Research can be classified in many ways depending on the purpose, method, data, and application.
Kothari provides several major classifications, explained below with examples.
A. Based on Purpose / Objective 🎯
1. Exploratory Research 🧐 (Formulative Research)
Used when very little information exists about a topic.
It helps researchers gain familiarity, identify variables, and form hypotheses.
Example:
Exploring how the metaverse might impact future employment by conducting interviews and preliminary observations.
2. Descriptive Research 📊
Describes characteristics or facts clearly and systematically.
It focuses on “what exists” rather than why it happens.
Example:
Surveying consumer preferences for electric vehicles in Bengaluru.
3. Analytical Research 📈
The researcher uses existing data to analyze patterns, relationships, or evaluations.
Example:
Using 10 years of inflation data to identify factors that influence India’s inflation rate.
4. Diagnostic Research 🔍
Aims to find the causes of a problem.
Example:
Identifying why a company is facing high employee turnover.
5. Hypothesis-Testing (Causal) Research ⚗️
Tests if one variable influences or causes change in another.
Example:
Testing whether increased advertising spending leads to higher sales.
B. Based on Method of Study 🔬
1. Qualitative Research 👥
Focuses on human opinions, behaviors, attitudes, and non-numerical data.
Methods: Interviews, focus groups, observations
Example: Understanding why students prefer online classes using in-depth interviews.
2. Quantitative Research 🔢
Uses numerical data and statistical analysis.
Methods: Surveys, experiments, structured questionnaires
Example: Examining the relationship between study hours and exam scores.
3. Mixed Methods Research 🔄
Combines qualitative + quantitative approaches for richer insights.
Example:
Studying employee satisfaction using interviews (qualitative) and surveys (quantitative).
C. Based on Nature of Data 🗂️
1. Primary Research 📝
Researchers collect the data themselves.
Example: Field surveys, experiments, direct observations.
2. Secondary Research 📚
Uses data already collected by others.
Examples: Government reports, journals, census data.
D. Based on Application 🛠️
1. Basic (Pure) Research 🧪
Develops new theories and expands scientific knowledge.
No immediate practical use is required.
Example: Studying quantum particle behavior.
2. Applied Research 🚀
Solves real-world problems.
Example: Designing a mobile app to provide maternal healthcare in rural areas.
E. Based on Inquiry Type 💡
1. Conceptual Research 🧠
Involves developing new theories, concepts, or models.
Example: Creating a new leadership model for digital workplaces.
2. Empirical Research 🔍
Based on observation or experimentation.
Relies on real-world evidence.
Example: Studying how light exposure affects plant growth in a lab.
F. Based on Time Dimension ⏳
1. Cross-Sectional Research 🕒
Data collected at one particular time.
Example: A 2025 survey of smartphone users.
2. Longitudinal Research 📆
Data collected from the same participants over several years.
Example: A 10-year study tracking children’s cognitive development.
G. Based on Control Over Variables ⚙️
1. Experimental Research 🧪
Researcher manipulates variables to identify cause-and-effect.
Example: Testing if a new teaching method improves exam results.
2. Non-Experimental Research 👀
No control over variables; the researcher only observes.
Example: Studying gender-based income differences.
H. Based on Environment 🌍
1. Field Research 🏞️
Conducted in the natural environment of participants.
Example: Observing customer behavior inside a supermarket.
2. Laboratory Research 🧫
Conducted in a controlled, scientific environment.
Example: Testing chemical reactions in a lab.
I. Based on Level of Analysis 🔎
1. Micro Research 👤
Focuses on individuals or small groups.
Example: Studying job satisfaction among 20 employees in one office.
2. Macro Research 🌏
Covers large populations or systems.
Example: Examining unemployment patterns across India.
Conclusion 📝
A single research study can fall under multiple categories—e.g., descriptive + quantitative + applied + field-based.
Kothari emphasizes that understanding these classifications helps researchers design better studies and select the correct methodology.
