The document discusses key elements of research design including the purpose of the study, type of investigation, study setting, extent of researcher interference, and unit of analysis. It provides examples of exploratory, descriptive, and hypothesis testing research and examines the difference between causal and correlational studies. The document also illustrates varying degrees of researcher interference from minimal to moderate to excessive levels.

1. The Research Process: Elements
of Research Design
CHAPTER 5
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2. Chapter Objectives
 Understand the different aspects relevant to
designing a research study.
 Identify the scope of any given study and the
end use of the results.
 Describe the type of investigation needed, the
study setting, the extent of researcher
interference, the unit of analysis, and the time
horizon of the study.
 Identify which of the two, a causal or a
correlational study, would be more
appropriate in a given situation.
2

3. The Research Design
 In this step we need to design the
research in a way that the requisite data
can be gathered and analyzed to arrive
at a solution.
 The research design was originally
presented in a simple manner in the
next Figure.
3

4. Research Design
.John Wiley & Sons Ltd 2009©
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5. Purpose of the Study
 Exploration
 Description
 Hypothesis Testing
5

6. Purpose of the Study
 Exploratory study:
 is undertaken when not much is known
about the situation at hand, or no
information is available on how similar
problems or research issues have been
solved in the past.
 Example:
 A service provider wants to know why his
customers are switching to other service
providers? .
6

7. Purpose of the Study
 Descriptive study:
 is undertaken in order to ascertain and be able to
describe the characteristics of the variables of
interest in a situation.
 Example:
 A bank manager wants to have a profile of the
individuals who have loan payments outstanding for
6 months and more. It would include details of their
average age, earnings, nature of occupation, full-
time/part-time employment status, and the like. This
might help him to elicit further information or decide
right away on the types of individuals who should be
made ineligible for loans in the future. 7

8. Purpose of the Study
 Hypothesis testing:
 Studies that engage in hypotheses testing
usually explain the nature of certain
relationships, or establish the differences
among groups or the independence of two
or more factors in a situation.
 Example:
 A marketing manager wants to know if the
sales of the company will increase if he
doubles the advertising dollars.
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9. Type of Investigation
 Causal Study
 it is necessary to establish a definitive
cause-and-effect relationship.
 Correlational study
 identification of the important factors
“associated with” the problem.
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10. Study Setting
 Contrived: artificial setting
 Non-contrived: the natural environment
where work proceeds normally
10

11. Examples
 A causal study question:
Does smoking cause cancer?
 A correlational study question:
Are smoking and cancer related?
Or
Are smoking, drinking, and chewing
tobacco associated with cancer?
If so, which of these contributes most to the
variance in the dependent variable?
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12. Example: causal relationship
 Fears of an earthquake predicted
recently in an area were a causal of a
number of crashes of some houses in
the area in order to be eligible of
insurance policy.
12

13. Example: correlational relationship
 Increases in interest rates and property
taxes, the recession, and the predicted
earthquake considerably slowed down
the business of real state agents in the
country.
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14. Extent of Researcher Interference
With the Study
 The extent of interference by the
researcher with the normal flow of work
at the workplace has a direct
bearing on whether the study
undertaken is causal or correlational.
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15. Extent of Researcher Interference
With the Study
 A correlational study is conducted in
the natural environment of the
organization with minimum interference
by the researcher with the normal flow
of work.
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16. Extent of Researcher Interference
With the Study
 In studies conducted to establish cause-
and-effect relationships , the researcher
tries to manipulate certain variables so
as to study the effects of such manipulation
on the dependent variable of interest.
 In other words, the researcher deliberately
changes certain variables in the setting
and interferes with the events as they
normally occur in the organization.
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17. Minimal Interference
Example
 A hospital administrator wants to
examine the relationship between the
perceived emotional support in the
system and the stress experienced by
the nursing staff. In other words, she
wants to do a correlational study.
17

18. .(Example (Cont
 The researcher will collect data from the
nurses ( through a questionnaire) to indicate
how much emotional support they get in the
hospital and to what extent they experience
stress. By correlating the two variables, the
answer is found.

In this case, beyond administering a
questionnaire to the nurses, the
researcher has not interfered with the
normal activities in the hospital.
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19. Moderate Interference
 If the researcher wants to establish a
causal connection between the
emotional support in the hospital and
stress, or, wants to demonstrate that if
the nurses had emotional support, this
indeed would cause them to
experience less stress.
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20. Moderate Interference
 To test the cause-and-effect
relationship, the researcher will measure the
stress currently experienced by the nurses in
three wards in the hospital, and then
deliberately manipulate the extent of
emotional support given to the three groups
of nurses in the three wards for perhaps a
week, and measure the amount of stress at
the end of that period.
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21. Moderate Interference
 For one group, the researcher will ensure
that a number of lab technicians and doctors
help and comfort the nurses when they face
stressful events.
 For a second group of nurses in another
ward, the researcher might arrange for them
only a moderate amount of emotional support
and employing only the lab technicians and
excluding doctors.
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22. Moderate Interference
 The third ward might operate without any
emotional support.
 If the experimenter’s theory is correct ,
then the reduction in the stress levels
before and after the 1-week period should be
greater for the nurses in the first ward,
moderate for those in the second ward,
and nil for the nurses in the third ward.
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23. Moderate Interference
 We find that not only does the researcher
collect data from nurses on their experienced
stress at two different points in time, but also
manipulated the normal course of events
by deliberately changing the amount of
emotional support received by the
nurses in two wards, while leaving things in
the third ward unchanged.

Here, the researcher has interfered
more than minimally.
23

24. Excessive Interference
Example
 IF the researcher feels, after conducting the previous
experiments, that the results may not be valid
since other external factors might have
influenced the stress levels experience by the nurses.
 For example, during that particular experimental
week, the nurses in one or more wards may not
have experienced high levels of stress
because there were no serious illnesses or deaths in
the ward. Hence the emotional support
received might not be related to the level of
stresses experienced.
24

25. Excessive Interference
 The researcher want to make sure that
such external factors that might affect
the cause-and-effect relationship
are controlled .
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26. Controlling the External factors
 The researcher might take three groups of
medical students, put them in different rooms,
and confront all of them with the same
stressful task.
 For example, he might ask them to describe
in detail, the surgical procedures in
performing surgery on a patient who has not
responded to chemotherapy and keep asking
them with more and more questions.
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27. Controlling the External factors
 Although all are exposed to the same
intensive questioning, one group might get
help from a doctor who voluntarily offers
clarifications and help when students
stumble.
 In the second group, a doctor might be
nearby, but might offer clarifications and help
only if the group seeks it.
 In the third group, there is no doctor
present and no help is available.
27

28. Controlling the External factors
 In the above example, not only is the
support manipulated , but even the
setting in which this experiment is
conducted is artificial inasmuch as the
researcher has taken the subject away from
their normal environment and put them in a
totally different setting.
 The researcher has intervened maximally
with the normal setting, the participants, and
their duties.
28

29. Excessive Interference
 The extent of researcher interference
would depend on whether the study is
correlational or causal and also the
importance of establishing causal
relationship beyond any doubt.
 Most organizational problems seldom
call for a causal study, except in some
market research areas.
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30. Study Setting: Contrived and
Noncontrived
 Correlational studies are conducted
in noncontrived settings (normal
settings), whereas most causal
studies are done in contrived settings.
 Correlational studies done in
organizations are called field studies.
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31. Study Setting: Contrived and
Noncontrived
 Studies conducted to establish cause-and-
effect relationship using the same
natural environment in which employees
normally function are called field
experiments .
 Experiments done to establish cause-and-
effect relationship in a contrived
environment and strictly controlled are
called lab experiments .
31

32. Example: Field Study
 A bank manager wants to analyze the
relationship between interest rates and bank
deposit patterns of clients.
The researcher tries to correlate the two by
looking at deposits into different kinds of
accounts (such as savings, certificates of
deposit, and interest-bearing checking
accounts) as interest rates changed.
32

33. Example: Field Study
 This is a field study where the bank
manager has taken the balances in various
types of accounts and correlated them to
the changes in interest rates.
 Research here is done in a noncontrived
setting with no interference with the normal
work routine.
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34. Example: Field Experiment
 The bank manager now wants to
determine the cause-and-effect
relationship between interest rate and
the inducements it offers to clients to
save and deposit money in the bank.
The researcher selects four branches
within 60/km radius for the experiment.
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35. Example: Field Experiment
 For 1 week only, he advertises the annual
rate for new certificates of deposit received
during that week. The interest rate would be
9% in one branch, 8% in another, and
10% in the third. In the fourth branch,
the interest rate remains unchanged at
5%. Within the week, the researcher would
be able to determine the effects, if any, of
interest rates on deposit mobilization.
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36. Example: Field Experiment
 This example would be a field experiment
since nothing but the interest rate is
manipulated, with all activities occurring in the
normal and natural work environment.
 Hopefully, all four branches chosen
would be compatible in size, number of
depositors, deposit patterns, and the like, so
that the interest-savings relationships
are influenced by some third factor .
36

37. Example: Lab Experiment
 To be sure about the true relationship
between the interest rate and deposits, the
researcher could create an artificial
environment by choosing, for instance, 40
students who are all business majors in their
final year of study and in the same age. The
researcher splits the students into four groups
and give each one of them $1000, which they
are told they might buy their needs or save
for the future, or both.
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38. Example: Lab Experiment
The researcher offers them interest on what they save
as followings:
 6% on savings for group 1.
 8% for group 2.
 9% for group 3.
 1% for group 4 ( the old rate of interest).
Here, the researcher has created an artificial
laboratory environment and has manipulated
the interest rates for savings. He also chosen
subjects with similar backgrounds.
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39. Population to be Studied
 Unit of analysis:
 Individuals
 Dyads
 Groups
 Organizations
 Cultures
.
39

40. Unit of Analysis: Individual
 If the researcher focuses on how to
raise the motivational levels of
employees, then we are interested in
individual employees in the
organization. Here the unit of
analysis is the individual (the data
will be gathered from each individual).
40

41. Unit of Analysis: Dyads
 If the researcher is interested in
studying two-person interaction, then
several two-person groups also
known as dyads, will become the
unit of analysis ( analysis of
husband-wife, and supervisor-
subordinate relationships at the work
place.
41

42. Unit of Analysis
 Groups as a unit of analysis
 Organizations as a unit of
analysis
 Cultures as a unit of analysis
42

43. Example: Individuals as The Unit
of Analysis
 The Chief Financial Officer of a
manufacturing company wants to know how
many of the staff would be interested in
attending a 3-day seminar on making
appropriate investment decisions.
 Data will have to be collected from each
individual staff member and the unit of
analysis is individual.
 The unit of analysis is the individual .
43

44. Example: Dyads as the Unit of
Analysis
 A human resources manager wants to
first identify the number of employees in
three departments of the organization
who are in mentoring relationships, and
then find out what the jointly perceived
benefits of such a relationship are.
44

45. Example: Dyads as the Unit of
Analysis
 Once the mentor and the mentored pairs are
identified, their joint perceptions can be
obtained by treating each pair as one unit.
 If the manager wants data from a sample of
10 pairs, he will have to deal with 20
individuals, a pair at a time. The information
obtained from each pair will be a data point
for subsequent analysis.
 Thus, the unit of analysis is the dyad .
45

46. Example: Groups as Unit of
Analysis
 A manager wants to see the patterns of
usage of the newly installed Information
System (IS) by the production, sales, and
operations personnel.
 Here three groups of personnel are involved
and information on the number of times the
IS is used by each member in each of the
three groups as well as other relevant issues
will be collected and analyzed.
 Here the unit of analysis is the group .
46

47. Example: Divisions as the Unit of
Analysis
 Johnson & Johnson company wants to see
which of its various divisions (soap, shampoo,
body oil, etc.) have made profits of over 12%
during the current year.
 Here, the profits of each of the divisions will
be examined and the information
aggregated across the various geographical
units of the division.
 The unit of analysis will be the division,
at which level the data will be
aggregated.
47

48. Example: Industry as the Unit of
Analysis
 An employment survey specialist wants to
see the proportion of the workforce employed
by the health care, transportation, and
manufacturing industries.
 The researcher has to aggregate the data
relating to each of the subunits
comprised in each of the industries and report
the proportions of the workforce employed at
the industry level.
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49. Example: Industry as the Unit of
Analysis
 The health care industry, for instance,
includes hospitals, nursing homes, small and
large clinics, and other health care providing
facilities.
 The data from these subunits will have to be
aggregated to see how many employees are
employed by the heath care industry.
 This will need to be done for each of the other
industries.
49

50. Example: Countries as the Unit
of Analysis
 The Chief Financial Officer (CFO)
of a multinational corporation wants to
know the profits made during the past 5
years by each of the subsidiaries in
England, Germany, and France. It is
possible that there are many regional
offices of these subsidiaries in each of
these countries.
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51. Example: Countries as the Unit
of Analysis
 The profits of the various regional
centers for each country have to be
aggregated and the profits for each
country for the past 5 years provided to
the CFO.
 The data will now have to be
aggregated at the country level .
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52. Time Horizon
 Cross-sectional studies
 Snapshot of constructs at a single point in time
 Use of representative sample
 Multiple cross-sectional studies
 Constructs measured at multiple points in time
 Use of different sample
 Longitudinal studies
 Constructs measured at multiple points in time
 Use of same sample = a true panel
.
52

53. Time Horizon: Cross-Sectional
Versus Longitudinal Studies
Example
 Data were collected from stock brokers
between April and June of last year to
study their concerns in a turbulent stock
market.
 Data has to be collected at one
point in time. It is a cross-
sectional design.
53

54. Time Horizon: Cross-Sectional
Versus Longitudinal Studies
Example
 A drug company desirous of investing in
research for a new headache pill conducted a
survey among headachy people to see how
many of them would be interested in trying
the new pill.
 This is a one-shot or cross-sectional
study to assess the likely demand for the
new product.
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55. Time Horizon: Cross-Sectional
Versus Longitudinal Studies
 Longitudinal Studies
Studying people or phenomena at more
than one point in time in order to
answer the research question.
 Because data are gathered at two
different points in time, the study is not
cross-sectional kind, but is carried
longitudinally across a period of time.
55

56. Example
 A marketing manager is interested in tracing
the pattern of sales of a particular product in
four different regions of the country on a
quarterly basis for the next 2 years.
 Since the data are collected several
times to answer the same issue, the study
falls under the longitudinal category.
56

57. Time Horizon: Cross-Sectional
Versus Longitudinal Studies
 Longitudinal studies take more time and effort
and cost more than cross-sectional studies. However,
well-planned longitudinal studies could help to identify
cause-and-effect relationships.
 For example, one could study the sales volume of
a product before and after an advertisement,
and provided other environmental changes have not
impacted on the results, one could attribute the
increase in the sales volume, if any, to the
advertisement.
57

58. Exercise
A supervisor thinks that the low
efficiency of the machine tool operators
is directly linked to the high level of
fumes emitted in the workshop. He
would like to prove this to his supervisor
through a research study.
1. Would this be a causal or a
correlational study? Why?
58

59. Exercise
2. Is this an exploratory, descriptive, or
hypothesis-testing (analytical or predictive)
study? Why?
3. What kind of study would this be: field study,
lab experiment, or field experiment? Why?
4. What would be the unit of analysis? Why?
5. Would this be a cross-section or a
longitudinal study? Why?
59

60. Answers to the Exercise
1. This would be a causal study because the
operator wants to prove to the supervisor that the
fumes are causing operators to be low in their
efficiency. In other words, the machine tool operator
is trying to establish the fact that fumes cause low
efficiency in workers.
2. This is an analytical study because the machine
tool operator wants to establish that fumes cause
low efficiency and convince his workshop supervisor
through such analysis (i.e. establish cause and
effect relationship).
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61. Answers to the Exercise
3. This would be a field experiment . Though the
study would be set up in the natural environment of
the workers where the work is normally done, the
amount of fumes will have to be manipulated while
other factors such as atmospheric pressure may
have to be controlled. Because of the location of
the study, it will be a field experiment.
4. The unit of analysis would be the individual
operators. The data will be collected with respect to
each operator and then the conclusions will be
made as to whether the operators are less efficient
because of the fumes emitted in the workshop.
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62. Answers to the Exercise
5. This would be a longitudinal study
because data will be gathered at more than
one point in time. First, the efficiency of the
operators would be assessed at a given rate
of fume emission. Then the fumes emitted
would be manipulated to varying degrees,
and at each manipulation, the efficiency of
the workers would again be assessed to
confirm that the high rate of fume emission
causes a drop in operators’ efficiency.
62

63. Answers to the Exercise
6. This would be a longitudinal study
because data will be gathered at more than
one point in time. First, the efficiency of the
operators would be assessed at a given rate
of fume emission. Then the fumes emitted
would be manipulated to varying degrees,
and at each manipulation, the efficiency of
the workers would again be assessed to
confirm that the high rate of fume emission
causes a drop in operators’ efficiency.
63