FACTORS AFFECTING IMPLEMENTATION OF REVENUE COLLECTION SYSTEMS IN COUNTY GOVERNMENTS IN KENYA, A CASE OF MERU COUNTY
Abstract
Revenue collection is a key source of income to all governments. The purpose of this study was to establish factors affecting revenue collection systems at the county governments of Kenya with specific reference to Meru County. The study sought to determine the effect of financial management system on revenue collection systems. The design for the study was cross-sectional mixed method. The target population was 150 respondents comprising employees at county revenue department of Meru County. The sample size was 62 respondents. The instruments for data collection were questionnaires. Data was analyzed Using SPSS version 25 and STATA version 12. From pilot test Cronbach’s alpha tested reliability. While Regression analysis, ANOVA, Correlation, descriptive statistics, presented the data results and findings. It was expected that; the outcome of the study could be used to develop strategies to be used in facilitating efficiency in revenue collection. The study found that ability to make payments using mobile money Platforms and tax payer’s ability to pay rates, fees through different bank accounts were very good. The study found out that revenue collection systems used have achieved expected revenue targets and revenue collection system available have improved taxpayers’ compliance in a greater extent. The study found out that the respondents strongly agreed that they are encouraged to take up responsibility for their personal development, learning and career growth. In addition, the study found out that respondents agreed that they have been trained on revenue collection systems available in the last one year and that employee experience, knowledge, skills & competence will improve service delivery. Taxes payable to County Governments should be distinct from the ones payable to the National Government. The foregoing would reduce tax evasion, non-compliance and also Double Taxation of Citizens. All variables were significant since their p-values were less than 0.05
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