Title:
Data Analytics and Efficiency of Companies Income Tax Revenue Generation in Nigeria

Authors:
Dada, Samuel. Olajide., Olayinka Moses Ifayemi., & Mba Okoko Obasi, Nigeria

Abstract:

Globally, tax revenue plays a crucial role in government revenue generation. In Nigeria, the efficiency of company income tax has been hampered by various inefficiencies and inaccurate data analysis. Evidence suggests that data analytics has the potential to enhance the efficiency of company income tax revenue collection; however, the extent of its effectiveness remains unclear. This study, therefore, examined the impact of data analytics on the efficiency of company income tax revenue generation in Nigeria. A survey research design was adopted, utilizing a structured questionnaire for data collection. The population comprised approximately 2,000,000 individuals, including employees of the Federal Inland Revenue Service (FIRS), professional accountants, tax consultants, and other experts with knowledge of data analytics and tax-related matters in Nigeria. The Taro Yamane formula was used to determine a sample size of 400, selected using a purposive sampling technique. The validity and reliability of the research instrument were confirmed through the Kaiser-Meyer-Olkin (KMO) and Bartlett’s tests, with Cronbach’s alpha values ranging between 0.798 and 0.880. The study achieved a 96% response rate. Both descriptive and inferential statistical methods were used to analyze the data. Findings revealed that a significant proportion of respondents agreed that data analytics enhances the efficiency of company income tax revenue generation. Furthermore, regression analysis showed that data analytics had a joint significant effect on the efficiency of tax revenue generation from companies in Nigeria. The study recommends that policymakers and tax administrators leverage data analytics to improve tax revenue generation in the country.

DOI: https://doi.org/10.51505/IJEBMR.2025.9534