The findings suggest that digital tax supervision depends not only on technological capabilities but also on taxpayers’ perceptions of audit risks and their confidence in the institutions administering the system.
Technology Is Changing How Tax Authorities Monitor Compliance
Tax administration is increasingly incorporating digital systems to process information, identify potential risks, and support decisions about which taxpayers may require further examination. Algorithmic risk profiling can help authorities analyze taxpayer data and identify patterns that may indicate possible noncompliance.
However, the use of algorithms also raises questions about transparency, fairness, and public trust. Taxpayers may respond differently to digital supervision depending on how they perceive the likelihood of an audit, how much they trust the tax administration, and whether they consider algorithm-based monitoring reliable and fair.
Understanding these behavioral factors is important because technological improvements alone do not necessarily guarantee better compliance. Tax administration also depends on how taxpayers interpret and respond to digital oversight.
Survey of 200 Taxpayers in Surabaya
The study, titled “Taxpayer Behavioral Adaptation to Algorithmic Risk Profiling and Emerging Compliance Strategy Displacement,” examined the relationship between algorithmic risk profiling, perceived audit risk, trust in digital tax administration, and taxpayer compliance behavior.
The research involved 200 taxpayers in Surabaya, Indonesia. The respondents included individual taxpayers, who accounted for 71% of the sample, and business taxpayers, who represented the remaining 29%. The largest age group was 31–40 years old, accounting for 39% of respondents. In addition, 58.5% reported having at least three years of experience with digital tax services.
The researcher used a survey-based quantitative approach and multiple regression analysis to examine the relationships between the variables. The analysis assessed whether taxpayers’ perceptions of algorithmic risk profiling, perceived audit risk, and trust in digital tax administration were associated with compliance behavior.
The results provide evidence of statistically significant relationships within the surveyed group. However, because the study focused on taxpayers in one city and relied on self-reported responses, its findings should not automatically be generalized to all Indonesian taxpayers.
Perceived Audit Risk Has the Strongest Association with Compliance
The regression results identified perceived audit risk as the strongest of the three reported predictors of taxpayer compliance behavior. Its standardized regression coefficient was β = 0.341, with a significance level of p < 0.001.
Trust in digital tax administration also showed a significant positive relationship with compliance behavior, with a coefficient of β = 0.298 and p < 0.001. Meanwhile, perceptions of algorithmic risk profiling had a coefficient of β = 0.286, also with p < 0.001.
These findings indicate that all three factors were positively associated with compliance behavior in the study. Among them, perceived audit risk had the largest standardized coefficient, followed by trust in digital tax administration and perceptions of algorithmic risk profiling.
The regression model reported an R² value of 0.524. This means that the three predictors collectively explained 52.4% of the variation in taxpayer compliance behavior within the analyzed data. It does not mean that compliance increased by 52.4%.
The results highlight the importance of taxpayers’ perceptions of enforcement. When taxpayers perceive a meaningful likelihood of an audit, compliance behavior may be associated with that perceived risk. Nevertheless, the survey findings establish statistical associations rather than proving that any one factor directly causes changes in compliance.
Public Trust Remains Important in Digital Tax Supervision
The positive relationship between trust in digital tax administration and compliance suggests that taxpayers’ confidence in digital systems is an important consideration for tax authorities.
Digital tax services must be perceived as credible, consistent, and accountable. If taxpayers do not understand how their information is processed or how algorithm-based assessments influence administrative decisions, concerns about fairness and transparency may undermine confidence.
For this reason, digital tax modernization should not focus exclusively on automation. Authorities also need to communicate how digital systems are used, clarify the purposes of data collection, and maintain appropriate human oversight of consequential decisions.
Transparent procedures can help taxpayers understand their responsibilities and the role of technology in tax administration. Clear explanations of audit procedures and opportunities to question or correct inaccurate information may also support perceptions of procedural fairness.
Implications for Indonesia’s Tax Administration
The study offers several considerations for the continued digitalization of tax administration in Indonesia.
First, authorities should communicate tax audit procedures clearly so taxpayers understand their obligations and the consequences of noncompliance. Second, algorithmic risk profiling should be supported by transparent governance, appropriate data protection, and accountability mechanisms. Third, digital tax services should be designed to strengthen public confidence rather than rely solely on automated monitoring.
Human review remains relevant when algorithmic assessments influence decisions that may significantly affect taxpayers. Such oversight can help identify errors, address unusual circumstances, and provide a way to challenge potentially incorrect assessments.
The findings should also be interpreted in light of the study’s limitations. The sample consisted of 200 taxpayers in Surabaya, and the data were based on self-reported responses. Further research involving taxpayers from different regions and using additional methods could help establish whether similar relationships appear across Indonesia.
Overall, the study suggests that effective digital tax administration involves more than identifying risks through algorithms. Perceived enforcement, institutional trust, and taxpayer perceptions of digital monitoring are all relevant to understanding compliance behavior.
Author Profile
Danny Wibowo is affiliated with Sekolah Tinggi Ilmu Ekonomi Indonesia Surabaya (STIESIA), Indonesia. His 2026 article examines taxpayer behavioral responses to algorithmic risk profiling and emerging compliance strategies in digital tax administration. The source information provided for this article does not specify further biographical details.
Research Source
Wibowo, D. (2026). Taxpayer Behavioral Adaptation to Algorithmic Risk Profiling and Emerging Compliance Strategy Displacement.
Journal: International Journal of Management and Business Intelligence (IJMBI)
DOI: https://doi.org/10.59890/ijmbi.v4i5.63
Journal website: https://journalijmbi.my.id/index.php/ijmbi
ISSN-E: 3025-5589
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