Adaption of E-Filling of Income Tax Returns in Kurdistan

Abstract

The study aimed to examine factors influencing E-filling in Kurdistan region of Iraq. To measure the current study, the researchers used three factors (perception, awareness, and quality) as independent variables and E-filling as dependent variable. A quantitative technique applied in order to analyze the current study. Sample design refers to the procedure or method the researcher is willing to accept in choosing items for the sample. Research sample was selected using a procedure of random sampling and it was carried out in different banks. A total of 120 questionnaires were distributed, however 109 participants properly filled out the questionnaires. The results of the study revealed that low levels of computer literacy have a substantial impact on the compliance levels of government organizations. The research determined that in the context of security, the danger of tax noncompliance did not have a major effect on the degree of compliance among the various Iraqi government institutions in the Kurdistan area. The extension or upgrade would be sure to assist in better understanding the determining factor for electronic filing acceptability. Moreover, government agencies, government policy makers, and system designers could also profit from a management policy such as policy makers and agencies. Because of this, the theory and discussion on the subject would provide factual support for the reasons behind why this technology was difficult to adopt. The results show that awareness influences E-as an influential factor significantly and positively E-filling at 5% level. The results show that quality influences E-as an influential factor significantly and positively E-filling at 5% level. The results show that E-filling E-as an influential factor influences significantly and positively E-filling at 5% level. Moreover, all beta value is higher than .001. All models have very high adjusted R2 (0.693, 0.621, 0.712, and 0.763 respectively) indicating the ability of the models explaining the variation of E-filling due to variation of independent variables is very high. The F-value shows that the explanatory variables are jointly statistically significant in the model and the Durbin-Watson (DW) statistics reveals that there is autocorrelation in the models.