1. INTRODUCTION TO RESEARCH METHODS ..........................................................................................
2. HYPOTETHIC-DEDUCTIVE APPROACH + ONTOLOGY/EPISTEMOLOGY .................................................
3. LITERATURE REVIEW ..........................................................................................................................
4. THEORY .............................................................................................................................................
5. RESEARCH DESIGN .............................................................................................................................
, 1. Chapter 1: Introduction to Research
• What is research?
The process of finding answers or solutions to a problem after study and analysis of a specific
phenomenon.
Carried out in a scientific way: organized, systematic, data-based, critical, and objective
investigation.
• Research comes in many forms:
Research aims at:
• building theory
• testing a theory
• describing a situation/phenomenon
ð Theory: a set of ideas that intends to explain a phenomenon, a causal relationship,…
Research is the result of analysis of:
• primary data = gathered first-hand
• secondary data = already available (company, industry, country level, etc.)
Data can be:
• quantitative (numbers – ex. through surveys)
• qualitative (words – ex. through interviews)
• Applied vs. basic research
Applied:
Purpose:
• Driven by practice
• To improve understanding of specific business problem
• To apply the results of research findings in solving specific problems, e.g. in an
organization
ð Problem of generalizability
ð Set by clients
ð Conducted by academics, practitioners, policy makers
Examples:
“A study into the ways of improving job satisfaction at Uber”
“Development of diversification strategies in the pharmaceutical industry in view of market
expansion”
2
,Basic (or fundamental, or pure):
Purpose:
• Driven by curiosity
• To create new knowledge
• To build theories that may serve as a foundation of further studies
• No commercial purpose, yet innovations or practical implications may occur later
ð Problem of applicability
ð Self-initiated
ð Mainly conducted by academics
Examples:
“A critical analysis of word of mouth as a marketing strategy”
“A study of factors impacting the platform economy”
• Why managers need to know about research?
• To understand empirical research in the business domain
• To identify and solve problems
• To get a feel for causal relationships
• To make the right decisions, based on facts rather than vested interests
• To help distinguish between good and bad studies
• To interact effectively with researchers or consultants
• To cope with increasing complexity and uncertainty
• The hallmarks of scientific research:
Example: a manager is interested in investigating how employees’ commitment to the
organization can be increased.
1. Purposiveness
Purpose with a specific focus: “increase commitment”.
2. Rigor
Good theoretical base and methodology.
ð High degree of exactitude
Assume: managers asks 10-12 employees to indicate what would increase their level of
commitment.
Is this approach scientific? No, it is biased because he asks about their personal feelings.
Check theory, previous studies, etc to know what to do on a large scale.
3
, 3. Testability
Applies to the hypotheses of the study
What is a hypothesis? Testable statement:
• derived from theory
• which predicts what you expect to find in empirical data
• about “what will happen?”
Hypothesis – an example:
“Employees who actively participate in decision making will have a higher level of
commitment”
4. Replicability
Findings and conclusions should be replicable in other studies.
Tests of hypotheses should be supported in other circumstances,
adding to validity of the study.
5. Precision and confidence
Findings are based on a model, a sample, differing from population.
Precision = about exactness, how correct we are.
ð Important to avoid that small errors from sample lead to big errors on a larger scale.
Confidence = how certain we are that estimates hold true for population
6. Objectivity
Conclusions drawn should be fact-based, derived from actual data, not subjective.
If hypothesis not supported by results => conclusion that higher participation would lead to
higher commitment would not make sense.
Hypothesis – an example:
“Employees who actively participate in decision making will have a higher level of
commitment”
7. Generalizability
Applicability of findings in various settings.
The wider the applicability, the more useful the research.
Hypothesis – an example:
“Employees who actively participate in decision making will have a higher level of
commitment”
8. Parsimony (simplicity)
Simplicity is preferred over complexity.
4
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