizations.It also represents organizational, production, and delivery activities.
- Software connector: The software connector links the blockchain to the simulation model and can connect it to enterprise information systems in a real supply-chain environment.This provides the integration layer for the proposed framework.
2.1. UnicalCoin: an Ethereum-like blockchain
The study uses UnicalCoin, an experimental Ethereum-like blockchain, to certify off-chain supply-chain data through hashes. The design preserves regulated access to original data but depends on network participation and retains blockchain and storage limitations.
- UnicalCoin: UnicalCoin is an experimental Ethereum-like blockchain used for testing, while the authors identify the official Ethereum network as preferable in a real environment.UnicalCoin was developed at the University of Calabria and uses the Ucal cryptocurrency.
- Network properties: A larger participant network is described as important for reliability, consensus, and data immutability, while UnicalCoin has thousands of nodes.Its participants keep the ledger synchronized through a consensus protocol that can append but not edit records.
- Limitations: UnicalCoin is not free from software-attack risks, and permissionless-chain operation has no guarantee of working under every circumstance.The paper also notes that distributed storage technologies do not guarantee permanent file availability.
- Data certification: The system stores original supply-chain data off-chain and archives their hash sums on-chain for authenticity and integrity verification.MySQL is used as the off-chain relational database in the application.
- Storage boundary: The design does not treat blockchain as a replacement for traditional databases because blockchains are not designed to store large amounts of data.Distributed storage alternatives such as IPFS and SWARM are discussed, but conventional relational databases are preferred for the application.
- Data certification: Off-chain storage keeps confidential originals under regulated access while the blockchain serves as a certification agent for data integrity.Partners can access the off-chain data and verify whether it corresponds to the archived hash.
2.2. A supply chain simulation model
The study develops a multi-paradigm simulation model of a supply chain to evaluate how shared information and data accuracy affect enterprise performance. It represents supply-chain actors, goods and information flows, operational processes, and inventory policies across manufacturers, wholesalers, retailers, and customers.
- Model scope: The model supports what-if scenario analysis by recreating supply-chain actors, goods and information flows, and organizational, production, and delivery processes.The implementation combines discrete-event and agent-based paradigms in a Java-based simulation.
- Supply-chain structure: The conceptual network includes four manufacturers, three wholesalers, twenty big-box retailers, and their stores, with manufacturers outside the paper’s detailed scope.Stores operated by the same retailer are assumed to have real-time visibility and no internal trust issues.
- Retail operations: Retail demand is modeled with Poisson arrivals and triangular order quantities, while stores use a modified (r, R) policy and single exponential smoothing for forecasting.Stores select wholesalers using lead time, lead-time demand, and immediately available quantity; unmet demand is recorded for fill-rate calculation.
- Implementation: The simulation implements supply-chain agents, purchase orders, event generators, and database updates to track demand forecasts and inventory levels.The modeled processes include inventory control and order fulfillment, with parameters for retailer and wholesaler operations summarized in two tables.
- Wholesaler operations: Wholesalers use dynamic safety stock and single exponential smoothing, fulfill retailer orders by prioritizing available inventory, and record lost quantities for fill-rate evaluation.When inventory is insufficient, available quantities are divided using ordered quantity as the weighting factor; wholesalers replenish from manufacturers daily.
- Inventory policies: Inventory decisions are represented through reorder, target-level, review-period, and cost calculations based on forecasts, safety stock, inventory position, ordering, reception, storage, and purchasing costs.The inventory position combines on-hand inventory, quantities already on order, and quantities to be shipped; the optimized review period minimizes unitary inventory cost.
2.3. A software connector to bridge the simulation model with blockchain
The study develops a Java-based software connector that links enterprise information systems and a supply-chain simulation model with an Ethereum-like blockchain. It supports controlled information sharing and verification of data authenticity, integrity, and invariability.
- The software connector bridges the supply-chain simulation model or enterprise information systems with the UnicalCoin blockchain.The same connector can be used with simulated agents or real companies.
- Companies are represented by Ethereum wallets, while SharedInfo stores shared data and TransactionVerification records transaction details.Transaction records can include block numbers and transaction hashes.
- The connector stores supply-chain data off-chain and records their hash sums on the blockchain through smart-contract-supported services.Communication, coordination, and facilitation services support data transfer, control transfer, and transaction validation or signature.
- Authorized companies can grant or deny Ethereum addresses, publish data, query permitted information, and verify authenticity, integrity, and invariability through hash sums.Authorization can change over time, with pending requests decided by a majority of authorized addresses.
- The publication workflow receives a JSON payload, reference date, and visibility group, checks and hashes the data, submits a signed transaction, and stores verification details.The blockchain node validates and stores the transaction, then returns a generated shared-data identifier and transaction information.
- Blockchain events notify registered applications when new data are published, after which companies can query databases for information within their visibility rights.The design supports structured publication frequencies such as daily or weekly schedules.
3. Results
The results compare no information sharing with blockchain-enabled sharing in a 60-day, three-replication simulation. Blockchain sharing improved demand visibility and fulfillment, with different effects on wholesalers’ and retailers’ economic outcomes.
- Scenario design: The blockchain-enabled scenario lets wholesalers verify demand-data authenticity and invariability through blockchain-stored hash sums, providing a trusted reference point.Big-box retailers share lead-time demand daily with a specified group of wholesalers.
- Wholesalers’ performance: 17.44% higher average wholesaler revenues were observed with blockchain-enabled sharing, while all orders were fulfilled and missing revenues were eliminated.The increase was 18.32% for wholesaler 1, 17.29% for wholesaler 2, and 16.62% for wholesaler 3.
- Wholesalers’ performance: Wholesalers’ profit margin changed little: 49,904,198.21€ with blockchain-enabled sharing versus 49,873,559.77€ without it.The Mann-Whitney test did not provide enough power to reject equal wholesaler-profit medians.
- Wholesalers’ inventory management: Wholesalers’ average fill rate increased from 63.67% to 100.00%, indicating that all retailer orders were fulfilled without stockouts.The study also reports differences in inventory position and total inventory cost between scenarios.
4. Discussion
The blockchain-enabled information-sharing scenario improves supply-chain operational performance and provides economic benefits for retailers, while wholesalers’ profit margins remain nearly stable. The study also finds that blockchain can support trust, reduce information-asymmetry effects, and discourage inaccurate or counterfeit data, although data entered incorrectly can still harm performance.
- Operational and economic effects: Supply-chain companies perform better in the B-IS scenario than in the No-IS scenario, particularly through higher service levels and more satisfied orders.The study identifies blockchain as a cost-convenient instrument for overcoming collaboration and trust issues and minimizing information-asymmetry consequences.
- Information sharing and trust: Sharing actual daily lead-time demand data through blockchain enables more precise wholesaler forecasts and better planning.Blockchain’s trust function allows retailers to share data with upstream wholesalers, who can use it instead of relying only on purchase-order history.
- Wholesalers: Wholesalers’ average revenues increase by 17,44%, while their profit margins remain nearly stable because revenue growth compensates for higher inventory costs.Blockchain significantly improves wholesalers’ operational performance, but does not significantly affect their economic benefits.
- Retailers: Retailers achieve better demand fulfillment and significantly higher profit margins, despite a 17,18% average increase in total inventory costs.Big-box retailers’ inventory position increases by only 0,41% in B-IS, while their higher fill rate generates stronger economic benefits.
- Data accuracy and misconduct: Blockchain does not correct inaccurate or counterfeit data entered in advance, which can damage overall supply-chain performance and undermine trust in the system.The application study provides quantitative evidence about potential benefits but remains a step toward investigating deployment in real systems.
- Information sharing and trust: The benefits are concentrated among supply-chain members that share information, with greater advantages when all entities at a level participate.Wholesalers seeking similar advantages must share information upstream with manufacturers.
- Data accuracy and misconduct: Blockchain’s immutability and traceability can discourage misconduct because inaccurate data can negatively affect the sharing company’s own performance.Maximum competitiveness and performance require all supply-chain entities to share correct information.
- Implementation and maintainability: Network maintenance costs are negligible at 0,003% of total costs, supporting the use of blockchain as a low-cost trust mechanism.The proposed software connector is presented as a first step toward tools that connect enterprise systems with blockchain and other applications.
5. Conclusions
The paper presents blockchain as a certification mechanism and evaluates it through an integrated enterprise connector and supply-chain simulation. Results indicate benefits for trust, collaboration, performance, information asymmetry, and data-related misconduct.
- Implications: The work addresses limited blockchain knowledge and scarce supply-chain application studies by providing an experimental application and a simulated test environment.The authors position the blockchain-enabled simulation as a basis for exploring further supply-chain phenomena.
- Contribution and approach: Blockchain certifies data origin, authenticity, and integrity while enabling secure information sharing and checks over time.The proposed connector links enterprise information systems with an Ethereum-like blockchain for this purpose.
- Contribution and approach: The study integrates a supply-chain simulation model with blockchain to quantitatively assess benefits through what-if scenario analysis.The simulation is connected through the software connector and REST web services as a replica of a real supply chain.
- Results: Blockchain is reported as a convenient instrument for overcoming collaboration and trust issues in supply chains.The motivation is that partners may withhold information when trust is low, even when data are accessible.
- Results: The application study reports increased overall supply-chain performance and minimized negative consequences of information asymmetry across supply-chain echelons.Trust and information sharing are linked in the paper to supply-chain performance and order variability concerns.
- Results: Blockchain is also reported to discourage misconduct, including data counterfeiting and low data accuracy.The certification approach is intended to support reliable and trustworthy planning and forecasts.