Abstract
The increasing use of blockchain technology in various industries has generated a significant amount of interest among researchers and practitioners. This study aims to determine a predictive classification model of technological service innovation adoption for blockchain implementation across cultures. Questions of the research are: 1) does national culture impact the prediction of blockchain adoption across countries? and 2) if so, what cultural dimensions have the highest impact on service innovation adoption rates, across and between countries? and finally, 3) are penetration rates of blockchain adoption significantly different across countries? Industry, country, and managerial level variables along with adoption rates are examined. Model formulation and analysis is supported using a neural network to predictively classify firm and country innovation adoption. This study helps organizations understand the factors that impact the adoption of blockchain technology and will also inform policymakers about the potential benefits and cultural challenges of blockchain implementation.
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