Evidence map›Paper›PMID 35755830›Full record

ArticleAnnals of operations research2022

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

Naoum Tsolakis, Roman Schumacher, Manoj Dora, Mukesh Kumar

Abstract read
In one paragraph

Article in Annals of operations research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Naoum TsolakisCentre for International Manufacturing, Institute for Manufacturing (IfM), Department of Engineering, School of Technology, University of Cambridge, Cambridge, CB3 0FS UK.ORCID 0000-0003-2042-7047
Roman SchumacherIndustrial Resilience Research Group, Institute for Manufacturing (IfM), Department of Engineering, School of Technology, University of Cambridge, Cambridge, CB3 0FS UK.ORCID 0000-0003-0764-5867
Manoj DoraBrunel Business School, Brunel University London, London, UB8 3PH UK.ORCID 0000-0003-4730-8144
Mukesh KumarIndustrial Resilience Research Group, Institute for Manufacturing (IfM), Department of Engineering, School of Technology, University of Cambridge, Cambridge, CB3 0FS UK.ORCID 0000-0002-1961-5078

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Artificial intelligenceBlockchain technologyData monetisationFish supply networksSupply chain digitalisationSustainability

Identifiers

PMID35755830
PMCPMC9212209

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.