Read the summary and the most important questions on BRT Slides

• Setting the scene

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• Why should future managers know about business research?

  - To be able to perform business research.
  - To be able to steer business research.
  - To be able to evaluate business research.

• The research process

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• What makes a good business problem?

  - Feasibility, is it doable?
  - Relevance, is it worthwhile?

• Theoretical framework consist of

  - Variable definitions:
              - Define all variables.
              - Motivate why these variables are important to include.
  - Conceptual model - graphical representation:
              - Cover all variables and relationships.
  - Hypotheses - relationships between variables:
              - Provide a logical justification/backing.
              - Based on theory.

• How to build a conceptual model?

  - Variables are building blocks: Dependent variables, Independent variables, Mediating variables, Moderating variables.
  - Relationships are arrows: Main effect, Direct/Indirect effect, Moderating effect.

• Causal and correlational research

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• Critical research design questions

  - Choosing between (deductive) research strategies.
  - Choosing between statistical techniques.
  - Choosing between sampling designs.

• Two types of deductive research

  - Causal research
  - Correlational research

• Can causal claims never be made in a correlational setting?

  To establish causality, randomized experiments are the gold standard. But econometric methods that allow making causal claims in a correlational setting.

• Statistical techniques and sampling design

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• Low representativeness of a sample

  - Properties of the population are over- or underrepresented in the sample.
  - High sampling error.

• Solutions for coverage errors

  - If small, recognize but ignore.
  - If large, redefine the population in terms of the sampling frame.

• Survey research

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• When to use survey research?

  - When you want to say something about a population, but you cannot measure the whole population (very often).
  - When you are interested in quantitative descriptors.
  - Personal measures:
     - subjective measures
     - observation not possible/feasible