Article Details
Vol. 6 No. 1 (2026): Juli
Artificial Intelligence, Coretax, Digital Tax Administration, Employee Performance, Service Training
Purpose: Drawing on the Resource-Based View (RBV), this study investigates the association between employees’ perceptions of artificial-intelligence-enabled tax services, digital tax administration, and service training with frontline tax employee performance at two Pratama Tax Offices in Bandar Lampung, Indonesia.
Methods: A quantitative census survey was conducted involving all 26 employees in the service sections of KPP Pratama Bandar Lampung Satu and Dua. Saturated sampling was applied due to the limited population size. Data were collected using 16 Likert-scale items representing four constructs and analyzed using IBM SPSS Statistics 26 through validity and reliability testing, regression diagnostics, multiple regression analysis, t-tests, F-tests, and adjusted R² evaluation.
Results: AI services showed no significant effect on employee performance (B = -0.043; p = .698), while digital tax administration had a positive and significant effect (B = 0.596; p = .007). Service training was insignificant (B = -0.170; p = .221). The model was significant, F(3,22) = 4.278, p = .016, with an adjusted R² of .282.
Limitations: The study is limited by its small and localized sample, restricting generalizability. Self-reported measures may also introduce response bias.
Conclusion: Digital tax administration represents the strongest performance-related resource, while AI and training require stronger integration with organizational routines.
Contributions: This study contributes to technology and public administration research by demonstrating that RBV resources generate different performance pathways depending on organizational integration and implementation mechanisms.nisms.
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