blockchain: blockchain Bayesian Network

In bnRep: A Repository of Bayesian Networks from the Academic Literature

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.

bnRep documentation built on April 12, 2025, 1:13 a.m.