Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?
View / Open Files
Publication Date
2022-06-21Journal Title
Ann Oper Res
ISSN
0254-5330
Publisher
Springer Science and Business Media LLC
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Tsolakis, N., Schumacher, R., Dora, M., & Kumar, M. (2022). Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?. Ann Oper Res https://doi.org/10.1007/s10479-022-04785-2
Abstract
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.
Keywords
Supply chain digitalisation, Artificial Intelligence, Blockchain Technology, Data monetisation, Sustainability, Fish supply networks
Sponsorship
British Council in India (UKUTP201100194)
Engineering and Physical Sciences Research Council (EP/K02888X/1)
EPSRC (via Aston University) (56532 (EP/S036091/1))
EPSRC (via Aston University) (EP/S036091/1)
Embargo Lift Date
2023-06-21
Identifiers
External DOI: https://doi.org/10.1007/s10479-022-04785-2
This record's URL: https://www.repository.cam.ac.uk/handle/1810/337487
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.
Recommended or similar items
The current recommendation prototype on the Apollo Repository will be turned off on 03 February 2023. Although the pilot has been fruitful for both parties, the service provider IKVA is focusing on horizon scanning products and so the recommender service can no longer be supported. We recognise the importance of recommender services in supporting research discovery and are evaluating offerings from other service providers. If you would like to offer feedback on this decision please contact us on: support@repository.cam.ac.uk