Main ingredients of science
- Theory: formalized explanations of phenomena
- Expectations: hypotheses about what we expect to observe
- Studies: experiments, surveys, case studies, etc.
- Observations: data stemming for studies
Logics of scientific reasoning
- Inductive reasoning
- Deductive reasoning
- Abductive reasoning
Inductive reasoning
give a series of observations, you can derive an explanation/generalization that is probably true.
- From specific to general.
- Theory-building
Example: when you see a pond with white swans (observation) and therefore you conclude that probably all swans are white (generalization)
Deductive reasoning
based on premises that are true, you can logically come to a conclusion that is true
- From general to specific.
- Theory-testing
Example: all men are mortal, socrates is a men, therfore socrates is mortal
Abductive reasoning
based on interactions between observations and theories, you come to a likely explanation for what you see
- From interactions between specific and general.
- Theory building or modification
Example: when your engine will not start and there are different theories that can explain this
Scientific argumentation logics
- Induction: observe reality and generalize
- Deduction: logically construct propositions/hypothesis
- Abduction: conceive new ideas or hunches
Research cycle
- Managerial problem
- Knowledge question
- Review of evidence
- Research design
- Data collection
- Data analysis
- Research outcomes
- Recommendation to management
in all steps: critical reflection
4 types of knowledge questions
- Descriptive knowledge
- Explanatory knowledge
- Predictive knowledge
- Prescriptive knowledge
Research design
- Plans for data collection
- Plans for data analysis
- Threats to validity and how to deal with those
- Time plan/project plan
Elements of a discussion
- Conclusion
- Contribution to theory
- Contribution to practice
- Limitations
- Suggestions for future research
CIMO statement
From this research we learn that in Context C, if you do Intervention I, the Mechanism M will help to achieve Outcome O.
Simulated data
you create a model that can be manipulated logically to determine how the ‘real’ physical world works
Empirical data
can be historical or real-time, but cannot provide you with future records, for future simulated
Theory building
output of this are theoretical propositions that explain a certain phenomenon or process
Theory testing
output of this is ‘evidence’ and quantifications of relationships between established variables
