Return to search

Barriers to the adoption of blockchain technology in business supply chains: a total interpretive structural modelling (TISM) approach

Yes / Blockchain is an emerging technology with a wide array of potential applications. This
technology, which underpins cryptocurrency, provides an immutable, decentralised, and
transparent distributed database of digital assets for use by firms in supply chains. However,
not all firms are appropriately suited to adopt blockchain in the existing supply chain primarily
due to their lack of knowledge on the benefits of this technology. Using Total Interpretive
Structural Modelling (TISM) and Cross-Impact Matrix Multiplication Applied to
Classification (MICMAC), this paper identifies the adoption barriers, examines the
interrelationships between them to the adoption of blockchain technology, which has the
potential to revolutionise supply chains. The TISM technique supports developing a contextual
relationship based structural model to identify the influential barriers. MICMAC classifies the
barriers in blockchain adoption based on their strength and dependence. The results of this
research indicate that the lack of business awareness and familiarity with blockchain
technology on what it can deliver for future supply chains, are the most influential barriers that
impede blockchain adoption. These barriers hinder and impact businesses decision to establish
a blockchain-enabled supply chain and that other barriers act as secondary and linked variables
in the adoption process.

Identiferoai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/18202
Date25 November 2020
CreatorsMathivathanan, D., Mathiyazhagan, K., Rana, Nripendra P., Khorana, S., Dwivedi, Y.K.
Source SetsBradford Scholars
LanguageEnglish
Detected LanguageEnglish
TypeArticle, Accepted manuscript
Rights© 2021 Taylor & Francis. The Version of Record of this manuscript has been published and is available in International Journal of Production Research 2021, https://doi.org/10.1080/00207543.2020.1868597.

Page generated in 0.002 seconds