Mode of purchasing car

MODE OF PURCHASING CAR : A REVIEW ON BRAND EQUITY AND
EXPERIENCE WITH RESPECT TO LAKSHMI NISSAN
BY
N.VAISHNAVI
(Reg.No.212016631049)
Of
S.K.R ENGINEERING COLLEGE
A PROJECT REPORT
Submitted to the
DEPARTMENT OF MANAGEMENT STUDIES
In partial fulfillment of the requirements
For the award of the degree of
MASTER OF BUSINESS ADMINISTRATION
ANNA UNIVERSITY, CHENNAI
JUNE 2018

BONAFIDE CERTIFICATE
Certified that this project report title “MODE OF PURCHASING CAR : A REVIEW ON
BRAND EQUITY AND EXPERIENCE WITH RESPECT TO LAKSHMI NISSAN.” is
the bonafide work of Ms. N.VAISHNAVI (Reg.No:212016631049) who carried out the
research under my supervision. Certified further, that to the best of my knowledge the work
reported herein does not form part of any other project report or dissertation on the basis of
which a degree or award was conferred on an earlier occasion on this or any other candidate.
Prof. C.GANESH KUMAR Prof. C.GANESH KUMAR
Head of the department Project Guide
Department of the Management Studies Department of the Management Studies
S.K.R Engineering College S.K.R Engineering College
Agarmel, Poonamallee Agarmel, Poonamallee
Chennai – 602 103 Chennai – 602 103
Submitted to Project and Viva Examination held on --------------------------------------------
Internal Examiner External Examiner

DECLARATION
I, Ms. N.VAISHNAVI, M.B.A student of S.K.R Engineering College, would like to declare
that the project work entitled, “MODE OF PURCHASING CAR : A REVIEW ON
BRAND EQUITY AND EXPERIENCE WITH RESPECT TO LAKSHMI NISSAN”,
in partial fulfillment of Master of Business Administration course under Anna university is
original project done independently by me under the guidance of Prof. C.GANESH
KUMAR, Department of Management studies, SKR Engineering college, Poonamallee,
Chennai -602103.
Place:
Date:
(N.VAISHNAVI)

ACKNOWLEDGEMENT
This is with sincere gratitude that I would lie to my record my profound thanks to all the
people who helped and encourage me to complete this project.
I wish to express my gratitude to our Institution and Principal Dr. M.SENTHILKUMAR
M.E., PhD, and Head of the Department Prof. C.GANESHKUMAR for timely advice and
support given to me right from the initial stage of my project.
I take this grand opportunity to record my everlasting thanks and hearty feeling of gratitude
to my project guide Prof. C.GANESH KUMAR for his valuable suggestions.
I express my sincere thanks to Mr. RAJA RAJAN, Manager of LAKSHMI NISSAN for
allowing us to do this Project in the esteemed organization and for valuable guidance.
I also thank my faculty member Prof. R.KUMAR, Ms. K.P.SAJANA, of Management
studies.
This work will be incomplete if I fail to thank my family and friends for their moral support.
I also thank the almighty for making me complete this project successfully.
(N.VAISHNAVI)

ABSTRACT
Marketing is the wide range of activities involved in making sure that you are continuing to meet
the needs of the customers and are getting appropriate value in return. A study on expenditure
pattern of Indian household revealed that spending on transport and communications has
soared and transport accounted the second most important category of spending after
food. The contribution of automobile industry is significant in the development of Indian
economy. Growth of automobile industry induces growth in all sectors of engineering and
related industries. The study primarily intends to explore the deciding factors of new cars from
the stage of need recognition through the purchase process, usage and maintenance, evaluation,
and disposal and repurchase. The respondents with the gender of male agreed very much useful
towards the statement of sales personnel, the respondents with the gender of female agreed
useful to some extent towards the statement of sales personnel. To fulfill the customer
requirement the company can concentrate on the appearance, ground clearance and interior to
improve and to provide a better use of technology. From the study on mode of purchasing car: a
review on brand equity and experience with respect to Lakshmi Nissan, it is concluded that the
customer satisfaction is the important factor, which affects the financial position and goodwill of
the company. Customer demands are dynamic, but its consideration is necessary for every
company to make existence into the market. This project concludes that the Lakshmi Nissan
should provide lowest price of cars for the sake of increasing sales and increasing Nissan motor
market. The study conducted in Lakshmi Nissan helped me to acquire lot of knowledge and also
I personally realize the real difference that exists in theoretical and practical situation.

LIST OF CONTENT
Chapter Title Subtitle Content Page No
Title page A
Bonafide certificate B
Project completion letter C
Declaration D
Acknowledgement E
Abstract F
List of content G
List of tables H
List of figures I
1 Introduction
1.1 Introduction 1
1.2 Statement of the problem 2
1.3 Importance of the study 5
1.4 Scope of the study 5
1.5 Objectives of the study 6
1.6 Limitations of the study 6
I 1.7 Research Methodology 7
1.7.1 Data collection instrument 7
1.7.2 Field work and collection of data 8
1.7.3 Analysis 8
2 Theoretical Background
II 2.1 Literature Review 10
2.2 Study relating to Buyer Behaviour 11
2.3 Studies relating to Passenger Car 12
3 Data Analysis & Interpretation
III 3.1 Data Analysis 13
3.2 Statistical Tools & Interpretation 56
4 Findings and Suggestions
4.1 Findings 82
IV 4.2 Suggestions 88
4.3 Conclusions 88
Appendix
A1 Bibliography 89
A 2 Questionnaire 90

LIST OF TABLES
TABLE NO TITLE PAGE NO
1 Gender 13
2 Age 14
3 Education 15
4 Occupation 16
5 Income 17
6 Time 18
7 Earning members 19
8 Secondary sources of income 20
9 Mode of savings 21
10 Pleasant travel 22
11 First car 23
12 Purchase 24
13 Sales Personnel meet 25
14 Sources of fund 26
15 Repayment 27
16 Yourself 28
17 Grand parents 29
18 Father 30
19 Mother 31
20 Son 32
21 Daughter 33
22 Experience 34
23 Advertisement exposure 35
24 Information 36
25 Car usage 37
26 Drive 38
27 Gender vs Advertisement, Mechanic, Sales personnel 39

28 Age vs Users, Family members, Friends, Internet 40
29 Income vs Price, Maintenance cost, Resale value 42
30 Occupation vs Appearance, Colour, Seating capacity 44
31 Education vs Engine, Suspension, Safety, Braking 46
32 Gender vs Status symbol, Social recognition 48
33 Age vs Newspaper, Radio, Hoardings 49
34 Gender vs Cinema, Internet, window display 51
35 Occupation vs Mechanical breakdown 53
LIST OF FIGURES

1 Gender 13
2 Age 14
3 Education 15
4 Occupation 16
5 Income 17
6 Time 18
7 Earning members 19
8 Secondary sources of income 20
9 Mode of savings 21
10 Pleasant travel 22
11 First car 23
12 Purchase 24
13 Sales Personnel meet 25
14 Sources of fund 26
15 Repayment 27
16 Yourself 28
17 Grand parents 29
18 Father 30
19 Mother 31
20 Son 32
21 Daughter 33
22 Experience 34
23 Advertisement exposure 35
24 Information 36
25 Car usage 37
26 Drive 38
27 Gender vs Advertisement, Mechanic, Sales personnel 39
28 Age vs Users, Family members, Friends, Internet 40
29 Income vs Price, Maintenance cost, Resale value 42
30 Occupation vs Appearance, Colour, Seating capacity 44
31 Education vs Engine, Suspension, Safety, Braking 46

32 Gender vs Status symbol, Social recognition 48
33 Age vs Newspaper, Radio, Hoardings 49
34 Gender vs Cinema, Internet, window display 51
35 Occupation vs Mechanical breakdown 53

CHAPTER I
1.1 INTRODUCTION
India, the largest democracy in this world, has the second largest volume of human resource
in the world. India possesses enormous market size and positive business climate. Assisted
by a comprehensive reforms programme since early 1990s, India has become world's fourth
largest economy in tense of purchasing power parity in 2004 (Chaturvedi, 2004). Now,
India has emerged as one amongst the five fastest growing economies of the world
("Indian Economy," 2007). The growth in Indian economy enabled the people to spend more
on consumable and consumer durable. Increase in per capita income increases the level of
consumption expenditure of the Indian household and is changing the consumption basket
with a shift away from satisfying basic needs to fulfilling higher order needs (Sanyal, 2005).
The demand created in the consumer market has a multiplier effect on the economy by
stimulating the industrial growth further. The growing consumer market necessitates faster
mobility as the products are produced and distributed from the regions where economies of
scale are obtained. As the need for mobility increases, the need for having a good
transportation system also has increased. In Indian context, road transport plays a pivotal
role in transportation system and it remains as the predominant mode of transport for
passengers and freight movement as it is the only transport system that connects almost
all places including remote areas in the country ("Motor Vehicles,"2006). Consistent
increase in demand for the road transportation system made the automobile industry as
one of the largest industrial sectors with the turnover that contributes to roughly 5 per
cent of India's GDP (Sumantran, 2005). The prosperity of the automobile industry is
reflective- of the progress of the economy of the nation.
According to the Society of Indian Automobile Manufacturers (SlAVl), automobile
domestic sales of the year 2006 -07 was 10,109,037 units that includes 1,379,698
units of passenger vehicles, 467,882 units of commercial vehicles,403,909 units of three
wheelers and 7,857,548 units of two wheelers ("Domestic."2007). The number of
vehicles in Tamilnadu state increased 2.5 fold in a decade (1997 - 2006) and it was
8,221,730 in 2006 ("Growth," 2007). Tamilnadu has 581,106 transport vehicles including
stage carriages, bus, cab, fire lighters. Ionics, etc., and 7,640,624 non-transport
vehicles including two wheelers, passenger cars,tractors, etc. Tamil Nadu has around 6.75
million two wheelers and around 0.73 million cars. The rate of growth of number of
vehicles in the state is roughly 11per cent per annum, Among the vehicles that provide

transportation, personal transportation vehicles support our everyday life and providing us a
faster, cheaper, and more convenient mobility. In India, personal transportation vehicles,
that include bikes, mopeds, scooters, scooterettes, and passenger cars facilitate the travel of
individuals / families effectively in reaching places on time in spite of heavy traffic
and poor infrastructure. These personal transportation vehicles have an important
and inseparable role in the day-to-day life of everyone. These wheeled machines make
people's life comfortable and fetch a status for the users. The users create a personal and
emotional attachment with ihe personal transportation vehicles.
A study on expenditure pattern of Indian household (Sanyai, 2005) revealed that spending
on transport and communications has soared and transport accounted the second
most important category of spending after food. Also, Indian households with
rising incomes seem to prefer spending more on passenger cars. In India, the passenger
car sales in 2006 - 07 was 1,076,408 ("Domestic," 2007). Though cars are costly proposition
for the Indian household, the cars are distinctive indicator of the social status of the user.
In buying a passenger car, the buyer not only sees the usability and purpose but also the
inherent image of the brand of the car. The purchase of a car requires careful decision
making as the useful life of the car would stretch over many years. The purchase process of
a car involves considerable time, money, physical and psychological cost. The buyers
require great efforts to make a decision as they need to analyse information that are
floated through various sources. The competing marketers try to understand the needs,
media habits, and influencing forces of the buyers to design their strategy to win the
attention of the buyers.
1.2 STATEMENT OF THE PROBLEM
The contribution of automobile industry is significant in the development of Indian
economy. Growth of automobile industry induces growth in all sectors of engineering and
related industries. The automobile industry provides employment opportunities by
directly employing approximately 0.5 million people and indirectly employing
approximately 10 million people (Ambani, 2004). The Indian automobile industry
includes a range of products in varied categories namely two wheelers, three wheelers,
passenger cars, commercial vehicles, tractors, and also the auto component sectors (Baig,
2004a). Passenger Car, a four wheeled automobile that enable comfortable and convenient
travel, got in to the lime light of the automobile industry by crossing sales over a million.

In earlier days, only people belonging to very rich families and higher income class
purchased cars. The number of brands and models of cars available was also very limited.
Buyers had to wait for a long time to get a car, even after paying full amount, as supplies
were regulated and demands were high. The buyers paid premium to bypass the queue
and even some people made business out of selling their right to buy as they had seniority
in the queue. Today, the demand and supply scenario has totally changed due to
liberalization and entry of many manufacturers. Indian consumers are enjoying the fruit of
new developments in the market; availability of varieties, advanced technology, intensive
distribution practices of marketers, and new and cheaper models that suit various consumer
segments, in short, a buyers' market.
The Indian passenger car market has undergone a major transformation within a short
period. The passenger car market is widening up due to growing numbers of white-collar
workforce, entrepreneurs, rising per capita income, increase in multiple income families,
changing life styles, easy availability of credit, increase in the number of nuclear families,
and increasing consumer awareness .The consumers of rising middle class of India are
aspiring for a better quality of life and they are ready to spend a reasonable share of their
income on passenger car. In India, a new car is considered as a prestigious asset and buying
a car involves significant purchase efforts Indian consumers, while purchasing their
car, are more focused on equating the price and performance compared with their
Western counterparts. Indian buyers also require customization in many fronts like
technology, usability, financing, etc. Indian and foreign passenger car manufacturers attempt
to attract the customers by providing a number of differentiated products that lead to a hefty
competition in the market.
Sometimes, market leaders of various segments struggle hard to survive and even some
proven models fail in the market due to rapid changes in the expectations of the consumers.
To tackle the market dynamics, the marketers of cars are even bound to extend in to non-
core offers such as arranging easy financing, before and after sale service, and exchange of
new makes for old cars. Multiple models and variants offered along with non-core offers of
the marketers make the buying decision more complex and time consuming. Purchase of
passenger cars usually involves many planned steps as the buyers perceive the purchase of a

passenger car as a process of problem solving .Car manufacturers are compelled to design
their products to create
competitively distinct images in the customers' mind. The passenger car industry can
perform better, if the marketer understands the opinions, requirements, likes and
dislikes of those who buy and use cars. Marketers need to understand the customers, in
terms of what they want, what they buy, why they buy, when they buy, where they buy, how
often they buy, and how often they use (Schiffman & Kanuk, 2005, p. 8). Also, the
marketers need to look into personal and group influences along with other
environmental factors in order to formulate strategies to match the resources of the
organisations to the demands of market.
Successful companies identify the latent needs of the market and offer products that are
economically feasible and marketable (Levitt, 1969). Due to many characteristics peculiar to
India, the performance of the Indian automobile industry and the behaviour of the Indian
consumers are difficult to predict (Ambani, 2004).Studying buyer bchaviour is very difficult
due to the rapid changes in cultural value systems, nature of beliefs and perceptions in
society, and the attitude and behaviour of individuals. Introduction of new variants and non-
core offers of the manufacturers and dealers due to the high competition among the
manufacturers and the dynamics in the response of the buyers to different offers made the
situation of car market as complex. The complexity in the car market needs to be mapped to
formulate the strategy. This necessitates a study to understand the factors influencing
car buyers. Since the population of the car buyer is very vast, the researcher made an
attempt to study the buyer behaviour of cars confined to buyers of new cars. The study was
undertakenwith people of all demographic characteristics and income groups; village,
town, and city dwellers; government employees, private employees, professionals and
entrepreneurs; and a good number of retired personnel. It has many business houses,
government establishments, educational institutions, and private firms. It also has a good
number of banks and financial institutions that cater to the financial requirements of the
public.
1.3 IMPORTANCE OF THE STUDY
Increasing incomes among the educated middle class rural Indians, due to the development
of information technology industry, has paved the way for automobile sector to
penetrate into geographical areas which were unmarketable propositions. The

growth of agricultural business and small scale industry in the rural parts of many states of
India has also created a demand for both new and used cars. The increasing activity of
the infrastructure construction has also played a part in expanding the markets for cars.
The study would assist in devising strategies for marketing and developing of markets for
high cost up-market products. In this respect, the findings of this study may enable the
marketer to understand the attitude and expectations of the car buyers and to design
products to cater the buyer's need. This research will make a sketch on the factors
involved in the purchase of cars that are preferred by various customer segments. This
research also enables the designers and manufacturers to identify the perceptions of buyers
of new cars on specific product features and understand the buyers' behaviour. The
understanding on the buyers will help the manufacturers to plan and design customized
products and strategies for the future.
1.4 SCOPE OF THE STUDY
The present study includes the current scenario of the industry, the expectation of the buyers
of new cars, the factors affecting the purchase of new cars, and post purchase behaviour of
new car buyers. Theoretical framework Indian car market, and car buying in Indian
scenario has also been studied. An attempt has been made to study the expectation and
evaluation on different attributes of new cars. The dynamics in deciding car purchase
from information seeking process to actual purchase, usage and evaluation after
utilization have also been studied. The study did not cover vans, cargo vehicles, three
wheelers, or any other automobile except passenger cars.
1.5 OBJECTIVES OF THE STUDY
The study primarily intends to explore the deciding factors of new cars from the stage of
need recognition through the purchase process, usage and maintenance, evaluation, and
disposal and repurchase.
The objectives of the study are:
1. To study the dynamics in the pre-purchase behaviour of the buyers of new cars,
2. To understand the usefulness of different information sources in car
purchasing,
3. To explore the forces initiating, influencing, and deciding the brand of a new car
purchased.

4. To identify the factors that affects the purchase decision of new car buyers,
5. To offer suggestions based on the findings of the study for improving the
effectiveness of marketing of new passenger cars. The study will be relevant to the
industrialists and manufacturers of passenger cars in India.
1.6 LIMITATIONS OF THE STUDY
A sincere attempt was made to study the new car market in Chennai district as specified in
the objectives. Precautionary steps were taken in every stage of data collection. All new
car buyers who were residing and using the car in Chennai district was taken as the
population of the study. Buyers who have purchased new cars in Chennai district and sold
the car or shifted their residence to other districts are not included in the study. Some of the
respondents who reside in Chennai district and use the car in the district have purchased
and registered the car from some other districts. The samples were selected from the
restricted geographical area and thus the findings may not be appropriate for metropolitan
and cosmopolitan cities.
This study adopts the segmentation of cars as followed by SI AM which was based on the
overall length of the body of the car despite a different segmentation methods
that are adopted by the media like small car, mid segment car, and large car, or segments A,
B, C and D which are based on price or engine cubic capacity. All possible efforts were
made to minimize the margin of error. The responses for usefulness of information sources,
sufficiency of information in advertisements, and influence of advertisement were the
perceptions of the respondents.
1.7 METHODOLOGY
This study was explorative and descriptive in nature and it attempted to describe the
behaviour of buyers of new cars in Chennai district. This study was based upon the
survey method that describes the state of affairs at the time of research. This research was
planned to portray the characteristics of new car market in Chennai district. Survey and
fact finding inquiries of different kinds were employed. This research involved in
investigating motives of consumer behavior in order to enable the marketer to develop
suitable marketing strategy with appropriate product design, features, advertising,
and other promotional techniques.

1.7.1 Data Collection Instrument
Data were collected through an interview schedule that was prepared for the purpose.
Secondary data were collected from the published literature, published research articles,
books, journals, news, and websites.
SAMPLING TECHNIQUE
As comprehensive detail of the universe was unavailable, the research to be more pertinent,
the researcher adopted the revenue administrative division which divided the district
into three revenue divisions. Multi-stage sampling technique (Krishnaswami, 1993, pp.
147 – 177) was used. Care was taken to maintain the randomness of the sample.
SAMPLE SIZE
Since the population size was unknown, sample size needed for the study was independent
of population size. The sample size is arrived by considering the practical quantitative
(economic issues, time frame of the research, etc) and qualitative (accessibility to the sample
unit, ethical issues, etc), environmental issues, and the like. At the end of the period the
researcher could collect data from a good number of 134 respondents from the 150
respondents approached for the purpose.
1.7.2 FIELD WORK AND COLLECTION OF DATA
Pre-tested interview schedule was administered by the researcher to the respondents
through personal discussion.
1.7.3 ANALYSIS
The data collected were classified and tabulated. Statistical tools including Garret's ranking
technique, chi-square test, analysis of variance, semantic differential, correlation,
weighted average, and percentage analysis were deployed for analyzing data. SPSS
and Microsoft Excel packages were used for analysis. The statistical tools used in the
research are discussed briefly.
1) Chi-square Test
Chi-square test was applied to test the effect of various socio-economic factors and
behavioural aspects of the buyers, x is useful to establish and measure the existence
of the association between any two attributes (Hooda, 2003, pp.090 718; Levin & Rubin,
2002, pp. 569 - 581). y^ test is applied to find out the dependence of behaviour aspect of a

buyer on the variables like age, gender, education, occupation, family size, number of
earning members, family income, individual income, etc, which depend on the applicability
of the variable on the behaviour. X " may be calculated using the following formula.
Where, Oith Observed value in the (ij) cell Expected value in the (ij) "' cell (More than 20 %
cells should not have a value less than 5 and no cell can have a value zero) number of rows
in the contingency table number of columns in the contingency table On the assumption of
independence of attributes E.J Where, A, N If = total of i "^ row = total of j ' column = total
number of observation '/calculated <xV/o table value for (r -1) (c - 1) degrccs of frccdom,
then it is accepted that the two attiibutes A and IH are independent or there is
Insignificant association between them at 5 percent level and vice versa.
2) Analysis of Variance
Analysis of Variance (ANOVA) is a technique for partitioning the total variation of a set
of data in such a manner that it identifies the component sources of variation (Gupta,
2007, pp. 1009 - 1038; Levin & Rubin, 2002, pp. 591 - 603). This technique enables the
researcher to test the hypothesis concerning the equality of more than two population
means.
3) Correlation
Correlation measures the degree of association between variables (Hair, Anderson, Tatham,
& Black, 2003, pp.151 152). When two variables move in the same direction, their
association is termed as positive correlation. When two variables move in the opposite
direction, their association is termed as negative or inverse correlation. The correlation is
calculated using the following formula. NZXiYi-(IX,)(IYi) Y =V((N2Xi'- (SXi)'-) (NIYi^ -
(lYi)')) Where,r = Correlation coefficient Xj = i"^ Value of the variable XYj = i"' Value of
the variable Y N ^ Number of pairs compared.
4) Weighted Average
Weighted average is used to find out the overall measure when a rating scale was used for
data collection. Weightages were assigned to each values and the average was calculated
using the following formula. Where, X = Weighted average Wj = Weightage of the i"^
variable Xi = Value of the i"'variable
5) Percentage Analysis

Percentage analysis calculates the proportion of the value of any variable to the total value.
It is used to describe the variable using the proportion of the population. Percentage was
calculated using the following formula. Proportion of i = Xj / SXj Where,Xi = i'%alueofX

CHAPTER II
Literature review
STUDIES RELATING TO BUYER BEHAVIOUR
Hoyer and Brown (1990) have conducted a controlled experiment with 173 respondents on
the role of brand awareness in the consumer choice process and found that brand awareness
is a dominant choice heuristics among awareness- group subjects in the consumer choice
process. It is also found that subjects with no brand awareness tend to sample more
brands and select the high-quality brand on the final choice significantly more often than
those with brand awareness. Thus, when quality differences exist among competing
brands and when the well known brand does not offer a quality product, consumers may
"pay a price" for employing simple choice heuristics such as brand awareness in the interest
of economizing time and effort. However, building brand awareness is a viable strategy for
increasing brand-choice probabilities.
Kahn and Baron (1995) have examined how consumers process information in making
high-stakes decision. It is understood that buyers choose compensatory models
when they have more options, more information about the options, more time, less certainty
about their goals, and more accountability. It is also found in the investigation that decision
analysts generally agree that explicit use of compensatory decision rules based on utility
theory approximates the normative rule for decision making. Results also show that the
stronger preference for advisors helps the subjects in impersonal decision making. Subjects
even seem to favour the advisor's assistance over their own opinion. Lee and Lou (1995-96)
have studied the extent to which consumers rely on intrinsic and extrinsic cues in product
evaluation using conjoint analysis and found that consumers with different price schema,
knowledge, and involvement levels rely on different types of product attributes. The study
has also identified that several consumer individual characteristics give rise to
differences in reliance.
It is found that consumers with a stronger price-reliance schema use price more heavily than
those with a weaker schema. It is found that consumer reliance on country-of-origin

information is neither correlated with enduring involvement Nor with patriotism. They
have suggested that companies may measure the schema strength and classify the consumer
on the basis of the schema strength. It is also suggested that marketers may segment their
markets on the basis of consumer characteristics like price schema, knowledge, and
involvement level and manipulate product cues differently for different segments to position
their products.
STUDIES RELATING TO BEHAVIOUR OF BUYERS OF CONSUMER
DURABLES
Carpenter, Glazer, and Nakamoto (1994) have examined how meaningless differentiation
produces a meaningfully differentiated brand and showed that an irrelevant attribute can be
positively valued but that there are limits as to when and how much, depending on
price. It is stated that at a low price, irrelevant attributes are not valued, regardless of
whether consumers acknowledge their true irrelevance, however at a high price,
regardless of the revelation of the irrelevance of the differentiating attribute, the
irrelevant attribute adds distinguishing, unique, and greater brand valuation to the
consumers. It is noted that adding an irrelevant attribute to one brand changes the
structure of the decision consumers face, especially if the differentiating attribute is
difficult to evaluate and consumers may infer the attribute's value and conclude that
attribute as valuable. Venkateswarlu and Reddy (1997) have studied the influences of the
external and internal factors with 200 respondents and found that family members act as
initiators and influencers. It is found that in most of the cases the head of the family along
with their spouse acted as decision-makers and buyers. It is understood that level of
education of the respondent have no impact on the purchase decision.
The popular media for advertising are identified as newspapers, pamphlets,
showroom display, radio, magazines, wall-posters, films and televisions in its order.
Arora and Auenby (1999) have analysed the preference structures among the randomly
selected married couples. They have developed a hierarchical Bayes model of group
decision making that yields individual estimates of influence at f)e product attribute level. It
is explained that group purchase decisions are affected by the preference structures of
individual members and the influence they have in the group. Information about product

attribute sensitivities, channel preferences, and price elasticity of the more influential
members in a group is useful for the marketers in framing their marketing strategy.
STUDIES RELATING TO PASSENGER CARS
Biischken (2007) has analysed the efficiency of the advertising and the determinants in the
German car market with 35 brands of cars and found that 8% of a brand's advertising
budget is wasted. Data Envelopment Analysis (DEA) is applied to a multiple input-output
model of advertising. It is noted that smaller product portfolios are less efficient in brand
advertising. It is also noted that previous brand choice does not have the postulated effect on
advertising inefficiency.
Swaminathan, Page, and Giirhan-Canli (2007) have studied the relationship between the
consumer and the brand and found that consumer-brand relationships can be
formed based on individual-level or group-level connections. They have suggested that the
effects of self-concept connection and brand country-of-origin connection vary based on
self-construal. It is also revealed that, under independent self-construal, self-
concept connection is more important and under interdependent self-construal,
brand country-of-origin connection is more important. Chapter (2007) states that companies
can make better decisions about market opportunities and new products, if the designers
are involved at each stage of the development process. It is also stated that the traditional
approach to product strategy, which consists of the phases of options portfolio, business
case, road map and execution plan, is inflexible and often based on outdated assumptions
about consumer preferences. It is noted that the U.S. automobile industry lost first-
mover advantage when it failed to recognize a market for hybrid c.

CHAPTER III
DATA ANALYSIS AND INTERPRETATIONS
GENDER
Table 1
Gender
Frequency Percent Valid Percent Cumulative Percent
Valid
Male 82 61.2 61.2 61.2
Female 52 38.8 38.8 100.0
Total 134 100.0 100.0
Chart 1
Inference: From the above table, it is inferred that 61.2% of the respondents are of gender male,
38.8% of the respondents are female.

AGE
Table 2
Age
Valid
20-25 8 6.0 6.0 6.0
26-30 43 32.1 32.1 38.1
31-35 36 26.9 26.9 64.9
36-40 30 22.4 22.4 87.3
above 41 17 12.7 12.7 100.0
Total 134 100.0 100.0
Chart 2
Inference: It is inferred that 32.1% of the respondents are in the age group of 26-30 years,
26.9% of the respondents are 31-35 years, 22.4% of the respondents are 36-40 years, 12.7% of
the respondent are above 41.6% of the respondents are 20-25 years.

EDUCATION
Table 3
Chart 3
Inference: From the above table, it is inferred that 69.4% of the respondents are of education
qualification UG degree and 30.6% of the respondents are PG degree.
Education
Valid
UG 93 69.4 69.4 69.4
PG 41 30.6 30.6 100.0
Total 134 100.0 100.0

OCCUPATION
Table 4
Occupation
Valid
self employed 25 18.7 18.7 18.7
Managers 16 11.9 11.9 30.6
Educationalists 17 12.7 12.7 43.3
Service 4 3.0 3.0 46.3
Professionals 72 53.7 53.7 100.0
Total 134 100.0 100.0
Chart 4
Inference: It is inferred that 53.7% of the respondents are Professionals, 18.7% of the
respondents are self employed, 12.7% of the respondents are educationalists, 11.95% of the
respondents are managers, 3% of the respondents are service.

INCOME
Table 5
Income
Valid
100001-200000 11 8.2 8.2 8.2
200001-300000 46 34.3 34.3 42.5
300001-400000 54 40.3 40.3 82.8
400001-500000 17 12.7 12.7 95.5
above 500000 6 4.5 4.5 100.0
Total 134 100.0 100.0
Chart 5
Inference: It is inferred that 40.3% of the respondents have income of 300001-400000 per
annum, 34.3% of the respondents have income of 200001-300000 per annum, 12.7% of the
respondents have income of 400001-500000 per annum, 8.2% of the respondents have income of
100001-200000 per annum, 4.5% of the respondents have income above 500000 per annum.

TIME
Table 6
Time
Valid
0-2 101 75.4 75.4 75.4
3-5 29 21.6 21.6 97.0
6-8 4 3.0 3.0 100.0
Total 134 100.0 100.0
Chart 6
Inference: It is inferred that 75.4% of the respondents took 0-2 months to decide the brand of the
car , 21.6% of the respondents took 3-5 months and 3% of the respondents took 6-8 months.

EARNING MEMBERS
Table 7
Earning members
Valid
one 91 67.9 67.9 67.9
two 35 26.1 26.1 94.0
three 7 5.2 5.2 99.3
more than three 1 .7 .7 100.0
Total 134 100.0 100.0
Chart 7
Inference: It is inferred that 67.9% of the respondents have one earning member in their family,
26.1% of the respondents have two earning members, 5.2% of the respondents have three
earning members, 0.7% of the respondents have more than three earning members.

SECONDARY SOURCES OF INCOME
Table 8
Secondry sources
Valid
trading 49 36.6 36.6 36.6
properties 18 13.4 13.4 50.0
deposits/investments 64 47.8 47.8 97.8
pension 3 2.2 2.2 100.0
Total 134 100.0 100.0
Chart 8
Inference: It is inferred that 47.8% of the respondents have secondary source of income in
Deposit/Investments, 36.6% of the respondents have secondary source of income in trading,
13.4% of the respondents have secondary source of income in properties, 2.2% of the
respondents have secondary source of income in pension.

MODES OF SAVINGS
Table 9
Savings mode
Valid
savings bank 97 72.4 72.4 72.4
land/building 20 14.9 14.9 87.3
fixed deposits 5 3.7 3.7 91.0
bonds/securities 6 4.5 4.5 95.5
shares 3 2.2 2.2 97.8
gold 3 2.2 2.2 100.0
Total 134 100.0 100.0
Chart 9
Inference: It is inferred that 72.4% of the respondents save in bank, 14.9% of the respondents
save in land/building, 4.5% of the respondents save in bonds/securities, 3.7% of the respondents
save in fixed deposits, 2.2% of the respondents save in shares, 2.2% of the respondents save in
gold.

PLEASANT TRAVEL
Table 10
Chart 10
Inference: It is inferred that 97% of the respondents agreed that they had pleasant travel in the
newly purchased car but 3% of the respondents disagreed.
Pleasant travel
Valid
Yes 130 97.0 97.0 97.0
No 4 3.0 3.0 100.0
Total 134 100.0 100.0

FIRST CAR
Table 11
First car
Valid
yes 127 94.8 94.8 94.8
no 7 5.2 5.2 100.0
Total 134 100.0 100.0
Chart 11
Inference: It is inferred that 94.8% of the respondents agreed that the new car was their first car
but 5.2% of the respondents disagreed.

PURCHASE
Table 12
Purchase
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid
from local dealer 104 77.6 77.6 77.6
from dealers of other
area
30 22.4 22.4 100.0
Total 134 100.0 100.0
Chart 12
Inference: It is inferred that 77.6% of the respondents purchased from local dealer and 22.4% of
the respondents purchased from the dealers of other area.

SALES PERSONNEL MEET
Table 13
Sales meet
Valid
yes 128 95.5 95.5 95.5
no 6 4.5 4.5 100.0
Total 134 100.0 100.0
Chart 13
Inference: It is inferred that 95.5% of the respondents agreed that they met the sales personnel
before the purchase of car but 4.5% of the respondents disagreed.

SOURCES OF FUND
Table 14
Sources of fund
Valid family savings 114 85.1 85.1 85.1
borrowings 20 14.9 14.9 100.0
Total 134 100.0 100.0
Chart 14
Inference: It is inferred that 85.1% of the respondents purchased the new car from family
savings and 14.9% of the respondents purchased from borrowings.

REPAYMENT
Table 15
Repayment
Valid
monthly 86 64.2 64.2 64.2
quarterly 11 8.2 8.2 72.4
half yearly 6 4.5 4.5 76.9
yearly 8 6.0 6.0 82.8
onetime 23 17.2 17.2 100.0
Total 134 100.0 100.0
Chart 15
Inference: It is inferred that 64.2% of the respondents repaid the amount monthly, 17.2% of the
respondents repaid onetime, 8.2% of the respondents repaid quarterly, 6% of the respondents
repaid yearly, 4.5% of the respondents repaid half-yearly.

YOURSELF
Table 16
Yourself
Valid
initiator 19 14.2 14.2 14.2
influencer 4 3.0 3.0 17.2
decider 111 82.8 82.8 100.0
Total 134 100.0 100.0
Chart 16
Inference: It is inferred that 82.8% of the respondents agreed that they themselves are decider,
14.2% of the respondents are initiator, 3% of the respondents are influencer.

GRAND PARENTS
Table 17
Grand parents
Valid
initiator 49 36.6 36.6 36.6
influencer 82 61.2 61.2 97.8
decider 3 2.2 2.2 100.0
Total 134 100.0 100.0
Chart 17
Inference: It is inferred that 61.2% of the respondents agreed that grandparents are influencer,
36.6% of the respondents are initiator, 2.2% of the respondents are decider.

FATHER
Table 18
Father
Valid
Initiator 53 39.6 39.6 39.6
influencer 67 50.0 50.0 89.6
decider 14 10.4 10.4 100.0
Total 134 100.0 100.0
Chart 18
Inference: It is inferred that 50% of the respondents agreed that father is the influencer, 39.6%
of the respondents are initiator, 10.4% of the respondents are decider.

MOTHER
Table 19
Mother
Valid
Initiator 52 38.8 38.8 38.8
influencer 80 59.7 59.7 98.5
Decider 2 1.5 1.5 100.0
Total 134 100.0 100.0
Chart 19
Inference: It is inferred that 59.7% of the respondents agreed that Mother is the influencer,
38.8% of the respondents are initiator, 1.5% of the respondents are decider.

SON
Table 20
Son
Valid
initiator 62 46.3 46.3 46.3
influencer 67 50.0 50.0 96.3
decider 5 3.7 3.7 100.0
Total 134 100.0 100.0
Chart 20
Inference: It is inferred that 50% of the respondents agreed that Son is the influencer, 46.3% of
the respondents are initiator, 3.7% of the respondents are decider.

DAUGHTER
Table 21
Daughter
Valid
Initiator 74 55.2 55.2 55.2
Influencer 59 44.0 44.0 99.3
Decider 1 .7 .7 100.0
Total 134 100.0 100.0
Chart 21
Inference: It is inferred that 55.2% of the respondents agreed that Daughter is the initiator, 44%
of the respondents are influencer, 0.7% of the respondents are decider.

EXPERIENCE
TABLE 22
Experience
Valid Test drive 100 74.6 74.6 74.6
friends/relatives 24 17.9 17.9 92.5
Taxi 9 6.7 6.7 99.3
Others 1 .7 .7 100.0
Total 134 100.0 100.0
Chart 22
Inference: It is inferred that 74.6% of the respondents says test drive as experience of
purchasing new car, 17.9% of the respondents says friends/relatives, 6.7% of the respondents
says taxi, 0.7% of the respondents says others.

ADVERTISEMENT EXPOSURE
Table 23
Advertisement exposure
Valid
yes 121 90.3 90.3 90.3
no 13 9.7 9.7 100.0
Total 134 100.0 100.0
Chart 23
Inference: It is inferred that 90.3% of the respondents had advertisement exposure and 9.7% of
the respondents does not have advertisement exposure.

INFORMATION
Table 24
Information
Valid
Yes 103 76.9 76.9 76.9
No 31 23.1 23.1 100.0
Total 134 100.0 100.0
Chart 24
Inference: It is inferred that 76.9% of the respondents agreed that they had sufficient
information to decide the brand and 23.1% of the respondents disagreed.

CAR USAGE
Table 25
Car usage
Valid
daily 104 77.6 77.6 77.6
once in two days 22 16.4 16.4 94.0
once in a fortnight 3 2.2 2.2 96.3
occasionally 4 3.0 3.0 99.3
very rarely 1 .7 .7 100.0
Total 134 100.0 100.0
Chart 25
Inference: It is inferred that 77.6% of the respondents says that the car usage was daily and
16.4% of the respondents says once in two days, 3% of the respondents says occasionally and
2.2% of the respondents says once in a fortnight, 0.7% of the respondents says very rarely.

DRIVE
Table 26
Drive
Valid
self 114 85.1 85.1 85.1
paid driver 14 10.4 10.4 95.5
family member 6 4.5 4.5 100.0
Total 134 100.0 100.0
Chart 26
Inference: It is inferred that 85.1% of the respondents prefer self driving and 10.4% of the
respondents prefer paid driver, 4.5% of the respondents prefer family member.

GENDER VS ADVERTISEMENT, MECHANIC, SALES PERSONNEL, TEST DRIVE.
Table 27
Report
Gender Advertisement Mechanic Sales personnel Test drive opinion
Male
Mean 3.74 3.57 3.78 3.71
Std. Deviation 1.174 1.166 1.089 1.105
Female
Mean 3.79 3.25 3.52 3.52
Std. Deviation 1.405 1.135 1.111 1.111
Total
Mean 3.76 3.45 3.68 3.63
Std. Deviation 1.264 1.161 1.101 1.107
Chart 27
Inference:
It is inferred that most of the respondents with the gender of both male and female agreed very
much useful towards the statement of advertisement.
0
0.5
1
1.5
2
2.5
3
3.5
4
Male Mean
Male Std. Deviation
Female Mean
Female Std. Deviation

It is inferred that most of the respondents with the gender of both male and female agreed useful
to some extent towards the statement of mechanic.
It is inferred that most of the respondents with the gender of male agreed very much useful
towards the statement of sales personnel, the respondents with the gender of female agreed
useful to some extent towards the statement of sales personnel.
It is inferred that most of the respondents with the gender of male agreed very much useful
towards the statement of test drive, the respondents with the gender of female agreed useful to
some extent towards the statement of test drive.
AGE VS USERS, FAMILY MEMBERS, FRIENDS, INTERNET.
Table 28
Report
Age Users Family members Friends Internet
20-25 Mean 3.75 3.50 3.00 3.25
Std. Deviation 1.282 1.414 1.309 1.035
26-30 Mean 3.67 3.65 3.42 3.49
Std. Deviation 1.229 1.089 1.180 1.183
31-35 Mean 3.53 3.50 3.28 3.47
Std. Deviation 1.134 1.254 1.186 1.108
36-40 Mean 3.70 3.47 3.30 3.33
Std. Deviation 1.149 1.224 1.317 1.322
above 41 Mean 3.59 3.53 3.59 3.47
Std. Deviation 1.228 1.281 1.176 1.179
Total Mean 3.63 3.54 3.35 3.43
Std. Deviation 1.173 1.193 1.209 1.173
Chart 28

Inference:
It is inferred that most of the respondents with the age of 20-25 years, 26-30 years, 31-35 years,
36-40 years, above 41 years agreed very much useful towards the statement of users of the brand.
above 41 years agreed very much useful towards the statement of members of family/relatives,
the respondents in the age of 36-40 years agreed useful to some extent towards the statement of
members of family/relatives.
36-40 years agreed useful to some extent towards the statement of friends/colleagues, the
respondents in the age of above 41years agreed very much useful towards the statement of
friends/colleagues.
36-40 years, above 41 years agreed useful to some extent towards the statement of internet.
0
0.5
1
1.5
2
2.5
3
3.5
4
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
20-25 26-30 31-35 36-40 above 41
Users
Family members
Friends
Internet

INCOME VS PRICE, MAINTENANCE COST, RESALE VALUE, FUEL EFFICIENCY.
Table 29
Report
Income Price factor Maintenance cost Resale value Fuel factor
100001-200000
Mean 4.45 4.27 4.00 4.45
Std. Deviation .688 .905 1.095 .688
200001-300000
Mean 4.35 4.26 4.17 4.33
Std. Deviation .795 .681 .769 .701
300001-400000
Mean 4.35 4.20 4.15 4.07
Std. Deviation .781 .762 .810 1.007
400001-500000
Mean 4.41 4.35 4.35 4.35
Std. Deviation .618 .702 .606 .702
above 500000
Mean 4.33 4.33 4.67 4.50
Std. Deviation .816 .816 .516 .548
Total
Mean 4.37 4.25 4.19 4.25
Std. Deviation .751 .733 .790 .836

Chart 29
Inference:
It is inferred that most of the respondents in all income levels agreed more important towards the
statement of price factor.
It is inferred that most of the respondents in all income levels agreed more important towards the
statement of maintenance cost.
It is inferred that most of the respondents above 500000 income agreed most important towards
the statement of resale value, 100001-200000 per annum, 200001-300000 per annum, 300001-
400000 per annum, 400001-500000 per annum agreed more important towards the statement of
resale value.
It is inferred that most of the respondents above 500000 income agreed most important towards
the statement of fuel efficiency, 100001-200000 per annum, 200001-300000 per annum, 300001-
400000 per annum, 400001-500000 per annum agreed more important towards the statement of
fuel efficiency.
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
100001-
200000
200001-
300000
300001-
400000
400001-
500000
above
500000
Price factor
Maintenance cost
Resale value
Fuel factor

OCCUPATION VS APPEARANCE, COLOR, SEATING CAPACITY, COMFORTABLE
INTERIOR, GROUND CLEARANCE, MULTIPLE USAGE.
Table 30
Report
Occupation Appearance Color Seating Interior
Ground
clearance
Multiple
usage
self employed
Mean 3.76 3.80 3.72 3.60 3.60 3.60
Std.
Deviation
.779 .764 .737 .816 .816 .913
Managers
Mean 3.63 3.81 3.81 3.81 3.81 3.50
Std.
Deviation
1.025 .655 .750 1.109 1.109 .894
Educationalists
Mean 3.65 3.41 3.71 3.47 3.47 3.82
Std.
Deviation
.931 .870 .588 .874 .874 .636
Service
Mean 2.50 3.25 4.00 2.75 2.75 3.00
Std.
Deviation
1.732 1.500 .816 1.500 1.500 1.155
Professionals
Mean 3.83 3.81 3.78 3.69 3.69 3.81
Std.
Deviation
.839 .799 .773 .882 .882 .799
Total
Mean 3.73 3.74 3.77 3.63 3.63 3. 71
Std.
Deviation
.911 .813 .735 .922 .922 .830

Chart 30
Inference:
It is inferred that most of the respondents of self employed, managers, educationalists,
professionals agreed more important towards the statement of appearance, the respondents of
service agreed important towards the statement of appearance.
It is inferred that most of the respondents of self employed, managers, professionals agreed more
important towards the statement of color, the respondents of educationalists, service agreed
important towards the statement of color.
professionals, service agreed more important towards the statement of seating capacity.
important towards the statement of comfortable interior, the respondents of educationalists,
service agreed important towards the statement of comfortable interior.
important towards the statement of ground clearance, the respondents of educationalists, service
agreed important towards the statement of ground clearance.
professionals agreed more important towards the statement of multiple usage, the respondents of
service agreed important towards the statement of multiple usage.
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
self employed Managers Educationalists Service Professionals
Appearance
Colour
Seating
Interior
Ground clearance
Multiple usage

EDUCATION VS ENGINE, SUSPENSION, SAFETY, BRAKING, GEAR, ELECTRICAL
ACCESSORIES.
Table 31
Report
Education Engine Suspension Safety Braking Gear Electrical accessories
UG
Mean 4.03 4.12 4.13 3.97 3.99 3.94
Std. Deviation .800 .792 .824 1.037 .950 .965
PG
Mean 4.02 3.98 4.02 4.07 4.02 4.05
Std. Deviation .758 .851 .851 .755 .935 .805
Total
Mean 4.03 4.07 4.10 4.00 4.00 3.97
Std. Deviation .785 .810 .831 .958 .942 .917

Chart 31
Inference:
It is inferred that most of the respondents with education qualification of UG and PG agreed
more important towards the statement of engine technology.
more important towards the statement of suspension system.
more important towards the statement of safety provision.
more important towards the statement of braking system.
more important towards the statement of gear system.
more important towards the statement of electrical accessories.
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
ug Mean
ug Std. Deviation
pg Mean
pg Std. Deviation

GENDER VS STATUS SYMBOL, SOCIAL RECOGNITION, SENSE OF
ACHIEVEMENT.
Table 32
Report
Gender Status Social factor Sense factor
Male
Mean 3.80 3.76 3.57
Std. Deviation 1.048 1.095 1.111
Female
Mean 3.62 3.73 3.83
Std. Deviation 1.105 1.105 1.024
Total
Mean 3.73 3.75 3.67
Std. Deviation 1.070 1.095 1.081
Chart 32
Inference:
It is inferred that most of the respondents with the gender of both male and female agreed more
important towards the statement of status symbol.
It is inferred that most of the respondents with the gender of both male and female agreed more
important towards the statement of social recognition.
0
1
2
3
4
5
Mean Std. Deviation Mean Std. Deviation
Male Female
Status
Social factor
Sense factor

AGE VS NEWSPAPER, RADIO, HOARDINGS.
Table 33
Report
Age EA newspaper EA radio EA hoardings
20-25
Mean 3.75 3.88 3.75
Std. Deviation 1.282 .991 1.165
26-30
Mean 3.79 3.77 3.70
Std. Deviation 1.125 .895 .887
31-35
Mean 3.50 3.22 3.44
Std. Deviation .737 .898 .843
36-40
Mean 3.80 3.50 3.43
Std. Deviation .961 1.106 .858
above 41
Mean 3.82 3.29 3.47
Std. Deviation .951 1.105 1.068
Total
Mean 3.72 3.51 3.54

Chart 33
Inference:
36-40 years, above 41 years agreed often towards the statement of newspaper/magazines.
It is inferred that most of the respondents with the age of 20-25 years, 26-30 years, 36-40 years
agreed often towards the statement of radio, the respondents with the age of 31-35 years, above
41years agreed sometimes towards the statement of radio.
It is inferred that most of the respondents with the age of 20-25 years , 26-30 years agreed often
towards the statement of hoardings, the respondents with the age of 31-35 years, 36-40 years,
above 41 years agreed sometimes towards the statement of hoardings.
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
20-25 26-30 31-35 36-40 above 41
EA newspaper
EA radio
EA hoardings

GENDER VS CINEMA, INTERNET, WINDOW DISPLAY.
Table 34
Report
Gender EA cinema EA internet EA window display
Male
Mean 3.59 3.71 3.70
Female
Mean 3.44 3.21 3.37
Total
Mean 3.53 3.51 3.57
Chart 34
0
0.5
1
1.5
2
2.5
3
3.5
4
Mean Std.
Deviation
Mean Std.
Deviation
Male Female
EA cinema
EA internet
EA window display

Inference:
It is inferred that most of the respondents with the gender of male agreed often towards the
statement of cinema, the respondents with the gender of female agreed sometimes towards the
statement of cinema.
statement of internet, the respondents with the gender of female agreed sometimes towards the
statement of internet.
statement of window display, the respondents with the gender of female agreed sometimes
towards the statement of window display.

OCCUPATION VS MECHANICAL BREAKDOWN, FAILURES IN ELECTRICAL
SYSTEM, UNCOMFORTABLE TO SELF DRIVE, UNCOMFORTABLE SEATS, HARD
IN ROUGH ROADS, LESS LUGGAGE SPACE.
Table 35
Report
Occupation
Mechanica
l
breakdow
n
Failure
in
electrica
l system
Uncomfortabl
e self drive
Uncomfortabl
e seat
Roug
h
roads
Luggag
e space
self employed
Mean 3.40 3.36 3.52 3.56 3.76 3.76
Std.
Deviatio
n
1.000 .757 .872 .961 .779 .831
Managers
Mean 3.06 3.00 3.56 3.50 3.06 3.19
Std.
Deviatio
n
1.237 1.095 .892 .816 1.237 1.223
Educationalist
s
Mean 3.12 2.88 3.24 3.35 3.18 3.24
Std.
Deviatio
n
.993 .928 1.300 .931 1.237 1.147
Service
Mean 4.00 3.00 3.00 3.00 2.25 2.25
Std.
Deviatio
n
1.155 .816 .816 .816 .957 1.500
Professionals
Mean 3.24 3.36 3.40 3.58 3.49 3.51
Std.
Deviatio
n
1.132 .997 .899 .868 .964 1.021
Total Mean 3.25 3.25 3.41 3.52 3.41 3.45

Report
Occupation
Mechanica
l
breakdow
n
Failure
in
electrica
l system
Uncomfortabl
e self drive
Uncomfortabl
e seat
Roug
h
roads
Luggag
e space
self employed
Mean 3.40 3.36 3.52 3.56 3.76 3.76
Std.
Deviatio
n
1.000 .757 .872 .961 .779 .831
Managers
Mean 3.06 3.00 3.56 3.50 3.06 3.19
Std.
Deviatio
n
1.237 1.095 .892 .816 1.237 1.223
Educationalist
s
Mean 3.12 2.88 3.24 3.35 3.18 3.24
Std.
Deviatio
n
.993 .928 1.300 .931 1.237 1.147
Service
Mean 4.00 3.00 3.00 3.00 2.25 2.25
Std.
Deviatio
n
1.155 .816 .816 .816 .957 1.500
Professionals
Mean 3.24 3.36 3.40 3.58 3.49 3.51
Std.
Deviatio
n
1.132 .997 .899 .868 .964 1.021
Total Mean 3.25 3.25 3.41 3.52 3.41 3.45
Std.
Deviatio
n
1.102 .961 .944 .882 1.035 1.066

Chart 35
Inference:
It is inferred that most of the respondents of occupation service agreed sometimes towards the
statement of mechanical breakdown, the respondents of self employed, managers,
educationalists, professionals neither agreed nor disagreed towards the statement of mechanical
breakdown.
It is inferred that most of the respondents of occupation self employed, managers,
educationalists, service, professionals neither agreed nor disagreed towards the statement of
failures in electrical system.
It is inferred that most of the respondents of occupation self employed, managers agreed
sometimes towards the statement of uncomfortable to self drive, the respondents of
educationalists, service, professionals neither agreed nor disagreed towards the statement of
uncomfortable to self drive.
It is inferred that most of the respondents of occupation self employed, managers, professionals
agreed sometimes towards the statement of uncomfortable seats, the respondents of
educationalists, service neither agreed nor disagreed towards the statement of uncomfortable
seats.
It is inferred that most of the respondents of occupation service agreed often towards the
statement of hard in rough roads, the respondents of self employed agreed sometimes towards
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
Mean
Std.Deviation
self employed Managers Educationalists Service Professionals
Mechanical breakdown
Failure in electrical system
Uncomfortable self drive
Uncomfortable seat
Rough roads
Luggage space

the statement of hard in rough roads, the respondents of managers, educationalists, professionals
neither agreed nor disagreed towards the statement of hard in rough roads.
It is inferred that most of the respondents of occupation service agreed often towards the
statement of less luggage space, the respondents of self employed, professionals agreed
sometimes towards the statement of less luggage space, the respondents of managers,
educationalists neither agreed nor disagreed towards the statement of less luggage space.

STATISTICAL TOOLS AND INTERPRETATION
CHI SQUARE 1
AIM : To set the significant associations between purchase of new car with sales
representative meet.
H0 : There is no significant associations between purchase of new car with sales
H1 : There is a significant associations between purchase of new car with sales
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Exact Sig. (2-
sided)
Exact Sig. (1-
sided)
Pearson Chi-Square .433a 1 .510
Continuity Correctionb .025 1 .875
Likelihood Ratio .395 1 .529
Fisher's Exact Test .616 .404
Linear-by-Linear
Association
.430 1 .512
N of Valid Cases 134
a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 1.34.
b. Computed only for a 2x2 table
RESULT:
Significant level : 0.05
P Value : 0.404
Therefore the null hypothesis is accepted.
INTERPRETATION:
The significant level is less than P value so the null hypothesis is accepted. Hence it is concluded
that there is no significant associations between purchase of new car with sales representative
meet.

CHI SQUARE 2
AIM : To set the significant associations between savings mode with sources of fund.
H0 : There is no significant associations between savings mode with sources of fund.
H1 : There is a significant associations between savings mode with sources of fund.
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 35.240a 5 .000
Likelihood Ratio 26.220 5 .000
Linear-by-Linear Association 21.236 1 .000
a. 8 cells (66.7%) have expected count less than 5. The minimum expected count is .45.
RESULT:
P value : 0.00
Therefore the null hypothesis is rejected.
INTERPRETATION:
The significant level is greater than P value so the null hypothesis is rejected. Hence it is
concluded that there is a significant associations between savings mode with sources of fund.

CHI SQUARE 3
AIM : To set the significant associations between advertisement information with
advertisement exposure.
H0 : There is no significant associations between advertisement information with
H1 : There is a significant associations between advertisement information with
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Exact Sig. (2-
sided)
Exact Sig. (1-
sided)
Pearson Chi-Square 7.636a 1 .006
Continuity Correctionb 5.843 1 .016
Likelihood Ratio 6.474 1 .011
Fisher's Exact Test .012 .012
Linear-by-Linear
Association
7.579 1 .006
a. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 3.01.
b. Computed only for a 2x2 table
RESULT:
P value : 0.012
Therefore the null hypothesis is rejected.
INTERPRETATION: The significant level is greater than P value so the null hypothesis is
rejected. Hence it is concluded that there is a significant associations between information with

ANOVA 1
AIM : To find whether the mean score of mechanical breakdown is same on car usage.
H0 : The mean score of mechanical breakdown is same on car usage.
H1 : The mean score of mechanical breakdown is not same on car usage.
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1
Regression .087 1 .087 .071 .790a
Residual 161.287 132 1.222
Total 161.373 133
a. Predictors: (Constant), Car usage
b. Dependent Variable: Mechanical breakdown
RESULT:
P value : 0.790
INTERPRETATION:
The significant level is less than the P value so we accept the null hypothesis. Hence it is
concluded that the mean score of mechanical breakdown is same on car usage.

ANOVA 2
AIM : To find whether the mean score of failure in electrical system is same on car usage.
H0 : The mean score of failure in electrical system is same on car usage.
H1 : The mean score of failure in electrical system is not same on car usage.
ANOVAb
1
Regression 1.959 1 1.959 2.139 .146a
Residual 120.914 132 .916
Total 122.873 133
a. Predictors: (Constant), Car usage
b. Dependent Variable: Failure in electrical system
RESULT:
P value : 0.146
INTERPRETATION:
concluded that the mean score of failure in electrical system is same on car usage.

ANOVA 3
AIM : To find whether the mean score of uncomfortable to self drive is same on car drive.
H0 : The mean score of uncomfortable to self drive is same on car drive.
H1 : The mean score of uncomfortable to self drive is not same on car drive.
ANOVAb
1
Regression 1.630 1 1.630 1.842 .177a
Residual 116.796 132 .885
Total 118.425 133
a. Predictors: (Constant), Drive
b. Dependent Variable: Uncomfortable self drive
RESULT:
P value : 0.177
INTERPRETATION:
concluded that the mean score of uncomfortable to self drive is same on car drive.

ANOVA 4
AIM : To find whether the mean score of uncomfortable seats is same on car drive.
H0 : The mean score of uncomfortable seats is same on car drive.
H1 : The mean score of uncomfortable seats is not same on car drive.
ANOVAb
1
Regression .354 1 .354 .454 .502a
Residual 103.078 132 .781
Total 103.433 133
a. Predictors: (Constant), Drive
b. Dependent Variable: Uncomfortable seat
RESULT:
P value : 0.502
INTERPRETATION:
concluded that the mean score of uncomfortable seats is same on car drive.

REGRESSION 1
AIM : To find whether the model designed with advertisement, newspaper, hoardings, cinema,
internet, window display.
H0 : The mean score of advertisement, newspaper, hoardings, cinema, internet, window
display is equal.
H1 : The mean score of advertisement, newspaper, hoardings, cinema, internet, window
display is unequal.
Model Summaryb
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .174a .030 .023 1.249
Model Summaryb
Model
Change Statistics
R Square Change F Change df1 df2 Sig. F Change
1 .030 4.097 1 132 .045
ANOVAb
1
Regression 7.328 5 1.466 .915 .474a
Residual 205.030 128 1.602
Total 212.358 133
a. Predictors: (Constant), EA window display, EA newspaper, EA internet, EA hoardings, EA
cinema
b. Dependent Variable: Advertisement
Coefficients

Model
Unstandardized Coefficients Standardized Coefficients
t Sig.
B Std. Error Beta
1
(Constant) 2.934 .558 5.257 .000
EA newspaper .021 .141 .017 .152 .879
EA hoardings .039 .185 .028 .210 .834
EA cinema .242 .197 .170 1.229 .221
EA internet -.124 .176 -.082 -.702 .484
EA window display .053 .169 .038 .317 .752
a. Dependent Variable: Advertisement
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 3.14 4.12 3.76 .219 134
Residual -2.877 5.369 .000 1.244 134
Std. Predicted Value -2.842 1.652 .000 1.000 134
Std. Residual -2.303 4.298 .000 .996 134
a. Dependent Variable: Advertisement
RESULT:
The P value 0.474 is greater than 0.05 so we accept null hypothesis. Hence the mean score of
advertisement, newspaper, hoardings, cinema, internet, window display is equal.
INTERPRETATION:
R value is 0.174 which means that fair relationship exist between advertisement, newspaper,
hoardings, cinema, internet and window display.

REGRESSION 2
AIM : To find whether the model designed with status symbol, appearance, color, seating
capacity, comfortable interior, ground clearance.
H0 : The mean score of status symbol, appearance, color, seating capacity, comfortable
interior, ground clearance is equal.
H1 : The mean score of status symbol, appearance, color, seating capacity, comfortable
interior, ground clearance is unequal.
Model Summaryb
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .374a .140 .106 1.012
Model Summaryb
Model
Change Statistics
R Square Change F Change df1 df2 Sig. F Change
1 .140 4.157 5 128 .002
ANOVAb
Model
Sum of
Squares
df
Mean
Square
F Sig.
1
Regression 21.278 5 4.256 4.157 .002a
Residual 131.050 128 1.024
Total 152.328 133
a. Predictors: (Constant), Ground clearance, Appearance, Seating, Colour,
Interior
b. Dependent Variable: Status
Coefficientsa

Model
Unstandardized Coefficients Standardized Coefficients
t Sig.
B Std. Error Beta
1
(Constant) 1.682 .511 3.293 .001
Appearance .458 .158 .390 2.902 .004
Colour -.381 .203 -.289 -1.876 .063
Seating .446 .242 .306 1.847 .067
Interior -.068 .255 -.051 -.266 .790
Ground clearance .090 .155 .078 .583 .561
a. Dependent Variable: Status
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 2.83 4.46 3.73 .400 134
Residual -1.866 1.680 .000 .993 134
Std. Predicted Value -2.265 1.814 .000 1.000 134
Std. Residual -1.844 1.660 .000 .981 134
a. Dependent Variable: Status
RESULT:
The P value 0.002 is less than 0.05 so we reject null hypothesis. Hence the mean score of status
symbol, appearance, color, seating capacity, comfortable interior, ground clearance is unequal.
INTERPRETATION:
R value is 0.374 which means that good relationship exist between status symbol, appearance,
color, seating capacity, comfortable interior, ground clearance.

CLUSTER 1
AIM: To identify the different cluster among the categorical variables appearance, color, seating
capacity, comfortable interior, ground clearance, multiple usage, engine technology, suspension
system, electrical accessories, safety provision are very structure.

INFERENCE: From the above cluster analysis there are two clusters identified, the size of the
smallest cluster is 19(14.2%) and the size of the largest cluster is 115(85.8%). Thus the ratio
between the size of the largest cluster and smallest cluster is 6.05. Hence the categorical
variables appearance, color, seating capacity, comfortable interior, ground clearance, multiple
usage, engine technology, suspension system, electrical accessories, safety provision are very
structure.

CORRELATION 1
AIM: To find whether the model designed with decision and magazines, radio, hoardings,
cinema, internet, window display.
H0: The model designed with decision and magazines, radio, hoardings, cinema, internet,
window display is equal.
H1: The model designed with decision and magazines, radio, hoardings, cinema, internet,
window display is unequal.
Correlations
Decision Magazines Radio Hoardings Tv
Internet
rank
Window
display
Decision
Pearson
Correlation
1 .005 -.084 -.124 .125 .125 .101
Sig. (2-
tailed)
.958 .336 .154 .149 .149 .247
N 134 134 134 134 134 134 134
Magazines
Pearson
Correlation
.005 1 -.193* -.219* -.158 -.158 -.251**
Sig. (2-
tailed)
.958 .025 .011 .069 .069 .003
N 134 134 134 134 134 134 134
Radio
Pearson
Correlation
-.084 -.193* 1 .129
-
.506**
-.506** -.352**
Sig. (2-
tailed)
.336 .025 .136 .000 .000 .000
N 134 134 134 134 134 134 134
Hoardings
Pearson
Correlation
-.124 -.219* .129 1
-
.532**
-.532** -.340**
Sig. (2-
tailed)
.154 .011 .136 .000 .000 .000
N 134 134 134 134 134 134 134

Tv
Pearson
Correlation
.007 -.310** -
.269**
-.238** .212* .212* -.155
Sig. (2-
tailed)
.939 .000 .002 .006 .014 .014 .074
N 134 134 134 134 134 134 134
Internet
rank
Pearson
Correlation
.125 -.158
-
.506**
-.532** 1 1 .294**
Sig. (2-
tailed)
.149 .069 .000 .000 .001
N 134 134 134 134 134 134 134
Window
display
Pearson
Correlation
.101 -.251**
-
.352** -.340** .294** .294** 1
Sig. (2-
tailed)
.247 .003 .000 .000 .001 .001
N 134 134 134 134 134 134 134
* Correlation is significant at the 0.05 level (2-tailed).
RESULT AND INFERENCE:
DECISION AND MAGAZINES, RADIO, HOARDINGS, TV, INTERNET, WINDOW
DISPLAY.
The correlation value between decision and magazines is 0.005 which shows there exist low
relationship between the two factors, the correlation value between decision and radio is -0.084
which shows there exist negative relationship between the two factors, the correlation value
between decision and hoardings is -0.124 which shows there exist negative relationship between
the two factors, the correlation value between decision and tv is 0.125 which shows there exist
low relationship between the two factors, the correlation value between decision and internet is
0.125 which shows there exist low relationship between the two factors, the correlation value
between decision and window display is 0.101 which shows there exist low relationship between
the two factors.
MAGAZINES AND DECISION, RADIO, HOARDINGS, TV, INTERNET, WINDOW
DISPLAY.

The correlation value between magazines and decision is 0.005 which shows there exist low
relationship between the two factors, the correlation value between magazines and radio is -
0.193 which shows there exist negative relationship between the two factors, the correlation
value between magazines and hoardings is -0.219 which shows there exist negative relationship
between the two factors, the correlation value between magazines and tv is -0.158 which shows
there exist negative relationship between the two factors, the correlation value between
magazines and internet is -0.158 which shows there exist negative relationship between the two
factors, the correlation value between magazines and window display is -0.251 which shows
there exist negative relationship between the two factors.
RADIO AND DECISION, MAGAZINES, HOARDINGS, TV, INTERNET, WINDOW
DISPLAY.
The correlation between radio and decision is -0.084 which shows there exist negative
relationship between the two factors, the correlation value between radio and magazines is -
value between radio and hoardings is 0.129 which shows there exist low relationship between the
two factors, the correlation value between radio and tv is -0.506 which shows there exist
negative relationship between the two factors, the correlation value between radio and internet is
-0.506 which shows there exist negative relationship between the two factors, the correlation
value between radio and window display is -0.352 which shows there exist negative relationship
between the two factors.
HOARDINGS AND DECISION, MAGAZINES, RADIO, TV, INTERNET, WINDOW
DISPLAY.
The correlation between hoardings and decision is -0.124 which shows there exist negative
relationship between the two factors, the correlation value between hoardings and magazines is -
value between hoardings and radio is 0.129 which shows there exist low relationship between the
two factors, the correlation value between hoardings and tv is -0.532 which shows there exist
negative relationship between the two factors, the correlation value between hoardings and
internet is -0.532 which shows there exist negative relationship between the two factors, the
correlation value between hoardings and window display is -0.340 which shows there exist
negative relationship between the two factors.
TV AND DECISION, MAGAZINES, RADIO, HOARDINGS, INTERNET, WINDOW
DISPLAY.

The correlation between tv and decision is 0.007 which shows there exist low relationship
between the two factors, the correlation value between tv and magazines is -0.310 which shows
there exist negative relationship between the two factors, the correlation value between tv and
radio is -0.269 which shows there exist negative relationship between the two factors, the
correlation value between tv and hoardings is -0.238 which shows there exist negative
relationship between the two factors, the correlation value between tv and internet is 0.212
which shows there exist low relationship between the two factors, the correlation value between
tv and window display is -0.155 which shows there exist negative relationship between the two
factors.
INTERNET AND DECISION, MAGAZINES, RADIO, HOARDINGS, TV, WINDOW
DISPLAY.
The correlation between internet and decision is 0.125 which shows there exist low relationship
between the two factors, the correlation value between internet and magazines is -0.158 which
shows there exist negative relationship between the two factors, the correlation value between
internet and radio is -0.506 which shows there exist negative relationship between the two
factors, the correlation value between internet and hoardings is -0.532 which shows there exist
negative relationship between the two factors, the correlation value between internet and tv is
between internet and window display is 0.294 which shows there exist low relationship between
the two factors.
WINDOW DISPLAY AND DECISION, MAGAZINES, RADIO, HOARDINGS, TV,
INTERNET.
The correlation value between window display and decision is 0.101 which shows there exist
low relationship between the two factors, the correlation value between window display and
magazines is -0.251 which shows there exist negative relationship between the two factors, the
correlation value between window display and radio is -0.352 which shows there exist negative
relationship between the two factors, the correlation value between window display and
hoardings is -0.340 which shows there exist negative relationship between the two factors, the
correlation value between window display and tv is 0.294 which shows there exist low
relationship between the two factors, the correlation value between window display and internet
is 0.294 which shows there exist low relationship between the two factors.

CORRELATION 2
AIM: To find whether the model designed with comparative analysis and magazines, radio,
hoardings, tv, internet, window display.
H0: The model designed with comparative analysis and magazines, radio, hoardings, tv, internet,
window display is equal.
H1: The model designed with comparative analysis and magazines, radio, hoardings, tv, internet,
window display is unequal.

Correlations
Comparative
analysis
Magazines Radio Hoardings
Comparative
analysis
Pearson
Correlation
1 -.076 -.149 -.294**
Sig. (2-tailed) .385 .086 .001
N 134 134 134 134
Magazines
Pearson
Correlation
-.076 1 -.193* -.219*
Sig. (2-tailed) .385 .025 .011
N 134 134 134 134
Radio
Pearson
Correlation
-.149 -.193* 1 .129
Sig. (2-tailed) .086 .025 .136
N 134 134 134 134
Hoardings
Pearson
Correlation
-.294** -.219* .129 1
Sig. (2-tailed) .001 .011 .136
N 134 134 134 134
Tv
Pearson
Correlation
.132 -.310** -.269** -.238**
Sig. (2-tailed) .128 .000 .002 .006
N 134 134 134 134
Internet rank
Pearson
Correlation
.247** -.158 -.506** -.532**
Sig. (2-tailed) .004 .069 .000 .000
N 134 134 134 134
Window display
Pearson
Correlation
.237** -.251** -.352** -.340**

Sig. (2-tailed) .006 .003 .000 .000
N 134 134 134 134
Correlations
Tv
Internet
rank
Window
display
Comparative
analysis
Pearson
Correlation
.132 .247** .237**
Sig. (2-tailed) .128 .004 .006
N 134 134 134
Magazines
Pearson
Correlation
-.310** -.158 -.251**
Sig. (2-tailed) .000 .069 .003
N 134 134 134
Radio
Pearson
Correlation
-.269** -.506** -.352**
Sig. (2-tailed) .002 .000 .000
N 134 134 134
Hoardings
Pearson
Correlation
-.238** -.532** -.340**
Sig. (2-tailed) .006 .000 .000
N 134 134 134
Tv
Pearson
Correlation
1 .212* -.155
Sig. (2-tailed) .014 .074
N 134 134 134
Internet rank
Pearson
Correlation
.212* 1 .294**
Sig. (2-tailed) .014 .001

N 134 134 134
Window display
Pearson
Correlation
-.155 .294** 1
Sig. (2-tailed) .074 .001
N 134 134 134
RESULT AND INFERENCE:
COMPARATIVE ANALYSIS AND MAGAZINES, RADIO, HOARDINGS, TV,
INTERNET, WINDOW DISPLAY.
The correlation value between comparative analysis and magazines is- 0.076 which shows there
exist negative relationship between the two factors, the correlation value between comparative
analysis and radio is -0.149 which shows there exist negative relationship between the two
factors, the correlation value between comparative analysis and hoardings is -0.294 which shows
comparative analysis and tv is 0.132 which shows there exist low relationship between the two
factors, the correlation value between comparative analysis and internet is 0.247 which shows
there exist low relationship between the two factors, the correlation value between comparative
analysis and window display is 0.237 which shows there exist low relationship between the two
factors.
MAGAZINES AND COMPARATIVE ANALYSIS, RADIO, HOARDINGS, TV,
The correlation value between magazines and comparative analysis is -0.076 which shows there
exist negative relationship between the two factors, the correlation value between magazines and
radio is -0.193 which shows there exist negative relationship between the two factors, the
correlation value between magazines and hoardings is -0.219 which shows there exist negative
relationship between the two factors, the correlation value between magazines and tv is -0.310
between magazines and internet is -0.158 which shows there exist negative relationship between
the two factors, the correlation value between magazines and window display is -0.251 which
shows there exist negative relationship between the two factors.
RADIO AND COMPARATIVE ANALYSIS, MAGAZINES, HOARDINGS, TV,

The correlation between radio and comparative analysis is -0.149 which shows there exist
negative relationship between the two factors, the correlation value between radio and magazines
is -0.193 which shows there exist negative relationship between the two factors, the correlation
value between radio and hoardings is 0.129 which shows there exist low relationship between the
two factors, the correlation value between radio and tv is -0.269 which shows there exist
negative relationship between the two factors, the correlation value between radio and internet is
-0.506 which shows there exist negative relationship between the two factors, the correlation
value between radio and window display is -0.352 which shows there exist negative relationship
HOARDINGS AND COMPARATIVE ANALYSIS, MAGAZINES, RADIO, TV,
The correlation between hoardings and comparative analysis is -0.294 which shows there exist
negative relationship between the two factors, the correlation value between hoardings and
magazines is -0.219 which shows there exist negative relationship between the two factors, the
correlation value between hoardings and radio is 0.129 which shows there exist low relationship
between the two factors, the correlation value between hoardings and tv is -0.238 which shows
hoardings and internet is -0.532 which shows there exist negative relationship between the two
factors, the correlation value between hoardings and window display is -0.340 which shows
there exist negative relationship between the two factors.
TV AND COMPARATIVE ANALYSIS, MAGAZINES, RADIO, HOARDINGS,
The correlation between tv and comparative analysis is 0.132 which shows there exist low
relationship between the two factors, the correlation value between tv and magazines is -0.310
between tv and radio is -0.269 which shows there exist negative relationship between the two
factors, the correlation value between tv and hoardings is -0.238 which shows there exist
negative relationship between the two factors, the correlation value between tv and internet is
between tv and window display is -0.156 which shows there exist negative relationship between
the two factors.
INTERNET AND COMPARATIVE ANALYSIS, MAGAZINES, RADIO, HOARDINGS,
TV, WINDOW DISPLAY.

The correlation between internet and comparative analysis is 0.247 which shows there exist low
relationship between the two factors, the correlation value between internet and magazines is -
value between internet and radio is -0.506 which shows there exist negative relationship between
the two factors, the correlation value between internet and hoardings is -0.532 which shows
there exist negative relationship between the two factors, the correlation value between internet
and tv is 0.212 which shows there exist low relationship between the two factors, the correlation
value between internet and window display is 0.294 which shows there exist low relationship
WINDOW DISPLAY AND COMPARATIVE ANALYSIS, MAGAZINES, RADIO,
HOARDINGS, TV, INTERNET.
The correlation value between window display and comparative analysis is 0.237 which shows
there exist low relationship between the two factors, the correlation value between window
display and magazines is -0.251 which shows there exist negative relationship between the two
factors, the correlation value between window display and radio is -0.352 which shows there
exist negative relationship between the two factors, the correlation value between window
display and hoardings is -0.340 which shows there exist negative relationship between the two
factors, the correlation value between window display and tv is -0.155 which shows there exist
low relationship between the two factors, the correlation value between window display and
internet is 0.294 which shows there exist low relationship between the two factors.

CHAPTER IV
FINDINGS:
Demographic Information
 61.2% of the respondents are of gender male, 38.8% of the respondents are female.
 32.1% of the respondents are in the age group of 26-30 years, 26.9% of the respondents
are 31-35 years, 22.4% of the respondents are 36-40 years, 12.7% of the respondent are
above 41.6% of the respondents are 20-25 years.
 69.4% of the respondents are UG degree holder and 30.6% of the respondents are PG
degree holder.
 53.7% of the respondents are Professionals, 18.7% of the respondents are self employed,
12.7% of the respondents are educationalists, 11.95% of the respondents are managers,
3% of the respondents are service.
 40.3% of the respondents have income of 300001-400000, 34.3% of the respondents
have income of 200001-300000, 12.7% of the respondents have income of 400001-
500000, 8.2% of the respondents have income of 100001-200000, 4.5% of the
respondents have income above 500000 per annum.
 75.4% of the respondents took 0-2 months to decide the brand of the car, 21.6% of the
respondents took 3-5 months and 3% of the respondents took 6-8 months.
 67.9% of the respondents have one earning member in their family, 26.1% of the
respondents have two earning members, 5.2% of the respondents have three earning
members, 0.7% of the respondents have more than three earning members.
 47.8% of the respondents have secondary source of income in Deposit/Investments,
36.6% of the respondents have secondary source of income in trading, 13.4% of the
respondents have secondary source of income in properties, 2.2% of the respondents have
secondary source of income in pension.
 72.4% of the respondents save in bank, 14.9% of the respondents save in land/building,
4.5% of the respondents save in bonds/securities, 3.7% of the respondents save in fixed
deposits, 2.2% of the respondents save in shares, 2.2% of the respondents save in gold.
Pleasant Travel
 97% of the respondents says yes for pleasant travel and 3% of the respondents says no.
 94.8% of the respondents agreed as their first car and 5.2% of the respondents disagreed.
 77.6% of the respondents purchased from local dealer and 22.4% of the respondents
purchased from the dealers of other area.

 95.5% of the respondents agreed that they met the sales personnel before the purchase of
car and 4.5% of the respondents disagreed.
 85.1% of the respondents bought from family savings and 14.9% of the respondents
bought from borrowings.
 64.2% of the respondents repaid the amount monthly, 17.2% of the respondents repaid
onetime, 8.2% of the respondents repaid quarterly, 6% of the respondents repaid yearly,
4.5% of the respondents repaid half-yearly.
Role of family members
 82.8% of the respondents agreed that they themselves are decider, 14.2% of the
respondents are initiator, 3% of the respondents are influencer.
 61.2% of the respondents agreed that grandparents are influencer, 36.6% of the
respondents are initiator, 2.2% of the respondents are decider.
 50% of the respondents agreed that father is the influencer, 39.6% of the respondents are
initiator, 10.4% of the respondents are decider.
 59.7% of the respondents agreed that Mother is the influencer, 38.8% of the respondents
are initiator, 1.5% of the respondents are decider.
 50% of the respondents agreed that Son is the influencer, 46.3% of the respondents are
initiator, 3.7% of the respondents are decider.
 55.2% of the respondents agreed that Daughter is the initiator, 44% of the respondents are
influencer, 0.7% of the respondents are decider.
Test drive
 74.6% of the respondents says test drive as experience of purchasing new car, 17.9% of
the respondents says friends/relatives, 6.7% of the respondents says taxi, 0.7% of the
respondents says others.
Advertisement Exposure
 90.3% of the respondents had advertisement exposure and 9.7% of the respondents does
not have advertisement exposure.
 76.9% of the respondents agreed that they had sufficient information to decide the brand
and 23.1% of the respondents disagreed.
Car Usage
 77.6% of the respondents says that the car usage was daily and 16.4% of the respondents
says once in two days, 3% of the respondents says occasionally and 2.2% of the
respondents says once in a fortnight, 0.7% of the respondents says very rarely.
 85.1% of the respondents prefer self driving and 10.4% of the respondents prefer paid
driver, 4.5% of the respondents prefer family member.

Source of Information
 Most of the respondents with the gender of both male and female agreed very much
useful towards the statement of advertisement.
 Most of the respondents with the gender of both male and female agreed useful to some
extent towards the statement of mechanic.
 Most of the respondents with the gender of male agreed very much useful towards the
statement of sales personnel, the respondents with the gender of female agreed useful to
some extent towards the statement of sales personnel.
 Most of the respondents with the gender of male agreed very much useful towards the
statement of test drive, the respondents with the gender of female agreed useful to some
extent towards the statement of test drive.
 Most of the respondents with the age of 20-25 years, 26-30 years, 31-35 years, 36-40
years, above 41 years agreed very much useful towards the statement of users of the
brand.
 Most of the respondents with the age of 20-25 years, 26-30 years, 31-35 years, above 41
years agreed very much useful towards the statement of members of family/relatives, the
respondents in the age of 36-40 years agreed useful to some extent towards the statement
of members of family/relatives.
years agreed useful to some extent towards the statement of friends/colleagues, the
respondents in the age of above 41years agreed very much useful towards the statement
of friends/colleagues.
years, above 41 years agreed useful to some extent towards the statement of internet.
Factors deciding the brand of car
 Most of the respondents in all income levels agreed more important towards the
statement of price factor.
 Most of the respondents in all income levels agreed more important towards the
statement of maintenance cost.
 Most of the respondents above 500000 income agreed most important towards the
statement of resale value, 100001-200000, 200001-300000, 300001-400000, 400001-
500000 agreed more important towards the statement of resale value.

 Most of the respondents above 500000 income agreed most important towards the
statement of fuel efficiency, 100001-200000, 200001-300000, 300001-400000, 400001-
500000 agreed more important towards the statement of fuel efficiency.
 Most of the respondents of self employed, managers, educationalists, professionals
agreed more important towards the statement of appearance, the respondents of service
agreed important towards the statement of appearance.
 Most of the respondents of self employed, managers, professionals agreed more
important towards the statement of color, the respondents of educationalists, service
agreed important towards the statement of color.
 Most of the respondents of self employed, managers, educationalists, professionals,
service agreed more important towards the statement of seating capacity.
important towards the statement of comfortable interior, the respondents of
educationalists, service agreed important towards the statement of comfortable interior.
important towards the statement of ground clearance, the respondents of educationalists,
service agreed important towards the statement of ground clearance.
 Most of the respondents of self employed, managers, educationalists, professionals
agreed more important towards the statement of multiple usage, the respondents of
service agreed important towards the statement of multiple usage.
 Most of the respondents with education of UG and PG agreed more important towards
the statement of engine technology.
the statement of suspension system.
the statement of safety provision.
the statement of braking system.
the statement of gear system.
the statement of electrical accessories.
 Most of the respondents with the gender of both male and female agreed more important
towards the statement of status symbol.

towards the statement of social recognition.
towards the statement of sense of achievement.
Advertising media
years, above 41 years agreed often towards the statement of newspaper/magazines.
 Most of the respondents with the age of 20-25 years, 26-30 years, 36-40 years agreed
often towards the statement of radio, the respondents with the age of 31-35 years, above
41years agreed sometimes towards the statement of radio.
 Most of the respondents with the age of 20-25 years , 26-30 years agreed often towards
the statement of hoardings, the respondents with the age of 31-35 years, 36-40 years,
above 41 years agreed sometimes towards the statement of hoardings.
 Most of the respondents with the gender of male agreed often towards the statement of
cinema, the respondents with the gender of female agreed sometimes towards the
statement of cinema.
internet, the respondents with the gender of female agreed sometimes towards the
statement of internet.
window display, the respondents with the gender of female agreed sometimes towards the
statement of window display.
Frequency of discomforts
 Most of the respondents of occupation service agreed sometimes towards the statement of
mechanical breakdown, the respondents of self employed, managers, educationalists,
professionals neither agreed nor disagreed towards the statement of mechanical
breakdown.
 Most of the respondents of occupation self employed, managers, educationalists, service,
professionals neither agreed nor disagreed towards the statement of failures in electrical
system.
 Most of the respondents of occupation self employed, managers agreed sometimes
towards the statement of uncomfortable to self drive, the respondents of educationalists,
service, professionals neither agreed nor disagreed towards the statement of
uncomfortable to self drive.

 Most of the respondents of occupation self employed, managers, professionals agreed
sometimes towards the statement of uncomfortable seats, the respondents of
educationalists, service neither agreed nor disagreed towards the statement of
uncomfortable seats.
 Most of the respondents of occupation service agreed often towards the statement of hard
in rough roads, the respondents of self employed agreed sometimes towards the statement
of hard in rough roads, the respondents of managers, educationalists, professionals
neither agreed nor disagreed towards the statement of hard in rough roads.
 Most of the respondents of occupation service agreed often towards the statement of less
luggage space, the respondents of self employed, professionals agreed sometimes towards
the statement of less luggage space, the respondents of managers, educationalists neither
agreed nor disagreed towards the statement of less luggage space.

SUGGESTIONS:
 To fulfill the customer requirement the company can concentrate on the
appearance, ground clearance and interior to improve and to provide a better use
of technology.
 If possible, the company can focus on improvised new technology adaptation for
upgrading the suspension system for a smoother travel on rough roads in the city.
 If the company focus in car design structure by providing a flexible interior space
where multiple usage can be enjoyed by the customer, since the expectation
towards the brand Nissan is high.
CONCLUSION:
From the study on mode of purchasing car: a review on brand equity and experience with respect
to Lakshmi Nissan, it is concluded that the customer satisfaction is the important factor, which
affects the financial position and goodwill of the company. Customer demands are dynamic, but
its consideration is necessary for every company to make existence into the market. This project
concludes that the Lakshmi Nissan should provide lowest price of cars for the sake of increasing
sales and increasing Nissan motor market. The study conducted in Lakshmi Nissan helped me to
acquire lot of knowledge and also I personally realize the real difference that exists in theoretical
and practical situation.

Mode of purchasing car

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