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MKI/RM/FMS 1 04/08/23

RESEARCH METHODOLOGY

WHAT IS 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 formulated hypothesis.”

- Clifford Woody.

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WHAT IS RESEARCH ?“The manipulation of things, concepts and symbols for the purpose of generalizing to extend, correct or verify knowledge, whether that knowledge aidsin construction of theory or in the practice of an art.”- D. Slesinger and M.Stephenson“Search for knowledge through objective and systematic method of finding solutions to a problem is research”- C.R.Kothari

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RESEARCH MOTIVES

Inquisitiveness (Jidnyasa)

Uncomfortable with uncertainness

Sustainable growth of business

Academic and career excellence

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Objectives of Research

√ Disciplined inquiry for taking decision in management

dilemma related to functional areas like marketing, HR,

Finance, System, Operations etc.

√ To understand formulative or descriptive characteristics of the

elements involved in decision making, frequency of their

occurrence and associative or causal relationship amongst

them.

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Objectives of Research

To know and understand a phenomenon.

To know characteristics of a situation

To know frequency and association between two or more

entities or events

To know the causal relationship between two or more entities

or events

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Utility of research :

√ Inculcation of scientific, logical and inductive thinking.

√ Basis for governmental policies,

√ Solving operational and planning problems of business and

industry,

√ Seeking answers to social problems.

√ Useful for academicians, consultants etc.

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TYPES OF RESEARCH

Descriptive V/s Analytical

Descriptive research, also known as statistical research,

describes data and characteristics about the population or

phenomenon being studied. Descriptive research answers the

questions who, what, where, when and how...

Descriptive research cannot be used to create a causal

relationship, where one variable affects another.

In short descriptive research deals with everything that can be

counted and studied.

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TYPES OF RESEARCH Descriptive V/s Analytical

Analytical research identifies patterns in the description of the

population and tries to find out the logical relationship or causal

relationship in the patterns. Analytical research answers the

Question why.

For example, if the descriptive research gives the educational

background of students joining PGDM, the analytical research

will find the pattern as more students from Engineering and

commerce background join the programme. Further it will also

try to establish the cause for this phenomenon.

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TYPES OF RESEARCH Fundamental V/s Applied

Fundamental research (also called basic or pure research) has

as its primary objective the advancement of knowledge and the

theoretical understanding of the relations among variables. It is

exploratory and often driven by the researcher’s curiosity, interest

or hunch. It is conducted without a practical end in mind.

Maslow’s theory or McGregor’s theory is a fundamental research.

Through theory generation, basic research provides the

foundation for further, often applied research.

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TYPES OF RESEARCH Fundamental V/s Applied

Applied research is done to solve specific, practical questions.

Its primary aim is not to gain knowledge for its own sake.

It can be exploratory but often it is descriptive.

It is almost always done on the basis of basic research.

Theory of elasticity of demand to price is a basic research which

can be applied to find out what price should be fixed for a

particular product to get desired market share is an applied

research.

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TYPES OF RESEARCH Exploratory V/s Diagnostic

Exploratory research is conducted into an issue or problem

where there are few or no earlier studies to refer to. The focus

is on gaining insights and familiarity for later investigation.

Diagnostic research is aimed at finding out the root

cause of a problem such as falling sales, increase in

suicides by students etc.

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TYPES OF RESEARCH

Conceptual V/s Empirical

Conceptual Research aims at bringing clarity in concepts to

form the basis for further research.

Concepts like income, intelligence, leadership need research to

find out common understanding by respondents.

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TYPES OF RESEARCH Conceptual V/s Empirical

Empiricism refers to a theory of knowledge in philosophy which

adheres to the principle that knowledge arises from experience

and evidence gathered specifically using the senses. In scientific

use the term empirical refers to the gathering of data using only

evidence that is observable by the senses or in some cases using

calibrated scientific instruments.

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RESEARCH APPROACHESQuantitative approach (Collection of quantitative data and analysis)

1. Inferential – To form a database for inferences2. Experimental – Manipulation of variable in controlled

environment3. Simulation – Operation of numerical model which

represents the structure of a dynamic process.

Qualitative approach

Subjective assessment of attitudes, opinions and behaviour.

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Research Process

Steps in research :

1. Define research problem – What is to be found out ?

2. Review concepts/theory, Review previous research finding:

-- What research work has been done so far ?

3. Formulate hypotheses – What is the likely out come ? or

researcher’s learned opinion ?

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Research Process

Steps in research :

4. Research design –

What information is needed ? Who will give the information ?

from how many to collect the information ? how to collect and

analyse the information ?

5. Data collection – What is the response to the questions ?

6. Data analysis and interpretation – Do the hypotheses test positive or otherwise ?

7. Report – how to present the findings, conclusions and suggestions ?

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The Research Process(As described by Cooper & Schindler)

The researcher

encounters a curiosity, doubt, suspicion, or obstacle.

struggles to state the problem – asks questions, contemplates

existing knowledge, gathers facts and moves from an

emotional to an intellectual confrontation with the problem.

Proposes hypothesis to explain the facts that are believed to

be logically related to the problem.

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The researcher

Deducts outcome or consequences of the hypothesis –

attempts to discover what happens if the results are in the

opposite direction of that predicted or if the results support

the expectations.

Formulates several rival hypotheses.

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The researcher

Devises and conducts a crucial empirical test with various possible outcomes, each of which selectively excludes one or more hypotheses.

Draws a conclusion (an inductive inference) based on acceptance or rejection of the hypotheses.

Feeds information back into the original problem, modifying it according to the strength of the evidence.

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RELIABILITY AND VALIDITY IN RESEARCH

Reliability : The accuracy and precision of a

measurement procedure.

Validity : Extent to which a test measures what

we actually want to measure.

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METHODS FOR RELIABILITY ESTIMATES

Test – retest :

1. Implement the measuring instrument at two separate times for each subject

2. Compute the correlation between the two separate measurements

3. Assume that there is no change in the underlying conditions between the two separate measurements.

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METHODS FOR RELIABILITY ESTIMATES

Internal consistency :

Two sets of questions aimed at measuring the same

concept are administered to the same respondent and

correlation is found out.

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METHODS FOR VALIDITY ESTIMATES

1. Content Validity : Extent to which the measuring instrument provides adequate coverage of the investigative questions guiding the study.

2. Criterion validity : Extent to which each criteria can be correctly measured. E.g. income of a family.

3. Construct Validity : Extent to which the scales of measurement represent the actual opinions. ( 1 to 10 scale or very good to very poor scale)

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RESEARCH DESIGN

“Research design is the arrangement of conditions for

collection and analysis of data in a manner that aims to

combine relevance to research purpose with economy in

procedure”

- Claire Selltiz et.al.

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Importance of proper research design :

Without a proper research design the purpose or the objective of

the research will not be served. The reliability of the research

finding depends greatly on the research design.

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STEPS IN RESEARCH DESIGN 1. What is our problem ?2. What information will help in answering our problem ?3. What outcome is expected ?4. Who will give this information?5. From how many shall the information be collected ?6. How shall the information be collected?7. Who will collect the information ?8. How will the information be analyzed ?9. How will the conclusions be reported ?10. What are the constraints of time and money?

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FEATURES OF A GOOD RESEARCH DESIGN

Clear objective Relevant information gathering Well formulated hypotheses Representative sample profile and size Appropriate research instruments Appropriate investigators Appropriate tools for data analysis User oriented reporting Optimum utilization of available resources

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RESEARCH DESIGN & TYPES OF RESEARCH

Type of research Characteristics of design

Exploratory

Or

Formulative

Only formulating problem or working hypothesis Flexible More literature survey and experience survey

Descriptive

Or diagnostic

Need valid and reliable data Quantitative/qualitative analysis important

Hypothesis testing research

Experimental interventionExperimental intervention Cause-effect studyCause-effect study

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EXPERIMENTAL RESEARCH DESIGN

An experiment is a study involving intervention by the researcher

beyond that required for measurement.

The usual intervention is to manipulate some variable in setting

and observe how it affects the participants or subjects being

studied. (People or physical entities)

The researcher manipulates the independent or explanatory

variable and then observes whether the hypothesized dependent

variable is affected by the intervention.

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INDEPENDENT VARIABLE (IV)The variable manipulated by the researcher, thereby causing an effect on the dependent variable. Independent variable is also known as explanatory variable or predictor variable.

DEPENDENT VARIABLE (DV) A measured predicted or otherwise monitored variable expected to be affected by manipulation of an independent variable.Dependent variable is also known as criterion variable.

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CONTROL GROUPA group that is measured but not exposed to experimental treatment.

REPLICATION The process of repeating an experiment with different participant groups, and conditions to determine the average effect of the independent variable across people, situations and times.

FIELD EXPERIMENTATION A study of the dependent variable in actual environmental conditions

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SAMPLE DESIGN

A sample design is a definite plan for obtaining a

sample from a given population.

It refers to the technique or procedure the researcher

would adopt in selecting items for the sample

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STEPS IN SAMPLE DESIGN1. Type of Universe – Finite and infinite2. Sampling unit – geographic, Social3. Source list – Sampling frame4. Size of sample – Optimal in number, precision and

cost.5. Parameters of interest – answering relevant questions 6. Budgetary constraints - Cost considerations 7. Sampling procedure – Technique of collecting sample.

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SAMPLING PROCEDUREThe sampling procedure shall avoid1. Systematic bias : Error in sampling procedure due to

inappropriate sampling frame, Defective measuring device, non-respondents, abnormal behaviour under observation etc.

2. Sampling error : random variation in the sample estimate around the true population parameters.

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SAMPLING DESIGN

Sample Size :

Too small sample size may not be representative and hence

generalization may not be possible.

Too large sample size will lead to high cost and wastage of

resources. Optimum size can be decided by considering the

following factors.

√ Nature of Universe – Homogenous or heterogeneous ?

(Dispersion)

√ Number of classes – Groups and subgroups in the universe.04/08/23 35MKI/RM/FMS

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SAMPLING DESIGN

Sample Size : (Cont.)

√ Nature of study – intense and continuous or general survey ?

√ Type of sampling – random sampling or non-probability

sampling ?

√ Accuracy and confidence level – High or low ?

√ Availability of finance – low or high ?

√ Time frame – short or long ?

√ Probability of no response or wasted responses – High or low ?

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CHARACTERISTICS OF A GOOD SAMPLE DESIGN

True representation of the population/universe

Small sampling error

Viable within the given budget

Minimum systemic bias

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RANDOM SAMPLING DESIGN

Selection

technique

Probability

sampling

Non- Probability

sampling

Unrestricted

sampling

Simple random sampling (Random number tables by Fisher, Yates, Tippett)

Convenience sampling

Restricted

sampling

Complex random sampling like Systematic, stratified, Clustered etc.

Purposive sampling like quota or judgment sampling

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COMPLEX RANDOM SAMPLING DESIGN

Systematic Random sampling

Suppose if 10 % sampling out of 1000 population size is to be taken, then every 10th member is selected as 1st, 11th, 21st, 31st and so on till 91st member.

Stratified Random sampling

If the population is not a homogenous group, then total population is divided into strata with homogenous members and proportionate sample is selected.

Cluster Sampling When the total area of interest is large, the area is divided into smaller non-overlapping areas and equal samples are selected from each subarea randomly.If the area is divided in ten clusters and the total sample size is 1000, then 100 samples will be selected from each cluster.

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Probability sample:

Unrestricted Simple random sampling – Every item of the

universe has an equal chance of inclusion in the sample.

Random number tables by Fisher, Yates, Tippett are used for

selection of sample.

Restricted complex random sampling

■ Systematic Random sampling – Suppose if 10 % sampling out

of 1000 population size is to be taken, then every 10th member is

selected as 1st, 11th, 21st, 31st and so on till 91st member.

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Probability sample:

■ Stratified Random sampling – If the population is not a

homogenous group, then total population is divided into strata

with homogenous members and proportionate sample is selected.

■ Cluster Sampling - When the total area of interest is large, the

area is divided into smaller non-overlapping areas and equal

samples are selected from each subarea randomly. If the area is

divided in ten clusters and the total sample size is 1000, then 100

samples will be selected from each cluster.

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Non-probability sample:

Unrestricted sampling – Convenience sampling.

Restricted sampling – Purposive sampling like quota or judgment

sampling.

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