An overview of the importance of research methods in the field of management, the types of research methods commonly used, and the role of research in decision-making.
Introduction to Research Methods in Management
Key concepts, steps, and tools for conducting rigorous managerial research
| Reason | What It Looks Like in Practice |
|---|---|
| Informed Decision‑Making | Use data to choose strategies, allocate resources, and set performance targets. |
| Problem Solving | Identify root causes of low productivity, high turnover, or market decline. |
| Theory Development | Build or test models of leadership, motivation, or organizational change. |
| Credibility & Accountability | Provide evidence for stakeholders, investors, and regulators. |
| Paradigm | Ontology (Nature of Reality) | Epistemology (How We Know) | Typical Methods |
|---|---|---|---|
| Positivist | Objective, measurable reality | Knowledge through observation & testing | Experiments, surveys, secondary data analysis |
| Interpretivist | Constructed, socially negotiated reality | Knowledge through understanding meanings | Interviews, focus groups, case studies |
| Critical | Reality shaped by power & ideology | Knowledge through critique & emancipation | Action research, discourse analysis |
| Pragmatic | Multiple realities, useful truth | Knowledge through what works for the problem | Mixed‑methods, design‑based research |
Define the Problem / Research Question
Review the Literature
Develop a Conceptual Framework & Hypotheses
Choose a Research Design
Select the Methodology & Data Collection Techniques
| Technique | When to Use | Strengths | Limitations |
|---|---|---|---|
| Questionnaire Survey | Large samples, quantifiable variables | Standardized, statistically analyzable | Response bias, limited depth |
| Semi‑structured Interview | Exploring meanings, motivations | Rich, flexible data | Time‑consuming, interviewer effect |
| Observation (e.g., shadowing) | Studying actual behavior | Contextual, real‑time | Observer bias, limited generalizability |
| Experiment / Field Trial | Testing causal effects | High internal validity | May lack external realism |
| Secondary Data Analysis | Historical trends, financial metrics | Cost‑effective, large N | Data quality depends on source |
Sampling Design
Data Collection & Management