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On the partial fulfillment of 3rdTri-semester ofPOST GRADUATE DIPLOMA IN BUSINESS MANAGEMENT

AT

INSTITUTE OF MANAGEMENT STUDIES, Ghaziabad

We the following students submit our report entitled

:: FACTORS AFFECTING CAR BUYING BEHAVIOUR OF

CUSTOMERS::

Under the esteemed guidance of Prof. Manish Agarwal

ACADEMIC SESSION

200!200"

:: S#b$i%%&d T' :: :: S#b$i%%&d B( ::

Dr. Manish Agarwal !"##$ D%&%T '(3)*

TAMO+A! AD%T$A '(,*

TAU+ /UMA '(,0*

1%2$A+ '()*

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AC*NO+LEDGEMENT

This report bears the imprint of man4 people and without their support it would

not ha=e e>isted. press our sincere indebt ness and

profound sense of gratitude to our parents whose support in all manners had made

us capable to complete this pro9ect.

We ac5nowledge our deepest than5s toP'-. Ma/ih A1aa3 for all

her care and encouraging words and gi=ing suggestion at different point of times.

At the outset we would li5e to put on record our sincere gratitude to all of our

friends for gi=ing us =aluable ideas throughout of our pro9ect.

hell4 Di>it'(3)*Tamonash Adit4a '(0(*

Tarun /umar '(03*1ig4an '()*

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I/%'d#4%i'/

According to the ninth annual ?apgemini automoti=e stud4 @ Cars Online 07/08. "ach 4ear

the4 e>tend the scope and depth of their sur=e4 to e>plore new and e=ol=ing trends within theretail side of the automoti=e industr46 with a particular focus on consumer bu4ing habits. Cars

Online 07/08 continues the detailed anal4sis of the changing patterns of consumer demand6

shopping trends6 web usage and customer lo4alt4 that we ha=e unco=ered o=er the past eight

4ears. This 4ear6 howe=er6 we ha=e broadened the scope to e>plore in greater detail

en=ironmental issues6 including fuel-efficient and alternati=e-fuel =ehicles6 as well as consumer

use of new online tools6 such as web logs6 discussion forums and search engines. These

additional areas of focus reflect changes in toda4s automoti=e landscape. The industr4 is

clearl4 in transition6 with static sales in almost all de=eloped mar5etsB growing pressure from

Asian manufacturersB eroding customer lo4alt4B and increased emphasis on en=ironmental and

regulator4 compliance. ?onsumer beha=iour will be a primar4 force in determining how this

transition will e=ol=e. 2etting closer to the customer in toda4s highl4 competiti=e landscape is

essential for the entire industr4 and is no longer 9ust a retail issue. %t reCuires all organisations

across the suppl4 chain to wor5 as a single enterprise6 sensing and responding rapidl4 to

consumer demand in a co-ordinated manner.

?apgeminis annual Cars Online stud4 is designed to gi=e automoti=e companies information

that can help them get a better grasp on changing consumer trends6 shopping patterns and

demands. This 4ears research in=ol=ed almost 76, consumers in fi=e countries; ?hina6

ecuti=e summar4 pro=ides an o=er=iew of5e4 findings from the stud46 and the sections that follow offer more in-depth data and anal4sis

on consumer beha=iour6 en=ironmental issues6 web usage6 lead management and customer

lo4alt4. The automoti=e world toda4 is changingB consumers are changing. And the speed of

change is continuing to accelerate.

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E5&4#%i6& S#$$a(

?ompetiti=e pressures and increasing comple>it4 ha=e led automoti=e companies to loo5 for an

edge where=er the4 can find it. %mpro=ed consumer insight into =ehicle shopping and bu4ingbeha=iour can pro=ide that =aluable ad=antage. ?apgeminis Cars Online report contains insight

that can help =ehicle manufacturers and dealers de=elop and e>ecute more effecti=e strategies in

areas such as sales6 mar5eting and ad=ertising6 after sales ser=ice6 ?ustomer elationship

Management '?M* and manufacturerdealer collaboration.

AUTOMOBILE INDUSTRY IN INDIA

In India there are 100 people per vehicle, while this figure is 82 in China. It is expected thatIndian automobile industry will achieve mass motoriation status by 201!.

I/d#%( O6&6i&

ince the first car rolled out on the streets of Mumbai 'then :omba4* in ()8)6 the Automobile

%ndustr4 of %ndia has come a long wa4. During its earl4 stages the auto industr4 was o=erloo5ed

b4 the then 2o=ernment and the policies were also not fa=orable. The liberaliEation polic4 and

=arious ta> reliefs b4 the 2o=t. of %ndia in recent 4ears has made remar5able impacts on %ndian

Automobile %ndustr4. %ndian auto industr46 which is currentl4 growing at the pace of around ()

F per annum6 has become a hot destination for global auto pla4ers li5e 1ol=o6 2eneral Motors

and ception to it. With the growth of transportation s4stem the Automoti=e %ndustr4 of

%ndia is also growing at rapid speed6 occup4ing an important place on the Gcan=asG of %ndian

econom4.

Toda4 %ndian automoti=e industr4 is full4 capable of producing =arious 5inds of =ehicles and

can be di=ided into 3 broad categories; ?ars6 two-wheelers and hea=4 =ehicles.

S/i77&%

The first automobile in %ndia rolled in ()8 in :omba4.

%ndia is being recogniEed as potential emerging auto mar5et.

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Unli5e the UA6 the %ndian passenger =ehicle mar5et is dominated b4 cars '8F*.

Tata Motors dominates o=er ,F of the %ndian commercial =ehicle mar5et.

73rd of auto component production is consumed directl4 b4 O"Ms.

%ndia is the largest three-wheeler mar5et in the world.

%ndia is the largest two-wheeler manufacturer in the world.

%ndia is the second largest tractor manufacturer in the world.

%ndia is the fifth largest commercial =ehicle manufacturer in the world.

The number one global motorc4cle manufacturer is in %ndia.

%ndia is the fourth largest car mar5et in Asia - recentl4 crossed the ( million mar5.

S&1$&/% */' h'

Among the two-wheeler segment6 motorc4cles ha=e ma9or share in the mar5et. !ero !onda

contributes 0F motorc4cles to the mar5et. %n it !onda holds H,F share in scooter andT1

ma5es )7F of the mopeds in the countr4.

HF of the three-wheelers are used as goods transport purpose. Piaggio holds HF of the

mar5et share. Among the passenger transport6 :a9a9is the leader b4 ma5ing ,)F of the three-

wheelers.

?ars dominate the passenger =ehicle mar5et b4 8F.MarutiuEu5ihas 07F share in passenger

cars and is a complete monopol4 in multi purpose =ehicles. %n utilit4 =ehiclesMahindraholds

H7F share.

%n commercial =ehicle6 Tata Motorsdominates the mar5et with more than ,F share. Tata

Motors is also the worldGs fifth largest medium I hea=4 commercial =ehicle manufacturer.

Mi4&33a/&'#

!4derabad6 the !i-Tech ?it46 is going to come up with the first automobile mall of the countr4

b4 the second half of 7). %t would be set up b4 cit4-based Pra9a4 "ngineers 4ndicate in area

of more than 30 acres. This GAutopolisG would ha=e facilities for automobile financinginstitutions and insurance ser=ices to create a complete range of ser=ices reCuired for both auto

companiesand customers. %t will also ha=e a multi-purpose con=ention centre for auto fairs and

product launches.

Ca b( Pi4& Ra/1&

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U/d& R. 8 La9h

Maruti )6 Alto6Omni

e=a

R. 8! La9h

Ambassador

ster6 ?a4enne6 8(( ?arrera I ?a4man

To4ota Prado

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Ab'6& R. ; C'&

:entle4 Arnage6 :entle4 ?ontinental 2TI

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Ma

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A/%i4i7a%i/1 C'/#$& Cha/1&

What do these findings tell usK The4 ma5e it clear that consumer beha=iour is e=ol=ing and that

automoti=e companies need to anticipate this e=olution in order to be part of6 or e=en influence6

the changes. %s 4our compan4 read4K What changes will 4ou need to ma5eK ?ompanies will

need to ta5e a loo5 at their multi-channel approach as the4 consider the potential mar5et for

online sales. "ffecti=e web strategies will be =itall4 important6 as the online landscape e=ol=es

rapidl4 with the emergence of powerful consumer-to-consumer tools li5e blogs6 discussion

forums6 social networ5ing sites and =irtual worlds. Automoti=e companies will need to sta4

focussed on en=ironmental de=elopments and e=ol=ing consumer attitudes about fuel-efficient

and alternati=e-fuel =ehicles. As with the web6 green issues are d4namic and its still too earl4

to determine their ultimate impact on the automoti=e industr4. Manufacturerdealer

collaboration in the form of effecti=e retail integration and integrated lead management will

become more important than e=er to satisf4 increasingl4 sophisticated and demanding

consumers and to retain lo4alt4. And companies will need to establish and maintain a true two-

wa4 dialogue with indi=idual customers through personalised communication. While this

topline re=iew pro=ides a summar4 of 5e4 findings from this 4ears Cars Online stud46 the

sections that follow offer more in-depth data and anal4sis of consumer beha=iour6

en=ironmental issues6 web usage6 lead management and customer lo4alt4.

C'/#$& B&ha6i'#: T#/i/1 %' %h& +&b a/d N& C2C T''3

?onsumers toda4 ha=e a multitude of sources from which to gather information during the

=ehicle bu4ing process6 but the %nternet tops the list. The web has become a standard resource in

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the shopping process for eight out of ( consumers when researching car purchases. !owe=er6

the wa4 the4 use it is changing. As the web matures6 =ehicle bu4ers are =isiting fewer sites and

focussing more on manufacturer and ?7? websites and less on third-part4 information sites and

independent e-tailer sties.

Ma/#-a4%#& Si%& a *&( I/-'$a%i'/ S'#4&

Lust two 4ears ago6 information websites were identified as the number one information sourceb4 web users responding to the Cars Online sur=e4 'tied with famil4 and friends andmanufacturer specific dealer*6 named b4 00F of consumers. This 4ear6 the4 dropped to thenumber four source6 named b4 H(F of web users. %n comparison6 manufacturer sites are nowthe top source for consumers who use the web when researching =ehicles6 named b4 F ofrespondents. Two 4ears ago manufacturer sites held the number three position6 named b4 H3Fof web users. The use of dealer websites has remained stead46 with about half of web users

turning to these sites.

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At the same time6 the use of new online consumer-to-consumer tools such as blogs6 'eall4

imple 4ndication* feeds6 user-generated content6 social networ5ing sites and web forums is

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growing. %n this 4ears stud46 78F of web users indicated that the4 use these 5inds of tools

when researching during the =ehicle shopping process6 up from 7(F a 4ear ago. 'ample6 which has shown a stead4

downward trend particularl4 among consumers who rel4 on the web during the =ehicle

shopping process. This 4ear6 9ust 7F of web users said the4 use

print ads when researching =ehicles6 compared with 37F in 70. The message for automoti=e

companies is clear; ?onsumers trust the information the4 recei=e from manufacturer and ?7?

sites. 1ehicle manufacturers and dealers need to be aware of how fast online changes are

occurring and continuall4 ad9ust their mar5eting mi> and resources accordingl4 to anticipate

tomorrows mi>. Mar5eting funds directed toward more traditional media such as print

ad=ertising should be regularl4 re-e>amined for O%.

*&( Fa4%' i/ V&hi43& Ch'i4&

When it comes to ma5ing their final decision about which =ehicle to bu46 consumers focus on

factors such as reliabilit46 safet46 price and fuel econom4. At the bottom of the list are cash-bac5

incenti=es6 named b4 fewer than half of consumers. The importance of incenti=es as a deciding

factor has declined for the past se=eral 4ears6 indicating that consumers toda4 seem less

interested in gimmic5s when it comes to their car purchases. Where consumers are in the bu4ing

c4cle can ma5e a difference in how the4 ran5 the factors that influence their =ehicle choice. ample6 additional warrant4 co=erage is important to consumers who are furthest awa4 from

the point of purchaseB it was named b4 ,8F of respondents who were (3 to () months from

purchase. !owe=er6 the number declines as consumers get closer to actuall4 bu4ing the car;

00F of respondents who were within three months of purchase said e>tra warrant4 co=erage

was important. This reflects the fact that consumers will narrow down the factors that reall4

matter to them as the4 get closer to the point of purchase. Demographic factors such as age and

gender accounted for some =ariances. ample6 older consumers tend to put more emphasis

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on reliabilit4 and safet4 than do 4ounger respondents. Those in the 0-plus age group were also

more concerned with en=ironmental issues and fuel econom4. The 4oungest respondents were

most li5el4 to rate the abilit4 to research information on the %nternet as an important factor in

their =ehicle decision. Women tend to rate most of the factors as more important than do men.

The difference was most pronounced for cash-bac5 incenti=es6 low financing6 safet46

en=ironmental issues6 fuel econom4 and additional warrant4 co=erage.

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G'i/1 =G&&/>: F#&3 E--i4i&/4( Ta9& C&/%& S%a1&

pected to continue to grow. ample6 L.D. Power and Associates predicts that

U.. sales of h4brid =ehicles will increase b4 30F in 76 compared with 7,.

?urrent ownership of fuel-efficient and alternati=e-fuel =ehicles tended to be Cuite consistent

across gender and age groups6 although the oldest consumers were somewhat more li5el4 to be

seriousl4 thin5ing about bu4ing an alternati=e-fuel car.

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+h( B#( a G&&/ V&hi43&?

credits

and cost factors were less important. ome consumers pointed to less tangible reasons such as

it ma5es me feel better.N This is in line with research conducted b4 ?+W Mar5eting esearch.

When as5ed wh4 the4 bought a To4ota Prius6 0F of Prius owners said because it ma5es a

statement about me.N !owe=er6 the Cars Online research unco=ered some differences in the

reasons behind consumer decisions about green =ehicles. ample6 "uropean consumers

were more li5el4 to cite en=ironmental impact as a primar4 factor6 while more respondents in

?hina and the U.. pointed to fuel econom4. Older consumers were somewhat more li5el4 to

identif4 fuel econom4 as a primar4 factor6 compared with the 4oungest respondents '()-3H*.

Men put more emphasis than did women on fuel econom46 while a higher proportion of women

identified en=ironmental impact as the primar4 reason dri=ing their decisions about green

=ehicles.

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PERSONAL SELLING:

CONSUMER BUYING BEHAVIOR

CONSUMER BUYING 6. ORGANI)ATIONAL BUYING

Fi/a3 @' #3%i$a%& 4'/#$& 7#4ha& -':

personal6

famil46 or

household use

O1a/iza%i'/a3 4'/#$& 7#4ha& -':

further production6

usage in operating the organiEation6 andor

resale to other consumers

C'/#$& B#(i/1 B&ha6i'

The decision processes and acts of final household consumers associated with e=aluating6

bu4ing6 consuming6 and discarding products for personal consumption

?onsider the purchase an automobile. $ou generall4 will not consider different options until

some e=ent triggers a need6 such as a problem needing potentiall4 e>pensi=e repair. Once this

need has put 4ou on the mar5et6 4ou begin to as5 4our friends for recommendations regarding

dealerships and car models. After =isiting se=eral dealerships6 4ou test dri=e se=eral models and

finall4 decide on a particular model. After pic5ing up 4our new car6 4ou ha=e doubts on the wa4

home6 wondering if 4ou can afford the monthl4 pa4ments6 but then begin to wonder if instead4ou should ha=e purchased a more e>pensi=e but potentiall4 more reliable model. O=er the ne>t

fi=e 4ears6 the car has se=eral une>pected brea5downs that lead 4ou to want to purchase a

different brand6 but 4ou ha=e been =er4 happ4 with the ser=ices of the local dealership and

decide to again purchase 4our ne>t car there.

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%n this particular case6 the followinggeneric model of consumer decision ma"ingappears to

hold;

/&&d &4'1/i%i'/

i/-'$a%i'/ &a4h

&6a3#a%i'/ '- a3%&/a%i6&

7#4ha& d&4ii'/

7'%7#4ha& b&ha6i'

+ow consider the purchase of a Cuart of orange 9uice. $ou purchase this product when 4ou do

4our grocer4 shopping once per wee5. $ou ha=e a fa=orite brand of orange 9uice and usuall4 do

4our grocer4 shopping at the same store. When 4ou bu4 orange 9uice6 4ou alwa4s go to the

same place in the store to pic5 it up6 and ne=er notice what other brands are on the shelf or what

are the prices of other brands. !ow is it that the generic model abo=e wor5s differentl4 in this

second scenarioK Wh4 does it wor5 differentl4K Wh4 would we generall4 need the ministrations

of a sales person in the sale of a car6 but we generall4 do not need the help of a salesperson in

the purchase of orange 9uiceK

!ow can the mar5eter of orange 9uice get a consumer li5e 4ou to e>ert more effort intoinformation search or to consider alternati=e productsK !ow is it that the mar5eter of 4our brand

got 4ou to ignore alternati=e competing brandsK What is the in=ol=ement of salespeople in sales

promotionsthat might be associated with products such as orange 9uiceK

?onsumer beha=ior researchers are not so interested in stud4ing the =alidit4 of the abo=e

generic model6 but are more interested in =arious factors that influence how such a model might

wor5.

INFLUENCES ON THE GENERIC MODEL

&5%&/a3

o 1'#7

-e.g.6 cultural6 famil46 reference group influences

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o &/6i'/$&/%a3i%#a%i'/a3

-e.g.6 time of da46 temperature and humidit46 etc.

i/&/a3

o lifest4le6 personalit46 decision ma5ing process6 moti=ation6 etc.

GROUP INFLUENCES ON CONSUMER BEHAVIOR

C#3%#&

the set of basic =alues6 beliefs6 norms6 and associated beha=iors that are learned b4 a member of

societ4

+ote that culture is something that is learnedand that it has a relati=el4 long lasting effect onthe beha=iors of an indi=idual. As an e>ample of cultural influences6 consider how the

salesperson in an appliance store in the U.. must react to different couples who are considering

the purchase of a refrigerator. %n some subcultures6 the husband will pla4 a dominant role in the

purchase decisionB in others6 the wife will pla4 a more dominant role.

S'4ia3 C3a

A group of indi=iduals with similar social ran56 based on such factors as occupation6 education6

and wealth

R&-&&/4& G'#7

2roups6 often temporar46 that affect a personGs =alues6 attitude6 or beha=iors

".g.6 4our beha=iors around colleagues at wor5 or friends at school are probabl4

different from 4our beha=iors around 4our parents6 no matter 4our age or stage in the

famil4 life c4cle. %f 4ou were a used car salesperson6 how might 4ou respond differentl4

to a nineteen 4ear old prospect accompanied b4 her bo4friend from one accompanied b4

two girlfriendsK

O7i/i'/ 3&ad&

A person within a reference group who e>erts influence on others because of special

s5ills6 5nowledge6 personalit46 etc.

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o $ou might as5 the webmaster at wor5 for an opinion about a particular software

application. oftware manufacturers often gi=e awa4 free beta copies of software

to potential opinion leaders with the hope that the4 will in turn influence man4

others to purchase the product.

Fa$i3(

A group of people related b4 blood6 marriage6 or other sociall4 appro=ed relationship

ENVIRONMENTAL SITUATIONAL INFLUENCES ON CONSUMER

BEHAVIOR

?ircumstances6 time6 location6 etc.

Do 4ou li5e grapesK Do 4ou li5e peasK

$ou might li5e grapes as a snac5 after lunch6 but probabl4 not as a dessert after a fanc4 meal in

a restaurant. $ou might li5e peas6 but probabl4 not as a topping on 4our panca5es. "=er4da4

situations cause an interaction between =arious factors which influence our beha=iors. %f 4ou

wor5 for tips 'a form of incenti=e related to commission* as a waiter or waitress6 4ou must

certainl4 be aware of such interactions which can increase or decrease 4our sales.

%f 4ou are doing 4our aturda4 grocer4 shopping and are loo5ing for orange 9uice6 4ou are

probabl4 much more sensiti=e to price than if 4ou stop at the Cuic5 store late at night6 when 4ou

are tired and cran546 after a late meeting at the office. A prospect shopping for a new

automobile while debating the wisdom of a necessar4 e>pensi=e repair to his car might be more

interested in what cars are on the lot than in shopping for the best deal that might in=ol=e a

special order.

INTERNAL INFLUENCES ON CONSUMER BEHAVIOR

P&'/a3i%(

A personGs distinguishing ps4chological characteristics that lead to relati=el4 consistent and

lasting responses to stimuli in the en=ironment

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We are each uniCue as indi=iduals6 and we each respond differentl4 as consumers. ample6

some people are optimiEers who will 5eep shopping until the4 are certain that the4 ha=e found

the best price for a particular item6 while other people are satisficers who will stop shopping

when the4 belie=e that the4 ha=e found something that is good enough. %f 4ou are a

salesperson in a retail shoe store6 how might 4ou wor5 differentl4 with these two personalitiesK

Li-&%(3& a/d P(4h'1a7hi4

3i-&%(3& is a pattern of li=ing e>pressed through a personGs acti=ities6 interests6 and

opinions

7(4h'1a7hi4is a techniCue for measuring personalit4 and lifest4les to de=eloping

lifest4le classifications

M'%i6a%i'/: M#3%i73& $'%i6&

?onsumers usuall4 ha=e multiple moti=es for particular beha=iors. These can be a combination

of;

$a/i-&%

5nown to the person and freel4 admitted

3a%&/%

un5nown to the person or the person is =er4 reluctant to admit

+ote; different moti=es can lead to the same beha=iorB obser=ing beha=ior is not sufficient to

determine moti=es.

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What are the thoughts of LohnGs friendK

What is LohnGs manifest moti=eK

What might be his latent moti=eK

!ow might a salesperson disco=er these moti=esK What features should a salesperson

emphasiEeK

I/6'36&$&/%

!as to do with an indi=idualGs

intensity of interestin a product and the

importanceof the product for that person

The purchase of a car is much more ris54 than the purchase of a Cuart of orange 9uice6 and

therefore presents a higher in=ol=ement situation. This modifies the wa4 that the generic model

wor5s.

As in=ol=ement increases6 consumers ha=e greater moti=ation to comprehend and elaborate on

information salient to the purchase. A life insurance agent6 for e>ample6 would t4picall4 be

more interested in contacting a 4oung couple who 9ust had a bab4 than an eighteen 4ear old

college student - e=en though the new parents might be struggling to ma5e ends meet while the

student is li=ing more comfortabl4. Although the annual in=estment into a polic4 is much lower

if started at a 4ounger age6 most 4oung college students are not open to thin5ing about long term

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estate planning. A 4oung couple with a new child6 howe=er6 is much more open to thin5ing

about issues associated with planning for the childGs future education6 sa=ing to bu4 a house6 or

e=en sa=ing to ta5e an e>tended =acation upon retirement.

TYPES OF CONSUMER PROBLEM!SOLVING PROCESSES

R'#%i/iz&d

used when bu4ing freCuentl4 purchased6 low cost items

used when little searchdecision effort is needed

e.g.6 bu4ing a Cuart of orange 9uice once per wee5

Li$i%&d P'b3&$ S'36i/1

used when products are occasionall4 purchased

used when information is needed about an unfamiliar product in a familiar product

categor4

E5%&/d&d 7'b3&$ '36i/1

used when product is unfamiliar6 e>pensi=e6 or infreCuentl4 purchased

e.g.6 bu4ing a new car once e=er4 fi=e 4ears

Under what sorts of conditions would the assistance of a salesperson be neededK +ot neededK

POST!PURCHASE CONSUMER BEHAVIOR

Sa%i-a4%i'/

After the sale6 the bu4er will li5el4 feel either satisfied or dissatisfied. %f the bu4er belei=es that

she recei=ed more in the e>change than what was paid6 she might feel satisfied. %f she belie=es

that she recei=ed less in the e>change than what was paid6 then she might feel dissatisfied.

Dissatisfied bu4ers are not li5el4 to return as customers and are not li5el4 to send friends6

relati=es6 and acCuaintences. The4 are also more li5el4 to be unhapp4 or e=en abusi=e when the

product reCuires post-sale ser=icing6 as when an automobile needs warrant4 maintenance.

The abo=e idea can be modeled as H'$a/ bai4 &54ha/1& a%i'/:

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Profit = Rewards - Costs

Unfortunatel46 e=en a bu4er who got a good deal with respect to price and other terms of the

sale might feel dissatisfied under the perception that the salesperson made out e=en better.

This idea is called i%( %h&'(6 where we are concerned with;

Outcomes of A

Inputs of A

=s.

Outcomes of B

Inputs of B

?onsider6 for e>ample6 that 4ou ha=e purchased a used car for (H6 after finding that the

eBblue boo5 =alue is listed at (,6. $ou are probabl4 delighted with the purchase until 4ou

accidentall4 meet the prior owner who had recei=ed a trade-in of (6 on the car 9ust a few

da4s before. That the dealer appears to ha=e recei=ed substantiall4 greater benefit than 4ou

could lead to e>treme dissatisfaction6 e=en though 4ou recei=ed good =alue for the mone4 spent.

'+ote that the selling dealer might actuall4 ha=e paid (76 for the car at a statewide dealerGs

auction6 and then might ha=e incurred another (6 in e>penses associated with transporting

the car and preparing it for sale. Management of bu4er perceptions is =er4 importantQ*

An issue related to this is a%%ib#%i'/ %h&'(. According to attribution theor46 people tend to

assign cause to the beha=ior of others. Mar4Gs life insurance agent ad=ises her to purchase a

whole life polic46 while her accountant ad=ises her6 bu4 term insurance and in=est the

difference.. The reason6 e>plains the accountant6 is that insurance agents recei=e substantiall4higher commission pa4ments on sales of whole life policies.

%f Mar4 belie=es that the insurance agent is recommending a product merel4 because he

recei=es a higher commission6 she will li5el4 be displeased with the relationship and will not

ta5e his recommendation. %f the agent is able to show Mar4 that the recommended product is the

best solution for her situation6 then she will li5el4 attribute his recommendation to ha=ing her

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best interests in mind and will not be concerned about how it is that he is compensated for his

ser=ices.

C'1/i%i6& di'/a/4&

%t has to do with the doubt that a person has about the wisdom of a recent purchase

%t is =er4 common for people to e>perience some an>iet4 after the purchase of a product that is

=er4 e>pensi=e or that will reCuire a long term commitment. Lane and ample6 signed

a one 4ear lease on an apartment6 committing themsel=es to pa4ments of (0 per month. A

wee5 later6 the4 are wondering if the4 should ha=e instead leased a smaller 8 apartment in a

more rough part of townB the4 are not sure if the4 reall4 can afford this much of a monthl4

obligation. Dic5 and all46 on the other hand6 ultimatel4 rented the 8 apartment6 and now

are wondering if the sa=ings in rent will be offset b4 nois4 and sometimes unsafe conditions in

this neighborhood.

Perhaps neither couple would be e>periencing this an>iet4 if their landlords had gi=en them 9ust

the smallest of assurances that the4 had made a good decision. After a close on products that are

e>pensi=e or that reCuire a long term commitment6 the salesperson should pro=ide the prospect

with some reasons to be happ4 with the decision. Allow the car bu4er to reinforce her own

positi=e feelings b4 calling her a wee5 after the purchase to as5 how things are going. ?all the

new life insurance polic4 holder after two months to see if there are an4 CuestionsB a lac5 of

Cuestions can onl4 help the bu4er to con=ince himself that he did the right thing.

M&%h'd'3'1(

The stud4 is based on primar4 data collection with a sample siEe of ( respondents residing in

+ational ?apital egion of +ew Delhi6 %ndia. The Cuestionnaire used for the sample sur=e4 is a

structured and non-disguised Cuestionnaire and consisted of two ma9or sections. The first

section intended to collect the =arious demographic factorsB the second section intended to

collect the =arious opinions containing Cuestions about the =arious factors affecting the car

purchasing decision. A fi=e point #i5ert scale was used to capture the consumers responses

ranging from strongl4 agree to strongl4 disagree. The different statements regarding the =arious

factors affecting the car bu4ing beha=ior of customers were generated based on literature re=iew

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as well as e>pert opinion in an iterati=e manner. %t could be therefore said that the itemiEed scale

in this case actuall4 as5s the respondents to ran5 their opinions in a decreasing order of

importance. Data anal4sis was done using P software. The statistical anal4sis methods

emplo4ed was factor anal4sis. To stud4 the impact most freCuentl4 indulged in weighted

a=erage method was used.

Da%a 4'33&4%i'/

The stud4 entailed data collection with the help of a Cuestionnaire from the residents of

+ational ?apital egion of +ew Delhi6 %ndia. Data was collected b4 personall4 contacting the

respondents and e>plaining in detail about the sur=e4. A total of (7 customers from different

areas were contacted and ( correctl4 completed Cuestionnaires were obtained from all the

customers6 the brea5-up of which is gi=en in

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0

20

40

60

Below 18 18-25 26-35 36-50 Above 51

Percentage

O44#7a%i'/

0

20

40

60

Service Buine Stu!ent "oue-#i$e

Percentage

Fi1 8

Fi/di/1 a/d A/a3(i

Fa4%' A/a3(i -' -a4%' a--&4%i/1 4a 7#4hai/1 d&4ii'/

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is factoring with =arima> rotation to reduce potential multicollinearit4 among the

items and to impro=e reliabilit4 on the data 'see Table ,; otated *. 1arima>

rotation 'with /aiser +ormaliEation was con=erged in thirt4-one iterations. Thirt4 items were

reduced to nine orthogonal factor dimensions which e>plained 3.000F of the o=erall =ariance

'Table H* indicating that the =ariance of original =alues was well captured b4 these nine factors.

The nine factors and their components is gi=en in table .

R&3iabi3i%( '- Da%a

Tab3& ;: *MO a/d Ba%3&%% T&%

Kaiser-Meyer-Olkin Measure of SamplingAdequacy. .769

Bartletts !est ofSp"ericity

Appro#. $"i-Square %6&'.'''

df ()&

Sig. .'''

*ai&!M&(&!O39i/

R%nde> for comparing the magnitudes of the obser=ed co-relation coefficient to themagnitude of the partial correlation coefficientsS

T&% '- S7h&i4i%(

Rtrength of relationship among =ariables is strong. %t presents good idea to proceed tofactor anal4sis for the data.S

H' :There is significant indifference of all the factors affecting car purchase decision H; : There is significant difference of all the factors affecting car purchase decision

The obser=e significance le=el is . which is less than .06 which is small enough tore9ect the h4pothesis. %t means there is a significant difference between the factors affectingcar purchasing decisions.

C'$$#/a3i%(! C'$$'/ Fa4%' Vaia/4&

?ommunalit4 of each statement refers to the =ariance being shared or commonb4 other statements. With reference to the first statement6 the e>traction is .)33 which indicatesthat )3.3F of the =ariance is being shared or common to other statements. efer Table 7.

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Ei1&/ Va3#&; %ndicates the amount of =ariance in the original =ariables accounted or b4 eachcomponent. The total initial =ariance in the new components will be 3.

Tab3& 2: C'$$#/a3i%i&

*nitial +#traction

S% %.''' .,))

S %.''' .69

S) %.''' .76'

S( %.''' .,''

S& %.''' .69&

S6 %.''' .79&

S7 %.''' .7(6

S, %.''' .7)%

S9 %.''' .7,)

S%' %.''' .,7&

S%% %.''' .,&%

S% %.''' .7,

S%) %.''' .6(

S%( %.''' .6,

S%& %.''' .67(S%6 %.''' .7%&

S%7 %.''' .66

S%, %.''' .7'7

S%9 %.''' .6&)

S' %.''' .7,

S% %.''' .76

S %.''' .7%'

S) %.''' .6(

S( %.''' .6,7

S& %.''' .,)&

S6 %.''' .6,(S7 %.''' .,')

S, %.''' .6,)

S9 %.''' .,&7

S)' %.''' .6&'

+#traction Met"od /rincipal $omponent Analysis.

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Tab3& 8: T'%a3 Vaia/4& E573ai/&d

">traction Method; Principal ?omponent Anal4sis.

$omponent *nitial +igen0alues+#traction Sums of Squared

1oadings 2otation Sums of Squared 1oadin

!otal3 of

4ariance$umulati0e

3 !otal3 of

4ariance$umulati0e

3 !otal3 of

4ariance$umulat

3

% 7.%' ).67 ).67 7.%' ).67 ).67 ).)9, %%.)7 %%.) ).&)9 %%.79, )&.(7' ).&)9 %%.79, )&.(7' ).7 %'.7&6 .',

) .&() ,.(77 ().9(7 .&() ,.(77 ().9(7 ).',' %'.6, ).)&

( .%,, 7.9 &%.)9 .%,, 7.9 &%.)9 .&&6 ,.&' ('.,7

& %.7%6 &.7% &6.96' %.7%6 &.7% &6.96' .&() ,.(76 (9.)(

6 %.6)% &.()& 6.)96 %.6)% &.()& 6.)96 .)&6 7.,&& &7.'

7 %.%, (.'&9 66.(&& %.%, (.'&9 66.(&& %.9'9 6.)6( 6).&6(

, %.%% ).7'6 7'.%6% %.%% ).7'6 7'.%6% %.7%, &.7& 69.,

9 %.'%, ).)9( 7).&&& %.'%, ).)9( 7).&&& %.,' (.66 7).&&

%' .9(, ).%6' 76.7%&

%% .,%& .7%7 79.()

% .6,) .7, ,%.7%'

%) .6)( .%%) ,).,)

%( .&67 %.,,9 ,&.7%

%& .&'' %.667 ,7.)79

%6 .(,9 %.6)% ,9.'%'

%7 .()9 %.(6( 9'.(7&

%, .(% %.(') 9%.,7,

%9 .))' %.'99 9.976

' .97 .99% 9).967

% .77 .9( 9(.,9%

.7% .9'& 9&.796

) .6 .7& 96.&(7

( .'9 .697 97.(&

& .%9( .6(7 97.,9

6 .%,) .6', 9,.&'%

7 .%6% .&)7 99.'),

, .%9 .()% 99.(6,

9 .',9 .97 99.766

)' .'7' .)( %''.'''

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Tab3& :

C#$#3a%i6& F&/4(

?omponent ( ">plain a =ariance of 3.38)6 whichis ((.37 F of the total =ariance of

3

((.37F

?omponent 7 ">plain a =ariance of 3.376 whichis (.0, F of the total =ariance of3

77.)3F

?omponent 3 ">plain a =ariance of 3.)6 whichis (.7,) F of the total =ariance of3

37.30F

?omponent H ">plain a =ariance of 7.00,6 whichis ).07 F of the total =ariance of3

H.)F

?omponent 0 ">plain a =ariance of 7.0H36 which

is ).H, F of the total =ariance of3

H8.3H0F

?omponent , ">plain a =ariance of 7.30,6 whichis .)00 F of the total =ariance of3

0.7F

?omponent ">plain a =ariance of (.886 whichis ,.3,H F of the total =ariance of3

,3.0,HF

?omponent ) ">plain a =ariance of (.()6 whichis 0.70 F of the total =ariance of3

,8.7)8F

?omponent 8 ">plain a =ariance of (.7)6 whichis H.7,, F of the total =ariance of3

3.000F

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Component Number

)'-9-,-7-6-&-(-)---%-'%9%,%7%6%&%(%)%-%%%'9,76&()-%

Eigenvalue

,

6

(

-

'

0%0&

0%0'

0%130%16

0%18

0%1'

0%21

0%23

0%2&

0%280%3

0%330%42

0%44

0%4'

0%5

0%5&

0%63

0%68

0%82

0%'5

1%02

1%11

1%22

1%63

1%&2

2%1'

2%54

3%54

&%1

Scree Plot

Fi1

With the help of table 3 and H6 we can interpret that 3 statements are now reduced to 8components contributing 3.000F of the total =ariance. With the help of

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+#traction Met"od /rincipal $omponent Analysis.a 9 components e#tracted.

"ach number represents the correlation between the item and the unrotated factor. Thiscorrelation helps to formulate an interpretation of the factors orcomponents. This is done by looking for a common thread among thevariables that have large loadings for a particular factor or component. It ispossible to see items with large loadings on several of the unrotated factors,which makes interpretation difficult. In these cases, it can be helpful toexamine a rotated solution.

Tab3& J: R'%a%&d C'$7'/&/% Ma%i5

Component

% ) ( & 6 7 , 9

S% .)77 .67 .&(% -.))) .%7 .%7% -.)7 .%76

S -.%66 -.%6) -., .66& -.%%9 .%,' .)')

S) .6(9 -.), .)(7 .%%9 .%,, .%%

S( -.&&% -.%9% .&') .)), -.7% -.%'6S& .&99 -.(( .),, .%(% .%' .%%& .%', -.%66 .%'

S6 .7&% -.6& -.%6( -.%&6 .9% .%)%

S7 .) .) -.%), .) -.)(( .)9' -.)7 .(9,

S, .()' .%( .%, .(9 .&,% .%& .)'6

S9 -.%'( -.67 .9 .699 -.( -.7% -.%(7

S%' -.%7' .69, -.(%, .)6) .%9 .%7,

S%% .) .,', -.7 .%) -.%6% .%&7

S% -.&( -.%% .6, .%(( .%)&

S%) .%77 .&, .(6 -.%6 -.%') .'& -.%''

S%( .67 -.%)9 -.%7% -.' .79 -.7

S%& .6,9 .))7 .%'' -.%97S%6 .&69 .)&7 .%7' .7) -.%%9 -.)(6 -.%&(

S%7 -.)% .)9, .&9 .%6% -.%'9

S%, .(,% .)() .(7 .%%7 -.)() -.%,)

S%9 .7%, -.%'6 -.%96 -.7)

S' -.)9& -.% .&( .%'7 .667 .%6)

S% .7)' -.'& -.%)9 .%%6 -.)67 .%%(

S .&)7 -.9( .%&( -.%', .(& .(7'

S) .(,( -.)&( .%%& .)%% .)9&

S( .)6, .%6, .6 -.& .&7 .%'( -.)(%

S& -.(99 .'7 .6%7 -.,, -.%'6 -.%(& .%9%

S6 .6% .%% .%,7 .&6 .)) .%,6 -.%9&S7 -.&') .()' .&%6 .&% -.%),

S, .6& .(7 .7 -.7, -.)6

S9 -.&)& .%,6 .66) .%% .%&, -.&

S)' .(&9 .( .%%7 -.)'' -.%) -.%&) .))&

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+#traction Met"od /rincipal $omponent Analysis.2otation Met"od 4arima# 5it" Kaiser ormaliation.

a 2otation con0erged in )% iterations.

+ith the help of table ,6 we can categoriEe each statements depending upon the factor loadingsand shown in table.

Tab3& : Fa4%'

Fa4%' ;:

S;" : %nformation Pro=ided :4 alesperson

S2 :afet4

S2 :"as4 A=ailabilit4 Of pare Parts

S2" : Technolog4

$omponent

% ) ( & 6 7 , 9

S% .((7 .7&) .'

S .%9% -.76& -.%%& .'

S) -.% -.(%( .&9% ., .%&) .%9( .,(

S( .%,9 -.%) -.799 -.) -.%)( -.%7

S& -.)7( .&7' .9& .%&, .%&, .%' .&

S6 .7&& -.%9 .%' .)'( .%%( .6

S7 .%9 .%9% .%%% .79

S, .%&' .,% .%)%

S9 .)', -.)', .%9) .),, -.(66 -.%) -.)(( .%)

S%' .,6 -.%& -.&) -.9)

S%% .,7 .%)( .%%7 .&

S% .%' -.%), -.)9 .%77 -.&7' -.', -.('( .%', .%9

S%) .)%9 .% .% .%'9 .( .6()

S%( -.))7 .(,% .%& -.%%( .)7% .7 .%,

S%& -.%7( .7% .),& .%& .%&6 .)79 .)' .))

S%6 -.%) .(), .&66 .)& -.67 .%7

S%7 .%%) .(9 .%6% -.%6& -.&9% -.%)9 -.%9

S%, .)%% .&%) .)) .(6 .%)6 -.), -.%9

S%9 -.(99 .& .%& .(, .69 .%(

S' -.%, -.,%

S% -.( .)) .,' .%(, -.%% .&() .%7 -.%(

S -.%&% -.'& .6 .(%) .6) -.%9 .&&% -.%7

S) -.%,7 .% .%7, .%,7 .67' .%7

S( .,'9 .%()

S& .,,& -.%6' -.%'

S6 -.%79 .%'& .&)7 .)9% .%67 .(6 -.%)& .'7 -.S7 .,&% .%9& -.%') -.%&%

S, -.,9 .&' .6)6 .%& .%% .%(, -.%&7 .%&

S9 .,6' -.9' -.%'7

S)' .%(% .(%) .%'7 .7( .(6% .76 .,%

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Fa4%' 2:

S;0 :2o=ernment Policies And egulations

S;; : %mport Duties %mposed :4 2o=ernment

Fa4%' 8:

S8 :

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6 we can obtain the Cuantifiable data of each

factor. The coefficients between the statements and the factors are ta5en according to the statement

affecting the factor ' on the basis of Table *

C'/43#i'/ a/d R&4'$$&/da%i'/

ince %ndian Automobile mar5et is continuousl4 in the prowl of surging as a ma9or car

manufacturer6 people are purchasing car as there is increase of income of common people as

well as change in tastes and preferences of consumers. %t is important for the car manufacturers

and car dealers to be able to understand the different factors affecting the e>tent in car

purchasing beha=iour. The factor anal4sis results indicate that factor ( 'table * which consists

of %nformation pro=ided b4 salespersonB safet4B eas4 a=ailabilit4 of spare partsB technolog4 are

affecting the car purchasing beha=ior. People are more conscious about the on spot information

pro=ided about =arious cars who ser=es according to the needs and wants of the customer. The

t4pe of technolog4 used and the wider reach of the ser=ice stations also affect the most on car

purchasing decision. While go=ernment obligations and =arious policies li5e import duties6

custom e>emptions is seen as second most affecting dri=er 'factor 76 table * of purchase of

cars.

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ANNEURE

O7i/i'/ S#6&(

Section (

D&$'1a7hi4 Fa4%'

Na$&G&/d&..

A1&

:elow() ()-70 7,-30 3,-0 0( and abo=e

O44#7a%i'/

er=ice :usiness tudent !ousewife

Section II

A44'di/1 %' ('# hi4h '- %h&& Fa4%' a& A--&4%i/1 Ca P#4hai/1 D&4ii'/ i/ I/dia.

P3&a& -i33 a44'di/1 %' i/%#4%i'/ i/ ba49&% 1i6&/ b&3'

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2K. A=ailabilit4 Of er=ice tation

2". Technolog4

80. O=erall6 % Am atisfied With M4?ar % Own