Summary Class notes - BRT Slides

- BRT Slides
- -
- 2019 - 2020
- Tilburg University (Tilburg University, Tilburg)
- Information Management
256 Flashcards & Notes
1 Students
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Summary - Class notes - BRT Slides

  • 1574290800 Setting the scene

  • What is business research?
    A series of well-thought out activities and carefully executed data analyses that help a manager to avoid, solve, or minimize a problem.
  • Why should future managers know about business research?
    Managerial decisions based on the results of good research tend to be more effective.
    Managerial decisions based on hunches, intuition, and past experiences are more likely to be wrong.
  • 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.
  • Hallmarks of "good" business research
    - Purposiveness
    - Rigor
    - Objectivity
    - Parsimony
    - Replicability
    - Generalizability
  • Purposiveness
    Knowing the why of the research.
  • Rigor
    - Ensuring a sound theoretical base.
    - Ensuring a sound methodological design.
  • Objectivity
    Drawing conclusions based on facts (rather than on subjective ideas).
  • Parsimony
    - Shaving away unnecessary details.
    - Explaining a lot with a little.
  • Replicability
    Finding the same results if the research is repeated in similar circumstances.
  • Generalizability
    Being able to apply the research findings in a wide variety of different settings.
    - Should hold for fundamental research, but much less so for applied research.
  • Applied research
    - To solve a current problem faced by a manager.
    - Applies to a specific company.
    - Within firms or research agencies.
  • Fundamental (or basic) research
    - To generate new knowledge about how problems that occur in several firms can be solved.
    - Applies to several organizational settings.
    - Mainly within universities and knowledge institutes.
  • Deductive research
    Theory --> Data, testing theory.
  • Inductive research
    Data --> Theory, building theory.
  • Seven step deductive research process
    1. Define the business problem.
    2. Formulate the problem statement.
    3. Develop a theoretical framework.
    4. Choose a research design.
    5. Collect data.
    6. Analyze data.
    7. Write-up.
  • Seven step inductive research process
    1. Define the business problem.
    2. Formulate the problem statement.
    3. Provide a conceptual background.
    4. Choose a research design.
    5. Collect data.
    6. Analyze data.
    7. Develop theory.
  • 1574377200 The research process

  • When does a business problem occur?
    - The actual situation is not seriously wrong, but can be improved.
    - The actual situation is seriously wrong, and needs to be solved asap.
  • What makes a good business problem?
    - Feasibility, is it doable?
    - Relevance, is it worthwhile?
  • Feasibility
    - Is the problem demarcated?
    - Can the problem be expressed in variables?
    - Are you able to gather the required data?
  • Relevance
    - Managerial relevance: who benefits from having the problem solved?
    - Academic relevance: Has the problem already been solved in prior research?
  • Managerial relevance
    - Managers
    - End users
    - Public policy makers
  • Academic relevance
    - Completely new topic
    - New context
    - Integrate scattered research
    - Reconcile contradictory research
  • What makes a good problem statement?
    - Formulated in terms of variables and relations.
    - Open-ended question 
    - Stated clearly/unambiguously
    - Managerially and academically relevant
  • What makes good research questions?
    - Should collectively address the problem statement.
    - First theoretical, then practical research questions.
    - Stated clearly/unambiguously
  • Theoretical research questions
    - Context questions
    - Conceptualization questions
    - Relationship questions
  • Practical research questions
    - Relationships questions
    - Implication question
  • 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 define variables?
    - Based on careful literature review.
    - If many different definitions exist in literature
                 - Acknowledge the major differences.
                 - End with a definition that focuses on the shared meaning                         across definitions, or pick one definition and justify why.
    - Avoid jargon, use more simplified and commonplace terms.
    - Examples are not substitutes for a definition!!!!
    - Alway use exactly the same variable names throughout your research!!!!
  • 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.
  • Independent variable
    Influences the dependent variable in either a positive or a negative way.
  • Dependent variable
    The variable of primary interest.
  • Mediating variable
    A variable that explains the mechanism at work between X and Y. (How or why does X affect Y)
  • Full mediation
    X only has an effect on Y through MEDIATOR.
  • Partial mediation
    X has an indirect effect on Y through MEDIATIOR, but also a direct effect on Y.
  • Moderating variable
    A variable that alters the strength and sometimes even the direction (positive or negative) of the relationship between X and Y. (When or for whom the effect is stronger)
  • Quasi moderation
    MODERATOR moderates the relationship between X and Y, but it also has a direct effect on Y.
  • Pure moderation
    MODERATOR moderates the relationship between X and Y, but it has no direct effect on Y.
  • How to develop a good hypothesis?
    - Derived from theory.
    - Testable.
    - Unambiguous.
  • Hypotheses
    A tentative statement about the coherence between two or more variables. 
    - a relationship
    - a difference
  • Directional hypotheses
  • Undirectional hypotheses
  • Null-hypothesis
    - Expresses no relationship between variables or no difference between groups.
    - Set up in order to be rejected (in favour of the alternate hypothesis).
    - Rarely presented in research reports.
  • Alternate hypothesis
    - Expresses a relationship between variables or a difference between groups.
    - Research hypothesis.
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Sampling equivalence
Achieve representative AND comparable samples.
  • equivalence = comparability not keeping everything the same.
  • timing
  • sample frame 
  • data collection procedure
Measurement equivalence for secondary data
  • Categories may differ across countries.
  • Calibration systems may differ across countries.
  • Reliability threat: data may be old or scarce in certain countries.
  • Validity threat: governments may paint too rosy pictures.
How to obtain metric equivalence?
  • Pre-data collection (reliability)
  • Post-data collection (validity)
Super hero's
Predominantly men, lower educated people and more masculine countries.
Predominantly women, higher educated people and more feminine countries.
Socially desirable responding
  • Egoistic response tendencies.
    • Self-deceptive, exaggerated but honestly held positive self-view (Super Hero).
  • Moralistic response tendencies.
    • Deliberate attempt to project a favorable self-image (Saint).
Extreme responding
Positively related to individualism, uncertainty avoidance, and masculinity.
Metric equivalences: Threats to validity
  • Response style bias
    • Extreme responding
    • Socially desirable responding
Metric equivalence: Threats to reliability
  • Some languages have fewer terms to express gradation in evaluations than others.
  • Some countries lack familiarity with certain scaling/scoring formats.
Metric equivalence
Do the scores given by respondents have the same meaning in different countries?