Methodology

Methodology

CHAPTER THREE: METHODOLOGY

3.1 Introduction

This chapter outlines the research methodology employed in the study, which aimed to assess the effect of information systems on the performance of government agencies in Uganda. The chapter covers the research design, study area, target population, sample design, sample size, research instruments, variable measurement, data collection procedures, data analysis, and ethical considerations.

3.2 Research Design

The study adopted a cross-sectional research design, allowing data to be collected from a broad cross-section of the population. This design was chosen for its efficiency in terms of time and cost, as noted by Mugenda (2003) and Sekaran (2004). Both quantitative and qualitative approaches were utilized for data collection and analysis, as they complement one another and reduce bias (Mugenda, 2003). Amin (2005) highlights that triangulation, combining qualitative and quantitative methods, enables a comprehensive analysis using both inductive and deductive perspectives, ensuring a well-rounded understanding of the findings.

3.3 Study Population

The study population consisted of 239 Uganda Revenue Authority (URA) employees, including 1 Executive Director, 12 management staff, 40 division heads, 5 regional heads, and 181 staff members. These individuals were involved in duties that influence the role of information systems on the performance of government agencies.

3.4 Sample Size Determination

A sample size of 181 was determined from the total population of 239 employees, in addition to 100 prominent taxpayers, using Krejcie and Morgan’s (1970) sample size determination table.

CategoryPopulation SizeSample SizeSampling Technique
Executive Director11Purposive Sampling
Managers1212Purposive Sampling
Division Heads4038Purposive Sampling
Regional Heads55Purposive Sampling
Staff Members18193Simple Random Sampling
Taxpayers10032Simple Random Sampling
Total339181

Source: URA Employee List (2013)

3.5 Sampling Techniques and Procedure

Both probability and non-probability sampling techniques were employed. Simple random sampling was used for probability sampling, while purposive sampling was applied for non-probability sampling.

3.5.1 Simple Random Sampling

This technique ensured that every member of the population had an equal chance of being selected. It was used to select staff members and taxpayers, as it is known to avoid bias and is easy to implement (Neuman, 2006).

3.5.2 Purposive Sampling

Purposive sampling was utilized to select respondents with the most relevant information, such as the Executive Director, managers, division heads, and regional heads. Mugenda (2003) and Neuman (2006) argue that purposive sampling is effective for obtaining rich data from knowledgeable participants.

3.6 Data Collection Methods

The data collection methods included questionnaires, interviews, and documentary reviews.

3.6.1 Questionnaire Survey

Questionnaires were used to gather opinions from respondents. According to Onen and Onen (2013), questionnaires provide respondents with time to think and respond at their convenience. This method was used to collect data from staff members, regional heads, division heads, and taxpayers.

3.6.2 Interviews

Interviews allowed for in-depth exploration of respondents’ views on the effect of information systems on government agency performance. Open-ended questions enabled participants to express their opinions freely. Interviews were conducted with the Executive Director and managers.

3.6.3 Documentary Review

Documents such as URA reports, journals, research publications, textbooks, and newspapers were reviewed to provide additional context and data relevant to the study.

3.7 Data Collection Instruments

The instruments used in this study included questionnaires, an interview guide, and a document review checklist.

3.7.1 Self-administered Questionnaire

The questionnaire comprised both closed-ended and open-ended questions, with a Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). The questionnaire is provided in Appendices I and II.

3.7.2 Interview Guide

An unstructured interview guide was used to collect qualitative data from key informants at URA. This tool allowed for the collection of detailed data and facilitated clarifications where necessary. The interview guide is included in Appendix III.

3.7.3 Document Review Checklist

This checklist helped capture secondary data from reports and publications relevant to the study topic, particularly related to information systems and URA performance.

3.8 Data Quality Control of Instruments

The data collection instruments were pre-tested with a small group of respondents to ensure accuracy.

3.8.1 Validity

Validity refers to the accuracy of the research results. The content validity index (CVI) was computed by dividing the number of valid items by the total number of items. Expert reviewers helped assess the validity of the research instruments.

VariablesTotal ItemsValid ItemsCVI
Systems Software97.77
Systems Infrastructure98.88
User Knowledge and Skills118.72
Financial Performance331.00
Customer Satisfaction43.75
Growth54.80
Total4636.82
3.8.2 Reliability

Reliability was measured using Cronbach’s alpha, with a value of 0.7 or higher considered acceptable.

VariablesAlphaNumber of Items
Systems Software.8089
Systems Infrastructure.6739
User Knowledge and Skills.84011
Financial Performance.6703
Customer Satisfaction.7704
Growth.8605

The overall reliability was 0.77, which is deemed acceptable.

3.9 Procedure for Data Collection

An introductory letter from the Uganda Management Institute was obtained to seek permission from URA. Once permission was granted, questionnaires were administered, and interviews were conducted. Respondents’ consent was obtained prior to their participation.

3.10 Data Analysis

Both quantitative and qualitative data analysis methods were employed.

3.10.1 Quantitative Data Analysis

Data was processed using SPSS version 24.0. Spearman’s correlation coefficient and regression analysis were used to assess the relationship between information systems and performance in government agencies.

3.10.2 Qualitative Data Analysis

Qualitative data was analyzed using content analysis, focusing on evaluating the accuracy, credibility, and usefulness of the data.

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