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

被引:112
作者
Tsolakis, Naoum [1 ,2 ]
Schumacher, Roman [3 ]
Dora, Manoj [4 ]
Kumar, Mukesh [3 ]
机构
[1] Univ Cambridge, Ctr Int Mfg, Sch Technol, Inst Mfg IfM,Dept Engn, Cambridge CB3 0FS, England
[2] Int Hellen Univ, Sch Econ & Business Adm, Dept Supply Chain Management, Thermi 57001, Greece
[3] Univ Cambridge, Sch Technol, Inst Mfg IfM, Dept Engn,Ind Resilience Res Grp, Cambridge CB3 0FS, England
[4] Brunel Univ London, Brunel Business Sch, London UB8 3PH, England
基金
英国工程与自然科学研究理事会;
关键词
Supply chain digitalisation; Artificial intelligence; Blockchain technology; Sustainability; Data monetisation; Fish supply networks; SEAFOOD TRACEABILITY; BIG DATA; MANAGEMENT; DESIGN; FUTURE; TECHNOLOGY; QUALITY; CHALLENGES; OPERATIONS; LOGISTICS;
D O I
10.1007/s10479-022-04785-2
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
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.
引用
收藏
页码:157 / 210
页数:54
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