Prediction of Mutual Interdependencies Among the Drivers of Blockchain for Enhancing the Supply Chain Dynamics

Authors

  • Janpriy Sharma Department of Industrial and Production Engineering, Dr. B.R. Ambedkar National Institute of Technology, India https://orcid.org/0000-0002-9826-1203
  • Mohit Tyagi Department of Industrial and Production Engineering, Dr. B.R. Ambedkar National Institute of Technology, India https://orcid.org/0000-0002-7995-6990
  • Anish Sachdeva Department of Industrial and Production Engineering, Dr. B.R. Ambedkar National Institute of Technology, India
  • Sarthak Dhingra Department of Industrial and Production Engineering, Dr. B.R. Ambedkar National Institute of Technology, India
  • Mangey Ram Department of Mathematics, Graphic Era University, India

DOI:

https://doi.org/10.47852/bonviewJCCE2202433

Keywords:

performance system, ISM-MICMAC, neutrosophic set, Neutrosophic-based ranking

Abstract

Nowadays, demand for customized products is increasing in the era of globalization and competitiveness. But this has burdened the supply chain (SC) performance and demands for the digitalization of its operation to enhance the transparency within its operation. As SCs are operating across regional boundaries, their dynamics need to be aligned with the paradigm of industry 4.0 technologies. Blockchain is one among those, which promises to enhance product traceability and bring transparency to its operation. But, the adoption of blockchain is not getting much attention, which indicates the need of an analysis of its drivers. As the avenues of information technology are getting attention, drivers of blockchain adoption are identified in this study. Furthermore, to reveal the mutual interrelationships between the drivers interpretive structural modelling-Cross-Impact Matrix Multiplication Applied to Classification (ISM-MICMAC) analysis is exercised. Driving factors are further analyzed by the Neutrosophic-based robust ranking, resulting in the primacy of the drivers. The outcomes of the present work substantially outrank the drivers, relative to its impact in the adoption of blockchain operations in SC performance systems. It provides a structured approach to managers for aligning SC operations with blockchain technology.

 

Received: 29 September 2022 | Revised: 1 November 2022 | Accepted: 14 November 2022

 

Conflicts of Interest
The authors declare that they have no conflicts of interest to this work.

 

Data Availability Statement
Data available on request from the corresponding author upon reasonable request.

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Published

2022-12-01

How to Cite

Sharma, J. ., Tyagi, M., Sachdeva , A. ., Dhingra, S., & Ram, M. (2022). Prediction of Mutual Interdependencies Among the Drivers of Blockchain for Enhancing the Supply Chain Dynamics. Journal of Computational and Cognitive Engineering, 3(2), 141–152. https://doi.org/10.47852/bonviewJCCE2202433

Issue

Section

Research Articles