CHAPTER THREE
METHODOLOGY (Rephrased)
3.1 Research Design
The study employed a correlational research design, which is a non-experimental approach used to determine the relationship between closely related variables. This design enables researchers to examine associations among variables using techniques such as correlation analysis and cross-tabulation.
Both quantitative and qualitative methods were utilized. The quantitative approach focused on measuring and analyzing numerical data using statistical techniques to answer questions related to magnitude, frequency, and relationships among variables. It was specifically used to establish the relationship between motivation styles and tax compliance through correlation and regression analysis.
The qualitative approach was also applied to capture deeper insights into tax compliance behaviors, recognizing that such issues are influenced by real-life social contexts among taxpayers.
3.2 Study Population
The study was conducted in Lira Municipality, located in Lira District in Northern Uganda. The municipality comprises four divisions, 22 wards, and 64 cells.
The target population consisted of Small and Medium Enterprises (SMEs) operating within Lira Municipality and registered with the Uganda Revenue Authority (URA). According to URA (2019), there were 1,643 SMEs in the municipality.
For this study, the population was proportionately distributed across the four divisions, with a specific focus on 328 SMEs in the Central Division.
3.3 Sample Size
The sample size for quantitative data was determined using the Yamane (1967) formula:
n=X2NP(1−P)d2(N−1)+X2P(1−P)n = \frac{X^2NP(1-P)}{d^2(N-1) + X^2P(1-P)}
Where:
- n = required sample size
- X² = chi-square value (3.841 at 1 degree of freedom)
- N = population size
- P = population proportion (0.5)
- d = margin of error (0.05)
The calculated sample size was 176 SME operators.
3.4 Sampling Procedure
The study applied simple random sampling (SRS) to select respondents. This method ensures that each member of the population has an equal chance of being included in the sample, thereby minimizing bias. The technique was chosen to guarantee fairness and representativeness among SME owners and managers.
3.5 Sources of Data
The study relied on primary data, which was collected directly from respondents. Primary data collection allows researchers to obtain information tailored specifically to the objectives of the study.
Data was gathered from SME owners and managers using questionnaires, while interviews were conducted with URA staff to obtain additional insights.
3.6 Data Collection Methods and Instruments
Data collection involved systematically gathering information to answer research questions and test hypotheses.
A self-administered questionnaire (SAQ) with closed-ended questions was used to collect quantitative data. This type of questionnaire allows respondents to complete it independently without the assistance of the researcher, making it efficient and cost-effective.
A five-point Likert scale was used to measure responses, where:
1 = Strongly Disagree
2 = Disagree
3 = Neutral
4 = Agree
5 = Strongly Agree
Additionally, unstructured questionnaires were used to collect qualitative data, providing flexibility for respondents to express their views.
3.7 Measurement of Variables
The study variables and their respective measures were operationalized as follows:
- Tax Compliance: Tax filing, reporting, and payment
- Tax Education: Awareness, communication channels, and skilled personnel
- Tax Registration: Identification of taxpayers, issuance of tax IDs, business location details, and registration procedures
- Tax Assessment: Record keeping, personnel competence, information requirements, and assessment methods
- Tax Collection: Methods, procedures, manpower, and costs
All variables were measured using a Likert scale, as supported by relevant literature.
3.8 Validity and Reliability
3.8.1 Validity
To ensure validity, the research instruments were pre-tested and reviewed by two academic supervisors. Their feedback was used to assess the relevance of questionnaire items using a five-point Likert scale.
The Content Validity Index (CVI) was calculated as 0.90, indicating that 90% of the items were valid and suitable for data collection.
3.8.2 Reliability
Reliability was assessed using Cronbach’s Alpha coefficient. The instrument was tested on selected respondents, and the results were analyzed using SPSS version 23.
The study adopted a minimum acceptable reliability threshold of 0.65. The obtained Cronbach’s Alpha value was 0.928, indicating excellent reliability of the research instrument.
3.9 Data Processing and Analysis
Data analysis involved interpreting collected information to derive meaningful conclusions.
Quantitative data was edited, coded, and analyzed using SPSS version 23. Both descriptive statistics (such as frequencies and percentages) and inferential statistics were used.
Inferential analysis included:
- Pearson correlation to determine relationships between variables
- Multiple regression analysis to assess the effect of tax administration systems on tax compliance
Qualitative data was analyzed using an interpretative approach, involving identifying patterns, themes, and meanings from respondents’ perspectives.
3.10 Ethical Considerations
Ethical standards were strictly observed throughout the study. An introductory letter was obtained to seek permission from respondents. Participation was voluntary, and respondents were not coerced.
Confidentiality and privacy were maintained by not collecting personal identifiers and ensuring that data was used strictly for academic purposes. Additionally, all sources were properly acknowledged, and findings were reported objectively without bias.
