Business Research
Methods
Adopted From
Fourth Edition
Uma Sekaran
Instructor: Ahmad Sohail Lodhi
MBE, LLB
Chapter 2
SCIENTIFIC
INVESTIGATION
After completing this chapter you
would be able to understand:

The Hallmarks of Scientific Research
 Some obstacles to conducting scientific
research in the management area
 The building blocks of science in research
 The hypothetico deductive method
 Other types of research
Definition of Scientific
Research
Scientific Research focusing on
solving problems and pursues a
step by step logical, organized
and rigorous method to identify
the problems, gather data,
analyze them and draw valid
conclusions there from.
Why Scientific Research?

This research is not based on hunches,
experience and intuition.
 It is purposive and rigorous.
 Enables all those who are interested in
researching and knowing about the same or
similar issues to come up with comparable
findings when data are analyzed.
 Findings are accurate and confident.
 Apply solutions to similar problems.
 It is more objective.
Cont.

Highlights the most critical factors at the work
place that need specific attention to solve or
minimize problems.
 Scientific Investigation and Managerial Decision
Making are integral part of effective problem
solving.
 It can be applied to both basic and applied
research.
The Hallmarks of Scientific Research
The hallmarks or main distinguishing
characteristics of scientific research may be
listed as follows:
1.
2.
3.
4.
5.
6.
7.
8.
Purposiveness
Rigor
Testability
Replicability
Precision and Confidence
Objectivity
Generalizability
Parsimony
Hallmarks of Scientific Research
1.
Purposiveness
 It has to start with a definite aim or purpose.
 The focus is on increasing employee
commitment.
 Increase employee commitment will translate
into less turnover, less absenteeism and
increased performance levels.
 Thus it has a purposive focus.
2. Rigor

A good theoretical base and sound methodological design
would add rigor to the purposive study.
 Rigor adds carefulness, scrupulousness and the degree of
exactitude in research.
Example:
A manager asks 10-12 employees how to increase the level
of commitment. If solely on the basis of their responses the
manager reaches several conclusions on how employee
commitment can be increases, the whole approach to the
investigation would be unscientific. It would lack rigor for
the following reasons:
Based on few employees
2. Bias and incorrectness
3. There might be other influences on commitment
which are ignored and are important for a researcher
to know
Thus, Rigorous involves good theoretical base and
thought out methodology.
 These factors enable the researcher to collect the right
kind of information from an appropriate sample with
the minimum degree of bias and facilitate suitable
analysis of the data gathered.
 This supports the other six too.
1.
3. Testability
After random selection manager and researcher
develops certain hypothesis on how manager
employee commitment can be enhanced, then
these can be tested by applying certain statistical
tests to the data collected for the purpose.
The researcher might hypothesize
that those employees who perceive
greater
opportunities
for
participation in decision making
would have a higher level of
commitment.
4. Replicability
It means that it can be used again if
similar circumstances prevails.
Example:
The study concludes that participation in
decision making is one of the most
important factors that influences the
commitment, we will place more faith and
credence in these finding and apply in
similar situations. To the extent that this
does happen, we will gain confidence in
the scientific nature of our research.
5. Precision
and Confidence
Precision
– Precision refers to the closeness of the findings
to “reality” based on a sample.
– It reflects the degree of accuracy and exactitude
of the results of the sample.
Example: If a supervisor estimated the
number of production days lost during the
year due to absenteeism at between 30 and
40, as against the actual of 35, the precision of
my estimation more favorably than if he has
indicated that the loss of production days was
somewhere between 20 and 50.
Confidence
– Confidence refers to the probability that our
estimations are correct.
– That is, it is not merely enough to be precise,
but it is also important that we can
confidently claim that 95% of the time our
results would be true and there is only a 5%
chance of our being wrong.
– This is also known as confidence level.
6. 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 subjective
or emotional values.
Example: If we had a hypothesis that stated that greater
participation in decision making will increase
organizational commitment and this was not supported
by the results, it makes no sense if the researcher
continues to argue that increased opportunities for
employee participation would still help!
7. Generalizability
It refers to the scope of applicability of the
research findings in one organization setting to
other settings.
Example: If a researcher’s findings that
participation in decision making enhances
organizational commitment are found to be true in
a variety of manufacturing, industrial and service
organizations, and not merely in the particular
organization studied by the researcher, then the
generalizability of the findings to other
organizational settings in enhanced. The more
generalizable the research, the greater its
usefulness and value.
8. Parsimony
Simplicity in explaining the phenomenon or problems that
occur, and in generating solutions for the problems, is
always preferred to complex research frameworks that
consider an unmanageable number of factors.
For instance, if 2-3 specific variables in the work situation are
identified, which when changed would raise the
organizational commitment of the employees by 45%, that
would be more useful be more useful and valuable to the
manager than if it were recommended that he should
change 10 different variables to increase organizational
commitment by 48%.
The Building Blocks of Science in
Research
Deduction and Inductions
Answers to issues can be found
either by the process of
induction or the process of
induction, or by a combination
of the two.
Deduction

Deduction is the process by which we arrive at a
reasoned conclusion by logical generalization of a
known fact.
Example: we know that all high performers are highly
proficient in their jobs.
If John is a high performer, we then conclude that he
is highly proficient in his job
Induction

Induction is a process where we observe certain
phenomena and on this basis arrive at conclusions.
In other words, in induction we logically
establish a general proposition based on
observed facts.
To define or describe the
figure.
Figure is a five-sided figure
enclosing two dots.
The Hypothetico-Deductive Method
Observation
– Observation is the first stage, in which
one senses that certain changes are
occurring or that some new behaviors,
attitudes and feelings are surfacing in
one’s environment (i.e., the work
place).
– How does one observe phenomena and
changes in the environment?
Preliminary Information Gathering:
– It involves the seeking of information in depth, of
what is observed.
– This could be done by talking informally to several
people in the work setting or to clients or to other
relevant sources, thereby gathering information on
what is happening and why. (Unstructured
interviews)
– Then it is followed by structured interviews.
– Additionally by doing library research or obtaining
information through other sources, the investigator
would identify how such issues have been tackled
in other situations.
Theory Formulation
– It is an attempt to integrate all the
information in a logical manners, so that the
factors responsible for the problem can be
on conceptualized and tested.
– The theoretical framework formulated is
often guided by experience and intuition.
– In this step the critical variables are
identified and examined as to their
contribution or influence in explaining why
the problem occurs and how it can be
solved.
Hypothesizing
– It is the next logical step after theory formulation.
– From the theorized network of associations among
the variables, certain testable hypotheses or
educated conjectures can be generated.
– Hypothesis testing is called deductive research.
Sometimes, hypotheses that were not originally
formulated do get generated through the process of
induction.
Further Specific Data Collection
–After the development of the
hypotheses, data with respect
to each variable in the
hypotheses need to be
obtained.
–Further data are collected to
test the hypotheses that are
generated in the study.
Data Analysis
– Data gathered are statistically analyzed
to see if the hypotheses that were
generated have been supported.
– Co relational method will be used to
analyze and determine the relation ship
of two or more factors in the
hypotheses for example: stock
availability and customer satisfaction.
Deduction
–Deduction is the process of
arriving at conclusions by
interpreting the meaning of
results of the data analysis.
Other Types of Research

1.
2.
Case studies and action research
are sometimes used to study
certain types of issues.
Case Studies
Action Research
Case Studies

Case studies involve in depth, contextual analyses of
similar situations in the other organizations, where
the nature and definition of the problem happen to be
the same as experienced in the current situation.
 Case study, as a problem solving technique, is not
often undertaken in organizations because such
studies dealing with problems similar to the one
experienced by a particular organization of a
particular size and in a particular type of setting are
difficult to come by.
Action Research

The researcher begins with a problem that is already
identified and gathers relevant data to provide a
tentative problem solution.
 This solution is then implemented, with the
knowledge that there may be unintended
consequences following such implementation.
 The effects are then evaluated, defined and diagnosed
and the research continues on an ongoing basis until
the problem is fully resolved.