Research in business management an introduction.

Ravindra Pujari Ravindra_pujari@yahoo.com
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Ravindra_pujari@yahoo.com
Cell 9303239020
RESEARCH
in
BUSINESS MANAGEMENT
Ravindra Pujari

Research in common parlance means search for
knowledge.
Re-search means to “SEARCH AGAIN”.
In simple words, research is a systematic method of
finding solution to a problem.
It is an art of scientific investigation.
It is a movement from the known to the un-known and
is a voyage of discovery. It helps the Management
decision process for all aspects of business.
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Research in Business Management is an important tool
of Business Management.
It is a process of gathering relevant information about the
market. It helps find and understand the target markets
and produce products and services accordingly. The tool
is also used to find out and sort out different marketing
issues.
The basic five steps involved in the market research are:
1. Identify and define the problem or objective
2. Design research plan
3. Collect information
4. Analyze information
5. Present findings
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Business Research Defined.
Business research is defined as the
systematic and objective process of
generating information for aid in
making business decisions.
Research information is neither
intuitive nor haphazardly gathered.
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Characteristics of Research
1. A systematic approach is followed in research. Rules and
procedures are an integral part of research that set the
objective of a research process. Researchers need to
practice ethics and code of conduct while making
observations or drawing conclusions.
2. Research is based on logical reasoning and involves both
inductive and deductive methods.
3. The data or knowledge that is derived is in real time, actual
observations in the natural settings.
4. There is an in-depth analysis of all the data collected from
research so that there are no anomalies associated with it.
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5. Research creates a path for generating new questions.
More research opportunity can be generated from existing
research.
6. Research is analytical in nature. It makes use of all the
available data so that there is no ambiguity in inference.
7. Accuracy is one of the important character of research,
the information that is obtained while conducting the
research should be accurate and true to its nature. For
example, research conducted in a controlled environment
like a laboratory. Here accuracy is measured of
instruments used, calibrations, and the final result of the
experiment.
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Basic
Research
Applied
Research
Exploratory
Research
Conclusive
Research
Descriptive
Research
Casual
Research
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What are the types of Research?
Basic Research: Basic research is mostly
conducted to enhance knowledge. It covers
fundamental aspects of research. The main
motivation of this research is knowledge
expansion. It is a non-commercial research and
doesn’t facilitate in creating or inventing
anything.
For example, an experiment is a good example
of basic research.
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Applied Research: Applied research focuses
on analyzing and solving real-life problems. This
type of research refers to the study that helps
solve practical problems using scientific
methods. This research plays an important role
in solving issues that impact the overall well-
being of humans. For example, finding a specific
cure for a disease.
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Exploratory Research:
As the name suggests, exploratory research is
conducted to explore the research questions and
may or may not offer a final conclusion to the
research conducted. It is conducted to handle
new problem areas which haven’t been explored
before. Exploratory research lays the foundation
for more conclusive research and data collection.
For example, a research conducted to know the
level of customer satisfaction among the patrons
of a restaurant.
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Descriptive Research:
It focuses on throwing more light on current issues
through a process of data collection. Descriptive
studies are used to describe the behavior of a
sample population. In descriptive research, only
one variable (anything that has quantity or quality
that varies) is required to conduct a study. The
three main purposes of descriptive research are
describing, explaining and validating the findings.
For example, a research conducted to know if top-
level management leaders in the 21st century
posses the moral right to receive a huge sum of
money from the company profit.
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Explanatory Research: Explanatory research or
causal research, is conducted to understand the
impact of certain changes in existing standard
procedures. Conducting experiments is the most
popular form of casual research. For example,
research conducted to understand the effect of
rebranding on customer loyalty.
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Problem Oriented Research: As the name
suggests, problem-oriented research is
conducted to understand the exact nature of the
problem to find out relevant solutions. The term
“problem” refers to having issues or two
thoughts while making any decisions.
For e.g Revenue of a car company has
decreased by 12% in the last year. The following
could be the probable causes: There is no
optimum production, poor quality of a product,
no advertising, economic conditions etc.
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Problem Solving Research: This type of
research is conducted by companies to
understand and resolve their own problems. The
problem-solving research uses applied research
to find solutions to the existing problems.
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Qualitative Research: Qualitative research is
a process that is about inquiry, that helps in-
depth understanding of the problems or issues in
their natural settings. This is a non- statistical
research method.
Qualitative research is heavily dependent on the
experience of the researchers and the questions
used to probe the sample. The sample size is
usually restricted to 6-10 people in a
sample. Open-ended questions are asked in a
manner that one question leads to another. The
purpose of asking open-ended questions is to
gather as much information as possible from the
sample.
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Quantitative Research: Qualitative research is a structured way of
collecting data and analyzing it to draw conclusions. Unlike
qualitative research, this research method uses a computational,
statistical and similar method to collect and analyze data.
Quantitative data is all about numbers.
Quantitative research involves a larger population as more number of
people means more data. In this manner, more data can be analyzed
to obtain accurate results. This type of research method uses close-
ended questions because, in quantitative research, the researchers
are typically looking at measuring the extent and gathering foolproof
statistical data.
Online surveys, questionnaires, and polls are preferable data
collection tools used in quantitative research. There are various
methods of deploying surveys or questionnaires. In recent times
online surveys and questionnaires have gained popularity. Survey
respondents can receive these surveys on mobile phones, emails or
can simply use the internet to access surveys or questionnaires.
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Uncertainty about the future. ...
Financial management. ...
Monitoring performance. ...
Regulation and compliance. ...
Competencies and recruiting the right talent. ..
Technology. ...
Exploding data. ...
Customer service.
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Sampling is the process of selecting a
representative group from the
population under study. The target
population is the total group of
individuals from which the
sample might be drawn.
A sample is the group of people who
take part in the investigation. The
people who take part are referred to as
“participants”.

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A sample is a subset of the population one is
studying that is selected for the actual
research study. The purpose of sampling
in research to find representative samples to
avoid bias. It is often impractical and sometimes
undesirable to try and study the entire
population.
To draw conclusions about populations from
samples, we must use inferential statistics which
enables us to determine a population`s
characteristics by directly observing only a
portion (or sample) of the population.

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Sampling may be defined as the procedure in
which a sample is selected from an individual or a
group of people of certain kind for research
purpose. In sampling, the population is divided
into a number of parts called sampling units.

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In some types of research the target population might be as broad
as all humans, but in other types of research the target population
might be a smaller group such as teenagers, pre-school children or
people who misuse drugs.
It is more or less impossible to study every single person in a target
population so psychologists select a sample or sub-group of the
population that is likely to be representative of the target population
we are interested in.
If the sample we select is going to represent the target population
then we need to make sure that the people in it are similar to the
other members of the target population. This is important because
we want to generalize from the sample to target population.

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The following sampling methods are
examples of probability sampling:
Simple Random Sampling (SRS)
Stratified Sampling.
Cluster Sampling.
Systematic Sampling.
Multistage Sampling (in which some of
the methods above are combined in
stages)

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1. Random Sampling
Everyone in the entire target population has an equal
chance of being selected.
This is similar to the national lottery. Here the
“population/universe” is any person who has bought a
lottery ticket, then each person has an equal chance of
winning the lottery.
Random samples require a way of naming or numbering
the target population and then using some type of raffle
method to choose those to make up the sample.
Random samples are the best method of selecting your
sample from the population of interest.
The advantages are that your sample should represent
the target population and eliminate sampling bias, but
the disadvantage is that it is very difficult to achieve (i.e.
time, effort and money).

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2. Stratified Sampling
The researcher identifies the different types of people
that make up the target population and works out
the proportions needed for the sample to be
representative.
A list is made of each variable (e.g. IQ, gender etc.)
which might have an effect on the research.
For example, if we are interested in the money spent
on books by undergraduates, then the main subject
studied may be an important variable.
For example, students studying English Literature may
spend more money on books than engineering
students, so if we use a very large percentage of
English students or engineering students then our
results will not be accurate. Cont’d

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Cont’d….
We have to work out the relative percentage of each
group at a university e.g. Engineering 10%, Social
Sciences 15%, English 20%, Sciences 25%, Languages
10%, Law 5%, Medicine 15% The sample must then
contain all these groups in the same proportion as in the
target population (university students).
Gathering such a sample would be extremely time
consuming and difficult to do (disadvantage). This
method is rarely used in Psychology. However,
the advantage is that the sample should be highly
representative of the target population and therefore we
can generalize from the results obtained.

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3. Opportunity Sampling
Uses people from target population available at the time
and willing to take part. It is based on convenience.
An opportunity sample is obtained by asking members of
the population of interest if they would take part in your
research. An example would be selecting a sample of
students from those coming out of the library/picture hall.
This is a quick way and easy of choosing participants
(advantage), but may not provide a representative
sample, and could be biased (disadvantage).

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4. Systematic Sampling
Chooses subjects in a systematic (i.e. orderly / logical)
way from the target population, like every nth participant
on a list of names.
To take a systematic sample, you list all the members of
the population, and then decided upon a sample you
would like. By dividing the number of people in the
population by the number of people you want in your
sample, you get a number we will call n.
If you take every nth name, you will get a systematic
sample of the correct size. If, for example, you wanted
to sample 150 children from a school of 1,500, you
would take every 10th name.
The advantage to this method is that is should provide
a representative sample, but the disadvantage is that it
is very difficult to achieve (i.e. time, effort and money).

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The Multistage Sampling is the probability sampling technique
wherein the sampling is carried out in several stages such that
the sample size gets reduced at each stage.
The multistage sampling is a complex form of cluster sampling.
The cluster sampling is yet another random sampling technique
wherein the population is divided into subgroups called as
clusters; then few clusters are chosen randomly for the survey.
While in the multistage sampling technique, the first level is
similar to that of the cluster sampling, where the clusters are
formed out of the population, but further, these clusters are
sub-divided into smaller targeting groups, i.e. sub-clusters and
then the subject from each sub-clusters are chosen randomly.
Further, the stages can be added depending on the nature of
research and the size of the population under study.

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For example, If the government wants to take a sample
of 10,000 households residing in Madhya Pradesh state.
At the first stage, the state can be divided into the
number districts, and then few districts can be selected
randomly. At the second-stage, the chosen districts can
be further sub-divided into the number of villages and
then the sample of few villages can be taken at random.
Now at the third-stage, the desired number of
households can be selected from the villages chosen at
the second stage. Thus, at each stage the size of the
sample has become smaller and the research study has
become more precise.

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Probability vs. Non-Probability Samples
As a group, sampling methods fall into one of two categories.
Probability samples. With probability sampling methods, each
population element has a known (non-zero) chance of being chosen
for the sample.
Non-probability samples. With non-probability sampling methods,
we do not know the probability that each population element will be
chosen, and/or we cannot be sure that each population element has a
non-zero chance of being chosen.
Non-probability sampling methods offer two potential advantages -
convenience and cost. The main disadvantage is that non-probability
sampling methods do not allow you to estimate the extent to which
sample statistics are likely to differ from population parameters. Only
probability sampling methods permit that kind of analysis.
Non-Probability Sampling Methods
Two of the main types of non-probability sampling methods are
voluntary samples and convenience samples.

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Voluntary sample. A voluntary sample is made up of
people who self-select into the survey. Often, these folks
have a strong interest in the main topic of the survey.
Suppose, for example, that a news show asks viewers to
participate in an on-line poll. This would be a volunteer
sample. The sample is chosen by the viewers, not by the
survey administrator.
Convenience sample. A convenience sample is made up
of people who are easy to reach. Consider the following
example. A pollster interviews shoppers at a local mall. If
the mall was chosen because it was a convenient site from
which to solicit survey participants and/or because it was
close to the pollster's home or business, this would be a
convenience sample.

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Convenience sampling is a non-probability sampling technique
where subjects are selected because of their convenient
accessibility and proximity to the researcher.
The subjects are selected just because they are easiest to recruit for
the study and the researcher did not consider selecting subjects that
are representative of the entire population.
In all forms of research, it would be ideal to test the entire population,
but in most cases, the population is just too large that it is impossible
to include every individual. This is the reason why most researchers
rely on sampling techniques like convenience sampling, the most
common of all sampling techniques. Many researchers prefer this
sampling technique because it is fast, inexpensive, easy and
the subjects are readily available.

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Advantages of sampling
Sampling ensures convenience, collection of intensive
and exhaustive data, suitability in limited resources and
better rapport. In addition to this, sampling has the
following advantages also.
1. Low cost of sampling
If data were to be collected for the entire population, the
cost will be quite high. A sample is a small proportion of
a population. So, the cost will be lower if data is
collected for a sample of population which is a big
advantage.
2. Less time consuming in sampling
Use of sampling takes less time also. It consumes less
time than census technique. Tabulation, analysis etc.,
take much less time in the case of a sample than in the
case of a population.

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3. Scope of sampling is high
The investigator is concerned with the generalization of
data. To study a whole population in order to arrive at
generalizations would be impractical.
Some populations are so large that their characteristics
could not be measured. Before the measurement has been
completed, the population would have changed. But the
process of sampling makes it possible to arrive at
generalizations by studying the variables within a relatively
small proportion of the population.
.

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4. Accuracy of data is high
Having drawn a sample and computed the desired
descriptive statistics, it is possible to determine the
stability of the obtained sample value. A sample
represents the population from which its is drawn. It
permits a high degree of accuracy due to a limited area
of operations. Moreover, careful execution of field work is
possible. Ultimately, the results of sampling studies turn
out to be sufficiently accurate
5. Organization of convenience
Organizational problems involved in sampling are very
few. Since sample is of a small size, vast facilities are not
required. Sampling is therefore economical in respect of
resources. Study of samples involves less space and
equipment.

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6. Intensive and exhaustive data
In sample studies, measurements or observations are
made of a limited number. So, intensive and exhaustive
data are collected.
7. Suitable in limited resources
The resources available within an organization may be
limited. Studying the entire universe is not viable. The
population can be satisfactorily covered through
sampling. Where limited resources exist, use of
sampling is an appropriate strategy while conducting
marketing research.
8. Better rapport
An effective research study requires a good rapport
between the researcher and the respondents. When the
population of the study is large, the problem of rapport
arises. But manageable samples permit the researcher
to establish adequate rapport with the respondents.

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Disadvantages of sampling
The reliability of the sample depends upon the
appropriateness of the sampling method used. The
purpose of sampling theory is to make sampling more
efficient. But the real difficulties lie in selection,
estimation and administration of samples.
Disadvantages of sampling may be discussed under
the heads:
Chances of bias
Difficulties in selecting truly a representative sample
Need for subject specific knowledge
changeability of sampling units
impossibility of sampling.

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1. Chances of bias
The serious limitation of the sampling method is that it
involves biased selection and thereby leads us to draw
erroneous conclusions. Bias arises when the method of
selection of sample employed is faulty. Relative small
samples properly selected may be much more reliable
than large samples poorly selected.
2. Difficulties in selecting a truly representative
sample
Difficulties in selecting a truly representative sample
produces reliable and accurate results only when they
are representative of the whole group. Selection of a
truly representative sample is difficult when the
phenomena under study are of a complex nature.
Selecting good samples is difficult.

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3. Changeability of units
When the units of the population are not in
homogeneous, the sampling technique will be
unscientific. In sampling, though the number of cases is
small, it is not always easy to stick to the, selected
cases. The units of sample may be widely dispersed.
Some of the cases of sample may not cooperate with
the researcher and some others may be inaccessible.
Because of these problems, all the cases may not be
taken up. The selected cases may have to be replaced
by other cases. Changeability of units stands in the way
of results of the study.

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4. In adequate knowledge in the subject
Use of sampling method requires adequate subject
specific knowledge in sampling technique. Sampling
involves statistical analysis and calculation of probable
error. When the researcher lacks specialized knowledge in
sampling, he may commit serious mistakes.
Consequently, the results of the study will be misleading.
5. Impossibility of sampling
Deriving a representative sample is di6icult, when the
universe is too small or too heterogeneous. In this case,
census study is the only alternative. Moreover, in studies
requiring a very high standard of accuracy, the sampling
method may be unsuitable. There will be chances of
errors even if samples are drawn most carefully.

Research in business management an introduction.

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