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The purpose of this study is to identify the key data categories and characteristics defined by asset information requirements (AIR) and how this affects the development and maintenance of an asset information model (AIM) for a blockchain-based digital twin (DT).

A mixed-method approach involving qualitative and quantitative analysis was used to gather empirical data through semistructured interviews and a digital questionnaire survey with an emphasis on AIR for blockchain-based DTs from a data-driven predictive analytics perspective.

Based on the analysis of results three key data categories were identified, core data, static operation and maintenance (OM) data, and dynamic OM data, along with the data characteristics required to perform data-driven predictive analytics through artificial intelligence (AI) in a blockchain-based DT platform. The findings also include how the creation and maintenance of an AIM is affected in this context.

The key data categories and characteristics specified through AIR to support predictive data-driven analytics through AI in a blockchain-based DT will contribute to the development and maintenance of an AIM.

The research explores the process of defining, delivering and maintaining the AIM and the potential use of blockchain technology (BCT) as a facilitator for data trust, integrity and security.

This paper aims to contribute to the debate about the value of blockchain for supply chain management by assessing empirical evidence on the relationship between blockchain and supply chain performance.

The authors conducted a structured review of the academic literature to identify and assess papers providing empirical insight on operational blockchain applications. The authors complement the findings from this review with primary empirical data from 11 interviews with blockchain providers, users and experts involved in four recent projects.

The paper presents an integrated research framework that illustrates the impact of blockchain on supply chain performance. The findings highlight that blockchain can affect supply chain performance directly – via one of its core technological features – and indirectly via the broader business project through which blockchain technology is implemented.

Insights from this paper should provide managers with a more nuanced understanding of how blockchain technology can be leveraged to address important supply chain management challenges.

Prior research addressing the relationship between blockchain and supply chain performance mostly discusses potential performance effects of blockchain, presents individual blockchain applications and/or provides little explanation for how the core technological features of blockchain affect supply chain performance. This paper systematically assesses the ways in which blockchain can affect supply chain performance. In doing so, it goes beyond the initial hype around blockchain technology while countering some of the more recent critiques.