flowchart LR
RD[Research Design] --> E[Exploratory]
RD --> D[Descriptive]
RD --> DI[Diagnostic]
RD --> EX[Experimental / Causal]
EX --> P[Pre-experimental]
EX --> T[True experimental]
EX --> Q[Quasi-experimental]
EX --> F[Factorial]
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44 Research: Concept and types; Research designs
44.1 Concept of Research
Research is “a systematic investigation aimed at discovering, interpreting and revising facts, events, theories and applications”. Clifford Woody’s classic definition runs: research is “defining and redefining problems, formulating hypotheses, collecting, organising and evaluating data, making deductions and reaching conclusions, and at last carefully testing the conclusions to determine whether they fit the formulated hypotheses”. The word research literally means “to search again” — a continuous, critical, and creative pursuit of new knowledge. In business and management research, the goal is to generate evidence for decision-making — both at the level of theory (pure / fundamental research) and at the level of practice (applied research).
44.2 Objectives of Research
- Exploratory — to gain familiarity with a phenomenon.
- Descriptive — to portray accurately the characteristics of a particular situation.
- Diagnostic — to determine the frequency with which something occurs.
- Hypothesis-testing — to test a causal relationship.
- Predictive — to forecast future occurrence.
- Action / Evaluative — to evaluate the effectiveness of a programme.
44.3 Types of Research
| Basis | Categories |
|---|---|
| Purpose | Pure / Fundamental · Applied |
| Method | Descriptive · Analytical · Experimental |
| Inquiry | Quantitative · Qualitative · Mixed |
| Reasoning | Inductive · Deductive |
| Setting | Field · Laboratory · Simulation |
| Time | Cross-sectional · Longitudinal |
| Approach | Empirical · Conceptual · Historical |
44.4 Steps in the Research Process
- Identify and formulate the research problem.
- Review of literature — what is already known.
- Formulation of hypothesis (where applicable).
- Research design — blueprint.
- Data collection — primary and secondary.
- Data analysis — descriptive and inferential.
- Interpretation and reporting.
- Generalisation and theory-building / action recommendations.
44.5 Research Design — Concept
A research design is “the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research purpose with economy in procedure” (Selltiz et al.). It is the blueprint for the entire research, specifying what data to collect, from whom, how, and how to analyse it.
44.6 Types of Research Design
| Design | Purpose | Methods | Hypothesis? |
|---|---|---|---|
| Exploratory | Discover ideas; familiarise with topic | Literature review, expert interviews, focus groups, secondary data | Generates hypothesis |
| Descriptive | Describe characteristics or functions; what, when, where, how | Surveys, observation, panel, case-study | Tests hypothesis (typically) |
| Diagnostic | Identify causes / frequency / correlates | Surveys, correlation studies | Tests hypothesis |
| Experimental / Causal | Establish cause-effect; manipulate IV, measure DV | Laboratory and field experiments; RCTs | Tests causal hypothesis |
44.6.1 Experimental Designs
- Pre-experimental — one-group pre-test post-test; weakest internal validity.
- True experimental — random assignment to treatment / control; pre-test and post-test.
- Quasi-experimental — no random assignment; common in social science.
- Randomised Control Trial (RCT) — gold standard for causal inference.
- Factorial design — multiple IVs interacting.
- Latin square — controls two extraneous variables.
- Completely Randomised Design (CRD), Randomised Block Design (RBD).
44.7 Internal vs External Validity
| Validity | Question |
|---|---|
| Internal | Does the treatment actually cause the effect in the sample? |
| External | Can the findings be generalised to other settings, times, people? |
44.7.1 Threats to Internal Validity
History, maturation, testing, instrumentation, regression to mean, selection bias, mortality, diffusion of treatment.
44.8 Qualitative vs Quantitative Research
| Dimension | Qualitative | Quantitative |
|---|---|---|
| Data | Words, images, observations | Numbers |
| Sample | Small, purposive | Large, representative |
| Analysis | Coding, thematic, narrative | Statistical |
| Aim | Understand, interpret, explore | Test, generalise, predict |
| Methods | Interviews, focus groups, ethnography, case study | Surveys, experiments, secondary data |
44.9 Hypothesis
A hypothesis is “a tentative proposition relating two or more variables, capable of being tested empirically”. Null hypothesis (H₀) is the default — no effect, no difference; alternative (H₁) is what the researcher wants to demonstrate.
- Clear and precise.
- Testable — must be capable of empirical verification.
- Specific — variables clearly defined.
- Related to existing theory.
- Consistent with known facts.
- Simple and parsimonious.
PYQs ask: exploratory research is for idea-generation — it does not test a hypothesis. Descriptive and causal tests hypotheses.
44.10 Practice Questions
The definition of research as "defining and redefining problems, formulating hypotheses, …" is by:
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Research that aims at *generalising theoretical knowledge* without immediate practical use is:
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Match each design with its primary purpose:
| Design | Purpose | ||
| (i) | Exploratory | (a) | Describe characteristics |
| (ii) | Descriptive | (b) | Establish cause-effect |
| (iii) | Causal / Experimental | (c) | Generate ideas / hypotheses |
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The "gold standard" for establishing cause-effect is:
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**Internal validity** addresses:
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A good hypothesis must be:
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A study comparing brand attitudes of 18-25 and 26-35 age groups *at the same point in time* is:
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Which is **not** typically a qualitative method?
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The *null hypothesis* (H₀) typically:
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**Exploratory** research is typically used when:
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In a **Completely Randomised Design (CRD)**, treatments are assigned to experimental units:
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Which is **not** a threat to internal validity?
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Moving from *general theory to specific observations* is:
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A **Latin Square** design controls for:
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A *case study* is typically:
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Research design is best described as:
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Which is typically a **quantitative** approach?
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Arrange these research steps in order: (i) Hypothesis formulation (ii) Problem identification (iii) Data collection (iv) Interpretation
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External validity addresses:
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A study aimed at *identifying causes / frequency / correlates* of a phenomenon is:
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44.11 Quick Recall
- Research (Clifford Woody) — systematic problem-solving + hypothesis testing.
- Types: Pure vs Applied; Descriptive vs Analytical vs Experimental; Quantitative vs Qualitative; Inductive vs Deductive; Cross-sectional vs Longitudinal.
- Eight steps: Problem → Lit Review → Hypothesis → Design → Data Collection → Analysis → Interpretation → Generalisation.
- Research Design = blueprint (Selltiz).
- Four major designs: Exploratory (idea-gen), Descriptive (characteristics), Diagnostic (frequency / correlates), Experimental / Causal (cause-effect, RCT).
- Experimental designs: CRD, RBD, Latin Square (controls 2 nuisance variables), factorial.
- Internal validity — causation in sample; External validity — generalisability.
- Threats to internal validity: history, maturation, testing, instrumentation, regression-to-mean, selection, mortality.
- Hypothesis: testable, specific, theory-related. H₀ = no effect; H₁ = alternative.