Exploring the influencing factors of blockchain technology adoption in national quality infrastructure: a Dual-Stage structural equation model and artificial neural network approach using TAM-TOE framework

Abstract

This study explores the adoption of blockchain technology within the Ethiopian National Quality Infrastructure (NQI). Data from 178 professionals representing various organizations and roles were collected to investigate key adoption factors. By integrating the Technology Acceptance Model (TAM) and the Technology-Organization-Environment (TOE) framework, external factors (Technology Compatibility, Relative Advantage, Government Support, and Policy) and internal factors (perceived usefulness, perceived ease of use, and intention to use) were examined. A dual-stage analytical approach involving partial least square-based structural equation model (PLS-SEM) and artificial neural network (ANN) analyses was employed. The findings emphasize the significance of technological compatibility, perceived usefulness, and top management support as determinants of blockchain adoption in the NQI. Particularly, the compatibility of the existing system emerges as the most influential factor in adopting blockchain technology within the Ethiopian NQI. This study enhances the understanding of blockchain adoption within the NQI context, providing valuable insights for successful implementation. It contributes to the existing knowledge in this area and offers practical implications for quality infrastructure management.