Using Fuzzy-Set Qualitative Comparative Analysis and Multiple Regression Analysis to Determine Tax Compliance Model for Vietnam.

Abstract

Tax administration in a country has never been an easy and simple task, and a deep understanding of the factors affecting tax compliance is a vital task. We wonder if a single impacting factor may be useful or a compulsory combination of factors will be useful. The main purpose of this paper is to present the advantage of fsQCA in social sciences. It presents a non-popular approach in research, the combination of fuzzy-set Qualitative Comparative Analysis (fsQCA) and Multiple Regression Analysis (MRA) in hypothesis testing, for determining the Corporate Income Tax Compliance Model for Vietnam. This study is conducted by re-testing the Coporate Income Tax compliance model that used samples in Ho Chi Minh City only. The data used to re-test the hypotheses will come from five other provinces, sampling technique is simple random sampling. The first study of its kind, in order to examine to strengths and weaknesses of each methodological approach, it applies both fsQCA and MRA. The results shows that the statistically significant relationships between independent variables such as Business factor, Knowledge - Accounting Activities factor, Psychosocial factor, Tax Administration factor, Economic factor and dependent variable - Tax Compliance factor are identified; The results also shows that fsQCA leads to a more detailed understanding of the conditions under which the result occur than do MRA, and the using both of them to conduct the hypothesis test is better than using MRA only. By combining fuzzy-set Qualitative Comparative Analysis and Multiple Regression Analysis we can clearly and deeply understand the research problem more than do Multiple Regression Analysis only.