Types of Research in Research Methodology: The Complete PhD Guide 2026
Most PhD scholars start their journey with a focus on what they want to study, few start with a focus on how they will study it, and if they answer that question incorrectly, they will undo years of their life’s work.
Research methodology is a framework that guides how you will conduct your study, how you will collect your data, and how you will analyze your results. In doing so, the type of research you will conduct will dictate every other decision you will make in your study, from your literature review parameters, your data collection methods, and even your analysis tools, ultimately leading you to a credible result or not.
If you get the wrong type of research, it is not like you will get a formatting error; you will end up with a qualitative study when you should have had a quantitative study, or a cross-sectional study when you should have had a longitudinal study. These errors will come back to haunt you in your viva in the worst possible way.
Saunders, Lewis and Thornhill — authors of the most-cited PhD methodology textbook globally — describe research methodology choices as layers of a ‘Research Onion.’ Every outer layer you peel (philosophy → approach → strategy → method → time horizon) must be justified in relation to the one beneath it. Your research type is the very core of that onion.
Method vs Methodology: The Distinction That Trips Everyone Up
This is one of the most commonly misused words in dissertation writing, and supervisors are very aware of it
| Term | What It Means | PhD Example |
|---|---|---|
| Research Method | The specific technique used to collect or analyse data | Semi-structured interviews, SPSS regression, content analysis |
| Research Methodology | The strategic and philosophical framework governing method choice | Interpretivist, qualitative, phenomenological study using interviews |
The strategy is methodology, and the method is tactic. Your methodology is justified in Chapter 3. The methods are a natural consequence of that.
The Research Onion: A Framework for Classifying All Types
The Research Onion (Saunders et al., 2019) is the most structured method for conceptualizing where ‘types of research’ fit into the overall scheme. Starting from the outside in:
Layer 1: Research Philosophy — Positivism, Interpretivism, Critical Realism, Pragmatism
Layer 2: Research Approach — Deductive (theory-testing) vs. Inductive (theory-building)
Layer 3: Research Strategy — Survey, Case Study, Experiment, Grounded Theory, Ethnography
Layer 4: Research Choice — Mono method, Mixed Methods, Multi-method
Layer 5: Time Horizon — Cross-sectional vs. Longitudinal
Layer 6 (Core): Data Collection & Analysis — Interviews, questionnaires, observation, statistics
The 10 Core Types of Research — Explained for PhD Scholars
The various categories of research can be examined on four sides at the same time: data nature (qualitative/quantitative), purpose (applied/fundamental), design (exploratory/descriptive/explanatory), and time (cross-sectional/longitudinal). Here is the full list of all the categories that every doctoral student needs to know:
1. Qualitative Research
Data nature: Words, stories, observations | Research Onion layer: Interpretivism / Inductive
Qualitative research is an inquiry into human experiences that aims to achieve depth rather than breadth of data. The study of ‘why’ and ‘how’ questions about human behaviour, experience, and social events is an important part of qualitative research.
In a PhD context: In sociology, education, nursing, business, or humanities fields, qualitative research is predominant. A Chapter 3 written on qualitative research would include references to Creswell’s qualitative research design.
Real-world PhD example: ‘Exploring the lived experience of first-generation PhD scholars navigating imposter syndrome in Indian universities — a phenomenological study.’ This is a pure qualitative problem requiring depth, not measurement.
2. Quantitative Research
Data type: Numbers/statistics | Research Onion layer: Positivism / Deductive
Quantitative Research is a method that tests the hypothesis and measures the variables. It seeks generalization by extending the results from a sample to a larger population. Quantitative Research makes use of computer programs such as SPSS, R, AMOS, SmartPLS, and Python.
In a PhD: Standard in Engineering, Economics, Business, Health Sciences, and Education Measurement. Chapter 3: Justify the choice of the Positivism Paradigm. Explain the design of the instruments (validated scales) and the statistical tests that will be conducted (Regression, SEM, ANOVA).
Real-world PhD example: ‘The impact of transformational leadership on employee turnover intention among IT professionals in Chennai: a structural equation modelling approach.’ This requires quantitative, deductive, survey-based design.
3. Mixed Methods Research
Data type: Both numerical and narrative | Research Onion layer: Pragmatism
Mixed methods research combines qualitative and quantitative data collection methods into a single study. This type of research is becoming increasingly popular because it overcomes the limitations that each type of research has on its own. Creswell (2018) states that there are three main mixed methods research designs:
- Sequential Explanatory (QUAN → QUAL): Quantitative data collection precedes qualitative data collection for the purpose of explaining the results from the quantitative data.
- Sequential Exploratory (QUAL → QUAN): Qualitative data collection precedes quantitative data collection for the purpose of measuring the results from the qualitative data.
- Convergent Parallel (QUAL + QUAN simultaneously): Both qualitative and quantitative data collection methods are used simultaneously.
The point where the results from both data collection methods are integrated into a study is the most scrutinized part of a mixed methods Chapter 3.
4. Applied Research
Purpose: Solve a specific real-world problem
Applied research is based on existing science that is used to solve problems that are practical and immediately applicable. The purpose of applied research is utility, not theory development. It is often used in engineering, public health, education policy, or industry-based PhDs. The purpose of applied research is not to create theory, but to create solutions.
5. Fundamental (Pure / Basic) Research
Purpose: Expand the theoretical knowledge base
Fundamental research is curiosity-driven, not required to be immediately applicable in practical ways. Its purpose is to expand our understanding of our disciplines beyond our existing boundaries, creating foundations that applied researchers later build upon. Pure science, mathematics, philosophy, and
6. Exploratory Research
Design: Investigate new or under-documented phenomena
When the subject under study lacks substantial existing literature to draw on, exploratory research is the proper place to begin. This type of research does not seek to make definitive findings. Instead, it seeks to gain insight, identify patterns, and develop hypotheses. This type of research is often the initial phase of a multi-phase study. Its methods are flexible, including unstructured interviews, focus groups, and observations.
7. Descriptive Research
Design: Document the current state of a phenomenon
Descriptive research answers the question “what is happening?” This type of research systematically describes the characteristics of a population, an event, or a phenomenon without attempting to determine cause. Surveys, observations, content analyses are common tools. This type of research is often the initial phase of a study, providing the foundation necessary for the more analytical research.
8. Explanatory (Analytical / Causal) Research
Design: Examine the cause of a phenomenon
Explanatory research goes beyond description to establish cause-and-effect relationships. Explanatory research answers the question, “Why does this phenomenon exist?” Explanatory research employs techniques of regression analysis, SEM, or content analysis to determine cause-and-effect relationships. This type of research is the backbone of most theory-testing dissertations, which are the most academically valuable research contributions.
9. Cross-Sectional vs. Longitudinal Research
Time Horizon: Cross-sectional research – a single point in time, Longitudinal research – over a period of time
In cross-sectional research, the researcher studies the population at a single point in time. This research is more efficient, as the majority of PhD research employs the cross-sectional research design due to time constraints. Longitudinal research involves the same subjects over a period of time, which is more insightful but time-consuming, a luxury not afforded by the majority of PhD research, except for the use of a secondary longitudinal dataset.
10. Experimental vs. Non-Experimental Research
Control: Manipulated conditions vs. Natural observation
Experimental research is where the independent variable is artificially controlled to observe the effect on the dependent variable. This is the gold standard for establishing causality. Non-experimental is where the vast majority of social science and management PhDs fall – observing the natural occurrence of variables. The middle ground is the quasi-experiment.
Master Comparison Table: All 10 Types at a Glance
This table is designed to give you an at-a-glance reference for methodology decisions — and maps each type to its PhD dissertation context.
| Research Type | Data | Core Purpose | Chapter 3 Label | Common Discipline | Time Horizon |
|---|---|---|---|---|---|
| Qualitative | Words / narratives | Understand & interpret | Interpretive / Phenomenological | Social Sciences, Nursing, Education | Usually cross-sectional |
| Quantitative | Numbers / statistics | Measure & test hypotheses | Positivist / Deductive | Engineering, Economics, Sciences | Cross-sectional or longitudinal |
| Mixed Methods | Both | Triangulate & deepen findings | Pragmatist / Sequential or Convergent | Management, Health, Education | Both possible |
| Applied | Varies | Solve a real problem | Applied Research Design | Engineering, Policy, Healthcare | Cross-sectional typically |
| Fundamental | Theoretical | Build/extend theory | Pure / Basic Research | Physics, Maths, Philosophy | N/A (theoretical) |
| Exploratory | Qualitative often | Generate insights in new areas | Exploratory Design | Emerging fields / new phenomena | Cross-sectional |
| Descriptive | Survey / observation | Document current state | Descriptive Cross-Sectional | Business, Social Sciences | Cross-sectional |
| Explanatory | Existing or new data | Explain causal mechanisms | Critical / Causal / Analytical | Management, Health, Sciences | Both possible |
| Longitudinal | Time-series data | Track change over time | Longitudinal Survey / Panel | Psychology, Health Sciences | Longitudinal |
| Experimental | Controlled variables | Establish causality directly | True / Quasi-Experimental | Sciences, Education, Psychology | Cross-sectional usually |
How to Choose the Right Research Type: A PhD Decision Framework
Understanding all the various types is the theory. The practice is applying the right type to your research. And that is the area that most doctoral research scholars need the most help with. The following is the decision framework that idealaunch. uses with research scholars during methodology sessions:
Step 1: Carefully read your research question. If it is a ‘how many’, ‘how much’, or ‘to what extent’ question, then it is a quantitative research question. If it is a ‘why’, ‘how’, or ‘what does it mean to’ question, then it is a qualitative research question.
Step 2: Determine your philosophical approach. Is there a single objective measurable reality (positivism → quantitative)? Is reality socially constructed and subjective (interpretivism → qualitative)? Should you use the approach that best works for you (pragmatism → mixed research)?
Step 3: Examine the existing literature. Is there a lot of existing literature on your research topic with established surveys and questionnaires? Then it is a quantitative research topic. Is the research topic new, or is it an experience-based topic? Then it is a qualitative research topic.
Step 4: Evaluate your access to data. Can you reach 200+ participants for a survey, or is it more like 10-15 people for interviews? This is often a matter of data availability.
Step 5: Think about your schedule. Cross-sectional studies are feasible in a PhD timeline. Longitudinal studies are feasible if you’re using pre-existing panel data or if you have a relatively short study window.
Step 6: Think about your discipline. Examine 10 recent PhD dissertations in your department or discipline. What type of methodology is most common in your discipline? You may need more justification for a methodology that deviates from what’s most common in your discipline.
Step 7: Verify with a methodology expert. Before you write a single word of Chapter 3, talk to a supervisor, committee member, or methodology consultant about your methodology plans. Six months of revising Chapter 3 could be saved with a single conversation.
Common Methodology Mistakes PhD Scholars Make (And How to Avoid Them)
- Selecting a methodology based on how it sounds rather than how it is relevant to the research question. The use of the ‘mixed method’ is not inherently better than the ‘mono method’ unless the research question is such that it warrants the use of two data sets.
- Using ‘qualitative’ and ‘interpretive’ synonymously. Qualitative is a data type. ‘Interpretivist’ is a philosophical approach. Qualitative research can be done from a post-positivist approach.
- Failure to discuss the time horizon. Many students discuss their methodology without ever justifying the use of cross-sectional data. This is a viva question.
- Writing the third chapter as a definitions chapter. All definitions must be justified with an explanation of how it is relevant to the research question.
- Selecting a methodology that the supervisor is unaware of. This is a practical consideration that is rarely taken seriously. A supervisor who is unaware of the methodology that the student has adopted is unable to support the student in the viva.
Where PhD Scholars Get Stuck and Where idealaunch Steps In
The purpose of a guide like this is to create understanding. The limitation is that it does not enable you to know what specific methodology is best suited for your specific research question, specific department, specific supervisor expectations, and specific constraints of time and resources.=
That is precisely where we at idealaunch.in can step in to assist scholars. We have worked with PhD scholars all over India for many years now. We have identified precisely where scholars are getting stuck — and have specific services for each of those specific sticking points:
“I don't know which methodology fits my research question”
One-on-one methodology selection session with a domain specialist
“I know my methodology but I can't write Chapter 3”
Expert-written methodology chapters with full paradigm justification
“I have data but don't know how to analyse it”
Statistical analysis (SPSS, R, AMOS, SmartPLS) with full write-up
“I've conducted interviews but can't analyse them”
Thematic / content / discourse analysis using NVivo or ATLAS.ti
“My committee rejected my methodology — I need to rework it”
Emergency methodology audit, restructuring, and rewrite
“I need a full research proposal written and ready for approval”
Complete proposal: problem statement, objectives, framework, methodology, timeline
“I need a synopsis for my PhD panel”
Precisely structured synopses that communicate research vision to evaluation panels
Idealaunch. consultants are PhD holders themselves — not generic writers. They have sat in the chair you are sitting in, defended methodology chapters, answered viva questions about ontology and epistemology, and made it through. That lived experience is the difference between guidance that sounds right and guidance that actually works.
Frequently Asked Questions?
The main types of research in research methodology are qualitative, quantitative, and mixed methods — classified by the nature of data. Research is also classified by purpose (applied vs. fundamental), by design (exploratory, descriptive, explanatory), and by time horizon (cross-sectional vs. longitudinal). Most PhD dissertations combine types from multiple dimensions.
Qualitative research works with non-numerical data — words, meanings, and experiences — to build deep understanding of phenomena. Quantitative research works with numerical data and statistical analysis to test hypotheses and measure relationships. The choice between them depends on your research question: 'how' and 'why' questions lean qualitative; 'how much' and 'how many' lean quantitative.
Mixed methods research combines qualitative and quantitative data collection and analysis within a single study. It should be used when your research question cannot be answered adequately by either approach alone — typically when you need statistical findings AND nuanced explanations. Common in management, health, and education research, it requires careful planning of how the two data strands will be integrated.
A research method is a specific data collection or analysis technique — a survey, interview, regression, or content analysis. Research methodology is the overarching strategy that justifies which methods are used and why, including the philosophical assumptions behind them. You choose your methodology (e.g. positivist, inductive, quantitative) before selecting specific methods.
There is no universally best methodology. The right choice depends on your research question, your discipline, your data access, and your philosophical stance. Quantitative deductive designs are best for hypothesis testing. Qualitative inductive designs suit interpretive, experience-based questions. Mixed methods work when both depth and breadth are needed. The best methodology is always the one most defensible in relation to your specific research problem.
Applied research uses existing knowledge to solve a specific, real-world problem with immediate practical use. Fundamental (or pure) research aims to extend the boundaries of theoretical knowledge without requiring direct application. Most PhD programmes accept both — what matters is that your research clearly serves one purpose and that purpose is justified in your proposal and Chapter 1.
Exploratory research is used when a topic is new or under-documented and the goal is to generate insights, identify patterns, and build the groundwork for more conclusive future studies. It does not aim to produce definitive answers. It typically uses flexible, qualitative methods and is positioned in Chapter 3 as an appropriate response to the limited existing literature in the field.
Effective justification requires three elements: (1) a clear link between your research question and the chosen methodology — explain why the question demands this type of data and approach; (2) a discussion of the philosophical underpinnings (ontology and epistemology) that support your paradigm; and (3) an acknowledgment of limitations and why they are acceptable given your research aims. Citing Creswell, Saunders, or Bryman adds academic credibility to your justification.
Research Type Is Not a Chapter, It Is a Commitment
Every type of research in research methodology comes with a set of philosophical commitments, practical demands, and evaluative standards. Choosing a type is not an administrative task you complete on the way to ‘real’ research. It defines what your research is, what it can and cannot claim, and how it will be judged.
The scholars who defend their methodology chapters most confidently are not those who read the most textbooks. They are those who deeply understood the logic behind their choice — who could explain, in plain language, why their specific problem demanded their specific approach. That level of clarity is achievable. It just requires the right preparation and, often, the right guidance.
At idealaunch. that is exactly what we provide.