Car Purchase - Srishti Srivastava and Vayam Sood
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Marketing Research Project
A study of purchase criteria and relevance of consumerperception in the Indian Car Market
Srishti Srivastava - 50171
Vayam Sood - 50187
BBS II E
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ACKNOWLEDGEMENT
We would like to convey our heartfelt thanks to our teacher, Dr Preeti Rajpal
Singh, whose encouragement; guidance and support from the initial to thefinal level enabled us to develop an understanding of the subject and
successful completion of our project.
We would like to express our gratitude towards the members of Shaheed
Sukhdev College of Business Studies for their kind co-operation and
encouragement which helped us in completion of this project.
Lastly, yet importantly, we offer our regards and blessings to all those who
supported us in any respect during the completion of the project.
Srishti Srivastava
Vayam Sood
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TABLE OF CONTENTS
EXECUTIVE SUMMARY _____________________________________________________________ 4
INDIAN AUTO INDUSTRY ____________________________________________________________ 5
OBJECTIVE _______________________________________________________________________ 6
METHODOLOGY __________________________________________________________________ 7
RESEARCH DESIGN ________________________________________________________________________ 7
DATA COLLECTION ________________________________________________________________________ 7
SAMPLING PLAN __________________________________________________________________________ 7
DATA ANALYSIS TECHNIQUE ________________________________________________________________ 7
CARS PROFILE____________________________________________________________________ 8
CAR MODELS _____________________________________________________________________________ 8
CAR MODELS _____________________________________________________________________________ 9
FINDINGS _______________________________________________________________________ 11
RESPONDENT PROFILE ____________________________________________________________________ 11
OWNERSHIP OF CAR(S) ____________________________________________________________________ 13
STATEMENT AGREEMENT OR DISAGREEMENT _______________________________________________ 17
CHI SQUARE ANALYSIS ____________________________________________________________ 21
Analysis 1: Brand Value v/s Age _____________________________________________________________ 21
Analysis 2: Price v/s Income ________________________________________________________________ 22
Analysis 3: Promotional Scheme v/s Profession ________________________________________________ 23
Analysis 4: Mileage v/s Gender _____________________________________________________________ 24
Analysis 5: Comfort v/s Age ________________________________________________________________ 25
Analysis 6: Safety Features v/s Age __________________________________________________________ 26
Analysis 7: Design v/s Gender ______________________________________________________________ 27
Analysis 8: Dealer Proximity v/s Profession ____________________________________________________ 28
Analysis 9: Finance Scheme v/s Income _______________________________________________________ 29
Analysis 10: Accessories v/s Age ____________________________________________________________ 30
Analysis 11: Maintenance Cost v/s Profession _________________________________________________ 31
Analysis 12: Resale Value v/s Income ________________________________________________________ 32
LIMITATIONS ____________________________________________________________________ 33
CONCLUSION ____________________________________________________________________ 34
BIBLIOGRAPHY __________________________________________________________________ 35
ANNEXURE _____________________________________________________________________ 36
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EXECUTIVE SUMMARY
The automobile industry today is the most lucrative industry. Due to the
increase in disposable income in both rural and urban sector and easy financebeing provided by all the financial institutes, the passenger car sales have
increased over the years. Passenger Vehicles segment grew at 4.66 % during
April-March 2012 over same period last year. For the first time in history, car
sales crossed two million in 2011-12. However, competition is heating up in the
sector with a host of new players coming in and other like Porsche, Bentley,
Audi, and BMW penetrating into the Indian markets.
The development in automobile sector overhauls the perception of potentialcar buyers, with their increased disposable income, enormous information
search, and availability of lucrative financial options. People today are more
pragmatic before acquiring the automobile. For most people, purchasing a car
is one of the most important and expensive investment, next to purchase of a
house.
This report attempts to answer some of the questions regarding buying
behaviour of customers by conducting the market research. The buyingbehaviour of the customers has been studied by knowing their perceptions
about the cars in the market and about the possible entrants in the market.
The questionnaires were administered through an online survey as well as
personal in-home interviews. Other approaches used for analysis were cross-
tabs and chi-square analysis. These statistical tools were used with the help of
MS-Excel and SPSS. The analysis from these tools helped gather useful insights
upon the type of respondents, attributes the consumers consider while makingthe purchase decision and how the consumers perceive the various brands.
The market research will be helpful for the new car entrant companies in India
to find out the possible gaps between the customer expectations and the
present market offerings. This way these companies will be able to find their
share in the ever-expanding Indian market pie.
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INDIAN AUTO INDUSTRY
India is emerging as one of the worlds fastest growing passenger car markets.
The Indian passenger vehicle market, which constitutes around 80% ofautomobile sales, has immense growth potential as Society of Indian
Automobile Manufacturers (SIAM) has projected a growth of 10-12 per cent
for 2012-13.
Rising per capita income and the changing demographic distribution are
conducive for growth. India has the highest proportion of population below 35
years (70% potential buyers). The total automobile industry in India is 10
million vehicles per annum. Passenger cars contribute to approximately 16% of
the total automobile sales. The total automobile sales have been witnessinghealthy double-digit growth, however, this year it posted a slow growth of 7%.
The passenger car industry in India is very competitive with almost every
prominent global manufacturer being present in the country. There are 18
passenger vehicle manufacturers as listed below:
Maruti Suzuki Hyundai
Tata Motors Fiat
Chevrolet Ford
Honda Toyota
Mahindra & Mahindra BMW
Skoda Mercedes Benz
Hindustan Motors Nissan
Volkswagen Audi
Volvo Porsche
Maruti Suzuki is the leading passenger car manufacturer in India with a market
share consistently above 50% over the last few years followed by Hyundai and
Tata Motors.
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OBJECTIVE
PRIMARY OBJECTIVE
The objective is to analyse the car buying criteria of individuals based on
the demographic differences such as age group, gender, income and
profession.
SECONDARY OBJECTIVES
To ascertain various options of cars available in the Indian market.
To determine the various factors affecting the purchase of cars. To determine the brand preferences for cars among different
demographic factors.
To determine the positioning of various brands in the minds of
consumers.
To determine the relative importance of various functionalities attached
to numerous features and specifications of cars.
To know the overall perception of customers about cars.
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METHODOLOGY
RESEARCH DESIGN
A research design is a logical and systematic plan prepared for directing a
research study. It is the program that guides the investigator in the process of
collecting, analysing and interpreting observations. Here descriptive research
design is used for analysing buying motive of cars. It is very simple and more
specific than exploratory study. The descriptive study is a fact finding
investigation with adequate interpretation. It reveals potential relationships
between variables and also setting the stage for further investigation later.
DATA COLLECTION
Primary data are collected on original information gathered for a specific
purpose and secondary data is collected from already existing sources
Primary Data The study has used survey method for collecting the
primary data by conducting online survey as well as personal in-house
interviews.
Secondary Data Secondary data for the study were collected from the
websites of different brands to know their unique selling propositions,
SIAM, technical and subject based books, journals and magazines
SAMPLING PLAN
The samples for survey were being taken on the following basis.
Sample Frame: People residing or working in Delhi
Sample Unit: Students, working professionals and business persons
Sample Size: 207 respondents
Time Frame: 10-15 Days. Sampling Method: Simple random sampling (SRS)
DATA ANALYSIS TECHNIQUE
The data collected from the descriptive research provided us with the different
factors that a consumer looks for while purchasing a car. To evaluate whether
the preferences are different for various demographical factors, we have used
chi-square analysis with crosstab. These various techniques would be carried
out the help of MS-Excel and SPSS.
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CARS PROFILE
CAR MODELS
The passenger car industry in India offers the following car models:
1. Hatchback Cars
Hatchback car is a small passenger car
consisting of a full-height door at the rear
that also includes a window and used from
behind to access the cargo and luggage
space. These kinds of cars have two rows of
seats. In India the hatchback is the most competitive car segment.
2. Sedan Cars
Sedan is a car model with passenger carrying
capacity of four or more persons having two
rows of seats and two or four doors with a
separate trunk or boot at the rear side.
Sedan cars, carrying high price tag with
them, are featured with host of luxury
features like high-end entertainment system, integrated steering wheel,high class leather work, classy looks, contemporary and fully efficient
security features.
3. Sports Utility Vehicle (SUV)
Sports Utility Vehicle is a vehicle that
combines loading capability of a pickup truck
and has passenger carrying space that is of a
mini-van. These types of vehicles are famous
for their sturdy looks, strong on road
presence and carry much powerful engine
with high torque. SUVs are designed to run in any kind of terrain.
4. Multi Utility Vehicle (MUV)
The Multi Utility Vehicle is a kind of
automobile which is taller than a sedan and
hatchback and provides larger interior space
through their removable seats.
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CAR MODELS
1. Maruti Udyog
Synonymous with cars in India, Maruti Udyog Limited is the ranked as a top
passenger car manufacturing company in the country. The company since its
inception in 1981 has changed the face of the Indian four wheeler scenario.
With the introduction of the Maruti 800, Maruti Udyog became the most
trusted automobile company in India. Some of Maruti's most popular cars are:
Alto Omni Gypsy
A-Star Wagon R Swift
2. Ford India
Established in 1995, Ford India is a wholly owned subsidiary of Ford Motor
Company, a global automotive industry leader. Ford India manufactures and
distributes automobiles and engines. The company's popular models include:
Endeavour Fiesta Figo
3. Tata Motors
The name that leads the list of major car manufacturers in India is Tata Motors.
Originally called TELCO (TATA Engineering and Locomotive Company), Tata
Motors Limited is the largest automobile manufacturing company in India.
Apart from being the top heavy vehicle manufactures the company is also the
third largest passenger car manufacturer in India. Some of the well-known cars
manufactured by Tata Motors are:
Indigo Indica Nano
Safari Vista
4. Hyundai Motors India
Hyundai Motor Company of South Korean entered the India automobile
market in 1996. Among the top car manufacturing companies in India today,
Hyundai Motors is the company that has almost revolutionized the face of the
hatchback car segment in India. Some of the important models by Hyundai
Motors plying the Indian roads today are:
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Accent Santro i10 i20
5. Honda Siel Cars India
Honda Siel Cars India Limited was established in 1995. A joint venture between
Japanese automobile giants Honda Motor Co Ltd and Siel Limited, with the
promise of providing high order technological assistance to Honda motors for
their passenger cars segment meant for Indian consumers. Known for its series
of luxury and premium cars in India this company is among the major car
manufacturers of India. Some of its well-known models are:
City Accord Jazz Civic
6. Toyota
Toyota is one of the biggest vehicle manufacturers, and one of the most widely
known companies, in the world today. Rising from the ashes of industrial
upheaval in post-war Japan, Toyota has become the largest vehicle
manufacturer in Japan with over 40% market share and expanding its
operations in over 160 countries. Its popular models in India are:
Etios Corolla Fortuner Innova
7. Fiat Automobiles India
Among the major car manufactures in India Fiat Automobiles India Limited is a
joint venture between Tata Motors and the Italian giants Fiat Group
Automobile. Having over 100 years of experience in the automobile segment
this company is known for its series of strong and well built cars. Some of the
popular cars manufactured by Fiat Automobiles India Limited include:
Palio Punto Uno Linea
8. Chevrolet
Chevrolet is an American brand founded by Chevrolet and ousted GM founder
William C. Durant in 1911. In India, Chevrolet is not just a car. It is a name that
evokes memories of the dawn of Indias motoring; it is an icon of glamour and
style. Some of its popular models are:
Spark Beat Aveo Cruze
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FINDINGS
RESPONDENT PROFILE
AGE
Below 20 89
20-30 78
30-40 15
40-50 16
Above 50 9
TOTAL 207
Our sample had respondents from all age groups though the majority sampleof43% and 38% were from Below 20 years and 20 30 years.
GENDER
Female 78
Male 129
TOTAL 207
43%
38%
7%8% 4%
AGE
Below 20
20-30
30-40
40-50
Above 50
38%
62%
GENDER
Female
Male
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We did a survey on 207 people with 38% females and 62% males. Though
more males were surveyed, the responses collected have perceptions attached
with both the genders.
PROFESSIONStudent 123
Service 47
Business 37
TOTAL 207
Our survey consisted of students, service people and business professionals;
however, our survey was dominated by students consisting of 59% of the
sample.
INCOME
Below 3 lacs 85
3 6 lacs 41
6 10 lacs 29
10 15 lacs 32
Above 15 lacs 20
TOTAL 207
59%23%
18%
PROFESSION
Student
Service
Business
41%
20%14%
15%
10%
INCOME
Below 3 lacs
3 6 lacs
6 10 lacs
10 15 lacs
Above 15 lacs
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As evident the majority of the sample of41% is in the income bracket ofBelow
3 lacs annual income. But since there are respondents from other income
brackets also, this enables the study to be wide and not dependent on a set
income class.
OWNERSHIP OF CAR(S)
NO. OF CARS OWNED
0 27
1 68
2 53
3 32
4 and Above 27TOTAL 207
This pie chart shows number of cars owned by respondents. Out of 207
respondents, 13% did not own a car, 33% and 26% owned one and two cars
respectively. But only 15% and 13% owned 3 cars and 4 cars or more.
BRANDS OWNED
Maruti Suzuki 95Ford 33
Tata 29
Hyundai 86
Toyota 31
Honda 56
Other(s) 48
The graph shows the brand of the car owned by the respondents. It is clearly
visible that most of them own a Maruti Suzuki (95) or Hyundai (86) car while a
13%
33%
26%
15%
13%
NO. OF CARS OWNED
0
1
2
3
4 and Above
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few own a Tata (29), Ford (33) or Toyota (31) passenger cars. Also 48
respondents own other(s) brands, mostly of luxury brands like BMW and Audi.
TYPE OF CAR OWNED
Hatchback 117
Sedan 153
SUV 76
MUV 32
From the above pie chart, it can be concluded that most people - 41% own a
sedan while 31% own a hatchback. But a lesser percentage of people own a
SUV or MUV.
0 20 40 60 80 100
Maruti Suzuki
Ford
Tata
Hyundai
Toyota
Honda
Other(s)
95
33
29
86
31
56
48
BRANDS OWNED
31%
41%
20%
8%
TYPE OF CAR OWNED
Hatchback
Sedan
SUV
MUV
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LAST PURCHASE
Less than 6 months 47
6 months 1 year 28
1 year 2 years 24
2 years or more 82
This pie chart shows when the respondent bought their latest car. Out of those
who possess a car, 26% bought their car within the last 6 months while most
people, 45%, bought their cars at least 2 years back.
PURPOSE OF BUYING CARFor Everyday Use 96
As a Family Car 70
As a Gift 15
The above graph shows the reason for which the respondent bought their
latest car. While 53% and 39% bought it for everyday use and as a family car
respectively, just 8% bought it as a gift.
26%
16%
13%
45%
LAST PURCHASE
Less than 6
months
6 months 1 year
1 year 2 years
2 years or more
53%39%
8%
PURPOSE OF BUYING CAR
For Everyday Use
As a Family Car
As a Gift
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MONTHLY KILOMETERS DRIVEN
0 500 kms 59
500 1000 kms 64
1000 1500 kms 41
1500 kms or more 43
The above pie chart depicts the average monthly kilometres driven by the
respondent. About 28% and 31% drove from 0 500 kms and 500 1000 kms
respectively. But just 20% and 21% drove their cars for 1000 -1500 kms and
more than 1500 kms.
PREFERRED FUEL
Petrol 88
Diesel 74
CNG 45
TOTAL 207
Out of 207 respondents, 42% chose Petrol cars while 36% prefer Diesel Cars
and only 22% select CNG as their preferred fuel.
28%
31%
20%
21%
MONTHLY KILOMETERS
DRIVEN
0 500 kms
500 1000 kms
1000 1500 kms1500 or more
42%
36%
22%
PREFERRED FUEL
Petrol
Diesel
CNG
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PURCHASE CAR IN NEXT ONE YEAR
Definitely 102
Probably 53
Unsure 34
Probably Not 13Definitely Not 5
TOTAL 207
We can clearly observe from the above chart, that 49% will definitely buy a car
within this year, 26% will probably buy while 17% are unsure.
STATEMENTAGREEMENT OR DISAGREEMENT
Car design is more important than practicality
Out of 207 respondents, 80 disagreed with the statement while 83 agreed to it.But 44 neither agreed nor disagreed to it.
49%
26%
17%
6% 2%
PURCHASE CAR IN NEXT ONE
YEAR
Definitely
Probably
Unsure
Probably Not
Definitely Not
0
10
20
30
40
50
60
70
Strongly
Agree
Agree Neither
Agree nor
Disagree
Disagree Strongly
Disagree
32
51
44
69
11
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Performance is more important than mileage
121 respondents go along with the statement while 42 disagree to it, and just
44 are unsure about it. This indicates that performance of a car is more
important than the mileage.
Diesel cars require more maintenance than petrol
Apart from 57 respondents, 121 fall in with the statement while 29 disagree to
it. Hence mostly people believe that diesel cars require more maintenance
than petrol cars.
0
10
20
30
40
50
60
70
80
StronglyAgree
Agree NeitherAgree nor
Disagree
Disagree StronglyDisagree
43
78
44
32
10
0
10
20
30
40
50
60
70
80
Strongly
Agree
Agree Neither
Agree nor
Disagree
Disagree Strongly
Disagree
47
74
57
20
9
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Diesel cars are worth the extra premium they command
With the ever rising petrol prices, most of the respondents (121) consider the
extra premium diesel cars command, are worth it.
Only petrol cars are performance oriented
The typecast of petrol cars being performance oriented is slowly fading as
evident with the above chart as 89 respondents disagree to the statement
while 59 neither agree nor disagree.
0
10
20
30
40
50
60
70
80
90
Strongly
Agree
Agree Neither
Agree nor
Disagree
Disagree Strongly
Disagree
39
82
56
21
9
0
10
20
30
40
50
60
Strongly
Agree
Agree Neither
Agree nor
Disagree
Disagree Strongly
Disagree
16
43
59
52
37
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Owning a sedan is a status symbol
With the rise in the number of people owning a sedan, mostly respondents,
144, believe that owning a sedan car is a status symbol. Just 23 respondents
disagree with it.
Driving dynamics are more important than comfort
Out of 207 respondents, 124 are in flow with the statement while 49 are
against it. It is evident that driving dynamics is certainly considered more
important than comfort of the car.
0
10
20
30
40
50
60
70
80
StronglyAgree Agree NeitherAgree nor
Disagree
Disagree StronglyDisagree
67
77
40
15
8
0
10
20
30
40
50
60
70
80
90
Strongly
Agree
Agree Neither
Agree nor
Disagree
Disagree Strongly
Disagree
42
82
34
41
8
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CHI SQUARE ANALYSIS
Analysis 1: Brand Value v/s Age
H0: The age group has no significant impact on importance of brand value at
confidence level of 95%.
H1: The age group has a significant impact on importance of brand value at
confidence level of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
age * brandvalue 207 100.0% 0 .0% 207 100.0%
age * brandvalue Crosstabulation
brandvalue
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
age 1 Below 20 18 44 19 5 3 89
2 20
30 20 41 11 4 2 78
3 30 - 40 6 5 1 0 3 15
4 40 - 50 5 6 3 0 2 16
5 Above 50 6 1 0 0 2 9
Total 55 97 34 9 12 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 31.084a 16 .013
Likelihood Ratio 30.343 16 .016
Linear-by-Linear Association .115 1 .735
N of Valid Cases 207
a. 16 cells (64.0%) have expected count less than 5. The minimum expected count is .39.
At 95% confidence level, since Chi-Square observed is greater than the critical
value of 26.296, we reject the null hypothesis indicating that there is significantrelationship between age group and the importance of brand value.
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Analysis 2: Price v/s Income
H0: The income has no significant impact on importance of price at confidence
level of 95%.
H1: The income has a significant impact on importance of price at confidencelevel of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
income * price 207 100.0% 0 .0% 207 100.0%
income * price Crosstabulation
price
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
income 1 Below 3
lacs28 39 14 0 4 85
2 3 - 6 lacs 21 18 2 0 0 41
3 6 - 10 lacs 4 21 4 0 0 29
4 10 - 15 lacs 9 15 1 2 5 32
5 Above 15
lacs6 2 7 0 5 20
Total 68 95 28 2 14 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 59.730a 16 .000
Likelihood Ratio 58.044 16 .000
Linear-by-Linear Association 10.998 1 .001
N of Valid Cases 207
a. 12 cells (48.0%) have expected count less than 5. The minimum expected count is .19.
At 95% confidence level, since Chi-Square observed of 59.730 is greater than
the critical value of 26.296, we reject the null hypothesis indicating that there
is significant relationship between income and the importance of price.
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Analysis 3: Promotional Scheme v/s Profession
H0: The profession has no significant impact on importance of promotional
scheme at confidence level of 95%.
H1: The profession has a significant impact on importance of promotionalscheme at confidence level of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
profession * promotion 207 100.0% 0 .0% 207 100.0%
profession * promotion Crosstabulation
promotion
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
profession 1 Student 10 23 43 47 0 123
2 Service 9 9 13 12 4 47
3 Business 5 4 12 8 8 37
Total 24 36 68 67 12 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 32.390a 8 .000
Likelihood Ratio 32.890 8 .000
Linear-by-Linear Association .533 1 .465
N of Valid Cases 207
a. 3 cells (20.0%) have expected count less than 5. The minimum expected count is 2.14.
At 95% confidence level, since Chi-Square observed of 32.390 is greater than
the critical value of 15.507, we reject the null hypothesis indicating that there
is significant relationship between profession and the importance of
promotion scheme.
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Analysis 4: Mileage v/s Gender
H0: The gender has no significant impact on importance of mileage at
confidence level of 95%.
H1: The gender has a significant impact on importance of mileage at confidencelevel of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
gender * mileage 207 100.0% 0 .0% 207 100.0%
gender * mileage Crosstabulation
mileage
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
gender 1 Female 24 30 15 2 7 78
2 Male 50 57 10 5 7 129
Total 74 87 25 7 14 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 7.702a 4 .103
Likelihood Ratio 7.492 4 .112
Linear-by-Linear Association 2.994 1 .084
N of Valid Cases 207
a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 2.64.
At 95% confidence level, since Chi-Square observed of 7.702 is less than the
critical value of 9.488, we accept the null hypothesis indicating that there is no
significant relationship between gender and the importance of mileage.
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Analysis 5: Comfort v/s Age
H0: The age has no significant impact on importance of comfort at confidence
level of 95%.
H1: The age has a significant impact on importance of comfort at confidencelevel of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
age * comfort 207 100.0% 0 .0% 207 100.0%
age * comfort Crosstabulation
comfort
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
age 1 Below 20 38 37 14 0 0 89
2 20 30 31 34 10 3 0 78
3 30 - 40 5 5 5 0 0 15
4 40 - 50 8 7 1 0 0 16
5 Above 50 3 1 2 0 3 9
Total 85 84 32 3 3 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 78.668a 16 .000
Likelihood Ratio 32.643 16 .008
Linear-by-Linear Association 5.444 1 .020
N of Valid Cases 207
a. 15 cells (60.0%) have expected count less than 5. The minimum expected count is .13.
At 95% confidence level, since Chi-Square observed of 78.668 is greater than
the critical value of 26.296, we reject the null hypothesis indicating that there
is significant relationship between age and the importance of comfort.
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Analysis 6: Safety Features v/s Age
H0: The age has no significant impact on importance of safety features at
confidence level of 95%.
H1: The age has a significant impact on importance of safety features atconfidence level of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
age * safety 207 100.0% 0 .0% 207 100.0%
age * safety Crosstabulation
safety
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
age 1 Below 20 33 32 23 1 0 89
2 20 30 24 31 19 2 2 78
3 30 - 40 4 6 1 2 2 15
4 40 - 50 8 6 1 1 0 16
5 Above 50 3 4 0 0 2 9
Total 72 79 44 6 6 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 36.284a 16 .003
Likelihood Ratio 30.444 16 .016
Linear-by-Linear Association .857 1 .355
N of Valid Cases 207
a. 15 cells (60.0%) have expected count less than 5. The minimum expected count is .26.
At 95% confidence level, since Chi-Square observed of 36.284 is greater than
the critical value of 26.296, we reject the null hypothesis indicating that there
is significant relationship between age and the importance of safety features.
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Analysis 7: Design v/s Gender
H0: The gender has no significant impact on importance of design at confidence
level of 95%.
H1: The gender has a significant impact on importance of design at confidencelevel of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
gender * design 207 100.0% 0 .0% 207 100.0%
gender * design Crosstabulation
design
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
gender 1 Female 25 36 9 3 5 78
2 Male 45 46 27 7 4 129
Total 70 82 36 10 9 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 5.408a 4 .248
Likelihood Ratio 5.497 4 .240
Linear-by-Linear Association .000 1 .989
N of Valid Cases 207
a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 3.39.
At 95% confidence level, since Chi-Square observed of 5.408 is less than the
critical value of 9.488, we accept the null hypothesis indicating that there is no
significant relationship between gender and the importance of design.
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Analysis 8: Dealer Proximity v/s Profession
H0: The profession has no significant impact on importance of dealer proximity
at confidence level of 95%.
H1: The profession has a significant impact on importance of dealer proximityat confidence level of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
profession * dealer 207 100.0% 0 .0% 207 100.0%
profession * dealer Crosstabulation
dealer
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
profession 1 Student 11 22 42 36 12 123
2 Service 6 9 14 10 8 47
3 Business 11 5 9 8 4 37
Total 28 36 65 54 24 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 13.206a 8 .105
Likelihood Ratio 11.584 8 .171
Linear-by-Linear Association 2.908 1 .088
N of Valid Cases 207
a. 1 cell (6.7%) has expected count less than 5. The minimum expected count is 4.29.
At 95% confidence level, since Chi-Square observed of 13.206 is less than the
critical value of 15.507, we accept the null hypothesis indicating that there is
no significant relationship between profession and the importance of dealer
proximity.
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Analysis 9: Finance Scheme v/s Income
H0: The income has no significant impact on importance of finance scheme at
confidence level of 95%.
H1: The income has a significant impact on importance of finance scheme atconfidence level of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
income * finance 207 100.0% 0 .0% 207 100.0%
income * finance Crosstabulation
finance
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
income 1 Below 3 lacs 10 24 39 8 4 85
2 3 - 6 lacs 12 12 13 2 2 41
3 6 - 10 lacs 0 11 14 3 1 29
4 10 - 15 lacs 5 6 10 7 4 32
5 Above 15 lacs 6 5 1 4 4 20
Total 33 58 77 24 15 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 37.059a 16 .002
Likelihood Ratio 41.750 16 .000
Linear-by-Linear Association 1.614 1 .204
N of Valid Cases 207
a. 10 cells (40.0%) have expected count less than 5. The minimum expected count is 1.45.
At 95% confidence level, since Chi-Square observed of 37.059 is greater than
the critical value of 26.296, we reject the null hypothesis indicating that there
is significant relationship between income and the importance of finance
scheme.
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Analysis 10: Accessories v/s Age
H0: The age has no significant impact on importance of accessories at
confidence level of 95%.
H1: The age has a significant impact on importance of accessories at confidencelevel of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
age * accessories 207 100.0% 0 .0% 207 100.0%
age * accessories Crosstabulation
accessories
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
age 1 Below 20 25 29 26 9 0 89
2 20 30 23 10 29 14 2 78
3 30 - 40 3 4 7 1 0 15
4 40 - 50 3 10 3 0 0 16
5 Above 50 3 2 1 0 3 9
Total 57 55 66 24 5 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 64.203a 16 .000
Likelihood Ratio 43.805 16 .000
Linear-by-Linear Association .607 1 .436
N of Valid Cases 207
a. 16 cells (64.0%) have expected count less than 5. The minimum expected count is .22.
At 95% confidence level, since Chi-Square observed of 64.203 is greater than
the critical value of 26.296, we reject the null hypothesis indicating that there
is significant relationship between age group and the importance of
accessories.
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Analysis 11: Maintenance Cost v/s Profession
H0: The profession has no significant impact on importance of maintenance
cost at confidence level of 95%.
H1: The profession has a significant impact on importance of maintenance costat confidence level of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
profession * maintenance 207 100.0% 0 .0% 207 100.0%
profession * maintenance Crosstabulation
maintenance
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
profession 1 Student 37 53 21 6 6 123
2 Service 28 15 1 2 1 47
3 Business 14 10 7 2 4 37
Total 79 78 29 10 11 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 19.537a 8 .012
Likelihood Ratio 21.298 8 .006
Linear-by-Linear Association .095 1 .758
N of Valid Cases 207
a. 4 cells (26.7%) have expected count less than 5. The minimum expected count is 1.79.
At 95% confidence level, since Chi-Square observed of 19.537 is greater than
the critical value of 15.507, we reject the null hypothesis indicating that there
is a significant relationship between profession and the importance of
maintenance cost.
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Analysis 12: Resale Value v/s Income
H0: The income has no significant impact on importance of resale value at
confidence level of 95%.
H1: The income has a significant impact on importance of resale value atconfidence level of 95%.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
income * resale 207 100.0% 0 .0% 207 100.0%
income * resale Crosstabulation
resale
Total
1 Extremely
Important
2 Very
Important
3 Somewhat
Important
4 Not Very
Important
5 Not At All
Important
income 1 Below 3 lacs 7 26 28 18 6 85
2 3 - 6 lacs 16 10 10 4 1 41
3 6 - 10 lacs 10 11 8 0 0 29
4 10 - 15 lacs 4 8 6 7 7 32
5 Above 15 lacs 7 3 7 1 2 20
Total 44 58 59 30 16 207
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 45.212a 16 .000
Likelihood Ratio 50.091 16 .000
Linear-by-Linear Association .660 1 .416
N of Valid Cases 207
a. 8 cells (32.0%) have expected count less than 5. The minimum expected count is 1.55.
At 95% confidence level, since Chi-Square observed of 45.212 is greater than
the critical value of 26.296, we reject the null hypothesis indicating that there
is significant relationship between income and the importance of resale value.
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LIMITATIONS
Research was conducted within a constrained sample of respondents
mainly the students of various colleges. The study was limited to the geographical area of Delhi, therefore the
results cannot be generalised.
Unequal distribution of both the genders.
The result generated out of the study is completely dependent on the
nature of the response given by the customers.
Short span of time was a limiting factor.
Customer satisfaction varies from time to time. It will not remain
constant.
The chances of respondents filling the questionnaire hastily are high.
Despite these limitations, a sincere attempt has been made to collect and
analyse the data and present the information as accurately as possible.
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CONCLUSION
The market research survey was undertaken in Delhi on a sample size of 207,
and the responses were analysed indicating the buying behaviour of customersand their perceptions about the cars in the market.
Through our findings in this report, we have figured out various important
factors through consumers for passenger cars can be segmented. Among the
respondents, Maruti Suzuki and Hyundai cars are a favourite buy with a
majority owning a sedan car considering their luxurious looks, good mileage
and great range
According to our sample, mostly people purchase a car for everyday use with
average monthly kilometres driven in the range of 500 -1000 kms. Most of
them are currently using petrol cars and definitely plan to purchase a new car
within this year.
Upon further study, we observed that in India, owning a sedan car is more of a
status symbol. Performance of the cars and driving dynamics are considered
more crucial than the mileage and comfort respectively. However, respondents
were divided over choosing car design over practicality. They also believe that
diesel cars command extra premium for maintenance, however, it is
considered worth due to the exorbitant petrol prices.
With the help of chi square analysis, it was found that with the change in
demographic factors, the various consumer patterns for passenger cars also
change. The following results were found:
Young people give great importance to brand value, comfort and
accessories while older people are indifferent about it.
With increase in income, people are less concerned about the price,
finance scheme available and resale value of cars
According to profession, the importance of promotional scheme and
maintenance cost changes. While students and service class people pay
a lot of importance, business professionals are not concerned.
Dealer proximity, design and mileage do not vary with profession and
gender respectively.
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BIBLIOGRAPHY
www.google.com www.siamindia.com
www.autocarindia.com
www.ibef.org
www.yahoo.com
www.wikepedia.org
www.indiamarks.com
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ANNEXURE
QUESTIONNAIRE
Dear Sir / Maam
We, the students of Shaheed Sukhdev College of Business Studies, Delhi University are conducting a
survey on CONSUMERS PERCEPTION OF Car Purchasing Criteria as a part of our Business Research
project. We, therefore, request you to spare some of your time to fill this questionnaire. We assure
you that the information provided by you will be kept confidential and used for academic purposes
only.
1. Name :
2. Age : Below 20 20 30 30 40 40 50 Above 50
3. Gender : Male Female
4. Profession : Business Service Student
5. Annual Family Income : Below 3 lakhs 3 6 lakhs 6 10 lakhs
10 15 lakhs Above 15 lakhs
6. How many car/cars do you currently own?
None 1 2 3 4 More than 4
Please skip questions 7 12 if you do not own a car
7. What is/are the brand/brands of your car/cars?
Maruti Suzuki Ford Tata
Hyundai Toyota Honda
Other(s)
8. Which type of car/cars do you own?
Hatchback Sedan SUV MUV
9. When did you last purchase a car?
Less than 6 months 6 months 1 year 1 year 2 years 2 years or
more
10.For what purpose did you buy your latest car?
For everyday use As a family car As a gift
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11.What are your average monthly kilometres driven?
0 500 500 1000 1000 1500 1500 or more
12.What type of fuel do you prefer?
Petrol Diesel CNG
13.Do you wish to purchase a car in the next one year?
Definitely Probably Unsure Probably Not Definitely Not
14.Please rate the following features on the basis of their importance while buying a car :
extremely
important
very
important
somewhat
important
not very
important
not at all
important
Brand Value
Price
Promotional Schemes
Mileage
Comfort
Safety Features
Design
Dealer Proximity
Finance Scheme
Accessories
Maintenance Cost
Resale Value
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15.Please state whether you agree or disagree :
strongly
agreeagree unsure disagree
strongly
disagree
Car design is more
important than
practicality
Performance is more
important than mileage
Diesel cars require
more maintenance
than petrol
Diesel cars are worth
the extra premium they
command
Only petrol cars are
performance oriented
Owning a sedan is astatus symbol
Driving dynamics are
more important than
comfort
Thank You!
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