business research management

1. UNIT 1
INTRODUCTION OF RESEARCH

2. RESEARCH
• The systematic investigation into and study of materials and sources
in order to establish facts and reach new conclusions.
• According to the American sociologist Earl Robert Babbie, “research is
a systematic inquiry to describe, explain, predict, and control the
observed phenomenon. It involves inductive and deductive methods.”

3. PURPOSE OF RESEARCH
• The basic purpose of research:
1. To learn something
2. To gather evidence

5. PURPOSE OF RESEARCH
Exploratory
Research
Descriptive
Research
EXPLANATORY
RESEARCH
Approach used Unstructured Structured Highly structured
Conducted through Asking questions Asking questions
By using
hypotheses.
Time
Early stages of
decision making
Later stages of
decision making
Later stages of
decision making

7. CHARACTERISTICS OF GOOD RESEARCH
1. Clearly defined
2. State limitation and
Assumption
3. Planned
4. Sufficiency of data.
5. Generalization
6. Systematic
7. Logical
8. Empirical
9. Replicable
10. Integrity and
commitment

8. Business Research
1. Business research is a process of acquiring detailed information of all the areas
of business and using such information in maximizing the sales and profit of the
business.
2. Such a study helps companies determine which product/service is most
profitable or in demand.

9. SCOPE OF RESEARCH
ENVIORNMENTAL
TECHNOLOGICAL
INNOVATION
COMPETITORS ANALYSIS
MARKET ANALYSIS
NEW MARKET ANALYSIS
NEW PRODUCT
DEVELOPMENT
MARKETING
PRODUCT
PRICE
PLACE
PROMOTION
SALES
CUSTOMER
ORGANIZATIONAL
HRM
FINANCE
PRODUCT
ORGANIZATIONAL
EFFECTIVENESS AND
SUCCESS

10. TYPES OF RESEARCH

12. Pure Research
• Basic research is a type of research approach that is aimed at gaining a better
understanding of a subject, phenomenon or basic law of nature.
• This type of research is primarily focused on the advancement of knowledge rather than
solving a specific problem.
• The term ‘basic’ indicates that, through theory generation, basic research provides the
foundation for applied research. This approach of research is essential for nourishing the
expansion of knowledge.
• Basic research rarely helps practitioners directly with their everyday concerns but can
stimulate new ways of thinking about our daily lives.
• Example:
• An investigation looking at whether stress levels influence how often students engage
in academic cheating
• A study looking at how caffeine consumption impacts the brain
• A study assessing whether men or women are more likely to be diagnosed with
depression

13. Applied Research
• The pursuit of information that can be directly applied to practice is aptly known
as applied research.
• The goal of this research is to determine the applicability of theory and principles
by testing hypotheses within specific settings.
• The problem-solving nature of applied research means it is conducted to reveal
answers to specific questions related to action, performance, or policy needs.
• Applied research is designed to solve practical problems of the modern world,
rather than to acquire knowledge for knowledge’s sake.
• Example:
• Improve agricultural crop production;
• Treat or cure a specific disease;
• Improve the energy efficiency of homes, offices, or modes of transportation

14. Exploratory Research
• A research used to investigate a problem which is not clearly defined.
• It is conducted to have a better understanding of the existing problem, but
will not provide conclusive results.
• For such a research, a researcher starts with a general idea and uses this
research as a medium to identify issues, that can be the focus for future
research.
• An important aspect here is that the researcher should be willing to change
his/her direction subject to the revelation of new data or insight.
• Such a research is usually carried out when the problem is at a preliminary
stage.
• It is often referred to as grounded theory approach or interpretive research
as it used to answer questions like what, why and how.

15. Characteristics of Exploratory Research
• Exploratory research is inexpensive, highly interactive and open-ended in nature.
• There is usually no prior relevant information available from past researchers.
• It has no predefined structure.
• It answers questions like how and why aiding the researcher to acquire more
information about the research.
• The absence of relevant information from past research means the researcher
will spend a lot of time studying materials in detail. Therefore, spending so much
time conducting exploratory research.
• Since there is no standard for carrying out exploratory research, it is usually
flexible and scattered.
• There must a few theories which can verify your outcome.
• Researchers cannot form a conclusion based on exploratory research.
• The research problem must be important and valuable
• Exploratory research mostly deals with qualitative data.

16. Descriptive Research
• Descriptive research definition: Descriptive research is defined as a research method that
describes the characteristics of the population or phenomenon studied. This
methodology focuses more on the “what” of the research subject than the “why” of the
research subject.
• The descriptive research method primarily focuses on describing the nature of a
demographic segment, without focusing on “why” a particular phenomenon occurs. In
other words, it “describes” the subject of the research, without covering “why” it
happens.
E.g.
• Market researchers want to observe the habits of consumers.
• A company wants to evaluate the morale of its staff.
• A school district wants to understand if students will access online lessons rather than
textbooks.
• To understand if its wellness programs enhance the overall health of the employees.

17. Characteristic Qualitative market research Quantitative market research
Is well suited to… •Understanding the "how" or "why" behind
specific behaviors or attitudes
•Projects where the dynamics of a market or
decision-making process are not well-
understood
•Niche audiences, because quantitative
research may not be possible
•The initial stages of a larger program of
research – especially to further scope or refine
the design of later phases of the project
•Studies where measurement is the primary
objective
•Mass market audiences – such as consumer
markets or small businesses
•Projects that require a high level of statistical
confidence in the results
•Where the structure of a market is known and
research respondents are familiar with the
language that is used in questions
Sample sizes (number of
interviews, observations
etc.)
Small numbers – Frequently fewer than 100
responses
Larger numbers – Survey sample sizes are often
in the 100s or 1000s
Time taken Dependent on sample sizes, but simple qual
studies can be completed in days or just a few
weeks
The fieldwork phase for quant studies may
take many weeks or months to complete
How the data is reported Data are presented thematically, capturing the
main "stories" behind the data. Individual
responses in the form of videos, quotes and
audio are often used to demonstrate a specific
theme.
Usually charts, aggregated tables and
other statistical plots.

18. Unit of Analysis and Unit of Observation
1. A unit of analysis is the entity that you wish to be able to say something about at
the end of your study, probably what you would consider to be the main focus of
your study.
The first step in deciding how you will analyze the data is to define a unit of analysis (Trochim, 2006).
• Your unit of analysis is the “who” or the “what” that you are analyzing for your study.
• Your unit of analysis could be an individual student, a group, or even an entire program.
It is important to understand that your unit of analysis is not the same as your unit of
observation. It is possible to analyze data in various ways.
2. The unit of observation is the unit described by one's data. A unit of observation is
the item (or items) that you actually observe, measure, or collect in the course of trying
to learn something about your unit of analysis.
For example, a study may treat groups as a unit of observation with a country as the
unit of analysis, drawing conclusions on group characteristics from data collected at the
national level.

19. Concept
Construct
Variable
Single Dimensional
construct
Multi Dimensional
construct

20. CONCEPT
• Explanations require development of concepts or generalizable properties or
characteristics associated with objects, events, or people.
• While objects such as a person, a firm, or a car are not concepts, their specific
characteristics or behavior such as a person’s attitude toward immigrants, a firm’s
capacity for innovation, and a car’s weight can be viewed as concepts.
• Knowingly or unknowingly, we use different kinds of concepts in our everyday
conversations. Some of these concepts have been developed over time through
our shared language.
• Sometimes, we borrow concepts from other disciplines or languages to explain a
phenomenon of interest. For instance, the idea of gravitation borrowed from
physics can be used in business to describe why people tend to “gravitate” to
their preferred shopping destinations.
• Likewise, the concept of distance can be used to explain the degree of social
separation between two otherwise collocated individuals. Sometimes, we create
our own concepts to describe a unique characteristic not described in prior
research. For instance, technostress is a new concept referring to the mental
stress one may face when asked to learn a new technology.

21. CONSTRUCT
• Concepts may also have progressive levels of abstraction. Some concepts such as
a person’s weight are precise and objective, while other concepts such as a
person’s personality may be more abstract and difficult to visualize.
• A construct is an abstract concept that is specifically chosen (or “created”) to
explain a given phenomenon.
• A construct may be a simple concept, such as a person’s weight, or a
combination of a set of related concepts such as a person’s communication skill,
which may consist of several underlying concepts such as the
person’s vocabulary, syntax, and spelling.
• The former instance (weight) is a unidimensional construct, while the latter
(communication skill) is a multi-dimensional construct (i.e., it consists of multiple
underlying concepts).
• The distinction between constructs and concepts are clearer in multi-dimensional
constructs, where the higher order abstraction is called a construct and the lower
order abstractions are called concepts. However, this distinction tends to blur in
the case of unidimensional constructs.

22. VARIABLE
QUALITATIVE AND
QUANTITATIVE
DEPENDENT
INDEPENDENT
MEDIAITNG
MODERATING
EXTRANEOUS
CONTINOUS, DISCRETE,
CATEGORICAL
MEASURING VARIABLE
NOMINAL
ORDINAL
INTERVAL
RATIO

23. VARIABLES
• A variable is, as the name applies, something that varies. Age, sex, export, income and
expenses, family size, country of birth, capital expenditure, class grades, blood pressure
readings, preoperative anxiety levels, eye color, and vehicle type are all examples of
variables because each of these properties varies or differs from one individual to
another.
•
A variable is any property, a characteristic, a number, or a quantity that increases or
decreases over time or can take on different values (as opposed to constants, such as n,
that do not vary) in different situations.
• When conducting research, experiments often manipulate variables. For example, an
experimenter might compare the effectiveness of four types of fertilizers.
•
In this case, the variable is the ‘type of fertilizers’. A social scientist may examine the
possible effect of early marriage on divorce.
• Here early marriage is the variable. A business researcher may find it useful to include
the dividend in determining the share prices. Here dividend is the variable.
• Effectiveness, divorce and share prices are also variables because they also vary as a
result of manipulating fertilizers, early marriage, and dividends.

24. QUALITATIVE VARIABLE
• Qualitative variables are those that express a qualitative attribute
such as hair color, religion, race, gender, social status, method of
payment, and so on. The values of a qualitative variable do not imply
a meaningful numerical ordering.
• The value of the variable ‘religion’ (Muslim, Hindu, ..,etc.) differs
qualitatively; no ordering of religion is implied. Qualitative variables
are sometimes referred to as categorical variables.
• For example, the variable sex has two distinct categories: ‘male’ and
‘female.’ Since the values of this variable are expressed in categories,
we refer to this as a categorical variable.

25. Quantitative Variables
• Quantitative variables, also called numeric variables, are those variables
that are measured in terms of numbers. A simple example of a quantitative
variable is a person’s age.
• The age can take on different values because a person can be 20 years old,
35 years old, and so on. Likewise, family size is a quantitative variable,
because a family might be comprised of one, two, three members, and so
on.
• That is, each of these properties or characteristics referred to above varies
or differs from one individual to another. Note that these variables are
expressed in numbers, for which we call them quantitative or sometimes
numeric variables.
• A quantitative variable is one for which the resulting observations are
numeric and thus possesses a natural ordering or ranking.

26. INDEPENDENT & DEPENDENT VARIABLE
• In many research settings, there are
two specific classes of variables that
need to be distinguished from one
another, independent
variable and dependent variable.
• Many research studies are aimed at
unrevealing and understanding the
causes of underlying phenomena or
problems with the ultimate goal of
establishing a causal relationship
between them.
Look at the following statements:
1. Low intake of food causes
underweight.
2. Smoking enhances the risk of lung
cancer.
3. Level of education influences job
satisfaction.
4. Advertisement helps in sales
promotion.
5. The drug causes the improvement
of a health problem.
6. Nursing intervention causes more
rapid recovery.
7. Previous job experiences
determine the initial salary.
8. Blueberries slow down aging.
9. The dividend per share
determines share prices.
•

27. INDEPENDENT VARIABLE
• The variable that is used to describe or measure the factor that is assumed to cause or at
least to influence the problem or outcome is called an independent variable.
• The definition implies that the experimenter uses the independent variable to describe
or explain the influence or effect of it on the dependent variable.
• Variability in the dependent variable is presumed to depend on variability in the
independent variable.
• Depending on the context, an independent variable is sometimes called a predictor
variable, regressor, controlled variable, manipulated variable, explanatory variable,
exposure variable (as used in reliability theory), risk factor (as used in medical statistics),
feature (as used in machine learning and pattern recognition) or input variable.
• The explanatory variable is preferred by some authors over the independent variable
when the quantities treated as independent variables may not be statistically
independent or independently manipulable by the researcher.
• If the independent variable is referred to as an explanatory variable, then the term
response variable is preferred by some authors for the dependent variable.

28. DEPENDENT VARIABLE
• The variable that is used to describe or measure the problem or
outcome under study is called a dependent variable.
• In a causal relationship, the cause is the independent variable, and
the effect is the dependent variable. If we hypothesize that smoking
causes lung cancer, ‘smoking’ is the independent variable and cancer
the dependent variable.
• A business researcher may find it useful to include the dividend in
determining the share prices. Here dividend is the independent
variable, while the share price is the dependent variable.

29. DEPENDENT VARIABLE
• Depending on the context, a dependent variable is sometimes called
a response variable, predicted variable, measured variable, explained
variable, experimental variable, responding variable, outcome
variable, output variable, or label.
• An explained variable is preferred by some authors over the
dependent variable when the quantities treated as dependent
variables may not be statistically dependent.
• If the dependent variable is referred to as an explained variable, then
the term predictor variable is preferred by some authors for the
independent variable.

30. Moderating Variable
• A moderator is a variable that affects the strength of the relation between the
predictor and criterion variable. Moderators specify when a relation will hold. It
can be qualitative (e.g., sex, race, class…) or quantitative (e.g., drug dosage or
level of reward).
• Moderating variable are typically an interaction term in statistical models.
• For instance, imagine researchers are evaluating the effects of a new cholesterol
drug. The researchers vary the participants in minutes of daily exercise
(predictor/independent variable) and measure their cholesterol levels after 30
days (criterion/dependent variable).
• They find that at low drug doses, there is a small association between exercise
and cholesterol levels, but at high drug doses, there is a huge association
between exercise and cholesterol levels. Drug dosage moderates the association
between exercise and cholesterol levels.
• If you are focusing on the relationship between the age of the trainees and work
performance, you might use ‘type of training’ as a moderating variable.

31. MEDIATING VARIABLE
• A mediating variable explains the relation between the independent
(predictor) and the dependent (criterion) variable. It explains how or
why there is a relation between two variables.
• A mediator can be a potential mechanism by which an independent
variable can produce changes on a dependent variable.
• When you fully account for the effect of the mediator, the relation
between independent and dependent variables may go away.
• For instance, imagine that you find a positive association between
note-taking and performance on an exam. This association may be
explained by number of hours studying, which would be the
mediating variable.

32. HYPOTHESIS
• Hypothesis is an assumption that is made on the basis of some evidence.
• This is the initial point of any investigation that translates the research questions
into a prediction.
• It includes components like variables, population and the relation between the
variables.
• A research hypothesis is a hypothesis that is used to test the relationship
between two or more variables.
• A hypothesis is a tentative generalization, the validity of which remains to be
tested.

33. Characteristics of Hypothesis
• The hypothesis should be clear and precise to consider it to be reliable.
• If the hypothesis is a relational hypothesis, then it should be stating the
relationship between variables.
• The hypothesis must be specific and should have scope for conducting
more tests.
• The way of explanation of the hypothesis must be very simple and it should
also be understood that the simplicity of the hypothesis is not related to its
significance.

34. Types of Hypothesis
• There are six forms of hypothesis and they are:
• Simple hypothesis
• Complex hypothesis
• Directional hypothesis
• Non-directional hypothesis
• Null hypothesis
• Associative and casual hypothesis
•

35. RESEARCH
PROCESS
PROBLEM IDENTIFICATION & DEFINITION &
FORMULATION
CONDUCTING THE LITERATURE REVIEW
RESEARCH DESIGN- SELECTING METHODS OF
RESEARCH
DATA COLLECTION
DATA ANALYSIS
REPORT WRITING