Analysis of Individual Taxpayer Compliance After Implementation of The Coretax 3.0 System
Description
This dataset was gathered to analyze the elements affecting individual taxpayer compliance behaviors after the rollout of the Coretax 3.0 system in Indonesia. The research combines the Unified Model of Electronic Government Adoption (UMEGA) and the Theory of Planned Behavior (TPB) to illustrate how acceptance of technology affects taxpayers' intentions to behave and their resulting compliance-related usage behavior.The study proposed that Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions have a positive effect on taxpayers’ Behavioral Intention to utilize Coretax 3.0. Moreover, it was proposed that Behavioral Intention would positively affect Use Behavior, which signifies compliance-related actions like timely tax reporting, fulfilling tax payments, voluntary compliance, and actual utilization of the digital tax administration system.Information was gathered via a structured questionnaire given to individual taxpayers in Indonesia who previously used Coretax 3.0. A targeted sampling method was utilized, yielding 100 valid responses. Each item on the questionnaire was assessed utilizing a five-point Likert scale, which varied from strongly disagree (1) to strongly agree (5).The dataset includes feedback concerning six latent constructs: Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Behavioral Intention (BI), and Use Behavior (UB). The indicators were modified from recognized literature on technology acceptance and e-government adoption to better suit the context of digital taxation and Coretax 3.0 implementation in Indonesia.The analysis of the data was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that every suggested relationship was statistically significant. Behavioral Intention was positively influenced by Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions. Behavioral Intention, in turn, had a positive effect on Use Behavior. Of all the predictors, Social Influence was identified as the most significant predictor of Behavioral Intention, indicating that government outreach, social support, and endorsements from key stakeholders are crucial in promoting the adoption of digital tax systems. The findings indicate that effective digital tax management relies not just on technological skills and system efficiency but also on taxpayers’ trust, acceptance, social context, and readiness to utilize the system. This dataset is suitable for studies on digital taxation, taxpayer compliance, e-government adoption, technology acceptance, behavioral intention, and digital transformation in the public sector, especially in the context of developing economies.