Journal of Economics and Financial Analysis, 6 (2), pp. 21-41, [2022]
URI: https://ojs.tripaledu.com/jefa/article/view/75/86

South African Taxpayers Perceptions towards E-Filing


University of the Witwatersrand, South Africa


DOI: http://dx.doi.org/10.1991/jefa.v6i2.a53

Abstract

The study has two parts: the first part studies how South African taxpayers felt about e-filing, and the second part analyses how e-filing affected tax compliance. We use self-structured questionnaires to collect data from about 151 South African taxpayers, and we analyze them using binary logistic regression. The study finds that online tax registration and auto-assessment has a negative relationship with tax compliance in South Africa, while online payment methods, difficulty in tax evasion, and higher educational attainment have a positive association with tax compliance. The study also finds that the extent to which the e-filing system encourages taxpayers to become compliant has a positive and statistically significant relationship with tax compliance. Overall, the study suggests that the development of e-filing has a positive impact on taxpayers' perceptions in South Africa and significantly increases voluntary tax compliance. To maximize the benefits of e-filing, it is important to ensure that taxpayers have access to the necessary technology and knowledge to use it effectively.

Keywords

Tax Compliance; Information Technology; Binary Logistic Regression; E-Filing.

JEL Classification

H24, H26, C51, O31.

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References

Adegbite, T.A., Bojuwon, M., and Adegbite, A.F. (2019). The Impact of ICT on Taxation: Evidence from Oyo State. Copernican Journal of Finance & Accounting, 8(4), pp.7–25. http://dx.doi.org/10.12775/CJFA.2019.015

Ajala, M.O.O., & Adegbie, F.F. (2020). Effects of Information Technology on Effective Tax Assessment in Nigeria. Journal of Accounting and Taxation, 12(4), pp. 126-134. DOI: 10.5897/JAT2020.0416

Bauer, R.A. (1960). Consumer Behavior as Risk Taking. In R.S. Hancock (ed.), Dynamic Marketing for a Changing World. Proceedings of the 43rd Conference of the American Marketing Association, 389B400.

Chatama, Y.J. (2010). The Impact of ICT on Taxation: The Case of Large Taxpayer Department of Tanzania Revenue Authority. Developing Country Studies, 3(2), pp.91-101

Coolidge, J., & Yilmaz, F. (2014). Does e-Filing reduce Tax Compliance Costs in Developing Countries? Investment Climate Working Paper no.91191, World Bank Group

Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences, 2nd ed. Hillsdale, NJ: Erlbaum.

Deslonde, V., & Becerra, M. (2018). The Technology Acceptance Model (TAM): Exploring School Counselors’ Acceptance and Use of Naviance. The Professional Counsellor, 8(4), pp.369–382. doi:10.15241/vd.8.4.369

Fishbein, M., and Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Ontario: Addison-Wesley.

Kiema, J. (2011). Effects of ICT Support Services on Revenue Collection by Kenya Revenue Authority. MBA Thesis, University of Nairobi, Nairobi

Kimea, A., Chimilila, C. and Sichone, J. (2019). Analysis of Taxpayers’ Intention to Use Tax E-Filing System in Tanzania: Controlling for Self-Selection Based Endogeneity. African Journal of Economic Review, 7(2), pp.193-212

Kgonare, M.G.J. (2017). The Impact of Information Communication Technology on Tax Administration: A Systematic Review. Masters’ Thesis, University of Pretoria, South Africa. Retrieved from: https://repository.up.ac.za/handle/2263/68040

Liao, S., Hong, J., Wen, M., Pan, Y. and Wu, Y. (2018). Applying Technology Acceptance Model (TAM) to explore Users’ Behavioural Intention to Adopt a Performance Assessment System for E-book Production. EURASIA Journal of Mathematics, Science and Technology Education, 14(10), pp.1-12.

Lu, Y., Zhou, T., and Wang, B. (2009). Exploring Chinese users’ Acceptance of Instant Messaging Using the Theory of Planned Behavior, the Technology Acceptance Model, and the Flow Theory. Computers in Human Behaviour, 25(1), pp.29-39. https://doi.org/10.1016/j.chb.2008.06.002

Mertler, C.A. and Vannatta, R.A. (2005). Advanced and Multivariate Statistical Methods: Practical Application and Interpretation (3rd ed.). Glendale, CA: Pyrczak Publishing.

Mukaka, M.M. (2012). Statistics Corner: A guide to appropriate use of Correlation coefficient in medical research. Malawi Medical Journal, 24(3), pp.69-71

Olatunji, O.C. and Ayodele, K.B. (2017). Impact of Information Technology on Tax Administration in Southwest, Nigeria. Global Journal of Management and Business Research, 17(10), pp.1-11

Sanchez-Franco, M.J. (2010). WebCT–The Quasi-moderating Effect of Perceived Affective Quality on an Extending Technology Acceptance Model. Computers & Education, 54(1), pp.37-46. DOI: 10.1016/j.compedu.2009.07.005

Sperandei, S. (2013). Understanding Logistic Regression Analysis. Biochemia Medica, 24(1), pp.8-12

Peng, C.Y.J., Lee, K.L., and Ingersoll, G.M. (2002). An Introduction to Logistic Regression Analysis and Reporting. The Journal of Educational Research, 96(1), pp.3-14

Taherdoost, H. (2016). Sampling Methods in Research Methodology; How to Choose a Sampling Technique for Research. International Journal of Academic Research in Management, 5(2), pp.18-27

Umaru, A.F. Nasiru, M. and Yusuf, S.K. (2019). Information Technology and Tax Administration in Adamawa State Board of Internal Revenue Yola-Nigeria. Dutse Journal of Economics and Development Studies, 7(1), pp.13-21




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