A model for predicting the behavioral components of blockchain adoption in the banking industry using agent-based modeling

Blockchain is a technology that can be used in various organizations. Blockchain, through a decentralized computer network, leads to the facilitation of high-level transactions of organizations as well as their registration, in order to better respond to people's needs. In this research, a preliminary conceptual model consisting of the behavioral factors of blockchain technology acceptance in the banking industry, which is derived from theoretical literature and research background, is presented. Behavioral factors include facilitating conditions, attitude, literacy and skill, perceived risk, technology, perceived behavioral control, external motivation, internal motivation, competition and mental norm. Then, in order to check the fit of the model, structural equation modeling and smart pls software were used using a researcher-made questionnaire extracted from the research model. For this purpose, due to the unlimited size of the statistical population, 384 samples were randomly selected and the questionnaire was distributed among them. The result indicates that all the relationships are significant and the factors cause more than 80% of changes in technology adoption. In addition, agent-based modeling and Anylogic software have been used in order to predict changes in the adoption of blockchain technology over time, affected by the identified behavioral factors. The results showed that with the improvement of behavioral factors, the adoption of blockchain technology increases over time. In this study, insight is generated for key decision makers and relevant policy makers to propagate the adoption of blockchain technology in the banking industry.