Factors Affecting Decision to Adopt Artificial Intelligence During COVID-19 Pandemic Period: Evidence from PLS-SEM and fsQCA

Abstract

The study investigated the factors influencing the demand for Artificial Intelligence (AI) applications in Vietnam from the perspective of Accounting and Auditing. The data was gathered using a quantitative technique based on questionnaires to study a total of 206 accountants and auditors, and was analysed using the PLS-SEM method to determine influential factors and their relationships. In addition, we compare the PLS-SEM results with a recently established approach of panel data fuzzy-set qualitative comparative analysis (fsQCA). The results reveal that the components of finance, tasks, technology, epidemics, knowledge readiness and trust all have a favourable impact on the use of AI in Accounting and Auditing in Vietnam. Besides, the fsQCA results are consistent with the PLS-SEM method, which means that our findings are robust and valid. This study adds empirical evidence to the scientific literature on AI in Accounting and Auditing, which will be immensely beneficial for legislators and businesses looking to improve company efficiency. Besides, applying the fsQCA approach contributes significantly to the existing literature about the research method.