Identifying the important determinants of the adoption of AI-based accounting software for the SMEs in Pakistan. Binary Logistic Regression
Digital accounting with artificial intelligence technology represents a crucial means for facilitating the productivity and competitiveness of small and medium enterprises in developing countries. In regard to the state of Pakistan, the implementation and use of accounting software with artificial intelligence technology in SMEs has yet to reach satisfactory standards despite the crucial part played by SMEs regarding economic resilience in the country. This research aims to explore the crucial factors of the implementation process of accounting software with artificial intelligence technology from a quantitative research perspective. In order to discuss the research objectives and achieve its aims, the research employs the technology acceptance model and organization environment theory. A cross-sectional research design method was adopted to investigate 250 owners/managers of SMEs in the main Pakistani cities. To determine the values of perceptual variables, a 5-point Likert scale was adopted; yet, adoption is a binary variable. By using logistic regression analysis, hypotheses were tested. The results indicate that perceived ease of use and competitive pressure are significant positive predictors, yet perceived cost and security concerns are significant negative predictors. A positive relationship between the owner’s level of education and adoption is marginally significant. The Nagelkerke R² is 58%. The results indicate that, apart from using the basic applications developed through this technology, the adoption mechanism is itself a complex process that is fueled by cost and data security concerns. Implications of this research study would include developing cost-effective models by software companies regarding data security or designing a subsidy program by governments, according to the cost and/or data security concerns of Pakistani SME businessmen.