Process Model for Claim and Payment Management in a Construction Supply Chain Based on Smart Contracts

Abstract

The construction supply chain often faces challenges such as contract disputes, inefficient payments, and difficult claim management due to its complexity and the involvement of multiple parties. Most existing solutions focus on optimizing contract terms or improving local processes, but they lack systemization, automation, and transparency. Therefore, this study proposes a claim and payment process management model based on blockchain and smart contracts, aiming to achieve digital and automated governance of the construction supply chain. The study constructs three types of smart contracts: The supply chain decomposition smart contract automatically divides engineering projects into independent billing cycles. The billing unit smart contract monitors the compliance of construction. The negotiation and settlement smart contract automatically handles disputes and payments. These three types of smart contracts work together to form a decentralized dynamic management framework. Through simulation experiments comparing the traditional process with the smart contract model, the results show that in scenarios with a high probability of claims and a large proportion of construction defects, the capital flow efficiency of the smart contract model is increased by more than 20%, and it shows stronger stability under high claim risks. The contribution of this study lies in combining blockchain technology with the logic of supply chain decomposition, proposing a smart contract system applicable to dynamic engineering projects, thus providing a digital processing method for the integrated management of claims and payments in the construction supply chain. This digital dynamic management method can ultimately systematically solve the island problem in supply chain claim research. Its automated and transparent characteristics help reduce dispute costs and enhance trust among multiple parties, which has important practical significance for improving the overall efficiency of the industry.