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Complete summary for Business Research Methods 1 (quantitative) including calculations and examples

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This summary includes everything you will need in order to pass your quantitative research methods exam! The summary covers all the lecture content. In addition the summary includes examples, calculations and images to enhance your understanding of the material. People that used this summary have p...

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  • 30 december 2022
  • 110
  • 2021/2022
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Lecture 1 - Introduction



Managerial decisions that are based on:

• The results of “good” research tend to be more effective

• Hunches, intuition and past experiences are more likely to be wrong



The managers are from Mars, researchers are from Venus myth:

• There is no need to study business research for a future manager

But, managers with knowledge about business research have an advantage over
managers who don’t



The most research is not read myth:

• Business research ends up in the bottom drawer

This happens often, however this is often due to the manager being intimidated by
the research, caused by a lack of understanding.



The big bucks myth:

• Business research is only for the wealthiest organisations

This is not true, one of the solutions being A/B-testing. The practice of giving a part
of the visitors of the website version A and the other part of visitors version B. After
a while, you will look at the difference in conversion rate and select the version
with the highest rate. So, business research is diverse: it can be cheap or expensive.



The big decision myth:

• Business research is only useful when you have a major decision to make.



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, For small decisions, it is often better for the manager to carry out their own
research. Creating strategies often does not take a long time but analysing which
strategy to use is very time consuming.



The universal truth myth:

• There is just one best way of researching a business problem.

There is no such thing as an absolute truth in business, nevertheless this does not
imply that any research is good.



Business research

“A series of well-thought-out and carefully executed activities that enable the
manager to know how organisational problems can be solved, or at least
considerably minimised” (Sekaran & Bougie, , p. )



A business researcher:

• Speci es the information necessary to address these issues

• Designs the method for collecting information

• Manages and implements the data collection process

• Analyses the results

• Communicates the ndings and their implications



Hallmarks of scienti c research
• Purposiveness • Precision and con dence

• Rigor • Objectivity

• Testability • Generalisability

• Replicability • Parsimony




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, . Purposiveness

• Does it lead to the goal that you had in mind?

• Knowing the why of the research



. Rigor

• Ensuring a sound theoretical base and methodological design




• Left: A theoretical base that explains job performance based on articles
including the important concepts.

• Right: sample of a population that resembles this population



. Testability

• Being able to test logically developed ideas based on data

• Narrow down different explanations



. Replicability

• Finding the same results if the research is repeated in similar circumstances

• Can you replicate your ndings?



. Precision and con dence

• Drawing accurate conclusions with a high degree of con dence

• Narrow con dence intervals re ect accurate estimates


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, . Objectivity

• Drawing conclusions based on facts (rather than subjective ideas)

• did you incorporate intuition or were you completely objective?



. Generalisability

• Being able to apply research ndings in a wide variety of different settings




. Parsimony

• Shaving away unnecessary details, explaining a lot with a little

• did you include the right amount of variables that were actually required or did
you include unnecessary variables



Research process



• Identify problem area and de ne problem statement



• Theoretical framework, hypothesis and model



• Determine nature of research, methods, sampling…



• Data collection



• Data preparation and data analysis



• Data interpretation

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