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Cited by 16Taxation and Compliance StudiesE-Government and Public ServicesTechnology Adoption and User Behaviour

How Technology Can Aid Tax Compliance in the Us Economy

Open access
Adelakun, Beatrice Oyinkansola·2023·Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online)
DOI 10.60087/jklst.vol2.n2.p499
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Abstract

Tax is the price paid by citizens and businesses for their wellbeing and civilization. The payment of tax is a civic duty for every citizens. This study evaluates how technology can aid tax compliance in the US economy. Quantitative and qualitative approach was used for this study making use of 20 respondents. Data collected from respondents were analyzed using descriptive statistical packages (SPSS) where frequencies, percentages, and mean were obtained. The findings of the study shows that majority (50%) of the respondents agreed to proficient in the use of internet while 10% strongly agreed and disagreed to be proficient in the use of internet. The result of the study also shows that 35% strongly agreed with computer usage skills while 15% strongly disagreed to the use of computer and skills. The result obtained for quality system shows that 45% of the respondents agreed that the devices are easy to use compared to 15% who strongly disagreed that the device is easy to use. Devices and systems simplify works result for taxpayer’s shows that 50% agreed to this while 10% strongly disagreed. Conclusively, technology literacy and quality of the system used in tax needs to be focused on for tax compliance to help the economy.

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  • Multiple Pakistani banks are beginning to integrate new and emerging technologies into their operations, such as robotics process automation, AI-powered virtual assistants, and machine learning algorithms for fraud detection and risk management.

    “In its 2024 Financial Stability Review, the SBP reported that multiple Pakistani banks are beginning to integrate new and emerging technologies into their operations, such as robotics process automation, AI-powered virtual assistants, and machine learning algorithms for fraud detection and risk management (Vieira and Sehgal 2018; Taherdoost 2021; Adelakun 2023).”

    From AI-driven financial fraud detection in Pakistan’s banking sector: bridging strategic intent and operational implementation (2026) · cites this paper as Adelakun 2023

    The available indexed passages are journal-page material about Adelakun’s study of technology and US tax compliance; they do not address Pakistani banks. Searches for Pakistani banks, the 2024 Financial Stability Review, automation, and fraud detection found no passage supporting the attributed claim. (LLM, conf=0.74)

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Research works printed but not linked: 4

  1. Derek A. Smith , Nasrullah Abbasi , Cybersecurity in Healthcare: Securing Patient Health Information (PHI), HIPPA Compliance Framework and the Responsibilities of Healthcare Providers , Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online): Vol. 3 No. 3 (2024): Exploring Ethical Dilemmas in Artificial Intelligence and Machine Learning
  2. Patrick Zingisa Msekelwa, Effectiveness of technology in Open Distance Learning: A case study of the University of South Africa , Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online): Vol. 2 No. 1 (2023): Interdisciplinary Approaches to Education, Health, and Technology: Perspectives from South Asia and Beyond
  3. Victor Ogbo Akande, Debo Joseph Oyana, AI-Powered Crisis Management: Revolutionizing Customer Service Emergencies , Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online): Vol. 4 No. 2 (2025): Advancements: Bridging Research and Real-World Applications
  4. Friday Ugbebor, Olushola Aina, Mayowa Abass, Dare Kushanu, Employee Cybersecurity Awareness Training Programs Customized for SME Contexts to Reduce Human-Error Related Security Incidents , Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online): Vol. 3 No. 3 (2024): Exploring Ethical Dilemmas in Artificial Intelligence and Machine Learning

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Authors
Adelakun, B. O.
Affiliations
Illinois State University (US)
Corresponding author
Adelakun, Beatrice Oyinkansola
Venue
Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online)
Publisher
Open Knowledge
Published
2023-08-30
Volume
2
Issue
2
Pages
491-499
ISSN
2959-6386 (ISSN-L)
DOI
10.60087/jklst.vol2.n2.p499
OpenAlex
W4396682905
Cited by
16
References
7
Citations by year
2026: 3 · 2025: 4 · 2024: 9
FWCI
3.26
Type
journal article
Language
en
Open access
Licence
Locations
Journal of Knowledge Learning and Science Technology (publishedVersion, cc-by)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Taxation and Compliance Studies
  • Social Sciences › Political Science and International Relations › E-Government and Public Services
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Keywords
tax compliance, computer skills, technological literacy, tax administration system, ease of use, taxpayers, United States tax system

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