CHAPTER 1
INTRODUCTION TO RESEARCH
Instructional Goals
1. To generate interest in research for the students by driving home the point that
successful managerial problem solving is nothing other than understanding and
analyzing the situation at hand, which is what research is all about.
2. To help students differentiate between research‐based problem solving and “going by
gut‐feeling”, the latter of which might sometimes help to solve problems in the short
term, but might lead to systemic long‐term adverse consequences.
3. To create an appreciation in students that research is useful for solving problems in
ALL areas of business.
4. To help students develop an appreciation of the role of the manager in facilitating the
researcher or the consultant’s work.
5. To stress the importance of skill development in research, as opposed to mere
gathering of knowledge about research.
6. To emphasize that research and knowledge about research enhance managerial
effectiveness.
7. To sensitize students to ethical conduct in business research.
Discussion Questions
1. Why should a manager know about research when the job entails managing people,
products, events, environments and the like?
The manager, while managing people, products, events, and environments, will
invariably face problems, big and small, and will have to seek ways to find long
lasting, effective solutions. This can be achieved only through knowledge of research
even if consultants are engaged to solve problems.
2. For what specific purpose is Basic research important?
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Basic research is important for generating and building upon the existing
knowledge in the areas of interest. It offers the foundation for applied research by
which one can circumvent reinventing the wheel.
3. When is Applied research, as distinct from Basic research, useful?
Applied research is useful in solving specific problems in particular situations
where early action might be needed to solve problems in organizations.
4. Why is it important to be adept in handling the manager‐researcher relationship?
The manager who knows how to relate to researchers facilitates the problem
solving process and benefits the research team as well as the organization. One who
is not adept at this will frustrate and be frustrated during the research process and
thereafter.
Being capable of handling the manager‐researcher relationship is thus a big
advantage and some of the nuances of handling research teams are:
(i) knowing how much and what information to give to the team;
(ii) meaningful and purposeful interactions with the team members;
(iii) stating from the outset what records of the company will and will not be accessible to the
team members and expressing the core values of the system.
5. Explain, giving reasons, which is more important – Applied or Basic research?
Both are equally important. Without basic research, applied research cannot
work as well, and if the results of basic research are not applied, such research would
be futile. Whereas basic research is the foundation of knowledge, applied research is
its practical application and helps to provide the additional information base for
theory building and further generation of knowledge.
6. Give two specific instances where an external research team would be useful and
two other scenarios where an internal research team would be deployed, with
adequate explanations as to why each scenario is justified for an external or
internal team.
The answers will vary.
For the external team, the suggestions could be:
a. to help non‐tech companies to build up sophisticated technology in their
environment; (only those with specialized knowledge of technology can help non‐
tech companies).
b. to evaluate the successful and deficient operations of the company; (to avoid bias of
internal team members).
For the internal team, it could be:
a. to figure out how the companies affected by the September 11th disaster can rebuild
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themselves; (internal team would be more knowledgeable about the company and
could rebuild faster).
b. to solve the problem of consistent losses of a small division of a large company (only
a small pocket of a large company is involved and the situation can be rectified by
the internal team).
7. Describe a situation where research will help you as a manager to make a good
decision.
Again, the answers will vary. One scenario is that a work team fails to deliver
results time and again.
8. Given the situations below, (a) discuss with reasons, whether they will fall into the
category of Applied or Basic research, and (b) for scenario 1 explain, with reasons,
who will conduct the research.
Scenario 1
Companies are very interested in acquiring other firms even when the latter operate in totally unrelated realms of
business. For example, Coca‐Cola has announced that it wants to buy China Huiyuan Juice Group in an effort to
expand its activities in one of the world’s fastest‐growing beverage markets. Such acquisitions are claimed to
“work miracles.” However, given the volatility of the stock market and the slowing down of business, many companies are
not sure whether such acquisitions involve too much risk. At the same time, they also wonder if they are missing out on a
great business opportunity if they fail to take such risk. Some research is needed here!
This is a general issue that relates to all or most companies contemplating
acquisitions. Of course, the results of the study are likely to be useful to, and applied
by, all the concerned companies. This could fall into the realm of basic or applied
research, depending on who sponsors the study. If one company or a consortium of
companies investigates the issue to find an answer for immediate application, then it
will be applied research On the other hand, if a Finance professor in a university
undertakes the study as a matter of academic interest, it will be basic research.
Either an individual such as a professor or a finance expert can do this basic research,
or a company or consortium of companies can undertake the applied research.
Scenario 2
Reasons for Absenteeism
A university professor wanted to analyze in depth the reasons for absenteeism of employees in organizations. Fortunately,
a company within 20 miles of the campus employed her as a consultant to study that very issue.
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The basic research aspiration of the professor has taken the form of applied
research in this particular system, where they would apply the findings of her
research to solve the problem. No doubt, the professor would continue her research
in a variety of organizations to add to the existing base of knowledge on absenteeism
and continue the topic as a basic research project.
Scenario 3
Effects of Service Recovery on Customer Satisfaction
A research scientist wants to investigate the question: What is the most effective way for an organization to
recover from a service failure? Her objective is to provide guidelines for establishing the proper "fit" between
service failure and service recovery that will generalize across a variety of service industries.
This will be a case of basic research, the purpose of which was to study the
efficacy of different service recovery strategies and add to the body of existing
marketing knowledge.
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CHAPTER 2
SCIENTIFIC INVESTIGATION
Instructional Goals
1. To help participants comprehend that scientific research offers assurance to the
manager that the results of a study can be relied upon and further action can be
taken at low risk.
2. To impress on the students that business research, however rigorously conducted,
cannot produce 100 percent scientific results in terms of precise solutions.
3. To sensitize participants to being watchful about observing the different cues in the
environment which offer some idea of a gap in the desired and actual state of affairs.
4. To help students understand that applied research, though limited in generalizability,
still has to be “scientific”.
Discussion Questions
The first two questions are straightforward and the answers may be extracted
from the text.
3. One hears the word research being mentioned by several groups such as research
organizations, college and university professors, doctoral students, graduate
assistants working for faculty, graduate and undergraduate students doing their
term papers, research departments in industries, newspaper reporters, journalists,
lawyers, doctors, and several other professionals and nonprofessionals. In the light
of what you have learned in this unit, how would you rank the aforementioned
groups of people in terms of the extent to which they might be doing “scientific”
investigations? Why?
To the extent that any of the above groups conforms to the hallmarks of science,
they would be doing scientific investigation. It is quite possible that poor research is
done by research agencies, and excellent research is conducted by a graduate
assistant. The ultimate test is the rigor of the research which would lend itself to
testability, replicability, accuracy and precision, generalizability, objectivity, and
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parsimony.
Research organizations and research departments in industries engage
themselves in both basic and applied research and usually have the resources
required to conduct scientific investigations using rigorous data collection methods,
sampling designs, and data analysis. Most professors in colleges and universities are
well trained to conduct scientific investigations, though their resources may not, in
most cases, be as plentiful as that made available in research organizations and
research departments. Because of restricted resources, professors may have to
compromise somewhat on methodological rigor (e.g. use a small sample) which
might restrict the generalizability of their findings. However, their research might
otherwise be scientific. Applied researchers doing action‐oriented research, are
somewhat restricted in even disseminating information about their findings due to
the localized nature of their inquiry which may not pass many of the criteria of the
hallmarks of science. Doctoral dissertations conducted under able guidance and
supervision quite frequently make valuable contributions to the body of existing
knowledge. Much of this research is later published as journal articles, and some get
published as books because of their contributions to knowledge.
Students’ term papers are meant to be exercises in skill development for
integrating materials and communicating ideas in written form. Exceptional research
papers, when refined and published, could qualify for being termed as scientific
investigations. Newspaper reporters and journalists may obtain extensive primary
and secondary data but their investigations are confined to a narrow range of
current incidents, events, or individuals, which are of passing interest with little
generalizability to other times, events or individuals. Hence, they cannot ordinarily
be termed scientific investigations. Some newspaper articles, however – as for
instance, economic and environmental investigations – provide data, analysis of
data, and valid conclusions drawn there from, which might later be used as
secondary data by other researchers. These would be categorized as more scientific
in contrast to articles or editorials in the paper.
Academic journals usually publish articles that are scientific and some of the
practitioner‐oriented articles are probably somewhat less scientific than the
academic articles in terms of rigor and generalizability. To the extent that lawyers,
doctors, professionals and nonprofessionals present their findings that have wide
testability, replicability, generalizability, accuracy and precision, objectivity, and
parsimony, they will be scientific. However, if these investigations are confined to
single cases, incidents, or individuals, they cannot be called scientific investigations
despite the fact that they may be found useful.
4. Explain the processes of deduction and induction, giving an example of each.
The hypothetico‐deductive method of research helps the researcher to deduce or
infer from the results of data analysis and hence is the deductive process. For
example, if as a result of analysis of data collected, one infers that the problem of
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turnover can be minimized by three important factors: (i) flexible work hours; (ii)
recognition of superior performance of workers through suitable merit pay raises;
and (iii) enriching certain types of jobs, this is the deductive approach.
Induction is a process of drawing inferences from observed phenomena which
may subsequently be put to the test through hypothetico‐deductive method of
research. For instance, if a manager observes that people residing at distances
beyond 50 miles from the workplace remain absent more frequently than those he
knows to reside close by, and infers thereby that distance is a factor in absenteeism,
this is an inductive process.
5. If research in the management area cannot be 100 percent scientific, why bother to
do it at all? Comment on this statement.
Research in the management area dealing with human behavior cannot be 100
percent scientific. However, such research is necessary and useful for detecting
problems and coming up with solutions to ensure that problems do not get out of
control. Management research makes a valuable contribution inasmuch that it can
help organizations function smoothly and effectively and help managers and
individuals at all levels in organizations experience and enjoy a better quality of life.
6. Critique the following research done in a service industry as to the extent to which it
meets the hallmarks of scientific investigation discussed in this chapter.
The Friendly Telephone Company
Customer complaints were mounting, and letters of complaint regarding the
problems they experienced with the residential telephone lines were constantly
pouring in at the Friendly Telephone Company. The company wanted to pinpoint the
specific problems and take corrective action.
Researchers were called in, and they spoke to a number of customers, noting down
the nature of the specific problems they faced. Since the problem had to be attended
to very quickly, they developed a theoretical base, collected relevant detailed
information from a sample of 100 customers, and analyzed the data. The results are
expected to be fairly accurate with at least an 85% chance of success in problem
solving. The researchers will make recommendations to the company based on the
results of data analysis.
The hallmarks of science are purposiveness, rigor, testability, replicability,
precision and confidence, objectivity, generalizability, and parsimony. This study
meets the basic criterion of purposiveness. It cannot be called a rigorous study
inasmuch as a theoretical framework seems to have been formulated merely on the
basis of conversation with a number of customers and no scientific data seems to
have been collected thereafter. For this reason, the replicability and generalizability
criteria also suffer. With customer complaints mounting, an 85% confidence level
may not suffice. Unless we know the theoretical base, we cannot be sure that the
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criterion of parsimony is met. All in all, this is a good example of a non‐scientific
investigation.
7. Strictly speaking, would case studies be considered as scientific research? Why or
why not?
Case studies cannot be considered scientific since they do not subscribe to most
of the hallmarks of scientific research. Though they may be purposive and
parsimonious, they are not rigorous. Testability and replicability are difficult and
generalizability is virtually non‐existent since each case situation is unique.
8. What is Action Research? Describe a specific situation where action research will be
warranted.
Action research is undertaken when incremental planned changes are
contemplated in a system. It is a process of trial and error where tentative solutions
are generated to test out how well they work. Modifications are undertaken as each
step in the change process and its consequences are evaluated.
An example would portray that of an organization wanting to attain a certain goal
(shooting for a star) and taking incremental steps to reach the goal, one step at a
time. Specifically, a company could be aiming for near zero turnover of its staff. It
could try increasing the perks by first offering day care facilities and watch its effects.
Then it might give more vacation time, and then enhance pay, and so on.
The Dilemmas of Dorothy Dunning
Dorothy Dunning, Chief Production Manager, was on top of the world just two
years ago. In her nontraditional job, she was cited to be the real backbone of the
company, and her performance was in no small measure responsible for the mergers
the institution was contemplating with other well‐known global corporations.
Of late though, the products of the company had to be recalled several times owing
to safety concerns. Quality glitches and production delays also plagued the company.
To project a good image to consumers, Dunning developed a very reassuring web
site and made sweeping changes in the manufacturing processes to enhance the
quality of the product, minimize defects, and enhance the efficiency of the workers.
A year after all these changes, the company continues to recall defective products!
Creating a web site and making sweeping changes has not produced the
desired results. The real problem is undetected and can only be identified through
research. Maybe, the problem is not in the manufacturing processes, but the low
motivation of employees! A scientific research of the problem situation will help to
pinpoint the problem and solve it.
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CHAPTER 3
THE RESEARCH PROCESS: THE BROAD
PROBLEM AREA AND DEFINING THE
PROBLEM STATEMENT
Instructional Goals
1. To clarify to the students that though the Research Process has distinct phases, some
of the steps follow an iterative, rather than a linear process. For example, the problem
statement could be redefined after the theoretical framework is conceptualized, after
data analysis, and in fact, at any of the stages in the process.
2. To illustrate that identifying the Broad Problem Area sets the stage for focusing on
literature search and subsequently clearly defining the problem.
3. To emphasize that preliminary data collection through interviews offers a great
opportunity to narrow down the problem and identify the prospective variables
influencing it.
4. To develop interviewing and problem identification skills in students.
5. To create a mindset in students of viewing a problem as a gap between desired and
actual state of things in a system, and a solution as narrowing this gap.
6. To encourage students to develop bibliographies by accessing available on‐line data
bases.
7. To require students to write a good literature review in the areas of their research
interests and to make them aware that most class term papers could use this type of
introduction to enhance their value.
Discussion Questions
1. How would you describe the research process?
The research process includes a series of steps in identifying the variables to be
studied and the method for conducting the study. The problem statement is a critical
aspect. Though it is generated by having a good feel for where the gap between a
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desired state and the actual state exists in the system, the problem statement can be
repeatedly honed and made more precise at various stages in the research process.
The theoretical framework and hypotheses are important parts of the research
process since these focus on finding the answers to the research question. Good
research design helps in finding reliable answers to the problem that is investigated.
2. Explain the preliminary data collection methods.
Preliminary data can be obtained through interviews and/or through literature
search. These processes help to define the problem statement precisely and to
formulate the theoretical framework. Interviews conducted at various levels are
aimed at obtaining background information on the system that is investigated, the
structure and processes that operate in the system, the perceptions, attitudes, and
behaviors of the people in the institution, and other related matters. The literature
search will be based on the factors that seem pertinent to the problem that is
investigated. After locating all the references in the area, the work relevant to the
problem at hand will be studied and a literature review written up.
3. Why is it important to gather information on the background of the organization?
The background information of the company is likely to offer the researcher
several clues on when the problems that are currently experienced by the company
could have started and how they could have originated. One can also assess how the
other companies operating in similar types of environment in the industry might be
different and in what way. Since multiple factors can influence the problem, the
possibility that some of the background features of the company are influencing the
situational problem cannot be ruled out. Additionally, the background factors offer the
researcher a good idea of how the philosophy and culture of the company are shaped,
and to what extent they can be changed, if necessary.
Collecting background information also helps to focus on critical issues and raise
appropriate questions during the interview process. Examples of this are provided in
the book.
4. Should a researcher always find information on structural and job characteristics
from those interviewed? Give reasons for your answer with examples.
It is almost always advisable for the researcher to gather some information on the
structure and job characteristics even though it may appear that the problem may not
be related to either of these factors. For example, the problem of not meeting the
production deadlines may be directly related to the delayed deliveries of the raw
materials by the suppliers. In such a case, the tendency might be to focus the data
collection mainly as it relates to suppliers. However, interviewing the employees and
ascertaining their reactions to their job, work‐flow interdependencies, structure, and
the like, might offer the solution that deadlines can be met even with delayed raw
material supplies by changing the workflow patterns, or other structural aspects. It is
for such reasons that some time should be spent on finding the job and structure‐
related information.
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There is also another way of looking at this. Human beings operating in
organizations face a multitude of factors surrounding them, many of which, directly or
indirectly, influence their operating effectiveness. The structural factors such as
policies and procedures, reward systems and job factors do play a critical part in how
outcomes for the organization are achieved. Because of this, it certainly helps to get a
feel for these factors. Of course, there is no need to spend a great deal of time on
these unless there is some indication that there could be problems in these areas.
As an example, it is possible that the age of the machinery could be blamed for low
production, and sophisticated machinery might be installed without any appreciable
difference in the results. Further investigation might throw light on the fact that the
current incentive system does not encourage high levels of production, and this fact,
rather than the type of machinery used, is the problem. Not finding this before
investing heavily on new equipment would be a costly mistake!
5. How would you go about doing a literature survey in the area of business ethics?
I would first obtain all the references and abstracts relating to the area of business
ethics through on‐line systems, then organize the studies based on the particular
aspects they address, and finally, write up a review of the available literature.
6. What is the purpose of the literature survey?
Basically to make sure that none of the important variables are left out in the study
and to generate a parsimonious set of factors which would help to explain or predict
the phenomenon under investigation.
7. Why is appropriate citation important? What are the consequences of not giving
credit to the source from which materials are extracted?
Most published articles are copyrighted. There are rules as to how much can be
quoted from the original text without obtaining the journal’s and the author’s
permission. If permission is not obtained for quotes exceeding the authorized limit,
the individual quoting the material is liable to be sued for plagiarism and can even be
expelled from the professional society to which he or she belongs.
8. “The problem definition stage is perhaps more critical in the research process than
the problem solution stage”. Discuss this statement.
Finding the right solution to an incorrectly identified problem helps no one
because the original concerns will still continue to exist. Hence, pinpointing where
exactly the gap lies, for which a solution is needed, is critical.
9. Why should one get hung up on problem definition if one already knows the broad
problem area to be studied?
Since a problem statement is a clear, precise, and concise statement of the issue to
be researched, it offers a focus and direction to the research. In other words, it sets
out the exact purpose of the research and clearly states the question to which we are
trying to find an answer. The broad problem area, however, due to its vagueness and
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wide scope of the issues that could be involved, leaves the focus of the research
undetermined, and hence offers no sense of purpose or direction to the research.
To put it differently, a broad problem area does not highlight the specific problem
that exists. Unless the precise problem is identified, a solution to it cannot be found.
This is akin to an individual going to a doctor saying he is losing weight (broad
problem). Unless the physician can locate the reason for this weight loss (define the
problem), the situation cannot be rectified.
10. Offer a clearly focused problem statement in the broad area of corporate culture.
What constitutes corporate culture? Or,
How does corporate culture influence employee performance?
11. After studying and extracting information from all the relevant work done
previously, how does the researcher know which references, articles, and
information should be given prominence in the literature survey?
The mass of information extracted from the various published research and
technical and other reports, will indicate to the researcher the key variables that need
to be considered in the particular situation where the problem has been identified.
The choice of the variables for inclusion in the study will be a function of the
frequency with which they are repeatedly found to be significant in the various
research studies, the relevance of the variables to the current research context, and
considerations of parsimony. Having decided on the key variables for inclusion in the
study, the researcher can then integrate the information found in the studies that
discuss these variables. Other studies which had equally relevant variables but which
had to be excluded from the current research for certain valid reasons should also be
briefly discussed. The reasons for their exclusion should be explicitly stated in the
literature survey section.
12. Below is the gist of an article from Business Week. After reading it, (a) identify the broad
problem area, (b) define the problem, and (c) explain how you would proceed further.
While Chrysler’s minivans, pickups, and sports utilities take a big share of the truck
market, its cars trail behind those of GM, Ford, Honda, and Toyota. Quality problems
include, among other things, water leaks and defective parts.
a. The broad problem is that the Chrysler cars are lagging behind in market share.
b. Problem statement: How can the market share of Chrysler cars be improved?
c. It is best to interview the users of GM, Ford, Honda, and Toyota car users and obtain
from them their reactions – both positive and negative ‐ to the cars they use and why
they prefer them. Similar reactions from the users of Chrysler cars should also be
gathered. One should proceed further based on the analysis of these responses.
13. Comment on the following:
From 1932 to 1972, a research study was conducted in Tuskegee, Alabama, to chart
the effects of withholding treatment to African American men with syphilis.
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This research smacks of a totally unacceptable and unethical approach to the
investigation.
14. What is the problem statement in the following situation?
Employee Loyalty
Companies benefit through employee loyalty. Crude downsizing in organizations
during the recession crushed the loyalty of millions. The economic benefits of loyalty
embrace lower recruitment and training costs, higher productivity of workers,
customer satisfaction, and boost the morale of fresh recruits. In order that these
benefits may not be lost, some companies, while downsizing, try various gimmicks.
Flex leave, for instance, is one. This helps employees receive 20% of their salary, plus
employer‐provided benefits while they take a 6‐12 month sabbatical, with a call
option on their services. Others try alternatives like more communication, hand‐
holding, and the like.
Problem statement. How can employee loyalty be maintained during periods of
downsizing?
15. How would you define the problem in the following case?
Accounting Gets Radical
The GAAP (Generally Accepted Accounting Principles) do an unacceptable job of
accounting for the principal activities of the Information Age companies. Today,
investors are in the dark because the accounting is irrelevant. The basic purpose of
accounting is to provide useful information to help investors make rational
investment, credit, and similar decisions, but today’s most important assets and
activities – intellectual capital and knowledge work – are totally ignored. Professor
Robert A. Howell wants to reform the accounting system with the goal of making clear
the measurement of how companies produce cash and create value.
Problem Definition: What is the best way to improve the accounting system in the
Information Age that would furnish useful data and information to investors to make
rational decisions?
Practice Projects
Answers will vary.
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Additional Topics For Bibliography &
Literature Survey
Absenteeism
Alienation
Appraisal Systems
Conflict
Control Systems in Organizations
Communication
Competence
Drug Abuse and Alcoholism in Industry
Executive Stress
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Financial Markets
Interpersonal Communication
Leverage Buyout
Price Wars
Role Ambiguity
Role Conflict
Sense of Competence
Stress
Tax Reforms
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CHAPTER 4
THE RESEARCH PROCESS: THEORETICAL
FRAMEWORK AND HYPOTHESES
DEVELOPMENT
Instructional Goals
1. To clarify the differences in the four types of variables – dependent, independent,
mediating, and moderating. Students find it particularly difficult to differentiate
between mediating and moderating variables.
2. To elucidate the five basic components of the theoretical framework emphasized in
the book and to explain that paying attention to these, at this stage, enables students
to generate well‐developed, testable hypotheses at the subsequent step.
3. To stress the importance of formulating directional alternate hypotheses whenever it
is possible.
4. To require students to work on the 14 small exercises interspersed in the chapter, at
the appropriate times, and to discuss these in class as the lectures and discussions on
the different types of variables progress.
Discussion Questions
1. Because literature survey is a time‐consuming exercise, a good, in‐depth interview
should suffice to develop a theoretical framework. Discuss this statement.
Literature survey is an important though time‐consuming exercise and has to be
done for several reasons. Even an in‐depth interview may not surface some important
factors that may be relevant for finding answers to the problems. In other words,
certain critical factors may be overlooked both by the interviewee and the researcher,
in which case no solution to the problem will emerge even after the research findings
are implemented. A literature review will sensitize and make the researcher aware of
all the important factors that have been found to be related to the problem in past
studies. It will also help the researcher eliminate trivial factors or variables from the
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investigation, thus ensuring parsimony and increasing effectiveness. Secondly, a good
documentation of the previous work done in the area not only lends credibility to the
results found, but also adds to the scientific quality of the research by increasing
replicability, generalizability, and parsimony. Finally, good literature surveys, and a
theoretical framework formulated on the basis of past studies, contribute to the
growth of scientific knowledge, rather than research becoming a futile exercise in
reinventing the wheel.
2.Good models are complex. What’s more, a good model
should include both moderating and mediating variables. Discuss this statement.
There is no relationship between the quality of a model and the complexity of a
model. Recall that parsimony is one of the hallmarks of scientific research: Simplicity
in explaining the phenomena 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.
A good theoretical framework identifies and defines the important variables in the
situation that are relevant to the problem. Moderating and mediating variables may or
may not be important to the problem. A good model does not necessarily include
moderating and mediating variables.
3. Academic researchers usually develop more complex and elaborate models than
applied researchers. Discuss this statement.
No. The complexity of a model is not related to type of research in terms of basic
versus applied research. Again, parsimony is one of the hallmarks of scientific
research. The term scientific research applies to both basic and applied research.
4. In an applied research context you do not need to explain the relationships
between the variables in your conceptual model. Discuss this statement.
A theoretical framework is the foundation of hypothetico‐ deductive research as it is
the basis of the hypotheses that you will develop. A theoretical framework represents
your beliefs on how certain phenomena (or variables or concepts) are related to each
other (a model) and an explanation on why you believe that these variables are
associated to each other (a theory). Both the model and the theory flow logically from
the documentation of previous research in the problem area. Integrating your logical
beliefs with published research, taking into consideration the boundaries and
constraints governing the situation, is pivotal in developing a scientific basis for
investigating the research problem.
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A good theoretical base thus adds rigor to a purposive study. Rigor connotes
carefulness, scrupulousness, and the degree of exactitude in research investigations.
Rigor is one of the hallmarks of scientific research which pertains to both basic and
applied research.
5. There is an advantage to stating the hypothesis both in the null and the alternate;
it adds clarity to our thinking about what we are testing. Explain.
The null hypothesis is set so that the alternate hypothesis becomes testable. When
the observed Z value is greater than or equal to the critical Z value for a given
confidence level (usually 95 percent), then we know that we ought to accept the
alternate hypothesis. If, however, the critical Z value is more than the observed Z
value for a given level of confidence, we would be inclined not to reject the null but to
reject the alternate. Setting up the null thus helps us to understand that though the
null hypothesis itself is not testable, it helps to decide whether we should accept or
reject the alternate.
6. It is advantageous to develop a directional hypothesis whenever we are sure of the
predicted direction. How will you justify this statement?
In a directional hypothesis we might conjecture, on some sound and logical basis, that
variable X is greater than variable Y. In the non‐directional hypothesis we merely
conjecture that X and Y will not be equal, meaning that either can be greater than the
other. The directional hypothesis involves a one‐tailed significance test, and the non‐
directional involves a two‐tailed test. To reach a level of significance p=.05, the critical
value of the observed Z should be 1.64 for a one‐tailed test, and 1.96 for a two‐tailed
test. Supposing the true observed Z value in a particular case is 1.72, then we would
accept the hypothesis if it was stated directionally, and reject it if it was stated non‐
directionally. In a sense, the two‐tailed test is more conservative but a hypothesis that
is logically derived as a one‐tailed test would be rejected if it is non‐directionally
stated, and we would be incorrectly rejecting a hypothesis that is true, thus
committing a Type II error. It is for this reason that we should state a directional
hypothesis when we are sure of the predicted direction based on good theory and
logic.
7. In recent decades, many service markets have been
liberalized. For this
reason, incumbent service firms are facing new competitors and must address
customer switching. You are discussing the determinants of customer switching with
a service firm manager. She believes that product quality, relationship quality, and
switching costs are important determinants of customer switching.
You agree with the contention that product quality and relationship quality are
important determinants of switching. However, you believe that switching costs
moderates the relationships between product quality, relationship quality and
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customer switching.
Provide arguments for this contention.
Switching costs include the time, money and effort the customer perceives when
changing from one provider to another. We expect that switching costs do not directly
affect customer switching. That is, we posit that a customer will not switch service
providers because the switching costs are low or high. Instead, we propose that the
negative relationship between product and relationship quality and customer
switching is stronger in situations with low switching costs. When switching costs are
low customers switch service providers when the relationship quality and product
quality is low. However, when switching costs are substantial, customers are likely to
maintain business relationships with existing service providers even when the
relationship and product quality is low.
8. For the following case titled Sleepless Nights at Holiday Inn (published in Business
Week and adapted here):
a.
Identify the problem
b.
Develop a theoretical framework
c.
Develop at least four hypotheses.
Sleepless Nights at Holiday Inn
Just a few years ago, Tom Oliver, the Chief Executive of Holiday Hospitality Corp.,
was struggling to differentiate among the variety of facilities offered to clients under
the Holiday flagship – the Holiday Inn Select designed for business travelers, the
Holiday Inn Express used by penny pinchers, and the Crowne Plaza Hotels, the
luxurious hotels meant for the big spenders. Oliver felt that revenues could be
quadrupled if only clients could differentiate among these.
Keen on developing a viable strategy for Holiday Hospitality which suffered from
brand confusion, Tom Oliver conducted a customer survey of those who had used
each type of facility, and found the following. The consumers didn’t have a clue as to
the differences among the three different types. Many complained that the buildings
were old and not properly maintained, and the quality ratings of service and other
factors were also poor. Furthermore, when word spread that one of the contemplated
strategies of Oliver was a name change to differentiate the three facilities, irate
franchises balked. Their mixed messages did not help consumers to understand the
differences either.
Oliver thought that he first needed to understand how the different classifications
would be important to the several classes of clients, and then he could market the
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heck out of them and greatly enhance the revenues. Simultaneously, he recognized
that unless the franchise owners fully cooperated with him in all his plans, mere face
lifting and improvement of customer service would not bring added revenues.
Problem Statement:
How can brand awareness be brought about to increase the revenues of
Holiday Inn?
Theoretical Framework
Only after Oliver has understood how the different classifications would be
important to the three classes of intended clients through survey data, can a
meaningful theoretical framework be developed. But, based on what information is
currently available, the following framework can be attempted.
The nature of the building facilities, how the buildings are maintained, and the
quality of service provided – the three independent variables – would differentiate the
three distinct types of Holiday Inn facilities and increase brand awareness among the
users. The better the buildings, the better their maintenance, and the more
differentiated the services provided, the greater will be the perceived differences in
the three types of Holiday Inn facilities by clients. However, if the Franchise owners do
not cooperate in highlighting these differences to clients, no amount of the
improvements made in the independent variables will help to increase the brand
awareness. It is only when the Franchise owners actively promote the idea of
differentiated facilities‐ the moderating variable – can the brand awareness be
increased, and as a consequence, the revenues.
Hypotheses
1. The more differentiated the building facilities, the more the brand awareness.
2. The more differentiated the maintenance of the facilities, the more the brand
awareness.
3. The more differentiated the services to the clients, the more the brand awareness.
4. Differentiated building facilities, maintenance, and service will influence brand
awareness only if the Franchise owners cooperate and actively promote the idea of
differentiation. If they don’t, no amount of differentiation of the three independent
variables will help clients to understand the differentiation (increase brand
awareness).
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9. Develop a conceptual model for the scenario below.
Incidence of smoking in movies has started to increase again, after having declined
for several decades. According to the National Cancer Institute smoking is seen in at
least three out of four contemporary box‐office hits. What’s more, identifiable
cigarette brands appeared in about one‐third of all movies in 2008. Exposure to
smoking in movies is an important predictor of adolescent smoking initiation:
smoking in movies has been shown to affect adolescents’ intentions to start
smoking. In turn, the intentions to start smoking are determined by a more positive
attitude toward smoking after seeing a film character smoke. Recent research has
revealed that the relationship between seeing a film character smoke and the
attitude toward smoking is stronger when a person’s identification with a film
character increases. These findings are consistent with social learning theory, which
predicts that attitudes and behaviors are modeled by observing the behaviors of
others.
Exposure to smoking in movies
Attitude toward smoking
Smoking intentions
Identification with a film character
10.
Develop a theoretical framework for the following case.
Once given, perks are extraordinarily hard to take away without sapping employee
morale. The adverse effects of these cuts far outweigh the anticipated savings in
dollars. Research has shown that when the reason behind the cuts is explained to
employees, morale does not drop.
Perks (IV) boost the morale of employees (DV) while, understandably,
withdrawing the same saps it. However, if the reasons for the cuts in perks (MV) are
explained to the employees, they see the logic behind the cuts and their morale is not
affected. Thus, only when the reason for the cut in perks is explained to employees,
does their morale not sag.
11. Product placement is a form of advertising in which a company’s products and
name are intentionally positioned in motion pictures, television programs, radio
broadcasts, and the like. Product placement can take many forms: verbal mentions
in dialogue, actual use by a character, or visual displays (for instance a company logo
on a vehicle or billboard).
Develop a theoretical framework on this issue, based on a review of the current
literature. This framework should include:
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-
-
a specification and definition of an appropriate dependent variable;
a conceptual model that describes the relationships between the dependent
variable, at least one independent variable, and either a moderating or a mediating
variable;
a theory on why you would expect these relationships to exist;
an appropriate number of testable hypotheses.
Answers will vary.
Answers to Exercises 4.1 To 4.14 in the
Text Book
Exercise 4.1
The dependent variable is organizational performance because it is the primary
variable of interest to the applied researcher, who wants to increase the commitment
of the members in the bank.
Exercise 4.2
The dependent variable is product desirability.
Exercise 4.3
VARIABLE
Production
Supervision
Training
LABEL
Dependent variable
Independent variable
Independent variable
REASON
Main variable of interest
Help to explain the variance in production
Explanation
Production is the dependent variable because the manager seems to be
interested in raising the level of production of workers. The manager wants to explain
the variance in production levels through the two independent variables – supervision
and training.
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Exercise 4.4
VARIABLE
Gains
Buying at right time
Selling at right time
LABEL
Dependent variable
Independent variable
Independent variable
REASON
Variable of primary interest
Explain the variance in gains
(i.e. benefit)
Explanation
Gains or benefit from stock trading is the dependent variable. Buying stocks at
the opportune time and selling them likewise, are the two independent variables
because these two are expected to influence the gains (benefits) derived from stock
trading. That is, when stocks are bought and sold at the right times, there will be gains
or benefits derived.
Exercise 4.5
VARIABLE
Productivity
Off‐the‐job classroom training
Age
LABEL
Dependent variable
Independent variable
Moderating variable
Explanation
The main variable of interest to the manager is productivity ‐ the dependent
variable ‐ the variance in which is expected to be explained by the independent
variable, off‐the‐job classroom training. The more off‐the‐job training given to the
workers, the greater their productivity. However, only those who are under fifty years
of age would increase their productivity with increased off‐the‐job training. This will
not be true for those who are over fifty years of age since their interest in classroom
training and the like will not be high. Thus age is the moderating variable.
Exercise 4.6
VARIABLE
Sales performance
Intensity of E‐Business adoption
LABEL
Dependent variable
Independent variable
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Market uncertainty
Moderating variable
Exercise 4.7
Situation 1
Motivation to Work as an Independent Variable
The performance of employees is influenced by their motivation to work.
Situation 2
Motivation to Work as an Intervening Variable
Employees perform better when they are given challenging jobs, because such jobs
tend to motivate them to work.
Situation 3
Motivation to Work as a Moderating Variable
The performance of employees with low levels of motivation to work will not improve
despite increases in job challenge.
Exercise 4.8
VARIABLE
Problems
Following Accounting Principles
Confusion
Experience in Book Keeping
LABEL
Dependent variable
Independent variable
Intervening variable
Moderating variable
Explanation
The extent to which accounting principles are followed – the independent
variable – explains the variance in the dependent variable problems for the
organization. If individuals do not follow the accounting principles, confusion ensues
(intervening variable that results as a consequence of the independent variable at
time T2). But the failure to follow the principles will result in confusion and problems
only for those individuals who have no experience in book keeping. Those who have
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knowledge of book keeping will figure out ways to deal with the situation. Hence,
experience is the moderating variable.
Exercise 4.9
VARIABLE
Morale
Working conditions
Pay scale
Vacation benefits
Side income
Happiness
LABEL
Dependent variable
Independent variable
Independent variable
Independent variable
Moderating variable
Intervening variable
Explanation
The independent variables of improved working conditions, better pay, and
vacation benefits influence the dependent variable, morale. When these three
independent variables are high in a work situation, then morale is also high. However,
increased pay will not increase the morale of all workers. Only those who do not have
good side incomes will experience greater happiness (the intervening variable) when
their pay is increased, and their morale also increases. For others, the relationships
between pay and morale will not hold good. The intervening variable, happiness, is a
function of high pay (for those without side incomes). It clarifies the relationship
between pay and morale.
Exercise 4.10
Problem Statement
What are the benefits of using avatars as company representatives on commercial Web sites?
Conceptual Model
Involvement
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Informative Site
Satisfaction with
the Company
Entertaining Site
Purchase Intentions
Avatar Presence
Exercise 4.11
Problem Statement
Can cancer patients’ successful recovery be improved through quick and correct
diagnosis, carefully following the doctor’s instructions, and keeping the patients in
peaceful and quiet surroundings?
Theoretical Framework for Exercise 4.11
Cancer patients’ successful recovery is of main interest to the study, and
successful recovery is expected to be predicted by three independent variables. Thus,
recovery is the dependent variable in the study and the three independent variables
are: (1) quick and correct diagnosis by the doctor; (2) careful following of instructions
by the nurses; and, (3) peace and quiet in the vicinity. An intervening variable in the
situation is rest, and a moderating variable is the stage of cancer.
When the disease is quickly and correctly diagnosed by the doctor as soon as
the patient comes in for the initial check‐up, the chances of the patient being
successfully cured of cancer are greater, since the cancerous growth would then be
arrested in time. Also, when the nurses carefully follow the instructions of the doctor
and administer to the patient the proper medicines at the right time, give them the
diet as prescribed by the doctor, etc., the patients will recover without relapses. The
human system needs certain medical, dietary and other aids to recover, which need to
be administered at the right time and in the right quantities, and when this is done,
the patients’ recovery is almost assured. Peace and quiet in the vicinity of the patients
will allow the patient to rest properly, without any disturbances, which in turn, would
help the successful recovery of the cancer patient since the body would now have a
chance to build new healthy cells through the rest created by the peaceful
surroundings. Thus, rest is an intervening variable, which is facilitated by the peaceful
and quiet surroundings.
While the three independent variables of diagnosis, following instructions, and
peace and quiet would help the patients to successfully recover from cancer, these
three will not influence the recovery for those patients who come for treatment at
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advanced stages. In other words, only those cancer victims who come for treatment at
the early stages of the disease would be helped to recover successfully when the
doctor diagnoses the disease correctly and quickly, the nurses follow the doctor’s
instructions carefully, and the patients are kept in quiet and peaceful surroundings.
Those coming for treatment while in the advanced stages will not be helped.
Exercise 4.12
1. Ho: There is no relationship between working conditions and the morale of employees.
HA: If working conditions are improved, then the morale of the employees will also
improve.
2. Ho: There is no relationship between vacation benefits and employees’ morale.
HA: Better vacation benefits will improve employees’ morale.
3. Ho: There is no difference in the relationship between pay and happiness among those
who have side incomes and those who do not.
HA: Only those who do not have side incomes will become happier if their pay is
increased.
4. Ho: There is no relationship between happiness and morale.
HA: Happiness and morale are positively correlated.
5. Ho: Working conditions, vacation benefits, and pay have no influence on the morale of
employees.
HA: Working conditions, vacation benefits, and pay all have a positive influence on
morale.
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Exercise 4.13
Problem Statement
How can the job performance (output) of the employees be increased through
enriched jobs and rewards?
Theoretical Framework
Job performance is the main variable of interest since the production manager
is interested in increasing the output levels of employees. Job performance is, thus,
the dependent variable. Job enrichment and rewards are the two independent
variables which directly influence performance through the intervening variables of
motivation and satisfaction. However, the valence of rewards to the recipient
moderates the relationship among rewards, motivation, satisfaction and performance.
When the jobs done by the workers are such that they are more challenging
and utilize all the skills that the workers have, then the workers will be both satisfied
that they are able to use the skills they possess, and be motivated to engage in work
behavior. When employees are thus motivated and satisfied, their performance levels
will be high. Also, motivation and satisfaction will mutually influence each other. That
is, when satisfaction is high, motivation will be high, and the higher level of motivation
will, in turn, increase satisfaction. Thus, the two will mutually influence each other,
and both together will influence performance. If, on the other hand, the job is dull and
repetitive, employees will not derive any satisfaction at the workplace since they will
be bored, and their inclination to engage in work behaviors (motivation) will be low.
When employee satisfaction and motivation are low, their levels of output
(performance) will also be low.
Increased rewards will also offer employees both satisfaction and motivation,
because employees will know that the effort put in by them is recognized and
rewarded. This increased satisfaction and motivation will spur them on to perform
even better since they will now have more zeal and enthusiasm. However, the
relationship between increased rewards and the intervening variables of motivation
and satisfaction will hold good only for those who desire and value the rewards
dispensed by the organization. Those recipients who do not find the rewards valuable
or desirous will not be turned on by the rewards, and their levels of satisfaction,
motivation, and performance will not be enhanced. The valence of rewards thus
moderates the relationship between rewards and the intervening and dependent
variables.
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Hypotheses
HA1: If the job is enriched and utilizes all the skills possessed by the employee, then
employee satisfaction will be high.
HA2: If the job is enriched and utilizes all the skills possessed by the employee, then
employee motivation will also be high.
HA3: There will be a positive correlation between satisfaction and motivation.
HA4: Greater rewards will influence motivation and satisfaction only for those
employees who find the rewards valent; not for the others.
HA5: Satisfaction and motivation will positively influence performance.
HA6: The more enriched the job and the greater the skills utilized by the job, the higher
the level of employee performance.
Exercise 4.14
Problem Statement
How can minority women be retained in organizations?
Theoretical Framework
Retention of minority women is the main variable of interest to the study, and
hence, is the dependent variable. The independent variables that are likely to explain
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the variance in the retention of minority women are: (a) influential mentors willing to
help, (b) informal networking with influential colleagues, (c) role models, and (d) high
visibility projects. The intervening variable is satisfaction.
When influential officials in the system are willing to serve as formal or informal
mentors minority women can learn the ropes for progressing in the organization.
When women can network with influential colleagues, they will learn a lot about the
political system of the organization and know where and when there are opportunities
to advance. Role models help women to emulate the characteristics necessary to
climb the ladder of success in the system. When women work on high visibility
projects, they attract the attention of those in power and are likely to be promoted to
higher level positions.
When the above four factors are absent in the work environment,
dissatisfaction results due to the frustration of not having avenues for advancement.
Dissatisfaction, which surfaces as a function of the absence of the four independent
variables, is then the intervening variable which enables us to see why women quit the
organization. It should, however, be noted that not all dissatisfied minority women
leave the organization. Only those who have the resources and confidence to start
their own business leave the institution. The others remain trapped in the system.
Thus, wherewithal to start own business becomes the moderating variable.
More Exercises on Theoretical Framework
(with Answers)
Note: These can also be used as exam questions.
I. Develop a theoretical framework for the following situation and state one
testable hypothesis in the null and the alternate.
A school administrator is interested in finding how the threatened teachers’
strike can be averted. He knows that pay demands and the classroom’s physical
environment are the two main issues in the situation. He, however, feels that these
two are not major concerns for the teachers who are extremely dedicated to teaching.
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Answer
Theoretical Framework
Since the administrator’s main concern is about the strike, teachers’ strike is
the dependent variable, and an interest is evinced in averting it. Pay and the physical
environment of the classroom are the two independent variables, which influence the
strike situation. The greater the pay demands made by the teachers, the greater the
possibility of a strike, since the school administration will not easily give in to a high
pay hike which would bring any current negotiations between the two parties to an
impasse and would precipitate a strike. The more uncongenial the classroom physical
environment, the more difficult it will be for teachers to do an effective job in the
classroom, and hence the greater the possibility of teachers going on strike to have
the situation rectified. Thus, both pay demand and classroom physical environment
would explain the variance in the probability of teachers going on strike. However, this
relationship between the independent variables and the dependent variable will be
true only for those teachers who are not dedicated to teaching for its own sake. The
truly dedicated teachers would be more concerned about doing a good job despite the
hardships faced by them, and hence for them, the pay demands and the classroom
environment will not be factors influencing their decision to join the strike.
Hypothesis:
H01: Dedication to teaching will not alter the relationship between the independent
variables of pay and classroom environment and the dependent variable of teachers’
decision to go on strike.
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HA1: Only for those teachers who are not truly dedicated to teaching, will pay
considerations and classroom environment be factors that would influence their
decision to go on strike.
2. A factory foreman is concerned about the high rate of absenteeism of his workers
every Monday morning. His hunch is that the workers drink too much during the
weekend, have a hangover on Monday mornings and cannot attend work. He also
feels that the high rate of pay they receive allows them to become lethargic. From an
informal talk with his employees, the foreman finds that almost every single worker
drinks during the weekend. However, some said that they could handle drinks very
well and never had hangovers. “Ha! Now I know,” mused the foreman, “only those
who do not have an adequate tolerance level for alcoholic beverages suffer the effects
of hangover and remain absent on Monday mornings. Of course, high pay may also be
a reason.”
Given the above situation, answer the following:
a. What would be the problem statement?
b. Evolve a Theoretical Framework.
c. Develop three hypotheses for testing.
ANSWER:
a.
Problem Statement
Would pay and drinking influence absenteeism?
b. Theoretical Framework
Absenteeism is the dependent variable, the variance in which is to be explained
by the two independent variables, pay and weekend drinking. The more the pay
received by workers, the more they tend to be lethargic (intervening variable),
spending their time lazing around in the house, since they have enough money to take
care of their immediate needs without working. They thus tend to remain absent.
Excessive drinking during the weekend also contributes to absenteeism on Monday
mornings, since the hangover from the weekend drinking (the intervening variable)
would persist until late on Monday, which would prevent them from going to work.
However, for those who have a high tolerance for liquor, hangover will not be a
problem. In other words, tolerance for drinks is the moderating variable which has a
contingent effect on the relationship between the extent of drinking and the extent of
hangover people have. When people have hangovers, they will tend to remain absent
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since they will not be fit to perform their normal duties. In sum, pay and weekend
drinking will have an effect on the absenteeism of workers. However, only for those
who have a low tolerance for liquor, will more drinking during the weekends result in
their experiencing hangovers on Mondays, which would prevent them from attending
work. Those who have high tolerance levels will not experience hangover and will not
remain absent from work.
c. Hypotheses:
HA1: The higher the pay of the worker, the higher will be the rate of his absenteeism
from work.
HA2: Only for those who have a low tolerance for liquor, will heavy drinking lead to
hangover, not for others.
HA3: Hangover due to heavy weekend drinking and absenteeism will be positively
correlated.
3.a. With the following variables, develop a theoretical framework, using one of the
variables (appropriately) as an intervening variable, and one as a moderating variable.
1) Job level (i.e., managerial versus non‐managerial levels);
2) Loyalty (extent of loyalty felt for the organization in which the employee works);
3) Age (of employee);
4) Length of service (of employees);
5) Pride in working for the organization;
6) Organizational commitment (involvement with the system);
7) Lust for job hopping.
b. Develop three hypotheses based on the theoretical framework, one of which should
include the intervening variable, and another the moderating variable.
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c. What is the problem statement for which you have developed your theoretical
framework?
Answer:
a. Theoretical Framework
The four independent variables ‐ job level, age, length of service, and pride in
working for the organization ‐ influence the organizational commitment of the
members in work systems. Persons holding highly responsible positions tend to get
committed to the organization since they help shape the organization through their
policies and decision‐making. Generally, older persons tend to be more loyal to the
place where they work since opportunities to move on to other organizations become
limited. Those who have served for a long time in the organization would also be more
loyal to the organization (IV) and hence get committed to it. If one is proud of being a
member of the organization, naturally the individual’s loyalty to the system (of which
he is a part) would increase. We can also expect to find a correlation between length
of service and employees’ pride in working for the organization. The longer employees
work for the organization, the more they would tend to feel that they are an integral
part of the organizational system and feel they belong to it. These feelings, in turn, will
develop a sense of loyalty and attachment to the system. Once loyalty is developed,
commitment to stay in the organization and doing one’s best for the organization
would increase. However, high position, pride in working for the organization, age,
and length of service, would not be instrumental in developing the organizational
loyalty of such members as have a great adventurous spirit and a great desire to move
from one job to another in different organizations. Thus, lust for job hopping would be
the moderating variable which influences the relationship between the independent
variables and the intervening variable, and thus, the relationship between the
independent and the dependent variables.
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b. Hypotheses:
HA1: Only for those employees who do not have a lust for job hopping, would job level,
age, length of service, or pride in working for the organization be correlated to their
feelings of loyalty for the organization.
HA2: The more the employees are loyal to the organization the stronger will be their
sense of commitment to the organization.
HA3: The longer people work for the organization, the more their feelings of pride in
working for the organization are likely to be.
c. Problem Statement:
What factors would account for employees’ commitment to the organization?
4. Develop a theoretical framework and three hypotheses for the following statement.
People high in their Need for Achievement (N.Ach) and who have high
Protestant Work Ethic values, will be highly motivated to work. When they get
motivated, they also slowly become involved in their jobs.
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Answer:
Theoretical Framework
N.Achievement and work ethic values are the two independent variables that
would account for the variance in the dependent variable of interest–job involvement.
This relationship could be better understood through the intervening variable–
motivation. That is, those who have a high need to achieve and accomplish things in
their jobs, would be motivated to engage in work behavior, which in due course of
time will get them so absorbed in doing their jobs that their egos will be tied to the
job. Likewise, those who have high work ethic values, would feel that unless they
work, they are no good, and hence would keep engaging in work behavior. This again
is bound to increase their level of motivation to work. These frequent interactions
with work will again get them ego‐involved in their work. Thus, N.Ach and work ethic
values will motivate people to work, which in turn would get them ego‐involved in
work.
Hypotheses
HA1: The higher the Need for Achievement, the greater will be the level of motivation.
HA2: The greater the Protestant work ethic values people hold, the greater will be their
level of motivation to work.
HA3: The greater the motivation in individuals, the greater their level of job
involvement.
5. Here are eight variables:
1) Understanding Student Needs (by teacher);
2) Developing appropriate teaching strategies (by teacher);
3) In‐class examples and exercises;
4) Student entry level skills;
5) Student understanding;
6) Student exam performance;
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7) Difficulty of exam;
8) Stress.
a.
With these eight variables, develop a Theoretical
Framework, treating variable #4 as a moderator, and variable #5 as an intervening
variable.
b.
Develop four hypotheses.
Answer:
Theoretical Framework
a. The variance in the performance of students in the exam can be accounted
for by the four independent variables – teacher’s understanding of the needs of the
students, the different teaching strategies developed by the teacher, the number of
in‐class examples and exercises that the teacher gives, and how difficult the exam
itself happens to be. When the teacher understands students’ difficulties and needs in
terms of coaching and evolves appropriate teaching strategies in order to meet the
needs of the students to understand what is being taught, student understanding will
increase. In addition, if the teacher uses several examples to put across the points and
gives exercises in class to test the extent to which students have understood, then the
students’ level of understanding of what is being taught will increase. However, the
entry‐level skills of the students should be sufficiently adequate to enable them to
understand what is being taught. If the students’ entry level skills and comprehension
are very low, then no amount of the teacher making efforts to understand student
needs, evolving strategies, and giving new examples and exercises, will help the
student to understand better, since they do not have the basic prerequisite knowledge
for understanding what is going on in the class. If, however, the entry level skills are
adequate, then the teacher taking all the above steps would help enhance student
learning. When students’ level of understanding increases, their level of performance
in the exam will also be better. The level of difficulty of the exams is also another
factor that would account for the variance in student performance. The more difficult
the exam, the more stressed the students will feel while answering the exam, and the
lower will be their performance level in the exam. Thus, stress is the intervening
variable here.
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In sum, the three variables of understanding student needs, teaching strategies,
and in‐class exercises and examples will help increase the level of student
understanding, which, in turn, will enhance the level of their exam performance.
However, the more difficult the exam, the more the stress experienced by the
students, and the lower their level of performance in the exam.
b. Hypotheses
HA1: Only for those who have the requisite entry level skills, will more in‐class exercises
and examples help increase the students’ level of understanding of the subject taught.
HA2: The more difficult the exams, the greater the stress experienced by the students.
HA3: The higher the level of stress experienced by the students, the lower their level of
performance in the exam.
HA4: When students understand the subject better, they will perform better in the
exam.
Marketing
1. Factors Influencing Decision to Purchase
The four independent variables ‐ quality, price, felt need for the product, and
brand name ‐ influence customers’ decision to purchase products. When a product is
of good quality, consumer confidence in the product grows (the intervening variable),
and the stronger becomes the decision of the consumer to purchase the product. A
reasonable price and a good brand name also induces the consumer to purchase the
product. Of course, the more the consumer needs the product (such as basic needs or
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essentials), and the better the price, the quality, and the brand name, the greater the
prospect for the consumer making the decision to buy the product. Usually, the better
known the brand name, the greater the desire to purchase that product. However if a
prospective consumer happens to have a strong brand loyalty for a brand other than
the one marketed, then, the brand name of the product will not influence the
purchase decision. Thus, only for those who do not have a strong brand loyalty to a
different product, will the relationship between brand name (IV) and purchasing the
product (DV) hold true.
2. Factors Affecting Coupon Redemption Rates
Coupon redemption, a strategy for spurring sales, is the variable of interest to this
study. Needless to say, this sales strategy will be effective when the distribution
channels for the product in question are well planned, when there is sufficient
advertising to let the consumers know about the promotion, when the package clearly
indicates the coupon redemption scheme with the expiration date, if any, and the
packaging of the product is of the right size (neither too big nor too small to serve the
needs of the consumer). Of course, all these factors will not help, unless there is an
established frequent need for the product for consumers (Moderating variable).
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Accounting
3. Factors Influencing the Selection of Auditors by Companies.
The influence of the reputation of the auditing firm, the fees charged, and the
quality of service rendered, on the selection of the auditor for a firm is quite simple.
The greater the reputation of the auditing firm, the more the likelihood of its being
selected, the better the quality of service rendered, and the more reasonable the fee
that is charged, the more likely is a particular auditing firm going to be chosen.
Interaction is the intervening variable that helps us to see how the proximity of the
auditing firm to the business plays a part in auditor selection. If the auditing firm is
proximal to the business, the closeness encourages frequent interactions between the
two parties to have matters clarified at low cost. This, in turn, influences the business
to choose an auditing firm that is proximal. However, the very big business companies
will not choose any but the big eight Accounting firms. Hence, for them, the choice of
auditors from any but the big eight will not be influenced by the independent
variables in the model. Thus, the size of the business firm becomes the moderating
variable.
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4. Factors that Account for the Variance in Bad Debt.
Bad debt is the variable of interest to this study, the variance in which is theorized
to be explained by the three factors of credit policy, monitoring of receivables, and
pay‐out period on installment loans. A sensible credit policy, no doubt, will reduce bad
debt. A follow up on accounts receivable will further reduce bad debts by recovering
as much as possible before things get out of control. The pay‐out period will also have
an effect on the amount of bad debt. If the pay‐out period is too long (stretching over,
say, several years), there is likely to be a tendency to slack off on the installment
payments (the intervening variable), especially if the value of the product depreciates
substantially. However, customers who consider their reputation for creditworthiness
as paramount, will still honor their commitments despite the long drawn out payment
periods. Thus, class of customer will moderate the relationship between the
independent variable, pay‐out period, and the intervening variable, slacking off on
payments
.
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Finance
5. What are the most important factors that influence the profits of a firm?
6. Critical Factors that Influence the Value of a Company’s Stock.
The value of the company’s shares is of interest to the study. If a company sustains
its high earnings year after year, its credibility as a successful company would be
enhanced and the public will believe it has further prospects for growth (intervening
variable). This will help to explain how sustained earnings will increase the stock value
of the company. Faith in the managerial competence of the key people in the
company will hold the stock value high, even in times of mild recession. Thus the
perceived managerial competence of the individuals in the company would influence
the stock value.
Usually, the higher the dividends, the higher the stock value; however, if the higher
dividend declared is perceived as a stunt to hoodwink the public, the stock value will
not go up. Only when the public expects that the dividend policy will be maintained by
management in the future (moderating variable), will the stock value of the company
be influenced by the higher dividends that are declared.
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CHAPTER 5
THE RESEARCH PROCESS: ELEMENTS OF
RESEARCH DESIGN
Instructional Goals
1. To clarify the various components of research design as indicated in Figure 5.1 of the
book.
2. To highlight obvious combinations in research design choices; for example, a lab or
field experiment is invariably conducted to establish cause and effect relationships; a
lab experiment is always done in a contrived setting with maximal researcher
interference and in a longitudinal fashion.
3. To stress the importance of making optimal research design choices aimed at
balancing scientific rigor and research costs (and feasibility).
Discussion Questions
1. What are the basic research design issues? Describe them in some detail.
Basic research design issues are primarily a function of the purpose of the study
(whether it is exploratory, descriptive, or hypothesis‐testing), and relate to such
aspects as the type of study to be done (causal or correlational), the setting in
which it will be done (natural or contrived), how much researcher control will have
to be exercised (very little in the case of field studies, to very much in the case of
experimental designs), how many times data will have to be collected (one shot
versus longitudinal), and the unit of analysis – i.e. the level at which data will be
aggregated. For most correlational studies, the field setting with minimal
researcher influence will be the choice. Most field studies are generally cross‐
sectional, though some could be longitudinal. Longitudinal studies, though better
for understanding the dynamics of the situation fully, also consume more time and
resources. Thus, the costs of a study also determine some of the design choices.
The unit of analysis depends on whether the research question focuses on
individuals, dyads, groups, or entire systems.
2. Why is it important to consider basic research design issues before conducting the
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study and even as early as at the time of formulating the research question?
The research design ensures that the purpose for which a study is conducted is
effectively addressed. Some studies are focused on finding results which will be highly
reliable, whereas others might be interested in “getting some idea” of what is going
on, rather than wanting to know the “absolute truth”. If the rigor needed can be
achieved at only high cost (e.g. more manipulation and control, conducting the study
over an extended period of time with a big sample, etc), and if this cost is considered
too much, then the goals of research might have to be revised or even completely
changed. Thus, thinking through the research design issues at the early stages helps in
averting several problematic issues later.
3. Is a field study totally out of the question if one is trying to establish cause and effect
relationships?
Generally lab and field experiments, rather than field studies, are useful for
establishing greater internal validity, or faith in cause and effect relationships.
However, when longitudinal data are collected from field studies, or when particular
types of statistical analyses are done on cross‐ sectional data gathered from field
studies, it is sometimes possible to establish the existence of causal relationships.
More specifically, cross‐lagged correlation analysis (not discussed in the book) using
data collected at more than one point in time, can indicate causal relationships.
Even using cross‐sectional data (i.e. with data collected at one time only) statistical
techniques, such as path analysis, can identify cause and effect relationships.
However, in such cases, the data and the theory will have to lend themselves to
certain assumptions which are not always easily met.
4. “An exploratory study is just as useful as a predictive study”. Discuss this statement.
Without exploratory studies, new areas of knowledge cannot be developed. Every
theory we now have must at one time have started as an exploratory research study.
Exploratory research lays the groundwork for understanding new phenomena, and
developing new measures to test these. The exploratory studies of today blossom into
the predictive studies of tomorrow, and in that sense both types of study are useful
and essential to generate knowledge, understanding, and prediction of business
phenomena.
5. Why is the unit of analysis an integral part of the research design?
The unit of analysis is an important issue to be considered to find the right answers
to the research questions posed. The unit of analysis also determines the sample size.
For example, if one is interested in researching the factors that influence the stock
market in three different European countries, it is the behavior of stock markets in
those three countries that are of central interest to the study, and not the individual
stock market within each country. At the time of data analysis, the data gathered from
each of the stock markets within each country will somehow have to be meaningfully
aggregated, and only those three data points, which will form the three samples, have
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to be taken into consideration. Thus, the unit of analysis is a function of the research
question posed, and is an integral part of the research design. As will be seen later,
research design decisions relating to sampling also depend on the unit of analysis. Let
us say a researcher decides to have a sample size of 30 for a study. Sampling 30
individuals in an organization when the unit of analysis is individuals, is not as
problematic as sampling 30 organizations when the unit of analysis is organizations, or
sampling 30 countries when the unit of analysis is countries. Thus, the unit of analysis
influences other decisions such as the sampling design, the sample size, data
collection methods, etc.
6. Discuss the inter‐relationships among: non‐contrived setting, purpose of the study,
type of investigation, researcher interference, and time horizon of the study.
A non‐contrived setting simply indicates that the research is conducted where the
flow of events normally takes place – i.e. in the natural system. Such research could be
either field studies or field experiments. The purpose of the field study could be for
exploration and understanding of phenomena, for describing phenomena, or for
hypothesis‐testing. The field study is a correlational study, and not usually initiated to
explore cause and effect relationships. Researcher interference in field studies is
minimal. Field studies could be either cross‐ sectional or longitudinal. Field
experiments, on the other hand, are undertaken to establish cause and effect
relationships, are longitudinal in nature, and researcher interference in field
experiments is much more than in field studies, since the independent variable will
have to be manipulated. These are mostly hypothesis‐testing studies, though they
could be exploratory in nature, as well.
7. Below are three scenarios. For each, indicate how the researcher should proceed with
the following, giving reasons:
a. The purpose of the study
b. The type of investigation
c. The extent of researcher interference
d. The study setting
e. The time horizon for the study
f. The unit of analysis.
Scenario A
Ms. Joyce Lynn, the owner of a small business (a woman’s dress boutique), has
invited a consultant to tell her how she is different from similar small businesses within
a 60‐mile radius, in regard to her usage of the most modern computer technology,
sales volume, profit margin, and staff training.
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Answer
This will be a descriptive study (describing how she compares with the others).
Data will be collected from small businesses on the use of computers, sales volume,
profit margin, and training programs and comparisons made. Some of these
descriptions might be qualitative, as for example, in describing training methods. This
will be a field study (using many similar small businesses), and researcher interference
will be minimal. It will be a one‐shot study, and the unit of analysis will be small
business systems.
Scenario B
Mr. Paul Hodge, the owner of several restaurants is concerned about the wide
differences in the profit margins of the various restaurants. He would like to try some
incentive plans for increasing the efficiency levels of those restaurants that are lagging
behind. But, before he introduces this, he would like to be sure that the idea will work.
He asks a researcher to help him on this issue.
Answer
This would be a causal, hypothesis‐testing study. It will be a field experiment,
using one or two restaurants to manipulate incentive plans and see if this causes an
increase in profit margins in those restaurants. Because of the manipulation, there will
be some researcher interference with the natural flow of events. The time horizon for
the study would be longitudinal since data will be obtained on sales, profits, etc., both
before and after the manipulation. The unit of analysis would be the restaurant.
Scenario C
A manager is intrigued why some people seem to derive joy from work and get
energized by it, while others find it troublesome and frustrating.
This would be a correlational, hypothesis‐testing, field study with minimal
researcher interference. It will be a one‐shot study and the unit of analysis will be
individuals.
Exercises
Doing the exercises in the chapter will help the student to apply the basic
elements of research design to different scenarios. More in‐class exercises are offered
at the end of this chapter (with answers), that can be used either in the classroom or
as exam questions.
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Answers to Exercises in the Book
Exercise 5.1
A foreman 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?
2. Is this an exploratory, descriptive, or hypothesis‐testing (analytical or predictive)
study? Why?
3. What kind of a 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‐sectional or a longitudinal study? Why?
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).
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 conclusion will be made as to whether the
operators are less efficient because of the fumes emitted in the workshop.
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.
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Exercise 5.2
Many were concerned about the operations of the infamous BCCI, the
international banking institution. If the Government had desired to probe into the
details, would this investigation have called for:
1. A causal or correlational study? Why?
2. An exploratory, descriptive, or hypothesis‐testing study or case analysis? Why?
3. A field study, lab experiment, or field experiment? Why?
4. A cross‐sectional or longitudinal study? Why?
1. This would have been a correlational study since the details desired are to be probed
into without trying to establish cause and effect relationships.
2. It would be a descriptive study describing the operations of BCCI.
3. This would be a field study since data will be collected in the natural environment.
4. This will be a cross‐sectional study since the data will be collected at only one point in
time.
Exercise 5.3
You want to examine how exposure to thin or heavy models in advertisements influences a
person’s self‐esteem. You believe that the effect of exposure to models in advertisements
depends on the extremity of the model's thinness or heaviness.
Discuss the design decisions that you as a researcher will make to investigate this issue,
giving reasons for your choices.
An experimental study (causal study) will be needed since the goal of the study is to
test a cause‐and‐effect relationship.
-
A pretest will help you to select advertisements containing female models for the
following four conditions: moderately thin, extremely thin, moderately heavy, and
extremely heavy;
participants view an advertisement booklet containing ads with female models.
participants rate each model in terms of size (‐5 =extremely overweight, +5 =
extremely thin) and attractiveness (‐5 = extremely unattractive, + 5 = extremely
attractive).
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Based on these scores, you will be able to select advertising models in each condition.
Note that models should differ from each other in terms of size but not in terms of
attractiveness (you have to perform post hoc comparisons to test for this).
In the actual experiment, participants must be randomly assigned to one of the four
conditions of the 2 (model size: thin vs. heavy) and (extremity of model size: moderate
vs. extreme) between‐subjects design. Participants are then provided with a booklet
containing ads: ads with models, pertaining to their condition, and filler ads with no
models (randomize the order of the ads). Eventually (after one or more filler tasks)
participants complete a self‐esteem scale such as for instance the Appearance Self‐
Esteem Scale (Heatherton and Polivy 1991).
Exercise 5.4
You want to investigate the specific effects of specific emotions on customers'
behavioral responses to failed service encounters across industries.
Discuss the design decisions that you as a researcher will make to investigate this
issue, giving reasons for your choices.
Because it is difficult (and probably unethical) to induce specific emotions in an
experiment a field study seems to be the more logical choice. Note however, that
when you use a field study, it is very important to control for variables that might
potentially bias your results such as complaint success likelihood and switching costs.
The critical incident technique is a method that may help you to collect a wide variety
of negative experiences with service organizations.
Exercise 5.5
War on Cancer
Dr. Larry Norton of Memorial Sloan‐Kettering Cancer Center predicts that cancer
treatment will undergo major changes. Several drugs are being developed to battle
cancer without harming healthy tissues. It is a question of discovering which of these
drugs does the job best.
Design a study that would help find which drug would do the trick.
An experimental study (causal study) of the Solomon Four‐Group design will be
needed. A count of the healthy tissues in cancer patients at more or less the same
stage of cancer progress will first be taken, with about 20 patients in each group. Each
group, but the control group, will be treated with the different new drugs. The cancer
cell count will be taken both before and after treatment for a period of time (say, 3 to
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6 months) to see which has the most beneficial effect. Thus it would be a longitudinal
study with some manipulation (drug variation) and control (matched or randomized
groups). The unit of analysis will be groups.
More in‐Class Exercises on Research
Design (with Answers)
Several situations are given below. For each situation, respond to the following
research design questions.
a. What would be the nature of the study that would be designed ‐ Exploratory,
descriptive, or hypothesis‐testing?
b. Give reasons for your answer to (a) above.
c. Would it be a Field study, Comparative study, Lab experiment or Field experiment?
d. Would it be a causal or correlational study?
e. Justify the reasons for your answer to (d).
f. Would it be a longitudinal or cross‐sectional study?
g. How would you explain your answer to (f) above?
h. What would be the unit of analysis?
i. Defend your answer to (h) above.
1. A researcher wants to test the theory that low levels of oxygen in the mines is the
single most important factor that tires miners easily.
ANSWER:
a & b: Hypothesis‐testing, because the researcher wants to analyze and test if low
levels of oxygen would, in fact, cause tiredness in miners.
c: A Field Experiment, because there would be manipulation of the levels of oxygen
in the natural environment of the workers.
d & e: Causal study, because the researcher wants to see if low levels of oxygen
cause tiredness in miners. He wants to establish a cause and effect relationship
between the independent and the dependent variables.
f & g: It would be a Longitudinal study because data on tiredness will be collected
from the same batch of workers before and after each manipulation of the extent of
oxygen injected into the environment.
h & i: The unit of analysis will be individual miners because the data will not be
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aggregated across groups, but each individual miner’s level of tiredness will be
recorded and used in data analysis.
2. An Auditor is interested in knowing the relationship among the three variables –
depreciation, assets accounting, and taxes paid.
ANSWER:
a & b: Hypothesis‐testing, because the manager wants to analyze the correlations
among the three variables.
c: Comparative Field study since the data will be gathered from several firms.
d & e: It will be correlational since the relationship (and not cause and effect
relationships) among the variables is being studied.
f & g: Cross‐sectional since the data will be gathered only once.
h & i: Unit of analysis will be the firms.
3. The head‐nurse in a hospital would like to have a profile of the patients that come to
her ward.
ANSWER:
a & b: Descriptive since the head nurse only wants a profile – a mere description of
the type of patients who come to her ward.
c: Field study, since the people coming to her ward (natural setting) will be studied.
d & e: It is a descriptive study, using merely frequency distributions and means and
standard deviations. It is thus neither a causal nor a correlational study.
f & g: Cross‐sectional, since data will be gathered from each person just once to
get the profile.
h & i: Unit of analysis will be individual patients since individual profiles will be
studied.
4. A basic researcher wants to engage in a research project which will enable her to
establish the relationship between certain personality characteristics and the risk
taking tendencies of stock brokers.
ANSWER:
a & b: Hypothesis‐testing, since the researcher would have formulated a
conceptual framework of the type of personality characteristics that would induce
stock brokers to take more risks, and would want to test her hypotheses.
c: Field study since subjects will be studied in the natural environment in which
they usually operate.
d & e: Correlational study since the relationships among the personality
characteristics and risk‐taking are studied.
f & g: Cross‐sectional since data will be gathered at only one point in time.
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h & i: Unit of analysis will be individuals (stock brokers) since the data analysis will
be done on each individual’s responses without any aggregation across groups.
Note: This can also be set up as a Lab experiment in which Finance majors are put
in a contrived setting and offered some investment assignments that call for risk
taking. Their personality characteristics can be obtained through a questionnaire
survey, and their risk taking behavioral tendencies assessed by manipulating the level
of financial risk involved in the investments.
5. Bob’s Nissan and Toyota dealership is suffering from a severe decline in the number
of car sales. Bob decides to test two approaches to sales. He randomly assigns his 12
salesmen to two groups. He then trains one group to use the “hard sell” approach
and the other to use the “soft sell” approach so that he can determine which
method is more effective.
ANSWER:
a & b: Predictive, hypothesis‐testing study since Bob wants to be able to test which
one of the two sales approaches will help sell more cars (i.e. predict which sales
approach is effective).
c: Field experiment since the independent variable “sales approach” is
manipulated to be either hard or soft sell and tried in the natural environment in
which sales usually take place and not in an artificial lab setting.
d & e: Causal study, since Bob wants to know which approach would cause sales to
increase.
f & g: Longitudinal, because the sales levels, both before the manipulation and
after, will be measured.
h & i: Unit of analysis will be groups since the sales of each of the two groups –
“soft sell” and “hard sell” salesmen – will be aggregated and compared.
6. A production manager wants to see if, by providing enhanced automation
technology, the productivity of the workers in the plants can be raised. However,
before trying this with all the five plants, she would like to try this with a group of
apprentices who work in one plant.
ANSWER:
a & b: Hypothesis‐testing, analytical study, since the manager wants to be able to
analyze the cause and effect relationship between enhanced automation and worker
productivity.
c: Field experiment, since the study will be conducted in the natural environment
where events usually take place.
d & e: Causal study, since causal relationships are trying to be established.
f & g: Longitudinal, since productivity measures will be taken from the same
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workers before and after the introduction of the enhanced automation.
h & i: Individuals will be the unit of analysis since there will be no aggregation of
data across group members.
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CHAPTER 6
MEASUREMENT OF VARIABLES:
OPERATIONAL DEFINITION
Instructional Goals
1. To pinpoint the need to operationally define variables.
2. To highlight the importance of identifying the dimensions, and later during discussions
of content validity, to reconnect the dimensions of a concept to the establishment of
its content validity.
Discussion Questions
1.
What is meant by operational definition, when is it necessary, and why is it
necessary?
Operational definition refers to the process of defining an abstract concept in such a
manner that it can be measured. It is necessary because it allows us to measure
subjective characteristics and phenomena which do not lend themselves to objective
measurement.
2.
Why is it wrong to use correlates of a concept to measure that concept?
Because if we use the correlates of a concept to measure it, we do not measure the
right thing. Instead of measuring the concept that we want to measure we will
measure variables we do not intend to measure nor were we interested in.
3. Operationally define the following:
a. Customer loyalty
Airline example (Agustin and Singh 2005)
• I would continue flying with this airline.
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• The next time I need to air travel, I would fly with this airline.
• I would consider this airline my first choice to air travel.
• I would use the services of this airline in the next years.
b. Price consciousness
Lichtenstein, Ridgway, and Netemeyer (1993)




I tend to buy the lowest‐priced brand of (category) that will fit my needs.
When buying a brand of (category), I look for the cheapest brand available.
When it comes to buying (category), I rely heavily on price.
Price is the most important factor when I am choosing a brand of (category).
c. Career success
Career Success could be either objective (as judged by the profession), or subjective
(as judged by oneself).
Objective career success is usually defined in terms of the prestige of the position and
status one holds, and by one’s salary. Subjective career success is defined in terms of
how one feels about where one aspired to be at that particular point in one’s career
and where one actually is.
Some items to measure subjective career success are:
To what extent do you feel you have:
i.
Achieved whatever you had hoped to achieve at this stage in your career
ii.
Accomplished the kinds of goals you had set for yourself
iii.
Compared to others of similar background, made progress in your career
4. Is it useful to draw on existing measures to measure abstract and subjective
constructs such as for instance customer loyalty? Why (not)?
The use of existing measurement scales has several advantages. First, it will save you a
lot of time and energy. Second, it allows you to verify the findings of others and to
build on the work of others (this is very important in scientific research but impossible
if you would use measures that differ from the measures that our predecessors have
used!). Hence, if you want to measure something, see if it has been measured before
and then use this measure (adapt it to your specific needs whenever this is needed).
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Exercises
Exercise 6.1
a. Read the paper of Cacioppo and Petty (1982) and describe how the authors
generated the pool of 45 scale items that appeared relevant to need for cognition.
You can find the paper on John Cacioppo’s website:
http://psychology.uchicago.edu/people/faculty/cacioppo/jtcreprints/cp82c.pdf
Students should provide a detailed account of the four studies that were undertaken
to develop the need for cognition scale. Specific goals of these studies have to be
discussed and a detailed account of the method and procedure should be provided
per study. You can organize a discussion on why (these or all) four studies are needed.
b. Why do we need 34 items to measure “need for cognition”? Why do three or four
items not suffice?
Because this ensures that the measure includes an adequate and representative set of
items that tap the concept “need for cognition” (= content validity).
Exercise 6.2
Try to come up with two unidimensional and two multidimensional abstract
concepts. Explain why these concepts have either one or more than one dimension.
Answers will vary:
Examples of multidimensional scales:
-
service quality (dimensions: responsiveness, reliability, assurance, empathy,
and tangibles)
-
store loyalty (dimensions: cognitive, affective, and connotive loyalty)
-
power bases (dimensions: reward power, coercive power, legitimate power,
referent power, and expert power)
Examples of unidimensional scales:
-
anger
-
price perception
-
endorser attractiveness
-
buying intention
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Exercise 6.3
Provide an operational definition of the concept of service quality and develop
questions that would measure service quality.
Answers will vary.
Exercise 6.4
Compare your service quality measure to the measure of Zeithaml, Parasuraman,
and Berry (1988) presented in Journal of Retailing.
a. How does your measure differ from this measure in terms of dimensions and
elements?
Service quality: the consumer’s overall impression of the relative inferiority/
superiority of the organization and its services (Bitner and Hubert, 1994).
Zeithaml, Parasuraman, and Berry (1988) have operationalized service quality by
assessing service and performance on 22 items believed to represent five key
dimensions (reliability, responsiveness, assurance, empathy, and tangibles) of service
quality (you can find the paper on Valerie Zeithaml’s webpage:
http://areas.kenan‐flagler.unc.edu/Marketing/FacultyStaff/zeithaml/Selected%20Publications/Forms/AllItems.aspx.
Reliability items:
1. When XYZ Company promises to do something by a certain time, it does so.
2. When you have a
problem, XYZ Company shows a sincere interest in solving it.
3. XYZ Company performs the service right
the first time.
4. XYZ Company provides its services at the time it promises to do
so.
. 5. XYZ Company keeps customers informed about when services will be performed.
Responsiveness items:
1. Employees in XYZ Company give you prompt service.
2. Employees in XYZ Company are always willing to help you.
3. Employees in XYZ Company are never too busy to respond to your request.
Assurance items:
1. The behavior of employees in XYZ Company instills confidence in you.
2. You feel safe in your transactions with XYZ Company.
3. Employees in XYZ Company are consistently courteous with you.
4. Employees in XYZ Company have the knowledge to answer your questions.
Empathy items:
1. XYZ Company gives you individual attention.
2. XYZ Company has employees who give you individual attention.
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3. XYZ Company has your best interests at heart.
4. Employees of XYZ Company understand your specific needs.
Tangibles items:
1. XYZ Company has modern‐looking equipment.
2. XYZ Company's physical facilities are visually appealing.
3. XYZ Company's employees appear neat.
4. Materials associated with the service (such as pamphlets or statements) are visually appealing at XYZ
Company.
5. XYZ Company has convenient business hours.
b. Would you prefer using your own measure or the measure of Zeithaml,
Parasuraman, and Berry? Why?
The use of existing measurement scales (in this case the Zeithaml, Berry, and
Parasuraman scale) has several advantages. First, it will save you a lot of time and
energy. Second, it allows you to verify the findings of others and to build on the work
of others (this is very important in scientific research but impossible if you use
measures that differ from the measures that our predecessors have used!). Hence, if
you want to measure something, see if it has been measured before and then use this
measure (adapt it to your specific needs whenever this is needed).
In‐Class Exercises
Operational Definition
Beyond the exercises in the book, you might want students to operationally define
some other concepts to see if they have understood how to measure variables. A list
of further concepts for use as in‐class exercises is provided.
While discussing these exercises, many opportunities will present themselves, where,
as earlier mentioned, students would define the correlates of a concept as its
dimension. The more the in‐class exercises, the greater will be the clarity provided to
students.
Advertising effectiveness
Brand Loyalty
Compensation scheme
Competence
Group support
Intention to Turnover
Job skills
Life satisfaction
Media Trust
Mental health
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Organizational climate
Policy excesses
Role ambiguity
Role conflict
Role overload
Role stress
Work ethic
Work environment policies
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CHAPTER 7
MEASUREMENT: SCALING, RELIABILITY,
VALIDITY
Instructional Goals
1.
To start preparing students to think in terms of the power of the
scales for increasing levels of sophistication in data analysis (elaborated in the next
section).
2.
3.
To explain the different rating and ranking scales.
To help students understand how scaling techniques are applied,
and how some of the rating scales are treated as Likert‐type interval scales.
4.
To stress the importance of establishing the goodness of
measures.
5.
To explain the different types of validity and reliability.
Discussion Questions
1. Describe the four types of scales.
The four scales are nominal, ordinal, interval, and ratio.
The nominal scale separates individuals or items into categories – e.g. seniors and
juniors. The ordinal scale helps to rank order the separated items. The interval scale
helps to determine the extent to which the items are different from each other. In
other words, is the difference between item 1 and 2 the same as the difference
between 4 and 5? The ratio scale helps to determine the proportion of differences
among items since it has an absolute zero origin, and is the most powerful of the four
scales.
2. How is the interval scale more sophisticated than the nominal and ordinal scales?
Whereas the nominal and ordinal scales group and rank the subjects, respectively, the
interval scale, in addition, also indicates the magnitude of the differences. The
distance between any two points on the interval scale is the same. If an individual
prefers A to B, and another prefers C to D, we know that the difference in the
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magnitude of the preferences for both individuals is the same (if this is captured on an
interval, rather than on an ordinal scale).
Because of the above reason, an interval scale lends itself to more sophisticated
statistical analysis. The mean and standard deviation can be calculated for the
variables tapped on an interval scale, which cannot be done for those on an ordinal
scale.
3. Why is the ratio scale the most powerful of the four scales?
The ratio scale is the most powerful of the four scales because it not only indicates the
magnitude, but also the proportion of the differences. Whereas an interval scale only
indicates that the distance between any two points on the scale is the same, and any
identical additions or subtractions will maintain the differences, the ratio scale,
because of its true zero origin, also indicates the proportion of the differences. A
person with IQ 150 is expected to be two times as intelligent as the one who has
scored 75 on the IQ test. Any division or multiplication of the data by the same
number will still maintain this proportion. Because of this, the geometric mean and
the coefficient of variation can be calculated.
4. Briefly describe the difference between attitude rating scales and ranking scales
and indicate when the two are used.
As their names indicate, ranking scales rank the order of preferences, whereas rating
scales rate subjects on a continuum. Ranking scales are used with ordinal data, and
rating scales with interval or ratio‐scaled data. While the latter lend themselves to
sophisticated analyses, such as calculating the mean and standard deviation, the
former lends itself only to less sophisticated, non‐parametric statistical analyses.
Attitudinal scales are used for measuring nebulous subjective concepts (such as
attraction and weariness) where states of mind, feelings, and impressions are tapped.
Ranking scales are used to tap preferences among objects, such as preferences for
types of nursing homes, schools, etc.
5. Why is it important to establish the “goodness” of measures and how is this
done?
The goodness of measures indicates whether the scales we use are reliable and valid.
In other words, they indicate to what extent we are accurately measuring the concept
(reliability), and whether we are indeed measuring whatever we are supposed to
measure (validity). If we are not measuring the intended concept accurately, then our
study will not yield the correct results.
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Reliability is established by assessing the stability of the measure through test‐retest
reliability and parallel form reliability, and internal consistency of the measure through
Cronbach’s alpha.
Validity is established through construct validity, criterion‐related validity (concurrent
and predictive), and congruent validity (convergent and discriminatory).
6. Describe the difference between formative and reflective scales.
In a reflective scale, the items (all of them) are expected to correlate. Unlike the items used in
a formative scale, discussed next, each item in a reflective scale is assumed to share a
common basis (the underlying construct of interest). Hence, an increase in the value of the
construct would translate into an increase in the value for all the items representing the
construct.
A formative scale is used when a construct (such as for instance job satisfaction) is viewed as
an explanatory combination of its indicators (promotions, pay, satisfaction with supervision,
coworkers, and work); that is, when a change in any one of the indicators (dimensions) is
expected to change the score of the overall construct, regardless of the value of the other
indicators (dimensions).
7. Explain why it does not make sense to assess the internal consistency of a formative
scale.
While it makes sense to test the inter‐item consistency of reflective scales, it does not make
sense to test the inter‐item consistency of formative scales. The reason is that we do not
expect the items in a formative scale to be homogeneous; in other words we do not expect all
the items to correlate. For this reason, tests of the consistency of respondents’ answers to
the items of a formative measure do not tell us anything about the quality of our measuring
instrument. Note that there are other methods to assess the goodness of formative scales
(see for instance, Jarvis, MacKenzie, and Podsakoff, 2003).
8. “The job involvement measure described in the appendix is reflective in nature.”
Comment on this statement.
Yes, each item in this scale shares a common basis (the underlying construct of interest, in
this case job involvement). Hence, an increase in the value of the construct would translate
into an increase in the value for all the items representing the construct.
9. Construct a semantic differential scale to assess the properties of a particular brand of
tea or coffee.
Semantic Differential Scale for Upton Tea Bags
Fine Flavor
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No Flavor
64
8
7
Smooth Brew
8
7
Good Taste
8
7
Lifts the spirit
8
7
Gives Energy
8
7
6
5
4
3
6
5
4
3
6
5
4
3
6
5
4
3
6
5
4
3
2
Thick Brew
2
Distasteful
2
Depresses
2
Debilitates
2
1
1
1
1
1
10. “Whenever possible, it is advisable to use instruments that have already been
developed and repeatedly used in published studies rather than develop our own
instruments for our studies”. Do you agree? Discuss the reasons for your answer.
It is always advisable to use well‐validated instruments that have been repeatedly
used in published studies, rather than going through the cumbersome process of
developing one’s own instruments and laboriously establishing their validity and
reliability. However, simply because an instrument is used in some published studies
does not necessarily make it a good instrument. It is always wise to examine the
psychometric properties established for the instrument before using it. In case this is
not easily available, a pilot study can be conducted to see if the measures have at least
acceptable reliability.
11. “A valid instrument is always reliable, but a reliable instrument is not always
valid”. Comment on this statement.
If an instrument is valid, especially in terms of content validity, we would expect to
have a reliable instrument. However, an instrument can have both consistency and
stability, but may not be measuring what it is intended to measure – i.e. have low
validity. However, if an instrument does measure the concept that it is supposed to
measure, it will be reliable. Thus, a valid instrument will be reliable, but a reliable
instrument need not necessarily be valid.
Exercises
Exercise 7.1
Two variables that lend themselves to nominal scaling, along with mutually
exclusive and collectively exhaustive categories, are as follows:
Types of Employees in a Computer Firm
□
Accounts clerk
□
Systems analyst
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□
Supervisor
□
Machine operator
□
Mechanic
□
Manager
□
Other (specify)
Types of Department in a Research Laboratory
□
Mathematics department
□
Physics department
□
Chemistry department D Statistics department
□
Computer sciences department
□
Operations research department
□
Other (specify)
Exercise 7.2
The following is an ordinal scale for consumer preferences for different brands
of beer.
Rank the following brands of beer in the order of your preference. In the boxes
provided next to each brand name, write the number that denotes your ranking. That
is, write 1 next to your favorite brand, 2 next to the next favorite one, and so on, until
each brand name has a number. If you do not drink beer at all, put a check mark ( ) in
the last box.
□ Budweiser
□ Coors
□ Michelob
□ Miller
□ Olympia
□ Pabst
□ Strohs
□ Do not drink beer at all
Exercise 7.3
One of them could be Satisfaction with Organizational Facilities provided.
To what extent are you satisfied with the following facilities provided by your
organization? Please circle the appropriate response for each item, using the scale
indicated below.
Very Satisfied 1
Somewhat
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Neither
Satisfied 4
Very
66
1. With the vacation
2. Time off for emergencies
3. Flexible work hours
4. Career counseling
5. Training for career mobility
6. Transfer policies
Satisfied 2
Satisfied Nor
Dissatisfied 3
1
1
1
1
1
1
2
2
2
2
2
2
Satisfied 5
3
3
3
3
3
3
4
4
4
4
4
4
5
5
5
5
5
5
Exercise 7.4
SCALE
VARIABLE AND EXPLANATION
Nominal
Buyers of a product can be nominally grouped under three categories: those who
like the product and buy, those who are indifferent to the product and buy, and
those who do not like the product, yet buy it anyway.
Customer rank ordering of preferences for various name brands of jeans.
Extent of appeal of a particular advertisement to customers on a five point scale
ranging from very little to very much. Here customers are split into five groups;
they are ranked from those who like very little to those who like very much;
there is also an assessment of the extent of the appeal; and we know that the
difference between two adjacent points in the scale have the same magnitude of
difference.
Percentage of sales increase of a product. There is an absolute zero origin (when
there is no additional sale made at all during a particular year, the sales increase
is zero), and a 10 percent increase in sales is twice as much as a 5 percent
increase. Thus this scale has both a zero origin and a measure of proportion.
Hence, it is a ratio scale.
Ordinal
Interval
Ratio
Exercise 7.5
Develop and name the type of measuring instrument you would use to tap the
following:
a. Which brands of beer are consumed by how many individuals;
Nominal scale will be used.
The questionnaire might simply ask the name of the brand consumed by each
individual and, when the responses are received, categorize them under the different
brands, or
The popular brands can be categorized with a final item “Other” and respondents
asked to mark the one they consume.
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b. Among the three types of exams – multiple choice, essay type, and a mix of both ‐
, which is the one preferred most by students;
An ordinal scale will be used for this.
Rank your preferences for the types of exams below. For the most preferred one,
place 1 beside the item, for the next preferred, 2, and the least preferred, 3.
Multiple Choice Exams
Essay type Exams
Mix of multiple choice and Essay questions
_______
_______
_______
c. To what extent do individuals agree with your definition of accounting principles.
This will be tapped on a Likert scale (interval scale).
Use the following scale to respond to the item below:
Strongly Disagree
Disagree
1
2
To what extent do you agree with 1
my definition of Accounting
Principles as described below?
Neither Agree nor
Disagree
3
Agree
Strongly Agree
4
5
2
3
4
5
d. How much people like an existing organizational policy.
Interval‐scaled item as below.
For the item below, circle the appropriate number, using the scale below
Very Much
1
How much do you like the
existing organizational
policy?
e.
To some
Extent
2
1
Neither Like nor
Dislike
3
2
Somewhat
Dislike
4
3
Dislike
Intensely
5
4
5
The age of employees in an organization.
Ratio scale asking for the actual age of employees.
f.
The number of employees in each of the 20 departments of a company.
Ratio scale counting the exact number of employees in each of the departments.
Exercise 7.6
“The Index of Consumer Sentiment Towards Marketing described in the appendix is
formative in nature.” Comment on this statement. Explain why it does not make sense to
assess the inter‐item consistency of this scale.
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A formative scale is used when a construct is viewed as an explanatory combination of its
indicators. The Index of Consumer Sentiment Towards Marketing contains five dimensions
(e.g., product quality, price of products). It does not make sense to test the inter‐item
consistency of this scale because we do not expect the items in a formative scale to be
homogeneous; in other words we do not expect all the items to correlate.
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CHAPTER 8
DATA COLLECTION METHODS
Instructional Goals
1.
To develop interviewing skills in students;
2.
To help students become proficient in designing questionnaires;
3.
To introduce students to different methods of data collection
including observational surveys, electronic surveys, and collecting information from
unobtrusive sources;
4.
To emphasize the advantages of obtaining data from multiple
sources, and multiple methods of data collection;
5.
To offer an idea of which data collection method would be
appropriate during different stages of research.
Discussion Questions
1. Describe different data sources, explaining their usefulness and disadvantages.
Secondary sources of data constitute all available sources from which existing
information can be extracted. This could be published or unpublished information in
the Library, in Government or Company records, in data tapes, on the internet, etc.
Primary sources of data can be any source which provides information elicited directly
for the first time. This could be organizations, individuals, trash cans, or whatever
source from which the desired information can be obtained.
Secondary data sources are useful because they offer a base on which to build
further research without having to reinvent the wheel. Past findings can spur new
research; past data can also offer opportunities to analyze them from a different
perspective or angle. Under certain circumstances, however, secondary data might be
misleading if one does not take the changed circumstances into consideration. For
example, if old archives of national data are utilized to examine and draw conclusions
about gender differences at the workplace, this might become an exercise in futility.
The workplace has changed much now compared to 20 years ago – there are more
educated career women, their aspirations are different, their current expectations of
life are in contrast to what they were two decades ago, etc. As such, one has to be
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cautious while using secondary data sources.
Primary data will offer more correct and up‐to‐date information when phenomena
are investigated. However, it costs more to collect fresh data, access to organizations
is not always readily obtained, and people knowledgeable in research have to be co‐
opted. Generally, data collected through unobtrusive methods are more reliable than
data gathered through surveys.
2. As a manager, you have invited a research team to come in, study, and offer
suggestions on how to improve the performance of your staff. What steps would
you take to allay their apprehensions even before the research team sets foot in
your department?
As the manager, I would inform the employees of the Department, in a meeting
called for the purpose, that unless we can turn around and make some profits, the
organization may have to lay off people. Since management does not see laying off
personnel as an acceptable solution, at least at this stage, we are inviting outside
experts to examine our operations and give us some ideas on how we may be able to
increase our profits. If we all cooperate with the research team that will be coming in
shortly, and provide them with whatever information they might need, it would help
the company to implement the steps and processes necessary to increase output,
make a profit, and retain the current employees.
3. What is bias and how can it be reduced while interviewing?
Bias is any error that creeps into the information gathered. Biases occur whenever
incorrect information is provided to the researcher by whoever offers the information.
Sometimes, genuine mistakes might be made and hence incorrect information could
be provided. However, biases frequently occur because the researcher phrases the
question in a particular way, inflects the voice in a particular manner, or simply
because the respondent, zealous of pleasing the researcher, provides an answer that
the individual believes is what the researcher would like to hear, even though it is not
factual.
Bias can be reduced in interviewing by choosing the appropriate environment in
which the interview is conducted, by establishing trust with the respondent, by
phrasing questions so that they do not lead the interviewee to respond in a particular
manner, by clarifying issues when the respondent seems confused, by not coming
across as evaluative or judgmental, and by not placing special emphasis on specific
words.
4. Explain the principles of wording, stating how these are important in questionnaire
design, citing examples not in the book.
a. The wording of the question and the level of sophistication of the language used are
important. These are important because, if the respondent does not understand the
words, obviously, he or she is not going to be able to respond to the questions. An
underground coal miner and a top business executive may need to be asked some of
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the same issues differently. Thus, using words that fit the level of sophistication of
understanding of the respondent is necessary. To take an extreme example, to assess
the experienced quality of family life, a poorly educated farm hand may be first asked
to list the activities he normally engages in when he gets home from work, and then
asked to rate the extent of satisfaction gained from each of these activities. An index
of quality of family life might then be calculated by examining the family‐related
activities listed by the respondent. With a business executive, on the other hand, the
same concept can be tapped by asking the individual to rate his or her satisfaction to
questions such as: Balance between work and family life; the impact of travelling on
experiencing quality time with the family, and the like.
b. Both positively and negatively worded questions need to be asked in the
questionnaire so that the respondent does not mechanically answer the items without
much mental engagement. For example, if one question asks for the level of
excitement that a particular advertisement evoked, another could ask the extent to
which that same advertisement seemed irrelevant. Obviously, when both are tapped
on the same scale, the response to both cannot be the same. This break in the way the
questions are worded, both positively and negatively, helps to enhance the attention
span of the respondents who might otherwise respond mechanically.
c. Double‐barreled questions should be avoided. If one asks the question, “Do you value
and manage a diverse workforce well”? there may be no clear response given to the
question because one may value a diverse workforce, but hardly know how to manage
it! In such cases, it would be better to ask two separate questions rather than one.
d. Ambiguous questions should also be avoided. Questions such as “Do you discuss your
work with the president regularly”? or “Do you go to the movies frequently”? are
ambiguous, because the terms regularly and frequently are left open to the
interpretation of each respondent. One individual might discuss work with the
president on a daily basis, and another every six months. Both are “regularly” (or at
regular intervals) discussing work! But is this what the researcher is looking for?
Similarly, frequently going to the movies might mean one movie every week to one
person, one movie every month to another, and three times a week to a third person!
Since these terms are not defined, biased data will be procured from the respondents.
e. Recall‐dependent questions will also introduce biases. For example, not many people
remember when exactly they started smoking, or why they quit a particular school
and joined another when they were 10 years old.
f. Leading questions also result in biased responses because the interviewee might be
led to believe that a particular type of answer is sought and might try to oblige the
interviewer, even if the response is not what the individual believes to be true. An
example of a leading question is: Don’t you think that more women should be
promoted to decision‐making line positions in organizations? Such a question is likely
to elicit the obvious response, “Surely, Yes”!
g. Loaded questions should also be avoided because of the emotionality it invokes, thus
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eliciting biased responses. As an example: “Don’t you think that the L.A.P.D. is biased
against blacks?” is a question with racial overtones which will bring forth emotional,
rather than objective responses to the question.
h. Questions invoking social desirability will also produce biased responses. An example
would be to ask if anyone felt that workforce diversity is bad for the system. In the
context of the changing demographics of the workforce, even if some felt that
diversity at the workplace is disastrous, they would tend not to disagree because it is
not a socially acceptable response.
i. It is also important to avoid lengthy questions which might confuse the respondent
and introduce several types of bias. An example of a long question is: To what extent
would asking for responses from different groups of employees, such as for instance,
production, marketing, R & D, advertising, and sales, on such issues as the policy
governing the organization, the organizational culture, staff discipline and other
related matters, provide valid data to the president, to enable him to make some
critical decisions on how to run the company effectively and efficiently?
5. What are projective techniques and how can they be profitably used?
Projective techniques help the respondent to offer answers to questions which
might otherwise be rather difficult or cumbersome to respond to. Projective methods
which include such techniques as word association, sentence completion, thematic
apperception, and ink‐blot tests, usually tap the deep‐seated motivations of the
respondent and provide relevant answers to difficult questions. However, the
responses have to be analyzed by individuals well trained in interpreting the answers if
they are to be meaningfully utilized for research purposes. Marketing research can
benefit substantially by using projective techniques, as for example, in developing
products, designing ads, and selecting appropriate media.
6. How are multiple methods of data collection from multiple sources related to
reliability and validity of the measures?
If there is convergence or strong correlation among the data obtained from
different data collection methods on the same variable, then one can establish
convergent validity because the data converge even when collected by different
methods. The same holds true when there is a strong and significant correlation
between the data obtained on the same variable from different sources. Though
reliability cannot be directly assessed from multi‐methods or multi‐sources of data
collection, usually, since a valid instrument is reliable (though the converse may not
necessarily be true), one can presume reliability if validity is established through the
multi‐trait, multi‐matrix method.
7. Every data collection method has its own built‐in biases. Therefore, resorting to
multi‐methods of data collection is only going to compound the biases. Critique this
statement.
It is true that most data collection methods in the social sciences have their own
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built‐in biases. For instance, interviews are susceptible to interviewer and respondent
biases, observational data will have observer and actor biases, and so on. But when
data are collected through multiple methods and compared, if the correlations among
the several types of responses received through the different data collection methods
are high, we can be fairly confident that the data have good validity and reliability –
i.e. they are “good.” If the correlations are low, however, we would start wondering
about the goodness of our data. We would then pay closer attention to the methods
used. For instance, if respondents say that they experience a high level of
meaningfulness in their jobs when they are interviewed, and when the concept is
measured through several items in the questionnaire, we would be inclined to treat
these as acceptable data even though both may have a low correlation to data
obtained from a sentence completion motivational research. If, however, there is no
correlation at all among any of the methods, the goodness of the data collected will be
highly suspect.
Thus, multi‐methods of data collection help us to make certain judgments about
the goodness of our data and serves to make decisions on which sets of data may
perhaps be more acceptable than others.
8. One way to deal with discrepancies found in the data obtained from multiple sources
is to average the figures and take the mean as the value on the variable. What is
your reaction to this?
Wherever possible “objective” data, through unobtrusive methods, need to be
obtained. For instance, if an employee’s performance is to be measured, it is better to
go through the person’s records and evaluation forms of the superiors (in case more
objective measures of output are not available). However, such records are usually
confidential in nature and are not likely to be made accessible to the researcher.
Hence data will be sought from multiple sources–for example, from the subject, the
co‐workers, the immediate supervisor, other superiors, and perhaps even the
subordinates. If there is not much consistency in the data obtained through these
various sources, there is no option left but to average these. However, the researcher
should point out the biases inherent in this and acknowledge this limitation in the
report.
9. How has the advancement of technology helped data gathering?
Hand‐held computers used in field interviews are very useful for collecting and
recording information from many individuals. The recorded information can be
checked for accuracy the same day.
Electronic surveys by way of interviews or questionnaires, have the advantage of
self correction in data, in the sense that out of range responses etc., are automatically
corrected on the spot, and skip patterns can be conveniently applied (e.g. if answer is
‘No’ to question # 5, proceed to question # 19).
The only drawback is that people might ignore and not respond to electronic
surveys, and some may not have the requisite facilities.
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10. How will you use the data from observational study to reach scientific conclusions?
Observational studies have been profitably used for providing descriptive
information. However, by categorizing the responses in a meaningful way, and also
developing ordinal or Likert‐type scales therefrom, (e.g. High Frequency to Low
Frequency, etc.), scientific conclusions can be reached applying parametric or non‐
parametric statistics, as appropriate.
11. The fewer the biases in measurement and in the data collection procedures, the
more scientific the research. Comment on this statement.
This observation is correct. When reliable and valid measures are used to tap
concepts, and when the data collection methods have less built‐in biases, we would
have good data, provided that, of course, the sample is representative. Thus,
replicability, accuracy and precision, and generalizability, become possible. The
research then becomes more scientific.
Exercises
Exercise 8.1
A production manager wants to assess the reactions of the blue‐collar
workers in his department (including foremen) to the introduction of computer‐
integrated manufacturing (CIM) systems. He is particularly interested to know how
they would perceive the effects of CIM on:
a. their future jobs
b. additional training that they will have to receive
c. future job advancement.
Design a questionnaire for the production manager.
Questionnaire
Cria Software Enterprises
4571 Southwood Ave
Cupertino, California 94024
Date
Dear Employee,
As we had discussed in our meetings, Computer Integrated Manufacturing
(CIM) will form a part of our operations in the future. We would like to know how you
visualize certain aspects of the future environment as we introduce the changes.
Please take a few minutes to complete this short questionnaire and return it to the
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locked box with the slit on the top, in the front office. Thank you for responding within
the next five days.
sd
George Coelho
Production Manager
1. Personal Information (place a mark on the appropriate box)
JOB STATUS
□
□
□
□
□
□
□
Machinist
Fitter
Loader
Inspector
Foreman
Surveyor
Other
NUMBER OF YEARS WORKED IN THE
DEPARTMENT
□ Less than 1
□ 1‐3
□ 3‐5
□ 5‐10
□ Over 10 years
SHIFT CURRENTLY
WORKING IN
□ Day
□ Evening
□ Night
2. Your Opinions regarding the following.
Please circle the appropriate number for each of the following items using the
scale below.
STRONGLY AGREE 1
AGREE 2
DISAGREE 4 STRONGLY
DISAGREE 5
1
NEITHER
AGREE NOR
DISAGREE 3
2
1. I will need additional training to
work in the changed environment.
2. The new system will offer me
better opportunities for
advancement.
3. The opportunities for training will
have to be enhanced with CIM.
4. I am not sure if CIM will need all
the people we now have in this
department.
5. I feel that most of us may not have
better opportunities for future
promotions in the new manufacturing
environment.
6. Most of us will need special
training to work with CIM.
7. I am sure the future looks bright for
most of us here.
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
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Items 4 and 7 measure opinion about their future jobs
1, 3, and 6 measure perceived training needs
2 and 5 measure job advancement
Exercise 8.2
Answers may vary.
Exercise 8.3
Answers may vary.
Exercise 8.4
Answers may vary. The questionnaire should include valid and reliable scales measuring service quality,
customer satisfaction, and customer loyalty.
Exercise 8.5
Design an interview schedule to assess the Intellectual capital, as perceived
by employees, in an organization after identifying the dimensions and elements.
The dimensions of intellectual capital would primarily comprise, among other
things, the following:
The knowledge‐base of the employees;
Their know‐how
The patents owned by the organization;
The secret formulas utilized by the company (special formulas / manufacturing
process, and the like).
The extent to which the company has an edge over others, in terms of specialized
knowledge and skills.
The Unstructured Interview Schedule would basically ask for the employees’
ideas as to what the term means and what they consider are the essentials of
intellectual capital.
The Structured Interview Schedule will be on the following lines:
1. Department:
2. Nature of job:
3. Age:
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4. Designation:
5. To what extent do you think your organization depends on the knowledge of
operations of workers for its success?
6. To what extent do you think the success of this organization is due to the specialized
knowledge and skills possessed by employees?
7. Should some of the employees leave this organization, how difficult will it be to recruit
others with the same or similar knowledge?
8. To what extent is the know‐how relating to certain operations confined to particular
individuals who alone know how to do their job?
9. How many patents have been owned by your company in the last 5 years?
10. To what extent would you say your company has far more valuable patents than your
competitors in the industry?
Additional Exercises in Questionnaire Design
Two simple exercises on Questionnaire Design follow, and these can be used
for class discussion after the students have individually worked on them as homework
assignments. Different students can then be asked to write on the chalk board
different parts of the questionnaire – for example, the introduction, instructions to
respondents, measures for different concepts with scaling, and the end part of the
questionnaire. The class as a whole can then critique the exercise on the board. See
also Exercises 10.1 to 10.5 in the Book. These can also be used for class discussions
including discussions on possible ways of establishing reliability and validity for the
measures.
1. The Marketing Director of a pharmaceutical company wants to examine the
effects of number of sales personnel, population density, the average sales calls made
to the doctors in the region, and the average monthly sales calls made on the chemists
in the region, on the sales of the pharmaceutical products of the company. She has six
particular regions in mind. Design a questionnaire to do the study. Also discuss what
sources of data you will gather information from.
Population density can be obtained directly from the Census Bureau’s
Directory. All the other information should be readily available from the Regional Sales
Headquarter Records, or from the local offices. If necessary, a simple questionnaire
asking direct questions of the Regional Director to tap the variables could be used.
2. An R&D Project Manager wants to elicit the reactions of the machine
operators in the Production Department to three different types of machines currently
in use – Type A, Type B, and Type C. If he knows how the machinists experience these
three types in terms of ease of handling, sturdiness, flexibility for different adaptations,
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and maintenance, he would be able to decide whether or not to develop a new
prototype he has in mind. Design a questionnaire for the purpose.
This is also a relatively simple questionnaire that will be administered to the
machinists, asking for their views on the three types of machines, aiming the
questions to particular aspects of ease of handling, sturdiness, flexibility for different
adaptations, and maintenance.
Next to Chapter 3, this Chapter is perhaps the one which would demand more
in‐class exercises and discussions to ensure that students have understood and can
incorporate the learnings into their research project work. When the group puts
together a draft of the questionnaire for administering it to the organization when
they do their class project, the instructor can play a key role in offering constructive
criticisms and suggestions, and all in all, help students to understand how to design
reasonably good questionnaires.
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CHAPTER 9
EXPERIMENTAL DESIGNS
Instructional Goals
1. To offer students knowledge about what experimental designs are, and why, how, and
when they are used.
2. To pinpoint the differences among causation, co‐variation, and mutual causation, with
examples, as the one below.
Causation refers to one variable A, causing another variable B, to occur or to
change. As an example, the pollution of the burning oil wells in Kuwait caused a lot of
breathing difficulties for the Kuwaiti children.
Co‐variation refers to one variable A changing, as another variable B, also changes.
For example, when the winds blow lightly toward the city, the Kuwaiti children’s
breathing difficulties are very low, but as the velocity of the wind increases (carrying
with it increased spread of pollution), the breathing difficulties also increase. In other
words, the velocity of wind and breathing difficulties vary together or co‐vary.
Mutual causation occurs when variable A causes variable B to change, and variable
B, in turn, also causes variable A to change. For example, a high level of confidence is
instrumental in achieving success, and success (experiences), in turn, is instrumental in
enhancing individuals’ confidence level. The two mutually reinforce each other and
the increase in one is instrumental in increasing the other.
3. To explain the terms manipulation, control, matching, and randomization with several
examples.
4. To clarify the concepts of internal and external validity, the threats to each, and the
trade‐off between internal and external validity. Students should know that it is
possible to ensure both types of validity by doing a lab experiment first and a field
experiment next, should circumstances warrant this.
5. To familiarize students with some of the more commonly used experimental designs
to trace cause and effect relationships, and the types of factors that would undermine
or enhance internal validity in each of these designs.
6. To sensitize students to the ethical dilemmas, particularly as they relate to
experimental designs.
7. To introduce to the more advanced students, other experimental designs as discussed
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in the Appendix to the book chapter.
Discussion Questions
1. What are the differences between causal and correlational studies?
Correlational studies are always conducted in the environment in which the events
studied naturally occur, and there is very little researcher interference with the
setting. In causal studies, however, there is much greater researcher influence, and lab
experiments are always conducted in artificially created settings. All causal studies are
longitudinal in nature, whereas most correlational studies are one‐shot studies.
2. In what ways do Lab experiments differ from Field experiments?
Lab experiments are always conducted in contrived settings, whereas, field
experiments are always conducted in the natural environment where the flow of
events normally occur. Lab experiments are tightly controlled by either matching or
randomly assigning members to the various groups. In field experiments, however,
tight controls are not possible because people or events preexist and cannot be
altered. Lab experiments offer greater internal validity but lower external validity,
whereas field experiments offer more external validity and lesser internal validity.
3. Define the terms control and manipulation. Describe a possible Lab experiment
where you would need to control a variable. Further, include a possible variable,
over which you would have no control, that could affect your experiment.
Manipulation refers to deliberate variations in the independent variable to test its
effect on the dependent variable. Control refers to the efforts made to mitigate the
contaminating effects of nuisance factors that might affect the internal validity of the
experiment.
A Possible Lab Experiment with controllable and uncontrollable factors.
A pharmaceutical company wants to test the effects of incremental doses of AZT
administered to AIDS patients, isolating them in a special hospital‐type environment.
A possible factor to control, might be the age of the patient, since older people
might react slower to certain chemicals. This nuisance factor can be controlled either
by matching all three groups for age or by randomly assigning the members to the
three groups. A possible uncontrollable factor could be a sudden flu epidemic which
might kill many of these patients and make the testing of the effects of incremental
doses of AZT impossible.
4. Explain the possible ways in which you can control “nuisance” variables.
Nuisance variables, if known, can be controlled by matching the members in all the
groups for the contaminating (or nuisance) factors. For example, if subjects’ level of
experience would be a contaminating factor for a particular experiment, members of
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all groups could be so matched that, overall, all groups have members with the same
experience level. An even better way of controlling for all possible nuisance factors is
to assign the members randomly to the various groups. By doing this, all known and
unknown contaminating factors will have a high probability of being equally
distributed among all the groups. Thus, randomization is an effective way to control
for known and unknown nuisance factors.
5. What is internal validity and what are the threats to internal validity?
Internal validity refers to the confidence that one can place in the cause and effect
relationship. Internal validity is maximal in a well‐designed lab experiment where the
possible contaminating factors are tightly controlled.
The threats to internal validity are the following possible contaminating factors:
the effects of history, maturation, testing, instrumentation, selection, statistical
regression, and mortality (explained in detail in the book).
6. Explain the concept of “trade‐off” between internal and external validity.
In lab experiments where the nuisance factors that are likely to contaminate the
cause and effect relationships are tightly controlled, one can confidently say, if the
results warrant the statement, that variable A causes variable B. However, because
the contaminating factors are tightly controlled, one cannot be sure that this cause
and effect relationship will be generalizable to (i.e. hold true in) the real‐world
business setting where several contaminating factors do exist. Thus, the
generalizability of the cause and effect relationship found in the lab experiment is
limited.
In the field experiment, on the other hand, where there is a manipulation of the
independent variable but no tight controls, one is not sure that variable A and it alone
causes B (since some other factors might also have an effect on B). However, any
relationship found is likely to be generalizable to other similar business settings
because, many of the possible contaminating factors have not been deliberately and
artificially controlled.
Thus, lab experiments have high internal validity but low external validity or
generalizability, but field experiments have high external validity but low internal
validity. This is the trade‐off between internal and external validity in the lab and field
experiments.
7. Explain how the selection of participants may affect both the internal and
external validity of your experiments.
‘‘Every data collection method has its own built-in biases. Therefore, resorting to
multimethods of data collection is only going to compound the biases.’’
Another threat to both the internal and external validity of our findings is the
selection of participants. First, we will discuss how selection may affect the external
validity of our findings. Then, we will discuss how selection may affect the internal
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validity.
In a lab setting, the types of participants selected for the experiment could be very
different from the types of employees recruited by organizations. For example,
students in a university might be allotted a task that could be manipulated to study
the effects on their performance. The findings from this experiment cannot be
generalized, however, to the real world of work, where the employees and the nature
of the jobs would both be quite different. Thus, subject selection would pose a threat
to external validity.
The threat to internal validity could come from improper or unmatched selection of
subjects for the experimental and control groups. For example, if a lab experiment is
set up to assess the impact of working environment on employees’ attitudes toward
work, and if one of the experimental conditions is to have a group of subjects work for
about 2 hours in a room with some mild stench, an ethical researcher might disclose
this condition to prospective subjects, who may decline participation in the study.
However, some volunteers might be lured through incentives (say a payment of $70
for the 2 hours of participation in the study). The volunteers so selected may be quite
different from the others (inasmuch as they may come from an environment of
deprivation) and their responses to the treatment might be quite different. Such bias
in the selection of the
subjects might contaminate the cause‐and‐effect
relationships and pose a threat to internal validity as well. Hence, newcomers,
volunteers, and others who cannot be matched with the control groups would pose a
threat to internal validity in certain types of experiments. For this reason,
randomization or matching groups is highly recommended.
8. Explain the difference between main and interactive testing effects. Why is this
difference important?
Frequently, to test the effects of a treatment, subjects are given what is called a pre‐
test. That is, first a measure of the dependent variable is taken (the pre‐test), then the
treatment is given, and after that a second measure of the dependent variable is taken
(the post‐test). The difference between the post‐test and the pre‐test scores is then
attributed to the treatment. However, exposure of participants to the pre‐test may
affect both the
internal and external validity of the findings. Indeed, the afore‐
mentioned process may lead to two types of testing effects.
A main testing effect occurs when the prior observation (the pre‐test) affects the
later observation (the post‐test). Main testing effects typically occur because
participants want to be consistent. Let us assume that we have tested the effect of a
television commercial (the treatment) on attitudes towards the brand using a pre‐test
and a post‐test. Suppose that no significant difference in attitude towards the brand
was found. This finding could lead to the conclusion that the commercial was
ineffective. However, an alternative explanation is that our participants tried to be
consistent and answered the later questions so that their answers were similar to the
answers they gave the first time. The pre‐test may thus have affected the results of
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the experiment. Along these lines, main testing effects are another threat to internal
validity.
Interactive testing effects occur when the pre‐test affects the participant’s reaction
to the treatment (the independent variable). Again, let’s assume that we are testing
the effect of a television commercial on attitude towards the brand using a pre‐test
and a post‐test. It is possible that because of the pre‐test the participants watch the
television commercial more closely than consumers that do not take part in the
experiment. For this reason, any effects that are found may not necessarily be
generalizable to the population. Hence, interactive treatment effects are a threat to
the external validity of an experiment.
In sum, testing effects may affect both the internal and external validity of our
findings. The difference between main and interactive testing effects is important
because main testing effects threaten the internal validity, whereas interactive testing
effects threaten the external validity of an experiment.
9. History is a key problem in a time series design. “Other problems are main and
interactive testing effects, mortality, and maturation.” Explain.
A main testing effect occurs when the prior observation affects the later observation.
Main testing effects typically occur because participants want to be consistent.
Interactive testing effects occur when the prior observations affect the participant’s
reaction to the treatment (the independent variable).
Maturation: Cause‐and‐effect inferences can also be contaminated by the effects of
the passage of time ‐ another uncontrollable variable. Such contamination is called
maturation effects. The maturation effects are a function of the processes ‐ both
biological and psychological ‐ operating within the respondents as a result of the
passage of time. Examples of maturation processes could include growing older,
getting tired, feeling hungry, and getting bored.
Mortality (the dropout of individuals from groups) is a problem for all experimental
designs, including this one.
10. Explain why mortality remains a problem even when a Solomon four‐group
design is used.
Solomon Four‐Group Design: One experimental group and one control group can be
given both the pre‐test and the post‐test. The other two groups will be given only the
post‐test. Here the effects of the treatment can be calculated in several different
ways. To the extent that we come up with almost the same results in each of the
different calculations, we can attribute the effects to the treatment. This increases the
internal validity of the results of the experimental design. This design, known as the
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Solomon four‐group design, is perhaps the most comprehensive and the one with the
least number of problems with internal validity.
However, mortality (the loss of participants during the course of the experiment), is
possible in the pre‐test / post‐test conditions.
11. Explain fully how you would demonstrate to machine operators, and convince them
through research, that thorough knowledge of the operating policies and procedures
(by reading the Manual) will virtually eliminate all “on‐the‐job” accidents.
Let us say we have 20 machine operators in the shop. I will assign them randomly
to two groups, using one as an experimental group and the other as the control group.
For each member in both the groups, I will count the number of on‐the‐job accidents
that they have had in the past six months. I will then expose the experimental group
to the Manual asking them to learn the materials in it thoroughly and test them to
ensure that they have perfect knowledge of the contents. Six months after the
experimental group members have mastered the Manual I will again count the
number of on‐the‐job accidents for each member of the experimental and control
groups. If the mean number of accidents is close to zero for the first group, but
remains unchanged for the control group, it can be established that a thorough
knowledge of the operating policies and procedures causes on‐the‐job accidents to be
virtually eliminated.
12. If a control group is a part of an experimental design, one need not worry about
controlling for other exogenous variables. Discuss this statement.
All groups, including the control group have to be matched for all the exogenous
factors that could contaminate the cause and effect relationships. In other words, the
contaminating factors need to be spread equally among all the groups – both
experimental and control groups – so that the effects of manipulating the
independent variable on the dependent variable can be assessed without any doubt as
to whether other co‐varying factors were responsible for the results found. The
controlled exogenous variables can be distributed among all the groups through either
deliberately matching the groups with respect to these factors, or simply by randomly
assigning members to the groups. Thus, controlling for exogenous variables through a
process of matching, or by randomly assigning members, is a must in good
experimental designs, even when control groups are part of the design.
13. A researcher wants to set up a Lab experiment to test the effects of different kinds
of leadership styles on followers’ attitudes. The three types of leadership style she is
interested in are autocratic, democratic, and participative. You are asked to enlist
some students to play the part of followers. What cover story would you give the
participants?
The cover story could be that participants are being trained to observe the
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dynamics in the situation.
14. Comment on the following statement. Because the external validity of lab
experiments is not usually high, they are useless for investigating cause and effect
relationships in organizations.
Because of the tight controls in lab experiments, even though the internal validity
is high, the external validity, or the generalizability of the cause and effect
relationships becomes limited. However, internal validity cannot be established fully in
field experiments due to lack of control of nuisance variables in such experiments
(since they are conducted in the natural environment of the subjects who pre‐exist in
the situation). Thus, if knowledge of cause and effect relationships is important for a
manager in a business setting, it is better that the theorized causal connections are
first tested through a lab experiment. If a cause and effect relationship is established,
then a field experiment can be conducted in the work setting. Thus, both internal and
external validity can be established.
The usefulness of the lab experiment is that if it does not indicate a causal
relationship, then there is no need to try out a field experiment. The manager would
be better off avoiding unnecessary dislocation and disturbance at the workplace trying
to establish cause and effect relationship where none exists.
The probability of employees getting anxious, distrustful, and suspicious whenever
an experiment is in progress, cannot be underestimated. For these reasons, lab
experiments are extremely useful for organizational researchers to trace causal
relationships in work settings.
15. Co‐variance – that is, two variables varying together either positively or
negatively – and control are integral aspects of experimental designs. Discuss.
To establish a cause and effect relation between two variables X and Y, other
factors that co‐vary with Y, the dependent variable, need to be controlled, so that the
true causal influence of X on Y can be assessed (i.e., the internal validity is
established). Controlling the co‐varying factors can be done through either matching
or randomization. Thus, in experimental designs, co‐variance and control are different
aspects of the same issue – co‐variance confounds internal validity, which is taken
care of by controlling the nuisance variables.
16. The Solomon Four‐Group Design is the answer to all our research questions
pertaining to cause and effect relationships because it guards against all the threats
to internal validity. Comment.
The Solomon Four‐Group Design is probably the best experimental design that
would reduce many of the threats to internal validity. Though the history, maturation,
and testing effects are avoided in this design, and the selection and statistical
regression effects can also be minimized through the process of randomization,
instrumentation effects might still pose a threat to internal validity unless it is carefully
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guarded against (especially in cases where post‐test evaluations are done by different
people, etc.). Mortality effects are also a problem, if the experiment is carried over a
long period of time. Thus, the Solomon Four‐Group Design also faces some threats to
internal validity.
17. Below is an adapted note from Business Week published some time ago. After
reading it, apply what you have learned in this chapter, and design a study after
sketching the theoretical framework.
The Vital Role of Self‐Esteem
Why do some people earn more than others? Economists focused on the importance
of education, basic skills, and work experience ‐ what they called human capital ‐ on
increased productivity, and said these were reflected in greater earning power.
Researchers also found that self‐esteem was instrumental in acquiring human capital.
It would seem that self‐esteem causes the three components of human capital
to emerge and develop. Once developed, human capital would be correlated to
productivity, for which earnings would be a surrogate measure.
The theoretical framework for this can be depicted as per the following
diagram:
This study can be done in two ways. One, as a correlational field study,
obtaining data on each of the five variables above, and doing a path analysis. This will
trace the cause and effect relationship between self‐esteem and human capital, and
between human capital and earnings (productivity). This is the easiest way to trace the
causal connection between self‐esteem and human capital. A second way to conduct
the study is to first see if the three components of human capital are indeed
correlated to earnings from which an index of human capital can then be developed
based on the predictive power of each of the three variables.
A Lab study can then be conducted recruiting College students to perform a
task. An index of human capital (HC) would be first developed by giving appropriate
weighting to the three factors of education, skills, and work experience.
The causal effects of self‐esteem on human capital can be tested by randomly
assigning individuals to four groups and manipulating the self‐esteem of individuals.
This can be done by praising the intelligence of one group and telling them that the
task at hand would be child’s play for them; telling the second group, that they may
have some, but not all the necessary talent to do the task at hand well; telling the
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third group that they may not have what it takes to accomplish the task at hand; and
saying nothing to the fourth group.
A pre‐test (before manipulating self‐esteem) of the components of HC can be
obtained from all groups. The task to be done can then be explained to all four groups,
and just before the task is given, all the subjects can be asked to respond to a short
questionnaire eliciting how prepared they feel for the task in terms of their
background education, skills, and previous work experience to accomplish the task. If
the differences are found in HC among the groups, then a causal relationship can be
established. In other words, if the HC is felt to be the greatest in Group 1, a little less in
group 2, worse than before in group 3, with no change in group 4, then the causal
connection can be determined.
As a matter of interest, a similar questionnaire can be administered a third time
after the task is completed, to see if there are changes in the reported HC.
In the plant where the efficacy of the processes is desired to be tested, the two
types of machines can be leased for about six months. Then three comparable
production groups can be formed, the first two to test the efficacy of the two different
machines, and the third as a control group.
The productivity of all three groups can be measured before the introduction of
the new machines and six months after the machines are installed. It is expected that
the productivity of the two experimental groups would be more than that of the
control group. If so, the group with more productivity can be attributed to the
machine used by it.
To ensure that this is correct, a similar field experiment can also be set up at
another plant to see if similar results emerge.
18. Design a study to examine the following situation.
An organization would like to introduce one of two types of new manufacturing processes to
increase the productivity of workers, and both involve heavy investment in expensive technology. The
company wants to test the efficacy of each process in one of its small plants.
Answers will vary.
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CHAPTER 10
SAMPLING
Instructional Goals
1. To impress upon the students that the hallmarks of science discussed at the beginning
of the course, i.e. generalizability, replicability, and precision and confidence are
mainly ensured by the sampling design chosen, including the sample size.
2. To explain how the probability sampling designs are representative of the population.
3. To highlight the advantages and the drawbacks of different types of probability
sampling designs.
4. To make students realize that probability sampling designs are not always feasible, and
sometimes non‐probability sampling designs are the only viable alternative available.
5. To elucidate that either too large or too small a sample size could be detrimental for
drawing meaningful and valid conclusions.
6. To explain the notions of efficiency in sampling and the trade‐off between precision
and confidence.
7. To clarify the choice points in sampling design shown in Figure 11.3 in the textbook
and provided in Powerpoint.
8. To introduce the need for identifying and articulating the sample characteristics in
terms of gender, age, job level, tenure, etc., for purposes of replicability, and for
comparing the results of different research studies.
Note: The above aspect in item 8 is brought out later in the book, but is worth stating
now.
However, sensitizing students about sample characteristics at this stage will help them
to understand why a good description of sample characteristics is important and why
they should pay attention to it in their final report.
In‐Class Exercises on Sampling Designs
What kinds of sampling designs would be used for the following?:
a. A study to get a quick idea of the medical acceptability of a new aspirin substitute
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which cannot be dispensed over the counter without prescription.
b. A study involving a sample of 325 students in a university where 2,000 students are
enrolled.
c. An investigation of the career salience of professionals in the fields of medicine,
engineering, business, and law.
d. The generalizability of the attitudes of blue collar workers from a sample of 184, to the
total population of 350 blue collar workers in the entire factory of a particular
company.
Answers
a. Purposive Judgment Sampling.
b. A Systematic sampling design (using university listing of students).
c. A Stratified Random sampling with stratification along profession, gender, age, etc.
d. Simple random sampling because of the importance attached to high generalizability.
Estimation of Population Characteristics from Sample Characteristics
The book works out a problem on the estimations of the population
characteristics from the sample characteristics for different levels of precision and
confidence. Another example that can be used in class is provided below.
Problem
1(a).You want to estimate the production days that would be lost during the
next three months by sampling the vacation intentions of a few employees. You
randomly select 36 employees in the organization and find that the average number of
days they intend taking off is 16 during the coming three Summer months, with a
standard deviation of seven (7) days. Based on these sample statistics, you want to
estimate at a 99 percent confidence level, the days that will be lost due to the entire
population of workers taking vacation time during the next three months, so that the
plant manager knows how much temporary help he should plan on hiring during the
summer months in order for work to proceed smoothly.
Calculation
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μ  X  zSx
S x  S / n  7 / 6  1.167
μ  16   2.576 1.167 
 16  3.01
 12.99 to19.01
If there are 100 employees in the organization expected to take vacation during
Summer, then the most optimistic estimation of the days lost through vacation time
during the summer would be (13  100 =) 1,300 days and the most pessimistic would
be (19  100 =) 1,900 days. This would mean that temporary help would be needed
anywhere between 1,300 and 1,900 days worth of labor, for production to proceed
smoothly.
1(b). Now you might want to narrow the gap in the estimation since 1,300 and
1,900 days is a wide range, and you would like more precision using the same
information that is available to you. Well, it can be done only at the cost of taking
more chances that your estimation, though more precise, may not be stated as
confidently as before. You may, however, decide to lower your confidence level to
gain more precision in your estimation. At the 95 percent confidence level, the most
pessimistic and the most optimistic estimations would range from 1372 to 1828, a
narrower range – we are now gaining more precision, i.e., narrowing confidence
interval – but only at the risk of being wrong five percent (as opposed to one percent)
of the time. We could seek a further narrower interval range at the 90 percent
confidence level (1408 to 1792), if taking a higher risk in being wrong in the estimation
is not going to be disastrous. You as a manager will have to decide on the amount of
risk you want to take by increasing or decreasing the confidence level.
Estimating Sample Size
Estimating the sample size for given levels of required accuracy and precision is
discussed in the book with examples. Further problems can be given to students in
class. A sample problem given to them could be as follows.
Problem
How large a sample do you need if you want to estimate the mean age of a
population of 100 residents and be within 3 years of the true mean with a 95 percent
level of confidence, when you know that the sample mean is 28 years and the
standard deviation is 17 years?
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Solution
Sx  3/1.96  1.53
Sx  s / n
1.53  17 / n
1.53  n  17
n  17 /1.53
n  123
Discussion Questions
1. Identify the relevant population for the following research foci, and suggest the
appropriate sampling design to investigate the issues, explaining why they are
appropriate. Wherever necessary, identify the population frame as well.
a). A company wants to investigate the initial reactions of
drink users to a new “all natural” soft‐
drink.
heavy soft‐
“Initial reactions” non‐probability sampling.
Heavy soft‐drink users: purposive sampling.
b). A gun manufacturing firm would like to know the types of guns possessed by various
age groups in Washington, D. C.
When guns are sold, the dealers are expected to maintain records of the names
and ages of the buyers, and the types of guns sold. Thus, the population frame for gun
owners can be had from the records of gun dealers in the Washington, D.C. area. Once
a complete list is compiled, a stratified random sampling of appropriate age groups
can be done, and the relevant information obtained.
c). A hospital administrator wants to examine if single parents working in the hospital
have a higher rate of absenteeism than parents who are not single.
The marital status and parental status of the employees may be available from the
records of the hospital. If so, the population frame would be the hospital records from
which the information can be directly extracted. A stratified random sampling design
can be used and a t‐test done to examine if there are differences in absenteeism in the
two groups. If the marital or parental status of the employees is not available, then a
convenience sample of those who are known to be single parents and those who are
known to be not single parents can be used to check their records for absenteeism.
d). A researcher would like to assess the extent of pilferage in materials from storage
warehouses of manufacturing firms in the East coast.
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First, the researcher will have to randomly select some big, medium‐size, and small
cities in the East coast – say, two of each. Thereafter, three warehouses from each of
the large, medium, and small size cities will be randomly selected. This then will form
the sample for study. The pilferage rates can then be assessed by checking the records
of original supplies to the warehouses, the amount of stock sold, and the balance at
hand.
e). The Director of Human Resources wants to investigate the relationship between drug
abuse and dysfunctional behaviors of blue collar workers in a particular plant.
Identifying drug abusers is very difficult, unless there is a mandatory drug test
administered. Also, what is meant by ‘dysfunctional behaviors’ has to be clearly
defined. If a list of drug abusers is available through drug tests then, depending on the
numbers, either all of them (if the number is small), or a random sample among them
(if the number is large) can be observed for any dysfunctional behaviors and
compared with the behaviors of a random sample of those who are not drug abusers.
f). A marketer wants to generate some ideas on how
women differ from men in acquiring product knowledge
about cars.
Some ideas = non‐probability sampling
Women versus men = quota sampling.
2a). Explain why cluster sampling is a probability sampling design.
b). What are the advantages and disadvantages of cluster sampling?
c). Describe a situation where you would consider the use of cluster sampling.
a. Cluster sampling is a probability sampling design since each cluster has a known
chance of being selected as the sample.
b. Cluster samples offer ease of data collection within a relatively short time frame.
However, being homogenous, they do not offer the advantage of efficiency in
sampling.
c. Cluster sampling could be used to assess the types of films (comedies, fighting,
violence, social dramas, adventure, etc.,) that are most popularly rented by theater
owners. Different theater complexes, each of which might have anywhere from four
to eight different films being shown at any given time, could be treated as clusters.
More homogeneity within clusters, and heterogeneity between clusters can also be
expected since different complexes might be catering to different types of clientele. As
such, cluster sampling would be ideally suited for this purpose.
3a). Explain what precision and confidence are and how they would influence sample
size.
Precision indicates how close the sample statistics are to the population
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parameters. Usually, a bigger sample size offers greater precision than a smaller one,
especially when the population is heterogeneous in the characteristics of interest to
the study. Confidence indicates the percentage of times when our projected statistics
will be truly reflecting the population parameters. This, again, is a function of the
sample size – a bigger sample size will allow for a projection to be made at a higher
level of confidence. But, for any given sample size, we cannot increase both precision
and confidence simultaneously.
3b). Discuss what is meant by the statement: There is a trade‐ off between precision
and confidence under certain conditions.
There is a trade‐off between precision and confidence as a function of sample size.
For any given sample size, if the precision has to be increased, then the level of
confidence will go down. On the other hand, if one needs more confidence, then the
precision will have to go down. In other words, for any given sample size, either the
precision or the confidence, but not both, can be increased. As a matter of fact, either
can be increased only at the expense of the other.
4. The use of a convenience sample in organizational research is correct because all
members share the same organizational stimuli and go through almost the same
kinds of experiences in their organizational life. Comment.
It is not correct to say that all organizational members share the same kinds of
experiences because different supervisors, different departments, and different work
environments offer different kinds of stimuli to organizational members. Hence,
selecting a few members based on convenience sampling and generalizing the results
to the total population would not be advisable. Even among the same group of people
exposed to the same kinds of stimuli, perceptions will vary due to individual
differences in selective perception and interpretation. Hence, a probability sampling
design, rather than a convenience sample would be more appropriate to project the
properties of the sample on to the population.
5. Use of a sample of 5,000 is not necessarily better than having a sample of 500. How
would you react to this statement?
Not only is a sample of 5,000 not necessarily better, but it could also be
detrimental, since the probability of rejecting the null hypothesis becomes too large –
i.e., every trivial difference becomes significant. We could compare this to using an
electron microscope to examine the differences between two atoms. The differences
will be enormously magnified if we use the “power” of the electron microscope when,
actually, the difference between two atoms is negligible. In fact, statistical tables are
available which specify the appropriate sample size for desired levels of confidence.
Too big a sample size is likely to lead to erroneous conclusions, since with larger
sample sizes, even small correlations reach statistical significance, and thus, the
probability of our committing Type 1 error is high.
6. Non‐probability sampling designs ought to be preferred to probability sampling
designs in some cases. Explain with an example.
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The above statement is true in cases where the information needed for research
can be obtained only from a select category of people who are not plentiful in
numbers and for whom a population frame does not exist. In such cases, the non‐
probability purposive judgement sampling design is the most useful one. Here, the
most conveniently available members of the limited population of individuals who
have the necessary information are contacted to obtain information. This is the only
meaningful way to get information since a simple random sampling or any other
probability sampling design is impossible without the availability of a relevant
population frame. As an example, information on the effectiveness of AZT (even after
taking into consideration its side‐effects), for cancer patients, can be best obtained
only from those who are suffering from cancer and using AZT.
7. Because there seems to be a trade‐off between accuracy and confidence for any
given sample size, accuracy should always be considered more important than
precision. Explain with reasons, why you would or would not agree with this
statement.
Whether confidence or precision is more important is a decision that each
researcher has to make, based on the goals of the research. In some cases, confidence
may be more important to the research, and in others, precision. For instance, a
salesperson might want to place greater emphasis on the confidence in the projected
number of sales he is likely to make, than wanting to know the exact number of sales
he will make – i.e. he desires greater confidence in the projection than precision. In
other words, he may be willing to accept an error margin of seven percent (rather
than a three percent) so long as he is sure that the chance of being off the mean is no
more than .01 percent! On the other hand, a marksman might insist on more precision
(how close he will hit to the bull’s eye, thus testing his potential abilities to shoot the
target) and not so concerned about the percentage of times he is likely to hit the bulls
eye (the confidence level). He might prefer precision, because if he knows he has the
abilities, he can practice more and improve the probability of his chances for success.
These examples illustrate the trade‐off between accuracy and precision. The decision
whether accuracy or confidence is more important has to be made by the researcher
for good reasons, and one may not always necessarily be preferred over the other.
8. Over‐generalizations give rise to a lot of confusion and other problems for
researchers who try to replicate the findings. Explain what is meant by this.
A careful description of the sample characteristics is necessary to enable the
reader to judge the extent to which the conclusions drawn from the research findings
are generalizable. If the sample is not adequately described and sweeping
generalizations are made, then the researchers who try to replicate the findings will
run into difficulties, since the findings of the previous study may not be replicated,
simply because what is relevant to one population may not be so for another. The
conflicting findings would cause confusion and researchers will not know whether the
discrepancies are due to faulty theories or methodological problems. It is for this
reason that research reports should carefully describe the population and the sample
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characteristics.
9. Double sampling is probably the least used of all sampling designs in organizational
research. Do you agree? Provide reasons for your answer.
Double sampling is probably used more in the exploratory stages of research
where data are collected several times from subsets of a sample – e.g., a subset of
those who were interviewed with unstructured questions are again interviewed with
structured questions in order to obtain more specific and focused information on
phenomena that may not be well‐understood. For instance, double sampling is not
uncommon in cross‐cultural research, in research on dual career families, and the like.
While quantitative data through questionnaires are essential, for more in‐depth
probing of certain phenomena, structured interviews are sometimes conducted with a
subset of the sample from which questionnaire responses have been obtained.
10. Why do you think the sampling design should feature in a research proposal?
Details of the sampling design, giving details of how many and what cadres of
personnel will be included in the survey, helps the sponsor to see if such people would
be available and could respond to the survey. It also helps determine the extent to
which the findings will be generalizable to the entire organization.
In published studies, it also helps the reader become aware of the settings to
which the findings can be generalized.
Exercises
For the situations below, what would be the relevant population and the
most appropriate sampling design? Make sure you discuss the reasons for your
answers.
Exercise 10.1
The medical inspector desires to estimate the overall average monthly
occupancy rates of the cancer wards in 80 different hospitals which are evenly
located in the Northwestern, Southeastern, Central, and Southern suburbs of New
York City.
All the 80 hospitals in the four parts of New York City form the population from
which the overall occupancy rates are to be established. A simple random sampling
design would be best suited because hospitals of different sizes, and those serving
clientele from different socio‐economic status, would then be included in the survey,
and be most representative of the population.
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Exercise 10.2
A magazine article suggested that “Consumers aged 35 to 44 will soon be the
nation’s biggest spenders, so advertisers must learn how to appeal to this “over‐the‐
thrill crowd”. If this suggestion appeals to an apparel manufacturer what should be
the sampling design to assess the tastes of this group?
The population would, of course, be all those between the ages of 35 and 44.
However, targeting this population would be difficult since a population frame would
not be available (excepting with the Bureau of Census). A good way to obtain access to
a portion of this population could be through retail store outlets like J.C. Penney, Ross,
or Mervyns. If their cooperation can be obtained to generate a list of this age group
through their credit card information (which might have customers’ date of birth on
them), then a random sample or a systematic sample of this population can be used to
administer a mail survey. The responses obtained from consumers from a variety of
cities can then be used to formulate an idea of what the tastes of the target group are.
Exercise 10.3
The McArthur Co. produces special vacuum cleaners for conveniently cleaning
the inside of cars. About a thousand of these are produced every month with
stamped serial numbers and stored serially in a stock room. Once a month, an
inspector does a quality control check on fifty of these. When he certifies them as to
quality, the units are released from the stock room for sale. The production and
sales managers, however, are not satisfied with the quality control check, since quite
often, many of the units sold are returned by customers because of various types of
defects. What would be the most useful sampling plan to test the fifty units?
A systematic sampling design would be most useful since a probability sampling
design is called for, and also because it would be easy to locate the pieces to be
sampled since they have serial numbers and are stored according to the serial
numbers.
Exercise 10.4
A consultant had administered a questionnaire to some 285 employees using
a simple random sampling procedure. As she looked at the responses, she suspected
that two questions might not have been clear to the respondents. She would like to
know if her suspicion is well founded.
A double sampling design will be used in this case. That is, a sub‐sample of the
original sample can be approached to see whether or not the two questions were
clear to them.
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Exercise 10.5
The Executive board of a relatively small university located in Europe wants to
determine the attitude of their students toward
various aspects of the
university. The university, founded in 1928, is a fully accredited government‐
financed university with 11,000 students. The university specializes in the social
sciences and humanities and has 5 faculties, 6 service departments, 8 research
centers, and 2 graduate schools. The Executive board has asked you to come up with
a sampling plan. Develop a sampling plan and pay attention to the following aspects:
target population, the sampling frame, the sample technique and the sample size.
The population will comprise all the students of the University. A sampling
frame is available; hence probability sampling is a viable option. There are identifiable
subgroups (students of the five different faculties and graduate schools) which may be
expected to have different parameters to the variable of primary interest (attitude).
For that reason you may want to use a stratified sampling design. A minimum sample
size of 30 for each stratum is necessary.
Exercise 10.6
T‐Mobile is a mobile network operator headquartered in Bonn, Germany. The
company has enlisted your help as a consultant to develop and test a model on the
determinants of subscriber churn in the German mobile telephone market. Develop
a sampling plan and pay specific attention to the following aspects.
Define the target population. Discuss, in as much detail as possible, the sampling
frame and the sampling design that you would use. Give reasons for your choice.
Target population: German, T‐mobile, mobile phone subscribers.
Sampling Frame: A database of subscribers on a recent date (for instance 6 months
ago). This database will include both customers who have remained loyal to T‐mobile
and customers who have switched mobile phone providers.
Sampling design: proportionate stratified sampling with loyal customers and
customers who have switched mobile phone providers in proportion to their original
numbers in the population.
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CHAPTER 11
Quantitative Data Analysis
Instructional Goals
1. To make statistics come alive and become meaningful to students through examples
that they can relate to.
2. To get students to analyze data using any of the available PC software programs.
3. To impress on students that the data collected should first be edited, the blank
responses given an appropriate value, and then entered for analysis.
4. To stress the importance of getting a feel for the goodness of data after recoding.
5. To explain how the frequency distribution becomes a tool for explaining sample
characteristics.
6. To connect the application of descriptive statistics such as the means, standard
deviations, and variance to the dependent and independent variables of interest to
any study in order to get an idea of the central tendencies and to obtain a feel for the
data.
7. To make sense out of Pearson Correlations, by interpreting significant correlations,
and to sensitize students to extremely high correlations (over .8) which might cause
concerns regarding the discriminant validity of the measures.
8. To help them interpret the results they obtain from data analyses.
Exercises on Data Interpretation
Practice in the interpretation of the results of data analyses can be
encouraged through the exercises below. These can be done either as in‐class
exercises or given as take‐home assignments.
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Exercise #1 On Frequency Distributions
Below is a tabulation of the demographic data from the Frequency distribution
of a survey done by Ms. Sandra Jones. Her sample consisted of 148 of a total of 3,700
clerical employees in three service organizations. Based on the tabulation provided
below, describe the sample characteristics.
Table 1: Frequency Distributions of Sample (n = 148)
RACE
Non‐whites = 48 (32%)
Whites
= 100 (68%)
AGE
< 20 = 10(7%)
20‐30 = 20(14%)
31‐40 = 30(20%)
>40 = 88(59%)
EDUCATION
High School = 38 (26%)
College Degree = 74 (50%)
Masters Degree = 36 (24%)
# OF YEARS IN ORG.
< 1 year = 5 (3%)
1‐3
= 25(17%)
4‐10
= 98(66%)
>10
= 20(14%)
GENDER
Males = 11(75%)
Females = 37 (25%)
MARITAL STATUS
Single 20 (14%)
Married 108 (73%)
Divorced 13 (9%)
Alternative7 (4%)
Lifestyle
Answer
The tabulation indicates the percentages on all the demographic data (as
shown in parentheses above). A profile of the respondents will be as follows.
Population and Sample
The population consisted of 3,700 clerical employees in three service
organizations. Of these a sample of 148 clerical employees was drawn. Based on the
demographic characteristics provided in the table, we can say that the majority of the
respondents are white (67.6 percent of the sample), have at least a college degree (50
percent with college degrees and 24 percent with Masters degrees), are married (73
percent), are above 40 years of age (59 percent), and have served in their
organizations for four to ten years (66 percent).
Further breakdowns of educational levels can be given, depending on the
nature of the study, and the necessity for detailed descriptions.
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Exercise #2 on Means, Standard Deviations, and Other
Statistics
Here is another tabulation of the Means, Standard Deviations, etc., for Ms.
Jones’ data. How would you interpret these data?
Table 2: Means, Standard Deviations and Other Statistics
VARIABLE
Age
# of Years Married
Stress
Job Involvement
Performance
MEAN
37.5
12.1
3.7
3.9
3.6
STD. DEV
18
24
1.79
1.63
0.86
MODE
38
15
3
4
3
MIN
20
0
1
2
3
MAX
64
32
5
5
5
Answer
The mean age of the respondents is 37.5 and since the mode is also 38, it can
be presumed that many of the respondents are about 38 years old. The average
number of years the respondents have been married is about 12, with some not
married at all (minimum = 0).
The amount of stress experienced by the subjects in this sample seems to be a
little over the average, but not high (3.7 on a 5‐point scale); the same can be said for
their performance level (3.6 on a 5‐point scale). The extent of their job involvement is
close to a 4 (four) on a 5‐point scale and can be considered to be moderately high.
While there is more variance in stress and job involvement (1.79 and 1.63), the
variance in performance is rather low (.86). This would indicate that there is greater
dispersion in the experienced stress and extent of job involvement, but most of the
people have been performing at the same “just above the average” level.
We would thus describe the profile of the average worker in these three
organizations, assuming that the sample is representative of the population, as being
about 38 years old, married for about 12 years, performing at just above the average
level, fairly involved in the job and experiencing a moderate amount of stress.
Exercise #3 on Correlations
From the same research done by Ms. Jones, the following inter‐correlation
matrix is shown. Interpret these results.
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Table 3: Pearson Correlations
VARIABLE
Age
# of yrs. married
Stress
Job Involvement
Performance
AGE
1.0
.86
# OF YRS. MARRIED
.43
.53
.09
.61
.32
STRESS
JOB INVOLVEMENT
PERFORMANCE
1.0
.36
1.0
1.0
.06
1.0
.58
.49
a. All correlations above .30 are significant, at least at the .05 level.
b. All correlations above .50 are significant, at least at the .01 level.
Answer
Eight correlations in the above matrix are significant at least at the .05 level, of
which four are significant at least at the .01 level. Only two of the ten correlations in
the matrix are not significant.
Age and the number of years married are highly correlated (r = .86) and this is
not surprising because older people are likely to have been married for a longer
period of time than younger persons.
Older persons also experience less stress (r = .43) possibly because they have
either learned the ropes well and things do not stress them, or they are better able to
handle stress and hence hardly experience them as stress, or they are given easy jobs.
Older people are also more job involved (r =.53), but age is not related to
performance. That is, though the older employees may be more involved in their jobs
than the younger ones, they do not necessarily perform better than the latter.
Those experiencing more stress are more involved in their jobs (r = .58) and
also perform better (r = .49). The more the job involvement, the better the
performance (r = .36). The above relationships do not indicate causality, merely
correlations.
Those married for a longer period experience less stress, possibly because the
family demands are less on them since they would have settled down to a routine
family life which does not induce stress. The persons who are married for longer
periods of time are also more involved in their jobs. But the length of marriage is not
related to performance (r = .06).
If performance is the main variable of interest to this study we would say that
neither age nor the length of marriage has any relationship to performance, but that
the amount of stress and the level of job involvement do have significant bivariate
relationships with the performance of employees. The more job involved people are,
the better they perform; the more stress they experience, the better they perform.
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Note: Based on the correlations among stress, job involvement, and
performance, it would be inappropriate to conclude that the high performer gets job
involved and hence experiences stress. Causal inferences cannot be drawn from
correlational analyses.
Discussion Questions
1. What activities are involved in getting the data ready for analysis?
After data are obtained through questionnaires, they need to be coded, keyed in, and
edited. That is, a categorization scheme has to be set up before the data can be typed
in. Then, outliers, inconsistencies, and blank responses, if any, have to be handled in
some way.
2. What does coding the data involve?
Data coding involves assigning a number to the participants’ responses so they can be
entered into a database.
3. Data editing deals with detecting and correcting illogical, inconsistent, or illegal
data in the information returned by the participants of the study. Explain the
difference between illogical, inconsistent, and illegal data.
An example of an illogical response is an outlier response. An outlier is an observation
that is substantially different from the other observations. An outlier is not always an
error even though data errors (entry errors) are a likely source of outliers. Because
outliers have a large impact on the research results they should be investigated
carefully to make sure that they are correct.
Inconsistent responses are responses that are not in harmony with other information.
Illegal codes are values that are not specified in the coding instructions.
4. How would you deal with missing data?
One way to handle a blank response is to ignore it when the analyses are done. An
alternative solution would be to look at the participant’s pattern of responses to other
questions and from these answers deduce a logical answer to the question for the
missing response. A second alternative solution would be to assign to the item the
mean value of the responses of all those who have responded to that particular item.
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In fact, there are many ways of handling blank responses, each of them having its own
particular advantages and disadvantages.
5. What is reverse scoring and when is reverse scoring necessary?
Take for instance the perceived inequity measure of the Excelsior Enterprises case.
Perceived inequity is measured by five survey items: (1) ‘I invest more in my work than
I get out of it’; (2) ‘I exert myself too much considering what I get back in return’ ; (3)
‘For the efforts I put into the organization, I get much in return’ (reversed); (4) ‘If I take
into account my dedication, the organization ought to give me a better practical
training’; and (5) ‘In general, the benefits I receive from the organization outweigh the
effort I put in it’ (reversed). For the first, second and fourth item, a score indicating
high agreement would be negative, but for the third and fifth question a score
indicating high agreement would be positive. To maintain consistency in the meaning
of a response, the first, second, and fourth item have to be reverse scored (note that
we are measuring equity and not inequity). In this case a 5 (I completely agree) would
be transformed to a 1 (I completely disagree), a 4 to a 2, and so forth.
6. There are three measures of central tendencies: the mean, the median, and the
mode. Measures of dispersion include the range, the standard deviation, the
variance (where the measure of central tendency is the mean), and the interquartile
range (where the measure of central tendency is the median). Describe these
measures and explain which of these measures you would use to provide an
overview of a) nominal, b) ordinal and c) interval data?
Scale
Visual Summary ‐‐‐‐‐ Measure of Relation Visual Summary of
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐…for …between Variables Relation
a Single Variable
…between Variables
Nominal
Measures of Central Measures of
Tendency …for a
Dispersion
Single Variable
…for a Single
Variable
Mode
‐
Ordinal
Median
Bar chart, pie chart
Interval
Arithmetic mean
Ratio
Arithmetic or
geometric mean
Semi‐interquartile
range
Minimum, maximum,
standard deviation,
variance, coefficient
of variation
Minimum, maximum,
standard deviation,
variance, coefficient
of variation
Bar chart, pie chart
Histogram, scatter
plots, box‐ and
whisker plot
Histogram, scatter
plots, box‐ and
whisker plot
Contingency Table
(Cross‐Tab)
Contingency Table
(Cross‐Tab)
Correlations
Stacked bars,
Clustered bars
Stacked bars,
Clustered bars
Scatterplots
Correlations
Scatterplots
Measures of Central Tendency
The Mean. The mean or the average is a measure of central tendency that offers a
general picture of the data without unnecessarily inundating one with each of the
observations in a data set. The mean or average of a set of say, 10 observations, is the
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sum of the 10 individual observations divided by 10 (the total number of
observations).
The Median. The median is the central item in a group of observations when they are
arrayed in either an ascending or a descending order.
The Mode. In some cases, a set of observations would not lend itself to a meaningful
representation through either the mean or the median, but can be signified by the
most frequently occurring phenomenon.
Measures of Dispersion
Range. Range refers to the extreme values in a set of observations.
Variance. The variance is calculated by subtracting the mean from each of the
observations in the data set, taking the square of this difference, and dividing the total
of these by the number of observations.
Standard Deviation. The standard deviation, which is another measure of dispersion
for interval and ratio scaled data, offers an index of the spread of a distribution or the
variability in the data.
Other Measures of Dispersion. When the median is the measure of central tendency,
percentiles, deciles, and quartiles become meaningful. Just as the median divides the
total realm of observations into two equal halves, the quartile divides it into four
equal parts, the decile into 10, and the percentile to 100 equal parts. The percentile is
useful when huge masses of data, such as the GRE or GMAT scores, are handled.
When the area of observations is divided into 100 equal parts, there are 99 percentile
points. Any given score has a probability of .01 that it will fall in any one of those
points. If John’s score is in the 16th percentile, it indicates that 84% of those who took
the exam scored better than he did, while 15% did worse.
Oftentimes we are interested in knowing where we stand in comparison to others —
are we in the middle, in the upper 10 or 25%, or in the lower 20 or 25%, or where? For
instance, if in a company‐administered test, Mr. Chou scores 78 out of a total of 100
points, he would be unhappy if he were in the bottom 10% among his colleagues (the
test‐takers), but would be reasonably pleased if he were in the top 10%, despite the
fact that his score remains the same. His standing in relation to the others can be
determined by the central tendency median and the percentile he falls in.
The measure of dispersion for the median, the interquartile range, consists of the
middle 50% of the observations (i.e., observations excluding the bottom and top 25%
quartiles). The interquartile range could be very useful when comparisons are to be
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made among several groups. For instance, telephone companies can compare long‐
distance charges of customers in several areas by taking samples of customer bills
from each of the cities to be compared.
7. A researcher wants to provide an overview of the gender of the respondents in his
sample. The gender is measured like this:
What is your gender?
0 Male
0 Female
What is the best way to provide an overview of the gender of the respondents?
Provide a frequency table.
8. Consider the following reliability analysis for the variable customer
differentiation. What could you conclude from it?
R E L I A B I L I T Y A N A L Y S I S ‐ S C A L E (A L P H A)
Item‐total Statistics
CUSDIF1
CUSDIF2
CUSDIF3
Reliability Coefficients
N of Cases = 111.0
Alpha = .5878
Scale
Mean
if Item
Deleted
10.0405
9.7432
9.6486
Scale
Variance
if Item
Deleted
5.4733
5.0176
5.3754
Corrected
Item‐
Alpha
Total
if Item
Correlation
Deleted
.2437
.7454
.5047
.3293
.4849
.3722
N of Items = 3
The scale is not reliable. We can delete item 1 to increase the Cronbach’s alpha, which
will increase to .7454.
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CHAPTER 12
Quantitative Data Analysis Part 2:
Hypothesis Testing
Instructional Goals
1. To make students understand and apply the different types of analyses and tests to
get at the inferential information they need.
2. To help them interpret the results they obtain from data analyses.
Discussion Questions
1. When we collect data on the effects of treatment in experimental designs, which
statistical test would be most appropriate to test the treatment effects?
We would use a t‐test with paired samples to determine the treatment effects.
2. A tax consultant wonders whether he should be more selective about the class of
clients he serves so as to maximize his income. He usually deals with four categories
of clients: the very rich, rich, upper middle class, and middle class. He has
information on each and every client served, the taxes paid by them, and how much
he has charged them. Since many factors relating to the clients vary (number of
dependents, business deductibles, etc.), irrespective of the category they belong to,
he would like an appropriate analysis to be done to see which among the four
categories of clientele he should choose to serve in the future.
What kind of analysis should be done in the above case and why?
Undergraduate Students can be exposed to a simple ANOVA design.
An ANOVA will help the tax consultant to make the decision, since the differences
among the four groups on the dependent variable, income, can be obtained through
this analysis. A further test such as the Duncan Multiple Range test, will determine
which among the four groups provides the most income.
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More advanced students can take this approach.
Since there are four categories of clients – very rich, rich, upper middle class, and
middle class – and the tax consultant wants to see how the clients can be
differentiated on various independent variables which are on a continuous scale, in
order to increase his income, he could use a MANOVA. MANOVA deals with multiple
independent variables simultaneously and differentiates the groups on the critical
factors.
A discriminant analysis will indicate which of the entire set of variables are
maximally discriminated for the four groups. Action can then be taken based on the
results.
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CHAPTER 13
QUALITATIVE DATA ANALYSIS
Instructional Goals
1. To make qualitative data analysis come alive and become meaningful to students
through examples that they can relate to.
2. To explain that qualitative data can be very rich and to stress the importance of
reducing qualitative data to key ideas and concepts.
3. To get students to analyze data using a structured approach.
4. To stress the importance of reliability and validity in qualitative data analysis.
Discussion Questions
1. What is qualitative data? How do qualitative data differ from quantitative data?
Qualitative data is data in the form of words. Quantitative data is data in the form of
numbers.
2. What are the main steps in qualitative data analysis?
According to Miles and Huberman, there are generally three steps in qualitative data
analysis: data reduction, data display, and the drawing of conclusions.
3. Define reliability and validity in the context of qualitative research.
Reliability and validity have a slightly different meaning in qualitative research in
comparison to quantitative research. Reliability in qualitative data analysis includes
category and interjudge reliability. Category reliability “depends on the analyst’s
ability to formulate categories and present to competent judges definitions of the
categories so they will agree on which items of a certain population belong in a
category and which do not.” (Kassarjian, 1977, p. 14). Interjudge reliability can be
defined as the degree of consistency between coders processing the same data
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(Kassarjian 1977).
Validity refers to the extent to which the research results 1) accurately represent the
collected data (internal validity) and 2) can be generalized or transferred to other
contexts or settings (external validity).
4. How can you assess the reliability and validity of qualitative research?
A commonly used measure of interjudge reliability is the percentage of coding
agreements out of the total number of coding decisions. As a general guideline,
agreement rates at or above 80% are considered to be satisfactory.
Two methods that have been developed to achieve validity in qualitative research are
discussed next.
‐ Supporting generalizations by counts of events. This can address common concerns
about the reporting of qualitative data; that anecdotes supporting the researcher’s
theory have been selected, or that too much attention has been paid to a small
number of events, at the expense of more common ones.
‐ Ensuring representativeness of cases and the inclusion of deviant cases (cases that
may contradict your theory). The selection of deviant cases provides a strong test of
your theory.
5. What is grounded theory?
Categorization is the process of organizing, arranging, and classifying coding units.
Codes and categories can be developed both inductively and deductively. In situations
where there is no theory available, you must generate codes and categories
inductively from the data. In its extreme form, this is what has been called grounded
theory.
6. How does narrative analysis differ from content analysis?
Narrative analysis is an approach that aims to elicit and scrutinize the stories we tell
about ourselves and their implications for our lives. Narrative data are often collected
via interviews. These interviews are designed to encourage the participant to describe
a certain incident in the context of his or her life history. Like this, narrative analysis
differs from other content analysis; it is focused on a process or temporal order, for
instance by eliciting information about the antecedents and consequences of a certain
incident in order to relate this incident to other incidents.
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CHAPTER 14
THE RESEARCH REPORT
Instructional Goals
1. To integrate all that has preceded in this course so that the purpose of each of the
steps in the research process and design now becomes clear and meaningful to
students.
2. To help students to pull together the results of their study and discuss the
interpretation of the results in a way that helps to address the original research
question that they had posed.
3. To enable students to look at alternative solutions to solve the problem that has been
investigated and make recommendations on the best course of action, weighing the
pros and cons.
4. To encourage students to depict pictorial representations of the results of their data
analyses.
5. To help students address the limitations of their study, and enable them to suggest
what else might be done in the future by way of researching such problem situations.
6. To facilitate students to write different kinds of research reports, depending on the
goals and purpose of the study.
7. To sharpen the oral presentation skills of students after the research report is written,
enabling them to highlight the important aspects of their study in a succinct manner
to the relevant audiences, within a limited time.
Discussion Questions
1. Discuss the purpose and contents of the Executive Summary.
The Executive Summary offers a condensed version of the problem, the methods
of investigation, the results of the study, the interpretation of the results, and the
recommendations made. This helps the executive to go through just two or three
pages and grasp the essence of what is contained in the report.
2. What are the similarities and differences of basic and applied research reports?
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Both applied and basic research reports stress the scientific aspects of the study.
Whereas reports of basic studies focus on a general problem for research, the applied
research report will focus on a specific problem related to a specific setting at a
specific time. The latter will also discuss the pros and cons of various alternative
solutions offered and usually provide a cost‐benefit analysis.
3. How have technological advancements helped in writing and presenting research
reports?
Technological advances have not only helped in the analysis of data without the
help of a mainframe, but make graphic presentations more sophisticated. The
presentation is made more powerful through Power Point, CD Rom and
Videographics. Video presentations can be seen in any part of the world where the
company would want to beam them.
4. Why is it necessary to specify the limitations of the study in the research report?
If the limitations of the study are acknowledged and explicitly stated by the
researcher, then the reader will have an idea of the possible reasons why these
limitations could not be overcome, and hence will be able to make a judgment about
the scientific quality of the study. For example, in a study of dual career families, it is
practically impossible to come up with a population frame because organizations just
do not have a listing of employees who are members of dual career families. In such
cases, the utmost one can expect is for the researcher to have a large enough sample
from a variety of settings, so that some understanding of the dynamics of dual career
families can be had. By acknowledging the limitation, but still arguing that the results
of the study are not invalid for various reasons (empirical validity is established, the
results have been replicated with different samples, etc.), the reader would be
convinced that the researcher did try to make the study as scientific as possible.
When the limitations are not explicitly stated, the reader is left wondering why the
limitations are not even acknowledged, and hence might be inclined to downgrade
the usefulness of the study.
5. What aspects of a class research project would be stressed by you in the written
report and in the oral presentation?
In the written report, since there is no limitation on the number of pages, all
aspects of the study will be discussed in as much detail as is necessary, including
literature survey. But in the presentation, the problem statement, the sampling
design, data analysis and interpretation, the recommendations, and the cost‐benefit
will be emphasized much more than some other aspects, due to the limitations of
time. It is also appropriate to state during the presentation that only some of the
important aspects of the study are presented, and whatever is omitted, but
considered important by the audience, could be taken up during question time.
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Exercises
Exercise 14.1
1. Critique Report 4 in the Appendix. Discuss it in terms of good and bad
research, suggesting how the study could have been improved, what aspects of it
are good, and how scientific it is.
i. The good aspects of the research report are:
a. The report is well organized under appropriate heads and subheads, and has a
professional look about it.
b. The literature survey seems to be current and relevant, as can be gleaned from this
abridged report.
c. The theoretical framework, hypotheses, and the rest of the report flow logically. The
Method Section is quite informative. The data analysis and the discussion,
conclusions, and recommendations sections are well done.
d. The report summarized the main points addressed in the sub‐sections which help the
reader to keep track of what is going on.
ii. The not‐so‐good aspects of the report:
specific ideas as to
a. The recommendations seem to be broad with no
implementation. For example, what could be some of the ways of determining the
worth of employee contributions, rather than merely counting the hours worked?
Though a detailed study of this could be done later, some
would help at this stage.
suggestions
b. There is also no mention of the costs of implementing the ideas. For instance, what
resources would be necessary in assigning mentors, and giving sensitivity training
seminars etc. Also, will the executives be willing and have the time to attend a
sensitivity training seminar? These could be dealt with more specifically.
c. The limitations to the study are not stated. Every study has some limitation and this
was conspicuous by its absence in the report.
Exercise 14.2
Write a Research Proposal for conducting a study on the efficiency of
manufacturing teams in a company.
From:
To:
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Date:
ABC Company has requested us to study the efficiency of the manufacturing
teams in the six factories in this area, each having 25 to 30 employees.
We will begin the study on September 15th and have the final report ready by
December 23rd.
Ten employees from each factory site will be selected through a simple
random sampling procedure (where every individual will have an equal chance of
being selected), with a total of 60 employees forming the sample.
Several employees who are conveniently available at each of the factories will
first be interviewed to get a feel for how they perceive their work environment and
their own efficiency, what factors contribute to their successes and what others stand
in the way of their efficiency. Based on the results of these unstructured interviews,
we will then determine the important variables and administer a questionnaire to the
sample of 60 employees. An analysis of the responses will be done and a report
written up.
If you have any specific questions, the research team will be happy to respond.
University Research Team
(Sd)
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