Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation

441Citations
Citations of this article
1.0kReaders
Mendeley users who have this article in their library.
Get full text

Abstract

The logistics and supply chain management (SCM) field is experimenting with the integration of blockchain, a cutting-edge, and highly disruptive technology. Yet, blockchain is still nascent, and the extant literature on this technology is scarce, especially as regards the relationship between blockchain and SCM. Additionally, existing studies have not yet addressed sufficiently the enablers of blockchain adoption and the interplay with supply chain performance. In order to reduce this gap, this study aims to examine the potential influence of blockchain on supply chain performance. We draw on the literature on technology adoption and supply chain performance, as well as on the emerging blockchain literature, to develop and test a model in two countries, namely India and the US. Accordingly, we administered a survey in order to review the opinions and views of supply chain practitioners. The results support the model and indicate that blockchain applications can improve supply chain performance. In particular, our findings suggest that knowledge sharing and trading partner pressure play an important role in blockchain adoption, and that supply chain performance is significantly influenced by supply chain transparency and blockchain transparency. Another finding was the inexistence of evidence for a moderation effect of the industry variable on the outcomes. The research conclusions have substantial managerial and theoretical implications. Our model contributes mainly to the theoretical advancement of SCM-blockchain, thus allowing scholars to adapt our validated model.

Cite

CITATION STYLE

APA

Fosso Wamba, S., Queiroz, M. M., & Trinchera, L. (2020). Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation. International Journal of Production Economics, 229. https://doi.org/10.1016/j.ijpe.2020.107791

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free