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An Overview of Research Methods
1.0. Learning outcomes
By the end of this chapter you should:
 be able to define the term business research ;
 be able to describe the role of business research;
 be able identify the qualities of a good research;
 be able discuss the step by step activities in the process of conducting a business
research;
 be able explain the differences between basic vs. applied , quantitative vs. qualitative, and
descriptive vs. explanatory research;
 be able discuss the features of a scientific research
1.1.
Introduction
Progress in almost every field of science depends on the contributions made by systematic
research; thus research is often viewed as the cornerstone of scientific progress. Broadly defined,
the purpose of research is to answer questions and acquire new knowledge. Research is the
primary tool used in virtually all areas of science to expand the frontiers of knowledge. For
example, research is used in such diverse scientific fields as psychology, biology, medicine,
physics, and botany, to name just a few of the areas in which research makes valuable
contributions to what we know and how we think about things. Among other things, by
conducting research, researchers attempt to reduce the complexity of problems, discover the
relationship between seemingly unrelated events, and ultimately improve the way we live.
In short, research can be used for the purposes of exploration, description, and explanation, all of
which make important and valuable contributions to the expansion of what we know and how we
live our lives. In addition to sharing similar broad goals, scientific research in virtually all fields
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of study shares certain defining characteristics, including testing hypotheses, careful observation
and measurement, systematic evaluation of data, and drawing valid conclusions.
1.2.
The Nature of Research
When listening to the radio, watching the television or reading a daily newspaper it is difficult to
avoid the term ‗research‘. The results of ‗research‘ are all around us. A debate about the findings
of a recent poll of people‘s opinions inevitably includes a discussion of ‗research‘, normally
referring to the way in which the data were collected. Politicians often justify their policy
decisions on the basis of ‗research‘. Documentary programmes tell us about ‗research findings‘,
and advertisers may highlight the ‗results of research‘ to encourage you to buy a particular
product or brand. However, we believe that what these examples really emphasize is the wide
range of meanings given to the term ‗research‘ in everyday speech.
Walliman (2005) argues that many of these everyday uses of the term ‗research‘ are not research
in the true meaning of the word. As part of this, he highlights ways in which the term is used
wrongly:
 just collecting facts or information with no clear purpose;
 reassembling and reordering facts or information without interpretation;
 as a term to get your product or idea noticed and respected.
The first of these highlights the fact that, although research often involves the collection of
information, it is more than just reading a few books or articles, talking to a few people or asking
people questions. While collecting data may be part of the research process, if it is not
undertaken in a systematic way, on its own and, in particular, with a clear purpose, it will not be
seen as research.
The second of these is commonplace in many reports. Data are collected, perhaps from a variety
of different sources, and then assembled in a single document with the sources of these data
listed. However, there is no interpretation of the data collected. Again, while the assembly of
data from a variety of sources may be part of the process of research, without interpretation it is
not research.
Finally, the term ‗research‘ can be used to get an idea or product noticed by people and to
suggest that people should have confidence in it. In such instances, when you ask for details of
the research process, these are either unclear or not forthcoming.
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Based upon this brief discussion we can already see that research has a number of characteristics:
 Data are collected systematically.
 Data are interpreted systematically.
 There is a clear purpose: to find things out.
1.3.
Meaning of Research
Research in common parlance refers to a search for knowledge. One can also define research as a
scientific and systematic search for pertinent information on a specific topic. In fact, research is
an art of scientific investigation. The Advanced Learner‘s Dictionary of Current English lays
down the meaning of research as ―a careful investigation or inquiry especially through search for
new facts in any branch of knowledge.‖
SOME DEFINITIONS
 Emory and Cooper defined research as‖ any organized inquiry carried out to provide
information for solving problems.‖
 Redman and Mory define research as a ―systematized effort to gain new knowledge.‖
Some people consider research as a movement, a movement from the known to the
unknown. It is actually a voyage of discovery. We all possess the vital instinct of
inquisitiveness for, when the unknown confronts us, we wonder and our inquisitiveness
makes us probe and attain full and fuller understanding of the unknown. This
inquisitiveness is the mother of all knowledge and the method, which man employs for
obtaining the knowledge of whatever the unknown, can be termed as research.
 Research comprises defining and redefining problems, formulating hypothesis or
suggested solutions; collecting, organizing and evaluating data; making deductions and
reaching conclusions; and at last carefully testing the conclusions to determine whether
they fit the formulating hypothesis.( Clifford Woody )
 Specifically, business research is a formalized means of designing, gathering, analyzing
and reporting information that may be used to solve specific management problem.
The words ―problem‖ and ―systematic‖ are very crucial in the above definitions of research.
First, to be said a research any investigation should start with a problem. Meaning any
research is essentially problem based. After all the very purpose of researches is to solve
problems, be it social (real) or theoretical. Second, as a systematic approach to problem
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solving all researches follow some common and basic procedures (common frame work).
Otherwise, the investigation will not have any sense of science.
1.4.
Why is Research Conducted?
Research is conducted for a number of reasons, which in turn depend on the objectives of any
particular ‗research problem‘. Of course, there are particular reasons for undertaking research at
various levels to discover something new. As discussed above, it may be to find out something
we do not already know or to enhance our understanding of phenomena that we already know
something about. In the business arena, however, research tends to be undertaken in order to
achieve one or more of the following objectives:
 To gain a competitive advantage.
 To test new products and services
 To solve a management/organizational problem.
 To provide information so as to avoid future business problems.
 To forecast future sales.
 To better understand shifts in consumer attitudes and tastes.
 To enhance profitability.
 To reduce operational costs.
 To enable management to prioritize strategic options for the future.
One could go on and on with this list and we are sure that you can add to it. The main point,
however, is that research (in whatever business or public sector organization) is always
undertaken for a clear purpose—to strengthen an organization‘s ability to meet the demands of
the future.
1.5.
Classification of Research
Research comes in many shapes and sizes. Before a researcher begins to conduct a study, he or
she must decide on a specific type of research. Good researchers understand the advantages and
disadvantages of each type, although most end up specializing in one.
For classification of research we shall look from four dimensions:
1. The purpose of doing research;
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2. The intended uses of research;
3. How it treats time i.e. the time dimension in research; and
4. The research (data collection) techniques used in it.
The four dimensions reinforce each other; that is, a purpose tends to go with certain
techniques and particular uses. Few studies are pure types, but the dimensions simplify the
complexity of conducting research.
1. Purpose of Doing Research
If we ask someone why he or she is conducting a study, we might get a range of responses: ―My
boss told me to do‖; ―It was a class assignment‖; ―I was curious.‖ There are almost as many
reasons to do research as there are researches. Yet the purposes of research may be organized
into three groups based on what the researcher is trying to accomplish – explore a new topic,
describe a social phenomenon, or explain why something occurs. Studies may have multiple
purposes (e.g. both to explore and to describe) but one purpose usually dominates.
a. Exploratory/Formulative Research
You may be exploring a new topic or issue in order to learn about it. If the issue was new or the
researcher has written little on it, you began at the beginning. This is called exploratory research.
The researcher‘s goal is to formulate more precise questions that future research can answer.
Exploratory research may be the first stage in a sequence of studies. A researcher may need to
know enough to design and execute a second, more systematic and extensive study.
When a researcher has a limited amount of experience with or knowledge about a research issue,
exploratory research is useful preliminary step that helps ensure that a more rigorous, more
conclusive future study will not begin with an inadequate understanding of the nature of the
management problem. The findings discovered through exploratory research would the
researchers to emphasize learning more about the particulars of the findings in subsequent
conclusive studies.
Exploratory research rarely yields definitive answers. It addresses the ―what‖ question: ―what is
this social activity really about?‖ It is difficult to conduct because there are few guidelines to
follow. Specifically there could be a number of goals of exploratory research.
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Goals of exploratory research:
 Become familiar with the basic facts, setting, and concerns;
 Develop well grounded picture of the situation;
 Develop tentative theories, generate new ideas, conjectures, or hypotheses;
 Determine the feasibility of conducting the study;
 Formulate questions and refine issues for more systematic inquiry; and
 Develop techniques and a sense of direction for future research.
For exploratory research, the researcher may use different sources for getting information like (1)
experience surveys, (2) secondary data analysis, (3) case studies, and (4) pilot studies.
As part of the experience survey the researcher tries to contact individuals who are
knowledgeable about a particular research problem. This constitutes an informal experience
survey.
Another economical and quick source of background information is secondary data analysis. It is
preliminary review of data collected for another purpose to clarify issues in the early stages of a
research effort.
The purpose of case study is to obtain information from one or a few situations that are similar to
the researcher‘s problem situation. A researcher interested in doing a nationwide survey among
union workers, may first look at a few local unions to identify the nature of any problems or
topics that should be investigated.
A pilot study implies that some aspect of the research is done on a small scale. For this purpose
focus group discussions could be carried out.
b. Descriptive Research
Descriptive research presents a picture of the specific details of a situation, social setting, or
relationship. The major purpose of descriptive research, as the term implies, is to describe
characteristics of a population or phenomenon. Descriptive research seeks to determine the
answers to who, what, when, where, and how questions. Labor Force Surveys, Population
Census, and Educational Census are examples of such research.
Descriptive study offers to the researcher a profile or description of relevant aspects of the
phenomena of interest. Look at the class in research methods and try to give its profile – the
characteristics of the students.
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Goals of descriptive research
 Describe the situation in terms of its characteristics i.e. provide an accurate profile of a
group;
 Give a verbal or numerical picture (%) of the situation;
 Present background information;
 Create a set of categories or classify the information;
 Clarify sequence, set of stages; and
 Focus on ‗who,‘ ‗what,‘ ‗when,‘ ‗where,‘ and ‗how‘ but not why?
A great deal of social research is descriptive. Descriptive researchers use most data –gathering
techniques – surveys, field research, and content analysis.
c. Explanatory Research
When we encounter an issue that is already known and have a description of it, we might begin
to wonder why things are the way they are. The desire to know ―why,‖ to explain, is the purpose
of explanatory research. It builds on exploratory and descriptive research and goes on to identify
the reasons for something that occurs. Explanatory research looks for causes and reasons. For
example, a descriptive research may discover that 10 percent of the parents abuse their children,
whereas the explanatory researcher is more interested in learning why parents abuse their
children.
Goals of explanatory research
 Explain things not just reporting. Why? Elaborate and enrich a theory‘s explanation.
 Determine which of several explanations is best.
 Determine the accuracy of the theory; test a theory‘s predictions or principle.
 Advance knowledge about underlying process.
 Build and elaborate a theory; elaborate and enrich a theory‘s predictions or principle.
 Extend a theory or principle to new areas, new issues, new topics:
 Provide evidence to support or refute an explanation or prediction.
2. The Uses of Research
Some researchers focus on using research to advance general knowledge, whereas others use it to
solve specific problems. Those who seek an understanding of the fundamental nature of social
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reality are engaged in basic research (also called academic research or pure research or
fundamental research).
Applied researchers, by contrast, primarily want to apply and tailor knowledge to address a
specific practical issue. They want to answer a policy question or solve a pressing social and
economic problem.
A. Basic Research
Basic research advances fundamental knowledge about the human world. It focuses on refuting
or supporting theories that explain how this world operates, what makes things happen, why
social relations are a certain way, and why society changes. Basic research is the source of most
new scientific ideas and ways of thinking about the world. It can be exploratory, descriptive, or
explanatory; however, explanatory research is the most common.
Basic research generates new ideas, principles and theories, which may not be immediately
utilized; though are the foundations of modern progress and development in different fields.
Today‘s computers could not exist without the pure research in mathematics conducted over a
century ago, for which there was no known practical application at that time.
Police officers trying to prevent delinquency or counselors of youthful offenders may see little
relevance to basic research on the question, ―Why does deviant behavior occur?‖ Basic research
rarely helps practitioners directly with their everyday concerns. Nevertheless, it stimulates new
ways of thinking about deviance that have the potential to revolutionize and dramatically
improve how practitioners deal with a problem.
A new idea or fundamental knowledge is not generated only by basic research. Applied research,
too, can build new knowledge. Nonetheless, basic research is essential for nourishing the
expansion of knowledge. Researchers at the center of the scientific community conduct most of
the basic research.
B. Applied Research
Applied researchers try to solve specific policy problems or help practitioners accomplish tasks.
Theory is less central to them than seeking a solution on a specific problem for a limited setting.
Applied research is frequently a descriptive research, and its main strength is its immediate
practical use.
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Applied research is conducted when decision must be made about a specific real-life problem.
Applied research encompasses those studies undertaken to answer questions about specific
problems or to make decisions about a particular course of action or policy. For example, an
organization contemplating a paperless office and a networking system for the company‘s
personal computers may conduct research to learn the amount of time its employees spend at
personal computers in an average week.
C. Basic and Applied Research Compared
The procedures and techniques utilized by basic and applied researchers do not differ
substantially. Both employ the scientific method to answer the questions at hand.
The scientific community is the primary consumer of basic research. The consumers of applied
research findings are practitioners such as teachers, counselors, and caseworkers, or decision
makers such as managers, committees, and officials. Often, someone other than the researcher
who conducted the study uses the results of applied research. This means that applied researchers
have an obligation to translate findings from scientific technical language into the language of
decision makers or practitioners.
The results of applied research are less likely to enter the public domain in publications. Results
may be available only to a small number of decision makers or practitioners, who decide whether
or how to put the research results into practice and who may or may not use the results.
Applied and basic researchers adopt different orientations toward research methodology. Basic
researchers emphasize high standards and try to conduct near-perfect research. Applied
researchers make more trade-offs. They may compromise scientific rigor to get quick, usable
results. Compromise is no excuse for sloppy research, however. Applied researchers squeeze
research into the constraints of an applied setting and balance rigor against practical needs. Such
balancing requires an in-depth knowledge of research and an awareness of the consequences of
compromising standards.
D. Types of Applied Research
Practitioners use several types of applied research. Some of the major ones are:
I. Action research: The applied research that treats knowledge as a form of power and
abolishes the line between research and social action. Those who are being studied participate
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in the research process; research incorporates ordinary or popular knowledge; research
focuses on power with a goal of empowerment; research seeks to raise consciousness or
increase awareness; and research is tied directly to political action.
The researchers try to advance a cause or improve conditions by expanding public awareness.
They are explicitly political, not value neutral. Because the goal is to improve the conditions
of research participants, formal reports, articles, or books become secondary. Action
researchers assume that knowledge develops from experience, particularly the experience of
social-political action. They also assume that ordinary people can become aware of conditions
and learn to take actions that can bring about improvement.
II. Impact Assessment Research: Its purpose is to estimate the likely consequences of a planned
change. Such an assessment is used for planning and making choices among alternative
policies – to make an impact assessment of the Ethiopian Abay Dam on the environment; to
determine changes in housing if a major new highway is built.
II.
Evaluation Research: It addresses the question, ―Did it work?‖ The process of establishing
value judgment based on evidence about the achievement of the goals of a program.
Evaluation research measures the effectiveness of a program, policy, or way of doing
something. ―Did the program work?‖ ―Did it achieve its objectives?‖ Evaluation researchers
use several research techniques (survey, field research).
Practitioners involved with a policy or program may conduct evaluation research for their own
information or at the request of outside decision makers, who sometime place limits on
researchers by setting boundaries on what can be studied and determining the outcome of
interest.
3. The Time Dimension in Research
Another dimension of research is the treatment of time. Some studies give us a snapshot of a
single, fixed time point and allow us to analyze it in detail. Other studies provide a moving
picture that lets us follow events, people, or sale of products over a period of time. In this way
from the angle of time research could be divided into two broad types:
a. Cross-Sectional Research. In cross-sectional research, researchers observe at one point
in time. Cross-sectional research is usually the simplest and least costly alternative. Its
disadvantage is that it cannot capture the change processes. Cross-sectional research can
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be exploratory, descriptive, or explanatory, but it is most consistent with a descriptive
approach to research.
b. Longitudinal Research. Researchers using longitudinal research examine features of
people or other units at more than one time. It is usually more complex and costly than
cross-sectional research but it is also more powerful, especially when researchers seek
answers to questions about change. There are three types of longitudinal research: time
series, panel, and cohort.
I. Time series research is longitudinal study in which the same type of information is collected
on a group of people or other units across multiple time periods. Researcher can observe stability
or change in the features of the units or can track conditions overtime.
One could track the characteristics of students registering in the course on Research Methods
over a period of four years i.e. the characteristics (Total, age characteristics, gender distribution,
subject distribution, and geographic distribution). Such an analysis could tell us the trends in the
characteristic over the four years.
II. The panel study is a powerful type of longitudinal research. In panel study, the researcher
observes exactly the same people, group, or organization across time periods. It is a difficult to
carry out such study. Tracking people over time is often difficult because some people die or
cannot be located. Nevertheless, the results of a well-designed panel study are very valuable.
III. A cohort analysis is similar to the panel study, but rather than observing the exact same
people, a category of people who share a similar life experience in a specified time period is
studied. The focus is on the cohort, or category, not on specific individuals. Commonly used
cohorts include all people born in the same year (called birth cohorts), all people hired at the
same time, all people retire on one or two year time frame, and all people who graduate in a
given year. Unlike panel studies, researchers do not have to locate the exact same people for
cohort studies. The only need to identify those who experienced a common life event.
4. Research (data collection) Techniques Used
Every researcher collects data using one or more techniques. The techniques may be grouped
into two categories: quantitative, collecting data in the form of numbers, and qualitative,
collecting data in the form of words or pictures.
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a. Quantitative
The main quantitative techniques are:
1. Experiments
2. Surveys
3. Using Existing Statistics
b. Qualitative
The major qualitative techniques of research are:
1. Case Study
2. Focus Group Discussion
Details about the quantitative and qualitative techniques of research shall be discussed in later
chapters.
1.6. The Research process
So long as research is perceived as a science it should have some sort of procedures. A research
process is a step-by-step approach of capturing relevant information so as to tackle a problem of
interest through accomplishing an appropriate research. A research process encompasses a
number of stages/steps. However, it has to be noted that a given research may not essentially
pass through all the stages sequentially. It all depends on the nature and purpose of the research
being conducted.
The following are the major steps in conducting business related research.
Step1. Establish the Need for research
Step2. Defining the research problem
Step3. Establish Research Objective
Step4. Extensive Literature survey
Step5. Designing the research
Step6. Constructing an instrument for data collection
Step7. Writing a research proposal
Step8. Data collection
Step9. Analysis and interpretation of data
Step10. Research Report Writing
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The next part briefly discusses the major steps of the research process.
Step 1: Establish the Need for research
To establish the need for research all organizations should monitor their surrounding
environments on a continuous basis using a monitoring system. The primary objective of a
monitoring system is to bring operating information to management. Such information allows
management:
 to evaluate whether their current operating results are meeting performance objectives,
 if proposed legislation has an impact on consumer spending or other industry interests,
 whether changes in consumer values and lifestyles are occurring or
 if new strategies are being implemented by competitors
Monitoring may be accomplished either formally or informally and in a variety of ways. One
firm may have a sophisticated formal Management information system (MIS). Another firm may
have a more traditional control system that primarily relies on financial statements as feedback.
A small business owner/manager may diligently observe the environments that affect his or her
firm.
Research May Not Be Needed - when?
Management should not automatically commission a research study each and every time a
decision must be made. There are several situations in which management should not consider a
research project. Here are four situations in which research may be inappropriate.
I.
Information Is Already Available.
If management knows its markets, competition, and the products, services, they may have the
necessary information to make an informed decision without commissioning a research study.
Contemporary managers have access to much information about their business. One of the
problems in the past was that this information was not readily available, and a research project
would have to be undertaken just to find the information and produce it in the proper form.
Today computer technology has provided management with the ability to record, store, and
retrieve much information about the routine operation of a business. It is possible to have
information on sales, costs, and profitability available by product, customer, region, salesperson,
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and so on, at the touch of a key. This situation is likely to increase as more and more businesses
invest in information processing technology that makes more of the right information available
to the right decision makers at the right time. In the past, many research studies were undertaken
simply to correct inadequacies in information processing capabilities.
II.
There is Insufficient Time for Research.
Sometimes there is not enough time to conduct the research. Occasionally, a problem is
discovered that requires an immediate response on the part of management. Unfortunately,
although some research can be performed in a relatively short time frame, much of it requires
weeks or months to complete. When competitive pressures or customer shifts demand quick
management action there may not be enough time to carry out a properly conducted research
project. Competitive actions may be swift and so demanding that prompt reaction is deemed
imperative, and although research would be helpful, circumstances argue strongly against
performing it.
III.
Resources Are Not Available
Oftentimes, resources are not available for research. If conducted in- house, research requires a
commitment of personnel, facilities, and budget. If conducted by outside research firm money, as
well as some personnel time is needed. If there is not enough money to devote to the research,
management must simply make the decision that those resources are better spent elsewhere. Of
courses, management always runs the risk of discovering that it invested resources in a strategy
that research would have identified as being inferior to alternative strategies. The firms that are
strapped for cash, and thus feel they cannot afford to spend dollars on research, are usually the
firms that could probably benefit the most by performing the research to help them make the best
decisions. Nevertheless, resources may simply not be available for research.
IV.
Costs Outweigh the Value of the Research.
Even when funds and other resources are available to conduct research, management must
always weigh the costs of conducting the research with the potential value of conducting the
research. Some decisions have relatively little impact on company sales, profits. Consumer
loyalty, dealer goodwill, and so on, and, as a result, they simply do not justify the expenditure.
Other decisions, however, may be very important, thereby justifying research.
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Another aspect to consider when weighing the value to be gained against the cost of the research
has to do with the confidence that the manager has in the outcome of a proposed decision. The
purpose of research is to serve as an aid in decision making, in effect, to reduce the uncertainty in
the outcomes of alternative decisions. If the manger feels that he or she knows the possible
outcomes then research should not be used.
As management monitors the environment it receives information from many sources such as
stockholders. Who may be complaining of poor bottom line performance: or dealers. Who are
complaining about losing sales to competition. It is important to note that management may or
may not bear about the real problem. That is they may not discover what is casing poor earnings
or sales declines. More often, management learns of symptoms. It is part of the researcher‘s job
to determine what problem(s) are causing the symptoms. Defining the problem then, is the next
step in the research process.
Step 2: Define Research Problem
Formulating a research problem is the most important step in research process after the need for
research is justified. A clear, concise statement of the problem is a key to good research. There is
much truth to the saying, ―A problem well defined is half solved‖. Unfortunately, this is much
easier to say than to do.
There are two types of research problems, viz., those which relate to states of nature and those
which relate to relationships between variables. At the very outset the researcher must single out
the problem s/he wants to study, i.e., s/he must decide the general area of interest or aspect of a
subject-matter that s/he would like to inquire into. Initially the problem may be stated in a broad
general way and then the ambiguities, if any, relating to the problem be resolved. Then, the
feasibility of a particular solution has to be considered before a working formulation of the
problem can be set up. The formulation of a general topic into a specific research problem, thus,
constitutes the first step in a scientific enquiry. Essentially two steps are involved in formulating
the research problem, viz., understanding the problem thoroughly, and rephrasing the same into
meaningful terms from an analytical point of view.
The best way of understanding the problem is to discuss it with one‘s own colleagues or with
those having some expertise in the matter. In an academic institution the researcher can seek the
help from a guide who is usually an experienced man and has several research problems in mind.
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Often, the guide puts forth the problem in general terms and it is up to the researcher to narrow it
down and phrase the problem in operational terms. In private business units or in governmental
organizations, the problem is usually earmarked by the administrative agencies with whom the
researcher can discuss as to how the problem originally came about and what considerations are
involved in its possible solutions.
The researcher must at the same time examine all available literature to get himself acquainted
with the selected problem. He may review two types of literature—the conceptual literature
concerning the concepts and theories, and the empirical literature consisting of studies made
earlier which are similar to the one proposed. The basic outcome of this review will be the
knowledge as to what data and other materials are available for operational purposes which will
enable the researcher to specify his own research problem in a meaningful context. After this the
researcher rephrases the problem into analytical or operational terms i.e., to put the problem in as
specific terms as possible. This task of formulating, or defining, a research problem is a step of
greatest importance in the entire research process. The problem to be investigated must be
defined unambiguously for that will help discriminating relevant data from irrelevant ones. Care
must however; be taken to verify the objectivity and validity of the background facts concerning
the problem.
The statement of the problem is of basic importance because it determines the data which are to
be collected, the characteristics of the data which are relevant, relations which are to be explored,
the choice of techniques to be used in these explorations and the form of the final report.
Step 3: Establish Research Objective
Research objectives, although relate to and determined by the problem definition, are set so that
when achieved they provide the necessary information to solve the problem. A good way of
setting research objectives is to ask, what information is needed in order to solve the problem?‖
Research objectives are the specific bits of knowledge that need to be gathered to close the
information gaps highlighted in the research problem. Some researchers put the research
objective(s) as part and parcel of the research problem. The following are common
characteristics of research objective:
 Stated in action terms
 Serve as the standard to evaluate the quality and value of the research
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 Objectives should be specific and unambiguous
Examples:
 To assess viewer recall of our advertising campaign
 To describe the segment of the market place
 To measure the daily average monthly number of absentees
You should notice that the research objectives are different from the defined problem. Yet, when
the information is gathered as a result of carrying out the research objectives, the problem is
solved. A key aspect of the research objective step is the specification of the specified types of
information useful to the managers as they look for a solution to the management problem at
hand.
Step 4: Extensive Literature Survey
Once the problem is formulated and the objectives are identified, a brief summary of it should be
written down. It is compulsory for a research worker writing a thesis for B.A degree to write a
synopsis of the topic and submit it to the necessary Committee or the Research advisor for
approval. At this juncture the researcher should undertake extensive literature survey connected
with the problem. For this purpose, the abstracting and indexing journals and published or
unpublished bibliographies are the first place to go to. Academic journals, conference
proceedings, government reports, books etc., must be tapped depending on the nature of the
problem. In this process, it should be remembered that one source will lead to another. The
earlier studies, if any, which are similar to the study in hand, should be carefully studied. A good
library will be a great help to the researcher at this stage.
Step 5: Designing the Research
Once the problem has been carefully defined, the researcher needs to establish the plan that will
outline the investigation to be carried out. The main function of a research design is to explain
how you will find answers to your research questions. The research design indicates the steps
that will be taken and in what sequence they occur.
The preparation of the research design, appropriate for a particular research problem, involves
usually the consideration of the following:
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 the sample design
 the means of obtaining the information;
 the availability and skills of the researcher and his staff (if any);
 explanation of the way in which selected means of obtaining information will be
organized and the reasoning leading to the selection;
 the time available for research; and
 the cost factor relating to research, i.e., the finance available for the purpose.
For any investigation, the selection of an appropriate research design is crucial in enabling you to
arrive at valid findings, comparisons and conclusions. A faulty design results in misleading
findings and is therefore tantamount to wasting human and financial resources.
Step6. Constructing an Instrument for Data Collection
In dealing with any real life problem it is often found that data at hand are inadequate, and hence,
it becomes necessary to collect data that are appropriate. There are several ways of collecting the
appropriate data which differ considerably in context of money costs, time and other resources at
the disposal of the researcher.
Primary data can be collected either through experiment or through survey. If the researcher
conducts an experiment, he observes some quantitative measurements, or the data, with the help
of which he examines the truth contained in his hypothesis. But in the case of a survey, data can
be collected by any one or more of the following ways:
I. By observation: This method implies the collection of information by way of investigator‘s
own observation, without interviewing the respondents. The information obtained relates to what
is currently happening and is not complicated by either the past behavior or future intentions or
attitudes of respondents. This method is no doubt an expensive method and the information
provided by this method is also very limited. As such this method is not suitable in inquiries
where large samples are concerned.
II. Through personal interview: The investigator follows a rigid procedure and seeks answers
to a set of pre-conceived questions through personal interviews. This method of collecting data is
usually carried out in a structured way where output depends upon the ability of the interviewer
to a large extent.
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III. Through telephone interviews: This method of collecting information involves contacting
the respondents on telephone itself. This is not a very widely used method but it plays an
important role in industrial surveys in developed regions, particularly, when the survey has to be
accomplished in a very limited time.
IV. By mailing of questionnaires: The researcher and the respondents do not come in contact
with each other if this method of survey is adopted. Questionnaires are mailed to the respondents
with a request to return after completing the same. It is the most extensively used method in
various economic and business surveys. Before applying this method, usually a Pilot Study for
testing the questionnaire reveals the weaknesses, if any, of the questionnaire. Questionnaire to be
used must be prepared very carefully so that it may prove to be effective in collecting the
relevant information.
V. Through schedules: Under this method the enumerators are appointed and given training.
They are provided with schedules containing relevant questions. These enumerators go to
respondents with these schedules. Data are collected by filling up the schedules by enumerators
on the basis of replies given by respondents. Much depends upon the capability of enumerators
so far as this method is concerned. Some occasional field checks on the work of the enumerators
may ensure sincere work.
The researcher should select one of these methods of collecting the data taking into
consideration the nature of investigation, objective and scope of the inquiry, financial resources,
available time and the desired degree of accuracy. Though he should pay attention to all these
factors but much depends upon the ability and experience of the researcher.
Step7. Writing a research proposal
Now, step-by-step, you have done all the preparatory work. Next put everything together in a
way that provides adequate information, for your research supervisor and others, about your
research study. This overall plan tells a reader about your research problem and how you are
planning to investigate, and is called a research proposal. Broadly, a research proposal‘s main
function is to detail the operational plan for obtaining answers to your research questions.
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Step8. Execution of the project
Execution of the project is a very important step in the research process. If the execution of the
project proceeds on correct lines, the data to be collected would be adequate and dependable.
The researcher should see that the project is executed in a systematic manner and in time. If the
survey is to be conducted by means of structured questionnaires, data can be readily machineprocessed. In such a situation, questions as well as the possible answers may be coded. If the data
are to be collected through interviewers, arrangements should be made for proper selection and
training of the interviewers. The training may be given with the help of instruction manuals
which explain clearly the job of the interviewers at each step. Occasional field checks should be
made to ensure that the interviewers are doing their assigned job sincerely and efficiently.
A careful watch should be kept for unanticipated factors in order to keep the survey as much
realistic as possible. This, in other words, means that steps should be taken to ensure that the
survey is under statistical control so that the collected information is in accordance with the predefined standard of accuracy. If some of the respondents do not cooperate, some suitable
methods should be designed to tackle this problem. One method of dealing with the nonresponse problem is to make a list of the non-respondents and take a small sub-sample of them,
and then with the help of experts vigorous efforts can be made for securing response.
Step9. Analysis and interpretation of data
After the data have been collected, the researcher turns to the task of analyzing them. The
analysis of data requires a number of closely related operations such as establishment of
categories, the application of these categories to raw data through coding, tabulation and then
drawing statistical inferences. The unwieldy data should necessarily be condensed into a few
manageable groups and tables for further analysis. Thus, researcher should classify the raw data
into some purposeful and usable categories. Coding operation is usually done at this stage
through which the categories of data are transformed into symbols that may be tabulated and
counted. Editing is the procedure that improves the quality of the data for coding. With coding
the stage is ready for tabulation.
Tabulation is a part of the technical procedure wherein the classified data are put in the form of
tables. The mechanical devices can be made use of at this juncture. A great deal of data, specially
20
in large inquiries, is tabulated by computers. Computers not only save time but also make it
possible to study large number of variables affecting a problem simultaneously.
Analysis work after tabulation is generally based on the computation of various percentages,
coefficients, etc., by applying various well defined statistical formulae. In the process of analysis,
relationships or differences supporting or conflicting with original or new hypotheses should be
subjected to tests of significance to determine with what validity data can be said to indicate any
conclusion(s).
For instance, if there are two samples of weekly wages, each sample being drawn from factories
in different parts of the same city, giving two different mean values, then our problem may be
whether the two mean values are significantly different or the difference is just a matter of
chance. Through the use of statistical tests we can establish whether such a difference is a real
one or is the result of random fluctuations. If the difference happens to be real, the inference will
be that the two samples come from different universes and if the difference is due to chance, the
conclusion would be that the two samples belong to the same universe. Similarly, the technique
of analysis of variance can help us in analyzing whether three or more varieties of seeds grown
on certain fields yield significantly different results or not. In brief, the researcher can analyze
the collected data with the help of various statistical measures.
If a hypothesis is tested and upheld several times, it may be possible for the researcher to arrive
at generalization, i.e., to build a theory. As a matter of fact, the real value of research lies in its
ability to arrive at certain generalizations. If the researcher had no hypothesis to start with, he
might seek to explain his findings on the basis of some theory. It is known as interpretation. The
process of interpretation may quite often trigger off new questions which in turn may lead to
further researches.
Step10. Writing the Research Report
Finally, the researcher has to prepare the report of what has been done by him. Writing of report
must be done with great care keeping in view the following:
1. The layout of the report should be as follows: (i) the preliminary pages; (ii) the main text,
and (iii) the end matter.
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In its preliminary pages the report should carry title and date followed by
acknowledgements and foreword. Then there should be a table of contents followed by a
list of tables and list of graphs and charts, if any, given in the report.
The main text of the report should have the following parts:
A. Introduction: It should contain a clear statement of the objective of the research and an
explanation of the methodology adopted in accomplishing the research. The scope of the
study along with various limitations should as well be stated in this part.
B. Summary of findings: After introduction there would appear a statement of findings and
recommendations in non-technical language. If the findings are extensive, they should be
summarized.
C. Main report: The main body of the report should be presented in logical sequence and
broken-down into readily identifiable sections.
D. Conclusion: Towards the end of the main text, researcher should again put down the
results of his research clearly and precisely. In fact, it is the final summing up.
At the end of the report, appendices should be enlisted in respect of all technical data.
Bibliography, i.e., list of books, journals, reports, etc., consulted, should also be given in
the end. Index should also be given specially in a published research report.
2. Report should be written in a concise and objective style in simple language avoiding vague
expressions such as ‗it seems,‘ ‗there may be‘, and the like.
3.
Charts and illustrations in the main report should be used only if they present the
information more clearly and forcibly.
4. Calculated ‗confidence limits‘ must be mentioned and the various constraints experienced
in conducting research operations may as well be stated.
1.7. Criteria of Good Research
Whatever may be the types of research works and studies, one thing that is important is that they
all meet on the common ground of scientific method employed by them. One expects scientific
research to satisfy the following criteria:
1. Purpose Clearly Defined: The purpose of the research should be clearly defined and
common concepts be used.
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2. Research Process Detailed: The research procedure used should be described in
sufficient detail to permit another researcher to repeat the research for further
advancement, keeping the continuity of what has already been attained.
3. Research Design Thoroughly Planned: The procedural design of the research should
be carefully planned to yield results that are as objective as possible.
 When a sampling of the population is involved, the report should include
evidence concerning the degree of representativeness of the sample.
 A questionnaire ought not to be used when more reliable evidence is available
from documentary sources by direct observation.
 Bibliographic searches must be as thorough and complete as possible.
 Experiments should have satisfactory controls.
 Direct observations should be recorded in writing as soon as possible after the
event.
 Efforts should be made to minimize the influence of personal bias in selecting and
recording data.
4. Limitations Frankly Revealed: The researcher should report with complete frankness,
flaws in procedural design and estimate their effects upon the findings.
5. Adequate Analysis for Decision Maker‟s Needs: The analysis of data should be
sufficiently adequate to reveal its significance and the methods of analysis used should be
appropriate. The validity and reliability of the data should be checked carefully.
6. Conclusions Justified: Conclusions should be confined to those justified by the data of
the research and limited to those for which the data provide an adequate basis.
 Widening (broadening) the basis of inductions by including personal experiences
not subject to the controls under which the research data were gathered, tends to
decrease the objectivity of the research and weakens confidence in the findings.
 Drawing conclusions from a study of a limited population and applying them
universally is undesirable.
 Good researchers always specify the conditions under which their conclusions
seem to be valid.
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7. Researcher‟s Experience Reflected: Greater confidence in research is warranted if the
researcher is experienced, has a good reputation in research and is a person of integrity.
In other words, we can state the qualities of a good research as under:
A. Good research is systematic: It means that research is structured with specified steps to
be taken in a specified sequence in accordance with the well defined set of rules.
Systematic characteristic of the research does not rule out creative thinking but it
certainly does reject the use of guessing and intuition in arriving at conclusions.
B. Good research is logical: This implies that research is guided by the rules of logical
reasoning and the logical process of induction and deduction are of great value in
carrying out research. Induction is the process of reasoning from a part to the whole
whereas deduction is the process of reasoning from some premise to a conclusion which
follows from that very premise. In fact, logical reasoning makes research more
meaningful in the context of decision making.
C. Good research is empirical: It implies that research is related basically to one or more
aspects of a real situation and deals with concrete data that provides a basis for external
validity to research results.
D. Good research is replicable: This characteristic allows research results to be verified by
replicating the study and thereby building a sound basis for decisions.
1.8. Ethical Issues of Research
Researchers have responsibility to their profession; clients and respondents that must to high
ethical standards to ensure both the function and the information are not brought into disrepute.
Suppliers of research are ethically obligated to provide unbiased design and honest and objective
fieldwork regardless of the client's expectations about the desired outcomes. They are also held
responsible for ensuring that the information they obtain for their clients is held confidential. To
keep the trust of the respondents who provide the information, researchers must respect their
rights of anonymity (they should not be identified with their answer) and privacy (they can elect
to refuse to participate in the study).
There are a number of key phrases that describe the system of ethical protections that the
contemporary social and medical research establishments have created to try to protect better the
rights of their research participants. The principle of voluntary participation requires that people
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not be coerced into participating in research. This is especially relevant where researchers had
previously relied on 'captive audiences' for their subjects -- prisons, universities, and places like
that. Closely related to the notion of voluntary participation is the requirement of informed
consent. Essentially, this means that prospective research participants must be fully informed
about the procedures and risks involved in research and must give their consent to participate.
Ethical standards also require that researchers not put participants in a situation where they might
be at risk of harm as a result of their participation. Harm can be defined as both physical and
psychological. There are two standards that are applied in order to help protect the privacy of
research participants. Almost all research guarantees the participants confidentiality - they are
assured that the gathered information will not be made available to anyone who is not directly
involved in the study. The stricter standard is the principle of anonymity, which essentially
means that the participant will remain anonymous throughout the study -- even to the researchers
themselves. Clearly, the anonymity standard is a stronger guarantee of privacy, but it is
sometimes difficult to accomplish, especially in situations where participants have to be
measured at multiple time points (e.g., a pre-post study). Increasingly, researchers have had to
deal with the ethical issue of a person's right to service. Good research practice often requires the
use of a no-treatment control group -- a group of participants who do not get the treatment or
program that is being studied. But when that treatment or program may have beneficial effects,
persons assigned to the no-treatment control may feel their rights to equal access to services are
being curtailed.
Even when clear ethical standards and principles exist, there will be times when the need to do
accurate research runs up against the rights of potential participants. No set of standards can
possibly anticipate every ethical circumstance. Furthermore, there needs to be a procedure that
assures that researchers will consider all relevant ethical issues in formulating and conducting
research.
1.9. Summary
Business research is systematic and rational investigation to obtain valuable information that
influences the decision of a manager. We have to study research because of that research
methods enable us to solve problems and meet challenges of a fast-paced decision making
environment, captures valuable information, improves current techniques and increases the
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overall benefit of the organization, and evaluates research works (as an expert). Business
research is a systematic inquiry that provides information to guide business decisions. This
includes exploration, descriptive, and explanatory. Research can be classified based on different
dimensions such as application, statistical content or objectives of the investigation.
The research process can be grouped into need assessment, problem formulation, establishing the
objective, designing the research, writing the proposal, collection of data, analysis, and reporting
research.
For sound decisions qualities of good research is important. The situation of good research can
be recognized when purpose
is clearly defined, research process detailed, research design
thoroughly planned, high ethical standards applied, limitations frankly revealed, adequate
analysis for decision maker‘s needs, findings presented unambiguously, conclusions justified,
and researcher‘s experience reflected.
1. Define research and identify the two important features in any investigation which may be
considered as a research.
2. Explain succinctly the role of business research in managerial planning and decisions.
3. Name and briefly discuss the ten steps of the research process.
5. Identify at least five characteristics of a good research.
6. Explain briefly why data collection and data analysis should not be separated at the planning
stage of any research project.
7. Discuss with examples "Exploratory research", "Descriptive research", and "Explanatory
research".
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2
Defining the Research Problem
2.0. Learning outcomes
By the end of this chapter you should be able to:
 identify various sources of research problem;
 discuss the components of a research problem
 know the criteria in selecting a good research problem;
 turn research ideas into a research project that has clear research question(s) and
objectives;
 Identify your own research topic together with its research questions and objectives
2.1. Introduction
In research process, the first and foremost step happens to be that of selecting and properly
defining a research problem. A researcher must find the problem and formulate it so that it
becomes susceptible to research. Like a medical doctor, a researcher must examine all the
symptoms (presented to him or observed by him) concerning a problem before he can diagnose
correctly. Before you start your research you need to have at least some idea of what you want to
do. This is probably the most difficult, and yet the most important, part of your research project.
This chapter is concerned with how to formulate your research problem and your research
question. Without being clear about what you are going to research it is difficult to plan how you
are going to research it.
2.2. What is a Research Problem?
A research problem, in general, refers to some difficulty which a researcher experiences in the
context of either a theoretical or practical situation and wants to obtain a solution for the same.
We can state the components of a research problem as under:
I.
II.
There must be an individual or a group which has some difficulty or the problem.
There must be some objective(s) to be attained at. If one wants nothing, one cannot have
a problem.
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III.
There must be alternative means (or the courses of action) for obtaining the objective(s)
one wishes to attain. This means that there must be at least two means available to a
researcher for if he has no choice of means, he cannot have a problem.
IV.
There must remain some doubt in the mind of a researcher with regard to the selection of
alternatives. This means that research must answer the question concerning the relative
efficiency of the possible alternatives.
V.
There must be some environment(s) to which the difficulty pertains.
Thus, a research problem is one which requires a researcher to find out the best solution for the
given problem, i.e., to find out by which course of action the objective can be attained optimally
in the context of a given environment. There are several factors which may result in making the
problem complicated. For instance, the environment may change affecting the efficiencies of the
courses of action or the values of the outcomes; the number of alternative courses of action may
be very large; persons not involved in making the decision may be affected by it and react to it
favorably or unfavorably, and similar other factors. All such elements (or at least the important
ones) may be thought of in context of a research problem.
2.3. Potential Sources of Research Problem
Where do research topics come from? Problem originates from different sources.
The major potential sources of research ideas (problems) are:
I.
Interest
First and foremost, researchers typically choose research topics that are of interest to them.
Although this may seem like common sense, it is important to occasionally remind ourselves that
researchers engage in research presumably because they have a genuine interest in the topics that
they study. Regardless of whether researchers enter their chosen fields with specific interests or
develop new interests as they go along, many researchers become interested in particular
research ideas simply by observing the world around them. Merely taking an interest in a specific
observed phenomenon is the impetus for a great amount of research in all fields of study. In
summary, a researcher‘s basic curiosity about an observed phenomenon typically provides
sufficient motivation for choosing a research topic.
II.
Previous Research
Researchers also choose research topics based on the results of prior research, whether conducted
by them or by someone else. Researchers will likely attest that previously conducted research is a
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rich and plentiful source of research ideas. Through exposure to the results of research studies,
which are typically published in peer-reviewed journals, a researcher may develop a research
interest in a particular area. For example, a sociologist who primarily studies the socialization of
adolescents may take an interest in studying the related phenomenon of adolescent gang behavior
after being exposed to research studies on that topic. In these instances, researchers may attempt
to replicate the results obtained by the other researchers or perhaps extend the findings of the
previous research to different populations or settings.
III.
Theory of one‟s own interest
A theory is a conceptualization, or description, of a phenomenon that attempts to integrate all
that we know about the phenomenon into a concise statement or question. Theories often serve
as a good source for research ideas. Theories can serve several purposes, but in the research
context, they typically function as a rich source of hypotheses that can be examined empirically.
This brings us to an important point that should not be glossed over—specifically, that research
ideas (and the hypotheses and research designs that follow from those ideas) should be based on
some theory.
IV.
Management
In an organizational setup management is the core origin/source of problems that are to be
researched.
The external environment within which organizations are operating is so dynamic and it changes
frequently. This change is the source of either a threat or opportunity for the organization. Unless
management responds to such changes critical problems will develop in the organization.
Through time management starts to clearly observe different symptoms, which indicate the
existence of problem. These symptoms observed by management in an organization are called
management dilemma. The real cause of the symptom is not as such easily detectable. This is
what is supposed to be researched. This is a typical analogy to the medical practitioners. They
first observe the symptom, make their own analysis (research or experimentation), analyze
results, and then they detect the cause and medicate it.
Rising cost, falling market share, declining product quality, high labor turnover, high rate of
absenteeism, etc are some common examples of management dilemma (Symptoms).
Cause
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Problem
Symptom
Identifying management dilemma is rarely difficult unless the organization fails to truck its
performance factors-like sales, profits, employee turnover, etc. Rather choosing one dilemma to
focus on is a bit difficult as it involves the risk of misdirecting scarce resources.
2.4. Selecting the Problem
The research problem undertaken for study must be carefully selected. The task is a difficult one,
although it may not appear to be so. Help may be taken from a research guide in this connection.
Nevertheless, every researcher must find out his own salvation for research problems cannot be
borrowed. A problem must spring from the researcher‘s mind like a plant springing from its own
seed. If our eyes need glasses, it is not the optician alone who decides about the number of the
lens we require. We have to see ourselves and enable him to prescribe for us the right number by
cooperating with him. Thus, a research guide can at the most only help a researcher choose a
subject. However, the following points may be observed by a researcher in selecting a research
problem or a subject for research:
i.
Subject which is overdone should not be normally chosen, for it will be a difficult task to
throw any new light in such a case.
ii.
Controversial subject should not become the choice of an average researcher.
iii.
Too narrow or too vague problems should be avoided.
iv.
The subject selected for research should be familiar and feasible so that the related
research material or sources of research are within one‘s reach. Even then it is quite
difficult to supply definitive ideas concerning how a researcher should obtain ideas for
his research.
For this purpose, a researcher should contact an expert or a professor in the University
who is already engaged in research.
v.
The importance of the subject, the qualifications and the training of a researcher, the costs
involved, and the time factor are few other criteria that must also be considered in
selecting a problem. In other words, before the final selection of a problem is done, a
researcher must ask himself the following questions:
a) Whether he is well equipped in terms of his background to carry out the research?
b) Whether the study falls within the budget he can afford?
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c) Whether the necessary cooperation can be obtained from those who must
participate in research as subjects?
If the answers to all these questions are in the affirmative, one may become sure so far as
the practicability of the study is concerned.
vi.
The selection of a problem must be preceded by a preliminary study. This may not be
necessary when the problem requires the conduct of a research closely similar to one
that has already been done. But when the field of inquiry is relatively new and does not
have available a set of well developed techniques, a brief feasibility study must always
be undertaken.
If the subject for research is selected properly by observing the above mentioned points, the
research will not be a boring drudgery, rather it will be love‘s labor. In fact, zest for work is a
must. The subject or the problem selected must involve the researcher and must have an upper
most place in his mind so that he may undertake all pains needed for the study.
2.5. TECHNIQUE INVOLVED IN DEFINING A PROBLEM
Defining a research problem properly and clearly is a crucial part of a research study and must in
no case be accomplished hurriedly. However, in practice this frequently overlooked which
causes a lot of problems later on. Hence, the research problem should be defined in a systematic
manner, giving due weight to all relating points. The technique for the purpose involves the
undertaking of the following steps generally one after the other: (i) statement of the problem in a
general way; (ii) understanding the nature of the problem; (iii) surveying the available literature;
(iv) developing the ideas through discussions; and (v) rephrasing the research problem into a
working proposition.
A brief description of all these points will be helpful.
I) Statement of the problem in a general way: First of all the problem should be stated in
a broad general way, keeping in view either some practical concern or some scientific
or intellectual interest. For this purpose, the researcher must immerse himself
thoroughly in the subject matter concerning which he wishes to pose a problem. In
case of social research, it is considered advisable to do some field observation and as
such the researcher may undertake some sort of preliminary survey or what is often
called pilot survey. Then the researcher can himself state the problem or he can seek
31
the guidance of the guide or the subject expert in accomplishing this task. Often, the
guide puts forth the problem in general terms, and it is then up to the researcher to
narrow it down and phrase the problem in operational terms. In case there is some
directive from an organizational authority, the problem then can be stated
accordingly. The problem stated in a broad general way may contain various
ambiguities which must be resolved by cool thinking and rethinking over the
problem. At the same time the feasibility of a particular solution has to be considered
and the same should be kept in view while stating the problem
II) Understanding the nature of the problem: The next step in defining the problem is to
understand its origin and nature clearly. The best way of understanding the problem is
to discuss it with those who first raised it in order to find out how the problem
originally came about and with what objectives in view. If the researcher has stated
the problem himself, he should consider once again all those points that induced him
to make a general statement concerning the problem. For a better understanding of the
nature of the problem involved, he can enter into discussion with those who have a
good knowledge of the problem concerned or similar other problems. The researcher
should also keep in view the environment within which the problem is to be studied
and understood.
III)
Surveying the available literature: All available literature concerning the problem
at hand must necessarily be surveyed and examined before a definition of the research
problem is given. He must devote sufficient time in reviewing of research already
undertaken on related problems. This is done to find out what data and other
materials, if any, are available for operational purposes. ―Knowing what data are
available often serves to narrow the problem itself as well as the technique that might
be used‖. This would also help a researcher to know if there are certain gaps in the
theories, or whether the existing theories applicable to the problem under study are
inconsistent with each other, or whether the findings of the different studies do not
follow a pattern consistent with the theoretical expectations and so on. All this will
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enable a researcher to take new strides in the field for furtherance of knowledge i.e.,
he can move up starting from the existing premise. Studies on related problems are
useful for indicating the type of difficulties that may be encountered in the present
study as also the possible analytical shortcomings. At times such studies may also
suggest useful and even new lines of approach to the present problem.
IV) Developing the ideas through discussions: Discussion concerning a problem often
produces useful information. Various new ideas can be developed through such an
exercise. Hence, a researcher must discuss his problem with his colleagues and others
who have enough experience in the same area or in working on similar problems.
This is quite often known as an experience survey. People with rich experience are in
a position to enlighten the researcher on different aspects of his proposed study and
their advice and comments are usually invaluable to the researcher. They help him
sharpen his focus of attention on specific aspects within the field. Discussions with
such persons should not only be confined to the formulation of the specific problem at
hand, but should also be concerned with the general approach to the given problem,
techniques that might be used, possible solutions, etc.
V) Rephrasing the research problem: Finally, the researcher must sit to rephrase the
research problem into a working proposition. Once the nature of the problem has been
clearly understood, the environment (within which the problem has got to be studied)
has been defined, discussions over the problem have taken place and the available
literature has been surveyed and examined, rephrasing the problem into analytical or
operational terms is not a difficult task. Through rephrasing, the researcher puts the
research problem in as specific terms as possible so that it may become operationally
viable and may help in the development of working hypotheses.
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2.6. Turning Research Ideas into Research Projects
2.6.1. Writing research questions
After selecting a specific research topic and conducting a thorough literature review, you are
ready to take the next step in planning a research study: clearly articulating the research problem.
The research problem typically takes the form of a concise question i.e. research questions.
Research questions are refined statements of the specific components of the problem. It is the
statement of the information needed by decision makers to help solve a decision problem. One of
the key criteria of your research success will be whether you have a set of clear conclusions
drawn from the data you have collected. The extent to which you can do that will be determined
largely by the clarity with which you have posed your initial research questions.
When articulating a research question, it is critically important to make sure that the question is
specific enough to avoid confusion and to indicate clearly what is being studied. In other words,
the research problem should be composed of a precisely stated research question that clearly
identifies the variables being studied. A vague research question often results in methodological
confusion, because the research question does not clearly indicate what or who is being studied.
The following are some examples of vague and nonspecific research questions:
1. What effect does weather have on memory?
2. Does exercise improve physical and mental health?
3. Do taking street drugs result in criminal behavior?
As you can see, each of these questions is rather vague, and it is impossible to determine exactly
what is being studied. For example, in the first question, what type of weather is being studied,
and memory for what? In the second question, is the researcher studying all types of exercise,
and the effects of exercise on the physical and mental health of all people or a specific subgroup
of people? Finally, in the third question, which street drugs are being studied, and what specific
types of criminal behavior?
An effective way to avoid confusion in formulating research questions is by using operational
definitions. Through the use of operational definitions, researchers can specifically and clearly
identify what (or who) is being studied. Researchers use operational definitions to define key
concepts and terms in the specific contexts of their research studies. The benefit of using
operational definitions is that they help to ensure that everyone is talking about the same
34
phenomenon. Among other things, this will greatly assist future researchers who attempt to
replicate a given study‘s results. Obviously, if researchers cannot determine what or who is being
studied, they will certainly not be able to replicate the study. Let‘s look at an example of how
operational definitions can be effectively used when formulating a research question.
Let‘s say that a researcher is interested in studying the effects of large class sizes on the
academic performance of gifted children in high population schools. The research question may
be phrased in the following manner: ―What effects do large class sizes have on the academic
performance of gifted children in high-population schools?‖ This may seem to be a fairly
straightforward research question, but upon closer examination, it should become evident that
there are several important terms and concepts that need to be defined. For example, what
constitutes a ―large class‖; what does ―academic performance‖ refer to; which kids are
considered ―gifted‖; and what is meant by ―high-population schools‖?
To reduce confusion, the terms and concepts included in the research question need to be
clarified through the use of operational definitions. For example, ―large classes‖ may be defined
as classes with 30 or more students; ―academic performance‖ may be limited to scores received
on standardized achievement tests; ―gifted‖ children may include only those children who are in
advanced classes; and ―high-population schools‖ may be defined as schools with more than
1,000 students. Without operationally defining these key terms and concepts, it would be
difficult to determine what exactly is being studied. Further, the specificity of the operational
definitions will allow future researchers to replicate the research study.
It is often a useful starting point in the writing of research questions to begin with one general
focus research question that flows from your research idea (see the examples in table 2.1.)
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Table 2.1 Examples of research ideas and their derived focus research questions
Research idea
General focus research questions
Advertising and share prices
How does the running of a TV advertising campaign
designed to boost the image of a company affect its
share price?
Job recruitment via the Internet
How effective is recruiting for new staff via the
Internet in comparison with traditional methods?
The use of Internet banking
What effect has the growth of Internet banking had
upon the uses customers make of branch facilities?
Once you've chosen a general research question, it is a good idea to think about the more specific
issues you'll have to examine in order to answer your general question.
Indeed, a research question could have been broken down further into sub problems. This sub
questions emanated from a research question are called investigative questions. These sub
problems form the nucleus of the research itself and must be directly addressed by the research
instrument, as they are the foundation for the research data collection instrument. Investigative
questions are questions the researcher must answer to satisfactorily arrive at a conclusion about
the research question.
2.6.2. Writing research objectives
Your research may begin with a general focus research question that then generates more
detailed research questions, or you may use your general focus research question as a base from
which you write a set of research objectives. Objectives are more generally acceptable to the
research community as evidence of the researcher‘s clear sense of purpose and direction.
We contend that research objectives are likely to lead to greater specificity than research or
investigative questions. Below you will find a table that illustrates this point. It summarizes the
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objectives of some research conducted by a students. Expression of the first research question as
an objective prompted a consideration of the objectives of the organizations.
Table 2.2 Phrasing research questions as research objectives
Maylor and Blackmon (2005) recommend that personal objectives may be added to the list of
research objectives. These may be concerned with your specific learning objectives from
completion of the research (e.g. to learn how to use a particular statistical software package or
improve your word processing ability) or more general personal objectives such as enhancing
your career prospects through learning about a new field of your specialism.
Maylor and Blackmon suggest that such personal objectives would be better were they to pass
the well-known SMART test. That is the objectives are:
 Specific. What precisely do you hope to achieve from undertaking the research?
 Measurable. What measures will you use to determine whether you have achieved your
objectives? (e.g. secured a career-level first job in software design).
 Achievable. Are the targets you have set for yourself achievable given all the possible
constraints?
37

Realistic. Given all the other demands upon your time, will you have the time and
energy to complete the research on time?
 Timely. Will you have time to accomplish all your objectives in the time frame you have
set?
AN ILLUSTRATION
The technique of defining a problem outlined above can be illustrated for better understanding by
taking an example as under:
Let us suppose that a research problem in a broad general way is as follows:
―Why is productivity in Japan so much higher than in China‖?
In this form the question has a number of ambiguities such as: What sort of productivity is being
referred to? With what industries the same is related? With what period of time the productivity
is being talked about? In view of all such ambiguities the given statement or the question is too
much general to be amenable to analysis. Rethinking and discussions about the problem may
result in narrowing down the question to:
―What factors were responsible for the higher labor productivity of Japan‘s manufacturing
industries during the decade 1990 to 2000 relative to China‘s manufacturing industries?‖
This latter version of the problem is definitely an improvement over its earlier version for the
various ambiguities have been removed to the extent possible. Further rethinking and rephrasing
might place the problem on a still better operational basis as shown below:
―To what extent did labor productivity in 1990 to 2000 in Japan exceed that of China in respect
of 15 selected manufacturing industries? What factors were responsible for the productivity
differentials between the two countries by industries?‖
With this sort of formulation, the various terms involved such as ‗labor productivity‘,
‗productivity differentials‘, etc. must be explained clearly. The researcher must also see that the
necessary data are available. In case the data for one or more industries selected are not available
for the concerning time-period, then the said industry or industries will have to be substituted by
other industry or industries.
The suitability of the time-period must also be examined. Thus, all relevant factors must be
considered by a researcher before finally defining a research problem.
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2.7. SUMMARY
One of the most frustrating feelings in the world is to have an answer and wonder what the
question was. Unless problems are well defined, research may lead to this position. Only slightly
less frustrating is the feeling of having the right answer to the wrong question. Proper problem
definition can avoid this difficulty, but the difficulty is more likely to be avoided if many
alternatives are considered in the early stages of the formulation of the problem. Research ideas
can be identified from various sources such as personal interest, previous research, theories,
management or problem solving. We have also seen that in the process of articulating research
questions one should consider the SMART criteria.
1) Identify the components of research problem.
2) Discuss the major sources of research problem.
3) Briefly explain the steps in the technique involved in defining a problem.
4) Develop your own research problem. Then identify the research questions and the
research objectives related to the problem.
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3
The Research Proposal
3.0. Learning outcomes
By the end of this chapter you should be able to:
 Define Research Proposal;
 Explain characteristics, importance, types and purposes of research proposal;
 Discuss format and structure of the proposal; and
 Describe the contents of a proposal
3.1. Introduction
Research proposal is a written document of the research topic chosen. It is a plan of future
research and an explanation of how it will be achieved. The document is prepared for both
requesting authorization and funds to undertake a specific research project. It is an activity that
incorporates decisions made during early research-project planning phases of the study including
management-research question hierarchy and exploration. The proposal thus incorporates the
choices the investigator makes in the preliminary steps.
A proposal is as essential to successful research as an architect‘s drawing is to the construction of
a building. No one would start building a structure by rushing out to dig a hole in the ground for
the foundation without knowing in detail what the house will like when finished. Similarly, a
researcher should not start research undertaking without having a research proposal.
Writing a research proposal is a crucial part of the research process. If you are applying for
research funding, or if your proposal is going before an academic research committee, then you
will know that you will need to put a great deal of time into the preparation of your proposal.
However, even if the official need for a proposal is not so vital it is still a process that will repay
very careful attention. Other names for a proposal are prospectus, plan, outline, statement, and
draft. If you are asked to present any of these, you are asked to present a research proposal.
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3.2. What is Research Proposal?
A proposal is an individual or company‘s offer to produce a product or render a service to a
potential sponsor or buyer. It is a selling document; it is not a technical report. A proposal tells us
What, Why, how, Where, and to whom the research will be done. It must also show the benefit
of doing it. A proposal is also known as work plan, prospectus, outline, statement of intent, or a
draft plan.
3.3. The purposes of the research proposal
A research proposal serves the following major functions for the researcher and/or for the
sponsor of the project.
 Organizing your ideas
Writing can be the best way of clarifying our thoughts. This is a valuable purpose of the
proposal. Not only will it clarify your thoughts but it will help you to organize your ideas into a
coherent statement of your research intent. Your reader will be looking for this.
 Convincing your audience
However coherent your ideas and exciting your research plan, it counts for little if the proposal
reveals that what you are planning to do is simply not possible. As part of research methods
courses many tutors ask students to draft a research proposal. This is then discussed with the.
What usually happens is that this discussion is about how the proposed research can be amended
so that something more modest in scope is attempted.
Initially work that is not achievable in the given timescale is proposed. The student‘s task is to
amend initial ideas and convince the course instructor that the proposed research is achievable
within the time and other resources available.
 Contracting with your „client‟
If you were asked to carry out a research project for a commercial client or your own
organization it is unthinkable that you would go ahead without a clear proposal that you would
submit for approval. Acceptance of your proposal by the client would be part of the contract that
existed between you.
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 To demonstrate competency
It is also vital that your proposal convinces the reader that you have all the necessary skills to
carry out the proposed study. You do this by describing an appropriate and feasible research
method.
 To assess the genuineness of the research
A research proposal allows the sponsor to assess the sincerity of your purpose, the clarity of your
design, the extent of your background material, and your fitness for undertaking the project. The
proposal displays your discipline, organization, and logic. A poorly planned, poorly written, or
poorly organized proposal damages your reputation more than the decision not to submit one.
Depending on the type of research and the sponsors you have, various aspects of a standard
proposal design are emphasized. The proposal then provides a document the sponsor can
evaluate based on current organizational, scholastic, or scientific needs.
3.4. Characteristics of research proposal
The proposal will demonstrate whether you possess that quality. Your reputation as a researcher
more often than not rests squarely upon the quality of the proposal you submit. It is well,
therefore, to appreciate exactly what characteristics a proposal should have.
 A proposal is a straightforward document.
Whatever does not contribute directly to the delineation of the problem and its solution must be
eliminated. Remember the architect‘s drawing: clean, clear, and economical. It contains all that
is necessary; not one details more.
 A proposal is not a literally production.
An architect‘s drawing is no a work of art; a proposal is not a ―literally‖ production. The
mission of neither is to be artistic; the purpose of both is to communicate clearly. It provides no
opportunity for fine writing, for literally composition, for verbal extravagance. The language
must be clear, precise, and sharp. A proposal provides a chance to show with what ultimate
clarity and precision the researcher can state a problem, delineate the treatment of the data, and
establish the logical validity of a conclusion.
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 A proposal is clearly organized.
Organization and outline are absolutely essential. They hint at an orderly and disciplined mind –
one of the highest tributes to a researcher‘s qualification.
3.5. Types of research proposal
Depending on the type of project, the sponsoring individual or institution, and the cost of the
project, different levels of complexity are required for a proposal to be judged complete. For
example the government agencies demand the most complex proposals for their funding
analyses. On the other extreme, an exploratory study done within a manager‘s department may
need merely a one- to three-page memo outlining the objectives, approach, and time allotted to
the project.
In general, business proposals can be divided between those generated internally and externally.
An internal proposal is done for the corporation by staff specialists or by the research department
of the firm. External proposals are either solicited or unsolicited. Sponsors can be university
grant committees, government agencies, government contractors, corporations, and so forth.
With few exceptions, the larger the project, the more complex is the proposal. In public sector
work, the complexity is generally greater than in a comparable private sector proposal.
There are three general levels of complexity. The exploratory study is the first, most simple
business proposal. More complex and common in business is the small-scale study-either an
internal study or an external contract research project.
Now let us discuss the difference between internal proposal & external proposals.
3.5.1. Internal Proposals
Internal proposals are a memo from the researcher to management outlining the problem
statement, study objectives, research design, and schedule is enough to start an exploratory
study. Privately and publicly held firms are concerned with how to solve a particular problem,
make a decision, or improve an aspect of their business. Seldom do businesses begin research
studies for other reasons. In the small-scale proposal, the literature review and bibliography are
consequently not stressed and can often be stated briefly in the research design.
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Since management insists on brevity, an executive summary is mandatory for all but the most
simple of proposals (projects that can be proposed in a two-page memo do not need an executive
summary). Schedules and budgets are necessary for funds to be committed. For the smaller-scale
projects, descriptions are not required for facilities and special resources, nor is there a need for a
glossary. Since small projects are sponsored by managers familiar with the problem, the
associated jargon, requirements, and definitions should be included directly in the text. Also, the
measuring instrument and project management modules are not required. Managers will typically
leave this detail for others.
3.5.2. External Proposals
An external proposal is either solicited or unsolicited. A solicited proposal is often in response to
a request for proposals (RFP).The proposals likely competing against several others for a
contract or grant. An unsolicited proposal has the advantage of not competing against others but
the disadvantage of having to speculate on the ramifications of a problem facing the firm‘s
management. Even more difficult, the writer of an unsolicited proposal must decide to whom the
document should be sent.
The most important sections of the external proposal are the objectives, design, qualifications,
schedule and budget. The executive summary of an external proposal may be included within the
letter of transmittal. As the complexity of the project increases, more information is required
about project management, the facilities and special resources. In contract research, the results,
and objectives sections are the standards against which the completed project is measured. As we
move toward government-sponsored research particular attention must be paid to each
specification in the RFP.
3.6. The content of the research proposal
You should only begin to write your proposal when you are confident that you can answer
"YES" to the following five questions:
1. Have you read broadly and deeply in the area of your research topic?
2. Have you spent time thinking critically about the research topic?
3. Have you spent time discussing your research topic with others?
4. Have you found out how people in other disciplines think about your research topic?
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5. Do you feel ready to begin writing your research proposal?
Remember, if you start writing too soon, you will be forced to stop and go back to the initial
steps, perhaps changing the topic or redefining the title or redefining the problem, etc.
If you decide to write the proposal, you have to prepare checklist of items, which are included in
your writing proposal. The common checklist items include the preliminaries, the body and the
supplemental sections. The contents of research proposal are discussed under this section.
There is no single format for research proposals. This is because every research project is
different. Different disciplines, donor organizations and academic institutions all have different
formats and requirements. In some cases, the sponsor of a given research decides and presents a
format for the presentation of the proposal in the RFP. This is the case in most solicited external
proposals. In other cases, the format or structure of the proposal is determined by the researcher
himself/herself.
Proposal follows a simple logical form of presentation. Although there are many ways to
arrange the items within the proposal, the following is the outline of the proposal with three
major parts that students shall follow. The following serves as a checklist of items in your
writing of a proposal.
I.
II.
III.
The Preliminaries
The Body
The Supplemental
I. The Preliminaries
 Title or Cover page
 Table of contents
 Abstract
II. The Body
1. The problem and its Approach
 Introduction
 Statement of the Problem
 Objectives of the Study
 Significance of the Study
 Scope/delimitation of the Study
 Definition of Used Terms
 Research Methodology
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 Organization of the Study
2. Review of the Related Literature
III. The Supplemental
 Budget and Schedule
 Bibliography
 Appendices
The contents of a proposal are described in the following manner.
I.
The Preliminaries
 Title
The title page is the ―main gate‖ of the research proposal, which invites the reader to enter the
research proposal. It is the most widely read part of the proposal. Many people who may not
necessarily read the proposal itself or even its abstract will read the title. It should be long
enough to be explicit but not too long so that it is not too tedious-usually between 15 and 25
words. It should contain the key words-the important words that indicate the subject.
Titles may sometimes be too short to be clear. For instance, the title ‗promotion and businesses‘
may suffice as a textbook title but it needs to be explicit and say more if it is to serve usefully as
a research title. On the other hand, titles may be too long to be readily and easily compressible.
Excessive length in titles is often attributable to ‗waste‘ or ‗fat‘ words such as ‗an investigation
on…‘ or ‗studies to examine…‘ and the use of the words that should appear in the main text.
An effective title not only picks the reader's interest, but also predisposes him/her favorably
towards the proposal. It must be chosen based on the criteria: the relevance it has, the feasibility of
undertaking the study, the applicability of the research result, and the cost-effectiveness.
It should be concise and descriptive. For example, the phrase, "An investigation of . . ." can be
omitted. The very fact you are undertaking research implies you are investigating or analyzing.
Whenever possible think of an informative and catchy title.
Kinds of Title
A title can be in the form of Hanging, Question, or Indicative.
a) Indicative Title: -This type of title states the subject of the research (proposal) rather than
the expected outcome.
E.g., ‗The Role of Promotion for Business Success in the Banking Industry of Ethiopia‘
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b) Hanging Title: - The hanging title has two parts: a general first part followed by a more
specific second part. It is useful in rewording an otherwise long, clumsy and
complicated indicative title.
E.g., ‗Business Success in the Banking Industry of Ethiopia: The Impact of Promotion.‘
c) Question Title: - Question title is used less than indicative and hanging titles. It is,
however, acceptable where it is possible to use few words - say less than 15 words.
E.g., ‗Does Promotion affects Business Success in the Banking Industry of Ethiopia?‘
The title should express the main message of the research topic; be short; be clearly and precisely
formulated; exciting; appealing.
The title page should contain;
 the title of the research project
 name of the principal researcher
 name and address of the institution of the principal researcher
 telephone number, fax number, and e-mail address of the principal researcher(s)
 Name(s) of the scientific collaborator(es) (e.g. supervisors, advisor)
 Name(s) and address(es) of the institution(s) of the scientific collaborator(s
 Date of submission of the research proposal (month and year)
The curriculum vitae of the principal researcher should be included in the appendix of the
research proposal.
The process of focusing a topic takes practice, so be patient with yourself. It is challenging when
you don't know too much about a topic. It will get easier as your knowledge base increases.
Remember that the research process is a recursive one, which means that you may need to revisit
your topic choice more than once if you find it, doesn't work out.
EXAMPLE
TSUNAMI Not a good focus question - too broad
TSUNAMI IN JAPAN Improving, but still too wide a theme to research
TSUNAMI IN SOUTH EAST JAPAN A more limited title. Workable, but could be improved.
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THE 2011 G.C TSUNAMI IN SOUTH EAST JAPAN –this title is quite specific. It will make
research a lot easier as it narrows down the field by both time and place. It could in fact be made
more specific by relating it to a particular group - eg. residents or investors.
 Table of Contents
The table of contents outlines the structure of the research proposal. The headings and
subheadings are structured and numbered, and the appropriate page numbers appear at the righthand margin. The headings of the table of contents are identical to those in the body of the
report.
 Abstract
An abstract is known by different names like executive summary, synopsis, epitome, and so on.
It gives executives the chance to grasp the essentials of the proposal without having to read the
details. It should also include a brief statement of the problem, the research objectives/research
question(s), and the benefits of your approach. The purpose of the abstract is to summarize in
preferably less than 200 words all-important parts of the research proposal.
An effective abstract should present highlight, of the main aspects of the proposal concisely and
clearly. A good informative abstract starts by stating the problem to be solved through the
purpose, expected outcomes, beneficiaries, expected impact of the work being proposed and the
methods to be used.

To summarize the abstract should:

Describe the problem (management dilemma and management questions) and
general objective/research questions of the study;

Importance of the research

Describe the methodology including sampling design;

Summarize the total time and budget necessary to carry out the research.
II.
The Body
 Background or Introduction
This is an important part of the proposal. It should tell the reader why you feel the research that
you are planning is worth the effort. This may be expressed in the form of a problem that needs
solving or something that you find exciting and has aroused your curiosity. The reader will be
48
looking for evidence here that there is sufficient interest from you to sustain you over the long
months (or years) ahead.
This is also the section where you will demonstrate your knowledge of the relevant literature.
Moreover, it will clarify where your proposal fits into the debate in the literature. You will be
expected to show a clear link between the previous work that has been done in your field of
research interest and the content of your proposal. In short, the literature should be your point of
departure. This is not the same as the critical literature review you will present in your final
project report. It will just provide an overview of the key literature sources from which you
intend to draw.
The main purpose of the background is to provide the necessary context for your research
problem. Convince readers that the problem exists and it is critical, needs research. Perhaps one
may state the management dilemma.
The introduction should start with a clearly articulated statement to make the reviewer or sponsor
interested in supporting the problem. The study should show how it fits into a larger field or
wider problem. The impact of the research will not be seen unless a clearly visible problem
exists and is clearly articulated.
The problem statement must not be long. Often many of the details given in this part are
common knowledge and amount to ‗fat‘ that detract from the essence of the problem. Informed
reviewers will already be familiar with much of the background information, so it is advisable to
go straight to aspects that will be new and that add value to the problem statement.
It is also important to state who the target beneficiaries are and how they will benefit from the
proposed project. It should highlight how the study will contribute to solving a particular
problem or minimizing its effect.
 Statement of the problem
The problem statement is the guiding theme of the proposal. This section of the proposal presents
the management question and the resulting research questions/research objectives. The statement
of the problem shouldn‘t leave any room for ambiguity. It should be clear and well articulated.
Make sure that the problem is well defined and it lends itself to empirical justification.
The research questions or research objectives should be specific and fact oriented. The problem
statement contains the need for the research project. The problem is usually represented by a
49
management question or originating question followed by a more detailed set of objectives.
In this part of your work, you have to explain what the problem is all about. Problem statement
must do better than produce merely a splutter of wordy and meaningless fragments. Thus, if you
know the problem, state it clearly. Each word of the problem should be expressive, sharp,
indispensable, and definitive. Always state the problem in a complete grammatical sentence.
Your problems should be stated so well, in fact, that anyone, anyone (who understands English)
could read it, understand it, and react to it without benefit of your presence. If, for any reason,
your problem is not stated with such clarity, then you are merely deceiving yourself that you,
yourself know what the problem is. Such deception will cause trouble later on you.
The selection of the research problem doesn‘t put the researcher in a position of what data to
collect, how to collect, and analyze. There is a need to state a specific problem, which will be
investigated by scientific research. The purpose of the study should be exposed clearly and
briefly to depend on theoretical framework. The research problem must be researchable and it
must lend itself to empirical testing. There should not be any room for ambiguity in statement of
the problem. Clarity in statement of the problem is important for the following three basic
reasons.
A.
It is the foundation for the development of research problems which are
necessary for securing funds.
B.
It enables the researcher to describe the problem practically, to think about its
importance, its priority and to point out all the necessary points.
C.
It provides the researcher with the basis for the discussion with people in the
community, the relevant government agency, and/or the potential funding agency.
 Objectives of the study
This section addresses the purpose of the investigation. It is here that you layout exactly what is
being planned by the proposed research. In a descriptive study, the objectives can be stated as the
research question. Recall that the research question can be further broken down into investigative
questions. If the proposal is for a causal study, then the objectives can be restated as a
hypothesis. The objectives module flows naturally from the problem statement, giving the
sponsor specific, concrete, and achievable goals. It is best to list the objectives either in order of
importance or in general terms first, moving to specific terms (i.e., research question followed by
underlying investigative questions).
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The general objective provides a short statement of the scientific goal being pursued by the
research. The specific objectives, on the other hand, are operational in nature. They may
indicate specific types of knowledge to be produced, certain audiences to be reached, etc. The
research objectives section is the basis for judging the remainder of the proposal and, ultimately,
the final report. It is also important to distinguish the specific objectives from the means of
achieving them, such as pursuing fieldwork, organizing a workshop, or publishing a book.
An objective for a research/proposal should be SMART; i.e., Specific, Measurable, Achievable,
Realistic, and Time-bound.
It must flow logically and clearly from the purpose, problem
statement and justification already stated.
 Importance/ Benefits of the Study
This section allows you to describe explicit benefits that will accrue from your study. The
importance of ―doing the study now‖ should be emphasized. Usually, this section is not more
than a few paragraphs. If you find it difficult to write, then you have probably not understood the
problem adequately. Return to the analysis of the problem and ensure, through additional
discussions with your sponsor or your research team, or by a reexamination of the literature, that
you have captured the essence of the problem. The importance/benefits section is particularly
important to the unsolicited external proposal. You must convince the sponsoring organization
that your plan will meet its needs.
In this section, the researcher indicates the importance of the research and there by convinces the
reader.
The researcher is, thus, required to indicate what his/her research will contribute;
whether the research is to provide solution or to shed light on the nature of the problem or both.
The significance of the study is usually stated as follows. The purpose of the research is:

to shed light on the nature of the problem

to give solutions to the problem

to extend the frontiers of knowledge

to enrich the literature
The importance/benefits section is particularly important to the unsolicited external proposal.
You must convince the sponsoring organization that your plan will meet its needs.
 Scope/Delimitation of the Study
Delimitation is made to provide information for decision-making using the available resources.
The purpose is to make the research manageable not to minimize effort and get relief. We need
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the wider but at the same time manageable scope, there must be a trade-off between the two.
Naturally, delimitation starts from the topic/problem of the research. There can also be time and
area/coverage boundaries.
In this section, the researcher indicates the boundary of the study. The problem should be
reduced to a manageable size. The rule is ―Don‘t bite more than what you can chew.‖ The
motto of the researcher is ―This one thing I do; this one area I investigate; this one question I
attempt to answer, this one problem I aim to solve.‖ Delimitation is done to solve the problem
using the available financial, labor and time resources. This does not, however, mean that we
should delimit the research topic to a particular issue and/or organization or place because it is
less costly and take less time. Delimiting is done not to necessarily reduce the scope of the study
for the sake of minimizing the effort to be exerted. This means that we should not sniff the life of
the topic in the name of making it manageable. Thus, there should be balance between
manageability and representativeness of the universe being studied. See the following example.
The findings of the research would be more fruitful if it were conducted widely by including
other similar firms. But, due to time, labour, and money constraints it would be too tedious and
out of the reach of the (student) researcher to include all firms.

Limitations
Limitations are difficulties the researcher faced during doing the research. Even though the
researcher designs and plans his/her study carefully, there could still be certain constraints that
might hinder the researcher form doing the research as it should be. The sources of limitations
could be weakness of methodology, availability of financial resources; time constraints; lack of
books, journals, and the like literatures; lack of cooperation; etc. Any problem encountered and
interfered with carrying out the research should be indicated frankly.
This is usually written after the work is completed because it is known only then. Thus, it is not
usually indicated in the proposal. However, it is possible to indicate limitations expected and
solutions envisaged.

Definition of used Terminologies (Terms)
Many research works include some technical words. Thus, terms must be defined so that it is
possible to know what precisely the terms used in the phrasing of the problem and used in the
body of the research mean.
As discussed in chapter1 terms must be defined operationally; i.e., the definition must interpret
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the term as it is employed in relation to the researcher‘s project. Sometimes students rely on
―dictionary definitions.‖ Dictionary definitions are seldom neither adequate nor helpful

Research Design/ Methodology
Up to now, you have told the sponsor what the problem is, what your study goals are, and why it
is important for you to do the study. The proposal has presented the study‘s value and benefits.
The design module describes what you are going to do in technical terms. This section should
include as many subsections as needed to show the phases of the project. Provide information on
your proposed design for tasks such as sample selection and size, data collection method,
instrumentation, procedures, and ethical requirements. When more than one way exists to
approach the design, discuss the methods you rejected and why your selected approach is
superior.
Research design contains at least five parts.
A. Sampling Design
The researcher explicitly defines the target population being studied and the sampling methods
used. Example: - probability or non-probability? If probability
 Simple random, stratified, cluster or systematic?
 How were the elements selected?
 How is the size determined?
 How much confidence we have?
 How much error was allowed?
Explanations of the sampling methods, uniqueness of the chosen parameters, or other points that
need explanation should be covered with brevity. Calculations should be placed in the appendix.
B. Data Collection
This part describes the specifics of gathering the data. It contents depend on the selected design.
Typically, you would include a discussion on the relevance of secondary data that guided these
decisions.
Again, detailed materials such as questionnaires or interview guide should be
included in the appendix.
C. Data Analysis
This section summarizes the methods used to analyze the data. The rationale for the choice of
analysis approaches should be clear. This section then describes data handling, preliminary
analysis, statistical tests, computer programs, and other technical information.
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D. Limitations
This section should be thoughtful presentation of significant methodology or implementation
problem. All research studies have their limitations, and sincere investigator recognizes that
readers need aid in judging the study‘s validity.
 Organization of the study
This section explains what each chapter of the research report consists of.
Consider the
following example:
The study will be organized into four chapters. The first chapter deals with the problem and its
approach. The second chapter will be concerned with presenting the review of the related
literature. The third chapter will treat the analysis of the data collected. The fourth chapter will
bring to an end to the study with summary, conclusion and recommendation.
2. Literature Review
i.
What is Literature review?
Although you might think of novels and poetry when you hear the word "literature," for a piece
of research the meaning is more specific. In terms of a literature review, "the literature" means
the works you consulted in order to understand and investigate your research problem. Following
are the different sources of literature; Journal articles, books, conference proceedings,
government and corporate reports, newspapers, theses and dissertations, Internet (electronic
journal), and magazines.
The literature review section examines recent (or historically significant) research studies,
company data, or industry reports that act as a basis for the proposed study. Begin your
discussion of the related literature and relevant secondary data from a comprehensive
perspective, moving to more specific studies that are associated with your problem. If the
problem has a historical background, begin with the earliest references.
Avoid the extraneous details of the literature; do a brief review of the information, not a
comprehensive report. Always refer to the original source. If you find something of interest in a
quotation, find the original publication and ensure you understand it. In this way, you will avoid
any errors of interpretation or transcription.
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Emphasize the important results and conclusions of other studies, the relevant data and trends
from previous research, and particular methods or designs that could be duplicated or should be
avoided. Discuss how the literature applies to the study you are proposing; show the weaknesses
or faults in the design, discussing how you would avoid similar problems. If your proposal deals
solely with secondary data, discuss the relevance of the data and the bias or lack of bias inherent
in it.
ii.
THE FUNCTIONS OF THE REVIEW OF LITERATURE
There are five functions of review of literature:
1. The conceptual frame of reference for the contemplated research.
2. An understanding of the status of research in problem area.
3. Clues to the research approach, method, instrumentation and data analysis.
4. An estimate of the probability of success of the contemplated research and the significance or
usefulness of the findings and, assuming the decision is made to continue.
5. Specific information required to interpret the definitions, assumptions, limitations and hypotheses
of research.
The detailed descriptions of these functions have been given in the following paras:
1. Conceptual Frame of Reference
The first function provides the conceptual framework of research which involves both conceptual and
research literature. The most direct way of doing this is to read the basic writings in the field as well as
the recent writings of key thinkers. The researcher must feel fully satisfied when he has completed this
phase of his view that he is aware of all the points of view in the field and particularly that he has devoted
himself diligently to learning about the points of view which differ from or are opposite to his own. All
points of view relevant to the research problem should be presented as strongly as the most devoted
proponents of that point of view would wish.
2. Status of Research
The second function of the review of the literature is to provide an understanding of the status of research
in the field. This comes from reviewing the research literature. This phase has several specific subfunctions which can be described in terms of the questions words: what, when, who and how. These four
words provide the basic information which reveals the status of the research in hand.
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First, through his review of the research literature the researcher learns what researchers have already
been undertaken and completed in the problem area and the results that this research has already
achieved. The unnecessary repetition can be avoided. Learning about research in progress is difficult to
locate. Within specific university or the experts of research degree committee can help in this direction.
The other aspect of what, learning the results of previous research, is the best known purpose of
reviewing the literature. After intensive review of conceptual and research literature in such an area, a
researcher may develop confidence that he has an explanation for the inconsistencies.
In addition to learning what has been done, the researcher seeks to identify when the research has been
done, specifically how current research has been done, specifically how current research in the problem
area is. There are periods of time in which a great deal of research is done in the problem area.
Learning when previous research has been conducted has several meanings for researcher:

It will determine how far back chronologically his review of the literature will follow.

When there is a wealth of recent research in the problem area.

When there has been a recent lack of interest in the field, he will need to go further back until he
comes upon the research.

Replication is sensible when a research study has provided the basis of some current belief that
the findings still hold true.
With ‗what and when‘ considered, let us consider the importance of ‗where‘, that is, identifying the
geographic areas in which the previous research has been completed. The major categories within this
classification are national, regional, and degree of urbanization.
Finally, we should have to consider who was studied. This means identifying the universes or populations
which have previously been studied, how they were sampled, and the extent of the sampling. Here the
researcher is interested in the broad general levels of universes studied, as well as in the specific
populations sampled.
One purpose of this consideration of the ‗who‘ of previous research is to enable the researcher to make a
judgment as to the relevance of a universe and population for his own research. Theoretically, he would
advise students not to plan to study those universes or populations which have already been sufficiently
studied in the problem area, either at the general or specific level. In reality, with the current status of
research in most problem areas in education and the social disciplines, this is not a difficulty as there are
no problem areas in which populations have been sufficiently studied.
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3. Research Approach, Method, Instrumentation and Data Analysis
This function of the review will serve the third function of providing clues of methodology and
instrumentation. Specifically, the researcher will want to learn the extent to which previous research in
the problem area has utilized the historical survey, or experimental approaches, because this will help to
guide his own choice of research approach. For this same reason, he will want to identify the research
methods which have been used so that experience with these can help him select his own. Finally, he
seeks to become familiar with the data-gathering instruments which have been used so that if an already
existing instrument is appropriate, it can be used intact or adapted for his own research.
Again, we must put in a realistic qualification. Most journals which report research do not print the actual
instruments. Often these do appear in the appendix of the complete research report or thesis or
dissertation on which many journal articles are based, or else can be obtained directly from the author of
the article. The simplest procedure is usually to contact the author directly, since in any event he will be
contacted for permission to use or adopt any instruments he has developed.
It is important to distinguish between what are generally considered standardized instruments and those
specially developed for some previous research project. Standardized instruments are those which have
been used widely enough for normative data to be available. The process of standardizing instruments
also provides data on reliability, and sometimes on the availability of the instrument. The availability of
these three kinds of data norms, estimate of reliability, and estimate of validity make standardized
instruments attractive to researchers, particularly to students doing research. These attractions are quite
real using an instrument with norms and established reliability does have great advantages when these
data have been obtained from samples from the same universe as we plan to study.
The discussion above on these first three functions of the review of the literature for survey and
experimental research should also imply what it is that the researcher is seeking as he reads. For the first,
or overview function, he is concerned with identifying each point of view and supporting arguments and
evidence for that point of view. For the second function, the status of research, he will do much more
structured and specific review, concerned with identifying what was studied, the outcomes of each study,
how the outcome of the several separate studies relate to each other, who had studied and where, and
when the research was done. For the third function, clues to methodology and instrumentation, he is
concerned with how the previous research was done and why it was done, the way it was.
In a sense, it is the combination of these first functions which yield the fourth and fifth functions of the
review of the literature.
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4.
Probability of Success and Significance of Findings
With the full body of the previous research reviewed, the researcher is in a position to evaluate the
success which others have had done research in the problem area and the usefulness of their findings.
If others have been successful and the findings are useful, then the prognosis for his own research is good,
and the decision to continue on with the research is clear and simple to make. However, if others have
been unsuccessful and produced inconclusive research or research of little value, then the researcher has a
more difficult to make decision. He must ask himself whether there are specific reasons to believe that he
can succeed where all others have failed. For the literature truly to serve this function of providing as
estimate of the success potential of the contemplated research, the researcher must be willing to make the
negative decisions to abandon or alter the project, as well as the positive ones to continue on as intended.
All too often in research, only lip service is paid to this function. Researchers do review the literature and
do seek to determine the success potential of their contemplated research, but never truly entertain the
possibility of altering or abandoning their plan. If no one has ever succeeded in doing what they plan, they
argue that they must be the first.
If the researcher has some new idea, some new method, some new instrument, which leads him to
believe he will succeed where all others failed, then he has every right to proceed. However, if he only
intends to try again what has never worked before, then he should seriously consider whether he can
reasonably accept to do any better than his predecessors. If not, he should devote his time, energy, and
ability to a research problem in which there is a greater likelihood of his making a positive professional
contribution.
5. Definitions, Assumptions, Limitations, and Hypotheses
After considering the literature the researcher can honestly conclude that there is a reasonable expectation
that he will successfully complete the contemplated research with results that will make a contribution of
his field. Then he will use the material from the literature as the basis for stating his definitions,
assumptions, limitations, and hypotheses. Having read the works presenting opinion and theory in the
problem area, and having reviewed the relevant research as well, the researcher should be thoroughly
familiar with the way in which terms have been used, both in the theoretical sense in the conceptual
literature, and in the more functional sense in the research literature. Thus, he should be able to formulate
the definitions for his contemplated project. Where possible and sensible, he should use the definitions
which have previously been used in the literature, because this is one way of making old and new
research comparable. Where necessary however, he is free to adapt previous definitions or formulate new
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ones. The essential point is that this be a knowledge decision made with full awareness of how key terms
have been used previously.
In the same way that the review of research makes the researcher aware of how terms have been used, it
(the conceptual review as well) should have made him aware of those aspects of the problem area which
have been so well demonstrated by previous research that they are widely accepted as true. He can use
these as the assumptions of his own research. Finally, he should have become sufficiently attuned to the
controversial or open-to-question aspects of the problem area. Then, as he plans his research, he can be
alert to which of these aspects he can or which he cannot handle in his own project. Those he cannot
handle will form the basis for the statement of limitations of the research.
His awareness of the results of previous research, and his knowledge of the current thinking in the field,
can now be combined with his own experience to produce the statement of the hypotheses, or expected
results of the research. In addition of identifying the expected outcomes of his study, the researcher
should identify the bases in the literature for each specific belief. In this way in both the outline and the
report of his project, he can state the rationale for each hypothesis, identifying the theorist, previous
research study, personal experience, or combination of these which leads him to expect this particular
result.
iii.
Types of Reviews
When beginning a review, researcher may decide on a topic or field of knowledge to examine, how much
depth to go into, and the kind of review to conduct. There are six types of review:
1. Self-study reviews increase the reader’s confidence. A review that only demonstrates familiarity with
an area is rarely published but it often is part of an educational program. In addition to giving others
confidence in a reviewer‘s command of field, it has the side benefit of building the reviewer‘s self
confidence.
2. Context reviews place a specific project in the big picture. One of the goals of review is creating a link
to a developing body of knowledge. This is a background or context review. It introduces the rest of a
research and establishes the significance and relevance of a research question. It tells the reader how a
project fits into the big picture and its implications for a field of knowledge. The review can summarize
how the current research continues a developing line of thought, or it can point to a question or
unresolved conflict in prior research to be addressed.
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3. Historical review traces the development of an issue over time. It traces the development of an idea or
shows how a particular issue or theory has evolved over time. Researchers conduct historical review only
on the most important ideas in a field.
4. Theoretical reviews compare how different theories address an issue. It presents different theories that
purport to explain the same thing, then evaluates how well each accounts for findings. In addition to
examining the consistency of predictions with findings, a theoretical review may compare theories for the
soundness of their assumptions, logical consistency, and scope of explanation. Researchers also use it to
integrate two theories or extend a theory to new issues. It sometimes forms a hybrid – the historical
theoretical review.
5. Integrative review summarizes what is known at a point in time. It presents the current state of
knowledge and pulls together disparate research reports in a fast growing area of knowledge.
6. Methodological reviews point out how methodology varies by study. In it researcher evaluates the
methodological strength of past studies It describes conflicting results and shows how different research
designs, samples, measures, and so on account for different results.
iv.
CONDUCTING A SYSTEMATIC LITERATURE REVIEW
 Define and refine a topic
Prior to the review of literature have a good idea of the topic of your interest. Although, the new thoughts
emerging out of the review of literature may help in refocusing the topic, still the researcher needs to have
some clear research question that could guide him/her in the pursuit of relevant material.
Therefore begin a literature review with a clearly defined, well focused research question and a plan. A
good review topic should be as focused as a research question. For example ―crime‖ as such may be too
broad a topic. A more focus may be a specific ―type of crime‖ or ―economic inequality and crime rates.‖
Often a researcher will not finalize a specific research question for a study until he or she has reviewed
the literature. The review helps bring greater focus to the research question.
 Design a search
The researcher needs to decide on the type of review, its extensiveness and the types of material to
include. The key is to be careful, systematic, and organized. Set parameters on your search; how much
time you will devote to it, how far back in time you will look, the maximum number of research reports
you will examine, how many libraries you will visit, and so forth. Also decide how to record the
bibliographic citations for each reference. May be begin a file folder or computer file in which you can
place possible sources and ideas for new sources.
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 Locate research reports
Locating research reports depends on the type of report or ―outlet‖ of research being searched. Use
multiple search strategies in order to counteract the limitations of single search method.
 Articles in Scholarly Journals. Most social and behavioral research is likely published in
scholarly journals. These journals are thee vehicles of communication in science. There are
dozens of journal, many going back decades, each containing many articles. Locating the relevant
articles is formidable task.
Many academic fields have ―abstracts‖ or ―indexes‖ for the scholarly literature. Find them in
reference section of the library. (Many available on compute as well). Such indexes and abstracts
are published regularly.
Another resource for locating articles is the computerized literature search. Researchers organize
computerized searches in several ways – by author, by article title, by subject, or by keyword. A
keyword is an important term for a topic that is likely to be found in a title. You will want to use
six to eight keywords in most computer based searches and consider several synonyms.
 Scholarly Books. Finding scholarly books on a subject can be difficult. The subject topics of a
library catalog systems are usually incomplete and too broad to be useful. A person has to be well
conversant with the library cataloging system.
 Dissertations. A publication called Dissertation Abstract International lists most dissertations. It
organizes dissertations by broad subject category, author, and date.
 Government Documents. The ―government documents‖ sections of libraries contain specialized
lists of government documents.
 Policy Reports and Presented Papers. The most difficult sources to locate are policy reports and
presented papers. They are listed in some bibliographies of published studies; some are listed in
the abstracts or indexes.
 Remember the purpose
You should use the literature to explain your research - after all, you are not writing a literature review
just to tell your reader what other researchers have done. Your aim should be to show why your research
needs to be carried out, how you came to choose certain methodologies or theories to work with, how
your work adds to the research already carried out, etc.
 Read with a purpose
You need to summarize the work you read but you must also decide which ideas or information are
important to your research (so you can emphasize them), and which are less important and can be covered
61
briefly or left out of your review. You should also look for the major concepts, conclusions, theories,
arguments etc. that underlie the work, and look for similarities and differences with closely related
work. This is difficult when you first start reading, but should become easier the more you read in your
area.
 Write with a purpose
Your aim should be to evaluate and show relationships between the works already done (Is Researcher
Y's theory more convincing than Researcher X's? Did Researcher X build on the work of Researcher Y?)
and between this work and your own. In order to do this effectively you should carefully plan how you
are going to organize your work.
 Review the literature; don‟t reproduce it!
The review of the literature section of a proposal or a dissertation is perhaps one of the most challenging
to write. It requires that you keep a clear focus on just what this section is intended to do. Many students
seem to think they have the opportunity to quote long passages from the literature, to cite at length the
words or ideas of others. More important is what you say about the study than what the author of the
study says in the study. Thus,
 present your own discussion;
 paraphrase, (précis, résumé, give synopsis, an epitome);
 use short direct quotations if necessary; and
 long direct quotations are the last resort. Use them only for a very good reason.
That is a sound advice. Too often students consider the literature discussion as a ―lift‖ from one place to
another. It is rather a digest, a précis, a résumé.
 Get the proper psychological orientation
Too many students consider the related literature as an unnecessary appendage standing in the way of
their real goal. They are eager ―to get on with the research.‖ To the contrary, a conscientious and
thorough review of the literature review related to the problem can open up to any researcher possibilities
of which he/she was unaware, can open his/her eyes to new ways of looking at the problem which he/she
totally missed.
 Emphasize relatedness
Keep your reader constantly aware of the manner in which the literature you are discussing is related to
your problem. Point out precisely what that relationship is. Do not forget yourself - and never permit
your reader to forget - that you are writing a review of the related literature.
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Too many discussions of the literature are nothing but a chain of pointless isolated summarizes of the
writings of others. Jones says… Smith says… Green says… This is the format students generally use.
This is also, perhaps, the worst form of a discussion of related literature. There is no discussion, no
attempt to demonstrate the relatedness of the literature to the problem being researched. Thus, whenever
you cite a study, make yourself account for that particular study in terms of the problem you are
researching.
 Summarize what you have said
Every discussion of literature and associated research relating to the problem under consideration should
end with a brief section in the form of a summary in which the author gathers up all that has been said and
set, important question that any researcher can ask and it should be asked continually throughout the
whole progress of the research study- is: Now, what does it all mean?
Too many studies end in a fuzzy blur of the discussion of the literature. At the end of the presentation and
processing of data in the research report, in the final summary of the research, one question is always
appropriate: ―What does it all mean?‖ one heading is always in order: the heading entitled, ―Summary.‖
 Keep Record
Another important skill to develop is that of keeping good records. Often you will remember reading
something but will not know where you read it. If you have kept a detailed record of your reading, you
should be able to track these "lost" references down. Make reference cards (as in the example below) to
keep detailed records of your reading.
Example: While reading any literature record the following
Research on: Individualism and collectivism at UUC
Author (s): Tewodros Meshesha
Year of Publication: 2006
Title of book or journal: Ethiopian Journal of Business &Development
Volume Number: Vol 1 No. 2
Publisher and City: Unity University College. Addis Ababa
Where available: UUC Library
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v.
Styles of referencing in the text
Preferred styles of referencing differ both between universities and between departments within
universities. Even styles that are in wide use such as ‗Harvard‘ vary in how they are used in practice by
different institutions. When this is combined with the reality that some lecturers apply an adopted style
strictly, whilst others are more lenient, it emphasizes the need for you to use the precise style prescribed
in your assessment criteria. Within business and management, two referencing styles predominate, the
Harvard style and the American Psychological Association (APA) style, both of which are author-date
systems. The alternative, numeric systems are used far less widely.
Four points are important when referencing:
 Credit must be given when quoting or citing other‘s work.
 Adequate information must be provided in the reference to enable that work to be located.
 References must be consistent and complete.
 References must be recorded using precisely the style required by your university.
1. The Harvard style
The Harvard style is an author-date system, a variation of which we use in this book. It appears to have it
origins in a referencing practice developed by a professor of anatomy at Harvard University (Neville
2007) and usually uses the author‘s name and year of publication to identify cited documents within the
text. All references are listed alphabetically at the end of the text. The Harvard style for referencing work
in the text is outlined in table 3.1
Table 3.1. Using the Harvard style to reference in the text
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65
2. The American Psychological Association (APA) style
The American Psychological Association style or APA style is a variation on the author date system. Like
the Harvard style it dates from the 1930s and 1940s, and has been updated subsequently. The latest
updates are outlined in the latest edition of the American Psychological Association‘s (2005) concise
rules of the APA style, which is likely to be available for reference in your university‘s library. Relatively
small but significant differences exist between the Harvard and APA styles, and many authors adopt a
combination of the two styles. The key differences are outlined in table 3.2 below.
Table 3.2 Key differences between Harvard and APA styles of referencing
3. Numeric systems
When using a Numeric system such as the Vancouver style, references within the project report are
shown by a number that is either bracketed or in superscript. This number refers directly to the list of
references at the end of the text, and it means it is not necessary for you to include the authors‘ names or
year of publication:
66
‗Research1 indicates that . . .‘
Table 3.3 Bibliographic Abbreviations
III. The Supplemental
The supplemental part of the research proposal has three sub sections
A). Schedule and Budget
Schedule
This will help you and your reader to decide on the viability of your research proposal. It will be helpful if
you divide your research plan into stages. This will give you a clear idea as to what is possible in the
given timescale. Experience has shown that however well the researcher‘s time is organized the whole
process seems to take longer than anticipated.
As part of this section of their proposal, many researchers find it useful to produce a schedule for their
research using a Gantt chart. Developed by Henry Gantt in 1917, this provides a simple visual
representation of the tasks or activities that make up your research project, each being plotted against a
time line. The time we estimate each task will take is represented by the length of an associated horizontal
1
Ritzer, G. The McDonaldization of Society. (revised edn). Thousand Oaks, CA, Pine
Forge Press; 1996.1
67
bar, whilst the task‘s start and finish times are represented by its position on the time line. The figure
below shows a Gantt chart for a student‘s research project.
KEY DATES:
1. Nov 1st: Submit proposal to tutor.
2. Jan 20th: Begin fieldwork.
3. March 1st: Complete fieldwork.
4. April 20th: Complete draft and hand in.
5. May 20th: Final submission.
Figure 3.2 Gantt chart for a research project
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Budget
The budget should include all projected expenditures. The budget is divided into sections such as
personnel (salaries, wages, fringe benefits), equipment, materials and supplies, printing and publication,
travel, rental or lease of facilities, other (utilities, phone, insurance, advertising), overhead, contingency,
Escalation, etc.
Overhead (indirect costs) covers the cost of administering the project, such as office space, administrative
personnel, etc. It is often a set percentage of the entire cost of the project, based on an agreement between
the sponsoring organization and the project. If the research project will take more than one year, an
adequate inflation rate has to be factored into the budget planning (growth).
B. Bibliography
For all projects that require literature review, a bibliography is necessary. Use the bibliographic format
required by the sponsor. If none is specified, standard styles that may be used include Harvard style,
APA style, and the Numeric style. Either of the three is correct. But keep consistency in your writing.
Referencing in the references or bibliography
The concluding section of a research paper, thesis, or dissertation is usually an alphabetical listing of
source materials. This list is generally entitled ―Bibliography‖. This list allows the reader to observe the
scope of the research behind the paper or to see if a particular work has been used. The bibliography may
also provide the reader with a foundation for further research.
The type of bibliography required for both undergraduate and graduate research papers is a list of works
cited in notes or within the text. Another type of bibliography goes beyond works actually cited in a paper
and includes all the works used in preparation for writing the paper.
Three categories of information are needed for each bibliography entry: author, title, and facts of
publication. Each of these categories may contain more than one piece of information. A book may have
more than one author, and the facts of publication for some materials may be complicated. A period
follows each category of information in a bibliography entry. i.e., a period follows the author the title, and
the facts of publication. Because an entry in a bibliography (unlike an entry in a note) refers to the
complete work rather than to a specific passage, a bibliography entry does not include page numbers. A
bibliography entry for an article lists the inclusive pages of the entire article rather than specific pages
from which material was selected for action.
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Table 3.4. Using the Harvard style to reference in the references or bibliography
70
Table 3.4. (Continued)
71
72
 Mathematical derivations
 Sample information
3.7. Criteria for a good Grant Proposal
Most funding agencies apply similar criteria to the evaluation of proposals. It is important to address these
criteria directly in your case for support. A proposal that fails to meet them will be rejected regardless of
the quality of its source.
Here are the major criteria against which your proposal will be judged. Read through your case for
support repeatedly, and ask whether the answers to the questions below are clear, even to a non-expert.
 Does the proposal address a well-formulated problem?
 Is it a research problem, or is it just a routine application of known techniques?
 Is it an important problem, whose solution will have useful effects?
 Do the proposers have a good idea on which to base their work? The proposal must explain the
idea in sufficient detail to convince the reader that the idea has some substance, and should
explain why there is reason to believe that it is indeed a good idea. It is absolutely not enough
merely to identify a wish-list of desirable goals (a very common fault). There must be significant
technical substance to the proposal.
 Does the proposal explain clearly what work will be done? Does it explain what results are
expected and how they will be evaluated? How would it be possible to judge whether the work
was successful?
 Is there evidence that the proposers know about the work that others have done on the problem?
This evidence may take the form of a short review as well as representative references.
 Do the proposers have a good track record, both of doing good research and of publishing it? A
representative selection of relevant publications by the proposers should be cited. Absence of a
track record is clearly not a disqualifying characteristic, especially in the case of young
researchers, but a consistent failure to publish raises question marks.
 Is the proposed research cost effective? The programme manager tries to ensure that his or her
budget is to be used in a cost-effective manner.
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Common Shortcomings
Here are some of the ways in which proposals often fail to meet these criteria.
 It is not clear what question is being addressed by the proposal. In particular, it is not clear what
the outcome of the research might be, or what would constitute success or failure. It is vital to
discuss what contribution to human knowledge would be made by the research.
 The question being addressed is woolly or ill-formed. The committee are looking for evidence of
clear thinking both in the formulation of the problem and in the planned attack on it (design).
 It is not clear why the question is worth addressing. The proposal must be well motivated.
 There is no evidence that the proposers will succeed where others have failed. It is easy enough to
write a proposal with an exciting-sounding wish-list of hoped-for achievements, but you must
substantiate your goals with solid evidence of why you have a good chance of achieving them.
 A new idea is claimed but insufficient technical details of the idea are given for the committee to
be able to judge whether it looks promising. Since the committee cannot be expert in all areas
there is a danger of overwhelming them with technical details, but it is better to err by
overwhelming them than by under whelming them. They will usually get an expert referee to
evaluate your idea.
 The proposers seem unaware of related research. Related work must be mentioned, if only to be
dismissed. Otherwise, the committee will think that the proposers are ignorant and, therefore, not
the best group to fund. The case for support should have a list of references like any paper, and
you should look at it to check it has a balanced feel - your referee will do so. Do not make the
mistake of giving references only to your own work!
 The proposed research has already been done - or appears to have been done. Rival solutions
must be discussed and their inadequacies revealed.
 The proposers seem to be attempting too much for the funding requested and time-scale
envisaged. Such lack of realism may reflect a poor understanding of the problem or poor research
methodology.
 The proposal is too expensive for the probable gain
3.8. Summary
Research proposal is an offer to conduct research. It is essential to success or it can be the main cause for
failure. Research proposal usually contains the preliminaries, the body and the supplemental. The
preliminaries are title or cover page, table of contents and abstract. The body part deals with the problem
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and its approach. The problem and its approach includes introduction, statement of the problem,
objectives of the study, significant of the study, delimitation of the study, definition of used terms,
research methodology and organization of the study. Review of literature includes the works of others of
others consulted in order to understand and investigate the research problem. The supplemental section
treats budget and schedule, bibliography and appendices.
1. What are the purposes of research proposal?
2. What are the major check list items in writing of research proposal?
3. What are the major forms of research title?
4. List out importance of research proposal.
5. Compare and contrast the Harvard and APA referencing styles?
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4
The Scientific Method
4.0.
Learning outcomes
 By the end of this chapter you should be able to:
 Define scientific Methods of research
 Describe the reasoning process
 Discuss terms like concepts and definitions
 Describe variables, attributes and theory
4.1.
Introduction
Research is conducted based on reasoning. Good researchers and good managers alike practice
habits of thought that reflect sound reasoning, finding correct premises, testing the connections
between their facts and assumptions, making claims based on adequate evidence. Drawing
supportable generalization from limited data is the product of extending the inference process to
statistical testing.
4.2.
Meaning and Features of the Scientific Method
4.2.1.
Meaning of Scientific Method of Research
Research produces knowledge which could be used for the solution of problems as well as for
the generation of universal theories, principles and laws. But all knowledge is not science. The
critical factor that separates scientific knowledge from other ways of acquiring knowledge is that
it uses scientific approach. What is this approach? Or what is science?
The word science has its origins in the Latin verb scire, meaning "to know." Although, one can
"know" through tenacity, authority, faith, intuition, or science, the method of science [or the
"scientific method"] is distinct in its notion of inter subjective certification. In other words, it
should be possible for other investigators to ascertain the truth content of scientific
explanation(s).
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Science is a way to produce knowledge, which is based on truth and attempts to be universal. In
other words science is a method, a procedure to produce knowledge i.e. discovering
universalities/principles, laws, and theories through the process of observation and reobservation. Observation here implies that scientists use ―sensory experiences‖ for the study of
the phenomena. They use their five senses, which are possessed by every normal human being.
They not only do the observation of a phenomenon but also repeat the observation, may be
several times. The researchers do so because they want to be accurate and definite about their
findings.
Re-observation may be made by the same researcher at a different time and place or done by
other professionals at some other time or place. All such observations are made in this universe
where a normal professional human being can go, make the observation and come back.
Therefore we are focusing on this universe not on the one hereafter. By repeating the
observation, the researchers want to be definite and positive about their findings. Those who
want to be definite and positive are often referred to as positivists. The researchers do not leave
their findings into scattered bits and pieces rather the results are organized, systematized, and
made part of the existing body of knowledge; and this is how the knowledge grows. All this
procedure for the creation of knowledge is called a scientific method, whereby the consequent
knowledge may be referred to as scientific knowledge. In this way science refers to both a
system for producing knowledge and the knowledge produced from that system.
The scientific method is the process by which scientists, collectively and over time; endeavor to
construct an accurate (that is, reliable, consistent and non-arbitrary) representation of the world.
The scientific method attempts to minimize the influence of bias or prejudice in the experimenter
when testing a hypothesis or a theory. The scientific method to research differs from other forms
of explanation because of its requirement of systematic process.
The scientific method is limited to those phenomena, which can be observed or measured. For
example, what existed prior to the known universe is outside of the realm of science to
investigate.
Science does not really explain why the Universe exists. Science is good at
explaining, "how things work" but not necessarily for explaining "why do such things exist" or
"for what purpose."
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4.2.2. Important Characteristics of Scientific Method
1. Empirical
Scientific method is concerned with the realities that are observable through ―sensory
experiences.‖ It generates knowledge which is verifiable by experience or observation. Some of
the realities could be directly observed, like the number of students present in the class and how
many of them are male and how many female. The same students have attitudes, values,
motivations, aspirations, and commitments.
These are also realities which cannot be observed directly, but the researchers have designed
ways to observe these indirectly. Any reality that cannot be put to ―sensory experience‖ directly
or indirectly (existence of heaven, the Day of Judgment, life hereafter, God‘s rewards for good
deeds) does not fall within the domain of scientific method.
2. Verifiable
Observations made through scientific method are to be verified again by using the senses to
confirm or refute the previous findings. Such confirmations may have to be made by the same
researcher or others.
We will place more faith and credence in those findings and conclusions if similar findings
emerge on the basis of data collected by other researchers using the same methods. To the extent
that it does happen (i.e. the results are replicated or repeated) we will gain confidence in the
scientific nature of our research. Replicability, in this way, is an important characteristic of
scientific method. Hence revelations and intuitions are out of the domain of scientific method.
3. Cumulative
Prior to the start of any study the researchers try to scan through the literature and see that their
study is not a repetition in ignorance. Instead of reinventing the wheel the researchers take stock
of the existing body of knowledge and try to build on it. Also the researchers do not leave their
research findings into scattered bits and pieces. Facts and figures are to be provided with
language and thereby inferences drawn. The results are to be organized and systematized.
Nevertheless, we don‘t want to leave our studies as stand alone. A linkage between the present
and the previous body of knowledge has to be established, and that is how the knowledge
accumulates. Every new crop of babies does not have to start from a scratch; the existing body of
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knowledge provides a huge foundation on which the researchers build on and hence the
knowledge keeps on growing.
4. Deterministic
Science is based on the assumption that all events have antecedent causes that are subject to
identification and logical understanding. For the scientist, nothing ―just happens‖ – it happens for
a reason. The scientific researchers try to explain the emerging phenomenon by identifying its
causes. Of the identified causes which ones can be the most important? For example, in the 2013
grade 10 Ethiopian School leaving Examination of region ABC 56 percent of the students failed.
What could be the determinants of such a mass failure of students? The researcher may try to
explain this phenomenon and come up with variety of reasons which may pertain to students,
teachers, administration, curriculum, books, examination system, and so on. Looking into such a
large number of reasons may be highly cumbersome model for problem solution. It might be
appropriate to tell, of all these factors which one is the most important, the second most
important, the third most important, which two in combination are the most important. The
researcher tries to narrow down the number of reasons in such a way that some action could
taken. Therefore, the achievement of a meaningful, rather than an elaborate and cumbersome,
model for problem solution becomes a critical issue in research. That is parsimony which implies
the explanation with the minimum number of variables that are responsible for an undesirable
situation.
5. Ethical and Ideological Neutrality
The conclusions drawn through interpretation of the results of data analysis should be objective;
that is, they should be based on the facts of the findings derived from actual data, and not on our
own subjective or emotional values. For instance, if we had a hypothesis that stated that greater
participation in decision making will increase organizational commitment, and this was not
supported by the results, it makes no sense if the researcher continues to argue that increased
opportunities for employee participation would still help. Such an argument would be based, not
on the factual, data based research findings, but on the subjective opinion of the researcher. If
this was the conviction of the researcher all along, then there was no need to do the research in
the first place.
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Researchers are human beings, having individual ideologies, religious affiliations, cultural
differences which can influence the research findings. Any interference of their personal likings
and disliking in their research can contaminate the purity of the data, which ultimately can affect
the predictions made by the researcher. Therefore, one of the important characteristics of
scientific method is to follow the principle of objectivity, uphold neutrality, and present the
results in an unbiased manner.
6. Statistical Generalization
Generalisability refers to the scope of the research findings in one organizational setting to other
settings. Obviously, the wider the range of applicability of the solutions generated by research,
the more useful the research is to users. For instance, if a researcher‘s findings that participation
in decision making enhances organizational commitment are found to be true in a variety of
manufacturing, industrial, and service organizations, and not merely in the particular
organization studied by the researcher, the generalizability of the findings to other organizational
settings is enhanced.
For wider generalizability, the research sampling design has to be logically developed and a
number of other details in the data collection methods need to be meticulously followed. Here
the use of statistics is very helpful. Statistics is device for comparing what is observed and what
is logically expected. The use of statistics becomes helpful in making generalizations, which is
one of the goals of scientific method.
7. Rationalism
Science is fundamentally a rational activity, and the scientific explanation must make sense.
Religion may rest on revelations, custom, or traditions, gambling on faith, but science must rest
on logical reason.
There are two distinct logical systems important to the scientific quest, referred to as deductive
logic and inductive logic. Beveridge describes them as follows:
Logicians distinguish between inductive reasoning (from particular instances to general
principles, from facts to theories) and deductive reasoning (from the general to the particular,
applying a theory to a particular case). In induction one starts from observed data and develops
a generalization which explains the relationships between the objects observed. On the other
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hand, in deductive reasoning one starts from some general law and applies it to a particular
instance.
The classical illustration of deductive logic is the familiar syllogism: ―All men are mortal; Dawit
is man; therefore Dawit is mortal.‖ A researcher might then follow up this deductive exercise
with an empirical test of Dawit‘s mortality.
Using inductive logic, the researcher might begin by noting that Dawit is mortal and observing a
number of other mortals as well. He might then note that all the observed mortals were men,
thereby arriving at the tentative conclusion that all men are mortal.
In practice, scientific research involves both inductive and deductive reasoning as the scientist
shifts endlessly back and forth between theory and empirical observations.
There could be some other aspects of scientific method (e.g. self correcting) but what is
important is that all features are interrelated. Scientists may not adhere to all these
characteristics. For example, objectivity is often violated especially in the study of human
behavior, particularly when human beings are studied by the human beings. Personal biases of
the researchers do contaminate the findings.
Finally it may be said that anybody who is following the scientific procedure of doing research is
doing a scientific research; and the knowledge generated by such research is scientific
knowledge. Depending upon the subject matter, we try to divide the sciences into physical or
natural sciences and the social sciences. Due to the nature of the subject matter of the social
sciences, it is rather very difficult to apply the scientific method of research rigorously and that is
why the predictions made by the social researchers are not as dependable as the predictions made
by the natural scientists.
4.3.
UNDERSTANDING THEORY :COMPONENTS AND
CONNECTIONS
When we do research, we seek to know ―what is‖ in order to understand, explain, and predict
phenomena. We might want to answer the question ―what will be the employee reaction to the
new flexible work schedule?‖
Or ―Does student-teacher interaction influence students‘
performance?‖ when dealing with such questions, we must agree on definitions. Which
employee? What kind of reaction? What is performance? These questions require the use of
concepts, constructs, and definitions. Later we will use variables and hypotheses to make
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statements and propose tests for relationship that our questions express. These components or
building blocks of theory are reviewed in the next few sections.
Concepts
If one is to understand and communicate information about objects and events, there must be a
common ground on which to do it. Concepts are used for this purpose. A concept is a
generalized idea about a class of objects, attributes, occurrences, or processes that has been given
a name. Such names are created or developed or constructed for the identification of the
phenomenon, be it physical or non-physical. All these may be considered as empirical realities
e.g. leadership, productivity, morale, motivation, inflation, happiness, banana.
Concepts are an Abstraction of Reality
Concepts are everywhere, and you use them all the time. Height is simple concept form everyday
experience. What does it mean? It is easy to use the concept of height, but describing the concept
itself is difficult. It represents an abstract idea about physical reality, or an abstraction of
reality. Height is a characteristic of physical objects, the distance from top to bottom. All people,
buildings, trees, mountains, books and so forth have height. The word height refers to an abstract
idea. We associate its sound and its written form with that idea. There is nothing inherent in the
sounds that make up the word and the idea it represents. The connection is arbitrary, but it is still
useful. People can express the abstract idea to one another using the symbols.
Concepts are the building block of a theory. Concepts abstract reality. That is, concepts are
expressed in words, letters, signs, and symbols that refer to various events or objects. For
example, the concept ―asset‖ is an abstract term that may, in the concrete world of reality, refer
to a specific punch press machine. Concepts, however, may vary in degree of abstraction and we
can put them in a ladder of abstraction, indicating different levels.
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Degree of Abstraction
Concepts vary in their level of abstraction. They are on a continuum from the most concrete to
the most abstract. Very concrete ones refer to straightforward physical objects or familiar
experiences (e.g. height, school, age, family income, or housing). More abstract concepts refer to
ideas that have a diffuse, indirect expression (e.g. family dissolution, racism, political power).
Moving up the ladder of abstraction, the basic concept becomes more abstract, wider in scope,
and less amenable to measurement. The scientific researcher operates at two levels: on the
abstract level of concepts (and propositions) and on the empirical level of variables (and
hypotheses). At the empirical level we ―experience‖ reality – that is we observe the objects or
events. In this example the reality has been given a name i.e. banana. Moving up the ladder this
reality falls in wider reality i.e. fruit, which in turn becomes part of further wider reality called as
vegetation.
Constructs
As it is stated above, concepts have different levels of abstraction. Some concepts correspond to
objective referents. Other concepts, like power and personality, are highly abstract and difficult
to visualize. Such abstract concepts are often called constructs.
A construct is an image or idea specifically invented for a given research and/or theory building
purpose. We build constructs by combining the simpler concepts, especially when the idea or
image we intend to convey is not directly subject to observation.
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Definitions
Confusion about the meaning of concepts can destroy a research study‘s value without the
researcher or client even knowing it. If words have different meanings to the parties involved,
then they are not communicating on the same wave-length. Definitions are one way to reduce
this danger. Researchers must struggle with two types of definitions: dictionary and operational
definitions.
Dictionary Definitions
Dictionary definitions are also called conceptual or theoretical or nominal definitions.
Conceptual definition is a definition in abstract, theoretical terms. It refers to other ideas or
constructs. There is no magical way to turn a construct into precise conceptual definition. It
involves thinking carefully, observing directly, consulting with others, reading what others have
said, and trying possible definitions.
A single construct can have several definitions, and people may disagree over definitions.
Conceptual definitions are linked to theoretical frameworks and to value positions. For example,
a conflict theorist may define social class as the power and property a group of people in a
society has or lacks. A structural functionalist defines it in terms of individual who share a social
status, life-style, or subjective justification. Although people disagree over definitions, the
researcher should always state explicitly which definition he or she is using.
Some constructs are highly abstract and complex. They contain lower level concepts within them
(e.g. powerlessness), which can be made even more specific (e.g. a feeling of little power over
wherever on lives). Other concepts are concrete and simple (e.g. age). When developing
definitions, a researcher needs to be aware of how complex and abstract a construct is. For
example, a concrete construct such as age is easier to define (e.g. number of years that have
passed since birth) than is a complex, abstract concept such as morale.
Operational Definition
In research we must measure concepts and constructs, and this requires more rigorous
definitions. A concept must be made operational in order to be measured. An operational
definition gives meanings to a concept by specifying the activities or operations necessary to
measure it. An operational definition specifies what must be done to measure the concept under
investigation. It is like a manual of instruction or a recipe: do such-and-such in so-and-so
manner.
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Operational definition is also called a working definition stated in terms of specific testing or
measurement criteria. The concepts must have empirical referents (i.e. we must be able to count,
measure, or in some other way gather thee information through our senses). Whether the object
to be defined is physical e.g. a machine tool) or highly abstract (e.g. achievement motivation),
the definition must specify characteristics and how to be observed. The specification and
procedures must be so clear that any competent person using them would classify the objects the
same way. So in operational definition we must specify concrete indicators that can be
observed/measured (observable indicators).
VARIABLES
Scientists operate at both theoretical and empirical levels. At the theoretical level, there is a
preoccupation with identifying constructs and their relations to propositions and theory. At this
level, constructs cannot, as we said it before, be observed. At the empirical level where the
propositions are converted in to hypotheses and testing occurs, the scientist is likely to be dealing
with variables. In actual practice, the term variable is used by scientists and researchers as a
synonym for construct or the thing being studied.
A variable is defined as anything that varies or changes in value. Variables take on two or more
values. Because variable represents a quality that can exhibit differences in value, usually
magnitude or strength, it may be said that a variable generally is anything that may assume
different numerical or categorical values. Once you begin to look for them, you will see variables
everywhere.
For example gender is a variable; it can take two values: male or female. Marital status is a
variable; it can take on values of never married, single, married, divorced, or widowed. Family
income is a variable; it can take on values from zero to billions of Birr. A person‘s attitude
toward women empowerment is variable; it can range from highly favorable to highly
unfavorable. In this way the variation can be in quantity, intensity, amount, or type; the examples
can be production units, absenteeism, gender, religion, motivation, grade, and age. A variable
may be situation specific; for example gender is a variable but if in a particular situation like a
class of Research Methods if there are only female students, then in this situation gender will not
be considered as a variable.
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Types of Variable
I.
Continuous and Discontinuous variables
Variables have different properties and to these properties we assign numerical values. If the
values of a variable can be divided into fractions then we call it a continuous variable. Such a
variable can take infinite number of values. Income, temperature, age, or a test score are
examples of continuous variables. These variables may take on values within a given range or, in
some cases, an infinite set.
Any variable that has a limited number of distinct values and which cannot be divided into
fractions, is a discontinuous variable. Such a variable is also called as categorical variable or
discrete variable. Some variables have only two values, reflecting the presence or absence of a
property: employed-unemployed or male-female have two values. These variables are referred to
as dichotomous. There are others that can take added categories such as the demographic
variables of race or religion. All such variables that produce data that fit into categories are said
to be discrete/categorical/classificatory, since only certain values are possible. An automotive
variable, for example, where ―Chevrolet‖ is assigned a 5 and ―Honda‖ is assigned a 6, provides
no option for a 5.5 (i.e. the values cannot be divided into fractions).
II.
Dependent and Independent Variables
Researchers who focus on causal relations usually begin with an effect, and then search for its
causes.
The cause variable, or the one that identifies forces or conditions that act on something else, is
the independent variable. The variable that is the effect or is the result or outcome of another
variable is the dependent variable (also referred to as outcome variable or effect variable). The
independent variable is ―independent of‖ prior causes that act on it, whereas the dependent
variable ―depends on‖ the cause.
It is not always easy to determine whether a variable is independent or dependent. Two questions
help to identify the independent variable. First, does it come before other variable in time?
Second, if the variables occur at the same time, does the researcher suggest that one variable has
an impact on another variable? Independent variables affect or have an impact on other variables.
When independent variable is present, the dependent variable is also present, and with each unit
of increase in the independent variable, there is an increase or decrease in the dependent variable
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also. In other words, the variance in dependent variable is accounted for by the independent
variable.
In statistical analysis a variable is identified by the symbol (X) for independent variable and by
the symbol (Y) for the dependent variable. In the research vocabulary different labels have been
associated with the independent and dependent variables like:
Research studies indicate that successful new product development has an influence on the stock
market price of a company. That is, the more successful the new product turns out to be, the
higher will be the stock market price of that firm. Therefore, the success of the new product is
the independent variable, and stock market price the dependent variable.
The degree of perceived success of the new product developed will explain the variance in the
stock market price of the company. It is important to remember that there are no preordained
variables waiting to be discovered ―out there‖ that are automatically assigned to be independent
or dependent. It is in fact the product of the researcher‘s imagination demonstrated convincingly.
III.
Moderating Variables
A moderating variable is one that has a strong contingent effect on the independent variabledependent variable relationship. That is, the presence of a third variable (the moderating
variable) modifies the original relationship between the independent and the dependent variable.
For example, a strong relationship has been observed between the quality of library facilities (X)
and the performance of the students (Y). Although this relationship is supposed to be true
generally, it is nevertheless contingent on the interest and inclination of the students. It means
that only those students who have the interest and inclination to use the library will show
improved performance in their studies. In this relationship interest and inclination is
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moderating variable i.e. which moderates the strength of the association between X and Y
variables.
IV.
Intervening Variables
A basic causal relationship requires only independent and dependent variable. A third type of
variable, the intervening variable, appears in more complex causal relationships. It comes
between the independent and dependent variables and shows the link or mechanism between
them. Advances in knowledge depend not only on documenting cause and effect relationship but
also on specifying the mechanisms that account for the causal relation. In a sense, the intervening
variable acts as a dependent variable with respect to independent variable and acts as an
independent variable toward the dependent variable.
A theory of suicide states that married people are less likely to commit suicide than single
people. The assumption is that married people have greater social integration (e.g. feelings of
belonging to a group or family). Hence a major cause of one type of suicide was that people
lacked a sense of belonging to group (family). Thus this theory can be restated as a three-variable
relationship: marital status (independent variable) causes the degree of social integration
(intervening variable), which affects suicide (dependent variable). Specifying the chain of
causality makes the linkages in theory clearer and helps a researcher test complex relationships.
Look at another finding that five-day work week results in higher productivity. What is the
process of moving from the independent variable to the dependent variable? What exactly is that
factor which theoretically affects the observed phenomenon but cannot be seen? Its effects must
be inferred from the effects of independent variable on the dependent variable. In this work-week
hypothesis, one might view the intervening variable to be the job satisfaction. To rephrase the
statement it could be: the introduction of five-day work week (IV) will increase job satisfaction
(IVV), which will lead to higher productivity (DV).
V.
Extraneous Variables
An almost infinite number of extraneous variables (EV) exist that might conceivably affect a
given relationship. Some can be treated as independent or moderating variables, but most must
either be assumed or excluded from the study. Such variables have to be identified by the
researcher. In order to identify the true relationship between the independent and the dependent
variable, the effect of the extraneous variables may have to be controlled. This is necessary if we
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are conducting an experiment where the effect of the confounding factors has to be controlled.
Confounding factors is another name used for extraneous variables.
Attribute
An attribute is a specific value on a variable. For instance, the variable sex or gender has two
attributes: male and female. Or, the variable agreement might be defined as having five
attributes:
1 = strongly disagree
2 = disagree
3 = neutral
4 = agree
5 = strongly agree
Propositions and Hypothesis
We define propositions as statements about concepts which may be judged as true or false. If the
phenomenon under consideration happens to be observable reality then the said statement could
be empirically tested. A proposition that can be verified to determine its reality is a hypothesis.
Therefore one can say that a hypothesis is a verifiable counterpart of a proposition.
A hypothesis may be defined as a logically conjectured relationship between two or more
variables, expressed in the form of a testable statement. Relationship is proposed by using a
strong logical argumentation. This logical relationship may be part of theoretical framework of
the study.
Types of Hypotheses
i. Descriptive Hypothesis
Descriptive hypothesis contains only one variable thereby it is also called as univariate
hypothesis. Descriptive hypotheses typically state the existence, size, form, or distribution of
some variable. For example the hypothesis ―officers in my organization have higher than
average level of commitment‖
contains only one variable. It only shows the distribution of the level of commitment among the
officers of the organization which is higher than average. Such a hypothesis is an example of a
Descriptive Hypothesis.
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Researchers usually use research questions rather than descriptive hypothesis. For example a
question can be: What is the level of commitment of the officers in your organization?
ii. Relational Hypothesis
These are the propositions that describe a relationship between two variables. The relationship
could be non-directional or directional, positive or negative, causal or simply co relational.
While stating the relationship between the two variables, if the terms of positive, negative, more
than, or less than are used then such hypotheses are directional because the direction of the
relationship between the variables (positive/negative) has been indicated as in the following two
hypotheses.
 Level of job commitment of the officers is positively associated with their level of
efficiency.
 The higher the level of job commitment of the officers the lower their level of
absenteeism.
These hypotheses are relational as well as directional. The directional hypothesis is the one in
which the direction of the relationship has been specified.
Non-directional hypothesis is the one in which the direction of the association has not been
specified. The relationship may be very strong but whether it is positive or negative has not been
postulated as follows:
 Level of job commitment of the officers is associated with their level of efficiency.
iii. Null Hypothesis
It is used for testing the hypothesis formulated by the researcher. Researchers treat evidence that
supports a hypothesis differently from the evidence that opposes it. They give negative evidence
more importance than to the positive one. It is because the negative evidence tarnishes the
hypothesis. It shows that the predictions made by the hypothesis are wrong. The null hypothesis
simply states that there is no relationship between the variables or the relationship between the
variables is ―zero.‖ That is how symbolically null hypothesis is denoted as ―H0‖. For example:
H0 = There is no relationship between the level of job commitment and the level of efficiency. Or
H0 = The relationship between level of job commitment and the level of efficiency is zero. Or
The two variables are independent of each other.
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It does not take into consideration the direction of association (i.e. H0 is non directional), which
may be a second step in testing the hypothesis. First we look whether or not there is an
association then we go for the direction of association and the strength of association. Experts
recommend that we test our hypothesis indirectly by testing the null hypothesis. In case we have
any credibility in our hypothesis then the research data should reject the null hypothesis.
Rejection of the null hypothesis leads to the acceptance of the alternative hypothesis.
iv. Alternative Hypothesis
The alternative (to the null) hypothesis simply states that there is a relationship between the
variables under study. In our example it could be: there is a relationship between the level of job
commitment and the level of efficiency. Not only there is an association between the two
variables under study but also the relationship is perfect which is indicated by the number ―1‖.
Thereby the alternative hypothesis is symbolically denoted as ―H1‖. It can be written like this:
H1: There is a relationship between the level of job commitment of the officers and their level of
efficiency.
Theory
The term theory is often used by the layman to express the opposite of fact.
Basic to modern science is an intricate relation between theory and research. The popular
understanding of this relationship obscures more than it illuminates. Popular opinion generally
conceives of these as direct opposites: theory is confused with speculation, and thus theory
remains speculation until it is proved. When this proof is made, theory becomes fact. Facts are
thought to be definite, certain, without question, and their meaning to be self evident.
When we look at what scientists actually do when engaged in research, it becomes clear (1) that
theory and fact are not diametrically opposed, but inextricably intertwined; (2) that theory is not
speculation; and (3) that scientists are very much concerned with both theory and fact (research).
Hence research produces facts and from facts we can generate theories. Theories are soft mental
images whereas research covers the empirical world of hard, settled, and observable things. In
this way theory and fact (research) contribute to each other.
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Role of Theory
1. Theory as orientation.
A major function of a theoretical system is that it narrows the range of facts to be studied. Any
phenomenon or object may be studied in many different ways. A football, for example, can be
investigated within an economic framework, as we ascertain the patterns of demand and supply
relating to this play object. It may also be the object of chemical research, for it is made of
organic chemicals.
It has a mass and may be studied as physical object undergoing different stresses and attaining
certain velocities under various conditions. It may also be seen as the center of many
sociologically interesting activities – play, communication, group organization, etc.
Each science and each specialization within a broader field abstracts from reality, keeping its
attention upon a few aspects of given phenomena rather than on all aspects. The broad
orientation of each field then focuses upon limited range of things while ignoring or making
assumptions about others.
2. Theory as a conceptualization and classification.
Every science is organized by a structure of concepts, which refer to major processes and objects
to be studied. It is the relationship between these concepts which are stated in ―the facts of
science.‖ Such terms make up the vocabulary that the scientist uses. If knowledge is to be
organized, there must be some system imposed upon the facts which are observable. As a
consequence, a major task in any science is the development of development of classification, a
structure of concepts, and an increasingly precise set of definitions for these terms.
3. Theory in summarizing role.
A further task which theory performs is to summarize concisely what is already known about the
object of study. These summaries may be divided into two simple categories: (1) empirical
generalizations, and (2) systems of relationships between propositions.
Although the scientist may think of his field as a complex structure of relationships, most of his
daily work is concerned with prior task: the simple addition of data, expressed in empirical
generalizations.
The demographer may tabulate births and deaths during a given period in order to ascertain the
crude rate of reproduction. These facts are useful and are summarized in simple or complex
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theoretical relationships. As body of summarizing statements develops, it is possible to see
relationships between the statements.
Theorizing on a still larger scale, some may attempt to integrate the major empirical
generalizations of an era. From time to time in any science, there will be changes in this
It is through systems of propositions that many of our common statements must be interpreted.
Facts are seen within a framework rather than in an isolated fashion.
4. Theory predicts facts.
If theory summarizes facts and states a general uniformity beyond the immediate observation, it
also becomes a prediction of facts. This prediction has several facets. The most obvious is the
extrapolation from the known to the unknown. For example, we may observe that in every
known case the introduction of Western technology has led to a sharp drop in the death rate and a
relatively minor drop in the birth rate of a given nation, at least during the initial stages. Thus we
predict that if Western technology is introduced into a native culture, we shall find this process
again taking place.
Correspondingly we predict that in a region where Western technology has already been
introduced, we shall find that this process has occurred.
5. Theory points gaps in knowledge.
Since theory summarizes the known facts and predicts facts which have not been observed, it
must also point to areas which have not yet been explored.
Theory also points to gaps of a more basic kind. While these gaps are being filled, changes in the
conceptual scheme usually occur. An example from criminology may be taken. Although a
substantial body of knowledge had been built up concerning criminal behavior and it causes. A
body of theory dealing with causation was oriented almost exclusively to the crimes committed
by the lower classes.
Very little attention has been paid to the crimes committed by the middle class or, more
specifically, to the crimes labeled as ―white collar‖ and which grow out of the usual activities of
businessmen. Such a gap would not be visible if our facts were not systematized and organized.
As a consequence, we may say that theory does suggest where our knowledge is deficient.
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4.4.
Summary
The scientific knowledge, which consists facts and principles, are important to conduct research.
Induction, deduction and combination of the two are major reasoning processes. Meanings of
concepts in different context are important for reasoning and understanding. It is difficult to do
research unless you know how to talk about variables and attributes. Researcher develops
testable explanation and tentative answer to research problem in the form of hypothesis. The
basic difference between theories and hypotheses is in the level of complexity and abstraction.
Identifying patterns of relationships like positive, negative or none is important for sound
research findings. Qualitative and Quantitative data must be analyzed. One of the most important
ideas in research project, unit of analysis, must be clearly distinguished. If you are not able to use
above discussed scientific approaches, you will end up with fallacy of research findings.
1. Briefly discuss the characteristics of the scientific method.
2. Define concept and develop your own example that shows the ladder of abstraction of
concept.
3. What is the basic difference between deductive and inductive reasoning?
4. Name the different types of variables and explain each of them with your own examples.
5. Why operational definition in research?
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5
Formulating the Research Design
5.0. Learning outcomes
By the end of this chapter you should be able to:
 understand the importance of having thought carefully about your research design;
 identify the main research strategies and explain why these should not be thought of as
mutually exclusive;
 explain the differences between quantitative and qualitative data collection techniques
and analysis procedures;
 explain the reasons for adopting multiple methods in the conduct of research;
 consider the implications of adopting different time horizons for your research design;
 explain the concepts of validity and reliability and identify the main threats to validity
and reliability;
5.1 Introduction
In this chapter we uncover the next three layers: research strategies, research choices and time
horizons. These three layers can be thought of as focusing on the process of research design, that
is, turning your research question into a research project. As we saw, the way you choose to
answer your research question will be influenced by your research philosophy and approach.
Your research question will subsequently inform your choice of research strategy, your choices
of collection techniques and analysis procedures, and the time horizon over which you undertake
your research project.
Your research design will be the general plan of how you will go about answering your research
question(s) (the importance of clearly defining the research question cannot be overemphasized). It will contain clear objectives, derived from your research question(s), specify the
sources from which you intend to collect data, and consider the constraints that you will
inevitably have (e.g. access to data, time, location and money) as well as discussing ethical
issues. Crucially, it should reflect the fact that you have thought carefully about why you are
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employing your particular research design. For example, it would be perfectly legitimate for your
assessor to ask you why you chose to conduct your research in a particular organization, why
you chose the particular department, and why you chose to talk to one group of staff rather than
another. You must have valid reasons for all your research design decisions.
5.2. Meaning of Research Design
The formidable problem that follows the task of defining the research problem is the preparation
of the design of the research project, popularly known as the ―research design‖. Decisions
regarding what, where, when, how much, by what means concerning an inquiry or a research
study constitute a research design.
A research design is the arrangement of conditions for collection and analysis of data in a
manner that aims to combine relevance to the research purpose with economy in procedure.
In fact, the research design is the conceptual structure within which research is conducted; it
constitutes the blueprint for the collection, measurement and analysis of data. As such the design
includes an outline of what the researcher will do from writing the hypothesis and its operational
implications to the final analysis of data. More explicitly, the design decisions happen to be in
respect of:
i.
What is the study about?
ii.
Why is the study being made?
iii.
Where will the study be carried out?
iv.
What type of data is required?
v.
Where can the required data be found?
vi.
What periods of time will the study include?
vii.
What will be the sample design?
viii.
What techniques of data collection will be used?
ix.
How will the data be analyzed?
x.
In what style will the report be prepared?
In brief, research design must, at least, contain—(a) a clear statement of the research problem;
(b) procedures and techniques to be used for gathering information; (c) the population to be
studied; and (d) methods to be used in processing and analyzing data.
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5.3. Need for Research Design
Research design is needed because it facilitates the smooth sailing of the various research
operations, thereby making research as efficient as possible yielding maximal information with
minimal expenditure of effort, time and money. Just as for better, economical and attractive
construction of a house, we need a blueprint (or what is commonly called the map of the house)
well thought out and prepared by an expert architect, similarly we need a research design or a
plan in advance of data collection and analysis for our research project. Research design stands
for advance planning of the methods to be adopted for collecting the relevant data and the
techniques to be used in their analysis, keeping in view the objective of the research and the
availability of staff, time and money. Preparation of the research design should be done with
great care as any error in it may upset the entire project.
Research design, in fact, has a great bearing on the reliability of the results arrived at and as such
constitutes the firm foundation of the entire edifice of the research work.
5.4. The purpose of your research
In Chapter 2 we encouraged you to think about your research project in terms of the question you
wished to answer and your research objectives. Within this we highlighted how the way in which
you asked your research question would result in either exploratory, descriptive, or explanatory
answers. In thinking about your research question, you inevitably have begun to think about the
purpose of your research.
The classification of research purpose most often used in the research methods‘ literature is the
threefold one of exploratory, descriptive and explanatory. However, in the same way as your
research question can be both descriptive and explanatory, so your research project may have
more than one purpose. Indeed, as Robson (2002) points out, the purpose of your enquiry may
change over time.
A.
Exploratory studies
An exploratory study is a valuable means of finding out ‗what is happening; to seek new
insights; to ask questions and to assess phenomena in a new light‘. It is particularly useful if you
wish to clarify your understanding of a problem, such as if you are unsure of the precise nature
of the problem. It may well be that time is well spent on exploratory research, as it may show
that the research is not worth pursuing!
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The major emphasis in such studies is on the discovery of ideas and insights. As such the
research design appropriate for such studies must be flexible enough to provide opportunity for
considering different aspects of a problem under study. Inbuilt flexibility in research design is
needed because the research problem, broadly defined initially, is transformed into one with
more precise meaning in exploratory studies, which fact may necessitate changes in the research
procedure for gathering relevant data. Generally, the following three methods in the context of
research design for such studies are talked about:
I.A search of the literature (Historical method)
The survey of concerning literature happens to be the most simple and fruitful method of
formulating precisely the research problem or developing hypothesis. Hypotheses stated by
earlier workers may be reviewed and their usefulness be evaluated as a basis for further research.
It may also be considered whether the already stated hypotheses suggest new hypothesis. In this
way the researcher should review and build upon the work already done by others, but in cases
where hypotheses have not yet been formulated, his task is to review the available material for
deriving the relevant hypotheses from it.
Advantages of historical Method
 The historical method is unobtrusive -- the act of research does not affect the results of
the study.
 The historical method is well suited for trend analysis.
 Compared to longitudinal designs, content analysis is usually less expensive.
 There is no possibility of researcher-subject interaction.
Disadvantages of the historical method:
 Researchers are likely to be biased in interpreting historical sources.
 Interpreting sources is very time consuming.
 Computerized content analysis is costly to quantitatively analyze -- programs of this type
take large blocks of computer core time and make analysis much more expensive than
standard statistical procedures used in evaluating survey data.
 The sources of historical materials may well be problematic.
 Due to the lack of control over external variables, historical research is very weak with
regard to the demands of internal validity.
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II. Experience survey
Experience survey means the survey of people who have had practical experience with the
problem to be studied. The object of such a survey is to obtain insight into the relationships
between variables and new ideas relating to the research problem. For such a survey people who
are competent and can contribute new ideas may be carefully selected as respondents to ensure a
representation of different types of experience. The respondents so selected may then be
interviewed by the investigator.
The researcher must prepare an interview schedule for the systematic questioning of informants.
But the interview must ensure flexibility in the sense that the respondents should be allowed to
raise issues and questions which the investigator has not previously considered. Generally, the
experience collecting interview is likely to be long and may last for few hours. Hence, it is often
considered desirable to send a copy of the questions to be discussed to the respondents well in
advance. This will also give an opportunity to the respondents for doing some advance thinking
over the various issues involved so that, at the time of interview, they may be able to contribute
effectively. Thus, an experience survey may enable the researcher to define the problem more
concisely and help in the formulation of the research hypothesis. This survey may as well
provide information about the practical possibilities for doing different types of research.
III. Conducting focus group interviews
A focus group is a panel of people led by a trained moderator who meet for 1hour to 2 hours.
Participants exchange and digest ideas, feelings, and experiences on a specific topic. The number
of participants may range from 6 to 12.
In explorative research, the qualitative data that focus groups produce may be used for enriching
all levels of research questions and hypotheses and comparing the effectiveness of design
options.
The facilitator introduces the topic and encourages the group to discuss it among themselves.
S(h)e should stimulate discussion among group members rather than interview individual
members, that is to say every participant should be encouraged to express his/her views on each
topic as well as respond to the views expressed by the other participants. S(h)e is responsible for
ensuring that all relevant issues in the topic are discussed by the group, no dominance of few
individuals, each person enters in the discussion, etc.
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Similar participants, with respect to some variable, are placed in to different groups to create
some sort of homogeneity.
There are different types of focus group discussions:
 Face-to-face
 Telephone focus groups
 Online focus groups
 Video conferencing focus groups
Advantages of focus groups
 Ability to quickly and inexpensively grasp the core issues of a topic,
 A focus group takes advantage of the interaction between a small group of people
(synergy)
 Focus groups are inexpensive and extremely flexible
 Enable the exploration of surprise information and new ideas
B.
Descriptive and Diagnostic studies
Descriptive research studies are those studies which are concerned with describing the
characteristics of a particular individual, or of a group, whereas diagnostic research studies
determine the frequency with which something occur or its association with something else. The
studies concerning whether certain variables are associated are examples of diagnostic research
studies. As against this, studies concerned with specific predictions, with narration of facts and
characteristics concerning individual, group or situation are all examples of descriptive research
studies. Most of the social research comes under this category. From the point of view of the
research design, the descriptive as well as diagnostic studies share common requirements and as
such we may group together these two types of research studies. In descriptive as well as in
diagnostic studies, the researcher must be able to define clearly, what he wants to measure and
must find adequate methods for measuring it along with a clear cut definition of ‗population‘ he
wants to study. Since the aim is to obtain complete and accurate information in the said studies,
the procedure to be used must be carefully planned. The research design must make enough
provision for protection against bias and must maximize reliability, with due concern for the
economical completion of the research study. The design in such studies must be rigid and not
flexible and must focus attention on the following:
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a) Formulating the objective of the study (what the study is about and why is it being
made?)
b) Designing the methods of data collection (what techniques of gathering data will be
adopted?)
c) Selecting the sample (how much material will be needed?)
d) Collecting the data (where can the required data be found and with what time period
should the data be related?)
e) Processing and analyzing the data.
f) Reporting the findings.
In a descriptive/diagnostic study the first step is to specify the objectives with sufficient precision
to ensure that the data collected are relevant. If this is not done carefully, the study may not
provide the desired information. Then comes the question of selecting the methods by which the
data are to be obtained. In other words, techniques for collecting the information must be
devised. Several methods (viz., observation, questionnaires, interviewing, examination of
records, etc.), with their merits and limitations, are available for the purpose and the researcher
may user one or more of these methods which have been discussed in detail in later chapters.
In most of the descriptive/diagnostic studies the researcher takes out sample(s) and then wishes
make statements about the population on the basis of the sample analysis or analyses. More often
than not, sample has to be designed. Different sample designs have been discussed in detail in a
separate chapter in this book. Here we may only mention that the problem of designing samples
should be tackled in such a fashion that the samples may yield accurate information with a
minimum amount of research effort.
The data collected must be processed and analyzed. This includes steps like coding the interview
replies, observations, etc.; tabulating the data; and performing several statistical computations.
To the extent possible, the processing and analyzing procedure should be planned in detail before
actual work is started. This will prove economical in the sense that the researcher may avoid
unnecessary labor such as preparing tables for which he later finds he has no use or on the other
hand, re-doing some tables because he failed to include relevant data. Coding should be done
carefully to avoid error in coding and for this purpose the reliability of coders needs to be
checked.
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Last of all comes the question of reporting the findings. This is the task of communicating the
findings to others and the researcher must do it in an efficient manner. The layout of the report
needs to be well planned so that all things relating to the research study may be well presented in
simple and effective style.
Thus, the research design in case of descriptive/diagnostic studies is a comparative design
throwing light on all points narrated above and must be prepared keeping in view the objective(s)
of the study and the resources available. However, it must ensure the minimization of bias and
maximization of reliability of the evidence collected. The said design can be appropriately
referred to as a survey design since it takes into account all the steps involved in a survey
concerning a phenomenon to be studied.
The difference between research designs in respect of the above two types of research studies
can be conveniently summarized in tabular form as under:
Table 5.1.Differences between exploratory and Descriptive studies
C.
Explanatory studies
Studies that establish causal relationships between variables may be termed explanatory
research. The emphasis here is on studying a situation or a problem in order to explain the
relationships between variables. You may find, for example, that a cursory analysis of
quantitative data on manufacturing scrap rates shows a relationship between scrap rates and the
age of the machine being operated. You could go ahead and subject the data to statistical tests
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such as correlation in order to get a clearer view of the relationship. Alternatively, or in addition
to, you might collect qualitative data to explain the reasons why customers of your company
rarely pay their bills according to the prescribed payment terms.
5.5. The Need for a Clear Research Strategy
In this section we turn our attention to the research strategies you may employ. Each strategy
can be used for exploratory, descriptive and explanatory research. Some of these clearly belong
to the deductive approach, others to the inductive approach. However, often allocating strategies
to one approach or the other is unduly simplistic. In addition, we must emphasize that no
research strategy is inherently superior or inferior to any other.
Consequently, what is most important is not the label that is attached to a particular strategy, but
whether it will enable you to answer your particular research question(s) and meet your
objectives. Your choice of research strategy will be guided by your research question(s) and
objectives, the extent of existing knowledge, the amount of time and other resources you have
available, as well as your own philosophical underpinnings. Finally, it must be remembered that
these strategies should not be thought of as being mutually exclusive. For example, it is quite
possible to use the survey strategy as part of a case study.
In our discussion of research strategies we start with the experiment strategy. This is because,
although in their purest form experiments are infrequently used in management research, their
roots in natural science laboratory-based research and the precision required mean that the
‗experiment‘ is often the ‗gold standard‘ against which the rigor of other strategies is assessed.
The three strategies that we consider subsequently in this section are: experiment, survey and
case study.
5.5.1. Experiment
Experiment is a form of research that owes much to the natural sciences, although it features
strongly in much social science research, particularly psychology. The purpose of an experiment
is to study causal links; whether a change in one independent variable produces a change in
another dependent variable (Hakim 2000). The essential element of causation is that A produces
B or A forces B to occur. But that is an artifact of language, not what can be observed
empirically.
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To meet ideal standard of causation would require that one variable always caused another and
no other variable had the same causal effect.
Three conditions that must be satisfied to have casual relationship are:
i.
Co variation between A and B- there must be an agreement between the dependent and
independent variables. The presence or absence of one is associated with the presence or
absence of the other.
ii.
No other possible causes -other extraneous variables do not influence the dependent
variable.
iii.
Time order of events -the dependent variable should not precede the independent variable
in relation to their time order. The independent variable should occur before or
simultaneously with the dependent variable.
The method of agreement states that when two or more cases of a given phenomenon have one
and only one condition in common, then that condition may be regarded as the cause (or effect)
of the phenomenon. That is if we can find Z and only Z in every case where we find C, and no
others (A, B, or D) are found with Z, then we can conclude that C and Z are causally related. The
method of agreement may help in eliminating some variables. However, there is an implicit
assumption that there are no other variables to consider other than A, B, C, and D. In addition,
while C may be the cause, it may instead function only in the presence of some other variable not
included.
The negative cannon of agreement states that where the absence of C is associated with the
absence of Z, there is evidence of causal relationship between C and Z.
Generally, if there are two or more cases, and in one of them observation Z can be made, while
in the other it cannot; and if variable C occurs when observation Z is made, and does not occur
when observation Z is not made; then it can be asserted that there is a causal relationship
between C and Z.
The simplest experiments are concerned with whether there is a link between two variables.
More complex experiments also consider the size of the change and the relative importance of
two or more independent variables. Experiments therefore tend to be used in exploratory and
explanatory research to answer ‗how‘ and ‗why‘ questions. In a classic experiment (Figure 5.1),
two groups are established and members assigned at random to each. This means the two groups
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will be exactly similar in all aspects relevant to the research other than whether or not they are
exposed to the planned intervention or manipulation. In the first of these groups, the
experimental group, some form of planned intervention or manipulation, such as a ‗buy two,
get one free‘ promotion, is made subsequently. In the other group, the control group, no such
intervention is made. The dependent variable, in this example purchasing behavior, is measured
before and after the manipulation of the independent variable (the use of the ‗buy two, get one
free‘ promotion) for both the experimental group and the control group. This means that a before
and after comparison can be undertaken. On the basis of this comparison, any difference between
the experimental and control groups for the dependent variable (purchasing behavior) is
attributed to the intervention, in our example the ‗buy two, get one free‘ promotion.
In assigning the members to the control and experimental groups at random and using a control
group, you try to control (that is, remove) the possible effects of an alternative explanation to the
planned intervention (manipulation) and eliminate threats to internal validity. This is because the
control group is subject to exactly the same external influences as the experimental group other
than the planned intervention and, consequently, this intervention is the only explanation for any
changes to the dependent variable. By assigning the members of each group at random, changes
cannot be attributed to differences in the composition of the two groups. Therefore, in
minimizing threats to internal validity, you are minimizing the extent to which the findings can
be attributed to any flaws in your research design rather than the planned interventions.
Figure 5.1 .A classic experiment strategy
In summary, an experimental study will involve the following steps:
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Step1. Construction of control and Experimental groups
Whatever be the structure or type of experimental research design, it involves comparison of
two groups of subjects. One is the control group and the other is the experimental group. The
experimental group is exposed to the experimental variable (independent variable under
consideration) whereas the control group is not exposed to the experimental variable. If the two
groups are found to be similar on all other characteristics, except the exposure to the
experimental variable, then the difference in the dependent variable is assumed to have been
caused by the experimental variable.
Sometimes more than one experimental group is considered if the experimental variable is
presented in the form of different levels of treatment. These different levels of treatment will be
given to the different experimental groups and their respective effect will be observed.
There are two different processes through which the individuals are selected from the universe
and assigned to the different groups in a manner that they become similar to each other. These
are
Randomization: Experimental units will be selected from the population and assigned to the
experimental and control groups randomly. Every experimental unit has equal chance of being
assigned to any of the groups.
Matching: Here experimental units (subjects) are selected in a manner so as to create groups
with similar distributions on a few relevant variables, but not necessarily on all of them
simultaneously. These variables may be sex, age, experience, educational level etc.
The overall purpose is to control the effect of other variables. Before the application of the
treatment the experimental and control groups are assumed to be same. Controlling of variables
in experimental research is a difficult task. One must not only have a clear conception of what
variables are related to the problem but one must also know how to identify the variables
empirically.
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Step 2: Pre-Test
Pre-test is the process of measuring the initial position of the groups with respect to the
dependent variable. It is also a way of checking weather the groups are the same with respect to
other characteristics. This helps to safely conclude that the difference found is attributable to the
influence of the experimental variable.
Step 3: Exposure of the Experimental groups to the experimental variable
At this stage the treatment will be applied to the experimental group and the control group will
be provided with the treatment.
Step 4: Post Test
At this final stage measurements will be taken from the experimental group and are compared
with the pre-test measurements available. Comparative changes or differences in the two
measurements, pre and post, indicate the possibility of influence of the causal factors.
Comparison can also be made between control and experimental groups. Nevertheless, the
control group should show no change at all.
Inevitably, an experimental strategy will not be feasible for many business and management
research questions. For example, you could not, for ethical reasons, assign employees to
experience redundancy or small and medium-sized enterprises owners to experience their banks
foreclosing on business loans. Similarly, it may be considered unfair to carry out experiments in
relation to beneficial interventions such as providing additional support to research project
students only on the basis of them being selected for the experimental group! Some people are
not willing to participate in experiments and so those who volunteer may not be representative.
Because of this, the experiment strategy is often used only on captive populations such as
university students, employees of a particular organization and the like. As discussed earlier, the
design requirements of an experiment often mean that samples selected are both small and
atypical, leading to problems of external validity. Whilst you may be able to overcome this with
a large and representative sample, Hakim (2000) advises that this is likely to be both costly and
complex.
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5.5.2.
Survey
The survey strategy is usually associated with the deductive approach. It is a popular and
common strategy in business and management research and is most frequently used to answer
who, what, where, how much and how many questions. It therefore tends to be used for
exploratory and descriptive research. Surveys are popular as they allow the collection of a large
amount of data from a sizeable population in a highly economical way.
Often obtained by using a questionnaire administered to a sample, these data are standardized,
allowing easy comparison. In addition, the survey strategy is perceived as authoritative by people
in general and is both comparatively easy to explain and to understand. Every day a news
bulletin or a newspaper reports the results of a new survey that indicates, for example, that a
certain percentage of the population thinks or behaves in a particular way.
The survey strategy allows you to collect quantitative data which you can analyze quantitatively
using descriptive and inferential statistics. In addition, the data collected using a survey strategy
can be used to suggest possible reasons for particular relationships between variables and to
produce models of these relationships. Using a survey strategy should give you more control
over the research process and, when sampling is used, it is possible to generate findings that are
representative of the whole population at a lower cost than collecting the data for the whole
population. You will need to spend time ensuring that your sample is representative, designing
and piloting your data collection instrument and trying to ensure a good response rate. Analyzing
the results, even with readily available analysis software, will also be time consuming. However,
it will be your time and, once you have collected your data, you will be independent. Many
researchers complain that their progress is delayed by their dependence on others for
information.
The data collected by the survey strategy is unlikely to be as wide-ranging as those collected by
other research strategies. For example, there is a limit to the number of questions that any
questionnaire can contain if the goodwill of the respondent is not to be presumed on too much.
Despite this, perhaps the biggest drawback with using a questionnaire as part of a survey strategy
is the capacity to do it badly!
The questionnaire, however, is not the only data collection technique that belongs to the survey
strategy. Structured observation, of the type most frequently associated with organization and
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methods (O&M) research, and structured interviews, where standardized questions are asked of
all interviewees, also often fall into this strategy.
5.5.3. Case study
Robson (2002:178) defines case study as ‗a strategy for doing research which involves an
empirical investigation of a particular contemporary phenomenon within its real life context
using multiple sources of evidence‘. Yin (2003) also highlights the importance of context, adding
that, within a case study, the boundaries between the phenomenon being studied and the context
within which it is being studied are not clearly evident. This is the complete opposite of the
experimental strategy we outlined earlier, where the research is undertaken within a highly
controlled context. It also differs from the survey strategy where, although the research is
undertaken in context, the ability to explore and understand this context is limited by the number
of variables for which data can be collected.
The case study strategy will be of particular interest to you if you wish to gain a rich
understanding of the context of the research and the processes being enacted. The case study
strategy also has considerable ability to generate answers to the question ‗why?‘ as well as the
‗what?‘ and ‗how?‘ questions, although ‗what?‘ and ‗how?‘ questions tend to be more the
concern of the survey strategy. For this reason the case study strategy is most often used in
explanatory and exploratory research. The data collection techniques employed may be various
and are likely to be used in combination. They may include, for example, interviews,
observation, documentary analysis and questionnaires. Consequently, if you are using a case
study strategy you are likely to need to use and triangulate multiple sources of data.
Triangulation refers to the use of different data collection techniques within one study in order
to ensure that the data are telling you what you think they are telling you. For example,
qualitative data collected using semi-structured group interviews may be a valuable way of
triangulating quantitative data collected by other means such as a questionnaire.
Yin (2003) distinguishes between four case study strategies based upon two discrete dimensions:
 single case v. multiple case;
 holistic case v. embedded case.
A single case is often used where it represents a critical case or, alternatively, an extreme or
unique case. Conversely, a single case may be selected because it is typical or because it
provides you with an opportunity to observe and analyze a phenomenon that few have
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considered before. Inevitably, an important aspect of using a single case is defining the actual
case. A case study strategy can also incorporate multiple cases, that is, more than one case. The
rationale for using multiple cases focuses upon the need to establish whether the findings of the
first case occur in other cases and, as a consequence, the need to generalize from these findings.
For this reason Yin argues that multiple case studies may be preferable to a single case study and
that, where you choose to use a single case study, you will need to have a strong justification for
this choice.
Yin‘s second dimension, holistic v. embedded, refers to the unit of analysis. For example, you
may well have chosen to use an organization by which you have been employed or are currently
employed as your case. If your research is concerned only with the organization as a whole then
you are treating the organization as a holistic case study. Conversely, even though you are
researching and are concerned with a single organization as a whole, if you wish to examine also
a number of logical sub-units within the organization, perhaps departments or work groups, then
your case will inevitably involve more than one unit of analysis. Whatever way you select these
units, this would be called an embedded case study.
You may be suspicious of using a case study strategy because of the ‗unscientific‘ feel it has. We
would argue that a case study strategy can be a very worthwhile way of exploring existing
theory. In addition, a well constructed case study strategy can enable you to challenge an existing
theory and also provide a source of new research questions.
5.6. Time horizons
An important question to be asked in planning your research is ‗Do I want my research to be a
―snapshot‖ taken at a particular time or do I want it to be more akin to a diary or a series of
snapshots and be a representation of events over a given period?‘ (As always, of course, the
answer should be ‗it depends on the research question.‘) The ‗snapshot‘ time horizon is what we
call here cross-sectional while the ‗diary‘ perspective we call longitudinal.
We should emphasise here that these time horizons to research design are independent of which
research strategy you are pursuing or your choice of method. So, for example, you may be
studying the change in manufacturing processes in one company over a period of a year. This
would be a longitudinal case study.
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Cross-sectional studies
It is probable that your research will be cross-sectional, the study of a particular phenomenon (or
phenomena) at a particular time. We say this because we recognize that most research projects
undertaken for academic courses are necessarily time constrained. However, the time horizons
on many courses do allow sufficient time for a longitudinal study, provided, of course, that you
start it in plenty of time!
Cross-sectional studies often employ the survey strategy. They may be seeking to describe the
incidence of a phenomenon (for example, the IT skills possessed by managers in one
organization at a given point in time) or to explain how factors are related in different
organizations (e.g. the relationship between expenditure on customer care training for sales
assistants and sales revenue). However, they may also use qualitative methods. Many case
studies are based on interviews conducted over a short period of time.
Longitudinal studies
The main strength of longitudinal research is the capacity that it has to study change and
development. Adams and Schvaneveldt (1991) point out that in observing people or events over
time the researcher is able to exercise a measure of control over variables being studied, provided
that they are not affected by the research process itself. In longitudinal studies the basic question
is ‗Has there been any change over a period of time?‘
5.7. The credibility of research findings
Underpinning our earlier discussion on research design has been the issue of the credibility of
research findings. This is neatly expressed by Raimond (1993:55) when he subjects findings to
the ‗how do I know?‘ test: ‗. . . will the evidence and my conclusions stand up to the closest
scrutiny?‘ How do you know that the advertising campaign for a new product has resulted in
enhanced sales? How do you know that manual employees in an electronics factory have more
negative feelings towards their employer than their clerical counterparts? The answer, of course,
is that, in the literal sense of the question, you cannot know. All you can do is reduce the
possibility of getting the answer wrong. This is why good research design is important. This is
aptly summarized by Rogers: ‗scientific methodology needs to be seen for what it truly is, a way
of preventing me from deceiving myself in regard to my creatively formed subjective hunches
which have developed out of the relationship between me and my material‘.
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Reducing the possibility of getting the answer wrong means that attention has to be paid to two
particular emphases on research design: reliability and validity.
5.7.1. Reliability
Reliability refers to the extent to which your data collection techniques or analysis procedures
will yield consistent findings. It can be assessed by posing the following three questions:
1. Will the measures yield the same results on other occasions?
2. Will similar observations be reached by other observers?
3. Is there transparency in how sense was made from the raw data?
Threats to reliability
Robson (2002) asserts that there may be four threats to reliability. The first of these is subject or
participant error. If you are studying the degree of enthusiasm employees have for their work
and their employer it may be that you will find that a questionnaire completed at different times
of the week may generate different results. Friday afternoons may show a different picture from
Monday mornings! This should be easy to control. You should choose a more ‗neutral‘ time
when employees may be expected to be neither on a ‗high‘, looking forward to the weekend, nor
on a ‗low‘ with the working week in front of them.
Similarly, there may be subject or participant bias. Interviewees may have been saying what
they thought their bosses wanted them to say. This is a particular problem in organizations that
are characterized by an authoritarian management style or when there is a threat of employment
insecurity. Researchers should be aware of this potential problem when designing research. For
example, elaborate steps can be taken to ensure the anonymity of respondents to questionnaires,
as Section. Care should also be taken when analyzing the data to ensure that your data are telling
you what you think they are telling you.
Third, there may have been observer error. In one piece of research we undertook, there were
three of us conducting interviews with potential for at least three different ways of asking
questions to elicit answers. Introducing a high degree of structure to the interview schedule will
lessen this threat to reliability. Finally, there may have been observer bias. Here, of course, there
may have been different ways of interpreting the replies!
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5.7.2. Validity
Validity is concerned with whether the findings are really about what they appear to be about. Is
the relationship between two variables a causal relationship? For example, in a study of an
electronics factory we found that employees‘ failure to look at new product displays was caused
not by employee apathy but by lack of opportunity (the displays were located in a part of the
factory that employees rarely visited). This potential lack of validity in the conclusions was
minimized by a research design that built in the opportunity for focus groups after the
questionnaire results had been analyzed.
Threats to validity
 History
You may decide to study the opinions that customers have about the quality of a particular
product manufactured by a particular organization. However, if the research is conducted shortly
after a major product recall this may well have a dramatic, and quite misleading, effect on the
findings (unless, of course, the specific objective of the research was to find out about postproduct recall opinions).
 Testing
Your research may include measuring how long it takes telesales operators to deal with customer
enquiries. If the operators believe that the results of the research may disadvantage them in some
way, then this is likely to affect the results.
 Instrumentation
In the above example, the telesales operators may have received an instruction that they are to
take every opportunity to sell new policies between the times you tested the first and second
batches of operators. Consequently, the calls are likely to last longer.
 Mortality
This refers to participants dropping out of studies. This was a major problem for one of our
students, who was studying the effects on the management styles of managers exposed to a yearlong management development programme.
 Maturation
In the earlier management development example above, it could be that other events happening
during the year have an effect on their management style.
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 Ambiguity about causal direction
This is a particularly difficult issue. Suppose a students was studying the effectiveness of
performance appraisal in her organization. One of her findings was that poor performance ratings
of employees were associated with a negative attitude about appraisal among those same
employees. What she was not clear about was whether the poor performance ratings were
causing the negative attitude to appraisal or whether the negative attitude to appraisal was
causing the poor performance ratings.
5.8. Summary
Research projects are undertaken for different purposes. These can be categorized as exploratory,
descriptive and explanatory. Research design focuses upon turning a research question and
objectives into a research project. It considers research strategies, choices and time horizons. The
main research strategies are experiment, survey, case study, action research, grounded theory,
ethnography and archival research. You should not think of these as discrete entities. They may
be used in combination in the same research project. Using multiple methods can provide better
opportunities to answer a research question and to evaluate the extent to which findings may be
trusted and inferences made.
1. What is a research design?
2. Discuss the methods of data collection for explorative type of investigation.
3. Identify the three conditions that must be satisfied to have a causal relationship between
two variables
4. Compare and contrast case study and survey.
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6
Sampling Design
6.0. Learning outcomes
By the end of this chapter you should:
 understand the need for sampling in business and management research;
 be aware of a range of probability and non-probability sampling techniques and the
possible need to combine techniques within a research project;
 be able to select appropriate sampling techniques for a variety of research scenarios and
be able to justify their selection;
 be able to use a range of sampling techniques;
 be able to assess the representativeness of respondents;
 be able to assess the extent to which it is reasonable to generalize from a sample;
 be able to apply the knowledge, skills and understanding gained to your own research
project
6.1. Introduction
Whatever your research question(s) and objectives you will need to consider whether you need to
use sampling. Occasionally, it may be possible to collect and analyze data from every possible
case or group member; this is termed a census. However, for many research questions and
objectives, such as those highlighted in the vignette, it will be impossible for you either to collect
or to analyze all the data available to you owing to restrictions of time, money and often access.
Sampling techniques provide a range of methods that enable you to reduce the amount of data
you need to collect by considering only data from a sub-group rather than all possible cases or
elements. Some research questions will require sample data to generalize about all the cases
from which your sample has been selected. For example, if you asked a sample of consumers
what they thought of a new chocolate bar and 75 per cent said that they thought it was too
expensive, you might infer that 75 per cent of all consumers felt that way. Other research
questions may not involve such statistical generalizations. To gain an understanding of how
people manage their careers, you may select a sample of company chief executives. For such
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research your sample selection would be based on the premise that, as these people have reached
executive level and have been successful in managing their own careers they are most likely to
be able to offer insights from which you can build understanding. Even if you are adopting a case
study strategy using one large organization and collecting your data using unstructured
interviews, you will still need to select your case study (sample) organization and a group
(sample) of employees and managers to interview. Consequently, whatever you research
question an understanding of techniques for selecting samples is likely to be very important.
The full set of cases from which a sample is taken is called the population. In sampling, the term
‗population‘ is not used in its normal sense, as the full set of cases need not necessarily be
people. For research to discover relative levels of service at Ethiopian restaurants throughout a
country, the population from which you would select your sample would be all Ethiopian
restaurants in that country. Alternatively, you might need to establish the normal ‗life‘ of a longlife battery produced over the past month by a particular manufacturer. Here the population
would be all the long-life batteries produced over the past month by that manufacturer.
6.2. WHAT AND WHY‟S OF SAMPLING
6.2.1. Meaning of Sampling
Researchers usually cannot make direct observations of every individual in the population they
are studying. Instead, they collect data from a subset of individuals – a sample – and use those
observations to make inferences about the entire population as shown below in the figure.
Ideally, the sample corresponds to the larger population on the characteristic(s) of interest. In that
case, the researcher's conclusions from the sample are probably applicable to the entire
population.
Sampling is the act, process, or technique of selecting a suitable sample, or a representative part
of a population for the purpose of determining parameters or characteristics of the whole
population. The basic idea of sampling is that by selecting some of the elements in a population,
we may draw conclusions about the entire population. A population element is the subject on
which the measurement is being taken. A population is the total collection of elements about
which we wish to make some inferences.
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Your overarching goal in doing a survey is to determine what some group thinks or feels about
some issue. If money, time, or other resources were not a concern, the most accurate data you
could get would come from surveying the entire population of interest. Since limited resources
are a reality we all have to deal with, however, we are often forced to survey the views of only a
few members of the population. But never lose sight of the fact that the real purpose is to
discover the views of the entire population. Obviously, then, we want to be able to say with as
much confidence as possible that the views of the group we surveyed represents the views of the
entire population. Using a combination of powerful statistical tools known as inferential statistics
and unbiased sampling techniques, any surveyor can collect data that actually represent the views
of the entire population from which the sample was taken. Two things are absolutely necessary,
however, to ensure a high level of confidence that the sample represents the population: unbiased
sample and sufficiently large sample.
Bias as a statistical term means error. To say that you want an unbiased sample may sound like
you're trying to get a sample that is error free. As appealing as this notion may be, it is
impossible to achieve! Error always occurs -- even when using the most unbiased sampling
techniques. One source of error is caused by the act of sampling itself.
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The major objective of sampling theory is to provide accurate estimates of unknown parameters
from sample statistics that can be easily calculated.
The list from which the respondents are drawn is referred to as the sampling frame or working
population. It includes lists that are available or that are constructed from different sources
specifically for the study. Directories, membership or customer lists, even invoices or credit card
receipts can serve as a sampling frame. However, comprehensiveness, accuracy, currency, and
duplication are all factors that must be considered when determining whether there are any
potential sampling frame errors. For instance, if reservations and payments for certain business
travelers is made by their companies without specifying the actual guest name, these would not
be included if the sampling frame is the hotel‘s guest list. This could lead to potential under
representation of business travelers.
6.2.2. The need to sample
For some research questions it is possible to collect data from an entire population as it is of a
manageable size. However, you should not assume that a census would necessarily provide more
useful results than collecting data from a sample which represents the entire population.
Sampling provides a valid alternative to a census when:
 it would be impracticable for you to survey the entire population;
 your budget constraints prevent you from surveying the entire population;
 your time constraints prevent you from surveying the entire population;
 you have collected all the data but need the results quickly
For all research questions where it would be impracticable for you to collect data from the entire
population, you need to select a sample. This will be equally important whether you are planning
to use interviews, questionnaires, observation or some other data collection technique. You
might be able to obtain permission to collect data from only two or three organizations.
Alternatively, testing an entire population of products to destruction, such as to establish the
crash protection provided by cars would be impractical for any manufacturer.
With other research questions it might be theoretically possible for you to be able to collect data
from the entire population but the overall cost would prevent it. It is obviously cheaper for you to
collect, enter (if you are analyzing the data using a computer) and check data from 250
customers than from 2500, even though the cost per case for your study (in this example,
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customer) is likely to be higher than with a census. Your costs will be made up of new costs such
as sample selection, and the fact that overhead costs such as questionnaire, interview or
observation schedule design and setting up computer software for data entry are spread over a
smaller number of cases.
Sampling also saves time, an important consideration when you have tight deadlines. The
organization of data collection is more manageable as fewer people are involved. As you have
fewer data to enter, the results will be available more quickly. Occasionally, to save time,
questionnaires are used to collect data from the entire population but only a sample of the data
collected are analyzed. Fortunately advances in automated and computer assisted coding
software mean that such situations are increasingly rare.
Many researchers argue that using sampling makes possible a higher overall accuracy than a
census. The smaller number of cases for which you need to collect data means that more time
can be spent designing and piloting the means of collecting these data. Collecting data from
fewer cases also means that you can collect information that is more detailed. In addition, if you
are employing people to collect the data (perhaps as interviewers) you can afford higher-quality
staff. You also can devote more time to trying to obtain data from more difficult to reach cases.
Once your data have been collected, proportionally more time can be devoted to checking and
testing the data for accuracy prior to analysis.
6.3. SAMPLING VERSUS NON SAMPLING ERRORS
Sampling Error: This is a type of error that arises due to the fact that sample is taken rather than
the whole population. Sampling error comprises the differences between the sample and the
population that are due solely to the particular units that happen to have been selected. It reflects
the influences of chance in drawing the sample members. Sampling error is what is left after all
known sources of systematic variance have been accounted for.
Sampling error decreases with the increase in the size of the sample, and it happens to be of a
smaller magnitude in case of homogeneous population.
Sampling error can be measured for a given sample design and size. The measurement of
sampling error is usually called the ‗precision of the sampling plan‘. If we increase the sample
size, the precision can be improved. But increasing the size of the sample has its own limitations
viz., a large sized sample increases the cost of collecting data and also enhances the systematic
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bias. Thus the effective way to increase precision is usually to select a better sampling design
which has a smaller sampling error for a given sample size at a given cost. In practice, however,
people prefer a less precise design because it is easier to adopt the same and also because of the
fact that systematic bias can be controlled in a better way in such a design.
There are two basic causes for sampling error. One is chance and the other is sampling bias.
Sampling bias is a tendency to favor the selection of units that have particular characteristics.
Sampling bias is usually the result of a poor sampling plan.
Non-Sampling Error (systematic): A non-sampling error is an error that results solely from the
manner in which the observations are made. This type of error can occur whether a census or a
sample is being used. Usually a systematic bias is the result of one or more of the following
factors:
 Inappropriate sampling frame: If the sampling frame is inappropriate i.e., a biased
representation of the universe, it will result in a systematic bias.
 Defective measuring device: If the measuring device is constantly in error, it will result
in systematic bias. In survey work, systematic bias can result if the questionnaire or the
interviewer is biased. Similarly, if the physical measuring device is defective there will
be systematic bias in the data collected through such a measuring device.
 Non-respondents: If we are unable to sample all the individuals initially included in the
sample, there may arise a systematic bias. The reason is that in such a situation the
likelihood of establishing contact or receiving a response from an individual is often
correlated with the measure of what is to be estimated.
 Indeterminancy principle: Sometimes we find that individuals act differently when kept
under observation than what they do when kept in non-observed situations. For instance,
if workers are aware that somebody is observing them in course of a work study on the
basis of which the average length of time to complete a task will be determined and
accordingly the quota will be set for piece work, they generally tend to work slowly in
comparison to the speed with which they work if kept unobserved. Thus, the
indeterminancy principle may also be a cause of a systematic bias.
 Natural bias in the reporting of data: Natural bias of respondents in the reporting of
data is often the cause of a systematic bias in many inquiries. There is usually a
downward bias in the income data collected by government taxation department,
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whereas we find an upward bias in the income data collected by some social
organization. People in general understate their incomes if asked about it for tax
purposes, but they overstate the same if asked for social status or their affluence.
Generally in psychological surveys, people tend to give what they think is the ‗correct‘
answer rather than revealing their true feelings.
6.4. STEPS IN SAMPLE DESIGN
While developing a sampling design, the researcher must pay attention to the following points:
I. Type of universe: The first step in developing any sample design is to clearly define the set of
objects, technically called the Universe, to be studied. The universe can be finite or infinite. In
finite universe the number of items is certain, but in case of an infinite universe the number of
items is infinite, i.e., we cannot have any idea about the total number of items. The population of
a city, the number of workers in a factory and the like are examples of finite universes, whereas
the number of stars in the sky, listeners of a specific radio programme, throwing of a dice etc. are
examples of infinite universes.
II. Sampling unit: A decision has to be taken concerning a sampling unit before selecting
sample. Sampling unit may be a geographical one such as state, district, village, etc., or a
construction unit such as house, flat, etc., or it may be a social unit such as family, club, school,
etc., or it may be an individual. The researcher will have to decide one or more of such units that
he has to select for his study.
III. Source list: It is also known as ‗sampling frame‘ from which sample is to be drawn. It
contains the names of all items of a universe (in case of finite universe only). If source list is not
available, researcher has to prepare it. Such a list should be comprehensive, correct, reliable and
appropriate. It is extremely important for the source list to be as representative of the population
as possible.
IV. Size of sample: This refers to the number of items to be selected from the universe to
constitute a sample. This a major problem before a researcher. The size of sample should neither
be excessively large, nor too small. It should be optimum. An optimum sample is one which
fulfills the requirements of efficiency, representativeness, reliability and flexibility.
While deciding the size of sample, researcher must determine the desired precision as also an
acceptable confidence level for the estimate. The size of population variance needs to be
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considered as in case of larger variance usually a bigger sample is needed. The size of population
must be kept in view for this also limits the sample size. The parameters of interest in a research
study must be kept in view, while deciding the size of the sample.
Costs too dictate the size of sample that we can draw. As such, budgetary constraint must
invariably be taken into consideration when we decide the sample size.
V. Parameters of interest: In determining the sample design, one must consider the question of
the specific population parameters which are of interest. For instance, we may b interested in
estimating the proportion of persons with some characteristic in the population, or we may be
interested in knowing some average or the other measure concerning the population. There may
also be important sub-groups in the population about whom we would like to make estimates. All
this has a strong impact upon the sample design we would accept.
VI. Budgetary constraint: Cost considerations, from practical point of view, have a major
impact upon decisions relating to not only the size of the sample but also to the type of sample.
This fact can even lead to the use of a non-probability sample.
VII. Sampling procedure: Finally, the researcher must decide the type of sample he will use
i.e., he must decide about the technique to be used in selecting the items for the sample. In fact,
this technique or procedure stands for the sample design itself. There are several sample designs
(explained in the pages that follow) out of which the researcher must choose one for his study.
Obviously, he must select that design which, for a given sample size and for a given cost, has a
smaller sampling error.
6.5. TYPES OF SAMPLE DESIGNS
There are two bases on which sampling approaches may be classified. These are representation
and element selection. According to representation sampling is classified as Probability and NonProbability Sampling on the other hand, with respect to element of selection we have restricted
and Unrestricted samples.
i.
Probability Sampling
With probability sampling, all elements (e.g., persons, households) in the population have some
opportunity of being included in the sample, and the mathematical probability that any one of
them will be selected can be calculated.
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Probability sampling (or representative sampling) is most commonly associated with surveybased research strategies where you need to make inferences from your sample about a
population to answer your research question(s) or to meet your objectives. The process of
probability sampling can be divided into four stages:
1. Identify a suitable sampling frame based on your research question(s) or objectives.
2. Decide on a suitable sample size.
3. Select the most appropriate sampling technique and select the sample.
4. Check that the sample is representative of the population
1. Identifying a suitable sampling frame and the implications for generalisability
The sampling frame for any probability sample is a complete list of all the cases in the
population from which your sample will be drawn. If your research question or objective is
concerned with members of a local golf club, your sampling frame will be the complete
membership list for that golf club. You then select your sample from this list.
You need to ensure your sampling frame is as complete, accurate and up to date as possible. An
incomplete or inaccurate list means that some cases will have been excluded and so it will be
impossible for every case in the population to have a chance of selection. Consequently, your
sample may not be representative of the total population and your research may be criticized for
this reason.
The way you define your sampling frame also has implications regarding the extent to which you
can generalize from your sample. As we have already discussed, sampling is used when it is
impracticable to collect data from the entire population. Within probability sampling, by defining
the sampling frame you are defining the population about which you want to generalize. This
means that if your sampling frame is a list of all customers of an organization, strictly speaking
you can only generalize, that is apply the findings based upon your sample, to that population.
Similarly, if your sampling frame is all employees of an organization (the list being the
organization‘s payroll) you can only generalize to employees of that organization. This can
create problems, as often we hope that our findings have wider applicability than the population
from which are sample was selected. However, even if your probability sample has been selected
from one large multinational organization, you should not claim that what you have found will
also occur in similar organizations. In other words, you should not generalize beyond your
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sampling frame. Despite this, researchers often do make such claims, rather than placing clear
limits on the generalisability of the findings.
2. Deciding on a suitable sample size
Generalizations about populations from data collected using any probability sampling is based on
statistical probability. The larger your sample‘s size the lower the likely error in generalizing to
the population. Probability sampling is therefore a compromise between the accuracy of your
findings and the amount of time and money you invest in collecting, checking and analyzing the
data. Your choice of sample size within this compromise is governed by:
 the confidence you need to have in your data – that is, the level of certainty that the
characteristics of the data collected will represent the characteristics of the total
population;
 the margin of error that you can tolerate – that is, the accuracy you require for any
estimates made from your sample;
 the types of analyses you are going to undertake – in particular, the number of categories
into which you wish to subdivide your data, as many statistical techniques have a
minimum threshold of data cases for each cell; and to a lesser extent:
 the size of the total population from which your sample is being drawn
It is likely that, if you are undertaking statistical analyses on your sample, you will be drawing
conclusions from these analyses about the population from which your sample was selected. This
process of coming up with conclusions about a population on the basis of data describing the
sample is called statistical inference and allows you to calculate how probable it is that your
result, given your sample size, could have been obtained by chance. Such probabilities are
usually calculated automatically by statistical analysis software. However, it is worth
remembering that, providing they are not biased, samples of larger absolute size are more likely
to be representative of the population from which they are drawn than smaller samples and, in
particular, the mean (average) calculated for the sample is more likely to equal the mean for the
population. This is known as the law of large numbers.
Researchers normally work to a 95 per cent level of certainty. This means that if your sample
was selected 100 times, at least 95 of these samples would be certain to represent the
characteristics of the population. The confidence level states the precision of your estimates of
the population as the percentage that is within a certain range or margin of error.
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3. Selecting the most appropriate sampling technique and the sample
Having chosen a suitable sampling frame and established the actual sample size required, you
need to select the most appropriate sampling technique to obtain a representative sample. Five
main techniques can be used to select a probability sample:
 simple random;
 systematic;
 stratified random;
 cluster;
 Multi-stage.
Your choice of probability sampling technique depends on your research question(s) and your
objectives. Subsequently, your need for face-to-face contact with respondents, the geographical
area over which the population is spread, and the nature of your sampling frame will further
influence your choice of probability sampling technique. The structure of the sampling frame,
the size of sample you need and, if you are using support workers, the ease with which the
technique may be explained will also influence your decision.
A. Simple Random Sampling
A simple random sample is one in which each member (person) in the total population has an
equal chance of being picked for the sample. In addition, the selection of one member should in
no way influence the selection of another. Simple random sampling should be used with a
homogeneous population, that is, one composed of members who all possess the same attribute
you are interested in measuring. In identifying the population to be surveyed, homogeneity can
be determined by asking the question, ―What is (are) the common characteristic(s) that are of
interest?‖ These may include such characteristics as age, sex, rank/grade, position, income,
religious or political affiliation, etc. -- whatever you are interested in measuring.
Simple random sampling (sometimes called just random sampling) involves you selecting the
sample at random from the sampling frame using random number tables, a computer. To do this
you:
1. Number each of the cases in your sampling frame with a unique number. The first case is
numbered 0, the second 1 and so on.
2. Select cases using random numbers until your actual sample size is reached.
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The best way to choose a simple random sample is to use a random number table (or let a
computer generate a series of random numbers automatically). In either case, you would assign
each member of the population a unique number (or perhaps use a number already assigned to
them such as house number, telephone number, P.O.Box, etc.). The members of the population
chosen for the sample will be those whose numbers are identical to the ones extracted from the
random number table (or computer) in succession until the desired sample size is reached. Many
statistical texts or mathematical tables treat random number generation. A less rigorous
procedure for determining randomness is to write the name of each member of the population on
a separate card, and with continuous mixing, draw out cards until the sample size is reached.
Simple random sampling is best used when you have an accurate and easily accessible sampling
frame that lists the entire population, preferably stored on a computer.
Advantages of the simple random sampling method:
 Simple and easy method
 Assures good representativeness of sample (particularly if the population is large and
homogeneous).
 It is free from subjectivity and free from personal error.
 The observations of the sample can be used for inferential purpose.
Disadvantages of simple random sampling method:
 The selection of simple random sample requires an up- to - date sampling frame of
population from which samples are to be drawn.
 The population is assumed to be homogenous
B. Systematic sampling
Under systematic sampling only the first unit of the sample is selected at random and the
remaining units are selected at fixed intervals.
Systematic sampling is especially applicable when the population to be studied is arranged in
time. It is often used in industry, where an item is selected for testing from a production line
(say, every twenty minutes) to ensure that machines and equipment are working to specification.
Alternatively, the manufacturer might decide to select every 10th item on a production line to
test for defects and quality. This technique requires the first item to be selected at random as a
starting point for testing and, thereafter, every 10th item is chosen.
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This technique could also be used when questioning people in a sample survey. A market
researcher might select every 15 th person who enters a particular store, after selecting a person
at random as a starting point; or interview occupants of every 5th house in a street, after selecting
a house at random as a starting point.
Steps in Systematic Sampling
1. Begin with a numbered sampling frame again.
2. Choose your sampling interval-number in population divided by number desired in
sample, or N/n. If a systematic sample of 500 students were to be carried out in a
university with an enrolled population of 10,000, the sampling interval would be: I = N/n
= 10,000/500 =20. If I is not a whole number, then it is rounded up.
3. Choose your random number between 0 and N/n
4. Select the element that corresponds to the random number. Then instead of picking a
second random number, etc., count out the interval (N/n) and choose that element. When
you get to the end of the list go back to the beginning until you have your full sample.
Systematic sampling has certain plus points. It can be taken as an improvement over a simple
random sample in as much as the systematic sample is spread more evenly over the entire
population. It is an easier and less costlier method of sampling and can be conveniently used
even in case of large populations. But there are certain dangers too in using this type of
sampling. If there is a hidden periodicity in the population, systematic sampling will prove to be
an inefficient method of sampling. For instance, every 25th item produced by a certain
production process is defective. If we are to select a 4% sample of the items of this process in a
systematic manner, we would either get all defective items or all good items in our sample
depending upon the random starting position. If all elements of the universe are ordered in a
manner representative of the total population, i.e., the population list is in random order,
systematic sampling is considered equivalent to random sampling. But if this is not so, then the
results of such sampling may, at times, not be very reliable. In practice, systematic sampling is
used when lists of population are available and they are of considerable length.
C. Stratified Random Sampling
Stratified random sampling is a modification of random sampling in which you divide the
population into two or more relevant and significant strata based on one or a number of
attributes.
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A general problem with random sampling is that you could, by chance, miss out a particular
group in the sample. However, if you form the population into groups, and sample from each
group, you can make sure the sample is representative.
The following three questions are highly relevant in the context of stratified sampling:
a) How to form strata?
b) How should items be selected from each stratum?
c) How many items be selected from each stratum or how to allocate the sample size of each
stratum?
Regarding the first question, we can say that the strata be formed on the basis of common
characteristic(s) of the items to be put in each stratum. This means that various strata be formed
in such a way as to ensure elements being most homogeneous within each stratum and most
heterogeneous between the different strata. Thus, strata are purposively formed and are usually
based on past experience and personal judgment of the researcher. One should always remember
that careful consideration of the relationship between the characteristics of the population and the
characteristics to be estimated are normally used to define the strata. At times, pilot study may be
conducted for determining a more appropriate and efficient stratification plan. We can do so by
taking small samples of equal size from each of the proposed strata and then examining the
variances within and among the possible stratifications, we can decide an appropriate
stratification plan for our inquiry.
In respect of the second question, we can say that the usual method, for selection of items for the
sample from each stratum, resorted to is that of simple random sampling. Systematic sampling
can be used if it is considered more appropriate in certain situations.
Regarding the third question, we usually follow the method of proportional allocation under
which the sizes of the samples from the different strata are kept proportional to the sizes of the
strata. That is, if Pi represents the proportion of population included in stratum i, and n represents
the total sample size, the number of elements selected from stratum i is n . Pi. To illustrate it, let
us suppose that we want a sample of size n = 30 to be drawn from a population of size N = 8000
which is divided into three strata of size N1 = 4000, N2 = 2400 and N3 = 1600. Adopting
proportional allocation, we shall get the sample sizes as under for the different strata:
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For strata with N1 = 4000, we have P1 = 4000/8000 and hence n1 = n. P1 = 30 (4000/8000) = 15
Similarly, for strata with N2 = 2400, we have n2 = n. P2 = 30 (2400/8000) = 9, and for strata
with N3 = 1600, we have n3 = n. P3 = 30 (1600/8000) = 6.
Thus, using proportional allocation, the sample sizes for different strata are 15, 9 and 6
respectively which is in proportion to the sizes of the strata viz., 4000: 2400: 1600.
Advantages of stratified random sampling
 Increased accuracy at a given cost. Higher degree of representation as compared to
simple random sampling. (Increased statistical efficiency.)
 In certain cases it becomes not only essential but also unavoidable. A case in point can be
comparative studies.
 If you want to be able to talk about subgroups, this may be the only way to effectively
assure you'll be able to. For example, estimates of the population parameters may be
wanted for each sub-population;
 Enables use of different methods in the different strata,
 Researcher controls sample size in strata
Disadvantages of stratified random sampling
 One must know the characteristic of the population so as to apply stratification
 Mostly costly and time consuming (it is expensive)
D. Cluster Sampling
It is sometimes expensive to spread your sample across the population as a whole. For example,
travel can become expensive if you are using interviewers to travel between people spread all
over the country. To reduce costs you may choose a cluster sampling technique.
Cluster sampling divides the population into groups, or clusters. These clusters are internally
heterogonous and externally homogenous. In other words, any two clusters are assumed to be
similar while individual elements within a given cluster are different. Within each cluster simple
random sampling or some other method then chooses units. Ideally the clusters chosen should be
dissimilar so that the sample is as representative of the population as possible.
For cluster sampling your sampling frame is the complete list of clusters rather than a complete
list of individual cases within the population. You then select a few clusters, normally using
simple random sampling. Data are then collected from every case within the selected clusters.
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Cluster sampling is used in large geographic samples where no list is available of all the units in
the population but the population boundaries can be well-defined. For example, to obtain
information about the drug habits of all high school students in a state, you could obtain a list of
all the school districts in the state and select a simple random sample of school districts. Then,
within in each selected school district, list all the high schools and select a simple random sample
of high schools. Within each selected high school, list all high school classes, and select a simple
random sample of classes. Then use the high school students in those classes as your sample.
Cluster sampling must use a random sampling method at each stage. This may result in a
somewhat larger sample than using a simple random sampling method, but it saves time and
money. It is also cheaper to administer than a statewide sample of high school seniors, because
there are many fewer sites to obtain information from.
The basic premise in cluster sampling is that each cluster will be a prototype of the population.
Hence, analysis conducted on one cluster will reflect the attribute of the whole population. But
here the question is ―to what an extent is this assumption practical?‖ especially in the context of
business environment. This is why we say the statistical efficiency of cluster sampling is poor as
compared to other sampling options.
Advantages of Cluster Sampling
 Reduced costs (economic efficiency); Saving of traveling time, and consequent reduction
in cost
 No need of having complete sampling frame. It is sometimes more feasible and
economical to develop a sampling frame where the primary sampling units represent
groups of elements rather than individual elements of the population.
 Useful for surveying employees in a particular industry, where individual companies can
form the clusters
 Simplified fieldwork and administration is more convenient. Instead of having a sample
scattered over the entire coverage area, the sample is more localized in relatively few
centers (clusters)
Disadvantages of Cluster Sampling
 Units close to each other may be very similar and so less likely to represent the whole
population
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 Less accurate results are often obtained due to higher sampling error than for simple
random sampling with the same sample size (low statistical efficiency)
E. Multi-stage sampling
Multi-stage sampling is a further development of the principle of cluster sampling. Suppose we
want to investigate the working efficiency of nationalized banks in India and we want to take a
sample of few banks for this purpose. The first stage is to select large primary sampling unit
such as states in a country. Then we may select certain districts and interview all banks in the
chosen districts. This would represent a two-stage sampling design with the ultimate sampling
units being clusters of districts.
If instead of taking a census of all banks within the selected districts, we select certain towns
and interview all banks in the chosen towns. This would represent a three-stage sampling
design. If instead of taking a census of all banks within the selected towns, we randomly sample
banks from each selected town, then it is a case of using a four-stage sampling plan. If we select
randomly at all stages, we will have what is known as ‗multi-stage random sampling design‘.
Ordinarily multi-stage sampling is applied in big inquires extending to a considerable large
geographical area, say, the entire country. There are two advantages of this sampling design
viz., (a) It is easier to administer than most single stage designs mainly because of the fact that
sampling frame under multi-stage sampling is developed in partial units. (b) A large number of
units can be sampled for a given cost under multistage sampling because of sequential
clustering, whereas this is not possible in most of the simple designs.
ii.
Non-probability sampling
Unlike the case of probability sampling, in non-probability sampling the probability that an
elementary unit in the population will be included in the sample is unknown. It is not
predetermined. Instead of objective approach we follow subjective approaches. Individual
elementary units are selected based not on chance but on personal intuition feeling, judgment,
etc.
With non-probability sampling, not every unit has a chance of selection in the sample and the
process involves some amount of subjectivity instead of following predetermined, probabilistic
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pathways. This can be useful in small scale exploratory studies where we wish to gain great
familiarity with the population rather than to reach statistical solutions.
Samples are selected by the discretion of the researcher. They are often quick and cheap to
create, even if they usually are less representative than random ones.
I. Convenience sampling
Convenience sampling (or haphazard sampling) involves selecting haphazardly those cases that
are easiest to obtain for your sample, such as the person interviewed at random in a shopping
centre for a television programme or the book about entrepreneurship you find at the airport.
The researcher selects units that are convenient, close at hand, easy to reach, etc. The sample
selection process is continued until your required sample size has been reached. Although this
technique of sampling is used widely, it is prone to bias and influences that are beyond your
control, as the cases appear in the sample only because of the ease of obtaining them.
Such samples might not be representative of the population and so it might be difficult to make
conclusions about a population based on this type of sample. If your sample is made up of
volunteers, then it is likely to be biased because the volunteers may be actively
supporting/promoting a point of view.
II. Quota sampling
Quota sampling is entirely non-random and is normally used for interview surveys. It is based on
the premise that your sample will represent the population as the variability in your sample for
various quota variables is the same as that in the population. Quota sampling is therefore a type
of stratified sample in which selection of cases within strata is entirely non-random. For
example, men and women have somewhat different opinions in many areas. If you want your
survey to accurately reflect the general population's opinions, you will want to ensure that the
percentage of men and women in your sample reflect their percentages of the general population.
In quota sampling the selection of the sample is made by the interviewer, who has been given
quotas to fill from specified sub-groups of the population. For example, an interviewer may be
told to sample 35 males between the age of 40 and 55.
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Quota sampling has a number of advantages over the probabilistic techniques. In particular, it is
less costly and can be set up very quickly. If, as with television audience research surveys, your
data collection need to be undertaken very quickly then quota sampling may be the only
possibility. In addition, it does not require a sampling frame and, therefore, may be the only
technique you can use if one is not available.
III. Purposive sampling
Purposive or judgmental sampling enables you to use your judgment to select cases that will best
enable you to answer your research question(s) and to meet your objectives or to ask an expert
on the issue being investigated to define the members that should comprise the sample
This form of sample is often used when working with very small samples such as in case study
research and when you wish to select cases that are particularly informative.
IV. Snowball Sampling
Snowball sampling is commonly used when it is difficult to identify members of the desired
population, for example people who are working while claiming unemployment benefit. You,
therefore, need to:
1. Make contact with one or two cases in the population.
2. Ask these cases to identify further cases.
3. Ask these new cases to identify further new cases (and so on).
Stop when either no new cases are given or the sample is as large as is manageable.
The main problem is making initial contact. Once you have done this, these cases identify further
members of the population, who then identify further members, and so the sample snowballs. For
such samples the problems of bias are huge, as respondents are most likely to identify other
potential respondents who are similar to themselves, resulting in a homogeneous sample. The
next problem is to find these new cases. However, for populations that are difficult to identify,
snowball sampling may provide the only possibility.
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6.6. Summary
Sampling is a process of selecting representative elements from a population with the intention
of minimizing the resource consumption of a research project, and in some cases increasing the
accuracy of results.
There are different reasons for considering sample survey. These include, economic efficiency,
problem of accessibility, data analysis flexibility, ease of data collection, etc.
Sampling techniques can be categorized into two groups namely, random sampling and nonrandom sampling. In random sampling each and every elementary unit in the population has a
predetermined probability of being part and parcel of the sample. In contrast, in non-random
sampling there are some elementary units those probability of being incorporated is zero.
Random sampling includes simple random sampling, stratified sampling, systematic sampling,
cluster sampling, and multistage sampling.
On the other hand, non-random sampling involves judgment, quota, convenience and snowball
sampling.
Simple Random Sampling: A simple random sample (SRS) of size n is produced by a scheme
which ensures that each subgroup of the population of size n has an equal probability of being
chosen as the sample.
Stratified Random Sampling divides the population into "strata". There can be any number of
these. Then choose a simple random sample from each stratum. Combine those into the overall
sample. That is a stratified random sample. (Example: Church A has 600 women and 400 women
as members. One way to get a stratified random sample of size 30 is to take a SRS of 18 women
from the 600 women and another SRS of 12 men from the 400 men.)
Cluster sampling divides the population inn to different internally heterogeneous and externally
homogenous groups called clusters. The classification is in most cases based on location.
Multi-Stage Sampling: Sometimes the population is too large and scattered for it to be practical
to make a list of the entire population from which to draw a SRS. For instance, when the polling
organization samples voters, they do not do a SRS. Since voter lists are compiled by counties,
they might first do a sample of the counties and then sample within the selected counties. This
illustrates two stages. In some instances, they might use even more stages. At each stage, they
might do a stratified random sample on sex, race, income level, or any other useful variable on
which they could get information before sampling.
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1. Discuss the difference between random and non-random sampling?
2. What is the difference and similarity between quota and stratified sampling?
3. Compare the following sampling technique with respect to statistical efficiency and
economic efficiency.
 Note Statistical efficiency refers to representativeness
 Economic efficiency refers to time and cost.
A. Stratified Sampling
B. Convenience Sampling
C. Cluster sampling
4. What are the advantages of sample survey over census?
5. Distinguish between sampling and non-sampling errors.
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7
Methods of Data Collection
7.0.
Learning outcomes
By the end of this chapter you should be able to:
 Identify the difference between primary and secondary sources of data,
 Know the different means of collecting data from the primary source
 Design the different tools that are used in collecting primary data, like preparing
questionnaires, interview questions, etc.
7.1.
Introduction
The task of data collection begins after a research problem has been defined and research
design/plan chalked out. While deciding about the method of data collection to be used for the
study, the researcher should keep in mind two types of data viz., primary and secondary. The
primary data are those which are collected afresh and for the first time, and thus happen to be
original in character.
The secondary data, on the other hand, are those which have already been collected by someone
else and which have already been passed through the statistical process. The researcher would
have to decide which sort of data he would be using (thus collecting) for his study and
accordingly he will have to select one or the other method of data collection. The methods of
collecting primary and secondary data differ since primary data are to be originally collected,
while in case of secondary data the nature of data collection work is merely that of compilation.
Unless otherwise a researcher gives utmost care to the process of collecting data, the final end
point of the research will be ―garbage in garbage out!‖
We describe the different methods of data collection, with the pros and cons of each method.
7.2.
Concept of Measurement
Data collection is all about measuring something. In everyday usage, measurement occurs when
an established yardstick verifies the height, weight, or another feature of a physical object. How
well you like a song, a painting, or the personality of a friend is also a measurement. In a
dictionary sense, to measure is to discover the extent, dimensions, quantity, or capacity of
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something, especially by comparison with a standard. We measure casually in daily life, but in
research the requirements are rigorous.
Measurement in research consists of assigning numbers to empirical events in compliance with
a set of rules. This definition implies that measurement is a three part process:
 selecting observable empirical events,
 using numbers or symbols to represent aspects of the events, and
 applying a mapping rule to connect the observation to the symbols
Researchers deduce from a hypothesis that certain conditions should exist in the real world; then
they measure for these conditions. If found, they lend support to the hypothesis; if not,
researchers conclude the hypothesis is faulty. An important question at this point is, "Just what
does one measure?"
Concepts used in research may be classified as objects or as properties. Objects include the
things of ordinary experience, such as tables, people, books, and automobiles. Objects also
include things that are not as concrete, such as genes, attitudes, neutrons, and peer-group
pressures. Properties, on the other hand, are the characteristics of the objects. A person's physical
properties may be stated in terms of weight, height, posture. Psychological properties include
attitudes and intelligence. Social properties include leadership ability, class affiliation, or status.
These and many other properties of an individual can be measured in a research study.
In a literal sense, researchers do not measure objects or properties. They measure indicants of the
properties. Thus, they measure indicants of the properties of objects. It is easy to observe that A
is taller than B and that C participates more than D in a group process. Or suppose you are
analyzing members of a sales force of several hundred people to learn what personal properties
contribute to sales success. The properties are age, years of experience, and number of calls
made per week. The indicants in these cases are so accepted that one considers the properties to
be observed directly.
In contrast, it is not easy to measure properties like motivation to succeed, ability to stand stress,
problem-solving ability, and persuasiveness. Since they cannot be measured directly, one must
infer their presence or absence by observing some indicant or pointer measurement. When you
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begin to make these inferences, there is often disagreement about how to operationalize the
indicants.
Not only is it a challenge to measure such constructs, but a study's quality depends on what
measures are selected or constructed and how they fit the circumstances.
The nature of measurement scales, sources of error, and characteristics of sound measurement
are considered next.
7.3.
Measurement Scale
There are four basic measurement scales. These are:
Nominal Scale: In business and social science research, nominal data are probably more widely
collected than any other. When you collect nominal data, you partition a set into categories that
are mutually exclusive and collectively exhaustive.
The counting of members in each group is the only possible arithmetic operation when a nominal
scale is employed. If we use numbers to identify categories, they are recognized as labels only
and have no quantitative value.
Ordinal Scale Includes the characteristics of the nominal scale plus an indicator of order.
Ordinal data is possible if the transitivity postulate is fulfilled. This postulate states: If a is
greater than b and b is greater than c, then a is greater than C .The use of an ordinal scale implies
a statement of "greater than" or "less than" (an equality statement is also acceptable) without
stating how much greater or less. Like a rubber yardstick, it can stretch varying amounts at
different places along its length. Thus, the real difference between ranks 1 and 2 may be more or
less than the difference between ranks 2 and 3.
An ordinal concept can be generalized beyond the simple illustration of a > b >c. Any number of
cases can be ranked. While ordinal measurement speaks of "greater than" and "less than ―
measurements, other descriptors may be used-"superior to," "happier than," or "above." A third
extension of the ordinal concept occurs when more than one property is of interest. We may ask
a taster to rank varieties of carbonated soft drinks by flavor, color, carbonation, and a
combination of these characteristics.
Examples of ordinal data include opinion and preference scales. The widely used pairedcomparison technique uses ordinal data. Because the numbers of this scale have only a rank
meaning, the appropriate measure of central tendency is the median. A percentile or quartile
measure reveals the dispersion. Correlation is restricted to various rank-order methods. Measures
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of statistical significance are technically confined to that body of methods known as
nonparametric methods.
Interval Scale has the power of nominal and ordinal data plus one additional strength. It
incorporates the concept of equality of interval (the distance between 1 and 2 equals the distance
between 2 and 3). Calendar time is such a scale. For example, the elapsed time between 3 and 6
A.M. equals the time between 4 and 7 A.M. One cannot say, however, 6 A.M. is twice as late as
3 A.M. because "zero time" is an arbitrary origin. Centigrade and Fahrenheit temperature scales
are other examples of classical interval scales. Both have an arbitrarily determined zero point.
When a scale is interval, you use the arithmetic mean as the measure of central tendency. You
can compute the average time of first arrival of trucks at a warehouse or the average attitude
value for union workers versus nonunion workers on an election.
Ratio Scale incorporates all of the powers of the previous data types plus the provision for
absolute zero or origin. Ratio data represents the actual amounts of a variable. Measures of
physical dimensions such as weight, height, distance, and area are examples. In business
research, we find ratio scales in many areas. There are money values, population counts,
distances, return rates, productivity rates.
Thus, multiplication and division can be used with this scale but not with the others mentioned.
7.4. Sources of Data
There are two sources from which data for a given research emanate. These are primary and
secondary sources.
Primary source is the original source from where we get first hand information. Data collected
from a primary source is called primary data. The primary sources are the elementary units in the
population on which investigation is made. Using primary sources researchers can collect
precisely the information they want. They usually can specify the operational definitions used
and can eliminate, or at least monitor and record, the extraneous influences on the data as they
are gathered.
On the other hand, a secondary source is one that is not the original source of the data for the
research. It is ready-made data.
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7.4.1. Secondary Data
Secondary Data obtained from any secondary source are called secondary data. The original
data have been collected by other agency for a different purpose and a researcher will be using
the same data for another purpose. Most commonly used secondary sources are magazines,
newspapers, journals, proceedings, websites, and other related publications.
Secondary data are used for three purposes.
 To fill a need for specific reference or citation on some point (to learn from the past).
 To minimize the costs and benefits of doing primary research.
 To serve as sole basis for a research study
Advantage of secondary data
 Can be found quickly and cheaply
Limitation of Secondary data
 The information may not meet one‘s specific needs (units of analysis, definition of
variables, sample size, etc)
 Question of reliability
There are two types of secondary data sources, internal and external. Internal sources are those
documentations that are generated within an organization by the organization. They include
internal financial and accounting reports, production summaries, sales summaries, etc. External
sources are created outside the organization and are more varied than internal sources. They do
not necessarily refer to the organization under consideration. These are, rather, publications that
are generated by other agencies like statistics authority of a country, research groups, and
professional associations.
Internal Sources
Accounting and management information systems create and store much of the internal data.
Research and development, planning and marketing functions also contribute.
E.g. Departmental reports, production summaries, financial and accounting reports and
marketing and sales studies.
The collection methods used are unique to the specific situation, and collection success depends
on knowing just where and how to look.
Systematic searches should be made through
exploratory interviews with who handles the information.
External Sources
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They are created outside the organization and more varied than internal sources. There are also
better defined methods for finding them.
E.g.
- Computerized databases
- Government documents
- Periodicals
- Special Collections
- Books
- University publications
- Company publications
- Personal document
Evaluating Secondary Data
This evaluation takes two forms: first, how well do the data fit the research needs; and second,
what confidence can you put in the accuracy and legitimacy of the data?
The data were not originally collected for our needs. Do you understand the definitions and
classifications employed? Are their meanings consistent with your own? The measurement used
and the topical coverage and time frame are important.
The question of data quality is, first, a question of data accuracy. It is good research practice to
go to the original source of the information rather than use an intermediate source that has quoted
from the original.
This enables you to avoid any errors in transcription and review the
cautionary and other comments that went along with the original data. Finally, you may uncover
revisions that have been made in the data since the intermediate source used it.
Another aspect of data accuracy is concerns its completeness: How much does the reported
material cover? Is it based on a narrow sample, a large population, or what? Answers to these
questions may suggest that the data are not appropriate for the problem.
Another aspect of data quality concerns the capacity of the source of the data. In this context,
there are two concerns: (i) Are the persons who conducted the study people in whom you can
have confidence: Are they highly regarded? Is their organization well regarded? (ii) It concerns
the original source: Could the respondent answer this question? What are the chances that the
respondent would know and be willing to give such information under the study conducts?
Also, one must especially be on guard when a report does not contain the methodology and
sampling design.
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1. MEASURES OF CENTRAL TENDENCY
Measures of central tendency (or statistical averages) tell us the point about which items have a tendency
to cluster. Such a measure is considered as the most representative figure for the entire mass of data.
Measure of central tendency is also known as statistical average. Mean, median and mode are the most
popular averages. Mean, also known as arithmetic average, is the most common measure of central
tendency and may be defined as the value which we get by dividing the total of the values of various
given items in a series by the total number of items. We can work it out as under:
Mean is the simplest measurement of central tendency and is a widely used measure. Its chief use
consists in summarizing the essential features of a series and in enabling data to be compared. It is
amenable to algebraic treatment and is used in further statistical calculations. It is a relatively stable
measure of central tendency. But it suffers from some limitations viz., it is unduly affected by extreme
items; it may not coincide with the actual value of an item in a series, and it may lead to wrong
impressions, particularly when the item values are not given with the average. However, mean is better
than other averages, especially in economic and social studies where direct quantitative measurements are
possible.
Median is the value of the middle item of series when it is arranged in ascending or descending order of
magnitude. It divides the series into two halves; in one half all items are less than median, whereas in the
other half all items have values higher than median. If the values of the items arranged in the ascending
order are: 60, 74, 80, 90, 95, 100, and then the value of the 4th item viz., 88 is the value of median.
Median is a positional average and is used only in the context of qualitative phenomena, for example, in
estimating intelligence, etc., which are often encountered in sociological fields. Median is not useful
where items need to be assigned relative importance and weights. It is not frequently used in sampling
statistics.
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Mode is the most commonly or frequently occurring value in a series. The mode in a distribution is that
item around which there is maximum concentration. In general, mode is the size of the item which has the
maximum frequency, but at items such an item may not be mode on account of the effect of the
frequencies of the neighboring items. Like median, mode is a positional average and is not affected by the
values of extreme items. it is, therefore, useful in all situations where we want to eliminate the effect of
extreme variations. Mode is particularly useful in the study of popular sizes.
For example, a manufacturer of shoes is usually interested in finding out the size most in demand so that
he may manufacture a larger quantity of that size. In other words, he wants a modal size to be determined
for median or mean size would not serve his purpose. but there are certain limitations of mode as well.
For example, it is not amenable to algebraic treatment and sometimes remains indeterminate when we
have two or more model values in a series. It is considered unsuitable in cases where we want to give
relative importance to items under consideration.
2. MEASURES OF DISPERSION
Averages can represent a series only as best as a single figure can, but it certainly cannot reveal the entire
story of any phenomenon under study. Specially it fails to give any idea about the scatter of the values of
items of a variable in the series around the true value of average. In order to measure this scatter,
statistical devices called measures of dispersion are calculated. Important measures of dispersion are (a)
range, and (b) standard deviation.
A. Range is the simplest possible measure of dispersion and is defined as the difference between the
values of the extreme items of a series. Thus,
The utility of range is that it gives an idea of the variability very quickly, but the drawback is that
range is affected very greatly by fluctuations of sampling. Its value is never stable, being based on only
two values of the variable. As such, range is mostly used as a rough measure of variability and is not
considered as an appropriate measure in serious research studies.
B. Standard deviation is most widely used measure of dispersion of a series and is commonly denoted by
the symbol ‗ s ‘ (pronounced as sigma). Standard deviation is defined as the square-root of the average
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of squares of deviations, when such deviations for the values of individual items in a series are
obtained from the arithmetic average. It is worked out as under:
When we divide the standard deviation by the arithmetic average of the series, the resulting quantity is
known as coefficient of standard deviation which happens to be a relative measure and is often used
for comparing with similar measure of other series. When this coefficient of standard deviation is
multiplied by 100, the resulting figure is known as coefficient of variation. Sometimes, we work out
the square of standard deviation, known as variance, which is frequently used in the context of analysis
of variation.
The standard deviation (along with several related measures like variance, coefficient of variation, etc.)
is used mostly in research studies and is regarded as a very satisfactory measure of dispersion in a
series. It is amenable to mathematical manipulation because the algebraic signs are not ignored in its
calculation (as we ignore in case of mean deviation). It is less affected by fluctuations of sampling.
These advantages make standard deviation and its coefficient a very popular measure of the
scatteredness of a series. It is popularly used in the context of estimation and testing of hypotheses.
3. MEASURES OF ASYMMETRY (SKEWNESS)
When the distribution of item in a series happens to be perfectly symmetrical, we then have the
following type of curve for the distribution:
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Figure 8.1
Such a curve is technically described as a normal curve and the relating distribution as normal
distribution. Such a curve is perfectly bell shaped curve in which case the value of X or M or Z is just
the same and skewness is altogether absent. But if the curve is distorted (whether on the right side or
on the left side), we have asymmetrical distribution which indicates that there is skewness. If the curve
is distorted on the right side, we have positive skewness but when the curve is distorted towards left,
we have negative skewness as shown here under:
Figure 8.2.
Skewness is, thus, a measure of asymmetry and shows the manner in which the items are clustered
around the average. In a symmetrical distribution, the items show a perfect balance on either side of
the mode, but in a skew distribution the balance is thrown to one side. The amount by which the
balance exceeds on one side measures the skewness of the series. The difference between the mean,
median or the mode provides an easy way of expressing skewness in a series. In case of positive
skewness, we have Z < M < X and in case of negative skewness we have X < M < Z.
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Usually we measure skewness in this way:
The significance of skewness lies in the fact that through it one can study the formation of series and
can have the idea about the shape of the curve, whether normal or otherwise, when the items of a given
series are plotted on a graph.
SIMPLE REGRESSION ANALYSIS
Regression is the determination of a statistical relationship between two or more variables. In simple
regression, we have only two variables, one variable (defined as independent) is the cause of the
behaviour of another one (defined as dependent variable). Regression can only interpret what exists
physically i.e., there must be a physical way in which independent variable X can affect dependent
variable Y. The basic relationship between X and Y is given by
Where the symbol Y denotes the estimated value of Y for a given value of X. This equation is known
as the regression equation of Y on X (also represents the regression line of Y on X when drawn on a
graph) which means that each unit change in X produces a change of b in Y, which is positive for
direct and negative for inverse relationships.
Then generally used method to find the ‗best‘ fit that a straight line of this kind can give is the leastsquare method. To use it efficiently, we first determine
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These measures define a and b which will give the best possible fit through the original X and Y points
and the value of r can then be worked out as under:
Thus, the regression analysis is a statistical method to deal with the formulation of mathematical
model depicting relationship amongst variables which can be used for the purpose of prediction of the
values of dependent variable, given the values of the independent variable.
8.5. Meaning of Interpretation
Interpretation refers to the task of drawing inferences from the collected facts after an analytical and/or
experimental study. In fact, it is a search for broader meaning of research findings. The task
of interpretation has two major aspects viz., (i) the effort to establish continuity in research through
linking the results of a given study with those of another, and (ii) the establishment of some
explanatory concepts. ―In one sense, interpretation is concerned with relationships within the collected
data, partially overlapping analysis. Interpretation also extends beyond the data of the study to include
the results of other research, theory and hypotheses.‖ Thus, interpretation is the device through which
the factors that seem to explain what has been observed by researcher in the course of the study can be
better understood and it also provides a theoretical conception which can serve as a guide for further
researches.
Why Interpretation?
Interpretation is essential for the simple reason that the usefulness and utility of research findings lie in
proper interpretation. It is being considered a basic component of research process because of the
following reasons:
 It is through interpretation that the researcher can well understand the abstract principle that
works beneath his findings. Through this he can link up his findings with those of other
studies, having the same abstract principle, and thereby can predict about the concrete world of
events. Fresh inquiries can test these predictions later on. This way the continuity in research
can be maintained.
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 Interpretation leads to the establishment of explanatory concepts that can serve as a guide for
future research studies; it opens new avenues of intellectual adventure and stimulates the quest
for more knowledge.
 Researcher can better appreciate only through interpretation why his findings are what they are
and can make others to understand the real significance of his research findings.
The interpretation of the findings of exploratory research study often results into hypotheses for
experimental research and as such interpretation is involved in the transition from exploratory to
experimental research. Since an exploratory study does not have a hypothesis to start with, the findings
of such a study have to be interpreted on a post-factum basis in which case the interpretation is
technically described as ‗post factum‘ interpretation.
8.6. Technique of Interpretation
The task of interpretation is not an easy job, rather it requires a great skill and dexterity on the part of
researcher. Interpretation is an art that one learns through practice and experience. The researcher may,
at times, seek the guidance from experts for accomplishing the task of interpretation.
The technique of interpretation often involves the following steps:
I. Researcher must give reasonable explanations of the relations which he has found and he must
interpret the lines of relationship in terms of the underlying processes and must try to find out the
thread of uniformity that lies under the surface layer of his diversified research findings. In fact, this is
the technique of how generalization should be done and concepts be formulated.
II. Extraneous information, if collected during the study, must be considered while interpreting the
final results of research study, for it may prove to be a key factor in understanding the problem under
consideration.
III. It is advisable, before embarking upon final interpretation, to consult someone having insight into
the study and who is frank and honest and will not hesitate to point out omissions and errors in logical
argumentation. Such a consultation will result in correct interpretation and, thus, will enhance the
utility of research results.
IV. Researcher must accomplish the task of interpretation only after considering all relevant factors
affecting the problem to avoid false generalization. He must be in no hurry while interpreting results,
for quite often the conclusions, which appear to be all right at the beginning, may not at all be
accurate.
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8.7. Summary
In this chapter we covered the initial steps of the procedure for analyzing data once they are
collected. We saw the steps necessary to get the data ready for analysis- editing, coding and
categorizing. The three popular measures used to summarize data are measures of central
tendency, dispersion and asymmetry. In addition to this the gathered data must also be
interpreted .
1. ―Processing of data implies editing, coding, classification and tabulation‖. Describe in brief these
four operations pointing out the significance of each in context of research study.
2. Why tabulation is considered essential in a research study? Narrate the characteristics of a good table.
3.
How will you differentiate between descriptive statistics and inferential statistics? Describe the important
statistical measures often used to summaries the survey/research data.
4.
What does a measure of central tendency indicate? Describe the important measures of central tendency
pointing out the situation when one measure is considered relatively appropriate in comparison to other
measures.
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9
Research Report Writing
9.0. Learning outcomes
By the end of this chapter you should be able to:
 Identify the different components of a research report,
 Present a standard and professional research paper layout
 Know the basics of oral presentations
9.1. Introduction
After collecting and analyzing the data, the researcher has to accomplish the task of drawing inferences followed by
report writing. This has to be done very carefully, otherwise misleading conclusions may be drawn and the whole
purpose of doing research may get vitiated. It is only through interpretation that the researcher can expose relations
and processes that underlie his findings. In case of hypotheses testing studies, if hypotheses are tested and upheld
several times, the researcher may arrive at generalizations. But in case the researcher had no hypothesis to start with,
he would try to explain his findings on the basis of some theory. This may at times result in new questions, leading
to further researches. All this analytical information and consequential inference(s) may well be communicated,
preferably through research report, to the consumers of research results who may be either an individual or a group
of individuals or some public/private organization.
9.2. What is Report Writing?
A report is a very formal document that is written for a variety of purposes in the sciences, social sciences,
engineering and business disciplines. Generally, findings pertaining to a given or specific task are written up into a
report. It should be noted that reports are considered to be legal documents in the workplace and, thus, they need to
be precise, accurate and difficult to misinterpret.
An objective of organizing a research paper is to allow people to read your work selectively. When I research a
topic, I may be interested in just the methods, a specific result, the interpretation, or perhaps I just want to see a
summary of the paper to determine if it is relevant to my study.
A well presented/reported study will often impress the reader more than a study with greater scientific quality but a
weaker presentation. A poor final report can destroy a study.
A number of points should be taken in to consideration while writing a research report.
First, in writing a report one should remember the purpose of the report. One of the purposes of your report is to
convince people that you have produced a good, sound piece of research and the more professional your report looks
the better your chances of success.
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Second, one should consider the target readers. Thought should be given to the needs, temperament, and biases of
the audience. Knowing who will read the report may suggest its appropriate length. Generally, the higher the report
goes in an organization, the shorter it should be.
How many different types of reports are there?
Reports may be defined by their degree of formality and' design. The formal report follows a well-delineated and
relatively long format. This contrasts to the informal or short report. Short reports are appropriate when the problem
is well defined, is of limited scope, and has a simple and straightforward methodology. Most informational,
progress, and interim reports are of this kind: a report of cost~of-living changes for upcoming labor negotiations or
an exploration of filing "dumping" charges against a foreign competitor.
Short reports are about five pages. At the beginning, there should be a brief statement about the authorization for the
study, the problem examined, and its breadth and depth. Next come the conclusions and recommendations, followed
by I the findings that support them. Section headings should be used.
A letter of transmittal is a vehicle to convey short reports. A five-page report may be produced to track sales on a
quarterly basis. The report should be direct, make ample use of graphics to show trends, and refer the reader to the
research department for further information. Detailed information on the research method would be omitted,
although an overview could appear in an appendix. The purpose of this type of report is to distribute information
quickly in an easy-to-use format.
Short reports are also produced for clients with small, relatively inexpensive research projects.
The letter is a form of a short report. Its tone should be informal. The format follows that of any good business letter
and should not exceed a few pages. A letter report is often written in personal style (we, you), although this depends
on the situation.
Memorandum reports are another variety and follow the To, From, Subject format.
These suggestions may be helpful for writing short reports.
 Tell the reader why you are writing (it may be in response to a request).
 If the memo is in response to a request for information, remind the reader of the exact point raised,
answer it, and follow with any necessary details.
 Write in an expository style with brevity and directness.
 If time permits, write the report today and leave it for review tomorrow before sending it.
 Attach detailed materials as appendices when needed.
Long reports are of two types, the technical or base report and the management report. The choice depends on the
audience and the researcher's objectives.
Many projects will require both types of reports: a technical report, written for an audience of researchers, and a
management report, written for the non technically oriented manager or client. While some researchers try to write a
single report that satisfies both needs, this complicates the task and is seldom satisfactory. The two types of
audiences have different technical training, interests, and goals.
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The Technical Report: This report should include full documentation and detail. It will normally survive all
working papers and original data files and so will become the major source document. It is the report that other
researchers will want to see because it has the 'full story of what was done and how it was done. While completeness
is a goal, you must guard against including nonessential material. A good guide is that sufficient procedural
information should be included to enable others to replicate the study. This includes sources of data, research
procedures, sampling design, data-gathering instruments, index construction, and data analysis methods. Most
information should be attached in an appendix.
A technical report should also include a full presentation and analysis of significant data. Conclusions and
recommendations should be clearly related to specific findings. Technical jargon should be minimized but defined
when used. There can be brief references to other research, theories, and techniques. While you expect the reader to
be familiar with these references, it is useful to include some short explanations, perhaps as footnotes or endnotes.
The Management Report: Sometimes the client has no research background and is interested in results rather
than in methodology. The major communication medium in this case is the management report. It is still helpful to
have a technical report if the client later wishes to have a technical appraisal of the study.
Because the management report is designed for a non-technical audience, the researcher faces some special
problems. Readers are less concerned with methodological details but more interested in learning quickly the major
findings and conclusions.
They want help in making decisions. Often the report is developed for a single person and needs to be written with
that person's characteristics and needs in mind. The style of the report should encourage rapid reading, quick
comprehension of major findings and prompt understanding of the implication and conclusions. The report tone is
journalistic and must be accurate. Headlines and underlining for emphasis are helpful; pictures and graphs often
replace tables. Sentences and paragraphs should be short and direct. Consider liberal use of white space and wide
margins. It may be desirable to put a single finding on each page. It also helps to have a theme running through the
report and even graphic or animated characters designed to vary the presentation .
How does the structure of a report differ from the structure of an essay?
Reports are organized into separate sections according to the specific requirements of the given task. While it is
important that paragraphs are structured and there is unity, coherence and logical development to the report, it is not
a continuous piece of writing like an essay. Each type of report serves a very specific purpose and is aimed at a very
particular audience.
Report writing may seem repetitive to us, but this is because reports are not usually read from cover-to-cover by one
person. For example, a manager may read only the synopsis or abstract and act on the advice it contains while a
technical officer may read only the section that explains how things work. On the other hand, a personnel officer
may look at only the conclusions and recommendations that directly affect his or her working area.
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9.3. Report Content
Research reports, long and short, have a set of identifiable components. Usually headings and subheadings divide
the sections. Each report is individual; sections may be dropped or added, condensed or expanded to meet the needs
of the audience.
All research reports use roughly the same format. It doesn't matter whether you've done a customer satisfaction
survey, an employee opinion survey, a health care survey, or a marketing research survey. All have the same basic
structure and format. The rationale is that readers of research reports (i.e., decision makers, funders, etc.) will know
exactly where to find the information they are looking for, regardless of the individual report.
Each report is individual; sections may be dropped or added, condensed or expanded to meet the needs of the
audience. Following is a suggested layout
PREFATORY ITEMS
 Letter of transmittal
 Title Page
 Authorization Letter
 Acknowledgment
 Executive Summary
 Table of Contents
BODY
Chapter One: Introduction
Chapter Two: Review Of the Related Literature
Chapter Three: Data and Methodology
Chapter Four: Data Analysis and Discussion of Results
Chapter Five: Summary, Conclusion, and Recommendation
SUPPLEMENTAL
 Appendices
 Bibliography
 Prefatory Items
Prefatory materials do not have direct bearing on the research itself. Instead they assist the reader in using the
research report.
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Letter of Transmittal
This is a covering letter which is sent with the report to the person or organization that requested
the report.
When the relationship between the researcher and the client is formal, a letter of transmittal
should be included. This is appropriate when a report is for a specific client (e.g., the company
president) and when it is generated for an outside organization. The letter should refer to the
authorization for the project and any specific instructions or limitations placed on the study. It
should also state the purpose and the scope of the study. For many internal projects, it is not
necessary to include a letter of transmittal.
Title Page
The title page should include the title of the report, the date, and for whom and by whom it was
prepared.
The title page should include four items: the title of the report, the date, and for whom and by
whom it was prepared. The title should be brief but include the following three elements: (1) the
variables included in the study, (2) the type of relationship among the variables, and (3) the
population to which the results may be applied. Redundancies such as "A Report of' and" A
Discussion of' add length to the title but little else. Single-word titles are also of little value
Authorization Letter
When the report is sent to a public organization, it is common to include a letter of authorization
showing the authority for undertaking the research. The letter not only shows who sponsored the
research but also delineate the original request.
Executive Summary (Abstract)
An abstract or synopsis outlines, very briefly, the entire report. It contains: the aim or purpose,
the procedures followed, the main findings and conclusions and recommendations that are
outlined in the report. The abstract or synopsis is like an introduction of an essay.
An executive summary can serve two purposes. It may be a report in miniature covering all the
aspects in the body of the report, but in abbreviated form. Or it may be a concise summary of the
major findings and conclusions, including recommendations. A maximum of two pages are
generally sufficient for executive summaries. Economy of words is important throughout any
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paper, but especially in an abstract. However, use complete sentences and do not sacrifice
readability for brevity. You can keep it concise by wording sentences so that they serve more
than one purpose.
Write this section after the rest of the report is finished. After all, how can you summarize
something that is not yet written?
It should not include new information but may require graphics to present a particular
conclusion. Expect the summary to contain a high density of significant terms since it is
repeating the highlights of the report.
Summarize the study, including the following elements in any abstract. Try to keep the first two
items to no more than one sentence each.
 Purpose of the study - hypothesis, overall question, objective
 Model organism or system and brief description of the experiment
 Results, including specific data - if the results are quantitative in nature, report
quantitative data; results of any statistical analysis should be reported
 Important conclusions or questions that follow from the experiment(s)
Style:
 Single paragraph, and concise
 As a summary of work done, it is always written in past tense
 An abstract should stand on its own, and not refer to any other part of the paper such as a
figure or table
 Focus on summarizing results - limit background information to a sentence or two, if
absolutely necessary
 What you report in an abstract must be consistent with what you reported in the paper
 Correct spelling, clarity of sentences and phrases, and proper reporting of quantities
(proper units, significant figures) are just as important in an abstract as they are anywhere
else
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Table of Contents
As a rough guide, any report of several sections that totals more than 10 pages should have table of contents. If there
are many tables, chart, or other exhibits, they should also be listed after the table of contents in a separate table of
illustrations.
Contents
Introduction......................................................................................1
Aim...................................................................................................1
Scope...............................................................................................1
Background to study........................................................................1
Procedure.........................................................................................2
Data collection methods...................................................................2
Analysis of data................................................................................5
Conclusions.......................................................................................17
Recommendations.............................................................................21
References........................................................................................23
Appendices.......................................................................................24
 Body of the Report
 Introduction
Background
Problem Statement
Research Objectives
Limitations
Delimitations
 Literature Review
Conceptual Literature
Empirical Literature
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Data and Methodology
In this section, you would briefly outline how you collected the data that will provide the basis for analysis that will
produce conclusions and recommendations. Even though it may be called something different, all reports use
specific data and ways of collecting it that would be included in this section.
Sampling Design-The researcher explicitly defines the target population being studied and the
sampling methods used. For example, was this a probability or non probability sample? If probability, was it
simple random or complex random? How were the elements selected? How was the size determined? How
much confidence do we have, and how much error was allowed? Explanations of the sampling methods,
uniqueness of the chosen parameters, or other points that need explanation should be covered with brevity.
Calculations should be placed in an appendix instead of in the body of the report.
Research Design- The coverage of the design must be adapted to the purpose. In an experimental
study, the materials, tests, equipment, control conditions, and other devices should be described. In descriptive
or ex post facto designs, it may be sufficient to cover the rationale for using one design instead of competing
alternatives. Even with a sophisticated design, the strengths and weaknesses should be identified and the
instrumentation and materials discussed. Copies of materials are placed in an appendix.
Data Collection- In research reports, you would probably use a different heading because your
data would come mainly from texts and journal articles. This is the section where you would discuss the main
issues arising from your research. It describes the specifics of gathering the data. Its contents depend on the
selected design. Survey work generally uses a team with field and central supervision. How many were
involved? What was their training? How were they managed? When were the data collected? How much time
did it take? What were the conditions in the field? How were irregularities handled? In an experiment, we
would want to know about subject assignment to groups, the use of standardized procedures and protocols, the
administration of tests or observational forms, manipulation of the variables, and so forth. Typically, you would
include a discussion on the relevance of secondary data that guided these decisions. Again, detailed materials
such as field instructions should be included in an appendix.
In research reports, you would probably use a different heading because your data would come mainly from
texts and journal articles. This is the section where you would discuss the main issues arising from your
research.
In reports that are based on data you have collected yourself this section would detail the methods you used to
collect that data and why those methods were chosen. You would also outline the steps taken during the process
of collecting data and carrying out research. An example is set out below:
Analysis of data and Interpretation of Results
This section is perhaps the longest section in most reports and it is where, using visual displays, you outline the
data you have collected.
Graphs, charts, tables, maps, graphic displays should always be used to summarize the findings you have made
from the data you have collected.
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Each set of data may be displayed in more than one way and each diagram or visual should
have a title, figure or table number, and should be thoroughly labeled.
Each set of data is systematically displayed and analyzed in a paragraph under the
appropriate diagram.
Summary, Conclusion and Recommendations
Summary
This section includes brief presentation of the main content and findings of the research. One
can also include the mini version of all the previous chapters, except for literature review,
starting from the problem itself. But summary must focus on findings.
Conclusion
Conclusions are those inferences or generalizations made depending on the results of data
analysis. Any conclusion should not jump beyond the reach and coverage of the finings of
the research.
The conclusions are dot pointed and are drawn directly from the analysis section of the
report. Dot points are used when the sequential order is not important. For each section under
the main heading 'Analysis', there should be at least one corresponding conclusion.
Recommendations
These are your suggestions for further action based on your conclusions. Not all reports will
ask for recommendations. Recommendations must be realistic and be supported by
implementation strategies. Some will have a section where both conclusions and
recommendations are given. Recommendations are numbered as they normally follow
sequentially.
 Supplemental (refer to chapter three)
Appendices
Appendices include things like raw data sheets, extra or supplementary information or
diagrams, maps of regions etc. You draw your reader's attention to the appropriate appendix
by indicating this briefly at the appropriate place in the report.
Glossary
Sometimes, when there is a lot of 'jargon' contained in a report (as in Science or Engineering), a glossary of
terms should also be included. This ensures that those reading the report understand the way you have used the
terms or jargon in your report. Sometimes words can have different meanings in different disciplines. If you
need to include a glossary, it would generally be placed just after the contents page .
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Bibliography
List all literature cited in your paper, in alphabetical order, by first author. In a proper
research paper, only primary literature is used (original research articles authored by the
original investigators). Never include a web site as a reference - anyone can put just about
anything on a web site, and you have no way of knowing if it is truth or fiction. If you are
citing an on line journal, use the journal citation (name, volume, year, page numbers).
9.4. Oral Presentation
Researchers often present their findings orally. These presentations, sometimes called
briefings, have some unique characteristics that distinguish them from most other kinds of
public speaking: Only a small group of people is involved; statistics normally constitute an
important portion of the topic; the audience members are usually managers with an interest in
the topic, but they want to hear only the critical elements; speaking time will often be as short
as 20 minutes but may run longer than an hour; and the presentation is normally followed by
questions and discussion.
A successful briefing typically requires condensing a lengthy and complex body of
information. Since speaking rates should not exceed 100 to 150 words per minute, a 20minute presentation limits you to about 2,000 to 2,500 words. If you are to communicate
effectively under such conditions, you must plan carefully. Begin by asking two questions.
First, how long should you plan to talk? Usually there is an indication of the acceptable
presentation length. It may be the custom in an organization to take a given allotted time for a
briefing. If the time is severely limited, then the need for topical priorities is obvious.
This leads to the second question: What are the purposes of the briefing? Is it to raise concern
about problems that have been uncovered? Is it to add to the knowledge of audience
members? Is it to give them conclusions? and recommendations for their decision making?
Questions such as these illustrate the general objectives of the report. After answering these
questions, you should develop a detailed outline of what you are going to say. Such an
outline should contain the following major parts.
Opening: A brief statement, probably not more than 10percent of the allotted time, sets the
stage for the body of the report. The opening should be direct, get attention, and introduce the
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nature of the discussion that follows. It should explain the nature of the project, how it came
about, and what it attempted to do.
Findings and conclusions: The conclusions may be stated immediately after the opening
remarks, with each conclusion followed by the findings that support it.
Recommendations:
Where appropriate, these are stated in the third stage; each
recommendation may be followed by references to the conclusions leading to it. Presented in
this manner, they provide a natural climax to the report. At the end of the presentation, it may
be appropriate to call for questions from the audience.
Early in the planning stage you need to make two further decisions. The first concerns the
type of audiovisuals (AV) that will be used and the role they will play in the presentation.
AV decisions are important enough that they are often made before the briefing outline and
text are developed. More will be said about AV later.
Then you must decide on the type of presentation. Will you give a memorized speech, read
from your manuscript, or give an extemporaneous presentation? We rule out the impromptu
briefing as an option because impromptu speaking does not involve preparation. Your
reputation and the research effort should not be jeopardized by "winging it."
Memorization is a risky and time-consuming course to follow. Any memory slip during the
presentation can be a catastrophe, and the delivery sounds stilted and distant.
Memorization virtually precludes establishing rapport with the audience and adapting to their
reactions while you speak. It produces a self- or speaker-centered approach and is not
recommended.
Reading a manuscript is also not advisable even though many professors seem to reward
students who do so (perhaps because they themselves get away with it at (professional
meetings). The delivery sounds dull and lifeless because most people are not trained to read
aloud and therefore do it badly. They become focused on the manuscript to the exclusion of
the audience. This head-down preoccupation with the text is clearly inappropriate for
management presentations.
The extemporaneous presentation is audience centered and made from minimal notes or an
outline. This mode permits the speaker to be natural, conversational, and flexible. Clearly, it
is the best choice for an organizational setting. Preparation consists of writing a draft along
with a complete sentence outline and converting the main points to notes. In this way, you
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can try lines of argument, experiment with various ways of expressing thoughts, and develop
phraseology. Along the way, the main points are fixed sequentially in your mind, and
supporting connections are made.
While the content of a report is the chief concern, the speaker's delivery is also important. A
polished presentation adds to the receptiveness of the audience, but there is some danger that
the presentation may overpower the message. Fortunately, the typical research audience
knows why it is assembled, has a high level of interest, and does not need to be entertained.
Even so, the speaker faces a real challenge in communicating effectively. The delivery
should be restrained. Demeanor, posture, dress, and total appearance should be appropriate
for the occasion. Speed of speech, clarity of enunciation, pauses, and gestures all play their
part. Voice pitch, tone quality, and inflections are proper subjects for concern. There is little
time for anecdotes and other rapport developing techniques, yet the speaker must get and
hold audience attention.
Speaker Problems- Inexperienced speakers have many difficulties in making presentations.
They often are nervous at the start of a presentation and may even find breathing difficult.
This is natural and should not be of undue concern. It may help to take a deep breath or two,
holding each for a brief time before exhaling as fully as possible. This can be done
inconspicuously on the way to the podium.
9.5. Summary
Reports should be clearly organized, physically inviting, and easy to read. Writers can
achieve these goals if they are careful with mechanical details, writing style, and
comprehensibility.
A standard research report incorporates such elements as title page, table of contents,
abstract, acknowledgment, background, statement of the problem, research importance,
limitations and scope, literature review, methodology, data analysis and findings, summary,
conclusion, recommendation, and other supplemental items.
There is a special challenge to presenting statistical data. While some may be incorporated in
the text, most statistics should be placed in tables, charts, or graphs. The choice of a table,
chart, or graph depends on the specific data and presentation purpose.
Oral presentations of research findings are common and should be developed with concern
for the communication problems that are unique to such settings. Briefings are usually under
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time constraints; good briefings require careful organization and preparation. Visual aids are
a particularly important aspect of briefings but are too often ignored or treated inadequately.
Whether written or oral, poor presentations do a grave injustice to what might otherwise be
excellent research. Good presentations, on the other hand, add luster to both the research and
the reputation of the researcher.
The writer of research reports should be guided by four questions:
1. What is the purpose of this report?
2. Who will read it?
3. What are the circumstances and limitations under which it is written?
4. How will the report be used?
1. Write a brief note on the ‗task of interpretation‘ in the context of research methodology.
2. ―Interpretation is a fundamental component of research process‖, Explain. Why so?
3. What is/are the difference(s) between a research proposal and the final research report?
4. List the core components of the body part of a research report.
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