Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?

• Published in: Annals of operations research 2023-08, Vol.327 (1), p.157-210
• Main Authors: Tsolakis, Naoum, Schumacher, Roman, Dora, Manoj, Kumar, Mukesh
• Format: Article
• Language: English
• Subjects: Analysis; Artificial intelligence; Blockchain; Business and Management; Canned foods industry; Combinatorics; Cryptography; Decision making; Digitization; Information flow; Logistics; Management; Materials handling; Operations research; Operations Research/Decision Theory; Original Research; Supply chains; Sustainability; Sustainable development; Technology application; Theory of Computation
• ISSN: 0254-5330; 1572-9338
• DOI: 10.1007/s10479-022-04785-2

Digitalisation is expected to transform end-to-end supply chain operations by leveraging the technical capabilities of advanced technology applications. Notwithstanding the operations-wise merits associated with the implementation of digital technologies, individually, their combined effect has been overlooked owing to limited real-world evidence. In this regard, this research explores the joint implementation of Artificial Intelligence (AI) and Blockchain Technology (BCT) in supply chains for extending operations performance boundaries and fostering sustainable development and data monetisation. Specifically, this study empirically studied the tuna fish supply chain in Thailand to identify respective end-to-end operations, observe material and data-handling processes, and envision the implementation of AI and BCT. Therefore, we first mapped the business processes and the system-level interactions to understand the governing material, data, and information flows that could be facilitated through the combined implementation of AI and BCT in the respective supply chain. The mapping results illustrate the central role of AI and BCT in digital supply chains’ management, while the associated sustainability and data monetisation impact depends on the parameters and objectives set by the involved system stakeholders. Afterwards, we proposed a unified framework that captures the key data elements that need to be digitally handled in AI and BCT enabled food supply chains for driving value delivery. Overall, the empirically-driven modelling approach is anticipated to support academics and practitioners’ decision-making in studying and introducing digital interventions toward sustainability and data monetisation.