Skip to main content
SpringerLink
Log in

Data Modeling and Visualization of Tax Strategies Employed by Overseas American Individuals and Firms

  • Conference paper
  • First Online:
Advances in Internet, Data and Web Technologies (EIDWT 2019)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 29))

Abstract

A study of the tax behavior of overseas American individuals and small firms, where the researcher models behavior, through text analysis, using data mining technologies of KH Coder, with data collected from a wide range of sources using interviews, surveys, blog and forum postings, published reports as well as personal communications, to demonstrate and inform using the pattern matching method. Text mining and modeling techniques, using unsupervised machine learning facilitate large-scale analysis of behavioral approaches to taxation to motivate a better understanding of the phenomenon tax avoidance and tax evasion. There are an estimated 9 million taxable overseas Americans corporations and business entities and estimated that as many as 100 billion U.S. dollars may go uncollected, due to tax evasion. A similar shortfall of 100 billion dollars is due to tax avoidance. The researcher proposes a model explaining tax avoidance behavior by the US taxable entities.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Trochim, W.M.: Outcome program matching and pattern theory. Eval. Program Plan. 12, 355–366 (1989). https://www.socialresearchmethods.net/research/Outcome%20Pattern%20Matching%20and%20Program%20Theory.pdf

    Article  Google Scholar 

  2. Trochim, W.M.: Hindsight is 20/20: reflections on the evolution of concept mapping. Eval. Program Plan. (2016). https://doi.org/10.1016/j.evalprogplan.2016.08.009

    Article  Google Scholar 

  3. Gravelle, J.G.: Tax havens: international tax avoidance and evasion. Congr. Res. Serv. (2015). https://fas.org/sgp/crs/misc/R40623.pdf

  4. CA by the Numbers: Counsular Affairs by the Numbers. US Department of State, Bureau of Consular Affairs (2017). https://travel.state.gov/content/dam/travel/CA_By_the_Numbers.pdf

  5. UN: Sustainable development goals (2017). http://www.un.org/sustainabledevelopment/blog/2016/01/244-million-international-migrants-living-abroad-worldwide-new-un-statistics-reveal/

  6. Marshall, S.: Corporate inversion and the impact on the United States. Business, Lagrange.edu. (2016). http://www.lagrange.edu/resources/pdf/citations/2016/11_Marshall_Business.pdf

  7. degl’Innocenti, D.G., Rablen, M.: Income tax avoidance and evasion: a narrow bracketing approach. Public Financ. Rev. 45(6) (2017). https://doi.org/10.1177/1091142116676362

    Article  Google Scholar 

  8. K@W: Corporate tax avoidance: can the system be fixed? Knowledge at Wharton (2013). http://knowledge.wharton.upenn.edu/article/corporate-tax-avoidance-can-the-system-be-fixed/#comments

  9. IRS: Abusive offshore tax avoidance schemes-talking points (2017). https://www.irs.gov/businesses/small-businesses-self-employed/abusive-offshore-tax-avoidance-schemes-talking-points

  10. Gupta, S., Mills, L.F., Towery, E.M.: The effect of mandatory financial disclosures of tax uncertainty on tax reporting and collection: the case of fin 48 and multistate tax avoidance. J. Am. Tax. Assoc. 36(2), 231–239 (2014). https://doi.org/10.2308/atax-10402

    Article  Google Scholar 

  11. Bui, Q., Sanger-Katz, M.: Hacking the tax plan: ways to profit off the republican tax bill. The Upshot, The New York Times (2017). https://www.nytimes.com/interactive/2017/12/12/upshot/tax-hacks.html. Accessed 23 Dec 2017

  12. Tax Foundation: State-local tax burden rankings FY 2012 (2017). https://taxfoundation.org/publications/state-local-tax-burden-rankings/. Accessed Dec 30 2017

  13. Miller, A.H.: Computer-aided content analysis of the corpus of business discourse: a comparison of accounting and HR learners, NETs 2016, Osaka, Japan, 25 July 2015 (2016)

    Google Scholar 

  14. Miller, A.H.: Preparing students for career success in accounting: the SCIL-based model with a focus on content analysis. Transnatl. J. Bus. (2017). http://www.acbsp.org/members/group.aspx?id=143359

  15. Miller, A.H.: A corpus-based computer aided linguistic analysis of taxation learning outcomes. In: International Conference on Business, Big-Data, and Decision Sciences (2017 ICBBD), Chulalongkorn University, Bangkok, Thailand, 2–4 August 2017. http://icbbd2017.globalconf.org/site/page.aspx?pid=901&sid=1128&lang=en

  16. Miller, A.H.: Modeling taxation learning outcomes using unsupervised machine learning. Int. J. Eng. Technol. 7(2.4), 109–116 (2018). https://doi.org/10.14419/ijet.v7i2.4.13019. https://www.sciencepubco.com/index.php/ijet/article/view/13019/5200. Accessed 15 Aug 2018

    Article  Google Scholar 

  17. Hunston, S.: Corpora in Applied Linguistics. Cambridge University Press, Cambridge (2010)

    Google Scholar 

  18. Vesanto, J., Alhoniemi, E.: Clustering of the self-organizing map. IEEE Trans. Neural Netw. 11(3) (2000). http://ftp.it.murdoch.edu.au/units/ICT219/Papers%20for%20transfer/papers%20on%20Clustering/Clustering%20SOM.p

    Article  Google Scholar 

  19. Berinato, S.: Visualizations that really work. Harv. Bus. Rev., June 2016. https://hbr.org/2016/06/visualizations-that-really-work. Accessed 2 Sept 2016

  20. Buja, A., Swayne, D.F., Littman, M.L., Dean, N., Hofman, H., Chen, L.: Data visualization with multidimensional scaling. J. Comput. Graph. Stat. 17(2), 444–472 (2008). https://doi.org/10.1198/106186008X318440

    Article  MathSciNet  Google Scholar 

  21. Tamura, T.: Application of text-mining methodology to sociological analysis of internet text in Japan, Japan and the internet: perspectives and practices (2011)

    Google Scholar 

  22. Mori, J., Matsuo, Y., Ishizuka, M., Faltings, B.: Keyword extraction from the web for FOAF metadata. In: Workshop on Friend of a Friend, Social Networking and the Semantic Web, Galway, Ireland. Google Scholar (2004)

    Google Scholar 

  23. Minami, A., Ohura, Y.: How student’s attitude influences on learning achievement? An analysis of attitude representing words appearing in looking-back evaluation. In: ICIT Proceedings of the 8th International Conference on Information Technology and Applications, pp. 164–169 (2015)

    Google Scholar 

  24. Yu, C.H., Jannasch-Pennell, A., DiGangi, S.: Compatibility between text mining and qualitative research in the perspectives of grounded theory, content analysis, and reliability (2011)

    Google Scholar 

  25. Posner, R.: Opinion, United States of America, PlaintiffAppellee, v. Deanna L. Costello, Defendant-Appellant, No. 11-291 U.S. Court of Appeals Seventh Circuit Court (2012)

    Google Scholar 

  26. Smith, G.: Data and intuition. The Conglomerate (2014). http://www.theconglomerate.org/corpuslinguistics/

  27. O’Neil, C.: ‘Rogue Algorithms’ and the dark side of big data. Knowledge@Wharton. Wharton, University of Pennsylvania (2016). http://knowledge.wharton.upenn.edu/article/roguealgorithms-dark-side-big-data/?utm_source=kw_newsletter&utm_medium=email&utm_campain=2016-09-22

  28. Faul, F., Erdfelder, E., Buchner, A., Lang, A.G.: Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav. Res. Methods 41, 1149–1160 (2009). https://doi.org/10.3758/BRM.41.4.1149

    Article  Google Scholar 

  29. Teixeira, D.P.: Attitudes on the ethics of tax evasion: a survey of banking employees (Master thesis), Lisbon school of economics and management (2016). https://www.iseg.ulisboa.pt/aquila/getFile.do?fileId=868711&method=getFile

  30. Alm, J.: Measuring, explaining, and controlling tax evasion: lessons from theory, experiments, and field studies. Int. Tax Public Financ. 19(1), 54–77 (2012)

    Article  Google Scholar 

  31. Tenidoua, E., Valsamidisa, S., Petasakisa, I., Mandilasa, A.: Elenxis, an effective tool for the war against tax avoidance and evasion. Procedia Econ. Financ. 33, 303–312 (2015). https://doi.org/10.1016/s2212-5671(15)01714-1. 7th International Conference, The Economies of Balkan and Eastern Europe Countries in the changed world, EBEEC 2015, 8–10 May 2015

    Article  Google Scholar 

  32. Nie, L., Wang, M., Gao, Y., Zha, Z.J., Chua, T.S.: Beyond text QA: multimedia answer generation by harvesting web information. Trans. Multimed. 15(2), 426–441 (2013). https://doi.org/10.1109/TMM.2012.2229971

    Article  Google Scholar 

  33. Harvey, L: Beyond member-checking: a dialogic approach to the research interview. Int. J. Res. Method Educ., 1–16 (2014)

    Google Scholar 

Download references

Acknowledgments

The Higher Colleges of Technology, Fujairah Colleges, of Fujairah UAE, where the principle investigator is employed as an applied researcher.

Author information

Authors and Affiliations

  1. Fujairah Women’s College, Higher Colleges of Technology, Box 1626, Fujairah, UAE

    Alfred Howard Miller

Authors
  1. Alfred Howard Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alfred Howard Miller .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Technical University of Catalonia, Barcelona, Spain

    Fatos Xhafa

  3. Computer Information Science (CIS), Higher Colleges of Technology, Fujairah Campus, Fujairah, United Arab Emirates

    Zahoor Ali Khan

  4. Faculty of Computer Information Science, Higher Colleges of Technology, Dubai Campus, Dubai, United Arab Emirates

    Hamad Odhabi

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Miller, A.H. (2019). Data Modeling and Visualization of Tax Strategies Employed by Overseas American Individuals and Firms. In: Barolli, L., Xhafa, F., Khan, Z., Odhabi, H. (eds) Advances in Internet, Data and Web Technologies. EIDWT 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-030-12839-5_28

Download citation

Publish with us

Policies and ethics

Search

Navigation