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Master of Business Administration-MBA Semester 3

ASSIGNMENT

RESEARCH METHODOLOGY - MB0050

Question 1: What do you mean by research? Explain its significance in social and business sciences.

Answer 1:

Research simply means a search for facts answers to questions and solutions to problems. It is a

purposive investigation. It is an organized inquiry. It seeks to find explanations to unexplained

phenomenon to clarify the doubtful facts and to correct the misconceived facts.

The search for facts may be made through either:

Arbitrary (or unscientific) Method:Its a method of seeking answers to question consists of imagination,

opinion, blind belief or impression. E.g. it was believed that the shape of the earth was flat; a big snake

swallows sun or moon causing solar or lunar eclipse. It is subjective; the finding will vary from person to

person depending on his impression or imagination. It is vague and inaccurate. Or

Scientific Method: this is a systematic rational approach to seeking facts. It eliminates the drawbacks of

the arbitrary method. It is objective, precise and arrives at conclusions on the basis of verifiable

evidences.

Therefore, search of facts should be made by scientific method rather than by arbitrary method. Then

only we may get verifiable and accurate facts. Hence research is a systematic and logical study of an

issue or problem or phenomenon through scientific method.

Young defines Research as a scientific undertaking which, by means of logical and systematic

techniques, aims to:

a) Discover of new facts or verify and test old facts,

b) Analyze their sequences, interrelationships and causal explanations,

c) Develop new scientific tools, concepts and theories which would facilitate reliable and valid study of

human behaviour.

d) Kerlinger defines research as a systematic, controlled, empirical and critical investigation of

hypothetical propositions about the presumed relations among natural phenomena.

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Significance of Research in Social and Business Sciences

According to a famous Hudson Maxim, All progress is born of inquiry. Doubt is often better than

overconfidence, for it leads to inquiry, and inquiry leads to invention. It brings out the significance of

research, increased amounts of which makes progress possible. Research encourages scientific and

inductive thinking, besides promoting the development of logical habits of thinking and organization.

The role of research in applied economics in the context of an economy or business is greatly increasing

in modern times. The increasingly complex nature of government and business has raised the use of

research in solving operational problems. Research assumes significant role in formulation of economic

policy, for both the government and business. It provides the basis for almost all government policies of

an economic system. Government budget formulation, for example, depends particularly on the analysis

of needs and desires of the people, and the availability of revenues, which requires research. Research

helps to formulate alternative policies, in addition to examining the consequences of these alternatives.

Thus, research also facilitates the decision making of policy-makers, although in itself it is not a part of

research. In the process, research also helps in the proper allocation of a countrys scare resources.

Research is also necessary for collecting information on the social and economic structure of an

economy to understand the process of change occurring in the country. Collection of statistical

information though not a routine task, involves various research problems. Therefore, large staff of

research technicians or experts is engaged by the government these days to undertake this work. Thus,

research as a tool of government economic policy formulation involves three distinct stages of operation

which are as follows:

Investigation of economic structure through continual compilation of facts

Diagnoses of events that are taking place and the analysis of the forces underlying them; and

The prognosis, i.e., the prediction of future developments

Research also assumes a significant role in solving various operational and planning problems associated

with business and industry. In several ways, operations research, market research, and motivational

research are vital and their results assist in taking business decisions. Market research is refers to the

investigation of the structure and development of a market for the formulation of efficient policies

relating to purchases, production and sales. Operational research relates to the application of logical,

mathematical, and analytical techniques to find solution to business problems such as cost minimization

or profit maximization, or the optimization problems. Motivational research helps to determine why

people behave in the manner they do with respect to market characteristics. More specifically, it is

concerned with the analyzing the motivations underlying consumer behaviour. All these researches are

very useful for business and industry, which are responsible for business decision making.

Research is equally important to social scientist for analyzing social relationships and seeking

explanations to various social problems. It gives intellectual satisfaction of knowing things for the sake of

knowledge. It also possesses practical utility for the social scientist to gain knowledge so as to be able to

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do something better or in a more efficient manner. This, research in social sciences is concerned with

both knowledge for its own sake, and knowledge for what it can contribute to solve practical problems.

Question 2: What is meant by validity How does it differ from reliability and what are its types?

Answer :--

Validity - This means that a measurement scale should measure what it is supposed to measure.

Validity may be classified into different types, as described below. The degree of validity of each type is

determined by applying logic, statistical procedures or both.

1. Content validity: This type of validity may be of two types - a) Face validity and b) Sampling validity.

Face validity is determined through a subjective evaluation of a measuring scale. For example, a

researcher may develop a scale to measure consumer attitudes towards a brand and pre-test the scale

among a few experts. If the experts are satisfied with the scale, the researcher may conclude that the

scale has face validity. However, the limitation of this type of validity is that it is determined by opinions,

rather than through a statistical method.

Sampling validity refers to how representative the content of the measuring instrument is. In other

words, the measuring instrument's content must be representative of the content universe of the

characteristic being measured.

For example, if attitude is the characteristic being measured, its content universe may comprise

statements and questions indicating which aspects of attitude need to be measured. In this case,

sampling validity will be determined by comparing the items in the measuring instrument with the items

in the content universe.Sampling validity, like face validity, is also based on the judgment and subjective evaluation of both the

researcher and outside experts. The determination of the content universe and the selection of the

relevant items that are to be included in the measuring scale are both done based on the knowledge

and skill of the investigator and other judges.2. Predictive validity: This type of validity refers to the

extent to which one behavior can be predicted based on another, based on the association between the

results yielded by the measuring instrument and the eventual outcome.3. Construct validity: A construct

is a conceptual equation that is developed by the researcher based on theoretical reasoning. Various

kinds of relationships may be perceived by the researcher between a variable under study and other

variables2.4.2 Reliability

This refers to the ability of a measuring scale to provide consistent and accurate results. To give a simpleexample, a weighing machine may be said to be reliable if the same reading is given every time the same

object is weighed.

Question3a :--. Why is a Literature Review Important?

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Answer: --

To build knowledge and identify research methodologies and seminal works in your field.

To help focus and refine your research question by articulating the knowledge gap.

Provide the intellectual context for your work and situate it within the field.

Ensure you will not be replicating existing knowledge or reproducing technical errors.

Identify other researchers in your field (a researcher network is a valuable resource).

Identify the distinctive contribution your research will make and to produce a rationale and

justification for your study.

Learn how research findings are discussed and presented in your discipline area.

In addition to expanding your knowledge about a research area, undertaking a literature reviewis useful for:

Information seeking, as it hones your ability to locate and peruse the relevant literature

efficiently and effectively.

Critical analysis, as it enhances your ability to apply analytical principles in identifying unbiased

and valid research in your area.

For assistance contact your supervisor or theResearch Services Librarian

Question 3b:--. What are the Criteria of a good research problem?

Answer: --

A good research problem must support multiple perspectives. The problem most be phrased in a way

that avoids dichotomies and instead supports the generation and exploration of multiple perspectives. A

general rule of thumb is that a good problem is one that would generate a variety of viewpoints from a

composite audience made up of reasonable people.

A good research problem must be researchable. It seems a bit obvious, but more than one instructor has

found herself or himself in the midst of a complex collaborative research project and realized that

students don't have much to draw on for research, nor opportunities to conduct sufficient primary

research. Choose research problems that can be supported by the resources available to your students.

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Umbrella topics must be sufficiently complex. If you are using an umbrella topic for a large class of

students who will be working on related, more manageable problems in their learning teams, make sure

that there is sufficient complexity in the research problems that the umbrella topic includes. These

research topics must relate strongly to one another in such a way that there will be a strong sense of

coherence in the overall class effort.

Question 4:--. Explain the procedure for Testing Hypothesis

Answer: --

Procedure for Testing Hypothesis

To test a hypothesis means to tell (on the basis of the data researcher has collected) whether or not the

hypothesis seems to be valid. In hypothesis testing the main question is: whether the null hypothesis or

not to accept the null hypothesis? Procedure for hypothesis testing refers to all those steps that we

undertake for making a choice between the two actions i.e., rejection and acceptance of a null

hypothesis. The various steps involved in hypothesis testing are stated below:

1) Making a Formal Statement

The step consists in making a formal statement of the null hypothesis (Ho) and also of the alternative

hypothesis (Ha). This means that hypothesis should clearly state, considering the nature of the research

problem. For instance, Mr. Mohan of the Civil Engineering Department wants to test the load bearing

capacity of an old bridge which must be more than 10 tons, in that case he can state his hypothesis as

under:

Null hypothesis HO: =10 tons

Alternative hypothesis Ha: >10 tons

Take another example. The average score in an aptitude test administered at the national level is 80. Toevaluate a states education system, the average score of 100 of the states students selected on the

random basis was 75. The state wants to know if there is a significance difference between the local

scores and the national scores. In such a situation the hypothesis may be state as under:

Null hypothesis HO: =80

Alternative hypothesis Ha: 80

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The formulation of hypothesis is an important step which must be accomplished with due care in

accordance with the object and nature of the problem under consideration. It also indicates whether we

should use a tailed test or a two tailed test. If Ha is of the type greater than, we use alone tailed test, but

when Ha is of the type whether greater or smaller then we use a two-tailed test.

2) Selecting a Significant Level

The hypothesis is tested on a pre-determined level of significance and such the same should have

specified. Generally, in practice, either 5% level or 1% level is adopted for the purpose. The factors that

affect the level of significance are:

The magnitude of the difference between sample ;

The size of the sample;

The variability of measurements within samples;

Whether the hypothesis is directional or non directional (A directional hypothesis is one which predicts

the direction of the difference between, say, means). In brief, the level of significance must be adequate

in the context of the purpose and nature of enquiry.

3) Deciding the Distribution to Use

After deciding the level of significance, the next step in hypothesis testing is to determine the

appropriate sampling distribution. The choice generally remains between distribution and the tdistribution. The rules for selecting the correct distribution are similar to those which we have stated

earlier in the context of estimation.

4) Selecting A Random Sample & Computing An Appropriate Value

Another step is to select a random sample(S) and compute an appropriate value from the sample data

concerning the test statistic utilizing the relevant distribution. In other words, draw a sample to furnish

empirical data.

5) Calculation of the Probability

One has then to calculate the probability that the sample result would diverge as widely as it has from

expectations, if the null hypothesis were in fact true.

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6) Comparing the Probability

Yet another step consists in comparing the probability thus calculated with the specified value for , the

significance level. If the calculated probability is equal to smaller than value in case of one tailed test

(and /2 in case of two-tailed test), then reject the null hypothesis (i.e. accept the alternative

hypothesis), but if the probability is greater then accept the null hypothesis. In case we reject H0 we runa risk of (at most level of significance) committing an error of type I, but if we accept H0, then we run

some risk of committing error type II.

Question No 5:--. Explain the components of a research design.

Answer: --

Components of a Research Design: The classic research design consists of four components:

Comparison: It is an operation required to demonstrate that two variables are correlated. e.g. If a

researcher wants to demonstrate a correlation between cigarette smoking and lung cancer, a researcher

might compare the frequency of cancer cases among smokers and non-smokers or alternatively might

compare the number of cancer cases in a population of smokers before and after they started smoking.

Manipulation: Manipulation helps a researcher in establishing the time order of events. Here, the major

evidence is required to determine the time sequence of events i.e. the independent variable precedes

dependent variable. e.g. If a researcher is attempting to prove that the participation in an alcohol

treatment group decreases denial of drinking problems, he or she must demonstrate that a decrease in

denial took place after participation in the treatment group. The researcher needs to establish some

form of control over the assignment to the treatment group so that he can measure the level of denial

drinking problems before and after participation in the group

Control: Control enables the researcher to determine that the observed co variation is non-spurious.

Control requires that the researcher rule out other factors as rival explanations of the observed

association between the variables under investigation. Such factors could invalidate the inference that

the variables are causally related. This issue is termed as internal validity.

In order to establish the internal validity, a researcher must answer the question of whether changes in

the independent variable did infact, cause the dependent variable to change. The following are the

factors that may jeopardize the internal validity.

Extrinsic factors

Intrinsic factors

(1) History

(2) Maturation

(3) Experimental mortality

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(4) Instrumentation

(5) Testing

(6) Regression artifact

(7) Interactions with selections

Methods to counteract the effect of Existing factors:

Matching: It is the of equating the experimental group and control group on existing factors that are

known to be related to the research hypotheses. Two methods can be used for matching:

Precision Matching: In this method, for each case in an experimental group, another case with identical

characteristics is selected for the control group.

Frequency Distribution: In this method, the experimental groups and control groups are made similar for

each of the relevant variables separately rather than in combination.

Randomization: Even if it were possible to avoid the effects of all the factors, investigator can never be

sure that all of them have been isolated. Other factors of which the investigator is unaware may lead to

erroneous causal interpretations. Researchers avoid this problem by using Randomization, another

process whereby cases are assigned to the experimental group and control group.

4. Generalization : Most research is concerned not only with the effect of one variable on another in the

particular setting studied but also with its effect in other natural settings and on larger populations. This

concern is termed as external validity of research design.

The two main issues of external validity are:

Representativeness of the Sample

Reactive Arrangements

Conclusion: The classical experimental design is one of the strongest logical models for inferring causal

relations. The design allows for pretest, posttest and control group-experimental group comparisons. It

permits the manipulation of the independent variable and thus determination of the time sequence. It

controls the most sources of internal validity by including randomized group.

The external validity of this design is weak and it does not allow researchers to make generalization.

Two variations of the classical experiment design are stronger in this respect. They are:

The Solomon four-group design

The posttest- Only control group design

Question No 5b:--. Briefly explain the different types of research designs

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Answer: --

TYPES OF RESEARCH DESIGNS

A research design is like a roadmapyou can see where you currently are, where you want

to be at the completion of your journey, and can determine the best (most efficient and ef fect ive) route

to take to get to your destination. We may have to take unfore seen detours along the way,

but by keeping our ultimate objective constantly in mind and using our map we can

ar r i ve a t ou r des t i na t i o n . Our r e sea rc h pu rpo se and ob j ec t i ve s suggest which

route (design) might be best to get us where we wa nt to go. but there is more than one way to

"get there from here." Choice of research design is not like solving a problem in algebra where there

is only one cor rect answer and an inf ini te number of wrong ones. Choice of research design is

more like selecting a cheesecake recipesome are bet t er t han o ther s but ther e i s no on e

whi ch is uni ver sal ly ac ce pte d as "b es "Successful ly complet ing a research project

consists of making those choices that will f ulfill the research purpose and obtain answers

to t he r esear ch questi ons in an e ffic ient and effective manner. Choice of de sign t ype i s not

determined by the nature of the strategic decision faced by the manager such that we would useresearch design A whenever we need to evaluate the e x t e n t o f a ne w p r o d uc t op por t u n i t y, o r

d e s i gn B wh e n de c id i n g o n wh ic h of t wo advertising programs to run. Rather, choice of

research design is influenced by a number of variables such as the decision maker's attitude toward risk,

the types of decisions being faced, the size of the research budget , the deci sion -making t ime

frame, the nature of the resea rch obje ct ive s , a nd o ther subt le and not -so- subt le

f a c t o r s . Muc h o f t h e c ho i c e , however, will depend upon the fundamental objective implied by

the research question To c onduc t a ge ne ra l explorationo f t h e i s s u e , g a i n s o m e b r o a d

insights into the phenomenon, and achieve a better "feel" for the subject under

investigation (e.g.. What do customers mean by "good value"?).

Todescribea population, event, or phe nomenon in a precise manner where we ca n attachnumbers to represent the extent to which something occurs or determine the degree t w o o r m o r e

v a r i a b l e s c o v e r ( e . g . , d e t e r m i n e t h e r e l a t i o n s h i p b e t w e e n a g e a n d

consumption rate).

To attributecause and effect relationshipsamong two or more variables so that we can better

understand and predict the outcome of one variable (e.g., sales) when varying another (e.g.,

advertising).This classification is frequently used and is quite popular. Before we discuss

each of these design types, a cautionary note is in order. Some might think that the

research design decision suggests a choice among the design types. Although there are

research situations in which all the resea rch questions might be answered by doing only

one of these types (e.g., a causal research experiment to determine which of three prices results in the

greatest profi ts), it is more oft en the case that the researc h design might involve more than

one of these types performed in some sequence. The overall research design is intended to indicate

exactly how the different design types will be utilized to get answers to the research questions or test the

hypothesis.

This classification is frequently used and is quite popular. Before we discuss each of these

design types, a cautionary note is in order. Some might think that the research design

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decision suggests a choice among the design types. Although there are research situations

in which all the r esear ch ques tions might be answe red by doing only one of these types (e.g.,

a causal research experiment to determine which of three prices results in the greatest profits), it is

more often t he case that the research design might involve more than one of these types

performed in some sequence. The overall research design is intended to indicate exactly how the different

design types will be utilized to get answers to the research questions or test the hypothesis.

Question No 6a:--. What are the assumptions of Case Study Method?

Answer: --

Research may be classified crudely according to its major intent or the methods. According to

the intent, research may be classified as:

1 Pure Research

It is undertaken for the sake of knowledge without any intention to apply it in practice

2 Applied Research

It is carried on to find solution to a real-life problem requiring an action or policy decision.

3 Exploratory Research

It is also known as formulative research. It is preliminary study of an unfamiliar problem aboutwhich the researcher has little or no knowledge.

4 Descriptive Study

It is a fact-finding investigation with adequate interpretation. It is the simplest type of research.

5 Diagnostic Study

It is similar to descriptive study but with a different focus.

6 Evaluation Studies

It is a type of applied research.

Question No 6b:--. Explain the Sampling process?

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Answer: --

Sample and Sampling:

A Sampling is a part of the total population. It can be an individual element or a group of elements

selected from the population. Although it is a subset, it is representative of the population and suitable for

research in terms of cost, convenience, and time. The sample group can be selected based on a

probability or a non-probability approach. A sample usually consists of various units of the population.

The size of the sample is represented by n.

Sampling is the act, process, or technique of selecting a representative part of a population for the

purpose of determining the characteristics of the whole population. In other words, the process of

selecting a sample from a population using special sampling techniques called sampling. It should be

ensured in the sampling process itself that the sample selected is representative of the population.

Population OR Universe: The entire aggregation of items from which samples can be drawn is known as

a population. In sampling, the population may refer to the units, from which the sample is drawn.

Population or populations of interest are interchangeable terms. The term unit is used, as in a business

research process, samples are not necessarily people all the time. A population of interest may be the

universe of nations or cities. This is one of the first things the analyst needs to define properly while

conducting a business research. Therefore, population, contrary to its general notion as a nations entire

population has a much broader meaning in sampling. N represents the size of the population.

Census: A complete study of all the elements present in the population is known as a census. It is a time

consuming and costly process and is, therefore, seldom a popular with researchers. The general notion

that a census generates more accurate data than sampling is not always true. Limitations include failure

in generating a complete and accurate list of all the members of the population and refusal of theelements to provide information. The national population census is an example of census survey.

Precision: Precision is a measure of how close an estimate is expected to be, to the true value of a

parameter. Precision is a measure of similarity. Precision is usually expressed in terms of imprecision and

related to the standard error of the estimate. Less precision is reflected by a larger standard error.

Bias: Bias is the term refers to how far the average statistic lies from the parameter it is estimating, that is,

the error, which arises when estimating a quantity. Errors from chance will cancel each other out in the

long run, those from bias will not. Bias can take different forms.

Steps in Sampling Process:

An operational sampling process can be divided into seven steps as given below:

Defining the target population.

Specifying the sampling frame.

Specifying the sampling unit.

Selection of the sampling method.

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Determination of sample size.

Specifying the sampling plan.

Selecting the sample.