blockchain {bnRep} | R Documentation |
blockchain Bayesian Network
Description
A machine learning based approach for predicting blockchain adoption in supply chain.
Format
A discrete Bayesian network to predict the probability of blockchain adoption in an organization. Probabilities were given within the referenced paper. The vertices are:
- BA
Blockchain adoption (Low, High);
- COMPB
Compatibility (Low, High);
- COMPX
Complexity (Low, High);
- CP
Competitive pressure (Low, High);;
- PEOU
Perceived ease of use (Low, High);
- PFB
Perceived financial benefits (Low, High);
- PR
Partner readiness (Low, High);
- PU
Perceived usefulness (Low, High);
- RA
Relative advantage (Low, High);
- TE
Training and education (Low, High);
- TKH
Technical know-how (Low, High);
- TMS
Top management support (Low, High);
@return An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
References
Kamble, S. S., Gunasekaran, A., Kumar, V., Belhadi, A., & Foropon, C. (2021). A machine learning based approach for predicting blockchain adoption in supply chain. Technological Forecasting and Social Change, 163, 120465.