INDIAN CONSUMER PERCEPTIONS AND BEHAVIOUR: A STUDY WITH SPECIAL REFERENCE TO CAR

PURCHASE

Harihar Panigrahi Roll No. U211029

In this assignment, attempt has been made by the researcher to bring out Indian Consumer Perception and Behaviour with special reference to purchase of Cars. Regression Analysis (Bi-variate & Multi-variate) has been done to understand effect of various variable, followed by Factor and Cluster Analysis.

ExPGP 2011-2014Xavier Institute of Management, Bhubaneswar

Table of ContentsAbstract -------------------------------------------------------------------------------------- 2Introduction -------------------------------------------------------------------------------------- 2-3

Overview of Automobile Industry ------------------------------------------------------------------- 3-5

Passenger cars Industry in India ------------------------------------------------------------------- 5-9

Statement of Problem ------------------------------------------------------------------ 9

Literature Review ------------------------------------------------------------------ 9 – 10

Objective of the Study ------------------------------------------------------------------ 10

Scope of Study, Methodology & Sampling Design ---------------------------------------------- 11

Data Requirement and Source of Data ------------------------------------- 11 – 12

Analysis and Interpretation of Data Demographic Profile -------------------------------------------- 13 - 14Behavioural Attribute -------------------------------------------- 14 - 15

Bi-variate Analysis ----------------------------------------------------------------- 15 – 22

Multivariate AnalysisAdditive Model & Interpretation -------------------------------------------- 23 – 25Multiplicative Model & Interpretation -------------------------------------------- 25 – 28

Factor AnalysisCo-relation Matrix -------------------------------------------- 29 – 31KMO and Bartlett’s Test -------------------------------------------- 32Communalities -------------------------------------------- 32 – 33Total Variance -------------------------------------------- 34Scree Plot -------------------------------------------- 35Rotated Component Matrix -------------------------------------------- 36Grouping of Variables after Factorisation -------------------------------------------- 36 - 38

Cluster AnalysisDendrogram -------------------------------------------- 39 - 41Descriptive Statistics & Interpretation -------------------------------------------- 41 - 47

Suggestions -------------------------------------------- 47 - 48

Conclusion -------------------------------------------- 48 - 49

References -------------------------------------------- 49

Annexure-A (Survey Questionnaire) -------------------------------------------- 50 - 57

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Abstract In recent days India is witnessing a change in consumerism. The market is now predominantly consumer

driver. The focus is shifting for product based marketing to need based marketing. Consumer is given many

options to decide. Passenger car segment is no exception to this general trend. An effective market

communication is imperative for reaching the target audience. So it is important that we study the consumer

perceptions and behaviour of the car owners which will give us feedback on how marketing strategies can be

worked. A Simple Random sampling technique was adopted in the study to select the sample respondents. As

the size of the universe is restricted, the study has been conducted on the respondents who are the owners of

all the segments of passenger cars. A total of 100 surveys were prepared and out of this, only 71 surveyers

responded. Data were collected through an online survey process with help of “Qualitrics.com” regarding

perception of the respondents on the buying behaviours of cars. The following tools were used in testing the

hypotheses and in the analysis of the data. Descriptive statistical tools such as Percentage, Mean, Median and

Standard deviation have been used to describe the profiles of consumers, preferred product attributes and

level of satisfaction. Annova test has been used to test the association between the consumer demographic

characteristics and preferred product attributes and satisfaction. Multiple regression analysis has been used to

study the influence of income, interest rate and inflation rate. Factor analysis is employed to identify the key

factors responsible for the consumers’ purchase of cars and level of satisfaction after purchase. Cluster

analysis has been used to identify the consumers with similar tastes and preferences with respect to purchase

of car.

Introduction

Human beings, in general, are complex creatures who often do not seem even to know their own minds. It is

seldom easy, and sometimes impossible, to generalize about human behaviour. Each individual is a unique

product of heredity, environment and experience. Predicting such a strange behaviour of people is a difficult

and complicated task, filled with uncertainties, risks, and surprises. Accurate predictions can yield vast

fortunes and inaccurate predictions can result in the loss of millions of rupees. Today, business around the

world recognizes that „the consumer is the king‟. Knowing why and how people consume products helps

marketers to understand how to improve existing products, what types of products are needed in the market

place, or how to attract consumers to buy their products. The era of liberalization, privatization and

globalization has brought changes in society and lifestyle of people.

Today the success of any firm depends upon the satisfaction of consumers. For satisfying the consumers the

firm should know about the behaviour of the consumers. In these circumstances understanding consumer is a

very difficult task because of the changing technology, innovation, and changes in life style.

Marketers can justify their existence only when they are able to understand consumers? wants and satisfy

them. The modern marketing concept for successful management of a firm requires marketers to consider the

consumer as the focal point of their business activity. Although it is important for the firm to understand the

buyer and accordingly evolve its marketing strategy, the buyer or consumer continues to be an enigma -

sometimes responding the way the marketer wants and on other occasions just refusing to buy the product

from the same marketer. For this reason, the buyer's mind has been termed as a black box, which should be

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opened by the seller to be a successful marketer. Proportion of Vehicles Registered in India, Germany, Japan

and USA

Marketers can justify their existence only when they are able to understand consumers‟ wants and satisfy

them. The modern marketing concept for successful management of a firm requires marketers to consider the

consumer as the focal point of their business activity. Although it is important for the firm to understand the

buyer and accordingly evolve its marketing strategy, the buyer or consumer continues to be an enigma -

sometimes responding the way the marketer wants and on other occasions just refusing to buy the product

from the same marketer. For this reason, the buyer’s mind has been termed as a black box, which should be

opened by the seller to be a successful marketer. The study of consumer behaviour also includes an analysis

of factors that influence purchase decisions and product use. Understanding how consumers make purchase

decisions can help marketing managers in several ways. For example, if a manager knows through research

that fuel mileage is the most important attribute for a certain target market, the manufacturer can redesign the

product to meet that criterion. If the firm cannot change the design in the short run, it can use promotion in an

effort to change consumers‟ decision making criteria. For example, an automobile manufacturer can advertise

a car’s maintenance-free features while downplaying fuel mileage.

Overview of the Automobile Industry

Industry performance in 2011-12

Production

The cumulative production data for April-March 2012 shows production growth of 13.83 percent over same

period last year. In March 2012 as compared to March 2011, production grew at a single digit rate of 6.83

percent. In 2011-12, the industry produced 20,366,432 vehicles of which share of two wheelers, passenger

vehicles, three wheelers and commercial vehicles were 76 percent, 15 percent, 4 percent and 4 percent

respectively.

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Domestic Sales

The growth rate for overall domestic sales for 2011-12 was 12.24 percent amounting to 17,376,624 vehicles.

In the month of only March 2012, domestic sales grew at a rate of 10.11 percent as compared to March 2011.

Passenger Vehicles segment grew at 4.66 percent during April-March 2012 over same period last year.

Passenger Cars grew by 2.19 percent, Utility Vehicles grew by 16.47 percent and Vans by 10.01 percent

during this period. In March 2012, domestic sales of Passenger Cars grew by 19.66 percent over the same

month last year. Also, sales growth of total passenger vehicle in the month of March 2012 was at 20.59

percent (as compared to March 2011).

The overall Commercial Vehicles segment registered growth of 18.20 percent during April-March 2012 as

compared to the same period last year. While Medium & Heavy Commercial Vehicles (M&HCVs) registered a

growth of 7.94 percent, Light Commercial Vehicles grew at 27.36 percent. In only March 2012, commercial

vehicle sales registered a growth of 14.82 percent over March 2011.

Three Wheelers sales recorded a decline of (-) 2.43 percent in April-March 2012 over same period last year.

While Goods Carriers grew by 6.31 percent during April-March 2012, Passenger Carriers registered decline by

(-) 4.50 percent. In March 2012, total Three Wheelers sales declined by (-) 9.11 percent over March 2011.

Total Two Wheelers sales registered a growth of 14.16 percent during April-March 2012. Mopeds, Motorcycles

and Scooters grew by 11.39 percent, 12.01 percent and 24.55 percent respectively. If we compare sales

figures of March 2012 to March 2011, the growth for two wheelers was 8.27 percent.

Exports

During April-March 2012, the industry exported 2,910,055 automobiles registering a growth of 25.44 percent.

Passenger Vehicles registered growth at 14.18 percent in this period. Commercial Vehicles, Three Wheelers

and Two Wheelers segments recorded growth of 25.15 percent, 34.41 percent and 27.13 percent respectively

during April-March 2012. For the first time in history car exports crossed half a million in a financial year.

In March 2012 compared to March 2011, overall automobile exports registered a growth of 17.81 percent.

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Passenger Car Industry in India

SUMMARY

With expected sales of ~2.5 million passenger vehicles in FY11e, India’s passenger vehicle market ranks

as world’s seventh largest; larger than markets like United Kingdom, France and Spain by volume.

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India has been one of the few markets globally to buck the recessionary trend and record a strong 25.6%

volume growth in FY10. The growth momentum continues to be on track with first eleven months of FY11

registering a growth of 29.8% over the corresponding period in the previous year.

Strong economic growth, rising disposable income levels, favourable demographics, easy financing

environment and relatively low car penetration have been the prominent growth drivers for the industry.

While at the one end, the growing domestic market is attracting foreign OEMs, on the other, established

players are positioning themselves as strong contenders to offer low-cost car manufacturing capabilities to

the world.

So far, most foreign car makers, barring Hyundai have focused on the sedan and premium segment cars,

shying away from the highly competitive small-car segment; with these players now launching small-cars

that too designed keeping in mind specifically the Indian consumer, the small-car segment, which has so

far been dominated by three players commanding over 80% of the volumes is likely to see increase in

competitive intensity.

Some of the newly launched models have had good initial response and have been aggressively priced,

indicating new entrants’ strategy to grab market share while sacrificing profitability.

Large established incumbents in the Indian passenger vehicle market derive strength from their low-cost

manufacturing capabilities (especially in the small-car segment), strong brand recognition and wide

distribution & servicing reach, something which can be difficult to replicate.

We believe, while the incumbents will have these competitive advantage over newer entrants, these are

likely to diminish in the long-run as new players with global experience gain brand recognition and expand

their network and product offerings.

Superior small-car portfolio, a wide distribution and service network and competitive pricing on the back of

locally sourced auto components are going to be the key factors in determining the success of a foreign

OEM in the Indian market.

While competitive pressures are likely to intensify, we believe that strong GDP growth, rising disposable

income levels, easy availability of finance and more particularly Indian consumers’ aspiration to own cars,

especially given the state of public transport, would ensure that the industry will experience strong growth

in the foreseeable future.

We estimate the Indian passenger vehicle industry will reach ~4.85 million in annual sales by FY16,

representing a growth of 10.8% CAGR over the next five years.

Notwithstanding the strong long-term outlook, the industry faces certain near term challenges inform of

rising commodity prices, interest rates, tightening liquidity scenario and increased competitive intensity.

We believe that rising labour costs is also likely to see cost increases across the supplier network, though

it is likely to be mitigated by greater scale economies and higher degree of automation.

Within the lower priced segment (mini/compact), the price band is widening, with higher priced but better

value products achieving higher volumes than some of the lower priced models. The price range may

widen further depending on the success of the ‘Nano’ segment.

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Strong growth drivers augur favourable prospects for the Indian passenger vehicle market

The domestic passenger vehicles industry has been on a relatively steady growth phase over most of the last

decade and has registered a 10 years CAGR of 10.3% during the period. It has been one of the few markets

worldwide which saw growing passenger car sales during the liquidity crisis and recessionary phase witnessed

during FY09. Buoyant economic growth, rising disposable income levels, favourable demographics, strong

growth from tier II/III cities and rural India, together with improving availability of vehicle financing at

competitive interest rates have been the key factors fuelling growth in the Indian passenger vehicle market.

Among the emerging markets, India continues to have one the lowest car density, estimated at 13 cars per

1,000 people compared to other markets such as China (45), Brazil (160), and Indonesia (42). The growth has

also been supported by OEM led initiatives like whole host of new model offerings from both from existing

companies as well as new entrants in the market.

Furthermore, in India, the car prices have remained relatively flat over the years (adjusted for the decline in

duties) compared to steadily rising per capita income levels.

In addition to the strong domestic demand, the OEMs have also been positioning themselves as competitive

small-car makers, benefitting from India’s technological capabilities in the manufacturing small-cars, scale

economies and a well-established component supplier base. Over the past 10 years, export of vehicles have

grown at a CAGR of 31.7% to achieve volumes of 0.45 million units in FY10. ICRA expects overall growth

momentum to be sustained driven by strong domestic demand and increased thrust on exports.

The Indian Automobile Industry has got a tremendous market potential. With the growth of population and

change in their pattern of life style as a result of urbanization, there has been a rapid increase in demand for

Indian automobiles. The purpose of this chapter is to survey the growth of Automobile Industry in India and

their role in economic development and to bring out the profile of the study area. The entire discussion has

been divided into three main sections. The first section traces the growth of Automobile Industry. The second

section discusses origin, growth and other aspects of Passenger Car Industry. The third section gives a brief

profile of the study area.

The Indian Automobile Industry has flourished like never before in the recent years. This extraordinary growth

that the Indian automobile industry has witnessed is a result of a major factor namely, the improvement in the

living standard of the middle class and an increase in their disposable incomes. Moreover, the liberalization

steps, such as, relaxation of the foreign exchange and equity regulations, reduction of tariffs on imports, and

refining the banking policies initiated by the Government of India, have played an equally important role in

bringing the Indian Automobile Industry to great heights. The increased demand for Indian automobiles has

resulted in a large number of multinational auto companies, especially from Japan, the U.S.A., and Europe,

entering the Indian market and working in collaboration with the Indian firms. Also, the institutionalization of

automobile finance has further paved the way to sustain a long term high growth for the industry. The Future

Growth Drivers like higher GDP Growth, India’s huge geographic spread – mass transport system, increasing

road development, increasing disposable income with the service sector, cheaper (declining interest rates) and

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easier finance schemes, replacement of aging four wheelers, graduating from two wheelers to four wheelers,

increasing dispensable income of rural agricultural sector, growing concept of second vehicle in urban areas.

India produced about eight million two-wheelers, three million passenger cars and utility vehicles in 2009 -

2010. It ranks second in the world in the production of the two-wheelers and thirteenth in the production of the

passenger cars.

Automobile Industry – A Global Hub

15 manufacturers of passenger cars and multi-utility vehicles,

9 manufacturers of commercial vehicles,

16 manufacturers two/ three wheelers,

14 manufacturers tractors,

5 manufacturers of engines.

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Market Share of Car Manufacturer’s in India in 2012

Statement of the Problem

Due to the emergence of globalization and liberalization there is a stiff competition among the variety of car

industries which are focusing attention in capturing the Indian markets. Cars though considered as luxury

once, now occupies a part of day-to-day life and has become a necessity. People who were not ready to

spend their money on luxuries have now changed their attitude that „yesterday‟s luxuries are today‟s

necessities.‟ To be a successful marketer it is absolutely essential to read the minds and perceptions of the

prospective buyers of cars. In addition to the above, the due weightage which is given by the Government for

the growth of passenger car industry and the involvement of the consumers in the selection of a particular

brand of car have also made the researcher to undertake a study on the passenger car industry with special

reference to the perceptions, behaviour and satisfaction of owners of cars.

Review of Literature

Mandeep Kaur and Sandhu (2006) attempted to find out the important features which a customer considers

while going for the purchase of a new car. The study covers the owners of passenger cars living in the major

cities of the State of Punjab and the Union Territory of Chandigarh. The respondents perceive that safety and

comfort are the most important features of the passenger car followed by luxuriousness. So the manufacturers

must design the product giving maximum weightage to these factors.

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Chidambaram and Alfread (2007) postulates that there are certain factors which influence the brand

preferences of the customers. Within this framework, the study reveals that customers give more importance

to fuel efficiency than other factors. They believe that the brand name tells them something about product

quality, utility, technology and they prefer to purchase the passenger cars which offer high fuel efficiency, good

quality, technology, durability and reasonable price.

Satya Sundaram (2008) analyzed how the competition makes the automobile manufacturer to launch at least

one new model or a variant of the model every year. This survey also pointed out that diesel cars are

becoming popular in India and the announcement of reductions in excise duties by the government has helped

to some extent to boost the demand.

Clement Sudhakar and Venkatapathy (2009) studied the influence of peer group in the purchase of car with

reference to Coimbatore District. It was also found that the influence of friends is higher for the purchase of

small sized and mid sized cars.

Dr. S Subadra, Dr. K M Murugesan and Dr. R Ganapathi (2010) studied the behaviour of consumers, their

importance in the aspects of life style, perception of product attributes and level of satisfaction in the purchase

of car with reference to Namakkal District in Tamilnadu. It was also found that the influence of driving comfort

and fuel economy are the most important features of the passenger car followed by availability of spare parts

and price of the car.

Brown et al (2010) analyzed the consumers‟ attitude towards European, Japanese and the US cars. The

country – of – origin plays a significant role in the consumers‟ behaviour. The brand name, lower price and

distributor’s reputation completely have a significant impact on the sale of passengers‟ car.

However, the present study differs from the above, in that, the buyer behaviour in entire India is sought to be

analyzed here. The scope and the area of the study are unique in nature.

Objectives of the Study

The purpose of this research is to study the behaviour of consumers, their importance in the aspects of life style, perception of product attributes and level of satisfaction. Hence, the study is aimed at the following objectives.

1. To introduce samples for further analysis.

2. To identify the variables which effect domestic sale of cars in India through multivariate regression

analysis and establish relations.

3. To identify the various socio-economic factors that influences the purchasing pattern of respondents.

4. To understand the causes for purchasing car.

5. To evaluate car owners perception and behaviour pertaining to the purchase and use of cars.

6. To identify and analyze the factors influencing the purchase of cars and

7. To make suggestions in the light of the findings of the study.

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Scope of the Study

Now a days, car has become a necessity and forms a part of life. Therefore, there is a significant scope to

examine the perception and purchase behaviour of the consumers of cars. The study is restricted to educated

segments who are mostly in service spread across India mostly in Southern part of India.

Methodology

Before beginning to carry out the present study, the researchers initially conducted a pilot study in order to find

out the feasibility and the relevance of the study. The present study is based on the perceptions, behaviour

and satisfaction of the consumers for passenger cars. Sources of the primary and the secondary data are

discussed. The researcher has used online survey technique for the purpose of collecting primary data. It took

almost 4 weeks for the researcher to complete the process of collection. As the universe of the study is large,

the researcher has decided to select sample respondents by adopting the Simple Random Sampling

Technique. The secondary data have been collected from the companies‟ bulletins, annual reports and

websites. Further, the researchers has used national and international journals in the field of management, as

well as marketing, business magazines, business dailies, referred text books in marketing management as

well as consumer behaviour and academic studies conducted in the related areas for the purpose of building a

strong conceptual background including the review of literature for the study.

Sampling Design

This study was conducted among the car owners residing most parts of South India baring few from other

parts of India. A Simple Random sampling technique was adopted in the study to select the sample

respondents. As the size of the universe is restricted, the study has been conducted on the respondents who

are the owners of all the segments of passenger cars. A total of 100 surveys were prepared and out of this,

only 71 surveyers responded. Data were collected through an online survey process with help of

“Qualtrics.com” regarding perception of the respondents on the buying behaviours of cars. The following tools

were used in testing the hypotheses and in the analysis of the data. Descriptive statistical tools such as

Percentage, Mean, Median and Standard deviation have been used to describe the profiles of consumers,

preferred product attributes and level of satisfaction. Annova test has been used to test the association

between the consumer demographic characteristics and preferred product attributes and satisfaction. Multiple

regression analysis has been used to study the influence of income, interest rate and inflation rate. Factor

analysis is employed to identify the key factors responsible for the consumers’ purchase of cars and level of

satisfaction after purchase. Cluster analysis has been used to identify the consumers with similar tastes and

preferences with respect to purchase of car.

Data Requirement and Source of Data

The project assignment covers mainly 3 areas i.e.

Part-A : Regression Analysis – Bi-variate and Multivariate

Part-B : Factor and Cluster Analysis.

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For the part A of the assignment, the researcher had taken the relevant time series data from the following

source.

1) Society of Indian Automobile Manufacturer’s Association (SIAM)

2) India Stat Data Base

3) CMIE Data Base

Following Table shows Car Sales and it’s determinants.

Year Domestic Car Sales (x 1000)

Per Capita Net Income in Rs. (x 1000)

Inflation Rate

Interest Rate

Log_Domestic_Car_Sale

Log_Per_Capita_Income

Log_Inflation_Rate

Log_Interest_Rate

1989-90 233.388 6.93 9.94 16.5 2.37 0.84 1.00 1.221990-91 240.44 7.86 1.13 16.5 2.38 0.90 0.05 1.221991-92 251.879 12.18 12.29 16.5 2.40 1.09 1.09 1.221992-93 253.407 10.93 19.9 16.5 2.40 1.04 1.30 1.221993-94 257.648 10.35 12.45 19 2.41 1.02 1.10 1.281994-95 365.918 9.76 4.8 19 2.56 0.99 0.68 1.281995-96 518.762 11.34 4.58 15 2.71 1.05 0.66 1.181996-97 666.144 13.65 7.96 16.5 2.82 1.14 0.90 1.221997-98 755.229 16.19 12.3 14.5 2.88 1.21 1.09 1.161998-99 672.69 17.82 2.92 14 2.83 1.25 0.47 1.151999-00 648.458 18.31 12.77 13 2.81 1.26 1.11 1.112000-01 907.384 20.52 3.77 12 2.96 1.31 0.58 1.082001-02 827.863 21.96 3.03 11.5 2.92 1.34 0.48 1.062002-03 825.08 21.85 3.53 11.5 2.92 1.34 0.55 1.062003-04 903.713 20.42 1.7 10.75 2.96 1.31 0.23 1.032004-05 1211.979 23.19 1.12 10.25 3.08 1.37 0.05 1.012005-06 1469.866 28.55 2.76 10.25 3.17 1.46 0.44 1.012006-07 1617.423 33.75 2.69 10.25 3.21 1.53 0.43 1.012007-08 2017.622 38.25 10.48 12.25 3.30 1.58 1.02 1.092008-09 2047.668 40.61 9.1 14.5 3.31 1.61 0.96 1.162009-10 2483.605 46.49 1.78 13 3.40 1.67 0.25 1.112010-11 2788.665 54.84 9.56 11.75 3.45 1.74 0.98 1.07

For the part-B of the assignment a Survey questionnaire covering various aspects of consumer behaviour for

the car purchase has been framed out by the researcher including demographic profile.

An online survey managed by “Qualtrics.com” covering the questionnaire was sent out to various respondents

known to the researcher in all parts of Country and almost 2 weeks was given to the respondents to answer

the questions. There after response as received from the respondents were exported in the form of excel file

for further analysis with help of SPSS. (For details of the questionnaire, refer annexure-A at the end).

Following link can be referred for the online survey questionnaire done through Qualtrics.com.

https://qasiatrial.asia.qualtrics.com/SE/?SID=SV_bazduwbr8rwF6xn

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Analysis and Interpretation of Data

The results of the analysis of the collected data are presented below:

Demographic Profile :

Interpretation (Demographic Profile):

1. Maximum population (approx. 70%) of respondents are from South India followed by East. Hence, the

consumer buying behaviour will represent the South Indian behaviour to a large extent.

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2. There is almost a homogeneous distribution of income of the respondents across all slabs excepting less

than Rs. 5 Lakhs. This indicates that most of the respondents are either in middle class or higher middle

class and their affordability for the car is good.

3. The age, occupation and nature of job distribution indicate that most of the respondents are in middle age

and their occupation is service in private organisations. To a great extent it can be inferred that being in

service with private organisations, the salary might be good.

4. More than 50% of respondents are having post graduate and PhD degrees and this indicate that the

education and knowledge level of respondents is very high.

Behavioural Attribute :

Sl. No.

Factor Mean Standard Deviation

Median Rank

1 Mileage / Fuel Economy 1.254 0.47 1 1

2 Availability of Service Station Near 1.380 0.57 1 2

3 Comparison of cars before buying 1.380 0.57 1 3

4 Air Conditioning System 1.408 0.495 1 4

5 Easy Availability of Spare Parts 1.423 0.525 1 5

6 Technology 1.479 0.557 1 6

7 Power and Pick Up 1.521 0.557 1 7

8 Driving Comfort 1.549 0.529 2 8

9 Family Needs 1.549 0.580 2 9

10 Road Grip 1.62 0.618 2 10

11 Child Lock 1.662 0.736 2 11

12 Price 1.676 0.789 2 12

13 Based on Type of Fuel i.e. / Diesel / Petrol / Electric 1.704 0.684 2 13

14 Colour of the Car 1.704 0.684 2 14

15 Brand Name of the car 1.831 0.697 2 15

16 Free Pickup & Drop during Service 1.845 0.951 2 16

17 Good Audio/Video System 1.873 0.735 2 17

18 Advice from Friends / Colleagues 1.887 0.662 2 18

19 Anti Brake Skidding 1.930 0.834 2 19

20 Advice from Family Members 1.944 0.504 2 20

21 Air Bags 1.958 0.933 2 21

22 Car Accessories 1.972 0.845 2 22

23 Resale Value 1.986 0.933 2 23

24 Insurance Facility 2.042 1.034 2 24

25 Extended Warranty 2.099 1.030 2 25

26 Environmental / Pollution norms and regulations 2.127 0.940 2 26

27 Instalment Payment Facility 2.225 0.974 2 27

28 Fog Light 2.324 1.039 2 28

29 Rear View Camera and Reverse Gear Sensor 2.352 0.927 2 29

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30 In Built Navigation System 2.366 0.815 2 30

31 Location Of The Car Dealer Shop 2.408 1.103 2 31

32 Status Symbol 2.423 0.921 2 32

33 Sleek Gear Shift Knob 2.451 0.891 2 33

34 Advertisements And Promotions 2.577 0.822 3 34

35 Buying during Festival Season / Promotional Offers 2.620 1.019 3 35

36 Mobile Charger 2.648 1.232 3 36

37 Chrome Plated Door Handles 2.746 1.130 3 37

38 Availability Of Variety Of Cars Under One Roof 2.803 1.203 3 38

39 Soft Drinks Holder 2.958 1.006 3 39

Interpretation (Behavioural Attribute) :

Most of the respondents have rated “Mileage / Fuel Economy‟ as having strong influence on purchase

decision of the car. This is simple due to the fact that all the respondents are in private service where their

salary comes to their account after deduction of income tax unlike other service. Since fuel expenses is a

recurring expenses all the respondents need to have less cash outflow when buying fuel which is indicative of

fuel economy. This is in expected lines.

In the next category of strong to moderate influence are (1) Availability of Service Station (2) Comparison of

cars before Buying (3) Air Conditioning system (4) Availability of spare parts (5) Technology (6) Power and

Pick Up (7) Driving Comfort (8) Family Needs (9) Road Grip (10) Price. This is based on the obtained mean

values varying between 1.38 – 1.67.

The rest of the factors moderately influenced the respondents in their purchase decision.

Part-A : Regression Analysis

Bi-Variate Analysis:

Bi-variate analysis is one of the simplest forms of the quantitative (statistical) analysis. It involves the analysis

of two variables (often denoted as X, Y), for the purpose of determining the empirical relationship between

them. In order to see if the variables are related to one another, it is common to measure how those two

variables simultaneously change together. Bi-variate analysis can be helpful in testing simple hypothesis of

association and causality – checking to what extent it becomes easier to know and predict a value for the

dependent variable if we know a case's value on the independent variable.

We want to explain variation of domestic sales of car in India with respect to independent variable which in our

case is net per capita availability of income.

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A Priori Reasoning: With constant increase in Indian GDP year on year and with effect of globalisation

effect, the net per capita income / disposable income at the hands of every Indian is increasing. Further with

advent of MNCs in Indian market, the job prospect as well as better salary makes the pay cheques thicker and

thicker.

As a result, a rational human being would prefer to spend his disposable income in buying expensive products

like cars, electronic goods etc. This is more likely to push demand of car sales.

In the Bi-variate analysis, we will consider Domestic sale of cars as dependent variable and per capita net

availability of income (PCNI) is independent variable.

Bi-Variate Data Set

Year Domestic Car Sales (x 1000)

Per Capita Net Income in Rs. (x 1000)

Log_Domestic_Car_Sale

Log_Per_Capita_Income

Per Capita

Net Income 2

in Rs. (x 1000)

1989-90 233.388 6.93 2.37 0.84 48.021990-91 240.44 7.86 2.38 0.90 61.731991-92 251.879 12.18 2.40 1.09 148.301992-93 253.407 10.93 2.40 1.04 119.521993-94 257.648 10.35 2.41 1.02 107.181994-95 365.918 9.76 2.56 0.99 95.321995-96 518.762 11.34 2.71 1.05 128.491996-97 666.144 13.65 2.82 1.14 186.261997-98 755.229 16.19 2.88 1.21 262.211998-99 672.69 17.82 2.83 1.25 317.651999-00 648.458 18.31 2.81 1.26 335.412000-01 907.384 20.52 2.96 1.31 421.142001-02 827.863 21.96 2.92 1.34 482.242002-03 825.08 21.85 2.92 1.34 477.522003-04 903.713 20.42 2.96 1.31 416.942004-05 1211.979 23.19 3.08 1.37 537.782005-06 1469.866 28.55 3.17 1.46 814.942006-07 1617.423 33.75 3.21 1.53 1139.062007-08 2017.622 38.25 3.30 1.58 1463.062008-09 2047.668 40.61 3.31 1.61 1648.772009-10 2483.605 46.49 3.40 1.67 2161.512010-11 2788.665 54.84 3.45 1.74 3006.88

16 | P a g e

Summary of all 5-Types of Equations

Sl. No.

Equation Form a b c R2 Sig. Level

1

Y = a + bX

-260.019 56.995 - 0.979 0.000Car Sale = -260.019+56.995*PCNI R

2=0.979

(0.000)

2

Log Y = a + b Log X

1.176 1.333 - 0.935 0.000Log(Car Sale) = 1.176+1.333*Log(PCNI) R

2=0.935

(0.000)

3

Y = a + bx + cx2

-239.095 55.032 0.034 0.9790.000 &

0.811Car Sale = -239.095+55.032*PCNI+0.034*PCNI2 R

2=0.979

(0.000) (0.811)

4Y = a + bt

-248.798108.45

2- 0.859 0.000

Car Sale = -248.798+108.452*Year_Count R2=0.859 (0.000)

5Log Y = a + bt

2.271 0.053 - 0.963 0.000Log(Car Sale) = 2.271+0.053*Year_Count R2=0.963 (0.000)

1. Scatter Plot, Model and Co-efficients for the Equation Form : Y = a + bX

17 | P a g e

2) Scatter Plot, Model and Co-efficients for the Equation Form : LogY = a + bLogX

18 | P a g e

3) Scatter Plot, Model and Co-efficients for the Equation Form : Y = a + bX + cX2

19 | P a g e

4) Scatter Plot, Model and Co-efficients for the Equation Form : Y = a + bt

20 | P a g e

5) Scatter Plot, Model and Co-efficients for the Equation Form : LogY = a + bt

21 | P a g e

Conclusion :

1) In all the 5 equation forms i.e. (1) Y=a+bX, (2) LogY=a+bLogX, (3) Y = a+bX+cX2, (4) Y = a+bt and

(5) Log Y = a+bt, the value of R2 which is the co-efficient of determination that explains explanatory

power of the regression equation is high excepting for the equation (4) which is slightly lower

compared to others and in acceptable limits. This means the variables have strong co-relation.

2) Similarly, the significance level for all the 5 forms of equations is very good excepting for the

equation form (3) i.e. qudratic one (only square one) and within 0.10 and hence acceptable. This

means, we do not have sufficient reasons to reject the hypothesis.

However, looking into all 5 forms of the equations with their R2 values and significance level, we can fairly

estimate that the a priori reasoning that Sale of Cars will depend upon the net availability of per capita

income follows all 4 equation form no. i.e. (1) Y=a+bX, (2) LogY=a+bLogX, (3) Y = a+bt and (4) Log Y = a+bt.

However, among all these 4 forms, the value of R2 is high in equation form (1) i.e. Y = a+bX. Hence,we can

conclude that the regression quation for this bivariate data as :-

Car Sale = - 260.019 + 56.995*PCNI

(0.000) R2=0.979

Multi-Variate Analysis:

We want to explain variation of domestic sales of the car in India with respect to the independent variables.

Based on the details as obtained from CMIE, India Stat and SIAM data base we can define dependent and

independent variables, as indicated below.

Dependent Variable : Year wise sale of cars

Independent Variables : Per Capita Income, Inflation Rate, Lending (Interest) Rate

22 | P a g e

A Priori Reasoning : With constant increase in Indian GDP year on year and with effect of globalisation

effect, the net per capita income / disposable income at the hands of every Indian is increasing. Further with

advent of MNCs in Indian market, the job prospect as well as better salary makes the pay cheques thicker and

thicker.

As a result, a rational human being would prefer to spend his disposable income in buying expensive products

like cars, electronic goods etc. This is more likely to push demand of car sales.

Increase in inflation rate will lead to reduction in purchasing power of prospective car buyers and hence this

may lead to reduction of sale of cars.

Most of the Indian consumers buy their cars with bank loans. With increase in lending rates by the banks, the

prospective car buyers will think twice before going for bank loans. Hence, the increase in bank loan will lead

to reduction in sale of cars. Now, we shall test the hypothesis with both models i.e. Additive as well as

Multiplicative Model.

Additive Model: As per additive model for regression, we can write the following equation i.e.

Domestic Car Sales = a + b1*Per Capita Net Income+b2*Inflation Rate+b3*Interest Rate + U

Where a = Constant i.e. Y axis interceptb1 = Co-efficient of Per Capita Incomeb2 = Co-efficient of Inflation Rateb3 = Co-efficient of Interest Rate and U = Error Term

After incorporating the details i.e. dependent and independent variables in SPSS package, we get the following output.

Also, 3 iterations with elimination of one of independent variables at each time was done to see the effect more in detail.

23 | P a g e

Dependent Variable Constant (a)

Slope-X1 (b1) Slope-X2 (b2)

Slope-X3 (b3)

Adjusted R^2

Domestic car Sale Per Capita net Income (PCNI)

Inflation Rate

Interest Rate

(1) 

-388.93857.964 -8.895 12.15

0.979(0.000) (0.122) (0.337)

(2) 3288.089- 14.711 -172.411

0.278- (0.646) (0.008)

(3) -302.3657.32 - 2.54

0.977(0.000) - (0.824)

(4) -208.25456.607 -6.305 -

0.979(0.000) (0.205) -

The estimated Equation can be written by taking the values from the output as: (Additive Regression Model)

Domestic Car Sale = -388.938+57.964*PCNI-8.895*Inflation Rate+12.15*Interest Rate (0.00) (0.122) (0.337)

Adjusted R2=0.979

Interpretation:

1) The adjusted R2 which is a better estimate of co-efficient of determination (which defines the

explanatory power of regression equation) is 0.979. This means, the variability of Domestic Sale of Car

can be very well explained by these 3 variables i.e. Per capita Net Income, Inflation Rate as well as

Interest rate.

24 | P a g e

2) The value of F in the SPSS output is 324.075 which is very high. This means F is statistically significant

i.e. there is a fair degree of association between dependent and independent variable. This is also

explained by the explanatory power i.e. Adjusted R2.

3) Excepting inflation rate, all other variables are positively co-related. This means, with increase of per

capita net income and decrease in inflation rate, there will be increase in sale of cars, which is a priori

correct. However, the above equation also tells us that with increase in interest rate, there will be

increase in sale of car which is not a priory correct.

4) The sign of the slope of the variable “ per capita net income (PCNI)” is positive and it is highly

significant also i.e. 0.001 (less than 10%). Also, the sign of the slope of the variable “ Inflation Rate” is

negative and it’s significance level is very close to cut off limit of 10% (it is 12.2%). Even though from a

theoretical perspective we can ignore significance of inflation rate (due to it’s significance level > 10%)

but the fact lies that since the slope of the variable is negatively co-related, the sale of car will increase

with decrease in inflation rate.

5) Further, the significance level of the variable “Interest Rate” is 0.337 which is very high which means

this variable is statistically in significant and this is also explained by the +ve slope un-standardized

coefficient. The +ve relationship between domestic Car sales and interest rate is impractical. However,

since the co-efficient is statistically not significant, one can not be sure about the impact of the variable.

6) From all the standardized coefficients, it is clear that the value of the standardized coefficients for the

per capita net income is highest (1.006) compared to that of other variables. This means, per capita net

income (PCNI) is most important variables in explaining the variation as compared to other variables.

Multiplicative Model: As per multiplicative model for regression, we can write the following equation i.e.

Domestic Car Sales = a *Per Capita Net Incomeb1*Inflation Rateb2*Interest Rate b3

Taking Log on both sides, we can rewrite the above equation as :-

Log_Domestic Car Sales=Log a + b1*Log_Per Caipta Net Income + b2*Log_Inflation Rate + b3*Log_Interest Rate+U

Where a = Constant i.e. Y axis intercept

b1 = Co-efficient of Per Capita Income

b2 = Co-efficient of Inflation Rate

b3 = Co-efficient of Interest Rate and U = Error Term

After incorporating the details i.e. dependent and independent variables in SPSS package, we get the

following output.

As done in case of additive model, here also 3 additional iterations by eliminating the independent variables

one at a time is conducted to see the effect and the summary of the same is put below.

25 | P a g e

26 | P a g e

Dependent Variable Constant (a)

Slope-X1 (b1) Slope-X2 (b2)

Slope-X3 (b3)

Adjusted R^2

Log_Domestic car Sale Log_Per Capita net Income

(PCNI)

Log_Inflation Rate

Log_Interest Rate

(1) 

1.4011.288 -0.082 -0.098

0.935(0.000) (0.209) (0.799)

(2) 6.426- 0.134 -3.214

0.517- (0.419) (0.000)

(3) 1.7071.241 - -0.366

0.932(0.000) - (0.272)

(4) 1.2671.311 -0.091 -

0.938(0.000) (0.094) -

The estimated Equation can be written by taking the values from the output as: (Multiplicative Regression Model)

Log_Domestic Car Sale = 1.401+1.288*Log_PCNI-0.082*Log_Inflation Rate-0.098*Log_Interest Rate (0.00) (0.209) (0.799)

Adjusted R2=0.935

Interpretation: Log-Linear

1) The adjusted R2 which is a better estimate of co-efficient of determination (which defines the

explanatory power of regression equation) is 0.935. This means, 93.5% of the total variance of the

Domestic Sale of Car can be very well explained by these 3 variables i.e. Per capita Net Income,

Inflation Rate as well as Interest rate.

2) The value of F in the SPSS output is 101.436 which is very high. This means F is statistically significant

i.e. there is a fair degree of association between dependent and independent variables. This is also

explained by the explanatory power i.e. Adjusted R2.

3) Excepting PCNI, all other two variables are negatively co-related. This means, with increase of per

capita net income, decrease in inflation rate and decrease in interest rate, there will be increase in sale

of cars, which is a priori correct.

4) The sign of the slope of the variable “ per capita net income (PCNI)” is positive and it is highly

significant also i.e. 0.001 (less than 10%). Also, the sign of the slope of the variables “ Inflation Rate”

and “Inflation rate” is negative and their significance level is more than the cut off limit of 10%.

5) Further, the significance levels of the variable “Interest Rate” and “Inflation Rate” are higher than the

cut off limits of 10% which means these variable are statistically not significant.

27 | P a g e

6) From all the standardized coefficients, it is clear that the value of the standardized coefficients for the

per capita net income is highest (0.935) compared to that of other variables. This means, per capita net

income (PCNI) is most important variables in explaining the variation as compared to other variables.

7) The slope of the independent variable which is called the elasticity for that variable indicates that

keeping other variables fixed, any percentage change in independent variable will change the

dependent variable to that extent. In this case, 1% change on per capital net income will bring 1.288%

change in domestic car sale.

Part-B : Factor and Cluster AnalysisFactor Analysis – Factors influencing purchase

Factor Analysis is an interdependent technique. In interdependent techniques, the variables are not classified

as independent or dependent variable, but their interrelationship is studied.

It is a data reduction technique applicable when there is a systematic dependence amongst a set of observed

or manifest variables and the researcher is interested in finding out something more fundamental (or latent)

which creates this commonality. Factor analysis is done mainly for following reasons.

1. To identify a new smaller set of uncorrelated variables to be used in subsequent multiple regression

analysis.

2. To identify underlying dimensions/factors that are unobservable but explain correlations among a set of

variable.

The general purpose of factor analysis is to find a method of summarizing the information contained in a

number of original variables into a smaller set of new composite dimensions (Factors) with minimum loss of

information. It usually proceeds from the correlations matrix formed out of the selected variables included in

the study. The appropriateness of the factor model can also be calculated from this. Next, Factor extraction,

the number of factors necessary to represent the data and the method of calculating them must be

determined. At this step, how well the chosen model fits the data is also ascertained. Rotation focuses on

transforming the factors to make them more interpretable and following this, scores for each factor can be

computed for each case. These scores are then used for further analysis. For our study, it is interesting to

study the factors which can be derived out of several variables which contribute in influencing the purchase of

a car. There are 39 variables under the heading „factors influencing purchase‟. These variables were subject

to correlation analysis first

28 | P a g e

Co-Relation Matrix

Variables Pric

e

Sugg

estio

n_fro

m_fam

ily

Fami

ly_Ne

eds

Statu

s_Sy

mbol

Bran

d_Na

me

Comp

ariso

n_of

_Cars

Pref

eren

ce_F

estiv

e_Off

er

Type

_of_

Fuel

Advic

e_fro

m_Co

lleag

ues

Envir

onme

nt_P

olutio

n_No

rms

Adve

rtise

ment

_Pro

motio

n

Drivi

ng_C

omfo

rt

Resa

le_Va

lue

Instal

lamen

t_Pa

ymen

t

Insur

ance

_Fac

ility

Exte

nded

_Warr

anty

Deale

r_Lo

catio

n

All_C

ars_U

nder

_one

_Roo

f

Tech

nolog

y

Mob

ile_C

harge

r

Road

_Grip

Fuel_

Econ

omy

Powe

r_Pic

kup

Color

_of_

Car

Chro

me_P

lated

_Doo

r_Ha

ndles

Fog_

Light

Rear_

View

_Cam

era_

Reve

rse_G

ear_

Sens

or

Soft_

Drink

_Hold

er

Sleek

_Gea

r_Sh

ift_K

nob

Audio

_Vide

o_Sy

stem

Air_

Cond

ition

ing_S

yste

m

Inbuil

t_Na

vigati

on_S

yste

m

Anti_

Brak

e_Sk

idding

Air_

Bag

Child

_Loc

k_Re

ar_wi

ndow

s

Car_

Acce

ssorie

s

Easy

_Acce

ss_Sp

are_P

arts

Avail

abiili

ty_Se

rvice

_Stati

on

Free_

Picku

p_Dr

op_D

uring

_Ser

vice

Price 1 0.025 -0.011 0.191 0.133 0.12 -0 -0.1 0.01 -0.1 -0.1 -0 0.01 -0.1 -0.1 -0.1 -0.2 -0.1 -0.2 -0.3 -0.2 -0 -0.1 -0.1 -0.01 -0.1 -0 -0.1 -0 -0.1 0.05 -0.1 -0.1 -0.1 -0.02 -0.2 -0.01 -0 -0.1

Suggestion_from_family 0.025 1 0.205 -0.07 -0.068 0.03 0.18 0.03 0.12 0.14 0.11 0.06 0.06 0.17 0.28 0.12 0.09 -0 0.15 -0.1 0.11 0 -0 -0 0.15 0.01 -0 0.08 0.12 0.02 -0 -0.2 -0.2 -0.2 0.1 0.16 0.2 0.23 0.22

Family_Needs -0.011 0.205 1 -0.01 -0.085 0.05 -0 -0 -0 0.32 0.07 0.26 -0 0.08 0.13 0.24 0 -0.1 0.24 0.06 0.35 0.16 0.25 0.06 0.09 0.01 -0.1 0.19 -0 -0 0.2 -0 0.02 0.07 0.27 0.18 0.21 0.27 0.03

Status_Symbol 0.191 -0.071 -0.013 1 0.469 0.32 0.04 0.22 0.01 -0.2 -0 0.16 -0 -0 -0.2 -0 0.05 0.08 0.16 0.05 -0 -0.1 0.04 0.2 0.05 0 0.23 0.11 0.24 0.21 0.18 0.1 0.11 0.07 0.07 0.07 -0.08 -0.1 -0.1

Brand_Name 0.133 -0.068 -0.085 0.469 1 0.13 0.11 0.19 0.12 0.1 -0 0.1 0.04 0.06 0.03 0.16 0.05 0.06 0.25 0.15 -0.1 -0 0.16 0.1 -0.02 0.2 0.23 0.13 0.31 0.18 0.12 0.11 0.03 0.08 0.17 0.07 0.16 0.02 0.07

Comparison_of_Cars 0.119 0.026 0.05 0.316 0.128 1 0.13 0.04 0.2 -0.2 0.23 0.06 -0 -0.2 -0.2 -0.1 -0 -0.2 -0 -0.2 -0 0.17 -0 0.04 -0.14 -0.1 -0 -0.1 0.08 0.08 0.05 -0.2 -0.1 0 -0.03 -0 -0.02 -0 -0.2

Preference_Festive_Offer -0.031 0.18 -0.028 0.037 0.109 0.13 1 0.08 0.22 0.16 0.18 -0.1 0.28 0.25 0.27 0.28 0.24 0.16 0.02 0.1 -0.1 0.06 -0.1 -0.1 0.04 -0.3 -0.2 0.17 -0.2 0.14 -0.1 -0.1 -0.3 -0.2 -0.04 0.3 -0.02 0.06 0.1

Type_of_Fuel -0.127 0.034 -0.017 0.224 0.193 0.04 0.08 1 0.06 0.17 0 0.18 0.13 0.23 0.28 0.35 0.16 0.08 0.23 0.23 0.1 0.19 0.11 0.06 0.03 0.1 0.14 0.07 -0.1 0.32 0.11 0.22 0.14 0.09 0.05 0.43 0.15 -0 0.1

Advice_from_Colleagues 0.012 0.116 -0.024 0.009 0.12 0.2 0.22 0.06 1 0 0.02 -0 0.1 -0 0.05 0.13 0.03 0.01 -0 -0 0.15 0 0.05 0.02 0.04 -0.1 -0 -0.2 -0.1 -0.1 0.06 -0 -0.1 -0.2 0.07 0.18 -0.07 -0 -0.1

Environment_Polution_Norms -0.059 0.136 0.316 -0.23 0.099 -0.17 0.16 0.17 0 1 0.13 0.26 0.28 0.31 0.55 0.5 0.36 0.21 0.29 0.29 0.33 0.28 0.15 0.02 0.07 0.31 0.15 0.16 0.03 0.07 -0 0.26 0.12 0.27 0.29 0.24 0.27 0.26 0.18

Advertisement_Promotion -0.148 0.114 0.074 -0.04 -0.027 0.23 0.18 0 0.02 0.13 1 0.15 0.1 0.14 0.24 0.12 0.35 0.32 0.2 0.11 0.13 0.17 0.02 0.31 0.18 0.13 0.01 0.27 -0 0.15 0.08 -0.1 -0 -0.1 -0.15 0.21 0.19 0.32 0.24

Driving_Comfort -0.047 0.064 0.26 0.162 0.1 0.06 -0.1 0.18 -0 0.26 0.15 1 0.13 0.01 0.22 0.29 0.3 0.15 0.45 0.26 0.52 0.18 0.32 0.14 0.19 0.27 0.07 0.15 0.29 0.04 0.28 0.22 0.19 0.22 0.45 0.04 0.34 0.2 0.03

Resale_Value 0.013 0.059 -0.012 -0.01 0.04 -0.02 0.28 0.13 0.1 0.28 0.1 0.13 1 0.38 0.3 0.25 0.39 0.25 0.01 0.26 0.07 0.07 0.15 0.26 0.27 0.21 0.09 0.27 0.15 0.04 -0 0.08 -0.1 -0.1 0.01 0.36 0.16 0.14 0.18

Installament_Payment -0.071 0.172 0.081 -0.03 0.057 -0.23 0.25 0.23 -0 0.31 0.14 0.01 0.38 1 0.64 0.31 0.23 0.17 0.22 0.31 0.22 0.12 0.02 0.1 0.33 0.08 0.09 0.37 0.08 0.32 0.19 0.02 -0 -0.2 0.07 0.34 0.2 0.28 0.3

Insurance_Facility -0.071 0.279 0.127 -0.18 0.03 -0.2 0.27 0.28 0.05 0.55 0.24 0.22 0.3 0.64 1 0.56 0.36 0.37 0.29 0.45 0.36 0.3 0.16 0.06 0.39 0.31 0.25 0.43 0.15 0.35 0.08 0.22 0.15 0.08 0.26 0.35 0.31 0.38 0.5

Extended_Warranty -0.118 0.121 0.243 -0.01 0.163 -0.07 0.28 0.35 0.13 0.5 0.12 0.29 0.25 0.31 0.56 1 0.53 0.39 0.22 0.38 0.4 0.24 0.28 0.12 0.37 0.34 0.28 0.34 0.15 0.24 0.09 0.35 0.26 0.26 0.29 0.48 0.32 0.35 0.4

Dealer_Location -0.191 0.093 0.002 0.053 0.054 -0.02 0.24 0.16 0.03 0.36 0.35 0.3 0.39 0.23 0.36 0.53 1 0.54 0.19 0.32 0.23 0.32 0.18 0.33 0.27 0.38 0.22 0.35 0.23 0.17 0.06 0.21 0.02 0.07 0.09 0.32 0.14 0.34 0.29

All_Cars_Under_one_roof -0.144 -0.042 -0.088 0.076 0.062 -0.2 0.16 0.08 0.01 0.21 0.32 0.15 0.25 0.17 0.37 0.39 0.54 1 0.14 0.35 0.11 0.12 0.03 0.21 0.31 0.36 0.31 0.34 0.16 0.23 -0.1 0.21 0.06 0.17 0.12 0.32 0.16 0.22 0.39

Technology -0.162 0.148 0.235 0.157 0.248 -0.04 0.02 0.23 -0 0.29 0.2 0.45 0.01 0.22 0.29 0.22 0.19 0.14 1 0.33 0.45 0.19 0.34 0.15 0.13 0.2 0.11 0.24 0.31 0.26 0.32 0.11 0.07 0.04 0.23 0.15 0.42 0.14 0.09

Mobile_Charger -0.266 -0.101 0.055 0.045 0.146 -0.19 0.1 0.23 -0 0.29 0.11 0.26 0.26 0.31 0.45 0.38 0.32 0.35 0.33 1 0.39 0.13 0.29 0.16 0.45 0.38 0.25 0.55 0.39 0.53 0.15 0.53 0.39 0.36 0.17 0.29 0.15 -0.1 0.38

Road_Grip -0.198 0.114 0.352 -0.04 -0.085 -0.03 -0.1 0.1 0.15 0.33 0.13 0.52 0.07 0.22 0.36 0.4 0.23 0.11 0.45 0.39 1 0.29 0.5 0.17 0.29 0.22 0.01 0.18 0.21 0.3 0.42 0.28 0.28 0.22 0.34 0.25 0.37 0.3 0.19

Fuel_Economy -0.007 0.001 0.163 -0.05 -0.042 0.17 0.06 0.19 0 0.28 0.17 0.18 0.07 0.12 0.3 0.24 0.32 0.12 0.19 0.13 0.29 1 0.25 0.1 0.12 0.21 0.09 0.02 0.03 0.22 0.22 0.09 0.01 0.09 0.17 0.09 0.31 0.22 -0.1

Power_Pickup -0.065 -0.047 0.251 0.038 0.157 -0 -0.1 0.11 0.05 0.15 0.02 0.32 0.15 0.02 0.16 0.28 0.18 0.03 0.34 0.29 0.5 0.25 1 0.41 0.24 0.3 0.14 0.07 0.12 0.27 0.41 0.27 0.23 0.1 0.19 0.21 0.26 0.27 0.1

Color_of_Car -0.074 -0.049 0.055 0.201 0.103 0.04 -0.1 0.06 0.02 0.02 0.31 0.14 0.26 0.1 0.06 0.12 0.33 0.21 0.15 0.16 0.17 0.1 0.41 1 0.23 0.38 0.37 0.25 0.32 0.18 0.32 0.17 0.16 -0.1 -0 0.26 0.19 0.37 0.24

Chrome_Plated_Door_Handles -0.013 0.15 0.085 0.05 -0.019 -0.14 0.04 0.03 0.04 0.07 0.18 0.19 0.27 0.33 0.39 0.37 0.27 0.31 0.13 0.45 0.29 0.12 0.24 0.23 1 0.44 0.36 0.42 0.24 0.27 0.06 0.12 0.15 -0 -0.05 0.32 0.16 0.13 0.31

Fog_Light -0.097 0.008 0.009 0.004 0.195 -0.09 -0.3 0.1 -0.1 0.31 0.13 0.27 0.21 0.08 0.31 0.34 0.38 0.36 0.2 0.38 0.22 0.21 0.3 0.38 0.44 1 0.52 0.36 0.46 0.07 0.13 0.38 0.39 0.35 0.18 0.24 0.19 0.15 0.15

Rear_View_Camera_Reverse_Gear_Sensor -0.018 -0.049 -0.073 0.225 0.226 -0.04 -0.2 0.14 -0 0.15 0.01 0.07 0.09 0.09 0.25 0.28 0.22 0.31 0.11 0.25 0.01 0.09 0.14 0.37 0.36 0.52 1 0.29 0.45 0.13 0.03 0.51 0.35 0.18 0.16 0.29 0.19 0.28 0.23

Soft_Drink_Holder -0.107 0.08 0.187 0.112 0.132 -0.07 0.17 0.07 -0.2 0.16 0.27 0.15 0.27 0.37 0.43 0.34 0.35 0.34 0.24 0.55 0.18 0.02 0.07 0.25 0.42 0.36 0.29 1 0.44 0.4 0.27 0.25 0.17 0.15 0.12 0.37 0.25 0.2 0.47

Sleek_Gear_Shift_Knob -0.033 0.121 -0.016 0.235 0.309 0.08 -0.2 -0.1 -0.1 0.03 -0 0.29 0.15 0.08 0.15 0.15 0.23 0.16 0.31 0.39 0.21 0.03 0.12 0.32 0.24 0.46 0.45 0.44 1 0.2 0.13 0.28 0.22 0.25 0.3 0.07 0.23 0.08 0.17

Audio_Video_System -0.146 0.019 -0.002 0.207 0.181 0.08 0.14 0.32 -0.1 0.07 0.15 0.04 0.04 0.32 0.35 0.24 0.17 0.23 0.26 0.53 0.3 0.22 0.27 0.18 0.27 0.07 0.13 0.4 0.2 1 0.3 0.15 0.2 0.16 0.1 0.29 0.25 0.12 0.32

Air_Conditioning_System 0.051 -0.021 0.202 0.18 0.12 0.05 -0.1 0.11 0.06 -0 0.08 0.28 -0 0.19 0.08 0.09 0.06 -0.1 0.32 0.15 0.42 0.22 0.41 0.32 0.06 0.13 0.03 0.27 0.13 0.3 1 0.08 0.24 0.07 0.31 0.2 0.48 0.3 0.17

Inbuilt_Navigation_System -0.146 -0.193 -0.009 0.095 0.111 -0.18 -0.1 0.22 -0 0.26 -0.1 0.22 0.08 0.02 0.22 0.35 0.21 0.21 0.11 0.53 0.28 0.09 0.27 0.17 0.12 0.38 0.51 0.25 0.28 0.15 0.08 1 0.69 0.57 0.28 0.37 0.07 0.1 0.22

Anti_Brake_Skidding -0.144 -0.18 0.022 0.114 0.028 -0.09 -0.3 0.14 -0.1 0.12 -0 0.19 -0.1 -0 0.15 0.26 0.02 0.06 0.07 0.39 0.28 0.01 0.23 0.16 0.15 0.39 0.35 0.17 0.22 0.2 0.24 0.69 1 0.68 0.29 0.2 0.07 0.06 0.26

Air_Bag -0.135 -0.248 0.07 0.071 0.077 0 -0.2 0.09 -0.2 0.27 -0.1 0.22 -0.1 -0.2 0.08 0.26 0.07 0.17 0.04 0.36 0.22 0.09 0.1 -0.1 -0.02 0.35 0.18 0.15 0.25 0.16 0.07 0.57 0.68 1 0.48 0.11 0.01 -0.1 0.09

Child_Lock_Rear_windows -0.019 0.102 0.274 0.066 0.166 -0.03 -0 0.05 0.07 0.29 -0.1 0.45 0.01 0.07 0.26 0.29 0.09 0.12 0.23 0.17 0.34 0.17 0.19 0.00 -0.05 0.18 0.16 0.12 0.3 0.1 0.31 0.28 0.29 0.48 1 0.03 0.26 0.18 0.13

Car_Accessories -0.185 0.164 0.178 0.071 0.065 -0.01 0.3 0.43 0.18 0.24 0.21 0.04 0.36 0.34 0.35 0.48 0.32 0.32 0.15 0.29 0.25 0.09 0.21 0.26 0.32 0.24 0.29 0.37 0.07 0.29 0.2 0.37 0.2 0.11 0.03 1 0.35 0.38 0.35

Easy_Access_Spare_Parts -0.01 0.199 0.212 -0.08 0.159 -0.02 -0 0.15 -0.1 0.27 0.19 0.34 0.16 0.2 0.31 0.32 0.14 0.16 0.42 0.15 0.37 0.31 0.26 0.19 0.16 0.19 0.19 0.25 0.23 0.25 0.48 0.07 0.07 0.01 0.26 0.35 1 0.65 0.33

Availabiility_Service_Station -0.008 0.225 0.266 -0.15 0.02 -0.01 0.06 -0 -0 0.26 0.32 0.2 0.14 0.28 0.38 0.35 0.34 0.22 0.14 -0.1 0.3 0.22 0.27 0.37 0.13 0.15 0.28 0.2 0.08 0.12 0.3 0.1 0.06 -0.1 0.18 0.38 0.65 1 0.32

Free_Pickup_Drop_During_Service -0.106 0.22 0.027 -0.1 0.068 -0.23 0.1 0.1 -0.1 0.18 0.24 0.03 0.18 0.3 0.5 0.4 0.29 0.39 0.09 0.38 0.19 -0.1 0.1 0.24 0.31 0.15 0.23 0.47 0.17 0.32 0.17 0.22 0.26 0.09 0.13 0.35 0.33 0.32 1

Co-Relation Matrix

This is the correlation matrix and where the co-relation co-efficient is higher than 0.5, the same are highlighted in red font.

Since, it is not clearly legible to see the entire co-relation matrix, for convenience the same is shown in 2 separate pages.

Co-Relation Matrix in expanded View

29 | P a g e

Variables Pri

ce

Sugg

estio

n_fr

om_f

amily

Fam

ily_N

eeds

Stat

us_S

ymbo

l

Bran

d_N

ame

Com

paris

on_o

f_Ca

rs

Pref

eren

ce_F

estiv

e_O

ffer

Type

_of_

Fuel

Advi

ce_f

rom

_Col

leag

ues

Envi

ronm

ent_

Polu

tion_

Nor

ms

Adve

rtise

men

t_Pr

omoti

on

Driv

ing_

Com

fort

Resa

le_V

alue

Inst

alla

men

t_Pa

ymen

t

Insu

ranc

e_Fa

cilit

y

Exte

nded

_War

rant

y

Deal

er_L

ocati

on

All_

Cars

_Und

er_o

ne_R

oof

Tech

nolo

gy

Price 1 0.025 -0.011 0.191 0.133 0.12 -0 -0.1 0.01 -0.1 -0.1 -0 0.01 -0.1 -0.1 -0.1 -0.2 -0.1 -0.2

Suggestion_from_family 0.025 1 0.205 -0.07 -0.068 0.03 0.18 0.03 0.12 0.14 0.11 0.06 0.06 0.17 0.28 0.12 0.09 -0 0.15

Family_Needs -0.011 0.205 1 -0.01 -0.085 0.05 -0 -0 -0 0.32 0.07 0.26 -0 0.08 0.13 0.24 0 -0.1 0.24

Status_Symbol 0.191 -0.071 -0.013 1 0.469 0.32 0.04 0.22 0.01 -0.2 -0 0.16 -0 -0 -0.2 -0 0.05 0.08 0.16

Brand_Name 0.133 -0.068 -0.085 0.469 1 0.13 0.11 0.19 0.12 0.1 -0 0.1 0.04 0.06 0.03 0.16 0.05 0.06 0.25

Comparison_of_Cars 0.119 0.026 0.05 0.316 0.128 1 0.13 0.04 0.2 -0.2 0.23 0.06 -0 -0.2 -0.2 -0.1 -0 -0.2 -0

Preference_Festive_Offer -0.031 0.18 -0.028 0.037 0.109 0.13 1 0.08 0.22 0.16 0.18 -0.1 0.28 0.25 0.27 0.28 0.24 0.16 0.02

Type_of_Fuel -0.127 0.034 -0.017 0.224 0.193 0.04 0.08 1 0.06 0.17 0 0.18 0.13 0.23 0.28 0.35 0.16 0.08 0.23

Advice_from_Colleagues 0.012 0.116 -0.024 0.009 0.12 0.2 0.22 0.06 1 0 0.02 -0 0.1 -0 0.05 0.13 0.03 0.01 -0

Environment_Polution_Norms -0.059 0.136 0.316 -0.23 0.099 -0.17 0.16 0.17 0 1 0.13 0.26 0.28 0.31 0.55 0.5 0.36 0.21 0.29

Advertisement_Promotion -0.148 0.114 0.074 -0.04 -0.027 0.23 0.18 0 0.02 0.13 1 0.15 0.1 0.14 0.24 0.12 0.35 0.32 0.2

Driving_Comfort -0.047 0.064 0.26 0.162 0.1 0.06 -0.1 0.18 -0 0.26 0.15 1 0.13 0.01 0.22 0.29 0.3 0.15 0.45

Resale_Value 0.013 0.059 -0.012 -0.01 0.04 -0.02 0.28 0.13 0.1 0.28 0.1 0.13 1 0.38 0.3 0.25 0.39 0.25 0.01

Installament_Payment -0.071 0.172 0.081 -0.03 0.057 -0.23 0.25 0.23 -0 0.31 0.14 0.01 0.38 1 0.64 0.31 0.23 0.17 0.22

Insurance_Facility -0.071 0.279 0.127 -0.18 0.03 -0.2 0.27 0.28 0.05 0.55 0.24 0.22 0.3 0.64 1 0.56 0.36 0.37 0.29

Extended_Warranty -0.118 0.121 0.243 -0.01 0.163 -0.07 0.28 0.35 0.13 0.5 0.12 0.29 0.25 0.31 0.56 1 0.53 0.39 0.22

Dealer_Location -0.191 0.093 0.002 0.053 0.054 -0.02 0.24 0.16 0.03 0.36 0.35 0.3 0.39 0.23 0.36 0.53 1 0.54 0.19

All_Cars_Under_one_roof -0.144 -0.042 -0.088 0.076 0.062 -0.2 0.16 0.08 0.01 0.21 0.32 0.15 0.25 0.17 0.37 0.39 0.54 1 0.14

Technology -0.162 0.148 0.235 0.157 0.248 -0.04 0.02 0.23 -0 0.29 0.2 0.45 0.01 0.22 0.29 0.22 0.19 0.14 1

Mobile_Charger -0.266 -0.101 0.055 0.045 0.146 -0.19 0.1 0.23 -0 0.29 0.11 0.26 0.26 0.31 0.45 0.38 0.32 0.35 0.33

Road_Grip -0.198 0.114 0.352 -0.04 -0.085 -0.03 -0.1 0.1 0.15 0.33 0.13 0.52 0.07 0.22 0.36 0.4 0.23 0.11 0.45

Fuel_Economy -0.007 0.001 0.163 -0.05 -0.042 0.17 0.06 0.19 0 0.28 0.17 0.18 0.07 0.12 0.3 0.24 0.32 0.12 0.19

Power_Pickup -0.065 -0.047 0.251 0.038 0.157 -0 -0.1 0.11 0.05 0.15 0.02 0.32 0.15 0.02 0.16 0.28 0.18 0.03 0.34

Color_of_Car -0.074 -0.049 0.055 0.201 0.103 0.04 -0.1 0.06 0.02 0.02 0.31 0.14 0.26 0.1 0.06 0.12 0.33 0.21 0.15

Chrome_Plated_Door_Handles -0.013 0.15 0.085 0.05 -0.019 -0.14 0.04 0.03 0.04 0.07 0.18 0.19 0.27 0.33 0.39 0.37 0.27 0.31 0.13

Fog_Light -0.097 0.008 0.009 0.004 0.195 -0.09 -0.3 0.1 -0.1 0.31 0.13 0.27 0.21 0.08 0.31 0.34 0.38 0.36 0.2

Rear_View_Camera_Reverse_Gear_Sensor -0.018 -0.049 -0.073 0.225 0.226 -0.04 -0.2 0.14 -0 0.15 0.01 0.07 0.09 0.09 0.25 0.28 0.22 0.31 0.11

Soft_Drink_Holder -0.107 0.08 0.187 0.112 0.132 -0.07 0.17 0.07 -0.2 0.16 0.27 0.15 0.27 0.37 0.43 0.34 0.35 0.34 0.24

Sleek_Gear_Shift_Knob -0.033 0.121 -0.016 0.235 0.309 0.08 -0.2 -0.1 -0.1 0.03 -0 0.29 0.15 0.08 0.15 0.15 0.23 0.16 0.31

Audio_Video_System -0.146 0.019 -0.002 0.207 0.181 0.08 0.14 0.32 -0.1 0.07 0.15 0.04 0.04 0.32 0.35 0.24 0.17 0.23 0.26

Air_Conditioning_System 0.051 -0.021 0.202 0.18 0.12 0.05 -0.1 0.11 0.06 -0 0.08 0.28 -0 0.19 0.08 0.09 0.06 -0.1 0.32

Inbuilt_Navigation_System -0.146 -0.193 -0.009 0.095 0.111 -0.18 -0.1 0.22 -0 0.26 -0.1 0.22 0.08 0.02 0.22 0.35 0.21 0.21 0.11

Anti_Brake_Skidding -0.144 -0.18 0.022 0.114 0.028 -0.09 -0.3 0.14 -0.1 0.12 -0 0.19 -0.1 -0 0.15 0.26 0.02 0.06 0.07

Air_Bag -0.135 -0.248 0.07 0.071 0.077 0 -0.2 0.09 -0.2 0.27 -0.1 0.22 -0.1 -0.2 0.08 0.26 0.07 0.17 0.04

Child_Lock_Rear_windows -0.019 0.102 0.274 0.066 0.166 -0.03 -0 0.05 0.07 0.29 -0.1 0.45 0.01 0.07 0.26 0.29 0.09 0.12 0.23

Car_Accessories -0.185 0.164 0.178 0.071 0.065 -0.01 0.3 0.43 0.18 0.24 0.21 0.04 0.36 0.34 0.35 0.48 0.32 0.32 0.15

Easy_Access_Spare_Parts -0.01 0.199 0.212 -0.08 0.159 -0.02 -0 0.15 -0.1 0.27 0.19 0.34 0.16 0.2 0.31 0.32 0.14 0.16 0.42

Availabiility_Service_Station -0.008 0.225 0.266 -0.15 0.02 -0.01 0.06 -0 -0 0.26 0.32 0.2 0.14 0.28 0.38 0.35 0.34 0.22 0.14

Free_Pickup_Drop_During_Service -0.106 0.22 0.027 -0.1 0.068 -0.23 0.1 0.1 -0.1 0.18 0.24 0.03 0.18 0.3 0.5 0.4 0.29 0.39 0.09

30 | P a g e

Variables Mob

ile_C

harg

er

Road

_Grip

Fuel

_Eco

nom

y

Pow

er_P

icku

p

Colo

r_of

_Car

Chro

me_

Plat

ed_D

oor_

Hand

les

Fog_

Ligh

t

Rear

_Vie

w_C

amer

a_Re

vers

e_G

ear_

Sens

or

Soft

_Drin

k_Ho

lder

Slee

k_G

ear_

Shift

_Kno

b

Audi

o_Vi

deo_

Syst

em

Air_

Cond

ition

ing_

Syst

em

Inbu

ilt_N

avig

ation

_Sys

tem

Anti_

Brak

e_Sk

iddi

ng

Air_

Bag

Child

_Loc

k_Re

ar_w

indo

ws

Car_

Acce

ssor

ies

Easy

_Acc

ess_

Spar

e_Pa

rts

Avai

labi

ility

_Ser

vice

_Sta

tion

Free

_Pic

kup_

Drop

_Dur

ing_

Serv

ice

Price -0.3 -0.2 -0 -0.1 -0.1 -0.01 -0.1 -0 -0.1 -0 -0.1 0.05 -0.1 -0.1 -0.1 -0.02 -0.2 -0.01 -0 -0.1

Suggestion_from_family -0.1 0.11 0 -0 -0 0.15 0.01 -0 0.08 0.12 0.02 -0 -0.2 -0.2 -0.2 0.1 0.16 0.2 0.23 0.22

Family_Needs 0.06 0.35 0.16 0.25 0.06 0.09 0.01 -0.1 0.19 -0 -0 0.2 -0 0.02 0.07 0.27 0.18 0.21 0.27 0.03

Status_Symbol 0.05 -0 -0.1 0.04 0.2 0.05 0 0.23 0.11 0.24 0.21 0.18 0.1 0.11 0.07 0.07 0.07 -0.08 -0.1 -0.1

Brand_Name 0.15 -0.1 -0 0.16 0.1 -0.02 0.2 0.23 0.13 0.31 0.18 0.12 0.11 0.03 0.08 0.17 0.07 0.16 0.02 0.07

Comparison_of_Cars -0.2 -0 0.17 -0 0.04 -0.14 -0.1 -0 -0.1 0.08 0.08 0.05 -0.2 -0.1 0 -0.03 -0 -0.02 -0 -0.2

Preference_Festive_Offer 0.1 -0.1 0.06 -0.1 -0.1 0.04 -0.3 -0.2 0.17 -0.2 0.14 -0.1 -0.1 -0.3 -0.2 -0.04 0.3 -0.02 0.06 0.1

Type_of_Fuel 0.23 0.1 0.19 0.11 0.06 0.03 0.1 0.14 0.07 -0.1 0.32 0.11 0.22 0.14 0.09 0.05 0.43 0.15 -0 0.1

Advice_from_Colleagues -0 0.15 0 0.05 0.02 0.04 -0.1 -0 -0.2 -0.1 -0.1 0.06 -0 -0.1 -0.2 0.07 0.18 -0.07 -0 -0.1

Environment_Polution_Norms 0.29 0.33 0.28 0.15 0.02 0.07 0.31 0.15 0.16 0.03 0.07 -0 0.26 0.12 0.27 0.29 0.24 0.27 0.26 0.18

Advertisement_Promotion 0.11 0.13 0.17 0.02 0.31 0.18 0.13 0.01 0.27 -0 0.15 0.08 -0.1 -0 -0.1 -0.15 0.21 0.19 0.32 0.24

Driving_Comfort 0.26 0.52 0.18 0.32 0.14 0.19 0.27 0.07 0.15 0.29 0.04 0.28 0.22 0.19 0.22 0.45 0.04 0.34 0.2 0.03

Resale_Value 0.26 0.07 0.07 0.15 0.26 0.27 0.21 0.09 0.27 0.15 0.04 -0 0.08 -0.1 -0.1 0.01 0.36 0.16 0.14 0.18

Installament_Payment 0.31 0.22 0.12 0.02 0.1 0.33 0.08 0.09 0.37 0.08 0.32 0.19 0.02 -0 -0.2 0.07 0.34 0.2 0.28 0.3

Insurance_Facility 0.45 0.36 0.3 0.16 0.06 0.39 0.31 0.25 0.43 0.15 0.35 0.08 0.22 0.15 0.08 0.26 0.35 0.31 0.38 0.5

Extended_Warranty 0.38 0.4 0.24 0.28 0.12 0.37 0.34 0.28 0.34 0.15 0.24 0.09 0.35 0.26 0.26 0.29 0.48 0.32 0.35 0.4

Dealer_Location 0.32 0.23 0.32 0.18 0.33 0.27 0.38 0.22 0.35 0.23 0.17 0.06 0.21 0.02 0.07 0.09 0.32 0.14 0.34 0.29

All_Cars_Under_one_roof 0.35 0.11 0.12 0.03 0.21 0.31 0.36 0.31 0.34 0.16 0.23 -0.1 0.21 0.06 0.17 0.12 0.32 0.16 0.22 0.39

Technology 0.33 0.45 0.19 0.34 0.15 0.13 0.2 0.11 0.24 0.31 0.26 0.32 0.11 0.07 0.04 0.23 0.15 0.42 0.14 0.09

Mobile_Charger 1 0.39 0.13 0.29 0.16 0.45 0.38 0.25 0.55 0.39 0.53 0.15 0.53 0.39 0.36 0.17 0.29 0.15 -0.1 0.38

Road_Grip 0.39 1 0.29 0.5 0.17 0.29 0.22 0.01 0.18 0.21 0.3 0.42 0.28 0.28 0.22 0.34 0.25 0.37 0.3 0.19

Fuel_Economy 0.13 0.29 1 0.25 0.1 0.12 0.21 0.09 0.02 0.03 0.22 0.22 0.09 0.01 0.09 0.17 0.09 0.31 0.22 -0.1

Power_Pickup 0.29 0.5 0.25 1 0.41 0.24 0.3 0.14 0.07 0.12 0.27 0.41 0.27 0.23 0.1 0.19 0.21 0.26 0.27 0.1

Color_of_Car 0.16 0.17 0.1 0.41 1 0.23 0.38 0.37 0.25 0.32 0.18 0.32 0.17 0.16 -0.1 -0 0.26 0.19 0.37 0.24

Chrome_Plated_Door_Handles 0.45 0.29 0.12 0.24 0.23 1 0.44 0.36 0.42 0.24 0.27 0.06 0.12 0.15 -0 -0.05 0.32 0.16 0.13 0.31

Fog_Light 0.38 0.22 0.21 0.3 0.38 0.44 1 0.52 0.36 0.46 0.07 0.13 0.38 0.39 0.35 0.18 0.24 0.19 0.15 0.15

Rear_View_Camera_Reverse_Gear_Sensor 0.25 0.01 0.09 0.14 0.37 0.36 0.52 1 0.29 0.45 0.13 0.03 0.51 0.35 0.18 0.16 0.29 0.19 0.28 0.23

Soft_Drink_Holder 0.55 0.18 0.02 0.07 0.25 0.42 0.36 0.29 1 0.44 0.4 0.27 0.25 0.17 0.15 0.12 0.37 0.25 0.2 0.47

Sleek_Gear_Shift_Knob 0.39 0.21 0.03 0.12 0.32 0.24 0.46 0.45 0.44 1 0.2 0.13 0.28 0.22 0.25 0.3 0.07 0.23 0.08 0.17

Audio_Video_System 0.53 0.3 0.22 0.27 0.18 0.27 0.07 0.13 0.4 0.2 1 0.3 0.15 0.2 0.16 0.1 0.29 0.25 0.12 0.32

Air_Conditioning_System 0.15 0.42 0.22 0.41 0.32 0.06 0.13 0.03 0.27 0.13 0.3 1 0.08 0.24 0.07 0.31 0.2 0.48 0.3 0.17

Inbuilt_Navigation_System 0.53 0.28 0.09 0.27 0.17 0.12 0.38 0.51 0.25 0.28 0.15 0.08 1 0.69 0.57 0.28 0.37 0.07 0.1 0.22

Anti_Brake_Skidding 0.39 0.28 0.01 0.23 0.16 0.15 0.39 0.35 0.17 0.22 0.2 0.24 0.69 1 0.68 0.29 0.2 0.07 0.06 0.26

Air_Bag 0.36 0.22 0.09 0.1 -0.1 -0.02 0.35 0.18 0.15 0.25 0.16 0.07 0.57 0.68 1 0.48 0.11 0.01 -0.1 0.09

Child_Lock_Rear_windows 0.17 0.34 0.17 0.19 0.00 -0.05 0.18 0.16 0.12 0.3 0.1 0.31 0.28 0.29 0.48 1 0.03 0.26 0.18 0.13

Car_Accessories 0.29 0.25 0.09 0.21 0.26 0.32 0.24 0.29 0.37 0.07 0.29 0.2 0.37 0.2 0.11 0.03 1 0.35 0.38 0.35

Easy_Access_Spare_Parts 0.15 0.37 0.31 0.26 0.19 0.16 0.19 0.19 0.25 0.23 0.25 0.48 0.07 0.07 0.01 0.26 0.35 1 0.65 0.33

Availabiility_Service_Station -0.1 0.3 0.22 0.27 0.37 0.13 0.15 0.28 0.2 0.08 0.12 0.3 0.1 0.06 -0.1 0.18 0.38 0.65 1 0.32

Free_Pickup_Drop_During_Service 0.38 0.19 -0.1 0.1 0.24 0.31 0.15 0.23 0.47 0.17 0.32 0.17 0.22 0.26 0.09 0.13 0.35 0.33 0.32 1

31 | P a g e

KMO and Bartlett’s Test

KMO-Bartlett measure of sampling adequacy is an index used to test appropriateness of the factor analysis.

Bartlett's test of sphericity is used to test whether the correlation matrix is an identity matrix. The test value

(1346) and the significance level (P<.01) which are given above indicate that the correlation matrix is not an

identity matrix, i.e., there exists correlations between the variables. Kaiser-Meyer-Olkin (KMO) measure of

sampling adequacy or KMO measure is more than 0.5, and then it is good to use factor analysis. If the KMO is

closer to 0, then the factor analysis is not a good idea for the variables and the data. The value of test statistics

is given above as 0.641, which means the factor analysis for the selected variables is found to be appropriate

to the data. The Principal Components Analysis (PCA) is used to extract factors. The PCA is a method used to

transform a set of correlated variables into a set of uncorrelated variables (here factors) so that the factors are

unrelated and the variables selected for each factor are related.

Communalities

Communality (h2): It shows how much each variable is accounted for by the underlying factor taken into

consideration.

It is the summation of factor loading squares on all factors extracted in case of a variable

External communalities are estimates of the variance in each variable accounted for by the components. The

communalities in the below table are moderately high, which indicates that the extracted components

represents the variables to a great extent.

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Initial ExtractionPrice 1.000 0.675

Suggestion_from_family 1.000 0.726

Family_Needs 1.000 0.494

Status_Symbol 1.000 0.698

Brand_Name 1.000 0.678

Comparison_of_Cars 1.000 0.781

Preference_Festive_Offer 1.000 0.717

Type_of_Fuel 1.000 0.722

Advice_from_Colleagues 1.000 0.635

Environment_Polution_ Norms 1.000 0.697

Advertisement_Promotion 1.000 0.692

Driving_Comfort 1.000 0.654

Resale_Value 1.000 0.635

Installament_Payment 1.000 0.689

Insurance_Facility 1.000 0.784

Extended_Warranty 1.000 0.684

Dealer_Location 1.000 0.720

All_Cars_Under_one_roof 1.000 0.611

Technology 1.000 0.744

Mobile_Charger 1.000 0.824

Road_Grip 1.000 0.762

Fuel_Economy 1.000 0.742

Power_Pickup 1.000 0.676

Color_of_Car 1.000 0.728

Chrome_Plated_Door_ Handle 1.000 0.732

Fog_Light 1.000 0.750

Rear_View_Camera_ Reverse_Gear_Sensor 1.000 0.765

Soft_Drink_Holder 1.000 0.736

Sleek_Gear_Shift_Knob 1.000 0.722

Audio_Video_System 1.000 0.723

Air_Conditioning_System 1.000 0.732

Inbuilt_Navigation_ System 1.000 0.764

Anti_Brake_Skidding 1.000 0.773

Air_Bag 1.000 0.882

Child_Lock_Rear_ Windows 1.000 0.683

Car_Accessories 1.000 0.720

Easy_Access_Spare Parts 1.000 0.721

Availabiility_Service Station 1.000 0.835

Free_Pickup_Drop_ During_Service 1.000 0.681

Extraction Method : Principal Component Analysis

Communalities

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Total Variance:

The below table explains the total variance contributed by each component. We can see from the below table

that the percentage of total variance contributed by first component is 20.809, by 2nd component is 8.519, by

3rd component is 6.917, by 4th component is 5.942, by 5th component is 5.061, by 6th component is 4.393, by 7th

component is 4.096, by 8th component is 3.816, by 9th component is 3.482, by 10th component is 3.179, by 11th

component is 2.853 and by 12th component is 2.694.

It is also very clear from the table that there are total 12 distinct components for the given set of variables.

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Scree Plot

The scree plot gives the number of components against the eigen values which helps to determine the

optimum number of components.

In the scree plot, the component having steep slope indicate that good percentage of the total variance

explained by that component and hence that component is justified. The components having less/shallow

slope indicates that the contribution of total variance is less and this component should not be justified.

In the above plot, the first 12 components have step slope and others have shallow slope. This indicates that

the ideal number of components is 12.

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Rotated Component Matrix

In the rotated factor/component matrix, it is important to identify the maximum value of the factors irrespective

of signs. The maximum in each row indicates that the respective variable belongs to the respective factor. In

the above table of rotation component matrix, the maximum value in each rows have been encircled in pink

colour. The encircled variables against each column are highly co-related to each other and can be given a

common name.

Grouping of Variables after Factorisation:

After finding the common variables against each factor, it is time to name the factors such that the revised

name can be used in place of those variables, which will represent all the grouped variables.

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Name of the Variable Factor Value Factor Number Factor Name

Instalment Payment 0.622

Factor No. 1 Value for Money

Insurance Facility 0.536

Mobile Charger 0.645

Chrome Plated Door Handles 0.553

Soft Drink Holder 0.699

Audio_Video System 0.695

Free_Pick up & Drop during service 0.521

Family Needs 0.563

Factor No. 2 Technology for Family Safety

Driving Comfort 0.723

Technology 0.585

Road Grip 0.689

Rear Window Child Lock 0.612

Inbuilt Navigation system 0.766

Factor No. 3Driver Safety and Ease of

NavigationAnti Brake Skidding (ABS) 0.808

Air Bag 0.864

Environment Pollution Norms 0.427

Factor No. 4 Customer Delight

Resale Value 0.567

Extended warranty 0.428

Dealer Location 0.770

All Cars under one roof 0.676

Easy access of Spare parts 0.704Factor No. 5 Any Time Any Where Service

Availability of Service Station 0.840

Preference during Festive Offer 0.421

Factor No. 6 Car UpholsteryFog Light 0.721

Rear View Camera & Reverse Gear Sensor 0.691

Sleek Gear Shift Knob 0.576

Status Symbol 0.714Factor No.7 Personality & Brand Status

Brand Name 0.802

Suggestion from Family 0.485

Factor No. 8 Aesthetics & Family ComfortPower & Pick Up 0.637

Colour of the Car 0.598

Air Conditioning System 0.546

Type of Fuel 0.645Factor No. 9 Fuel Sensitiveness

Fuel Economy 0.675

Advice from Colleagues 0.761Factor No. 10 Miscellaneous

Car Accessories 0.519

Comparison of Cars 0.816Factor No. 11

Market Study &

AdvertisementsAdvertisement and Promotions 0.486

Price 0.772 Factor No. 12 Price

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After having the factoring completed as above, we can redefine the observations with simple average method and the result is shown below.

Summary after Factorisation

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Respondent No.

Value for Money

Technology for Family Safety

Driver Safety and Ease of Navigation

Customer Delight

Any Time Any Where Service

Car Upholstery

Personality & Brand Status

Aesthetics & Family Comfort

Fuel Sensitiveness

Miscellaneous

Market Study & Advertisements

Price

1 2.14 2.00 3.00 2.20 1.00 2.50 2.50 1.50 1.50 2.50 2.00 2.002 2.86 2.40 2.33 2.80 2.00 3.00 2.00 1.75 1.50 2.00 1.50 1.003 3.71 2.80 3.33 2.80 2.00 3.00 2.50 2.25 2.00 2.50 2.00 1.004 1.14 1.20 1.33 2.00 1.00 1.00 2.00 1.75 1.50 1.50 1.50 2.005 1.29 1.20 1.33 2.00 1.00 2.25 2.00 1.50 1.50 2.50 1.50 1.006 1.86 1.40 2.33 2.20 1.00 2.00 2.00 1.50 1.00 1.50 1.50 2.007 2.00 1.00 2.00 1.80 1.00 2.50 2.50 1.50 1.50 2.50 1.50 2.008 1.14 1.20 1.00 1.20 1.00 1.50 1.50 1.50 1.50 2.00 2.50 2.009 2.00 1.80 3.00 1.80 2.00 2.00 2.00 1.75 2.00 2.50 2.50 2.00

10 2.57 1.80 1.67 2.40 2.00 2.25 2.50 2.00 1.50 2.50 2.00 2.0011 2.71 2.20 2.33 2.00 2.00 2.50 1.50 1.75 2.00 1.50 3.00 1.0012 2.29 1.40 3.00 2.20 1.00 2.50 1.50 1.75 1.00 2.00 1.50 1.0013 2.14 1.60 2.33 2.60 1.00 2.00 1.00 1.00 1.00 2.00 1.50 1.0014 2.29 2.00 2.00 2.20 2.00 2.50 2.50 2.25 2.00 2.00 2.50 2.0015 2.57 1.20 2.00 1.20 1.50 2.00 2.00 1.50 2.00 2.00 1.50 2.0016 3.00 2.00 3.00 3.20 1.50 2.50 2.00 1.25 1.50 1.50 1.50 1.0017 2.29 2.20 2.67 1.80 1.50 3.25 3.00 1.25 1.00 2.00 1.50 2.0018 2.29 1.80 2.33 2.20 2.00 2.25 2.50 1.75 1.50 2.00 2.00 5.0019 3.57 1.20 2.33 4.20 3.00 3.75 1.00 2.00 1.00 3.00 3.00 1.0020 3.00 2.40 3.00 4.20 2.00 3.50 3.00 2.25 2.00 2.50 2.50 1.0021 1.29 1.40 3.00 1.00 1.00 2.50 2.00 1.50 1.00 1.00 1.00 2.0022 1.86 1.00 3.00 1.40 1.00 2.00 2.00 1.25 1.00 1.00 2.00 1.0023 2.43 2.00 2.00 2.60 2.00 2.50 1.50 2.00 2.50 2.00 2.50 2.0024 2.14 1.80 3.00 2.80 1.00 2.75 3.50 2.00 1.50 1.50 1.00 1.0025 1.43 1.20 2.00 2.40 2.00 2.50 1.00 1.25 2.00 1.50 1.50 2.0026 2.71 2.00 3.00 2.60 1.50 3.50 2.50 2.00 2.00 2.00 2.50 2.0027 3.00 1.40 3.33 3.00 1.00 2.75 1.00 1.50 2.00 3.50 1.50 1.0028 2.14 1.20 2.67 3.40 1.00 3.50 2.50 1.25 1.00 1.00 2.50 1.0029 2.29 1.20 2.00 2.00 1.00 4.25 3.50 2.25 1.50 2.50 2.00 2.0030 1.57 1.40 1.33 2.60 2.00 2.75 2.50 1.50 1.50 2.00 2.50 2.0031 3.57 1.00 1.33 1.80 1.00 2.25 3.50 1.75 1.50 1.00 2.00 2.0032 1.43 1.40 1.00 1.80 1.00 1.50 1.00 1.50 1.50 2.00 1.50 1.0033 1.14 1.20 1.00 1.60 1.00 1.50 1.50 1.50 1.00 2.00 2.50 2.0034 2.86 2.00 2.00 2.80 2.00 2.75 2.00 2.00 1.00 2.50 1.50 1.0035 2.57 2.00 1.33 2.40 2.00 2.25 2.00 1.75 1.00 2.00 2.00 2.0036 1.57 1.40 3.00 1.60 1.00 2.25 3.00 1.50 1.00 1.00 1.50 4.0037 1.71 1.20 2.33 1.80 1.50 2.00 2.00 1.50 1.00 2.00 2.00 2.0038 2.29 1.60 2.00 2.20 1.00 2.00 1.50 2.00 1.50 2.00 2.50 1.0039 2.29 2.00 4.00 2.00 1.00 2.50 2.00 1.75 1.50 1.50 1.00 1.0040 3.57 1.60 4.00 3.60 1.00 3.00 2.00 1.75 2.50 2.00 2.50 2.0041 2.14 2.00 1.33 2.60 1.00 2.00 1.50 1.25 1.00 1.00 2.50 1.0042 2.29 1.40 3.00 3.40 1.00 2.25 3.00 1.00 2.00 3.00 2.50 2.0043 2.00 1.60 1.67 2.20 1.00 1.75 2.00 1.50 1.50 1.50 2.00 2.0044 1.57 1.60 2.33 2.00 1.00 2.50 1.50 1.25 1.00 1.50 1.50 1.0045 2.29 2.00 2.00 2.60 2.50 2.00 3.00 2.00 1.50 2.50 2.50 1.0046 2.14 1.00 1.00 2.00 1.00 2.25 2.00 1.25 1.00 1.50 2.00 3.0047 1.57 1.00 1.00 1.40 1.00 2.25 2.00 1.25 1.00 2.00 1.50 3.0048 2.71 1.60 1.33 1.80 1.00 3.25 2.50 1.50 1.00 2.00 1.50 2.0049 1.71 1.20 1.33 1.60 1.00 2.25 2.00 1.50 1.50 1.50 2.00 1.0050 3.14 1.80 2.67 2.40 2.00 3.25 2.00 2.00 1.00 2.50 2.50 2.0051 3.57 2.00 2.00 3.40 1.50 3.00 2.50 2.00 2.00 2.50 2.00 2.0052 2.43 2.00 2.00 2.00 1.50 2.00 3.00 2.00 1.50 2.00 2.50 2.0053 2.00 1.20 2.33 1.80 1.00 2.50 3.50 1.75 2.00 3.00 2.50 1.0054 3.00 1.00 3.00 1.80 1.00 2.50 1.50 1.50 1.00 1.00 2.00 1.0055 2.14 1.40 1.00 1.80 1.00 1.75 1.00 1.25 1.50 1.50 1.50 1.0056 1.86 1.40 2.33 1.40 2.00 1.75 1.00 2.00 1.00 1.50 1.50 1.0057 2.14 1.40 2.00 1.60 2.00 1.75 2.50 1.50 1.00 1.50 1.00 2.0058 2.71 1.00 1.00 2.20 2.00 2.25 2.00 1.75 1.00 1.50 2.00 2.0059 2.00 1.40 1.33 2.60 1.00 2.00 1.00 1.50 1.50 2.00 2.50 1.0060 2.14 1.60 1.33 2.20 1.50 2.25 2.00 2.00 2.00 2.00 2.00 2.0061 2.43 1.00 1.67 1.20 1.00 2.25 2.00 1.00 2.00 1.00 1.50 2.0062 1.14 1.60 1.33 1.80 1.00 2.25 4.00 1.50 1.50 1.50 2.50 2.0063 3.43 2.20 2.00 1.80 1.00 2.25 2.00 1.50 1.50 1.50 2.50 1.0064 2.57 1.40 1.33 3.20 1.00 2.50 1.50 1.25 1.00 1.50 2.00 4.0065 3.71 1.80 1.33 3.60 2.00 3.25 2.00 2.75 1.50 2.00 2.50 2.0066 2.00 2.20 1.33 2.60 1.50 2.25 2.00 2.25 1.50 2.00 1.50 2.0067 3.14 1.40 1.67 4.20 2.00 3.25 3.00 1.25 3.00 2.00 1.50 1.0068 1.43 1.00 1.67 1.20 1.00 2.25 3.00 1.25 1.00 2.00 4.00 1.0069 2.71 1.40 1.67 1.60 1.50 2.25 1.50 1.75 1.50 2.00 2.00 1.0070 4.43 1.20 2.00 3.40 1.00 2.75 2.50 1.50 1.50 3.50 1.50 1.0071 2.43 2.00 2.33 2.40 2.00 2.50 2.00 1.75 2.00 2.00 2.00 1.00

Cluster Analysis

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Cluster is a group of similar objects (cases, points, observations, examples, members, customers, patients,

locations, etc) Cluster Analysis is a set of data-driven partitioning techniques designed to group a collection of

objects into clusters, such that the number of groups (clusters) as well as their forms are unknown the degree

of association or similarity is strong between members of the same cluster is weak between members of

different clusters. The nature of Cluster Analysis is data exploration that conducted in repetitive fashion.

Clusterization is not a single grouping, but the process of getting well interpretable groups of objects under

consideration.

Cluster Analysis classifies objects e.g. respondents, products or entities so that each object is very similar to

others within the cluster with respect to some predetermined selection criterion or variable specified.

The resulting clusters of objects exhibit high internal (within the cluster) homogeneity and high external

(between the cluster) heterogeneity.

The objective is to classify a sample of entries into a small number of mutually exclusive clusters based on the

premise that they are similar within clusters but dissimilar among clusters.

Following demographic features are used for the cluster analysis.

Demographic Feature

Scale

1 2 3 4 5 6

Total Income in Rs < 5 Lakhs 5 – 10 Lakhs 10 – 15 Lakhs 15 – 20 Lakhs >20 Lakhs -

Age 18 – 24 Yrs 25 – 34 Yrs 35 – 44 Yrs 45 – 54 Yrs 55 – 64 Yrs >65 Yrs

Education Level Diploma Graduate Post Graduate PhD - -

Marital Status Single Married Widowed Divorced - -

Occupation Service Business Student House Wife - -

Dendrogram

A dendrogram is a tree-structured graph used in heat maps to visualize the result of a hierarchical clustering

calculation. The result of a clustering is presented either as the distance or the similarity between the clustered

rows or columns depending on the selected distance measure.

From the below Dendrogram, we can make it out which are those Indian consumers, which can be

clubbed/clustered into 4 type of cluster based on the 5 factors that has been considered for cluster analysis.

With a scale of 15 on dendrogram these are:-

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Cluster-1

Cluster-3

Cluster-4

Cluster-2

Description Sample Size

Srl. No. of the Respondents in the specific Cluster

Cluster-1 3665,71,1,47,58,34,45,4,20,61,67,7,66,42,53,24,43,5,22,23,12,13,29,70,55,33,68,69,44, 60,11,63,41,46,2,52

Cluster-2 319,50,64,10,16,56,37,54,19,17,14,27,49,18,26,25,57,15,36,40,21,28,35,8,39,48,38,51,3, 6,32

Cluster-3 2 59,62

Cluster-4 2 30,31

Descriptive Statistics : The below table gives descriptive statistics for the dependent variables for each

of the clusters, whose short summary is shown below.

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Interpretation :Demographic Profile : On the demographic profiles considered, there is distinct observation

among the 4 clusters as found through cluster analysis, as mentioned below.

Cluster No. Demographic Profile Observation Remarks

Cluster-1

Total Income Above 15 Lakhs

Age Between 25 – 64 Years Most between 35 – 44 Years

Education Level Graduates & Post Graduates Few are at PhD Level

Marital Status Most are Married Few are Single

Occupation Mostly in Service Very Few have own Business

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Cluster No. Demographic Profile Observation Remarks

Cluster-2

Total Income Between 5 - 15 Lakhs Few between 15 – 20 Lakhs

Age Most between 25 – 44 Years Few between 45 – 54 Years

Education Level Mostly Graduates Few are Diploma & Post Graduates

Marital Status Most are Married Few are Single

Occupation Mostly in Service Very Few have own Business

Cluster-3

Total Income Between 5 - 15 Lakhs

Age All are between 25 – 44 Yrs

Education Level All are having PhD

Marital Status All are Married

Occupation All of them are in Service

Cluster-4

Total Income Between 10 - 20 Lakhs

Age All are between 45 – 54 Yrs.

Education Level All are having Diploma

Marital Status All are Married

Occupation All of them are in Service

Other Behavioural Profile: From the descriptive as shown in previous pages, we can interpret the

consumer behaviour profile from the descriptive as mentioned below for each of these 4 different type of

clusters.

Cluster No.

Observations

1 Highly Price Conscious & strongly agree that price, Fuel Economy and Air Conditioning

system is important influencing factor

They agree on taking suggestions from their family & colleagues before purchase of the car

and family need is equally important.

Neutral on Status symbol & Chrome plated door handles. However agree on the fact that

Brand name is important for car.

Agree on the fact that they compare the cars before buying and neutral on the fact that they

prefer to buy the cars during festive or promotional offers.

Agree on the type of fuel to be used and also on the environmental / pollution norms before

purchase of the car.

Purchase decision is Neutral on advertisement/promotions, Instalment Payment &

availability of Mobile charger, soft drinks holder in the car

Agree on the fact that Technology, Driving comfort, Road Grip, Power & Pick Up, Resale

value, Colour of the Car, Fog Lights, Rear View Camera & Reverse Gear Sensor, Sleek

Gear Shift Knob, High Quality Audio/Video System, Inbuilt navigation system, ABS, Air

Bags, Child Lock Rear Windows, Insurance Facility, Extended warranty and free pick up

and drop during servicing are important factor on car purchase

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Almost neutral on the fact that Car Dealer should be nearby and all cars must be under one

roof for deciding which car to purchase

Very strongly agree on the fact that availability of spare parts and nearby service station is

an important factor that need to be considered before purchase of the car.

Cluster No.

Observations

2

Agree that price, taking suggestions from their family members/colleagues, family needs

and preference to buy cars during festive or promotional offers are important.

Agree of the fact that Status symbol, Brand name is important for car.

Strongly agree on the fact that they compare the cars before buying.

Strongly agree that fuel economy and Power & Pick Up are important to be considered

before deciding on the car purchase. This is supported by that fact that this group is

relatively younger group in age who believes in power & pick up combined with very good

fuel economy.

Agree on the type of fuel to be used and also on the environmental / pollution norms before

purchase of the car.

Purchase decision is Neutral on advertisement/promotions, availability of Mobile charger,

Chrome plated door handles, Fog Lights, Rear View Camera & Reverse Gear Sensor,

Sleek Gear Shift Knob, Inbuilt navigation system and soft drinks holder in the car

Agree on the fact that Instalment Payment, Technology, Driving comfort, Road Grip, Resale

value, Colour of the Car, High Quality Audio/Video System, Air Conditioning System, ABS,

Air Bags, Child Lock Rear Windows, Insurance Facility, Extended warranty, Near By Dealer

Location and free pick up and drop during servicing are important factor on car purchase

Almost neutral on the fact that all cars must be under one roof for deciding which car to

purchase

Almost very strongly agree on the fact that availability of spare parts and nearby service

station is an important factor that need to be considered before purchase of the car.

Cluster No.

Observations

3 Strongly agree that family needs, Environmental / Pollution norms, Technology, Fuel

Economy, Power & Pick Up, ABS, Air Bags and Child Lock for Rear Windows are very

important influencing factor that need to be considered before purchase of the car.

Disagree with the fact that Status symbol, preference during festive or promotional offers,

availability of soft drinks holder in the car are important factor that need to be looked into

during purchase of the car.

Neutral with facts on Brand name, Advertisement & Promotions, Near By Dealer Location,

all cars must be under one roof, availability of Mobile charger, Chrome plated door handles,

Rear View Camera & Reverse Gear Sensor and Sleek Gear Shift Knob.

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Agree on the fact that they compare the cars before buying and sensitive about type of fuel

to be used in the car before purchase.

Purchase decision is Neutral on availability of High Quality Audio/Video System and free

pick up and drop during servicing.

Agree on the fact that Price, taking suggestions from their family members/colleagues,

Instalment Payment, Driving comfort, Road Grip, Resale value, Colour of the Car, Fog

Lights, Air Conditioning System, Inbuilt navigation system, Insurance Facility, availability of

spare parts and nearby service station and Extended warranty are important factor on car

purchase.

Cluster No.

Observations

4

Strongly agree that family needs, Instalment Payment, Insurance Facility, Road Grip, Fuel

Economy, Power & Pick Up, Fog Lights, Air Conditioning System, ABS and Air Bags are

very important influencing factor that need to be considered before purchase of the car.

Disagree with the fact that, preference during festive or promotional offers, Advertisement &

Promotions, Near By Dealer Location, all cars must be under one roof are important factor

that need to be looked into during purchase of the car.

Neutral with facts on Status symbol, availability of soft drinks holder in the car are factors of

consideration during purchase decision of the car.

Agree on the fact that they compare the cars before buying and sensitive about

Environmental / Pollution norms and type of fuel to be used in the car before purchase.

Agree on the fact that Price, Technology, Brand name, taking suggestions from their family

members/colleagues, Driving comfort, availability of Mobile charger, Resale value, Colour of

the Car, Chrome plated door handles, Rear View Camera & Reverse Gear Sensor, Sleek

Gear Shift Knob, High Quality Audio/Video System, Inbuilt navigation system, Child Lock for

Rear Windows, availability of and free pick up and drop during servicing and Extended

warranty are important factor on car purchase.

Almost very strongly agree on the fact that availability of spare parts and nearby service

station is an important factor that need to be considered before purchase of the car.

Suggestions

1. The respondents perceive that Fuel Economy, Availability of nearby Service station are the most important

features of the passenger car followed by availability of spare parts, Technology, Family Needs, Child Lock

for the Rear Windows and price of the car, thus the manufacturers should design the product giving

maximum weightage to these factors.

2. Experts believe the main driver of the Indian car market is the availability of car finance on easy instalments

and reasonable interest rates. Most of the respondents also reported that due to the easy availability of

finance they buy cars. So the car dealers should have tie-up arrangements with the authorized financial

institutions to boost sales.

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3. Most of the respondents preferred to have the Air Bags and Anti Brake Skidding feature in the car which is

meant for safety of the Driver. Mostly, in the salarised class in India the driver is the key bread owner of the

family and safety for the owner of the car is having much of importance. Hence, the Govt. of India as well as

all manufacturer’s need to seriously think of making ABS and Air Bags as a must feature in all cars in line

with European countries.

4. The study reveals that the middle class population has risen to 13 per cent of the total population. Hence

the brand image and brand loyalty could be boosted by selling quality cars at a reasonable price to suit the

needs of the middle income group.

5. Car owners feel that the hospitality shown by the dealers is more during their visits to the places of dealers

before and immediately after the purchase. But after some time they face a problem with their dealers

regarding after sales service. Therefore, it is suggested that the services rendered or to be rendered should

be properly explained, friendly approach and reliability in service are to be further improved.

Conclusion

Consumer Behaviour consists of all human behaviour that goes in making purchase decisions. An

understanding of the consumer behaviour enables a marketer to take marketing decisions which are

compatible with its consumer needs. There are four major classes of consumer behaviour determinants and

expectations, namely, cultural, socio-economic, personal and psychological. The socio-economic determinants

of consumer behaviour consist of age, marital status, occupation, education, income, family size etc. Realizing

the importance of passenger car industry in the present economic situation, the researcher has analyzed the

perceptions, and behaviour of consumers related to this product. It is rightly said; yesterday‟s luxuries are

today‟s necessities. Hence in this digital world, car is no longer a luxury. From the discussions made in the

previous chapters, there are certain product attributes which are identified in the study as influencing the

purchase decision and satisfying the consumers. The growth in the population of India and the increasing

number of middle class consumers has attracted the attention of car manufacturers and marketers. The

manufacturers and marketers who study the behaviour of consumers and cater to their needs will be

successful. It may be concluded that consumer behaviour has a greater role to play in the LPG era of

economic activities for which a necessary survey and research should be conducted in an efficient manner.

The study shows that brand perception is something which starts building up before a car is purchased and

goes on with its use and is reflected in the recommendations the customer makes to his acquaintances for the

same car. Also, its seen that the customer might not be using the car still he holds the perceptions about it.

Brand personality of a car is enforced by the sellers in the mindsets of the customers and the customers react

to it by forming their perceptions about the car and this reflects in the overall brand image of the car. So brand

image and brand personality complement each other and the brand perception aids the building of brand

image.

Since dealers are the connecting link between the customers and the manufacturers thus becoming the most

important link in joining the company to its customers as he is the person who will sell the product, will deliver it

and will keep on providing the after sales services to the customers as and when required.

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So, it becomes necessary automatically to study dealer as a part of customers’ satisfaction journey with the

product called car! Their proximity to the customers, the service provided by them and the relationship

maintained by them with the customers helps the car companies to establish and reinstate the brand

personality communicated by them to the customers.

Finally the major point that emerges out of this detailed study is a caution for the car companies. It says that

there is no doubt that Indian car market may be growing with a double digit figure still the car companies have

a long way to travel to convince their customers about the brand personality of their cars and how it suits the

prospective buyers. Simply because it simply is not a guarantee that how so ever good the customer might be

holding the brand perception and how so ever good the brand image may be it is not a guarantee that it will

convert into sale. Cars just like clothes and accessories suit the style and persona of a person and since all

cars will become commodity someday the key to sell and excel in the market will lie with a person who knows

how to use the perceptions of the customers to its use and sell the cars ‘coz ultimately only that car survives

which sells!

References :

1. www.siamindia.com2. www.autocarindia.com3. www.overdrive.com4. www.indiastat.com5. Chidambaram and Alfread „A Study on Brand Preference of Passenger Car with Reference to Coimbatore City‟,

Indian Journal of Marketing, Vol.34, No.9, September 2007, p.30. 6. Churchill, Gilbert A., and Carol Suprenant, „An Investigation into the Determinants of Customer Satisfaction‟,

Journal of Marketing Research, 14th November 1982, p.54. 7. Clement Sudhakar J., and Venkatapathy R., „A Study on Automobile Purchase – Peer Influence in Decision

Making‟, Indian Journal of Marketing, Vol.35, No.6, June 2009, p.16. 8. Furse, David H, Girish N. Punj and David W.Stewart, “A Typology of Individual search strategies among

purchasers of New Automobiles”, Journal of Consumer Research, Vol.10, March 1984, p.43. 9. Gaedebe, R (2007), “Consumer Attitude towards Cars Made in Developing Countries”, Journal of Retailing, 49

(summer), pp. 13 – 24.10. Joseph W. Newman, Richard Stalin, „Pre-purchase Information seeking for New Cars and Major Household

Appliances‟, Journal of Marketing Research, Vol. IX, August 1972, p.20. 11. Joseph W. Newman, Richard Werbel, „Automobile Brand Loyalty‟, Journal of the Academy of Marketing

Science, Vol. 2 (4), (Fall), 1974, p.19.

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Annexure-A:

Consumer Behaviour in India for Car Purchase

According to you, which of these factors are affecting Car Purchasing Decision in India.

Q1 Price is one of the most important factor for purchase decision

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q2 You take Suggestions from your family Members before selecting the car

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q3 Family Needs is important for you

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q4 You purchase the car for Status Symbol

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q5 Brand Name is Important for Buying the car

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

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Q6 You compare various cars before buying

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q7 You prefer to buy the car during Festival Season / Promotional Offers

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q8 You give importance to Type of Fuel used by the car i.e. Diesel/Petrol/Electric

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q9 You take Advice of from your Friends / Colleagues

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q10 You are very particular about Environmental / Pollution norms and regulations what the car conforms

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q11 You also look for Advertisements And Promotions of the car before purchase

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

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Q12 Driving Comfort is one of the factor you look for

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q13 Resale Value is a factor for consideration before car purchase

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q14 Selection of Car is influenced by Installment Payment Facility

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q15 Selection of Car is influenced by Insurance Facility

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q16 Your selection is also influenced by Extended Warranty feature as offered by manufacturers

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q17 Location Of The Car Dealer Shop is important to you as well

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

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Q18 You would like to have Availability Of Variety Of Cars Under One Roof before buying

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q19 You look out for the available Technology

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q20 Mobile Charger Port is important to you

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q21 Road Grip is important to you

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q22 You check Mileage / Fuel Economy before purchase of the car

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q23 You check & compare for Power and Pick Up before purchasing the car

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

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Q24 The Colour of the Car is important for you

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q25 You prefer to have Chrome Plated Door Handles in your car

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q26 You will look out for Fog Lights option as well

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q27 Your selection of car depends upon availability of Rear View Camera and Reverse Gear Sensor

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q28 Your selection of car depends upon availability of Soft Drinks Holder near Driver

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q29 Your selection of car depends upon availability of Sleek Gear Shift Knob

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

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Q30 Your selection of car depends upon availability of Good Audio/Video System

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q31 Your selection of car depends upon availability of Air Conditioning System

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q32 Your selection of car depends upon availability of In Built Navigation System

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q33 You will give importance to availability of Anti Brake Skidding (ABS) in the car

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q34 You will give importance to availability of Air Bags in the car

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q35 Your selection of car depends upon availability of Child Locks for the Rear Windows

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

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Q36 Other Car Accessories are important aspects of your selection of car

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q37 Easy Availability Of Spare Parts is important factor for your car selection

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q38 Availability of Service Station in the vicinity is equally important factor for car selection

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q39 You prefer to have Free Pick up & Drop during Servicing

Strongly Agree (1) Agree (2) Neutral (3) Disagree (4) Strongly Disagree (5)

Q40 Which region of the country do you live in?

East (1) West (2) North (3) South (4) Central (5)

Q41 What is your approx. total income before taxes?

Less than 5 Lakhs (1) Between 5 - 10 Lakhs (2) Between 10 - 15 Lakhs (3) Between 15 - 20 Lakhs (4) > 20 Lakhs (5)

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Q42 What is your age?

18 - 24 Years (1) 25 - 34 Years (2) 35 - 44 Years (3) 45 - 54 Years (4) 55 - 64 Years (5) Above 65 Years (6)

Q43 What is your education level?

Diploma (1) Graduate (2) Post Graduate (3) PhD (4)

Q44 What is your marital status?

Single (1) Married (2) Widowed (3) Divorced (4)

Q45 What is your gender?

Male (1) Female (2)

Q46 What is your Occupation?

Service (1) Business (2) Student (3) House Wife (4)

Q47 Which type of Organisation you are working?

Private (1) Public (2) Government (3) Others (4)

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