The Role of Big Data Analytics in Accounting Decision-Making Processes in the Digital Economy Era

Abstract

This study aimed to examine the level of big data analytics usage in accounting practices, to investigate the characteristics of accounting decision-making processes, and to analyze the role of big data analytics in accounting decision-making in the digital economy era. A quantitative research approach was employed using a survey design. The sample consisted of 150 professionals involved in accounting, finance, and accounting-related decision-making in business organizations. Data were collected through a structured questionnaire and analyzed using descriptive statistics and multiple linear regression analysis.

           The results indicated that the overall level of big data analytics usage was high (M = 3.609, SD = 0.596), while accounting decision-making processes were at a very high level (M = 4.213, SD = 0.425). The results of multiple linear regression analysis revealed that the use of data analytics tools (B = .188, p = .007), the application of analytical results in decision-making (B = .249, p < .001), and data readiness (B = .143, p = .005) had statistically significant effects on accounting decision-making. All predictors showed positive regression coefficients, indicating relationships in the same direction. The regression model was statistically significant (F = 14.256, p < .001) and explained 22.7% of the variance in accounting decision-making (R² = 0.227).

          The findings suggest that big data analytics is associated with the enhancement of accounting decision-making quality, particularly in terms of systematic processes, prudence, and transparency. These results provide useful implications for organizations in developing effective applications of data analytics technologies in accounting practices within the digital economy context.