Ensuring construction material provenance using Internet of Things and blockchain: Learning from the food industry

Abstract

Ensuring material provenance is widely considered a promising solution to the persistent issues related to material fraudulence in the construction industry. However, current strategies of managing construction logistics and supply chain perplex provenance tracing and tracking by adding too many intermediaries and using low technologies. By learning from the food industry which shares similar complexity, prolonged supply chain, and numerous stakeholders, this research aims to develop a framework deployable for material provenance tracing and tracking in the construction industry. It does so by mixing the uses of (a) cross-sectoral learning; (b) design science research; and (c) internet of things (IoT) and blockchain technology. The developed framework has four interconnected layers, namely the business layer with different stakeholders and activities, the IoT layer to collect the provenance footprints, the blockchain layer with a mainchain to store open provenance data and sidechains to store organizational private data, and the application layer to facilitate the management of quality, safety, payment, logistic and supply chain, and sustainability. The underpinning philosophy of the framework is to capture the IoT-driven provenance footprints and put them in custody in blockchain. The framework is further illustrated and refined by using a pilot construction project in Hong Kong, which was endeavored to track steel provenance from its adjacent Pearl River Delta, the so-called “World's Factory”. The framework shows enormous prospects, e.g., adopting digital twins, lifecycle traceability, improved efficiency, and transparent operations, meanwhile facing challenges, e.g., under-developed regulations, scalability issues, and information leakage risks, which all call for future research.