Your methodology chapter explains how you answered your research question and, just as importantly, why you chose that approach. A clear, well-justified methodology is one of the strongest signals of quality in a thesis. This guide breaks the decision into manageable steps and shows how the choices fit together.
Start with your research question
Every methodological choice should follow from your research question. Look at the verbs and the type of answer it needs:
- Questions about how much, how many or how strongly things are related point towards quantitative research. Example: “To what extent does perceived ease of use influence intention to adopt mobile banking?”
- Questions about how, why or what it is like point towards qualitative research. Example: “How do first-generation students experience their transition to university?”
- Questions with both elements, or that need one type of evidence to explain another, may call for mixed methods.
Understand the layers of a methodology
Many universities, especially in business and management, use the “research onion” from Saunders, Lewis and Thornhill to structure the methodology chapter. Working from the outside in, you make decisions about:
- Philosophy: your assumptions about knowledge. Positivism suits measurable, generalisable findings. Interpretivism suits understanding meanings and experiences. Pragmatism focuses on whatever works best to answer the question and is common in mixed methods.
- Approach to theory: deductive (testing existing theory, often with hypotheses), inductive (building theory from data) or abductive (moving between the two).
- Methodological choice: quantitative, qualitative or mixed methods.
- Strategy: for example a survey, experiment, case study, ethnography, grounded theory or archival research.
- Time horizon: cross-sectional (one point in time) or longitudinal (over time).
- Techniques and procedures: how you sample, collect and analyse data.
The layers must be consistent. An interpretivist philosophy combined with a large hypothesis-testing survey, for instance, will raise questions from your examiner.
Choose your data collection method
- Questionnaires: efficient for large samples and for measuring constructs with established scales. Use validated items wherever possible and pilot your survey.
- Interviews: semi-structured interviews give depth while keeping some comparability between participants.
- Focus groups: useful for exploring shared views and how people discuss a topic.
- Secondary data: company reports, financial databases or national statistics. Common in finance and economics theses using panel data.
- Experiments: the strongest design for causal claims, but harder to run in real settings.
Decide how you will sample
Quantitative studies usually aim for samples that allow generalisation and enough statistical power. Probability sampling is ideal but often impractical for students, so convenience or purposive samples are common; just be honest about the limitations. For sample size, base your decision on a power analysis (for example with G*Power) or on established guidance for your analysis method rather than a round number.
Qualitative studies use purposive sampling to select information-rich participants. Many studies reach saturation with roughly 12 to 20 interviews, but explain your reasoning rather than quoting a number.
Plan your analysis before you collect data
Students often design a questionnaire first and think about analysis later, then discover their data cannot answer their hypotheses. Decide now:
- Quantitative: descriptive statistics, reliability (Cronbach’s alpha), and the tests that match your hypotheses, such as regression, ANOVA or structural equation modelling.
- Qualitative: thematic analysis, content analysis, grounded theory coding or narrative analysis, and whether you will use software such as NVivo.
Address quality and ethics
Explain how you ensured quality: validity and reliability for quantitative research, and credibility, transferability, dependability and confirmability for qualitative research. Then describe your ethical procedures, including informed consent, anonymity and secure data storage.
If you collect personal data in Europe, the GDPR applies. In Sweden, research that processes sensitive personal data may require approval from the Swedish Ethical Review Authority. In Norway, student projects that process personal data are commonly registered with Sikt. In the UK, your university research ethics committee will set out the process. Check your institution’s rules early, because approval can take weeks.
A simple structure for your methodology chapter
- Introduction and restatement of the research questions
- Research philosophy and approach
- Research design and strategy
- Population, sampling and sample size
- Data collection instruments and procedures
- Data analysis methods
- Validity, reliability or trustworthiness
- Ethical considerations
- Limitations of the methodology
Justify, do not just describe
For every choice, add a sentence that explains why it is the best option for your study and cite methodological literature to support it. “A cross-sectional survey was used” describes. “A cross-sectional survey was used because the study tests relationships between constructs in a large population at one point in time (Saunders et al., 2023)” justifies.
Not sure your design holds together? Our research support specialists can review your methodology, suggest improvements and help you plan an analysis that answers your questions.