Agency Revenue Collection, Automation and Own Source Revenue Targets among Selected County Governments in Kenya

Abstract

The attainment of own source revenue targets by counties holds significant importance as it underpins their financial autonomy, local development initiatives, and effective service delivery. As per the Office of the Controller of Budget however, a declining trend has emerged from an analysis of own source revenue as a percentage of the targeted annual revenue over the past five financial years. A notable decline is observed during this period (2018/19 to 2022/2023), dropping consecutively from 74.8 percent, to 65.2 percent, to 64.2 percent, to 59.4 percent, to 46.4 percent. This trend reveals a consistent decline in performance with counties raising less than 60% of their estimated own source revenue potential despite using agents and having undertaken automation of the revenue collection processes. Against this backdrop, the study sought to establish the relationship between agency revenue collection and own source revenue target among selected county governments in Kenya with automation of revenue collection as a moderating variable. Specifically, it sought to determine competencies of revenue collectors, stakeholder engagement, regulatory compliance, revenue management and determine the moderating effect of revenue collection automation on the relationship between agency revenue collection and own source revenue target. Agency theory, New Public Management Theory and Resource-Based view theory guided the research. A cross-sectional study design was adopted by this study, targeting a population of 708 employees working in six selected county governments. All the 24 county revenue administration executives were selected using purposive sampling, while the stratified random sampling technique was employed in sampling revenue officers. A sample of 284 was determined in the latter, obtained by use of the Yamane formula. Primary data was collected through structured questionnaires while secondary data was collected using data extraction tool for actual own source revenue collected. In order to examine quantitative data, descriptive statistics including frequency, mean, and standard deviation were used, while inferential statistics were produced using both multiple and moderated regression analyses. Results indicate that competency of revenue collectors (β = 0.545, p = 0.000, Sig. <0.05); stakeholder engagement (β = .608, p = 0.000, Sig. <0.05); regulatory compliance (β = .703, p = 0.000, Sig. <0.05); and revenue management (β = .669, p = 0.000, Sig. <0.05) have a significant effect of own source revenue target. Revenue collection automation was also found to significantly moderate the relationship between own source revenue target and stakeholder engagement (β = -.108, p = 0.027, Sig. <0.05). It however fails to moderate the relationship between own source revenue target and competency of revenue collectors (β = -.075, p = .164, Sig. >0.05); regulatory compliance (β = -.069, p = .128, Sig. >0.05); and revenue management (β = -.062, p = .201, Sig. <0.05). The findings indicate that while revenue collection automation significantly moderates the relationship between stakeholder engagement and own source revenue target, it does not significantly moderate the relationships between own source revenue target and competency of revenue collectors, regulatory compliance, or revenue management. The study recommends that county governments prioritize strengthening their agency revenue collection systems, through ongoing capacity-building for revenue collectors, stakeholder engagement, robust regulatory compliance and effective revenue management. They should also strategically integrate revenue collection automation, ensuring that it strengthens rather than undermines these critical factors in optimizing OSR performance.