Research methods for Business and Economics
Lecture topics
• Introduction p. 2-3
• Scientific approach and choosing your topic p. 4-5
• Literature review p. 6-8
• Theory and concepts p. 9-11
• Research design p.12-15
• Interviews p.16-18
• Observation p. 19-22
• Experiments p. 23-28
• Content analysis p. 29-31
• Action research and grounded theory p. -
• Case study design p. 32-35
• Questionnaires p. 36-38
• Measurement p. 39-41
• Sampling p. 42-47
Lecture 1. Introduction
1
,What is research?
= the process of finding answers or solutions to a problem
Done scientifically organized, systematic, data-based, repeatable, and
critical
In business, research helps guide better decision-making
Forms and aims of research
Aims build theory, test theory, describe, explain situations
Theory: set of ideas to explain a phenomenon logically
Data sources:
1. Primary: collected first handed (surveys, interviews…)
2. Secondary: already collected (company reports, industry stats…)
Types of data:
1. Quantitative: numbers (statistics, questionnaires…)
2. Qualitative: words/meanings (interviews, case studies)
Applied and basic research
Applied research:
- Driven by practice, solves real business problems
- Directly useful for managers/policy makers
Basic research:
- Driven by curiosity, builds theory
- Long-term impact, often academic
Business research = applied science (uses applied research, but also borrows
theories from economics, psychology, sociology)
Why do managers need research?
- To identify/solve problems
- Understand causes of events
- Make fact-based decisions
- Spot good vs. bad studies
- Communicate with researchers/consultants
- Manage complexity and uncertainty
Characteristics pf scientific research
1. Purposiveness clear goal (ex. What drives employee commitment?)
2. Rigor strong theory and exact methodology
3. Testability hypothesis must be testable
4. Validity 2 major types
- Internal: does X really cause Y?
- External: can results be generalized?
5. Objectivity conclusions based on data not opinion
6. Generalizability applies to different settings/contexts
7. Representativity sample must be large enough and well chosen
2
, 8. Replicability other researchers should get similar results
9. Parsimony keep explanations simple (prefer fewer factors that explain
more)
Research roadmap
1. Topic selection
2. Problem statement
3. Research question
4. Literature search and review
5. Research methodology/design (data collection, sampling, quali, quanti, mixed,
time frame, context)
6. Data analysis and interpretation
7. Reporting (BA paper, MA thesis, PhD dissertation)
Method and methodology
Method (what?) = data collection tool (interviews, surveys, observations,
databases)
Methodology (why?) = overall strategy/design guiding methods (qualitative,
quantitative, mixed, case study, experiments, action research)
Lecture 2. Scientific approach and choosing your topic
3
, A hypothetico-deductive approach (a seven-step process)
1. Identify a board problem area
2. Define the problem statement (objectives/research questions)
3. Develop testable hypothesis
4. Choose measures for variables
5. Collect data
6. Analyze data (regression, correlation …)
7. Interpret results (accept/reject hypothesis, suggest implications, or call for
more research)
- Hypothesis = testable statement, proven true/false by data
- Keep explanations simple (Ockham’s razor: use the smallest number of
elements)
- If results support hypothesis strengthens theory/ policy
- If not theory rejected/needs revision
Deductive vs. inductive approaches
Deductive (top-down):
- Start with theory form hypotheses collect data test
- Example: test if “job autonomy increases job satisfaction”
Inductive (bottom-up):
- Start with data identify patterns build theory
- Example: interview customers find that eco-labels raise satisfaction
propose new theory
Best practice: combine both (theory informs data, data refines theory
Ontology and epistemology
Ontology = nature of reality (what exists?)
- Objectivism: reality is objective, same for everyone (process, GDP)
- Subjectivism: reality is socially constructed (stress, fairness)
some concepts can be both (culture)
Epistemology = nature of knowledge (how do we know?)
- Positivism: knowledge = observable facts, cause-effect, research is
independent
- Interpretivism: knowledge built through interpretation, context matters,
researcher’s viewpoint counts
- Critical realism: reality exists but can’t be fully observed, we only
approximate it
Choosing a research topic
1. Define the research problem and question
- Not “something wrong”, but a gap or issue worth exploring
4
Lecture topics
• Introduction p. 2-3
• Scientific approach and choosing your topic p. 4-5
• Literature review p. 6-8
• Theory and concepts p. 9-11
• Research design p.12-15
• Interviews p.16-18
• Observation p. 19-22
• Experiments p. 23-28
• Content analysis p. 29-31
• Action research and grounded theory p. -
• Case study design p. 32-35
• Questionnaires p. 36-38
• Measurement p. 39-41
• Sampling p. 42-47
Lecture 1. Introduction
1
,What is research?
= the process of finding answers or solutions to a problem
Done scientifically organized, systematic, data-based, repeatable, and
critical
In business, research helps guide better decision-making
Forms and aims of research
Aims build theory, test theory, describe, explain situations
Theory: set of ideas to explain a phenomenon logically
Data sources:
1. Primary: collected first handed (surveys, interviews…)
2. Secondary: already collected (company reports, industry stats…)
Types of data:
1. Quantitative: numbers (statistics, questionnaires…)
2. Qualitative: words/meanings (interviews, case studies)
Applied and basic research
Applied research:
- Driven by practice, solves real business problems
- Directly useful for managers/policy makers
Basic research:
- Driven by curiosity, builds theory
- Long-term impact, often academic
Business research = applied science (uses applied research, but also borrows
theories from economics, psychology, sociology)
Why do managers need research?
- To identify/solve problems
- Understand causes of events
- Make fact-based decisions
- Spot good vs. bad studies
- Communicate with researchers/consultants
- Manage complexity and uncertainty
Characteristics pf scientific research
1. Purposiveness clear goal (ex. What drives employee commitment?)
2. Rigor strong theory and exact methodology
3. Testability hypothesis must be testable
4. Validity 2 major types
- Internal: does X really cause Y?
- External: can results be generalized?
5. Objectivity conclusions based on data not opinion
6. Generalizability applies to different settings/contexts
7. Representativity sample must be large enough and well chosen
2
, 8. Replicability other researchers should get similar results
9. Parsimony keep explanations simple (prefer fewer factors that explain
more)
Research roadmap
1. Topic selection
2. Problem statement
3. Research question
4. Literature search and review
5. Research methodology/design (data collection, sampling, quali, quanti, mixed,
time frame, context)
6. Data analysis and interpretation
7. Reporting (BA paper, MA thesis, PhD dissertation)
Method and methodology
Method (what?) = data collection tool (interviews, surveys, observations,
databases)
Methodology (why?) = overall strategy/design guiding methods (qualitative,
quantitative, mixed, case study, experiments, action research)
Lecture 2. Scientific approach and choosing your topic
3
, A hypothetico-deductive approach (a seven-step process)
1. Identify a board problem area
2. Define the problem statement (objectives/research questions)
3. Develop testable hypothesis
4. Choose measures for variables
5. Collect data
6. Analyze data (regression, correlation …)
7. Interpret results (accept/reject hypothesis, suggest implications, or call for
more research)
- Hypothesis = testable statement, proven true/false by data
- Keep explanations simple (Ockham’s razor: use the smallest number of
elements)
- If results support hypothesis strengthens theory/ policy
- If not theory rejected/needs revision
Deductive vs. inductive approaches
Deductive (top-down):
- Start with theory form hypotheses collect data test
- Example: test if “job autonomy increases job satisfaction”
Inductive (bottom-up):
- Start with data identify patterns build theory
- Example: interview customers find that eco-labels raise satisfaction
propose new theory
Best practice: combine both (theory informs data, data refines theory
Ontology and epistemology
Ontology = nature of reality (what exists?)
- Objectivism: reality is objective, same for everyone (process, GDP)
- Subjectivism: reality is socially constructed (stress, fairness)
some concepts can be both (culture)
Epistemology = nature of knowledge (how do we know?)
- Positivism: knowledge = observable facts, cause-effect, research is
independent
- Interpretivism: knowledge built through interpretation, context matters,
researcher’s viewpoint counts
- Critical realism: reality exists but can’t be fully observed, we only
approximate it
Choosing a research topic
1. Define the research problem and question
- Not “something wrong”, but a gap or issue worth exploring
4
