Introduction
Key scientific terminology
Constructs are theoretical concepts that may or may not be observable and measurable (so they are
often abstract): trust, customer loyalty, job satisfaction, organizational interdependence, etc. Variables
are also theoretical concepts, but they must be observable and measurable -> essentially, they are
operationalized constructs. One construct can consist of many variables.
A proposition is a researcher’s statement about the relationship between two or more theoretical
constructs. It can be about abstract and non-measurable constructs. It can be developed conceptually
or based on empirical data. It does not have to be measurable or directly testable.
A hypothesis is a statement about the relationship between two or more variables (thus
operationalized constructs). A hypothesis is typically informed by any underlying proposition(s). It
should be testable and show the direction of the relationship / effect between the variables.
A theory is a statement of relationships between
units (constructs) observed or approximated in the
empirical world. A theory answers the questions:
how, when or why? Every theory has boundaries.
The research objective explains the main purpose of
a research project, its intended contribution to the
scientific literature and management practice:
- In academic papers, this can be found in the
introduction and abstract
- It should explain to the reader what, why and how (by doing what) should be achieved
The research question is the focal point of the research objective and project. This can be found in the
introduction of academic papers.
The research strategy is a ‘plan of action’: how the research objective will be achieved. It is always
described in every academic paper and can be typically found in the Method section. Existing
research strategies (survey, case study, etc.) represent a systematic set of rules and guidelines.
Some papers may only have a research objective or question (or both), and this depends on the field
or journal tradition and the personal preference.
Approaches to theory development
Research projects will involve the use of theory. That theory may or may not be made explicit in the
design of the research, although it will usually be made explicit in your presentation of the findings
and conclusions. The extent to which you are clear about the theory at the beginning of your research
raises an important question concerning the design of your research project. This is often portrayed as
two contrasting approaches to the reasoning you adopt: deductive or inductive. Deductive reasoning
occurs when the conclusion is derived logically from a set of premises, the conclusion being true
when all the premises are true. In contrast, in inductive reasoning there is a gap in the logic argument
between the conclusion and the premises observed, the conclusion being judged to be supported by
,the observations made. Although the conclusion is supported by the observations, it is not
guaranteed.
There is also a third approach to theory development that is common: abductive reasoning -> begins
with a ‘surprising fact’ being observed. This surprising fact is the conclusion rather than a premise.
Based on this conclusion, a set of possible premises is determined that is considered sufficient or
nearly sufficient to explain the conclusion. It is reasoned that, if this set of premises was true, then the
conclusion would be true as a matter of course. Because the set of premises is sufficient (or nearly
sufficient) to generate the conclusion, this provides reason to believe that it is also true.
Building on these three approaches, if your research starts with theory, often developed from reading
of literature, and you design a research strategy to test the theory, you are using a deductive
approach. If your research starts by collecting data to explore a phenomenon and you generate or
build theory (conceptual framework) then you are using an inductive approach. Where you are
collecting data to explore a phenomenon, identify themes and explain patterns, to generate a new or
modify an existing theory which you subsequently test through additional data collection, you are
using an abductive approach.
Deduction involves the development of theory that is then subjected to a rigorous test through a
series of propositions. As such, it is the dominant research approach in the natural sciences, where
laws present the basis of explanation, allow the anticipation of phenomena, predict their occurrence
and therefore permit them to be controlled.
There are six steps through which a deductive approach will progress:
1. Put forward a tentative idea, a premise, a hypothesis or set of hypotheses to form a theory
2. By using existing literature, or by specifying the conditions under which the theory is expected
to hold, deduce a testable proposition or number of propositions
, 3. Examine the premises and the logic of the argument that produced them, comparing this
argument with existing theories to see if it offers an advance in understanding. It it does, then
continue
4. Test the premises by collecting appropriate data to measure the concepts or variables and
analyzing them
5. If the results of the analysis are not consistent with the premises, the theory is false and must
either be rejected or modified and the process restarted
6. If the results of the analysis are consistent with the premises then the theory is corroborated
Deduction possesses several important characteristics. First, there is the search to explain causal
relationships between concepts and variables. The research would use a highly structured
methodology to facilitate replication, an important issue to ensure reliability. An additional important
characteristic of deduction is that concepts need to be operationalized in a way that enables facts to
be measured, often quantitatively. Reductionism is when problems as a whole are better understood
if they are reduced to the simplest possible elements. The final characteristic is generalization. In
order to be able to generalize it is necessary to select our sample carefully and for it to be of sufficient
size.
In the inductive approach, theory follows data rather than vice versa. The emergence of the social
sciences in the 20th century led social science researchers to be wary of deduction. They were critical
of a reasoning approach that enabled a cause-effect link to be made between particular variables
without an understanding of the way in which humans interpreted their social world. Developing
such an understanding is the strength of an inductive approach.
Followers of induction would also criticize deduction because of its tendency to construct a rigid
methodology that does not permit alternative explanations of what is going on. In that sense, there is
an air of finality about the choice of theory and definition of hypothesis.
Research using an inductive approach to reasoning is likely to be concerned with the context in which
events take place. Therefore, the study of a small sample of subjects might be more appropriate than
a large number as with the deductive approach. Researchers in this tradition are more likely to work
with qualitative data and to use a variety of methods to collect these data in order to establish
different views of phenomena.
An abductive approach moves from theory to data and vice versa, thereby combining an deductive
and inductive approach. It begins with the observation of a ‘surprising fact’, it then works out a
plausible theory of how this could have occurred.
Why is the choice about the approach to theory development so important? First, it enables you to
make a more informed decision about your research design, which is the overall configuration of a
piece of research involving questions about what kind of evidence is gathered and from where, and
how such evidence is interpreted in order to provide good answers to your initial research question.
Second, it will help you to think about those research strategies and methodological choices that will
work for you and those that will not. Third, the knowledge of different research traditions will enable
you to adapt your research design to cater for constraints. These may be practical or they may arise
from a lack of prior knowledge of the subject.
, The approach you should use depends on the emphasis of the research and the nature of the
research topic. A topic on which there is a wealth of literature from which you can define a theoretical
framework and a hypothesis lends itself more readily to deduction. With research into a topic that is
new, is much debate and on which there is little existing literature, it may be more appropriate to
work inductively by generating data and analyzing and reflecting upon which theoretical themes the
data are suggesting. Alternatively, a topic about which there is a wealth of information in one context
but far less in the context in which you are researching may lend itself to an abductive approach
enabling you to modify an existing theory.
The time you have available will be an issue. Deductive research can be quicker to complete, albeit
that time must be devoted to setting up the study prior to data collection and analysis. On the other
hand, abductive and inductive research can be more protracted. Often the ideas, based on a much
longer period of data collection and analysis, have to emerge gradually. This leads to another
important consideration, the extent to which you are prepared to indulge in risk. Deduction can be a
lower-risk strategy, although there are risks. With induction and abduction you have to live with the
fear that no useful data patterns and theory will emerge.
Lecture 1
Managers or other decision makers in any type of organization need to make decisions all the time.
Some can be made based on experience, intuition, or advice from others. Other decisions need
thoughtful contemplation of alternatives. If new knowledge is required to make a decision, research
may be needed. Understanding the principles of (good) research helps:
1. To execute (or commission) your own research
2. To critically understand the research done by others
Basic steps of research:
1. Formulate a knowledge question -> “what product features are valued the most?”
2. Collect relevant knowledge that is already out there -> knowledge on how to study this
question and existing lists of product features
3. Collect new, additional data -> develop a strategy to sample respondents, respondents rate
product designs in a survey
4. Analyze and interpret -> perform conjoint analysis, measure the utility of different product
features
5. Formulate the answer to the question -> rank product features and product designs based on
relative utility
Some principles of scientific research:
1. Science progresses on the basis of testable hypotheses and evidence
2. Research does not take place in a vacuum
3. Do not trust other people’s science without your own critical analysis
4. Confidence in a theory grows as more and more studies support (and perhaps refine) the
theory