Research Method for Business chapter 4

The Research Process;
Theoretical framework
and
hypothesis development
Chapter 4
Welcome
Research Methods: Chapter 4

S. No. Title Reference
1 Supply chain planning for a
multinational enterprise: a
performance analysis case
study
Fahimnia, B., Parkinson, E., Rachaniotis, N.,
Zubair, M. & Goh, A. (2013). Supply chain
planning for a multinational enterprise: a
performance analysis case study. International
Journal of Logistics Research and
Applications. Vol. 16 (5), 349-366
2
3
4

 After conducting the interviews, completing a literature
review and defining the problem, you are ready to
develop a theoretical framework;
 A theoretical framework is the foundation of hypothetico-
deductive research
 How certain phenomena are related to each other?
 Why these variables are associated with each other?
The Research Process for A & B Research
The need for the theoretical framework:

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 variable in the model.
The process of building a theoretical
framework includes:

OBSERVATION
Broad area
of research
interest identified
PRELIMINARY
DATA GATHERING
Interviewing
Literature survey
NO
PROBLEM
DEFINITION
Research
Problem
delineated
THEORETICAL
FRAMEWORK
Variables clearly
Identified and
labeled
GENERATION
OF
HYPOTHESES
SCIENTIFIC
RESEARCH
DESIGN
DATA COLLECTION,
ANALYSIS, AND
INTERPRETATION
DEDUCTION
Hypotheses
Substantiated?
Research question
answered?
Yes
Managerial
Decision
Making
Report
Presentation
Report
Writing
1
119
8
10
76
5
43
2

A variable is anything that can take on differing or varying
values. The value can differ at various times for the same object
or person, or at the same time for different objects or persons
The Research Process; Steps 4 & 5
Variables;
Examples;
1. Production Units
2. Absenteeism
3. Motivation

A variable is anything that can take on differing or varying values.
2.1 Types of Variables
Four main types of variables:
I. The Dependent variable (also known as the criterion variable).
II. The Independent variable (also known as the predictor variable).
III. The Moderating variable.
IV. The Intervening variable.
 Variables can be discrete (male/female) or Continuous (the age
of an individual).
Variables;

Independent Variable Dependent Variable
Variables;

New Product
success
Stock market price
Variables;

Reward Motivation Level
Variables;

Advertisement Sales
Variables;

Training Production Level
Variables;

Temperature Amount of Sweat
Variables;

i. A variable is one that has a conditional effect on the
independent variable relationships
ii. Presence of a third variable modifies the original relationship
between independent and dependent relationship
iii. The variable that moderate the relationship is known as
moderating variable
Moderating Variables;

Independent Variable
(IV)
Dependent Variable
(DV)
Moderating
Variable (MV)
Variables;

Availability of
Reference Manuals
(IV)
# of Rejects
(DV)
Interest
&
Inclination
(MV)
Variables;

Workforce diversity
Organizational
effectiveness
Managerial
expertise
Moderating Variable
Variables;

Willingnesstolearn
Training programs (Quality)
Growth needs
Influence of IV on DV:

Willingnesstolearn
Training programs
Effects for those high
in growth needs
Effects for those low
in growth needs
Influence of Intervening Variables:

Intervening variable influence the dependent variable while
moderating variable increase or decrease the influence .
For instance if we are seeing effects of televisions advertising on
children consumption behavior cognition comes into the way thus
it might totally change the DV .
On the other hand moderating variable would be parental influence
and peer pressure as they both would increase or decrease the Dv
IV, DV and Moderating Variable;

A manager finds that off-the-job classroom training has a great
impact on the productivity of the employees in her department.
However, she also observes that employees over 60 years of age
don’t seem to drive much benefit and do not improve with such
training.
Exercise No. 4.1;

Exercise No. 4.1;

Training Productivity
Age
Moderating Variable
Variables;

i. A 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.
Intervening (Mediating) Variables;

Workforce
diversity
Organizational
effectiveness
Creative
synergy
Time t₂t₁ t₃
Independent Variable Dependent VariableIntervening Variable
Relation between IV, DV and MV:

Workforce
diversity
Organizational
effectiveness
Creative
synergy
Independent Variable Dependent VariableIntervening Variable
Managerial
expertise
Relation between IV, DV, IV and MV:
Time t₂t₁ t₃

 The theoretical framework is the foundation on which the entire
research project is based.
 A good theoretical framework identifies and defines the
important variables those relevant to the problem
Theoretical Framework:

 It is a logically developed, described, and elaborated network of
associations among the variables deemed relevant to the
problem situation and identified through such processes as
interviews, observations, and literature survey.
 Experience and intuition also guide in developing the
theoretical framework.
 The relationship between the literature survey and the
theoretical framework
Theoretical Framework:

There are three basic features that should be incorporated in
the theoretical framework.
1. The variables considered relevant to the study should
be clearly identified, defined.
2. A conceptual model that describes the relationships
between the variables in the model should be given
3. There should be a clear explanation of why we expect
these relationships to exist. The arguments could be
drawn from the previous research findings.
Components of the Theoretical Framework;

List and label the variables in the following situation.
• The manager of a leading cellular company observes that
the morale of employees in her company is low.
• She thinks that if their working conditions are improved, pay
scales rose, and the vacation benefits made attractive, the
moral will be boosted.
• She doubts, however, if an increase of pay scales would
raise the morale of all employees.
• Her conjecture is that those that have supplemental incomes
will just not be “turned on” by higher pay, and only those
without side incomes will be happy with increased pay with
resultant boost of morale.
Quiz No. 2

Quiz No. 2
Each corrected response will carry 2 marks.
List of Variables: Label the Variables:
1. Working conditions ___________________________
2. Morale ___________________________
3. Pay scales ___________________________
4. Vacation benefits ___________________________
5. Supplemental Incomes ___________________________

List and label the variables in the following situation.
The manager of a leading cellular company observes that the
morale of employees in her company is low.
She thinks that if their working conditions are improved, pay
scales rose, and the vacation benefits made attractive, the
moral will be boosted.
She doubts, however, if an increase of pay scales would raise the
morale of all employees.
Her conjecture is that those that have supplemental incomes will
just not be “turned on” by higher pay, and only those without side
incomes will be happy with increased pay with resultant boost of
morale.
Quiz No. 2

The Research Process; Hypotheses
Hypotheses Development;

Definition;
 A tentative, yet testable, statement which predicts what you
expect to find in your empirical data.
 Hypothesis are derived from the theory on which your
conceptual model is based and are often relational in nature
 A hypothesis can be defined as a logically conjectured (guess)
relationship between two or more variables expressed in the
form of a testable statement.
 If the pilots are given adequate training to handle midair crowded
situations, air-safety violations will be reduced.

Definition;
 Relationships are conjectured on the basis of the network of
associations established in the theoretical framework
formulated for the research study.
 By testing the hypotheses and confirming the conjectured
relationships, it is expected that solutions can be found to
correct the problem encountered.

Question Hypothesis
Does a training program in driver safety
result in a decline in accident rate?
People who take a driver safety course will have a lower
accident rate than those who do not take the course.
Who is better in math, men or women? Men are better at math than women.
What is the relationship between age and
cell phone use?
Cell phone use is higher for younger adults than for older
adults.
Is there a relationship between education
and income?
Income increases with years of education.
Can public education reduce the
occurrence of AIDS?
The number of AIDS cases is inversely related to the
amount of public education about the disease.
In many cases the purpose of research is to answer a question or test a prediction, generally stated in
the form of hypotheses (-is, singular form) -- testable propositions. Examples

To put it another way, the fate of the research hypothesis depends upon what
happens to Hₒ. testable statements
Research Hypothesis (testable statements)
1. Exercise leads to weight loss
2. Exposure to classical music increases IQ score
3. Extroverts are healthier than introverts
4. Sensitivity training reduces racial bias
Null Hypothesis (testable statements)
1. Exercise is unrelated to weight loss.
2. Exposure to classical music has no effect on IQ score.
3. Extrovert and introverts are equally healthy.
4. People exposed to sensitivity training are no more tolerant than those
not exposed to sensitivity training.

a. If—Then Statements
 To examine whether or not the conjectured relationships or
differences exist, these hypotheses can be set either as
propositions or in the form of if—then statements. The two
formats can be seen in the following two examples.
 Example: Employees who are more healthy will take
sick leave less frequently.
 Example: If employees are more healthy, then they will
take sick leave less frequently.
Statement of Hypotheses: Formats

 If, in stating the relationship between two variables or
comparing two groups, terms such as positive, negative, more
than, less than, then these hypotheses are directional
 The direction of the relationship between the variables
(positive/negative) or the nature of the difference between two
groups on a variable (more than/less than) is postulated below.
Example:
 The greater the stress experienced in the job, the lower the
Job satisfaction of employees.
Example:
 Women are more motivated than men.
Directional and Nondirectional Hypotheses:

 On the other hand, non-directional hypotheses are those that do
hypothesize a relationship but offer no indication of the
direction of these relationships.
 In other words, though it may be conjectured that there would
be a significant relationship between two variables, we may not
be able to say whether the relationship would be positive or
negative.
Example:
 There is a relationship between age and job satisfaction.
 There is a difference between the work ethic values of American
and work ethic values Asian employees.
Directional and Non-directional Hypotheses:

 The null hypotheses is a proposition that states a definitive,
exact relationship between two variables.
 It states that the population correlation between two variables is
equal to zero or that the difference in the means of two groups
in the population is equal to zero (or some definite number).
 In general, the null statement is expressed as no (significant)
relationship between two variables or no (significant) difference
between two groups.
 The alternate hypothesis, which is the opposite of the null, is a
statement expressing a relationship between two variables or
indicating differences between groups.
Null and Alternate Hypotheses:

Null: The new drug has no health benefits
Alternate: The new drug has health benefits
In this case the doctor should tend to doubt with the alternate hypothesis
rather than the null, because if the researcher mistakenly rejects the null and
the drug is indeed unsafe, this mistake would cost human lives!

The null hypothesis in respect of group differences stated in our
Example 5.18 would be:
H0: µm = µw H0: Meanm = Meanw
or
H0: µm - µw = 0 H0: Meanm - Meanw = 0
The alternate for the above example would statistically be set as
follows:
HA: µM < µW HA: Meanm is less than Meanw
which is the same as
HA: µW >µM HA: Meanw is greater than Meanm
Hypotheses Development:

For the non-directional hypothesis of the mean group differences in
work ethic values, in Example 5.20, the null hypothesis would be:
H0: µAM = µAS or H0: µAM - µAS = 0
where H0 represents the null hypothesis, AM is the mean work ethic
value of Americans and AS is the mean work ethic value of Asians.
The alternate hypothesis for the above example would statistically
be set as:
HA: µAM ≠ µAS
where HA represents the alternate hypothesis and AM and AS are the
mean work ethic values of Americans and Asians, respectively.

The null hypothesis for the relationship between the two variables in
Example:
Ho: There is no relationship between stress experienced on the job
and the job satisfaction of employees.
This would be statistically expressed by H0: ρ= 0
Where “ρ” represents the correlation between stress and job
satisfaction, which in this case is equal to 0 (i.e., no correlation).

The alternate hypotheses for the above null, which has been
expressed directionally in Example; can be statistically expressed
as HA: ρ < 0 (The correlation is negative.)
For Example 5.19, which has been stated non-directionally, while the
null hypothesis would be statistically expresses as:
H0: ρ = 0
The alternate hypothesis would be expressed as:
HA: ρ ≠ 0

1) State the null and the alternate hypotheses.
2) Choose the appropriate statistical test depending on whether the data
collected are parametric or nonparametric
3) Determine the level of significance desired (p= 05, or more, or less).
Hypotheses Testing:

4) See if the output results from computer analysis indicate that the
significance level is met. If, as in the case of Pearson correlation
analysis in Excel software, the significance level is not indicated in the
printout, look up the critical values that define the regions of
acceptance on the appropriate table [(t, F, χ2)—see tables at the end of
the book].
a. This critical value demarcates the region of rejection from that of
acceptance of the null hypothesis.
5) When the resultant value is larger than the critical value, the null
hypothesis is rejected, and the alternate accepted. If the calculated
value is less than the critical value, the null is accepted and the
alternate rejected.
Hypotheses Testing:

Research Method for Business chapter 4

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Research Method for Business chapter 4