The Hallmarks of Scientific Research

Chapter 2
SCIENTIFIC INVESTIGATION
Research Methods: Chapter
2

 The Hallmarks of Scientific Research
 Limitations to scientific research in the management
 The building blocks of science and hypo-thetico
deductive method of research
 Seven steps of hypo-thetico deductive method
 Other types of research (Case studies and Action research)
Introduction to Research
TOPICS
2

Research Methods: Chapter 2
The Hallmarks of Scientific Research;
1. P
2. R
3. T
4. R
5. P
6. O
7. G
8. P
1. G
2. O
3. P
4. P
5. P
6. R
7. T
8. R
Main Characteristics

1. Purposiveness
2. Rigor
3. Testability
4. Replicability
5. Precision and Confidence
6. Objectivity
7. Generalizability
8. Parsimony
1. P
2. R
3. T
4. R
5. P
6. O
7. G
8. P
1. G
2. O
3. P
4. P
5. P
6. R
7. T
8. R
Main Characteristics

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

Increased performance levels
 Thus it has a purposive focus.
Purposiveness

 A good theoretical base and sound methodological
design would add rigor to the purposive study.
 Rigor adds carefulness, accuracy and the degree of
exactitude in research.
Example:
 A manager asks only from 10-12 employees how to
increase the level of commitment.
 And on the basis of their responses the manager reaches
to conclusions on how commitment can be increased?
 Whole approach to the investigation would be unscientific.
 It would lack rigor for the following reasons
Rigor

1. Based on few employees’ opinion that does not represent the
whole population
2. Bias and incorrectness in the responses
3. There might be other influences on commitment which are
ignored and are important for a researcher to know
 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.

 After random selection manager and researcher develop
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.
 If the scientific analysis of data supports the
hypothesis, it is accepted as a fact or as truth.
 The researcher might hypothesize that those employees
who perceive greater opportunities for participation in
decision making would have a higher level of
commitment.
Testability

 It means that the results of the tests of hypotheses
should be supported again and yet again when the
same type of research is repeated in other similar
circumstances.
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 credibility 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.
 Every object is attracted to the center of the earth.
Replicability

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 estimation more favorably than if he has
indicated that the loss of production days was somewhere
between 20 and 50.
Precision and 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.
Precision and Confidence

 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!
Objectivity

 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.
Generalizability

 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.
Example:
 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 and valuable to the manager than
 if it were recommended that he should change 10 different
variables to increase organizational commitment by 48%.
Parsimony

 It is not possible to conduct 100% scientific research
studies.
 It is due to human behavior being studied.
 Data collection in the subjective areas of feelings, moods,
attitudes and perceptions may not be 100% accurate.
 Sometimes, the obstacle is due to lack of a representative
sample.
Obstacles or Limitations
In business Research:

2
The Building Blocks of science in Research;

 A sales manager might observe that customers are
perhaps not as pleased as they used to be.
 This process of observation of the situation is what gets
most of the research started
 Now the manager is to determine weather there is a real
problem if it is so then how serious it is?
Observation: Example

 This problem identification calls for some preliminary
data gathering
 The manager might talk casually to a few customers to
find out how they feel about the products and customer
service
 During these conversation the manager might find that
the customers like the products but are upset because
of the stocks availability
 And they perceive the salesperson as not being helpful
The problem identification:

 From discussions with the salespersons, the manager
might discover that the factory does not supply the
goods on time and promise new delivery dates that it
fails on occasions to keep.
 Salespersons might also indicate that they try to please
and retain the customers by communication the delivery
dates given by the factory.
 Gathered information helped the manager to determine
that the problem does exist.
The problem identification:

 Gathered information also helps the manager to
formulate a conceptual model and theoretical framework
of all the factors contributing to the problems.
 In this case there is a network of connections among the
following factors.
 Delays by the factory in delivering the goods
 The notification of later delivery dates are not kept
 Salesperson’s promises can not be fulfilled
 All of them contribute to customer dissatisfaction
Theoretical Framework:

 From the theoretical framework several hypotheses can
be generated and tested to determine if the data support
them.
 Concepts are then operationally defined so that they
can be measured
Hypotheses:

 A research design is set up to decide on, among other
issues to collect further data, analyze and interpret
them.
 And finally to provide an answer to the problem.
 The process of drawing from logical analysis an
inference that declare to be conclusive is called
deduction.
A research design:

 Answers to issues can be found either by the;
 Process of Induction
 Process of Deduction,
 By a combination of the two.
Deduction and Inductions

2
Deduction & Induction Methods in Research;

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
The Hypothetico-Deductive Method;
The Seven-step Process

 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).
 Drop in sales
 Frequent production interruptions
 Customer switching
 Disinterestedness of employees
2
dentify a broad problem area

 Scientific research starts with a definite aim or purpose
 It involves the seeking of information in depth, of what is
observed, to find solutions for identified problems
 A problem statement that states the general objective of the
research should be developed
 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,
 Then it is followed by structured interviews.
efine the problem statement

 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.
 A scientific hypothesis must meet the two criteria
 Hypothesis must be testable and falsifiable
2
evelop hypotheses

 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.
2
Hypothesizing

 Measurement of variables (variables and measuring scales)
 After the development of the hypotheses, data with respect
to each variable in the hypotheses need to be obtained.
2
etermine measures

 Further data are collected to test the hypotheses that are
generated in the study.
2
ata Collection

 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 relationship of two or more factors in the
hypotheses for example:
 Stock availability and customer satisfaction.
2
Data Analysis

 Deduction is the process of arriving at conclusions
by interpreting the meaning of results of the data
analysis.
2
terpretation of data

 Case studies and action research are sometimes
used to study certain types of issues.
1. Case Studies
2. Action Research
2
Other Types of Research;
Other Types

 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.
2
Case Studies

 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.
2
Action Research

The Hallmarks of Scientific Research

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