Research — adoption is the bottleneck.

Implementing Machine Learning for Proactive Cyber Threat Detection and Prevention Using the UTAUT Model

A structural-equation-modeling study examining how the four UTAUT constructs predict adoption of machine-learning-based cyber-threat-detection tooling among security practitioners (N = 387). The empirical contribution is to demonstrate that facilitating conditions function as a threshold rather than a co-equal predictor — when below threshold, performance and effort expectancy effects collapse toward zero. The architectural implications follow directly: adoption is not solved by better marketing, it is solved by better facilitating conditions engineered into the product.

Institution

University of the Cumberlands

Chair

Dr. Irvin Heard

Method

SEM · N=387

Year

MMXXVI