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Business Research Techniques summary

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Summary made for final exam Business Research Techniques, passed this course with a 8.

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  • January 30, 2020
  • 18
  • 2019/2020
  • Summary

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By: wiebederuijsscher • 3 year ago

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Business Research Techniques
You should know about business research:
- To be able to perform business research;
- To steer business research;
- To evaluate business research.

The hallmarks of good research are:
1. Purposiveness, the knowing ‘why’ of your research;
2. Rigor, ensuring (zorgen voor) a theoretical base and a methodological design;
3. Objectivity, drawing conclusions based on facts;
4. Parsimony, shaving away unnecessary details, explaining a lot with a little;
5. Replicability, finding the same results in the research is repeated in similar circumstances;
6. Generalizability, being able to apply the research findings in a wide variety of different settings;

Applied research is research to solve a current problem faced by a manager and applies to a specific
company. Fundamental research is to generate new knowledge about how problems that occur in
several firms can be solved and applies to several organizational settings.

Deductive vs. Inductive research




The 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. Interpret results.


Deductive research = quantitative
research.

,The inductive research process contains the same steps as the deductive research process, only the
3rd and 7th steps are different.
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.

Inductive research = qualitative research.

What makes a good business problem?
Feasibility:
The problem needs to be demarcated (afgebakend), expressed in variables and you need to be able
to gather the required data.

Relevance:
Managerial relevance who benefits from having the problem solved?
This need to be the managers, end users (consumers, investors…) and public policy makers
(government, EU, …).
Academic relevance has the problem not already been solved in a prior research?
Completely new topic, new context, integrate scattered research, reconcile contradictory research
(solve contradictions through introducing one or more moderators).

What makes a good problem statement?
A good problem statement is formulated in term of variables and relations, is a open-ended question
and is stated clearly/unambiguously (ondubbelzinnig).

It is important that a problem statement is unambiguous, specific, focused and academic. The
problem state should be formulated in terms of variables and relations.

What makes good research questions?
- Should collectively address the problem statement, one problem statement is translated into
multiple research questions;
- First theoretical, then practical research questions, in the same order as addressed in the
research report!
- Stated clearly/unambiguously, no vague elements.

Developing a theoretical framework
A theoretical framework represents your beliefs on how certain variables are related to each other
and an explanation of why you believe that these variables are associated with each other.
The process of building a theoretical framework includes:
- Conceptual model, descriptive/graphical representation of your theory;
- Variable definitions, introducing definitions of the concepts or variables in your model;
- Hypotheses, relationship between the variables in the model.

Conceptual model:

,In your conceptual model you have different variables:
1. Dependent variable;
2. Independent variables;
3. Mediating variables;
4. Moderating variables.



The dependent variable is the variable of primary interest.
The independent variable influences the dependent variable in a positive or negative way.
A mediating variable is a variable that explains the mechanisms at work between X and Y.
(What is the underlying mechanism HOW or WHY does X affect Y?).




A moderating variable is a variable that alters the strength and sometimes even the direction
(positive/negative) of the relationship between X and Y.
(WHEN or FOR WHOM the effect is stronger).

Quasi moderation: MOD moderates the relationship
between X and Y, but it also has a direct effect on Y.




Pure moderation: MOD moderates the relationship between
X and Y, but it has no direct effect on Y

,Variable definitions:
Define all variables and motivate why these variables are important to include in your research.
Based on a careful literature review.
If many different definitions exist in the literature:
- Acknowledge the major differences;
- End with a definition that focuses on the shared meaning across definitions, or pick one
definition and justify why.

Always use EXACTLY the same variable names throughout your research

Hypothesis development:
A hypothesis can be defined as a tentative, yet testable, statement which predicts what you expect
to find in your empirical data.
It’s a tentative statement about the coherence between two or more variables
(relationship/difference).

What makes a good hypothesis?
- Derived from theory;
- Testable;
- Unambiguous (ondubbelzinnig).

Predicting relationships for example, companies that invest more in R&D are more profitable.
Predicting differences for example, woman have better parking skills then men.

There are directional and undirectional hypothesis and null and alternate hypothesis:
- Directional hypothesis are one-sided, if in the stating between the two variables such as
positive, negative, more than, less than and the like are used.
- Undirectional hypothesis are two sided, are used when the relationship between variables
has yet to be tested.
- Null hypothesis expresses no relationship between variables/groups and is set up to be
rejected (not very common).
- Alternate hypothesis expresses a relationship between variables or a difference between
groups.

, Causal and correlational research
Step 4. Choose a research design
A research design is a plan for the collection, measurement and analyses of data.
There are three critical research design decisions that have to be made:
1. Choosing between strategy;
2. Choosing between statistical techniques;
3. Choosing between sampling techniques.



Research Framework
Base Quantitative research Qualitative research

Type Causal Correlational Exploratory

Strategy Experiments Archival Survey In-dept interviews
Research Research Focus groups
Observations

Causal research
Causal studies test whether or not one variable causes another to change. Causal studies are being
executed with an experiment and should be measured with correlation between the variables.
- X and Y co-occur (there is correlation);
- A logical explanation for the effect of X on Y;
- X precedes (voorafgaat) Y in time;
- There is no other cause that explains the co-occurrence of X and Y.

You use experiments to study a new phenomenon, to capture concrete and vivid information.

Lab experiments are experiments done to establish a cause-and-effect relationship in an artificial,
contrived environment in which one or more independent variables are manipulated.

Field experiments are studies conducted to establish cause-and-effect relationships using the same
natural environment in which the subject under study normally function, but manipulation is still
possible.

Correlational research
Correlational research van be archival research or survey research.

Archival research is research based on data that already exist = secondary data.
External archival research is data collected by sources outside the form (by third parties).
Internal archival research is data collected by sources inside the form (existing company data).

Survey research is research based on a questionnaire, to which respondents record their answers,
typically with closely defined alternatives.

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