Charles, V., Emrouznejad, A. and Gherman, T. (2023) A critical analysis of the integration of blockchain and artificial intelligence for supply chain. Annals of Operations Research. , pp. 1-41. 0254-5330.
| Item Type: | Article |
|---|---|
| Abstract: | The integration between blockchain and artificial intelligence (AI) has gained a lot of attention in recent years, especially since such integration can improve security, efficiency, and productivity of applications in business environments characterised by volatility, uncertainty, complexity, and ambiguity (VUCA). In particular, supply chain is one of the areas that have been shown to benefit tremendously from blockchain and AI, by enhancing information and process resilience, enabling faster and more cost-efficient delivery of products, and augmenting products’ traceability, among others. This paper performs a state-of-the-art review of blockchain and AI in the field of supply chains. More specifically, we sought to answer the following three principal questions: Q1 – What are the current studies on the integration of blockchain and AI in supply chain?, Q2 – What are the current blockchain and AI use cases in supply chain?, and Q3 – What are the potential research directions for future studies involving the integration of blockchain and AI? The analysis performed in this paper has identified relevant research studies that have contributed both conceptually and empirically to the expansion and accumulation of intellectual wealth in the supply chain discipline through the integration of blockchain and AI. |
| Uncontrolled Keywords: | Artificial intelligence, Bibliometric Review, Blockchain, Supply Chain, Systematic Literature Review, Thematic Analysis |
| Creators: | Charles, Vincent, Emrouznejad, Ali and Gherman, Tatiana |
| Faculties, Divisions and Institutes: | Faculties > Faculty of Business & Law > International Strategy & Business |
| Date: | 25 January 2023 |
| Date Type: | Publication |
| Page Range: | pp. 1-41 |
| Journal or Publication Title: | Annals of Operations Research |
| Number of Pages: | 41 |
| Language: | English |
| DOI: | https://doi.org/10.1007/s10479-023-05169-w |
| ISSN: | 0254-5330 |
| Status: | Published / Disseminated |
| Refereed: | Yes |
| Related URLs: | |
| URI: | http://nectar.northampton.ac.uk/id/eprint/19540 |
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