research report on e-banking and its effect

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A

Research Report

Subject Code: 536276(76)On

“Effect of E-banking on customer satisfaction”

Submitted for partial fulfillment of requirement for the award of

degree

Of

Master of Business Administration

Of

CHHATTISGARH SWAMI VIVEKANAND TECHNICAL

UNIVERSTY

BHILAI (C.G.)

Session 2012-14

Supervision By: Submitted by:

Prof. Gazala .Y. Ashraf Priyanka SahuDesignation Roll

No.5057612094

Department FOM MBA II SEM.

Section – A

FACULTY OF MANAGEMENT

DISHA INSTITUTE OF MANAGEMENT AND TECHNOLOGY(Disha Education Society)

1 “Consumer perception towards Home Loan” By: Sujeet Pandit



Satya Vihar, Vidhansabha-Chandrakhuri Marg, Mandir Hasaud,

Raipur (C.G.) 492007

DECLARATION

I the undersigned solemnly declare that the report of the project work

entitled “Effect of E-banking on customer satisfaction”, is based my own

work carried out during the course of my study under the supervision of

Prof. Gazala Y. Ashraf.

I assert that the statements made and conclusions drawn are an outcome

of the project work. I further declare that to the best of my knowledge and

belief that the project report does not contain any part of any work which

has been submitted for the award of any other degree/diploma/certificate in

this University or any other University.

__________________

Priyanka Sahu

Roll No.: 5057612040




CERTIFICATE BY GUIDE

This to certify that the report of the project submitted is the outcome of the

project work entitled “Effect of E-banking on customer satisfaction” carried

out by Priyanka Sahu bearing Roll No.:5057612040 & Enrollment

No.:AK5419 carried by under my guidance and supervision for the award of

Degree in Master of Business Administration of Chhattisgarh SwamiVivekananda Technical University, Bhilai (C.G), India.

To the best of the my knowledge the report

i) Embodies the work of the candidate him/herself,

ii) Has duly been completed,

iii) Fulfils the requirement of the ordinance relating to the MBA degree

of the University and

iv) Is up to the desired standard for the purpose of which is submitted.

_______________________

(Signature of the Guide)

Prof. Gazala Y. Ashraf

Asst. Prof.

Faculty of ManagementDISHA INSTITUTE OF MANAGEMENT AND TECHNOLOGY

Satya Vihar, Vidhansabha-Chandrakhuri Marg, Mandir Hasaud,

Raipur (C.G.) 492007

The research report as mentioned above is hereby being recommended and

forwarded for examination and evaluation.




CERTIFICATE BYTHE EXAMINERS

This is to certify that the project entitled

“Consumer perception towards Home Loan”

Submitted by

Priyanka Sahu Roll No.:5057612040 Enrollments No.:AK5419.

Has been examined by the undersigned as apart of the examination for the award

of Master of Business Administration degree of Chhattisgarh Swami Vivekananda

Technical University, Bhillai (C.G.).

________________

__________________

________________

__________________

Name & Signature of Name & Signature

of

Internal Examiner External Examiner

Date: Date:

Forwarded by

Dean

Faculty of Management




ACKNOWLEDGEMENT

I would firstly like to express my gratitude towards my guide PROF: Mrs. Gazala for having

so much flexibility and guiding in such a way that I was really learning the subject all the time.

She help in deciding the project topic .She showed a lot of approach openness and I would like

to thank for her support in a way that has lead to proper and effective learning.

I respect and thank Prof. Gazala A., for giving me an opportunity to do the project work in

Consumer perception towards home loan and providing us all support and guidance which made

me complete the project on time. I am extremely grateful to her for providing such a nice

support and guidance though she had busy schedule.

I would not forget to remember Prof. Suresh Pattanayak, Prof Rupesh Kr. Tiwari and all faculty

members for their unlisted encouragement and more over for their timely support and guidance

till the completion of our project work.

I heartily thank our internal project guide, Dr.R.S.Mohan, Dean , Department of Management,

for his guidance and suggestions during this project work.

I am extremely thankful to all those persons who have positively helped me and customers

who respond my questionnaire, around whom the whole project cycle revolves.

Appendix – VI


Name: Priyanka Sahu

Roll.No.: 5057612040

MBA

2nd Semester

Section-A



Preface

This report presents the research, findings and recommendations resulting from the project,

“Consumer perception towards Home Loan”, supported by Prof. Gazala A. Ashraph

and authored by the Dean. The objective was to compile and synthesize information on the

status of Consumer perception. In so doing, it lays the foundation for the development of

bank resources management decision support system that will facilitate scientifically sound

decision making. The involvement in this project reflects its long-term interest in Consumer

perception towards Home Loan management activities consistent with its mandate to

“promote the orderly, integrated and comprehensive development, use and conservation of

the loan. This report has benefitted from the significant input and collaboration of numerous

partners that comprised a Project Management Team (PMT). The findings and

recommendations of this report address data and information gaps and needs, and provide

valuable information for guiding the next steps in the process of developing a decision

support system. This report, and the project’s many associated components, provides a

wealth of information about the bank resources and associated policies.

Introduction




Over the last few decades the role of banking sector has undergone a paradigm shift. It is

widely recognized as an important aspect of the source of loan for the people and considered

it as a short and long-term investment.

After zeroing down on my research area, I have collected information through only primary.I had a constant discussion with consumer.

The objective of this report is to study “Customer Awareness, Perception and Attitude

towards E-Banking”. For this survey was conducted through structured Questionnaire.

In today’s competitive business world every customer is significant for E-Banking

The customer expectations are very high so it should be kept in mind and offer them best

possible service.

The report deals with the conceptual background of E-Banking and over view of the

banks, the next part deals with research design of the study that is problem identification,

objectives and how the research was carried out. The outcome of the study shows that the

level of customer awareness towards Home Loan is good with the benefits and service what

they are giving and most of the people wants to go for investments.

Banks can start some good promotional activities to build its brand and to make

recognition by all the peoples in the market .The effective marketing channel with the

personal selling is an essential factor in influencing banks growth.

E-Banking has different products at differ. The growing competition between the financial

institutions had made each of them to delight their customer rather than satisfying them. The

emergence of new generation private financial institutions has made the entire financial

sector tougher and much more competitive. They provide various services to the customer to

solve the problem in convenient way without any danger.

Electronic commerce is now thought to hold the promise of a new commercial

revolution by offering an inexpensive and direct way to exchange information and to

sell or buy products and services. This revolution in the market place has set in

motion

a revolution in the banking sector for the provision of a payment system that is

Compatible with the demands of the electronic marketplace.

An electronic connection between the bank and the

Customer in order to prepare, manage and control financial transactions. Electronic




Banking according to Al-Abed (2003) is an umbrella term for the process by which a

Customer may perform banking transactions electronically without visiting a brick

and-mortar institution.

For the purpose of this research, we define electronic banking as the delivery of

Banking services and products through the use of electronic means irrespective

of place, time and distance. Such products and services can include deposit-

taking, lending, account management, the provision of financial advice,

electronic bill payment, and the provision of other electronic payment products

and services such as Electronic money.

E-banking brings different and arguably lower barriers to entry; opportunities for significant cost reduction; the capacity to rapidly reengineer business processes; and

greater opportunities to sell cross border. For customers, the potential benefits are:

more choice; greater competition and better value for money; more information;

better tools to manage and compare information; and faster service.

But it should be realized that electronic banking services is a brain child of

Information and Communication Technology (ICT) that made it possible for

service providers and their customers in developing economies to enjoy a good

semblance of the services enjoyed in the developed societies. Electronic

banking services have afforded banks the opportunities to impress customers

which encourage them to keep coming back. Today, it would be difficult to see

any bank in the country that does not render one form of electronic banking

service or the other, even banks in the most remote parts of the world.

Indian banking scenario had underwent dramatic changes after

the implementation of the new economic policy which

triggered out the economy in rapid speed as a result of that

drastic changes have been taken place in money transactions

hence the role of banking had expended incredibly, banks are

also have equipped immensely with the help of IT development

in unleashing the services in better way to its consumers in




such context number of studies have been carried out to find

out the consumer satisfaction of the bank customer in order to

enhance the service, most of the studies have revealed the

development has better impact on the service delivery but the

propose study would like to encompass all the spheres of the

banking services in assessing the service delivery and the

satisfaction level of the customer, hence it is became very

imperative to explore the consumer satisfaction at multi

dimensional level.

Unique features:

• Number of transaction should be done within a second.

• Option to less the consumer tiredness.

• Provide facility of online transaction.

•

Provision to cost of furnishing and consumer durables as part of project cost• Provide facility of cash payment online

•Provide facility to avoid hacking and easy service

• Internet applied on daily diminishing balance basis

• It help in both internet and phone service

• Special scheme to grant day by day which attract the customer.

It tries to reduce the impact of the risk on the owner of the asset and those who depend on

that asset.It only compensates the loose and that too, not fully. Only economic consequences

can be insured. If the loss is not financial insurance may not be possible.




OBJECTIVES

PRIMARY OBJECTIVE:

To analyze the level of Customer Satisfaction towards Services provided

by ICICI Bank Ltd.

SECONDARY OBJECTIVES:

1. To find out various type customers who prefer E-Banking…

2. To identify various facility of E-banks from where customer have use.

3. To evaluate the time for customer to going from banks.

4. To identify whether any procedure problem were faced by the customer in

availing the E-Banking

5. To find out the preferred mode of repayment of customer with regarding their

account from banks.

6. To find out the most attractive features that attracted the clients to avail E-

Banking.

7. To evaluate the customer satisfaction regarding various services offered at

E-Banking.

.




SCOPE AND LIMITATIONS OF THE STUDY SCOPE

OF THE STUDY

The scope of the study is to analyze the satisfaction level of customers towards E-Banking.

The study gathers information about rating the effectiveness of E- Bank services, rating and

ranking the different features and services offered by the bank.

Primary data was collected from the existing loan customers and also non existing

customers; secondary data was collected from book manuals, magazines and websites. The

study has come out with valuable suggestions on basis of concrete facts, which help to frame

its plan and strategies to increase satisfaction level of the loan customers.

LIMITATIONS OF THE STUDY

1. The study is limited to the banks.

2. Because of the limited time, research is conducted with only 80 customers.

3. The data collected from the customer are qualitative in nature i.e., views,

perception, satisfaction, opinion etc., may change from time to time.

4. The data collected are primary in nature. Hence there is chance for a biased of

misleading respondent from the customer.

5. On few occasions customer were reluctant to give information, because they were

busy.




RESEARCH METHODOLOGY

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 “Research Design”. Research design is a plan,

structure and strategy of investigation conceived to obtain answers to

research questions and to control variance.

A research design can be defined as “Arrangement of condition for

collection and analysis of data in the manner that aims to combine

relevance to the research purpose with economy in procedure.” It

consists of the blue print for the collection measurement and analysis

of data. The research used here is descriptive research

DESCRIPTIVE RESEARCH

The researcher is interested in knowing the proportion of people in a

given population who has behaved in a particular manner, making

projections of certain thing and determining the relationship between

two or more variables in some areas. As the set up has been well

structured and is a rigid one, which could not be changed by giving

sufficient thought in frail-ling question, deciding type of data to be

collected and procedure that has been used gives the, proof of using

description research. In descriptive research also there has been use of

cross sectional studies just because the researcher has taken only a

sample of elements from the given population. In the cross sectional

study the survey research has been selected, as a detailed study has to




be obtained from a sample of large population.

DATA COLLECTION METHOD

The data that is used in study in collected by two methods.

1. Primary data

2. Secondary data

Primary Data

The primary data does not exist already in records and publications.

The researcher has to gather primary data a fresh for a specific survey.

The primary data can be gathered by way of observation method where

the research mix with the people concerned with the use of particular

product and not important clauses by observing the respondents. The

second method of collection of primary data is by way of

experimentation method where some variables are allowed to vary

under a controlled environment and its cause and effect relationship is

studied.

The third method of collection of data is by way of conducting a

survey. This method is used for collection of primary data. The primary

data was collected from customers in Chennai city. For this research

study, data was collected from various account holders of the

CitiFinancial. Data collection was carried out using personal interview

method guided by questionnaire as follows:

. Open-ended questions

. Closed ended questions

. Dichotomous questions

. Multiple-choice questions

. Ranking questions

. Rating questions




SECONDARY DATA

It is needed for conducting this research work collected from the

various business magazines, bank brouchers, statistical and

management book, market research books etc. which are presented in

the literature various in details

SAMPLING DESIGN

The precision and accuracy of survey results are affected by the

manner in which the sample has been chosen. The first thing for a

sample plan is definition of the population to be investigated. Defining

the population is often one of the most difficult things to do in

sampling. Although ideal conditions might indicate threat the census

would be preferable, such ideal conditions rarely exist in the real

world. A census is not feasible practically, therefore sample is used.

Two of major advantages of using a sample rather than a census are

speed and timeliness. A survey based on sample takes much less time

to compete than based on census. In this particular research study

sample survey is done. Sample design is the most important heart of

sample planning. Sample design includes type of sample to use and the

appropriate sampling unit.

Sampling Frame

Sampling may be defined as a means of accounting for the elements in

the population. The sampled elements that are selected from the frame

sample size are directly related to precision. The size of sample can be

decided by way of random or arbitration or minimum cell sized needed

for analysis or budget based.

Sample Unit

The study was conducted among the loan holders in the selected areas

in India.

Population




All the people holding an account in different banks.

Types of Sampling

Sampling units focus the basis of the actual sampling procedure. It is

that which is actually chosen by the sampling process. The sampling,

which is used in research, is random sampling. In a simple random

sample, each member of the population has a known and equal chance

of being selected.

SAMPLING METHOD

The research is based on the study conducted in selected areas in

Chennai. Among these areas systematic random sampling is usedwhere in every second customer who walked into Chennai branch.

SAMPLE MEDIA

Personal interview method guided by questionnaires is used for

conducting the survey.

PILOT STUDY

Determination of sample size

Before the original questionnaire was drafted a preliminary

questionnaire was formed and a pilot survey was done with 10

personals.

TOOLS OF ANALYSIS:

Chi-square Test

The objective of the chi-square test is to determine whether there is any

significant difference exists among the various groups. Chi-square test

involves comparison of expected frequency (Ei) with observed frequency (Oi)

to determine whether the difference between the two is greater than the

tabulated value that might occur by chance. There are 5 steps in using chi-

square test.

1. The difference between each observed frequency and each expected

frequency is computed.

2. The difference is squared.




3. Each squared difference is divided by the respective expected

frequency.

4. Their quotients are added together to obtain the computed chi square

value.

5. This computed value is then compared to tabulate chi-square value.

If the computed x2 value is greater than the tabulated x2 value at a

predetermined level of significance and degrees of freedom, the hypothesis is

rejected.

On the other hand, if the calculated x2 value is less than the tabulated

valued, the hypothesis is accepted.

X2 =

(O-E)2/E

Where

,

O = Observed

frequency

E = Expected frequency

One way classification

The main object of one-way classification is to examine if there is a

significant difference between the class means in view of the interest

variability within the separate classes.

The test statistical for Ho is provided by the variance ratio

F = Between Sum of Squares

Within Sum of Squares

K – S TEST (Komogrorov-Smirnumberv test)

This test is used for comparing the distribution on an ordinary scale.

The test is concerned with the degree of agreement between the

distribution and some special theoretical distribution. It determines

whether the scores in the sample can be reasonable thought to have




come from popularize, having theoretical distribution.

A safe level of participation in the emergingproduct/service in the banking industry

1. Electronic Card:

According to Armed (2005) as we witness the globalization of markets,

a major instrument of it is the development in communications and

information technology. This development has therefore made the

introduction of electronic purse a reality in banking and is redefining

what a legal lender is in monetary terms financial conglomerates of the

world, is plenty:

. Visa is a membership association owned by more than 21000

financial institutions around the world that provides member

institutions with global payment platform development. While research

findings showed that, while about 5000 people carry e-cards (30,000

Val card and 20,000 Smart card) only about 50,000 actually use them

due to insecurity and the use of different cards on one terminal

(Babajide and Emma, 2004).

3. Mortgages loan for education:

If money is what is standing between the customer and a world-class

education, worry not! Now banks helps the customer to fund the

customer’s education by giving the customer a loan against the

customer’s home. So if the customer wants to pursue the customer’s

studies in India or overseas, the customer can do so now without any

financial worries.

REVIEW OF LITERATURE




The researcher has to refer few books and magazines to refer few

books and review for obtaining and understanding. The relationship in

customer satisfaction and quality of services. It was also useful for

knowing the customer satisfaction versus quality of service offered by

the concern.

The ICFAI journal of Monetary Economics, Numberv’2004 it is

studied that “greenwood and Jovanovich (1990) in their study analyzed

the role that financial institutions play in collecting and analyzing

information and use this information for utilizing funds by investing in

such projects that are high-risk while at the same time yield highest

return.

The ICFAI Journal of Service Marketing Dec’2004 “It is important to

note that whatever financial products are put in the market, it can only

be successful if customer has a need for it. Thus the need to study

customer behavior becomes paramount. This flows naturally from the

marketing concept that emphasis the idea of looking at the product

from the consumer’s point of view,”

In Indian Journal of Marketing, May’04 Marketing of Banking

Services in the Globalize Scenario – Emerging Challenges- By Dr. V.

GOPALAKRISHNAN.

Banking services largely depends upon customer demands and their

perceived performance. In urban and metropolitan sectors customers

are more knowledge and demand more facilities than offered. They are

looking for services that are cheaper, faster and qualitatively better”




The STATISTICAL METHODS, By S P GUPTHA. S.P gives a very

in-depth study about the various statistical tools and techniques that

could be used for various researches work purposes. Each statistical

test has been discussed very much in detail and this book has acted as

the back bone for this research study by helping the research work in

using various statistical tools like chi-square, One way ANOVA test,

Two way ANOVA test etc.,

The Marketing Management -By PHILIP KOTLER, which is one of

the masterpieces in the field of marketing, has given an excellent

coverage in the various fields of marketing. The author has very

elaborately examine the various issues in designing the marketing

strategies for various companies, tactical marketing and also the

hurdles that arises in the administrative side of marketing which were

all very much useful in analyzing the various problems of this research

study and finally in also putting forth various feasible recommendation

and suggestion for this research work. This book has also presented

various frameworks for analyzing certain recurrent problem in the field

of marketing, which were also effectively used in this research work.

The RESEARCH MARKETING, By McGauran L.L.gives more stress

on the various categories of information that should be collected for

carrying out the preliminary investigation for the various research

studies. The author McGauran L.L. gives importance to six categories

of information that re to be used for preliminary investigation namely

a. the product

b. the company, industry and competition

c. the market

d. the channel of distribution

e. the sales

f. the sales promotion policies.




Further this book also stresses on the pilot survey that should be

conducted before starting the original survey. Hence taking all this into

account, a preliminary questionnaire was drafted and it was testedamong five customers. The flows found in the questionnaire were later

rectified after consulting few experts too in this field and finally the

original questionnaire was drafted.

INTERPRETATION AND ANALYSIS

I.DESCRIPTIVE STATISTICS

SPSS Commands for a descriptive statistics

After the input data has been typed along with variable labels and value

labels in an SPSS file, to get the output for a descriptive statistics.

Click on ANALYZE at the SPSS menu bar (in older versions of SPSS,

click on STATISTICS instead of ANALYZE).

1. Click on Descriptive

2. On the dialogue box which appears, select all the variables for

which descriptive statistics are required by clicking on the right

arrow to transfer them from the variable list on the left. Then click

options and then select whatever the descriptive statistics to be

calculated and click continue.

3. Click OK to get descriptive statistics




Descriptive Statistics

N Minimum Maximum Mean Std. Kurtosis

Statistic Statistic Statistic Statistic Statistic Statistic Std. Error

HL EZY 2 UNDRSTND 80 1.00 5.00 2.7125 1.05775 -.286 .532

MORTG PRCS 80 .00 5.00 2.2750 1.10207 -.143 .532

EMI FIX 80 1.00 5.00 1.8875 1.19061 1.094 .532

SRVC RCVD 80 1.00 5.00 2.5125 1.24264 -.685 .532

INTRST CHRG BY BNK 80 1.00 5.00 2.3875 1.20646 -.954 .532

HL FVOR 80 1.00 5.00 2.0750 1.07650 .534 .532

DOC PRCZER 80 1.00 5.00 2.5250 1.12481 -.198 .532

PRCZING FEES 80 1.00 5.00 3.1375 1.07614 -.570 .532

SENCTION PRCZER 80 1.00 5.00 3.3500 1.08032 -.220 .532

SENCTION TIME 80 1.00 5.00 3.6625 1.16862 -.752 .532

4 CLZR CHRGD 80 1.00 5.00 3.6125 1.26785 -.630 .532

ONLINE 80 .00 5.00 2.3875 1.51360 -1.034 .532

INTRST AS INCME LVL 80 1.00 5.00 3.2625 1.45605 -1.212 .532

SIZ WHL NNP EMI 80 .00 5.00 2.8125 1.46774 -1.224 .532

FCLTY PRVD BANK 80 .00 5.00 3.0625 1.32497 -.306 .532

PUBLIC SECTOR 80 1.00 5.00 2.2375 1.39841 -.880 .532

PRIVATE SECTOR 80 1.00 5.00 2.6250 1.52925 -1.358 .532

Valid N (listwise) 80

II.BIVARIATE ANALYSIS AND MULTIVARIATE

ANALYSIS

SPSS Commands for Correlation and Regression

Correlation


labels in an SPSS file, to get the output for a Correlation problem Click

on ANALYZE at the SPSS menu bar (in older versions of SPSS, click

on STATISTICS instead of ANALYZE).

1) Click on CORRELATE, followed by BIVARIATE.

2) On the dialogue box which appears, select all the variables for

which correlations are required by clicking on the right arrow to

transfer them from the variable list on the left. Then select Pearson

under the heading Correlation Coefficients, and select 2-tailed

under the heading Tests of Significance.




3) Click OK to get the matrix of pair wise Pearson Correlations among

all the variables selected. Along with the two-tailed significance of

each pair wise correlation.

Correlations

HL EZY 2

UNDRSTNDMORTGPRCS EMI FIX SRVC RCVD

HL EZY 2 UNDRSTND Pearson Correlation 1 .362(**) .366(**) .094

Sig. (2-tailed) .001 .001 .406

N 80 80 80 80

MORTG PRCS Pearson Correlation .362(**) 1 .564(**) .284(*)

Sig. (2-tailed) .001 .000 .011

N 80 80 80 80

EMI FIX Pearson Correlation .366(**) .564(**) 1 .416(**)

Sig. (2-tailed) .001 .000 .000

N 80 80 80 80

SRVC RCVD Pearson Correlation .094 .284(*) .416(**) 1

Sig. (2-tailed) .406 .011 .000

N 80 80 80 80

** Correlation is significant at the 0.01 level (2-tailed).* Correlation is significant at the 0.05 level (2-tailed).

Correlations

INTRSTCHRG BY

BNK HL FVORDOC

PRCZERPRCZING

FEESSENCTIONPRCZER

INTRST CHRG BY BNK Pearson Correlation 1 .348(**) .343(**) .368(**) .128

Sig. (2-tailed) .002 .002 .001 .259

N 80 80 80 80 80

HL FVOR Pearson Correlation .348(**) 1 .093 .111 .064

Sig. (2-tailed) .002 .414 .326 .571

N 80 80 80 80 80




DOC PRCZER Pearson Correlation .343(**) .093 1 .515(**) .503(**)

Sig. (2-tailed) .002 .414 .000 .000

N 80 80 80 80 80

PRCZING FEES Pearson Correlation .368(**) .111 .515(**) 1 .546(**)

Sig. (2-tailed) .001 .326 .000 .000

N 80 80 80 80 80SENCTION PRCZER Pearson Correlation .128 .064 .503(**) .546(**) 1

Sig. (2-tailed) .259 .571 .000 .000

N 80 80 80 80 80

** Correlation is significant at the 0.01 level (2-tailed).

Correlations

SENCTION

TIME

4 CLZR

CHRGD ONLINE

INTRST AS

INCME LVLSENCTION TIME Pearson Correlation 1 .551(**) -.161 -.066

Sig. (2-tailed) .000 .153 .559

N 80 80 80 80

4 CLZR CHRGD Pearson Correlation .551(**) 1 .066 .152

Sig. (2-tailed) .000 .561 .179

N 80 80 80 80

ONLINE Pearson Correlation -.161 .066 1 .281(*)

Sig. (2-tailed) .153 .561 .012

N 80 80 80 80

INTRST AS INCME LVL Pearson Correlation -.066 .152 .281(*) 1

Sig. (2-tailed) .559 .179 .012N 80 80 80 80


Correlations

SIZ WHLNNP EMI

FCLTYPRVD BANK

PUBLICSECTOR

PRIVATESECTOR

SIZ WHL NNP EMI Pearson Correlation 1 .293(**) -.163 -.082

Sig. (2-tailed) .008 .148 .467

N 80 80 80 80




FCLTY PRVD BANK Pearson Correlation .293(**) 1 -.042 -.394(**)

Sig. (2-tailed) .008 .710 .000

N 80 80 80 80

PUBLIC SECTOR Pearson Correlation -.163 -.042 1 -.266(*)

Sig. (2-tailed) .148 .710 .017

N 80 80 80 80PRIVATE SECTOR Pearson Correlation -.082 -.394(**) -.266(*) 1

Sig. (2-tailed) .467 .000 .017

N 80 80 80 80


Output (Correlation Table)

The above said Table shows the output for correlation table. The values

in the correlation table are standardized. Correlation This means that

we may have chosen a fairly good set of independent. It is only the

index of competitor activity that is negatively correlated with behavior.

The correlation table can also be used to find out the correlation

between the independent variables. If they are like in Correlation Table,

then it can be inferred that all the factors are not independent of each

other. Thus, only one or two of them can be used to predict the

dependent variable

Regression

After the input data has been typed along with variable labels and

value labels in an SPSS file, to get the output for a Regression

problem

1. Click on ANALYZE at the SPSS menu bar (in older versions of

SPSS, click on STATISTICS instead of ANALYZE).

2. Click on REGRESSION, followed by LINEAR.

3. In the dialogue box which appears, select a dependent variable by

clicking on the arrow leading to the dependent box after

highlighting the appropriate variable from the list of variables on

the left side.




4. Select the independent variables to be included in the regression

model in the same way, transferring them from left side to the right

side box by clicking on the arrow leading to the box called

independent variables or independents.

5. In the same dialogue box select the METHOD. Choose

• ENTER as the method if you want all independent variable

to be included in the model.

• STERWISE if you want to use forward stepwise regression.

•

BACKWARD if you want to use backward stepwiseregression.

6. Select OPTIONS if you want additional output, select the ones you

want, and click CONTINUE.

7. Select PLOTS if you want to see some plots such as residual plots,

select those you want, and click CONTINUE.

8. Click OK from the main dialogue box to get the REGRESSION

output.

Regression Analysis

A regression analysis is done to explain the variation in one variable

(Dependent variable), based on variation in one or more other variables

(independent variables). In case there is only one independent variableto explain the variation in one dependent variable, it is known as simple

regression. If there are multiple independent variables to explain the

variation in a single dependent variable, it is known as a multiple

regression model.

Variables Entered/Removed(a)




ModelVariablesEntered

VariablesRemoved Method

1

INTRSTCHRG BYBNK

.

Stepwise(Criteria:Probability-

of-F-to-enter <= .050,Probability-of-F-to-remove>= .100).

A Dependent Variable: EMI FIX

Model Summary(b)

Model R R Square Adjusted R

SquareStd. Error of the Estimate

1 .639(a) .408 .400 .92190

a Predictors: (Constant), INTRST CHRG BY BNKb Dependent Variable: EMI FIX

ANOVA(b)

Model

Sum of Squares df

MeanSquare F Sig.

1 Regression 45.696 1 45.696 53.766 .000(a)

Residual 66.292 78 .850

Total 111.988 79

a Predictors: (Constant), INTRST CHRG BY BNKb Dependent Variable: EMI FIX

Coefficients(a)

Model Unstandardized CoefficientsStandardizedCoefficients

tSig.

B

Std. Error Beta

1 (Constant) .382 .230 1.665 .100INTRST CHRG BYBNK

.630 .086 .639 7.333 .000

a Dependent Variable: EMI FIX

Stepwise Multiple Linear Regression

When the problem involves one independent variable, all the variables

may not be equally important. It may be that some combinations can

effectively explain the variation better than others. To resolve this




uncertainty, one must evaluate various combinations of independent

variables used in different regression equation. The number of variables

to be included in the analysis should be decided upon. Stepwise

multiple regression analysis is done for the above purpose.

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation N

Predicted Value 1.0128 3.5344 1.8875 .76054 80

Residual -2.53441 2.35678 .00000 .91604 80

Std. Predicted Value -1.150 2.165 .000 1.000 80

Std. Residual -2.749 2.556 .000 .994 80

a Dependent Variable: EMI FIX

Charts




III. ANOVA

SPSS Commands for ANOVA


labels in an SPSS file, to get the first output for a One-Way ANOVA

problem described in the chapter on ANOVA in the text,


SPSS, click on STATISTICS instead of ANALYSIS).

2. Click on COMPARE MEANS.

3. Click on ONE-WAY ANOVA.

4. In the dialogue box that appears, select one appropriate variable as

the DEPENDENT by highlighting it in the left hand side box and

clicking on the arrow towards the DEPENDENT box. Then select

another appropriate variable as a FACTOR (independent variable)

from the list of variable labels that appears on the left side of the

box and click on the arrow directing it to the FACTOR box. The


3210-1-2-3

Regression Standardized Residual

25

20

15

10

5

0

F r e q

u e n c y

Mean = 2.83E-16Std. Dev. = 0.994N = 80

Dependent Variable: EMI FIX

Histogram



variables should get transferred to the right hand side boxes after

the selection.

5. For the FACTOR variable, the minimum value and the maximum

value have to be specified. For doing this, click on RANGE just

below the FACTOR variable, and type in the minimum and

maximum values for the FACTOR (independent variable). For

example, 1 and 3 could be the minimum and maximum values.

6. Click COUNTINE after specifying RANGE, and then OK to get

the output for the One- way ANOVA.

One-wayANOVA

MORTG PRCS

Sum of Squares df Mean Square F Sig.

Between Groups 4.426 4 1.107 .907 .464

Within Groups 91.524 75 1.220

Total 95.950 79

ANOVA

HL EZY 2 UNDRSTND


Between Groups 14.704 4 3.676 3.742 .008

Within Groups 73.683 75 .982Total 88.388 79

ANOVA

SRVC RCVD


Between Groups 46.859 4 11.715 11.695 .000


Total 121.988 79




ANOVA

DOC PRCZER


Between Groups 28.140 4 7.035 7.347 .000Within Groups 71.810 75 .957

Total 99.950 79

ANOVA

PRCZING FEES


Between Groups 31.006 4 7.751 9.612 .000

Within Groups 60.482 75 .806

Total 91.488 79

ANOVA

SENCTION TIME


Between Groups 37.130 4 9.283 9.839 .000

Within Groups 70.757 75 .943

Total 107.888 79

ANOVA

ONLINE


Between Groups 30.112 4 7.528 3.742 .008


Total 180.988 79

ANOVA

SIZ WHL NNP EMI


Between Groups 39.595 5 7.919 4.487 .001


Total 170.188 79

ANOVA

PUBLIC SECTOR


Between Groups 17.875 4 4.469 2.453 .053





Total 154.488 79

INFERENCE: Above calculation shows the result through one-way

ANOVAs.

IV –NON PARAMETRIC TEST- Chi-square Test

SPSS Commands for Frequency Tables and

Cross- tabs with Chi-squared Test


labels in an SPSS data file, to get the frequency tables output for a

problem similar to that described in Chapter 8 of the text,


SPSS, click on STATISTICS, instead of ANALYZE).

2. Click on DESCRIPTIVE STATISTICS, followed by

FREQUENCIES.

3. On the dialogue box which appears, select the variables for which

FREQUENCY TABLES are required, by clicking on the right

arrow to transfer them from the variable list on the left to the

VARIABLES box on the right.

4. Click OK to get the tables with counts and percentages, for each of

the selected variables.

Frequency TableHL EZY 2 UNDRSTND




Frequency Percent Valid PercentCumulative

Percent

Valid 1.00 10 12.5 12.5 12.5

2.00 24 30.0 30.0 42.5

3.00 30 37.5 37.5 80.0

4.00 11 13.8 13.8 93.85.00 5 6.3 6.3 100.0

Total 80 100.0 100.0

6.005.004.003.002.001.000.00

HL EZY 2 UNDRSTND

30

20

10

0

F r e q u e n c y

Mean = 2.7125

Std. Dev. = 1.05775

N = 80

HL EZY 2 UNDRSTND

MORTG PRCS





Percent

Valid .00 1 1.3 1.3 1.3

1.00 20 25.0 25.0 26.3

2.0029 36.3 36.3 62.53.00 19 23.8 23.8 86.3

4.00 8 10.0 10.0 96.3

5.00 3 3.8 3.8 100.0

Total 80 100.0 100.0


6.005.004.003.002.001.000.00-1.00

MORTG PRCS

30

25

20

15

10

5

0

F r e q u e n c y

Mean = 2.275Std. Dev. = 1.10207N = 80

MORTG PRCS



EMI FIX

Frequency Percent Valid Percent CumulativePercent

Valid 1.00 40 50.0 50.0 50.0

2.00 25 31.3 31.3 81.3

3.00 4 5.0 5.0 86.3

4.00 6 7.5 7.5 93.8

5.00 5 6.3 6.3 100.0

Total 80 100.0 100.0


6.005.004.003.002.001.000.00

EMI FIX

40

30

20

10

0

F r e q u e n c y

Mean = 1.8875Std. Dev. = 1.19061N = 80

EMI FIX



SRVC RCVD


Percent

Valid 1.00 21 26.3 26.3 26.3

2.00 20 25.0 25.0 51.3

3.00 23 28.8 28.8 80.0

4.00 9 11.3 11.3 91.3

5.00 7 8.8 8.8 100.0

Total 80 100.0 100.0


6.005.004.003.002.001.000.00

SRVC RCVD

30

25

20

15

10

5

0

F r e q u e n c y

Mean = 2.5125Std. Dev. = 1.24264N = 80

SRVC RCVD



INTRST CHRG BY BNK


Percent

Valid 1.00 23 28.8 28.8 28.8

2.00 25 31.3 31.3 60.0

3.00 13 16.3 16.3 76.3

4.00 16 20.0 20.0 96.3

5.00 3 3.8 3.8 100.0

Total 80 100.0 100.0




HL FVOR


Percent

Valid 1.00 27 33.8 33.8 33.8

2.00 33 41.3 41.3 75.0

3.00 10 12.5 12.5 87.5

4.00 7 8.8 8.8 96.3

5.00 3 3.8 3.8 100.0

Total 80 100.0 100.0


6.005.004.003.002.001.000.00

INTRST CHRG BY BNK

30

25

20

15

10

5

0

F r e q u e n c y

Mean = 2.3875Std. Dev. = 1.20646N = 80

INTRST CHRG BY BNK



6.005.004.003.002.001.000.00

HL FVOR

40

30

20

10

0

F r e q u e n c y

Mean = 2.07

Std. Dev. = 1

N = 80

HL FVOR

DOC PRCZER


Percent

Valid 1.00 14 17.5 17.5 17.5

2.00 30 37.5 37.5 55.0

3.00 22 27.5 27.5 82.5

4.00 8 10.0 10.0 92.5

5.00 6 7.5 7.5 100.0

Total 80 100.0 100.0




6.005.004.003.002.001.000.00

DOC PRCZER

30

25

20

15

10

5

0

F r e q u e n c y

Mean = 2.525

Std. Dev. = 1.12481

N = 80

DOC PRCZER

PRCZING FEES


Percent

Valid 1.00 6 7.5 7.5 7.5

2.00 16 20.0 20.0 27.5

3.00 26 32.5 32.5 60.0

4.00 25 31.3 31.3 91.3

5.00 7 8.8 8.8 100.0

Total 80 100.0 100.0




6.005.004.003.002.001.000.00

PRCZING FEES

30

25

20

15

10

5

0

F r e q u e n c y

Mean = 3.1375

Std. Dev. = 1.07614

N = 80

PRCZING FEES

SENCTION PRCZER


Percent

Valid 1.00 6 7.5 7.5 7.5

2.00 10 12.5 12.5 20.0

3.00 23 28.8 28.8 48.8

4.00 32 40.0 40.0 88.8

5.00 9 11.3 11.3 100.0

Total 80 100.0 100.0




6.005.004.003.002.001.000.00

SENCTION PRCZER

40

30

20

10

0

F r e q u e n c y

Mean = 3.35

Std. Dev. = 1.08032

N = 80

SENCTION PRCZER

SENCTION TIME


Percent

Valid 1.00 3 3.8 3.8 3.8

2.00 12 15.0 15.0 18.8




3.00 18 22.5 22.5 41.3

4.00 23 28.8 28.8 70.0

5.00 24 30.0 30.0 100.0

Total 80 100.0 100.0

6.005.004.003.002.001.000.00

SENCTION TIME

30

25

20

15

10

5

0

F

r e q u e n c y

Mean = 3.6625

Std. Dev. = 1.16862

N = 80

SENCTION TIME

4 CLZR CHRGD


Percent




Valid 1.00 7 8.8 8.8 8.8

2.00 6 7.5 7.5 16.3

3.00 25 31.3 31.3 47.5

4.00 15 18.8 18.8 66.3

5.00 27 33.8 33.8 100.0

Total 80 100.0 100.0

6.005.004.003.002.001.000.00

4 CLZR CHRGD

30

25

20

15

10

5

0

F r e q u e n

c y

Mean = 3.6125

Std. Dev. = 1.26785

N = 80

4 CLZR CHRGD

ONLINE





Percent

Valid .00 1 1.3 1.3 1.3

1.00 34 42.5 42.5 43.8

2.00 9 11.3 11.3 55.0

3.00 18 22.5 22.5 77.54.00 5 6.3 6.3 83.8

5.00 13 16.3 16.3 100.0

Total 80 100.0 100.0

6.005.004.003.002.001.000.00-1.00

ONLINE

40

30

20

10

0

F r e q u e n c y

Mean = 2.3875

Std. Dev. = 1.5136

N = 80

ONLINE




INTRST AS INCME LVL


Percent

Valid 1.00 15 18.8 18.8 18.8

2.00 8 10.0 10.0 28.83.00 21 26.3 26.3 55.0

4.00 13 16.3 16.3 71.3

5.00 23 28.8 28.8 100.0

Total 80 100.0 100.0

6.005.004.003.002.001.000.00

INTRST AS INCME LVL

25

20

15

10

5

0

F r e q u e n c y

Mean = 3.2625

Std. Dev. = 1.45605

N = 80

INTRST AS INCME LVL




SIZ WHL NNP EMI


Percent

Valid .00 1 1.3 1.3 1.3

1.00 17 21.3 21.3 22.5

2.00 21 26.3 26.3 48.8

3.00 14 17.5 17.5 66.3

4.00 11 13.8 13.8 80.0

5.00 16 20.0 20.0 100.0

Total 80 100.0 100.0




6.005.004.003.002.001.000.00-1.00

SIZ WHL NNP EMI

25

20

15

10

5

0

F r e q u e n c y

Mean = 2.8125

Std. Dev. = 1.46774

N = 80

SIZ WHL NNP EMI

FCLTY PRVD BANK


Percent

Valid .00 4 5.0 5.0 5.0

1.00 8 10.0 10.0 15.0

2.00 12 15.0 15.0 30.0

3.00 18 22.5 22.5 52.5

4.00 31 38.8 38.8 91.3

5.00 7 8.8 8.8 100.0

Total 80 100.0 100.0




6.005.004.003.002.001.000.00-1.00

FCLTY PRVD BANK

30

20

10

0

F r e q u e n c y

Mean = 3.0625

Std. Dev. = 1.32497

N = 80

FCLTY PRVD BANK

PUBLIC SECTOR


Percent

Valid 1.00 35 43.8 43.8 43.8

2.00 19 23.8 23.8 67.5

3.00 5 6.3 6.3 73.8

4.00 14 17.5 17.5 91.3

5.00 7 8.8 8.8 100.0

Total 80 100.0 100.0




6.005.004.003.002.001.000.00

PUBLIC SECTOR

40

30

20

10

0

F r e q u e n c y

Mean = 2.2375

Std. Dev. = 1.39841

N = 80

PUBLIC SECTOR

PRIVATE SECTOR


Percent

Valid 1.00 26 32.5 32.5 32.5

2.00 20 25.0 25.0 57.5

3.00 7 8.8 8.8 66.3

4.00 12 15.0 15.0 81.3

5.00 15 18.8 18.8 100.0




Total 80 100.0 100.0

6.005.004.003.002.001.000.00

PRIVATE SECTOR

30

25

20

15

10

5

0

F r e q u e n c y

Mean = 2.625

Std. Dev. = 1.52925

N = 80

PRIVATE SECTOR

INFERENCE: From the above frequencies table shows the makeable in

17 variables.

CROSS-TABS and Chi- Squared test




After the input data has been typed along with variable labels and

values labels in an SPSS data file, to get the CROSS-TABULATIONS

and CHI-Squared test output for a problem similar to that described in

Chapter 8 of the text,1. Click on ANALYZE at the SPSS menu bar (in older versions of


2. Click on DESCRIPTIVE STATISTICS, followed by CROSS-

TABS.

3. Select the row variable for a cross-tribulation by highlighting it in

the variable list on the left side and clicking on the arrow leading

to the row variable box. Similarly, select the variable you wish to

be the column variable in the cross-tabulation.

4. Click on STATISTICS in the main dialogue box. Then click on

“Chi-Square”. In the box titled “Nominal”, click on “Contingency

coefficient”, “Phi and Cramer’s V”, and “Lambda” to give you

these statistics associated which measure the strength of the

association in a cross-tab. Click CONTINUE to return to the maindialogue box.

5. Click on CELLS in the main dialogue box. Under “Percentages”,

select either “ROW” or “COLUMN” depending on which is

desired, as per the discussion and rule given in the text. Click

CONTINUES to return to the main dialogue box.

6. Click OK to get the output containing the required cross-tab,

along with the Chi-squared test and the measures of association

like Lambda and Contingency Coefficients.

Case Processing Summary

Cases




Valid Missing Total

N Percent N Percent N Percent

HL EZY 2 UNDRSTND* MORTG PRCS 80 100.0% 0 .0% 80 100.0%

HL EZY 2 UNDRSTND * MORTG PRCS Cross tabulation

MORTG PRCS Total

.00 1.00 2.00 3.00 4.00 5.00

HL EZY 2UNDRSTND

1.00 Count0 8 1 1 0 0 1

% within HLEZY 2UNDRSTND

.0% 80.0% 10.0% 10.0% .0% .0% 100.0

% withinMORTG PRCS

.0% 40.0% 3.4% 5.3% .0% .0% 12.5

2.00 Count 0 8 7 4 4 1 2


.0% 33.3% 29.2% 16.7% 16.7% 4.2% 100.0

% withinMORTG PRCS .0% 40.0% 24.1% 21.1% 50.0% 33.3% 30.0

3.00 Count 0 4 16 10 0 0 3


.0% 13.3% 53.3% 33.3% .0% .0% 100.0

% withinMORTG PRCS

.0% 20.0% 55.2% 52.6% .0% .0% 37.5

4.00 Count 0 0 3 4 4 0 1


.0% .0% 27.3% 36.4% 36.4% .0% 100.0

% withinMORTG PRCS

.0% .0% 10.3% 21.1% 50.0% .0% 13.8

5.00 Count 1 0 2 0 0 2% within HLEZY 2UNDRSTND

20.0% .0% 40.0% .0% .0% 40.0% 100.0

% withinMORTG PRCS

100.0% .0% 6.9% .0% .0% 66.7% 6.3

Total Count 1 20 29 19 8 3 8

% within HL EZY 2UNDRSTND 1.3% 25.0% 36.3% 23.8% 10.0% 3.8% 100.0

% within MORTG PRCS 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0




Chi-Square Tests

Value df Asymp. Sig.

(2-sided)

Pearson Chi-Square 75.356(a) 20 .000

Likelihood Ratio 58.870 20 .000

Linear-by-Linear Association

10.345 1 .001

N of Valid Cases80

a 24 cells (80.0%) have expected count less than 5. The minimum expected count is .06.

Directional Measures

Value

Asymp.Std.

Error(a) Approx.

T(b) Approx. Sig.

Nominal byNominal

Lambda Symmetric.198 .071 2.561 .010

HL EZY 2 UNDRSTNDDependent .220 .077 2.630 .009

MORTG PRCSDependent .176 .099 1.644 .100

Goodman andKruskal tau

HL EZY 2 UNDRSTNDDependent

.177 .040 .000(c)

MORTG PRCSDependent .164 .042 .000(c)

a Not assuming the null hypothesis.b Using the asymptotic standard error assuming the null hypothesis.c Based on chi-square approximation

INFERENCE: Form the output tables, the Chi-square test read asignificance level of 0.08325 at 90 per cent confidence level. For 90

percent, significance level is 0.1, that is , (1-0.9), so the above result

shows that at 0.08 (which is less than 0.1), there is a significant

relationship between the two variables. At 95 per cent confidence level,

significance level being 0.05, and the above output giving a




significance level of 0.08 which is greater than 0.05, there is no

relationship between the variable:

If contingency coefficient value is greater than +0.5 then the variables

are strongly associated. In the above case the contingency coefficientvalue being 0.6 which is greater than 0.5, hence the variables are

strongly associated.

IV – FACTOR ANALYSIS

SPSS commands for factor AnalysisAfter the input data has been typed along with variable labels and value

labels in an SPSS file, to get the output for a Factor Analysis problem

similar to that described in the text.



2. Click on DATA REDUCTION, followed by FACTOR.

3. On the dialogue box which appears, select all the variables

required for the factor analysis by clicking on the right arrow to

transfer them from the variable list on the left to the variables

box on the right.

4. Click on EXTRACTION in the lower part of the dialogue box.




i. Select “Principal Components” as the Method.

ii. Under DISPLAY, select “Unrotated Factor Solution”.

iii.Under EXTRACT, select “Eigen values over 1”.

iv.Under ANALYZE, choose “Correlation Matrix”.

v. Click CONTINUE.

5. Click on ROTATION in the lower part of the main dialogue

box. Select VARIMAX from the option under MRTHOD. Click

CONTINUE.

6. Click OK to get the FACTOR ANALYSIS output, including the

unrotated factor matrix, the rotated factor matrix using varimax

rotation and the extracted factors along with Eigen values and

cumulative variance. Communality figures would also be a part

of the output.

Note: it is possible to use other methods such as Generalized Least

Squares to get the factors analysis output instead of Principal

Components. It is also possible to use other rotation methods

instead of varimax.

Communalities

Initial Extraction

HL EZY 2 UNDRSTND 1.000 .675

MORTG PRCS 1.000 .798

EMI FIX 1.000 .702

SRVC RCVD 1.000 .778

INTRST CHRG BY BNK 1.000 .773




DOC PRCZER 1.000 .851

PRCZING FEES 1.000 .638

SENCTION PRCZER 1.000 .761

SENCTION TIME 1.000 .839

4 CLZR CHRGD 1.000 .683

ONLINE 1.000 .713INTRST AS INCME LVL 1.000 .609

SIZ WHL NNP EMI 1.000 .815

FCLTY PRVD BANK 1.000 .604

PUBLIC SECTOR 1.000 .783

PRIVATE SECTOR 1.000 .714

HL FVOR 1.000 .800

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component Initial Eigen values

Extraction Sums of SquaredLoadings

Rotation Sums of SquaredLoadings

Total% of

VarianceCumulativ

e % Total% of

VarianceCumulativ

e % Total% of

VarianceCumulativ

e %

1 4.376 25.738 25.738 4.376 25.738 25.738 2.631 15.475 15.475

2 2.765 16.268 42.006 2.765 16.268 42.006 2.463 14.486 29.961

3 1.930 11.355 53.361 1.930 11.355 53.361 2.392 14.071 44.032

4 1.260 7.409 60.770 1.260 7.409 60.770 2.029 11.933 55.964

5 1.112 6.541 67.311 1.112 6.541 67.311 1.683 9.898 65.862

6 1.094 6.433 73.744 1.094 6.433 73.744 1.340 7.882 73.744

7 .736 4.329 78.073

8 .689 4.055 82.129

9 .634 3.728 85.857

10 .519 3.054 88.911

11 .466 2.743 91.654

12 .407 2.396 94.050

13 .290 1.705 95.755

14 .246 1.446 97.201

15 .215 1.266 98.468

16 .152 .895 99.363

17 .108 .637 100.000


Component Matrix(a)

Component

1 2 3 4 5 6

HL EZY 2 UNDRSTND .412 -.247 .229 -.229 .581 -.045

MORTG PRCS .629 -.302 .349 -.298 -.286 -.138

EMI FIX .705 -.353 .257 -.036 -.004 -.115




SRVC RCVD .645 .184 .100 .488 -.241 -.148

INTRST CHRG BY BNK .759 -.289 .010 .279 .010 .189

DOC PRCZER .717 .160 .138 -.265 -.322 -.345

PRCZING FEES .661 .402 -.108 -.162 -.033 -.006

SENCTION PRCZER .533 .601 .090 -.249 .048 .207

SENCTION TIME .461 .687 -.129 -.087 .196 .3054 CLZR CHRGD .209 .643 .129 .102 -.062 .441

ONLINE -.351 .055 .688 -.108 .318 .027

INTRST AS INCME LVL -.498 .353 .401 .215 -.153 .084

SIZ WHL NNP EMI -.224 .228 .819 -.128 .068 -.148

FCLTY PRVD BANK -.383 .585 .136 .044 -.195 -.237

PUBLIC SECTOR .301 .333 -.343 .124 .537 -.400

PRIVATE SECTOR .259 -.553 .225 .053 .001 .536

HL FVOR .324 .006 .342 .728 .172 -.134

Extraction Method: Principal Component Analysis.a 6 components extracted.

Rotated Component Matrix(a)

Component

1 2 3 4 5 6

HL EZY 2 UNDRSTND .045 .204 .598 .276 -.027 .445

MORTG PRCS -.003 .812 .338 .058 .056 -.136

EMI FIX -.009 .606 .502 -.002 .279 .074

SRVC RCVD .261 .386 -.035 -.202 .720 .007

INTRST CHRG BY BNK .170 .302 .585 -.285 .479 -.019

DOC PRCZER .270 .862 -.048 -.095 .111 .104

PRCZING FEES .600 .426 .026 -.206 .078 .216

SENCTION PRCZER .814 .284 .006 .059 -.015 .117

SENCTION TIME .884 .003 -.006 -.086 .035 .220

4 CLZR CHRGD .765 -.108 -.122 .089 .171 -.184

ONLINE -.061 -.146 .033 .827 -.056 -.019

INTRST AS INCME LVL .047 -.295 -.442 .454 .129 -.319

SIZ WHL NNP EMI .020 .143 -.194 .865 .043 -.085

FCLTY PRVD BANK .132 -.085 -.719 .248 .003 -.026

PUBLIC SECTOR .206 -.031 -.086 -.170 .177 .820

PRIVATE SECTOR -.043 .010 .732 .019 .102 -.407

HL FVOR -.005 -.009 .118 .169 .861 .129


Rotation Method: Varimax with Kaiser Normalization. A Rotation converged in 19 iterations.

Component Transformation Matrix

Component 1 2 3 4 5 6

1 .432 .621 .439 -.271 .349 .197

2 .742 -.093 -.625 .137 .044 .170

3 -.003 .263 .096 .886 .254 -.269

4 -.132 -.395 -.084 -.149 .891 -.062

5 .074 -.423 .417 .314 -.033 .736




6 .489 -.448 .475 -.050 -.129 -.561

Extraction Method: Principal Component Analysis.Rotation Method: Varimax with Kaiser Normalization.

INFERENCE:

The output of the factor analysis is obtained by requesting the Principal

Component Analysis (PCA). We get the output comprises the

communality for all 17 variables and the Eigen values of all factors

which have Eigen values of 1 or more than 1 (in this case, we have

assumed only extracting factors having Eigen values 1 or more).The first step in interpreting the output is to look at the factors

extracted. There are 3 factors, which have an Eigen value of 1 or more

than 1. the 3 factors (reducing them from 10) we have lost only about

27% of the information content, while 73% is retained by the 3 factors

extracted out of the 10 original variables.

FINDINGS & SUGGESTIONS


1716151413121110987654321

Component Number

5

4

3

2

1

0

Scree Plot

E i g e n v a l u

e



Among the various loans offered the researcher found that most of the

customer availed home loan whereas the takers for Mortgages and

Housing loan are relatively less i.e. 44 percentages have availed home

loan. 31 percentages are auto loan and 16 percentages are of consumer durable loan respectively. 4 percentages are of personal loan and 2

percentages are of mortgages respectively. Hence it is recommended

for the company to aggressively advertise these loan facilities in both

newspapers and television channels so that many people may be aware

of the same.

♦ From the market research study it has been observed that 90% of the

respondents are aware of home loan.

♦ 62% of the respondents are aware of home loan through agent.

♦ It was founded that 63% of the respondents are rate the service of

home loan as very good.

♦ 90% of the Existing Customers are Happy with the Benefits of home

loan.

SUGGESTIONS

The home loan company should concentrate heavily on attractive

advertisements and various Promotional Strategies like, giving

Pamphlets, put the hoardings and banners at important locations

People should be educated by giving seminar in Business

Conferences, installing stalls in Business Exhibitions. And Company

should conduct seminars in Educational Institutions to provide

information about company and its products.

Company has to create a sense of security among the customers.

Because most of the people fear about security.




CONCLUSIONS

The results and findings of this research study exemplifies the fact that

an in- depth market research has been conducted and all research work

has been conducted and all the objectives set for the research work has

been fully accomplished and the analysis is also performed to the

maximum extent possible.

An in-depth study has been made on the aspect that influences the

banks to be the best private financier. Customer satisfaction is the core

element in the business. For customer satisfaction the services have to

be an edge over the other banks, which banks have achieved. Banks is

aptly targeted potential customers among the various levels of people

in India. The banks overall performance and services seems to be

highly satisfied.

From the analysis it is found that some customers have faced some

procedural problem, for which the researcher has given some

suggestions and recommendations.

Banks has got goodwill and reputation among the public and this can




be used for promoting it services. If new promotional activity and

services introduced, it will help very much the organization to increase

the business.

Documents

research report on e-banking and its effect