Reasearch consultancy
methodology
CHAPTER THREE
Research consultancy METHODOLOGY
3.1 Introduction
This study aimed to investigate the impact of information systems on the performance of government agencies in Uganda. This chapter outlines the research methodology employed, covering the research design, study area, target population, sampling strategy, sample size, research instruments, variable measurement, data collection procedures, data analysis, and ethical considerations.
3.2 Research Design
A cross-sectional research design was used to gather data across the entire population of interest in a cost-effective and time-efficient manner, as suggested by Mugenda (2003) and Sekaran (2004). The study adopted both quantitative and qualitative research approaches for data collection and analysis. According to Mugenda (2003), these two methods complement each other and help minimize bias. Amin (2005) argues that triangulation facilitates a deeper analysis through both inductive and deductive approaches, providing a more comprehensive and realistic interpretation of the findings. The qualitative approach allowed for a deeper understanding of participants’ opinions, perceptions, and attitudes toward the problem under investigation.
3.3 Study Population
The study population was drawn from the Uganda Revenue Authority (URA) and included 239 employees, comprising 1 Executive Director, 12 management staff, 40 Division Heads, 5 Regional Heads, and 181 staff members whose duties were relevant to the effect of information systems on the performance of government agencies.
3.4 Sample Size Determination
Using Krejcie and Morgan’s (1970) sample size determination table, a sample size of 181 participants was selected from a total population of 239 employees, along with 100 prominent taxpayers.
Table 3.1: Population and Sample Size
| Category | Population Size | Sample Size | Sampling Technique |
|---|---|---|---|
| Executive Director | 1 | 1 | Purposive Sampling |
| Managers | 12 | 12 | Purposive Sampling |
| Division Heads | 40 | 38 | Purposive Sampling |
| Regional Heads | 5 | 5 | Purposive Sampling |
| Staff Members | 181 | 93 | Simple Random Sampling |
| Taxpayers | 100 | 32 | Simple Random Sampling |
| Total | 339 | 181 |
3.5 Sampling Techniques and Procedure
The study utilized both probability and non-probability sampling techniques. Simple random sampling, a probability method, was used to ensure every member of the population had an equal chance of selection. Purposive sampling, a non-probability technique, was employed to target respondents with specific knowledge relevant to the study.
3.5.1 Simple Random Sampling
This method ensured that all population members had an equal likelihood of being chosen, minimizing bias and simplifying the selection process (Neuman, 2006). It was used to select staff members and taxpayers.
3.5.2 Purposive Sampling
Purposive sampling was used to select participants who possessed the required information, as argued by Mugenda (2003) and Neuman (2006). This method allowed the researcher to target knowledgeable respondents, optimizing the use of time and resources. It was employed to select the Executive Director, Managers, Division Heads, and Regional Heads.
3.6 Data Collection Methods
Data was gathered using three primary methods: questionnaire surveys, interviews, and documentary reviews.
3.6.1 Questionnaire Survey
Questionnaires were used to capture the opinions of staff members, Division Heads, Regional Heads, and taxpayers regarding the study topic. According to Onen & Onen (2013), questionnaires are advantageous because they allow respondents time to think before responding and can be retained for future reference.
3.6.2 Interviews
Interviews, particularly effective for qualitative data, were used to explore participants’ feelings, opinions, and experiences concerning information systems and their impact on agency performance. This method was employed for the Executive Director and Managers, allowing for the collection of rich, detailed data. Open-ended questions facilitated open expression and the collection of comprehensive insights.
3.6.3 Documentary Review
The researcher also reviewed relevant documents, including URA reports, journals, research publications, magazines, textbooks, and newspapers.
3.7 Data Collection Instruments
The instruments used in this study were tailored to each data collection method, including questionnaires, interview guides, and a document review checklist.
3.7.1 Self-Administered Questionnaire
Structured with both closed- and open-ended questions, the questionnaire was designed to motivate respondents. A Likert scale of 1–5 was used to capture respondents’ levels of agreement, where 1 represented “Strongly Disagree” and 5 represented “Strongly Agree.”
3.7.2 Interview Guide
An unstructured interview guide was used to collect qualitative data from key informants at URA. The guide contained open-ended questions that allowed the researcher to establish rapport, motivate participants, and gather more detailed responses.
3.7.3 Document Review Checklist
This instrument facilitated the collection of secondary data relevant to the study by analyzing reports, journals, and other documents.
3.8 Data Quality Control
Data collection tools were pre-tested to ensure accuracy, validity, and reliability.
3.8.1 Validity
Content validity was achieved by using expert evaluations from supervisors and consultants. The Content Validity Index (CVI) was calculated using the formula:
CVI=nNCVI = \frac{n}{N}
where n is the number of valid items and N is the total number of items in the instrument.
3.8.2 Reliability
Reliability was assessed using Cronbach’s alpha, which measures internal consistency. According to Amin (2005), a reliability coefficient of 0.7 and above is acceptable.
Table 3.3: Reliability of Research Instruments
| Variables | Alpha | Number of Items |
|---|---|---|
| Systems Software | .808 | 9 |
| Systems Infrastructure | .673 | 9 |
| User Knowledge & Skills | .840 | 11 |
| Financial Performance | .670 | 3 |
| Customer Satisfaction | .770 | 4 |
| Growth | .860 | 5 |
| Average | .77 | 41 |
3.9 Data Collection Procedure
The researcher obtained an introductory letter from the Uganda Management Institute (UMI) to seek permission for data collection from URA. After securing permission, questionnaires were distributed, and interviews were conducted with selected respondents.
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3.10 Data Analysis
Both quantitative and qualitative data analysis methods were applied in this study.
3.10.1 Quantitative Data Analysis
Data was entered into SPSS (Version 24.0) for processing. The analysis involved editing, classification, coding, and summarizing data in frequency tables. Spearman’s correlation coefficient and regression analysis were employed to examine the relationship between information systems and government agency performance.
3.10.2 Qualitative Data Analysis
Qualitative data was analyzed using content analysis, which involved organizing raw data into note cards, evaluating its accuracy, and determining its credibility.
3.11 Measurement of Variables
Variables were measured using a five-point Likert scale, ranging from “Strongly Agree” (5) to “Strongly Disagree” (1).
3.12 Ethical Considerations
Prior to participation, respondents were informed of the study’s academic purpose, and their consent was obtained. Confidentiality was assured, and participation was voluntary.
