Non-Administrative Models to Deteriorate Tax Evasion, a Socio-Cybernetic Application using NLP Archives for Taxpayer Euphoria Formation

Vasilios George Kanavas, Athanasios Dimitrios Zisopoulos and Razis Dimitrios

Research in Applied Economics, 2017, vol. 9, issue 4, 25-40

Abstract: With our Socio-Cybernetic Application we present a minimal approach to reduce tax evasion. Theoretically we use proven theories of Neuro Linguistic Processing, Christian Virtues influence, Cognitive Psychology guidelines, Tax collection and law enforcement principles. Our database are taxpayers, payments Beneficiary, Neuro Linguistic Programming reference points, Virtue points, etc. From the last two we create the Personal Human Space database with 1803 records. Then we analyze every person in the Taxpayers and money Receivers database and according to the theoretical guidance we formulate a specific limited human-space diagram for all 7 million persons and legal entities. As an example, we demonstrate the exact math and Matlab methodology to match a Taxpayer and money beneficiary with scoreboard 65 non-zero diagram points. The working system could be useful for Financial Intelligent Units, Economic Law enforcement agencies and Immigration Authorities.

Keywords: Tax Law; Tax Evasion; Tax Collection; Euphoria; Personal Data; Cognitive Psychology; Neuro-Linguistic-Programming; Mathematical Programming (search for similar items in EconPapers)
Date: 2017
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