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College aantekeningen QRM3-AM (E_EBE3_QRMAM)
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Lecture 1:inductive vs deductive reasoning:
• Inductive reasoning: drawing a conclusion based on an observation.
o So start with an observation and then you end with an hypothesis
o So the outcome of inductive reasoning is one or more hypothesis
o Most used in qualitative research, you interview someone and then you set a
hypothesis
o Works in the opposite direction. It is a process where we observe specific
phenomena and on this basis arrive at general conclusions. Hence, in inductive
reasoning, we work from the more specific to the more general.
• Deductive reasoning: conclusion follows from a set of reasons (premises)
o You start with an hypothesis and then you do the study
o Most used in quantitative research
o In deductive reasoning, we work from the more general to the more specific. We
start out with a general theory and then narrow down that theory into specific
hypotheses we can test. We narrow down even further when we collect specific
observations to test our hypotheses. Analysis of these
o specific observations ultimately allows us to confirm (or refute) our original theory.
• It is possible to combine these in research process
o In different cycles
Research process:
1. Theory:
2. Constructs/concepts
a. Constructs: more complex to measure
b. Concepts: things that are measurable and that is very clear (e.g., your height)
3. Via an operational definition you name variables
Hypothesis: expected relationship between variables based on a theory.
Theory: is a set of interrelated concepts, definitions, and propositions to explain and predict
phenomena
➔ Theory is not the opposite of a fact. If a theory does not work in practice
than the theory is incomplete
➔ Theory is more general than a hypothesis.
A complete theory must contain four elements:
1. What?: Which concepts/variables logically should be considered as part of the explanation
of the phenomena of interest?;
2. How?: Having identified a set of concepts/variables, how are they (causally) related?;
3. Why?: What are the underlying psychological, economic, or social dynamics that justify the
selection of concepts/variables and the proposed (causal) relationships?;
4. Who?, Where?, When?: These conditions place limitations on the propositions generated
from a theoretical model. These temporal and contextual factors set the boundaries of
generalizability, and as such constitute the range of the theory.
,In other words, a theory is constructed so as to answer a number of questions: What
concepts/variables are being studied and how do they relate? Why would this be so? And when
(where and to whom) does the theory apply?
Hypothesis: statement about concepts or constructs expressed in measurable units.
A hypothesis can be defined as a tentative, yet testable, statement, which predicts what you expect
to find in your empirical data. Hypotheses are derived from the theory on which your conceptual
model is based and are often relational in nature.
• Descriptive hypothesis: value of one variable, you just have one variable and you are
describing the value
o E.g., 80% of students pass the QRM course
• Relational hypothesis: relationship between 2 variables of one case, you have
multiple variables and you explain the relation between them
o E.g., students who have spent more time on the QRM course get a higher
grade
Constructs: conceived (by the researcher) specifically for the study or for theory building
• More abstract
• Difficult to observe
• Often built from concepts
o E.g., yuppies (construct), composed of concepts (age, amount of income, type of car)
o Other examples:
▪ Job satisfaction
▪ Customer loyalty
If you have an abstract construct you need to come up with an operational definition:
• Definition expressed in measurable units
• We have to be able to count, measure
• Definition must be so clear that everyone understands the meaning
Then when you have translated the abstract construct into something measurable than it is a
variable. (variable = empirical equivalent of a construct)
different types of variables:
• Dependent variable: the variable that we want to explain
o The dependent variable is the variable of primary interest to the researcher. The
researcher’s goal is to understand and describe the dependent variable, or to explain
its variability, or predict it. It is
o possible to have more than one dependent variable in a study.
• Independent variable: variable that explains (in part) the dependent variable
o This is the one that the researcher can manipulate
o It is generally conjectures that an independent variable is one that influences the
dependent variable in either a positive or negative way. The variance in the
dependent variable is accounted for by the independent variable. To establish that a
change in the independent variable causes a change in the dependent variable, all
o four of the following conditions should be met:
▪ A change in the dependent variable should be associated with a change in
the independent variable.
, ▪ There must be a time sequence in which the two occur: the cause must occur
before the effect.
▪ No other factor should be a possible cause of the change in the dependent
variable.
▪ A logical explanation (a theory) is needed and it must explain why the
independent variable
• Moderating variable: the strength of the relationship between a dependent and independent
variable is affected by a moderating variable
o Can strengthen and weaken it.
o The moderating variable is one that has a strong contingent effect on the
independent variable dependent variable relationship. That is, the presence of a
third variable (the moderating variable)
o modifies the original relationship between the dependent and the independent
variables.
• Intervening variable/mediating variable: the influence of an independent variable on a
dependent variable is through an intervening variable
o A mediating variable (or intervening variable) is one that surfaces between the time
the independent variables start operating to influence the dependent variable and
the time their impact is felt on it.
o Bringing a mediating variable into play helps you to model a process.
o E.g., the influence of price and loyalty programs on customer loyalty runs through
customer satisfaction
o E.g A researcher expects that top executives who have relatively many options in
their compensation packages make more risky decisions. By making these risky
decisions, the companies of these top managers are more likely to be in financial
trouble. What type of variable is the decision risk in this theory? → mediating
The hallmarks of scientific research
1. Purposiveness; the research has a purposive focus.
2. Rigor; rigor connotes carefulness, scrupulousness, and the degree of exactitude in research
investigations.
1. Testability; scientific research lends itself to testing logically developed hypotheses to see
whether or not the data support the educated conjectures or hypotheses that are developed
after a careful study of the problem situation.
2. Replicability; the extent to which a re-study is made possible by the provision of the design
details of the study in the research report.
4. Precision and confidence; precision reflects the degree of accuracy or exactitude of the
results on the basis of the sample, to what really exists in the universe. Confidence refers to
the probability that our estimations are correct.
5. Objectivity; the conclusions drawn through the interpretation of the results of data analysis
should be objective; that is, they should be based on the facts of the findings derived from
actual data, and not on our own subjective or emotional values.
6. Generalizability; refers to the scope of applicability of the research findings in one
organizational setting to other settings.
7. Parsimony; can be introduced with a good understanding of the problem and the important
factors that influence it.
a. E.g. If it is possible to explain 45% of the variance in the dependent variable using 3
variables then this is often preferred to a model in which you can explain 48% of the
variance in the dependent variable using 15 variables
, Hypothetico-deductive method
1. Identify a broad problem area
2. Define the problem statement
3. Develop hypotheses
4. Determine measures
5. Data collection
6. Data analysis
7. Interpretation of data
A scientific hypothesis must meet two requirements. The first criterion is that the hypothesis must be
testable. The second criterion and one of the most central tenets of the hypothetical deductive
method, is that the hypothesis must also be falsifiable.
The requirement of falsifiability emphasizes the tentative nature of research findings: we can only
“prove” our hypothesis until they are disproved.
A theoretical framework represents your beliefs on how certain phenomena (or variables or
concepts) are related to each other (a model) and an explanation of why you believe that these
variables are associated with each other (a theory).
The process of building a theoretical framework includes:
1. Introducing definitions of the concepts or variables in your model.
2. Developing a conceptual model that provides a descriptive representation of your theory.
3. Coming up with a theory that provides an explanation for relationships between the
variables in your model.
From the theoretical framework, then, testable hypotheses can be developed to examine whether
your theory is valid or not. The hypothesized relationships can thereafter be tested through
appropriate statistical analyses.
Part of theoretical framework:
- The definitions of key concepts in the framework
- The relationships among the concepts in the framework
- The reasons why there are relationships among the concepts in the framework
Not part of the theoretical framework:
- The measurement scales for each concept from the framework
Lecture 2: research design
Research process:
1. Research question
a. Literature review→ problem statement & hypotheses
2. Research design
a. Sampling
b. Data collection method (survey, interview, experiment, archival data)
3. Pilot testing
4. Data collection
5. Data analysis and interpretation
6. Reporting of results
Research design:
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