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This study investigated the effects of digitalisation of tax administration on tax compliance among selected small and medium enterprises (SMEs) in Ibadan North West Local Government Oyo State, Nigeria. The study was anchored on the Technology Acceptance Model (TAM), which explains technology adoption through perceived usefulness, perceived ease of use, and external constraints. A descriptive survey design was adopted, and structured questionnaires were administered to 367 SMEs across key business sectors. Of these, 352 valid responses were analysed using SPSS through descriptive statistics and ANOVA. The study examined the level of digital technology adoption, the perceived influence of digital tax administration on compliance, the drivers of non-compliance, and preferred policy measures for improvement. Findings revealed generally low digital technology adoption among SMEs, with 42.9% reporting very low adoption and 36.6% reporting low adoption. The major barriers were poor internet connectivity, high cost of technology and digital tools, limited technical skills, and inadequate awareness. Perceptions of digital tax reforms showed limited realised compliance benefits, as 48.9% of respondents reported no noticeable improvement in compliance, 21.3% reported improved ease of compliance, while 29.8% stated that compliance had become more difficult. Non-compliance was mainly linked to limited awareness of tax obligations, weak enforcement, affordability challenges, and low digital capability. The study concludes that digitalisation can improve SME tax compliance only when foundational readiness gaps are addressed. It recommends improving broadband reliability, reducing digital access costs, strengthening taxpayer education, simplifying digital tax processes, providing practical training, and ensuring consistent and fair enforcement.

Since the seminal work of Allingham and Sandmo in 1972, tax evasion has been firmly established as a complex and multifaceted global issue. This study posits that one practical approach to mitigate tax evasion in developing countries is to utilise Cressey’s (1953) fraud triangle model as a framework for analysing taxpayers’ decisions. The theory explains why individuals commit fraud, including tax evasion, through three key factors: pressure, opportunity, and rationalisation. The study used the theoretical research method (literature review) as postulated by Alm (2011) to examine and explain the tax evasion phenomenon. The findings suggest that utilising the fraud triangle model (in the context of new technology such as artificial intelligence, machine learning, data mining and deep learning) will be beneficial to policymakers. First, it will assist tax authorities in profiling taxpayers by focusing on behaviours and other factors (economic and non-economic) that influence tax evasion. Next, with this framework, tax authorities can formulate advanced risk management strategies that directly tackle the fundamental elements of the Fraud Triangle, thereby improving their efforts against tax evasion. Furthermore, it offers invaluable guidance to lawmakers and policymakers, preparing them to develop strong legislation aimed at narrowing the tax gap from aggressive tax avoidance and evasion schemes. Finally, the framework can illuminate broader economic or industry-wide circumstances that increase the overall risk of tax evasion, facilitating proactive measures before difficulties arise. Thus, integrating the fraud triangle framework into the tax administration process can improve the efficiency and effectiveness of tax authorities and contribute to fairer tax systems in developing countries.

MSMEs contribute more than 60% of economic growth. 99% of business operators in Indonesia are MSMEs. However, the contribution of MSMEs in tax revenue is still low. The government has sought to improve tax compliance for the MSME sector by the existence of an Account Representative position (AR) and an online reporting system, namely E Filling. This study aims to determine whether the role of Account representative (AR) and the use of E Filling can affect the compliance of MSMEs in reporting tax. The data used are MSMEs in the area of the Primary Tax Office in Duren Sawit. The number of questionnaires distributed was 120 and could be processed was 95 questionnaires. The analytical tool used is the Structure Equation Model (SEM). The results conclude that the value of the role of AR and the use of E-Filling affect the compliance of MSMEs in reporting taxes partially and simultaneously.