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Summary BRM 1 - IBA year 2
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BRM 1Lecture 1
Why should future managers know about research?
The results of good research tend to be more effective
Hunches, intuition, and past experiences are more likely to be wrong
Business research: a series of well-thought-out and carefully executed activities that enable the
manager to know how organizational problems can be solved, or at least considerably minimized.
Hallmarks of scientific research
Purposiveness: knowing the why of your research
Rigor: ensuring a sound theoretical base and methodological design
Testability: being able to test logically developed ideas based on data
Replicability: finding the same results if the research is repeated in similar circumstances
Precision & confidence: drawing accurate conclusions with a high degree of confidence
Objectivity: drawing conclusions based on facts
Generalizability: being able to apply research findings in a wide variety of different settings
Parsimony: shaving away unnecessary details, explaining a lot with a little
Research process
1. Problem definition
2. Research approach development
3. Research design development
4. Field work or data collection
5. Data integrity and analysis
6. Communicate research findings
Theoretical framework consists of:
Description of all relevant variables and their definitions
Hypotheses (expected relationships between variables)
Conceptual model (graphical representation)
Research design: A framework or plan for conducting a [...] research project. It details the
procedures necessary for obtaining the information needed to structure or solve [...] research
problems.
Exploratory research:
A flexible and evolving approach to understand phenomena that are inherently difficult to
measure
Often required when prior theory is absent and in-depth understanding is required
Aim is to develop new theory since phenomenon is new or previously uninvesitigated
Qualitve vs quantative data
Qualitative Quantitative
Smaller Larger
One on one One to many
In depth broader
Conclusive research:
1
, Characterized by clearly defined phenomena that can be measured by means of quantitative
data
Descriptive: testing the correlational relationship between two or more variables
Causal: testing the causal relationship between two or more variables by means of a
experiment
Plots in R
- Plot -> interval data
- Scatterplot -> two interval variables
- Boxplot -> one nominal and one interval variable, or just interval data
- Barplot -> categorical data or interval data
- Histogram -> interval data, gives distribution of one variable
Lecture 2
Errors
- Total error: variation between true mean value in the population of the variable of interest
and the observed value
- Random sampling error: error because the selected sample is imperfect representation of
the population of interest
- Non-sampling errors: error that can be attributed to sources other than sampling and that
can be random or non-random
- Non-response errors: error that occurs when some participants included in the sample do
not respond
- Response errors: error that arises from participants who do responds but who give
inaccurate answers or whose answers are mis-recorded or mis-analyzed
A structured technique for data collection consists of a series of questions, written or verbal, that a
participant answers.
A questionnaire is the result of trade-offs and is based on guidelines; it is not a matter of simply
following some rules to generate a questionnaire that guarantees optimality
Challenges:
1. Translate – the information needs to be a set of specific questions that participants can and
will answer
2. A questionnaire must uplift, motivate and encourage the participant to become involved, to
cooperate and to complete the task
3. A questionnaire should minimize response error
Research design process
1. Specify the information needed
2. Specify the type of interviewing method
3. Determine the content of individual questions
a. Guidelines to decide what to include in individual questions
i. Is the question necessary?
ii. Are several questions needed instead of one?
b. If several questions are needed, make sure to ask them in separate questions, avoid
double-barreled questions (do you think coca cola is tasty and refreshing? – you
should make two questions out of these)
4. Overcome the respondent’s inability and unwillingness to answer
a. Guidelines when composing questions:
i. Is the participant informed? -> adding filter questions
2
, ii. Is the participant able to articulate? -> pictures/maps/descriptions
iii. Can the participant remember? (how many liters of soft drinks did you
consume in the last four weeks? – you probably have no idea)
b. Reduce the effort for the participant
5. Choose question structure
a. Unstructured -> open questions
i. + enable to express general attitudes and opinions
ii. + enable to indicate other relevant issues
iii. - high risk of bias
iv. - coding costly and time-consuming
b. Structured -> specified set of response alternatives and response format
6. Choose question wording
a. Define the issue
b. Use ordinary words
c. Use unambiguous words
d. Avoid leading or biasing questions (do you agree that separating garbage is
important? – how important is separating garbage to you?)
e. Avoid implicit alternatives (do you like to fly when travelling short distances? – offer
an alternative)
f. Avoid implicit assumptions (do you think governments should increase budget for
environmental programs? – do you think governments should increase budget for
environmental programs if it would result into higher personal taxes?)
g. Avoid generalizations and estimates (what is the annual per capita per expenditure
on clothes in your household? )
h. Use positive and negative statements – people are more inclined to agree to
statements
7. Arrange the questions in proper order
a. Arrange the questions in proper order
i. Opening questions: simple, interesting and non-threatening in order to
boost confidence and willingness to cooperate
ii. Basic information (research topic) first, then classification information
(socio-economic) next, and finally identification (postal code) information
iii. Difficult questions late in sequence to increase answer likelihood
iv. Funnel approach: general questions should precede specific questions in
order to avoid the responses to specific questions biasing the answers to
general questions
v. Logical order: all questions that deal with a particular topic should be asked
before beginning a new topic and include transitional phases
8. Identify the form and layout
9. Reproduce the questionnaire
10. Eliminate problems by pilot testing
Remaining steps
Test on small samples
Best face-to-face to observe reactions
Debriefing: ask respondents about their experience
Poll:
Why would you measure digital competence with multiple questions? There are many aspects to
digital competence that need to be separately measured
Poll:
3
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