Abstract

Using a systematic review of literature, this study identifies the potential impact of blockchain solutions for augmenting supply chain resilience (SCR) to cybercrime. This rich literature synthesis forms the basis of a novel theoretical framework that provides guidance and insight for blockchain adopters and vendors as well as delineate palpable benefits of this novel technology. An interpretivist philosophical design and inductive reasoning are adopted to conduct the systematic review of literature. A total of 867 papers were retrieved from Scopus database between the years of 2016 and 2020 and subsequently analysed via abductive reasoning, grounded theory and a thematic meta-analysis; where the latter was achieved using a scientometric approach and software tools such as VOS viewer and NVivo. Scientometric analysis revealed the most prolific countries, sources, publications and authors who reside at the vanguard of blockchain developments and adoption. Subsequent grounded theory analysis identified six main clusters of research endeavour viz: “case study”, “challenges and opportunity”, “traceability”, “smart contract” “blockchain and IoT” and “data security”. From 28 SCR metrics identified within literature, five were found to have been positively impacted by blockchain technology solutions, namely: “visibility”, “collaboration”, “integration”, “risk management” and “information sharing.” Prominent applications of blockchain technology in practice were “traceability systems” and “smart contracts” which are often implemented separately or in combination and primarily in food supply chains. This research constitutes the first study to critically synthesise extant literature for evaluation of blockchain solutions’ implication on SCR metrics. New perspectives obtained provided a basis for the novel theoretical framework for implementation that will be valued by software developers and adopting organizations, whilst creating new direction for researchers interested in blockchain technology.

Highlights

  • Since the discovery of blockchain technology’s viability in environments other than original cryptocurrency practices, applications have exponentially proliferated in diverse industrial sectors such as: insurance [1]; content distribution [2]; logistics [3,4]; travel [5]; healthcare [6,7]; e-commerce [8]; and banking systems [9]

  • External risks are associated with unexpected events occurring extrinsically that stifle the supply chain system and induce a ripple effect that prolong the recovery from the disruption [21,22]

  • Network maps of scientometric data generated in VOS viewer comprise nodes signifying different items that present an object of interest such as publications, researchers, countries or keywords [35,83,84]

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Summary

Introduction

Since the discovery of blockchain technology’s viability in environments other than original cryptocurrency practices, applications have exponentially proliferated in diverse industrial sectors such as: insurance [1]; content distribution [2]; logistics [3,4]; travel [5]; healthcare [6,7]; e-commerce [8]; and banking systems [9]. Other examples of internal risks are information technology problems or breakdowns, uncertainties in lead times, power outages, equipment malfunctions and systemic failures [27] These numerous internal and external risks (and their frequency of occurrence) increase the vulnerability of supply chains and necessitate development of risk mitigation methods and strategies to engender organisational resilience and preparedness [20,28]. Despite these risks elucidated upon, circa 69% of organisations globally have no complete visibility of their supply chains [29] and 30% of organisations fail to analyse the source of disruptions [30]. New insights (including a novel framework) generated will serve to incite wider polemic debate but will provide much needed guidance and clarification for software developers and adopting organizations

Methodology
Grounded Theory Technique
Supply Chain Resilience
Supply Chain Resilience Metrics
Blockchain Technology
Analysis and Findings
Co-Occurrence of Keywords
Findings from Grounded Theory Analysis
Conclusions
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