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Dr. D. VENKATRAMARAJU, M.B.A., M.Com., M.A., M.Ed., M.Phil., Ph.D., ACS Inter, B.G.L., Associate Professor, Post Graduate and Research Department of Commerce, Pachaiyappa's College, Chennai - 600 030.

CERTIFICATE BY THE SUPERVISOR

I certify that the thesis entitled “PRE AND POST PURCHASE

BEHAVIOUR OF FOUR WHEELER USERS IN CHENNAI CITY "submitted

by S.VELMURUGAN for the award of the degree of Doctor of

Philosophy is a record of research work carried out by him under my

guidance and supervision and that this work has not formed the basis

for the award of any Degree, Diploma, Associateship, fellowship or

other similar titles in this University or any other University or

Institution of Higher Learning. The Thesis represents independent

work on the part of the candidate.

Place: Chennai

Date:

SIGNATURE OF THE SUPERVISOR

DECLARATION

I declare that the thesis entitled entitled “PRE AND POST

PURCHASE BEHAVIOUR OF FOUR WHEELER USERS IN CHENNAI

CITY” submitted by me for the award of the degree of Doctor of

Philosophy is the record of research work carried out by me under

the guidance of Dr. D. VENKATRAMARAJU and that has not

formed the basis for the award of any Degree, Diploma,

Associateship, fellowship or other similar titles in this University or

any other University or Institution of Higher Learning.

Place

Date:

S. VELMURUGAN

CERTIFICATE BY THE CANDIDATE

FOR THE LANGUAGE AND ORIGINALITY

I hereby declare that thesis entitled “PRE AND POST

PURCHASE BEHAVIOUR OF FOUR WHEELER USERS IN

CHENNAI CITY" has been checked for the language, spelling,

grammar, punctuation, originality etc., through the software

plagiarism Detector.

S. VELMURUGAN

ACKNOWLEDGEMENT

First and foremost, I thank the almighty for the blessings which

enabled me to carry out this study successfully.

I wish to place on record my sincere gratitude to my guide and

supervisor Dr. D. Venkatramaraju, Associate Professor, Post Graduate

and Research Department of Commerce, Pachaiyappa's College,

Chennai -600 030 for his valuable guidance which helped in

channelising my thoughts to shape this thesis. I am grateful to him, who

took pains and made significant suggestions without which this work

would not have become successful and meaningful.

I am thankful to the Vice-Chanceller, Dean Research of

VINAYAKA MISSIONS UNIVERSITY, SALEM for giving me this

valuable opportunity in pursuing Ph.D. programme.

I am grateful to the respondents who helped me in collecting the

data to complete my research work.

Last but not the least, I express special thanks to my Parents,

Family members and Well-wishers for lending me their constant support

throughout the research work.

S. VELMURUGAN

INDEX

Chapter Title Page

No

Acknowledgement

List of tables

I. Introduction research design methodology 8

II. Review of literature 18

III. Profile of organisations and products 28

IV. Pre purchase behaviour of four wheelers users 33

V. Post purchase behavior of four wheelers users 103

VI. Findings, conclusion and suggestion 166

Bibliography 188

Appendix

Questionnaire

197

2

LIST OF TABLES

Table

No TITLE OF THE TABLE

Page

No

4.1 Distribution of Samples on the Basis of Gender 35

4.2 Distribution of Samples on the Basis of Age 36

4.3 Distribution of Samples on the Basis of Education 37

4.4 Distribution of Samples on the Basis of Occupation 38

4.5 Distribution of Samples on the Basis of Earning

members in the family

39

4.6 Distribution of Samples on the Basis of Family

Monthly Income

41

4.7 Distribution of Samples on the family size 42

4.8 Source of awareness 43

4.9 Media specification 45

4.10 One-Sample Statistics for Brand Awareness 46

4.11 One-Sample Test for Brand Awareness 47

4.12 Brand acquaintances (or) proximity 49

4.13 Level of Product awareness and brand awareness

of cars

50

4.14 Brand of car used 52

4.15 Association between brands of cars used and level

of awareness

53

4.16 Number of cars used by the customers 54

4.17 Association between number of cars and

customers level of awareness

55

4.18 Nature of finance 57

4.19 Association between nature of finance and

customers satisfaction

58

3

Table


Page

No

4.20 Chi-Square Tests for Association between nature

of finance and customers satisfaction

58

4.21 Borrowing Sources 59

4.22 One-Sample Statistics for Customers opinion on

interest rate and road tax

60

4.23 One-Sample Test for Customers opinion on

interest rate and road tax

61

4.24 Type of Fuel influences the customers towards the

purchase of cars

63

4.25 Purpose of using car influences the customers

towards the purchase of cars

64

4.26 Reasons for buying a present car 65

4.27 KMO and Bartlett's Test for influencing to buy the

car

66

4.28 Total Variance Explained for influencing to buy the

car

66

4.29 Rotated Component Matrix for influencing to buy

the car:

67

4.30 Influence in decision making 69

4.31 KMO and Bartlett's Test as Reasons for brand

selection

70

4.32 Total Variance Explained as Reasons for brand

selection

71

4.33 Rotated Component Matrix a Reasons for brand

selection

72

4.34 Final Cluster Centers for product attraction,

product suitability and cost approach

74

4

Table


Page

No

4.35 Number of Cases in each Cluster 75

4.36 Final Cluster Centers for cost orientation,

comfortability and qualitative facilities of brand

selection reasons

75


4.38 Clusters for factors of influencers and brand

selection

77

4.39 Chi-Square Tests for factors of influencers and

brand selection

77

4.40 SWOT Ranking analysis for strength factors for

purchase of cars

79

4.41 SWOT Ranking analysis for weakness factors for

purchase of cars

80

4.42 SWOT Ranking analysis for opportunity factors for

purchase of cars

81

4.43 SWOT Ranking analysis for threat factors for

purchase of cars

82

4.44 ANOVA for relationship between gender and SWOT factors

83

4.45 ANOVA for Influence of Age 85

4.46 ANOVA for influence of education 87

4.47 ANOVA for Influence of occupational status 89

4.48 ANOVA for Influence of Number of earning members in the family

92

4.49 ANOVA for Influence of family income 95

4.50 ANOVA for influence of family size 97

5.1 One-Sample Statistics for Customers attitude and

expectations

103

5

Table


Page

No

5.2 One-Sample Test for Customers attitude and

expectations

104

5.3 KMO and Bartlett's Test for customer attitude and

expectations

106

5.4 Total Variance Explained for customer attitude and

expectations

107

5.5 Rotated Component Matrix for customer attitude

and expectations

108

5.6 Final Cluster Centers for Different types of attitude

and customer expectations

111


5.8 Tests of Equality of Group Means for Cluster

Justification

113

5.9 Test Results for Cluster Justification 113

5.10 Eigen values for Cluster Justification 114

5.11 Wilks' Lambda for Cluster Justification 114

5.12 Structure Matrix for Cluster Justification 115

5.13 Multivariate Tests for the customers attitude and

expectations

117

5.14 Tests of Between-Subjects Effects for the

customer’s attitude and expectations

120

5.15 One-Sample Statistics for Customer Satisfaction 128

5.16 One-Sample Test for Customer Satisfaction 129

5.17 KMO and Bartlett's Test for customer satisfaction 131

5.18 Communalities for customer satisfaction 132

5.19 Total Variance Explained for customer satisfaction 133

6

Table


Page

No

5.20 Rotated Component Matrix for customer

satisfaction

134

5.21 Brand of car used is superior to other brands of

cars

136

5.22 Reasons for superiority of Brands 137

5.23 Choice of purchase of car in future 138

5.24 Idea of shifting the present brand of car to other

brand

139

5.25 Reasons for Brand shift 140

5.26 Experience of frequent problems in Using cars 141

5.27 Problems encountered by car users in Chennai city 141

5.28 Customers recommending others to buy their

brand of car

142

5.29 Reasons for Brand Recommendation 143

5.30 Final Cluster Centers 144


5.32 Association between different levels of customer satisfaction and brand comparison behaviour of customers

146

5.33 Chi-Square Tests 147

5.34 Choice of Purchase of car in future 148


5.36 Experience frequent problems in using cars 149


5.38 As the title of Recommend others top buy your

brand of car

152


7

Table


Page

No

5.40 One-Sample Statistics for Opinion about dealers

services

153

5.41 One-Sample Test 153

5.42 Availing of Services 155

5.43 Behaviour of car users after free service period 156

5.44 Sales Promotion 157

5.45 Influence of sales promotional offer 158

5.46 Omnibus Tests of Model Coefficients 159

5.47 Model Summary 159

5.48 Variables in the Equation 160

5.49 Tests of Equality of Group Mean 161

5.50 Eigen values 162

5.51 Wilks' Lambda 162

5.52 Structure Matrix 163

8

CHAPTER I

INTRODUCTION

Consumer is the kingmaker of the industries. In the era of

liberalization, the shift from a local to a global economic paradigm had

enlarged the role of consumers which cannot be neglected in these

global economies. In a free market economy consumers are well

educated and informed and with the power to influence the market

through their rational decisions, when confronted with choices in the

market. Thus, consumer decision making is important for researchers

and marketers looking to aid the consumer. Business in a global

economy need to be more conscious about consumer behaviour in

different societies enabling effective marketing of their products and

services .It is obvious that India, the second most populous country in

the world and its ever growing population provides ample scope for

potential consumers and marketers of various products.

There is a huge transformation in the customary shopping

practices, disposable income and relative increase in the younger

population. The attitudinal changes towards shopping emphases a

change from price consideration to design, quality and trendiness. The

desire to look and feel good had become a guiding factor for consumers

while making their purchase decisions.

9

CONSUMER BEHAVIOUR

Consumer behaviour is the understanding of consumer

perception, attitude, satisfaction and dissatisfaction of the products what

he purchased.

In this generation of fast moving lifestyle, customers are busier than

what they were few years back. It is precisely for this reason customers

purchase the products or avail services online also. With technological

up-gradation, online purchase has gained popularity. A recent research

on the online purchasing shows that, it varies to a greater extent in

comparison with the traditional buying. Today, both urban and rural

areas enjoy internet facilities. Contemporary consumer buying

behaviour has changed to a great extent due to technological

upgradation. Companies are also well aware of these facts and hence

greater importance is given to online consumer behaviour.

The facility of online purchasing has allowed customers to

identify the different types of products available in the global market

including the newly introduced ones. Evaluating products according to

their prices just by a click of the mouse, without wasting precious time

walking to the retail stores is another advantage. Due to rapid

globalization, most of the products are available on the net.

The traditional approach to understand consumer behaviour is

as a sequence of stages through which the buyer moves, gathering

information and evaluating competitive offerings before reaching a

decision and acting upon it. A consumer moves through a series of

10

psychological stages and sequences of action before reaching a choice

decision. The following are the processes of Consumer Behaviour:

Need Recognition

The buying process starts with need recognition. At this stage,

the buyer recognizes a problem or need and responds to a marketing

stimulus.

Information Search

The second step is information processing. The consumers of

most products will search for availability of alternatives. For external

search, awareness alone may be sufficient to effect choice. Studies of

external information search and actual shopping behaviour for

consumer durables have found wide differences in the search behaviour

of the individuals.

Evaluation of Alternatives

In order to choose between competing brands the consumer

must decide which evaluative criteria will be used and employ the same

for the decision rule. The evaluative criteria (sometimes called choice

criteria) are the product attributes, functional, symbolic, and emotional,

on which the relative performance of the competing alternatives will be

compared. The decision rule is the strategy the consumer uses to deal

11

with the information available and arrive at a choice. However,

consumers also use certain tangible attributes as surrogate indicators,

or signals, of less tangible attributes. In particular, price and brand

name are often used as surrogate indicators of quality.

Pre-Purchase decision

Two important aspects of the purchase stage are the extent to

which the purchase is actually pre-planned, and the choice of outlet to

buy from. There are a range of factors which will intervene between a

formed purchase intention and actual purchase. The major factor is

time, in that the more time between intention formation and behaviour,

the more opportunity exists for unexpected factors to change the

original intention. However, in many instances a conscious purchase

intention is not formulated prior to the purchase act. In supermarket

shopping, the displays of products can act as a surrogate shopping list

and prompt a type of impulse purchase (Cobb and Hoyer 1996).This

would be more accurately termed as partly planned purchase, although

no specific intention is formed. A general intention to purchase exists,

and it is not a true impulse purchase, which involves a sudden strong

urge to purchase with diminished concern for the consequences.

Before deciding about the selection of brand, the selection of

shop from where the products to be purchased are important. For the

12

increasing number of people for whom shopping is a recreational

activity, browsing can lead to many unplanned purchases but is itself a

pleasure-giving activity for a significant proportion of the population

(Elliott, 1994).

Post-Purchase Decision

The consumer will decide to continue with the same product and

the brand after he evaluates the performance of the product.

The consumers of cars will search for information about the cars

particularly models, facilities. price, fuel consumption and availability of

after sale service in the pre-purchase process. After purchasing they

evaluate the performance of the cars. Thus, the owners of the cars have

pre-purchase and post purchase activities.

Need For the Study

To catch the car market and reach the consumers, the

manufacturers have to conduct various and continuous studies on car

consumers whose behaviour will be changing all the times. Though

there are some studies in four wheeler segment, they hardly help the

industry, because their data becomes obselete over a period of time.

Thus, there are some gaps in the literature of car industry. So this

study is undertaken to fill the gaps in the literature and provide current

information to the car industry. This study has selected Chennai to

conduct research as it is one of the most vibrant and developing cities

in India.

13

The title is framed to study the car user preferences before

purchase and their satisfaction after the purchase of the car. So four

objectives are prepared. The first two objectives concentrate on pre –

purchase and the other two objectives study the post – purchase

behavior. Accordingly the questionnaire schedules are prepared.

Analysis is also done as per the objectives. There are two analytical

Chapters - Chapter IV & V. Chapter IV deals with pre-purchase and

Chapters V studies the post purchase behavior. Hence, the study

correlates to the topic.

Scope of the study

Though there are other four wheeler vehicles, the study is

restricted to cars only, since its market is wider than others. The study

is conducted on the features of cars in the latest models. It is conducted

with the help of car owners perception and preferences.

OBJECTIVES OF THE STUDY

The study is undertaken with the following objectives:

1. To know the consumer sources of information about the cars.

2. To analyse the car features that influence the purchasing decision

of consumers.

3. To study the factors that influence the satisfaction of car owners.

4. To know the post - purchase behaviour of car owners.

14

RESEARCH METHODOLOGY

Data Collection

Primary data are collected from the car owners in Chennai City

through questionnaires by following proportionate random sampling

technique.

Chennai City is divided into four regions namely South, North,

East and West. From each region five popular car dealers are selected.

From each dealer two hundred car owners who bought the cars within

six months period are collected. From the total list of car owners in each

region 15% is selected on random basis. The Following table gives the

sample selection procedure.

15

CHENNAI CITY

Regions

South North East West

DEALERS

5 5 5 5

CAR OWNERS (5 x 200)

1000 1000 1000 1000

SAMPLE SELECTION (15%)

150 150 150 150

Total Sample Selection = 600

16

Out of 600 questionnaires circulated, only 517 questionnaires

were returned by the respondents. The researcher contacted the

remaining 83 respondents repeatedly but there were no encouraging

responses. After scrutinizing the 517 responses, it is found that 61

questionnaires have not completed properly. So, only 456 responses

are considered for the research. Hence the actual sample size of the

study is 456.

Secondary Data

The secondary data are collected from journals like – Indian

Journal of Marketing and books like Consumer Behaviour.

Data Analysis

Data analysis is conducted using SPSS V-15. The data are

screened in order to obtain the variance among various consumer

behavioural aspects. Factor analysis, cluster analysis, one way analysis

of variance, Karl Pearson’s co-efficient of correlation, t-test and ranking

analysis are used to analyse the data.

17

CHAPTER SCHEME

This study is presented in six chapters.

Chapter I deals with the brief introduction about four wheelers and

Methodology .

Chapter II Reviews the previous Literature in the area of study.

Chapter III deals with product and organisation profile.

Chapter IV presents the consumer awareness and preference.

Chapter V Elaborates the factors which influence four wheeler

consumers.

Chapter VI summarises the findings of the research, concluding

remarks and suggestions.

18

CHAPTER – II

REVIEW OF LITERATURE

The Following are the reviews collected to formulate the research

design:

Pre–Purchasing Behaviour - The following reviews are made to

understand the pre-purchase behaviour of car buyers.

Beatty and Smith (2007) in their study on the external search

efforts found that some consumers typically visited only one or two

stores and rarely sought out unbiased information sources prior to

making a purchase decision, especially when little time was available to

do so.

This pattern was especially prevalent for decision regarding cars

or autos, even when those products represented significant

investments.

Srinivasan and Ratchford (1991) found that more than a third

had made only two or fewer trips to inspect cars prior to buying one.

Prem (2010) has suggested that the variables investigated

(magnitude and components of perceived risk, specific self

confidenceand information load) do not have generalized effects upon

the utilization of price cues in the quality perception process of car

purchasing.

19

Raghubir (2008) has pointed out that car consumer knowledge

and information processing of prices is less than perfect. So that

consumers often utilize simplifying characteristics and cues in

evaluating prices and offer value.

Dickson and Sawyer (2007) have examined that the length of

time the consumers spend on observing prices and choosing brand

within the store are found no significant relationship between the price

checking, time interval and price knowledge.Ajzen and Fishbein (2006)

have pointed out that when information on a given product is missing,

consumers often have to utilize other product attributes as cues for

making inferences about the missing information.

Briesch et al., (2007) have concluded that partially comparative

pricing influences consumer’s relative price belief about non-

comparatively priced products. An understanding of the existence of

such effects is important because their beliefs can influence consumer

search.

Srinivasan and Narasiman (2004) have emphasized that

collecting information is an effective strategy for reducing perceived risk

and uncertainty and that buyers often consult personal sources to

acquire information. 12

20

Gordon and Lee (2005) pointed out that the total product in a

broad sense included all the features and conveniences, for which the

consumer paid. They also found that the knowledge of the product

characteristics could be utilized to predict the nature of the marketing

mix, which was suitable for a given product.

Myers and Alpert (2008) identified the attitudes and

predispositions of consumers towards the choice of products. In the

choice of automobiles, power, comfort, economy, appearance and

safety were the attributes that were salient in decision making.

They found that only certain features of a product were proved

closely associated with preferences, while other remaining features

proved immaterial. Features that were closely related to preference

were said to be the determinants

Cairelli (2007) established the priority given to visual design by

consumers in their choice of products. According to him, product

appearance gained precedence over structural and functional design,

which often increases the manufacturing cost and ultimately resulted in

a higher price. All compromise on design or performance would affect

the established standards. Therefore, priority should be given to visual

design.

21

Swan and Combs (2006)emphasized the prime instrumental

factor, that is performance was quite important since it must be satisfied

before satisfying the other expressive factors like style, image, status

and comfort.

Bloch and Richins (2008) pointed out that perception of product

importance depended on product attributes like cost, time, quality,

dependency on product, self image, amount of stake in the purchase of

the socially significant products, purchase situation, personality and

prepurchase search.

Garvin (2006) based on his study of behaviour of North American

Company Managers, listed out the dimensions of quality as

performance, features, reliability, confort, durability, service ability,

aesthetics and perceived quality. He also mentioned that the

relationship between quality and price ran in both directions. The

relationship broke down when multiple attributes such as brand name,

store image and product features were present.

J D Curry and Riesz P C (2008) argued that the role of price

played in consumer evaluation of product alternatives was not

anunidimentional one. Price may be viewed as a constraint and as one

conveying information on product quality.

22

Scitovsky (2007) supported the common observation that people

frequently judged the product by its price – more expensive a product,

the higher may be its quality.

McClure. P.J. and Ryan. J.K. (2008) have found that there was

scope for differences in perception between manager and consumers.

They also found that pack sizes, pack shapes and packaging materials

may all affect sales through influencing the consumer’s perception of

the firm's overall market offering.

Peter D. Bennet and H.Kassarijain (2008)in their psychological

approach emphasized the importance of the place of residence in

purchasing perceptions. They have concluded that the perception of an

individual is selectively organized. Only certain objects in the world

enter into the customer’s cognition, others have to be moulded or

altered to fit the requirements of the individual.

Gestner (2005) has worked on a number of durable and non-

durable products and his study indicated that for 120 products the

relation between quality and price is weak and product specific. It is

weaker for frequently purchased items compared with non-frequently

purchased items.

23

Zeithaml (2004) has proved that perceived quality of fruit juices

was associated with purity, freshness, flavor and appearance. Extrinsic

cues serve as generalized quality indicators across brands, products

and their categories. Apart from that, price is also widely used to

perceive quality.

Hundal and Sandhu(2007) with the main purpose of determining

the pre and post purchase behaviour and brand preference have

conducted a study with 250 car consumers. The findings revealed that

the main factors considered by the sample consumers were the price of

various brands and availability of various products attributes including

after sales service.

Rao and Monroe (2006) have reviewed the different studies on

price, brand and store name on buyers' perception of quality. Theory

has concluded that strength of association between price and quality is

very less for frequently purchased goods compared to the non-

frequently purchased items. The effect of brand name and perceived

quality was not statistically significant.

24

Erdem (2003) has identified that the brand names convey

information about product quality. Brand loyalty builds brand equity and

keeps the consumers under the shadow of the same brand.

Lavoie(2004) has pointed out that need is an important

determinant in the non – durable consumption expenditure decision

making process. He has used four hundred sample size and ANOVA

tool and found out that the need plays a key role in decision making.

Tolar(2007) has found that the respondents take stock of what

non-durables they have currently in their position prior to purchasing

more and also consumers follow established patterns of habit when

making non-durable purchases.

Webster(1994) in his study has drawn the following

conclusionsPredefined role specification affects which spouse has

dominance with respect to specific products. While the husband

dominates in purchase decision for products like insurance, automobile

and television, the wife exerts more influence for products like groceries

and kitchen appliances. Traditional role specification influences the

relative dominance with respect to product attributes. In the purchase

decisions husband tend to concern themselves with relatively important

and functional product attributes like the price, while the wife

concentrates on minor aesthetic product attributes like colour etc.

25

Traditional role specification affects relative influence during

different decision phases. Traditionally, the husband dominates on the

important decision phases (i.e. decision to buy where as the wife

dominates at minor phases i.e. suggesting the purchase).

A.C Nielsen(2006) a market research agency has found that

urban child has a major say in the buying decisions of the parents. The

Study applied survey method with one thousand sample size. The result

shows that child behavior is crucial in family decision making.

Monroe(2005) has found that the knowledge of price is

considered to be a fundamental requirement in rational consumer

decision making. He has further observed that increased exposure to

prices is expected to improve the associated memory tracks and to help

create a richer knowledge base for product prices.

Moreau, Lehman and Markman(2003) have concluded that the

adoption decision of the consumer and the market factors influence

these individual consumer decisions.

Rogers(2008) have stated that the trial probability of any new

product is predicted to differ systematically between consumers. We

consider personal and interpersonal dispositions as well as socio

behavioral covariates.

26

Post –purchase Behaviour :

Roplhe E. Anderson(2009) cited Random House dictionary and

defined dissatisfaction as ” What falls short of one’s wishes or

expectations”. Thus consumer dissatisfaction is measured by the

degree of disparity between expectation and the perceived product

performance, where by consumer satisfaction is viewed as a type of

comparison process.

Wooodruff, Cadotte and Jenkins (2009)have made a study on

consumer satisfaction process. The actual performance and the

expected performance of the consumers were analysed in their study.

The researchers proposed to modify the basis of confirmation or

disconfirmation paradigm in two ways. First, expectations were

replaced with experience-based norms as the standard for comparison

of a brand’s performance. Secondly a zone of indifference was

postulated as a mediator between confirmation or disconfirmation and

satisfaction.

Swanson and Kelley(2008) have found that satisfied consumer

may express their appraisals to various parties and have positive word

of mouth.

27

Mittal et al.,(2008) have identified that “a consumer can be both

satisfied and dissatisfied with different aspects of the same product.

Doney and Cannon(2009) have identified that in organizational

buyer – seller relationship, loyal buyers are more likely to focus on long

– term benefits and engage in cooperative actions beneficial to both

partners than disloyal buyers, thus enhancing the competitiveness of

both partners and reducing transaction cost.

The above reviews help to identify research gaps from which the

objetives for the study are framed.

28

CHAPTER - III

PROFILE OF PRODUCT AND INDUSTRY

This chapter presents the product and Industry information.

India is flooded with many brands of passenger cars. They are :

Popular micro car models in India

Some of the most popular micro car models in India are as follows:

Badal -198 cc (1975-1982) Sunrise Auto Industries Ltd (SAIL),

Bangalore (4 seats)

Badal 4 198 cc (1981-1982) Sunrise Auto Industries Ltd (SAIL),

Bangalore (4 seats)

G Wiz electric car (REV A) AC Traction Motor, 13 kW peak power 2009

(4 seats)

Mahindra Reva Electric Vehicles Private Limited or erstwhile REV

A Electric Car Company is an automaker located in Bangalore. It

designs and produces electric cars. It is mostly famous for making the

best selling electric vehicle in the world, the REVA.

29

REV A Electric Car Company presently manufactures two

editions of the REV A, a modem electric micro car accommodating two

adults and two kids:

• REV A L-ion, fitted with Lithium-ion batteries, which has quicker

speeding up and a small range of 120 km (75 mi) per charge.

Cars made by the REV A Motor Company have been running on

the Indian roads since 2001.

India will be coming up as a massive car market in the near future

because of its fast economic development and high population.

Therefore, the country is a very good market for micro cars. These cars

are ideal for its narrow and crowded roads in comparison to bigger

vehicles.

Indian Automotive industry

While the genesis of Indian Automotive Industry can be traced to

the 1940s, distinct growth decades started in the 1970s. Between 1970

and 1984 cars were considered a luxury product; manufacturing was

licensed, expansion was restricted; there were quantitative restrictions

(QR) on imports and a tariff structure designed to restrict the market.

The market was dominated by six manufacturers – Telco (Tata Motors),

Ashok Leyland, Mahindra & Mahindra, Hindustan Motors, Premier

30

Automobiles and Bajaj Auto. The Decade of 1985 to 1995 saw the entry

of Maruti Udyog in the passenger car segment and Japanese

manufactures in the two wheeler and light commercial vehicle

segments. Economic liberalization, started in 1991, led to the

delicensing of the passenger car segment in 1993.

HISTORY, ORIGIN AND GROWTH OF SELECTED CAR COMPANIES

Contributing significantly to the Indian Automotive industry for

over five decades, Hindustan Motors Limited manufacturing facilities are

situated in the states of Madhya Pradesh, Tamil Nadu and West

Bengal. Hindustan Motors Limited functions with a commitment to core

values such as quality, safety, and environmental care, combined with

consumer-oriented total solutions.

Maruti is the highest volume car manufacturer in Asia, outside Japan

and Korea. It is one of the most successful automobile companies since

its inception. The keys of the first Maruti car were handed over to Mr.

Harpal Singh of Delhi by the then Prime Minister Mrs. Indira Gandhi on

14th December, 1983. Despite there being 11 companies now in the

passenger car market in India, Maruti holds about 60% of the total

market share. Maruti factory is situated on old Gurgaon - Delhi Road, at

distance of about 7 km from Gurgaon Bus Stand.

31

Tata Motors Limited, the other partner to the Joint Venture, is the

largest automobile company in India, with revenues of Rs. 32,426

crores (USD 7.2 billion) in 2006-07. It is the leader in commercial

vehicles in every segment and is the second largest in the passenger

vehicles market with winning products in the compact, mid-size car and

utility vehicle segments. The company is the world’s fifth largest medium

and heavy commercial vehicle manufacturer and the world’s second

largest medium and heavy bus manufacturer.

Global scenario of Indian automobiles

The industry being highly capital intensive, has entry

barriers for smaller players. Even the existing global auto majors

themselves are realigning their production bases coming closer to the

scene of action in Asia – Pacific region, mainly in China, India and

Thailand. Besides the above, the constant pressure for cost reduction

on Original Equipment Manufacturers (OEMs) is compelling them to

outsource more and more components from low cost countries. The

changing scenario has opened up opportunities for Indian Automotive

Industry. India, with its huge domestic market, rapidly growing

purchasing power, and market linked exchange rate and well

established financial market and stable corporate governance frame

work is emerging as an attractive destination for new investments in this

sector.

32

CONCLUSION

The rapid improvement in infrastructure including road, port,

power and world class facilities for testing, certification and

homologation, coupled with availability of trained man power and

enabling government policies to promote fair competition make Indian

automotive industry more competitive in the world besides making the

country a favourable destination for investment by global majors in auto

industry.

33

CHAPTER- IV

CUSTOMER AWARENESS AND FACTORS INFLUENCING THE

PURCHASE OF CARS

This chapter presents the anatomical analysis of customer

awareness on cars, factors influencing car purchase and incidental

effect of SWOT factors. The notions of parametric t-test, analysis of

variance and ranking analysis are employed to ascertain the opinion of

respondents on various buying behaviour towards cars purchasers’

point of view.

Demographic Details of the Customers

The demographic detail is an essential aspect in relationship

marketing process useful for the marketing organisation to employ

suitable strategies. In particular, Gender, Age, Education, Occupation

and Annual Income play a vital role in ascertaining the characteristic

features of customer buying behaviour towards cars.

Income, education, gender marital status, and age will influence

buying habits of individuals. Relative advantage, complexity/simplicity,

compatibility, observables, risk tolerance, and product involvement are

associated with the buying behaviour of customers towards cars (Jane

et al 2004).

34

The present study also focuses in identifying the categorical

classifications of customers based on their demographic characteristics.

Gender

Gender plays a very crucial role as far as the customer’s

purchase of cars is concerned. Traditionally, men played an active role

in most of the families with regard to purchases for family. Due to the

social changes, the women have also become economically

empowered in the recent past. Women are slowly taking an upper hand

in taking decision towards making purchases for the family. Inspite of

the fact that women are better placed as far as the purchases are

concerned; still most of the men have retained their authority in

managing the purchases for the family.

Gender affects service quality perceptions and the relative

importance attached to various buying behaviour. Gender differences

affect customers’ perceptions of service quality dimensions such as

effectiveness and assurance, access, price, tangibles, service portfolio,

and reliability. (Charalambos et al 2004). The following table illustrates

the distribution of male and female respondents among the customers

buying behaviour towards cars in the Chennai city.

35

Table 4.1

Distribution of Samples on the Basis of Gender

Gender

Frequency Valid Percent Cumulative Percent

Male 347 76.1 76.1

Female 109 23.9 100.0

Total 456 100.0

From the above table, it is found that 76.1% of the respondents

are male and 23.9% of the respondents are female. Hence, it is clear

that nearly one fourth of the respondents are male customers and

nearly three fourths of them are female customers of cars in Chennai

city.

Age

Age of the respondents plays a very vital role on the customer’s

of car purchase. The needs for purchase of cars will be different for

different types of age groups depending on their behavioural aspects.

Aging appears to be related especially to the risk and image barriers;

the most significant differences between mature and younger

36

consumer’s perceptions of car purchase are related to input and output

mechanisms of information. (Tommi et al 2007). The following table

expresses the purchase decision of cars by different age group of the

customers in Chennai city.

Table 4.2

Distribution of Samples on the Basis of Age

Age in Years

Frequency Valid Percent

Cumulative F1Percent

25-40 144 31.6 31.6

40-55 242 53.1 84.6

above 55 years 70 15.4 100.0

Total 456 100.0

From the above table it is found that 31.6 % of the customers are

in the age group of 25-40. 53.1 % are in the age group of 40-55. The

customers between and above 55 years of the age group are covering

15.4 percent of the total sample. Therefore it is inferred that

37

maximum number of customers belongs to the age group of 40-55

showing interest towards purchase of cars.

Education

Education is an essential tool for empowering individuals and

helps them to handle the financial situations in a much better way.

Education would lead to rational thinking which would further guide

them to exercise a prudent financial planning in their purchasing

behaviours. The following table expresses the buying behaviour of

customers with different educational qualifications towards car

purchases in Chennai city.

Table 4.3

Distribution of Samples on the Basis of Education

Educational Qualification

Frequency Valid Percent Cumulative

Percent

UG- Level 56 12.3 12.3 PG-Level 333 73.0 85.3

Others 67 14.7 100.0

Total 456 100

From the above table it is found that 12.3% of the respondents

have completed undergraduates and 72.0% of them are post

graduates. 14.7% of them have acquired various other degrees and

professionals. Hence, it is analysed that maximum number of

38

respondents of various other degrees and professions are showing

more interest towards buying of car purchases in Chennai city.

Occupation

Occupation of the individuals determines to a very great extent

the nature of transactions that they are likely to have at the time of

purchasing of cars in Chennai city. Age and occupation are associated

with service loyalty factors such as repurchase intention and loyalty

behavior. (Paul 2007)

The following table expresses the distribution of customers in

Chennai city with various occupational patterns.

Table 4.4

Distribution of Samples on the Basis of Occupation

Occupation

Frequency

Valid Percent

Cumulative Percent

State Govt Employed 145 31.8 31.8

Central Govt Employed 201 44.1 75.9

Quasi Govt Employed 50 11.0 86.9

Service Sector Employed 59 12.9 99.8

Industrial Sector Employed 1 0.2 100.0

Total 456 100.0

39

From the above table it is found that 31.8 % of the respondents

interested in purchasing car are State Govt employees and 44.1 % of

them are employed in Central Government. 11% of the respondents

interested in purchasing of car are Quasi Govt Employed and 12.9

percent are service sector employed and 0.2 are industrial sector

employed. Therefore it is obvious that most of the respondents showing

more interest towards buying behaviour of car are employed in Central

Government jobs

Earning members in the family

The number of earning members in the family influences the

buying behaviour of car purchases of consumers in Chennai city. The

following table explains the analysis for the number of earning members

in the family

Table 4.5

Distribution of Samples on the Basis of Earning members in the family

Earning member


One Member 165 36.16 25.4

Two Member 221 48.47 43.0

3,4 Members 70 15.37 100

Total 456 100.0

40


are single earning members in the family and 48.47 percent of the

respondents are two members earning in family and only 15.37

percent of the families consists of 3, 4 and above respondents who are

earning in the family. It is confirmed from the above analysis that

families have two earning are showing more interest in buying car in

Chennai city as there is comfort in traveling in car when compared to

earning members of 3,4 or more..

Family Monthly Income

The Monthly income has an important bearing on the car

purchases. The buying behaviour of car purchases of consumers will be

highly influenced by the disposable income in their hands. The increase

of competition in the car manufacturing industry has resulted to downfall

of prices of cars and has increased the buying behaviour of car

purchases among the consumers of Chennai city.

41

Table 4.6

Distribution of Samples on the Basis of Family Monthly Income

Monthly Income


Rs. 10000-20000 58 12.7 12.7

Rs.20000-30000 80 17.5 30.3

Rs. 30000- Above 255 55.9 86.2

Other 63 13.8 100.0

Total 456 100.0


have a monthly income of Rs.10000-20000. The income level of 17.6%

of the respondents is between Rs. 20000-30000 and 55.9% have a

monthly income of Rs.30000 and Above. 13.8% of the consumers have

monthly income at different ranges. From the above analysis it is clear

that consumers having a monthly income of Rs.30000 and above show

more interest towards buying behaviour of car purchases in Chennai

city

Family Size

The Family size which means number of members in the family

influences the purchasing behaviour of Cars in Chennai city.

42

Table 4.7

Distribution of Samples on the family size

Family size Frequency Valid Percent

Cumulative

Percent

Single 38 8.3 8.3

Two 72 15.8 24.1

Three 118 25.9 50.0

Four and above 228 50.0 100.0

Total 456 100.0

From the above table it is found that 50 percent of the family

possess four and above members residing together in a house. It is

followed by 25.9 percent of the families where three persons are

residing together and 15.8 percent of the families have, two persons

residing together and 8.3 percent of the families are the ones where

only one person is residing. From the above analysis it is concluded

that the families with more number of members are showing more

interest towards purchase of cars in Chennai city than single members

residing in a house.

43

Awareness of customers

The customer’s awareness is an indispensable behavioural

aspect to determine their preference, need for the product, purchase

decision information search and post purchase behaviour(Abdel

BasetI.M. Hasouneh, 2003).

Source of awareness

The customer obtain the awareness of cars through attractive

advertisements dealers/sales person’s interactions, explanation of

friends and relatives. The following percentage analysis reveals source

of customers awareness about the mid segment cars in Chennai city.

Table 4.8

Source of awareness

Frequency PercentValid

PercentCumulative

Percent 1. Advertisements 176 38.6 38.6 38.6 2. Dealers/Sales

Persons 45 9.9 9.9 48.5

3. Friends/Relatives 149 32.7 32.7 81.1 4. Others 10 2.2 2.2 83.3 5. Ad and Dealers 25 5.5 5.5 88.8 6. Ad and Friends 41 9.0 9.0 97.8 7. All 10 2.2 2.2 100.0 Total 456 100.0 100.0

The percentage analysis revealed that advertisements 38.6

percent plays highest role as source of awareness followed by 32.7

44

percent obtain their awareness through their friends and relatives. Only

9.9 percent possessed their awareness through dealers on four

wheelers. The remaining 18.8 percent consumers are influenced by the

various combinations of advertisement, dealers/sales person and

friends and relatives. It is concluded that advertisement and friends /

relatives provide more information.

Media specification

Advertisement targets the customers to give maximum

information about the product. It intends to create deep inroads over

customer preferences and convert the targeted audience to purchases.

(Arunkumar and Meenakshi N.,2006). Iindividually and combinatorial

58 percent customers obtain through advertisements. They are

successful through media newspaper and magazines, notices,

pamphlets, handbills, television, radio and internet. The percentage

distribution of 262 customers who obtained significant awareness of

product through media is presented below.

45

Table 4.9

Media specification

Media Frequency Percentage

News paper and magazines 59 22.52

Notice, pamphlets, hording 39 14.89

Television/Radio 108 41.22

Internet 56 21.37

Total 262 100.00

From the above table it is identified that television is the most

powerful media to create more awareness among car customers in

Chennai city. It is found 41.22 percent customers are influenced by TV

followed by news papers and magazines (22.52 percent) and websites

in the internet (21.37) percent are considered as significant awareness

creating media. A minimum of 14.89 percent customers obtains their

information through notices, pamphlets and hoardings. It is concluded

that press has more impact.

Brand awareness

Brand awareness among customers explains the popularity of the

product. It also indicates the customers awareness in evaluating the

brand and comparing with other before materializing their purchase

46

(Churchill G.A. Jr. and Peter J.P, 1998). The degree on awareness is

proportional to brand knowledge and brand loyalty (De Chernatony L.

and McDonald M.,2003). The following table explains the Chennai city

car customer’s awareness on various brands.

Table 4.10

One-Sample Statistics for Brand Awareness

N Mean Std.

Deviation Std. Error

Mean Fiat 456 2.7478 .93761 .04391

Hindustan Motors 456 2.7303 .91366 .04279

Hyundai 456 3.6096 .98841 .04629

Mahindra 456 3.0000 1.02496 .04800

Tata 456 3.4868 .99440 .04657

Chevrolet 456 2.9101 1.09275 .05117

Ford 456 3.0548 1.15752 .05421

Reva 456 2.3947 1.12411 .05264

Maruti 456 3.9912 1.00544 .04708

47

Table 4.11

One-Sample Test for Brand Awareness

Test Value = 3

T df Sig. (2-tailed)

Mean Difference

95% Confidence

Interval of the Difference

Lower Upper Lower Upper Lower Upper

Fiat -5.744 455 .000 -.25219 -.3385 -.1659 Hindustan

Motors -6.304 455 .000 -.26974 -.3538 -.1857

Hyundai 13.171 455 .000 .60965 .5187 .7006 Mahindra .000 455 1.000 .00000 -.0943 .0943

Tata 10.455 455 .000 .48684 .3953 .5784 Chevrolet -1.757 455 .080 -.08991 -.1905 .0107

Ford 1.011 455 .312 .05482 -.0517 .1613 Reva -11.498 455 .000 -.60526 -.7087 -.5018 Maruti 21.052 455 .000 .99123 .8987 1.0838

From the above parametric table, the mean values indicate Fiat

(mean=2.75), Hindustan (mean=2.73), Chevrolet (mean = 2.91) and

Reva (mean = 2.39) are less than 3. Similarly the mean values of

Hyundai (mean = 3.61), Mahindra (mean = 3.00), Tata (mean = 3.49),

Ford (mean = 3.05) and Maruthi (mean = 3.99) are greater than 3. But

the negative t-values of Fiat (t = -5.744), Hindustan motors (t = -6.304),

and Reva (t = -11.498) are significant except Chevrolet (t = -1.757).

This shows the Chennai city car customers have low awareness on

Fiat, Hindustan motors and Reva, but moderate awareness on

Chevrolet. It is found customers have moderate awareness on

48

Mahindra (t = 0.000) and Ford (t = 1.011). The parametric t-values

indicate Hyundai (t = 13.171), Tata (t = 10.455) are more popular and

customers in Chennai city possess high awareness on those brands.

The study revealed Maruthi (t = 21.052) is the most popular brand and

the Chennai city customers have very high awareness on Maruthi brand

cars.

Level of Product awareness and brand awareness

The general product awareness and brand awareness for a

specific duration are associated to each other. (David L. Loudon and

Albert J. Della Bitta, 2006). The customer’s awareness on cars

indirectly indicates their awareness on a particular brand. The duration

of awareness like more than 5 years, 1-5 years and recent awareness

determines their varieties and depth of awareness of a particular brand.

This research concentrated on the popular brands in Chennai city

namely Fiat, Hindustan, Hyundai Mahindra, Tata, Chevrolet, Ford, Reva

and Maruti. The awareness level for the years and level of awareness

are tested through chi-square analysis variance and the results are

presented below.

Brand acquaintances (or) proximity

The brand acquaintances, proximity induce all the customers to

have good awareness. The present study considered 9 popular brand,

49

Fiat, Hindustan Motors, Hyundai, Mahindra, Tata, Chevrolet, Ford, Reva

and Maruthi in Chennai city. The respondents are requested to express

how long they are aware of the 9 popular brands in 3 options namely

more than 6 years, 1-5 years and recently. The following frequency

distribution presented car customer years of acquaintance with different

brands in Chennai city.

Table 4.12


Brand More than 5

years 1-5years Recently Total

Fiat 210(46.1) 84(18.4) 162(350.5) 456(100)

Hindustan 187(41.0) 112(24.6) 157(34.4) 456(100)

Hyundai 181(39.7) 148(32.5) 127(27.9) 456(100)

Mahindra 146(32) 133(29.2) 177(38.8) 456(100)

Tata 196(43) 137(30) 123(27) 456(100)

Chevrolet 78(17.1) 152(33.3) 226(49.6) 456(100)

Ford 133(29.2) 144(31.6) 179(39.3) 456(100)

Reva 29(6.4) 110(24.1) 317(69.5) 456(100)

Maruthi 280(61.4) 72(15.8) 104(22.8) 456(100)

The percentages in the above table revealed that car customers

in Chennai city have more awareness on Maruthi (61.4%) for more than

5 years followed by Fiat (46.1%), Tata (43 percent) and Hyundai

(39.7%) for more than 5 years. In the years interval 1-5 years Chevrolet

50

(33.3%) obtained its momentum of popularity followed by Hyundai

(32.5%) and Mahindra (29.2%) among car customers in Chennai city

and they are aware of these brands. In recent years the percentage

analysis ascertained that the customers are highly aware of Reva

(69.5%) followed by Ford (39.3%) and Mahindra (38.8%). Therefore it

is concluded that Maruthi has more proximity with Chennai city car

customers and in recent years. The new brand induced the

anxiousness of car customers in Chennai city.

The frequency for the years of awareness and level of awareness

of brands are presented in the frequency table

Table 4.13

Level of Product awareness and brand awareness of cars

Brand Chi-square Significance

Fiat 107.651 0.000

Hindustan 101.519 0.315

Hyundai 132.825 0.000

Mahindra 70.974 0.000

Maruthi 122.043 0.001

Tata 132.386 0.437

Chevrolet 70.261 0.490

Ford 193.686 0.216

Reva 122.043 0.815

51

From the above table it is found that 249 (54.6%) customers

possess very high awareness due to more than 5 years of awareness

on the Fiat brand. The chi-square value indicates 107.651 the

significant level at 5 percent. Therefore, it can be concluded that

awareness of Fiat brand cars is well associated with number of years of

proximity with the brand. The analysis also revealed brand usage level

of awareness and brand acquaintance are very well associated in the

case of Hindustan motors (Chi-square=101.519), Hyundai (Chi-square

= 132.825) and Mahindra (Chi-square = 70.974). The Chi-square

analysis of association also ascertained that Tata (Chi-square =

132.386), Chevrolet (Chi-square = 70.261) Ford (chi-square = 193.686)

Reva (Chi-square = 122.043) and Maruti (Chi-square =122.043)

awareness level and brand acquaintance (or) brand proximity are

intimately associated with each other. This non-parametric approach

profoundly concluded that the brand acquaintance is an independent

behaviour of Chennai city car customers. Their acquaintance and

proximity for many years with brand clearly exposed their level of

awareness of the cars.

Brand of car used

The previous section encountered with Chennai city car

customers’ awareness on different brands without considering their

possession of brands. The Present section aims at studying the brands

52

of car they use and its association with level of awareness. The

following frequency distribution presents the details of brands:

Table 4.14

Brand of car used

Brand Frequency Percentage Fiat 14 3.07

Hindustan 12 2.63 Hyundai 82 17.98 Mahindra 23 5.04 Maruthi 210 46.05

Tata 62 13.61 Chevrolet 14 3.07

Ford 29 6.36 Reva 10 2.19 Total 456 100.00

From the above table it is found that Maruthi (46.05%) is a

popular brand in Chennai city used by maximum number of customers.

Hyundai (17.98%) and Tata (13.61%) come next in the popularity list in

Chennai city. Besides these three cars, Ford (6.36%) and Mahindra

(5.04%) are sporadically used by the Chennai city customers. The

possession of different brands also indicates the depth of awareness on

the products. The following analysis is going to verify the statement.

Association between brands of cars used and level of awareness

This study considered the popular brands Fiat, Hindustan Motors,

Hyundai, Mahindra, Maruthi,Tata, Chevrolet, Ford and Reva and

53

Chennai city customers also possessed these brands with considerable

percentage. The association between brands they possess and level of

awareness is established through non-parametric chi-square analysis.

Table 4.15



Fiat 77.077 0.000

Hindustan 4.742 0.315

Hyundai 77.554 0.000

Mahindra 37.938 0.000

Maruthi 19.453 0.001

Tata 3.776 0.437


Ford 5.780 0.216

Reva 1.565 0.815

The above table has given some interesting results that the

possession of cars alone cannot determine the level of awareness of

the product. In the previous section number of years and brand

proximity are well associated but the chi-square analysis revealed brand

possession of Fiat (Chi-square 77.077), Hyundai (Chi-square 77.554),

Mahindra (chi-square = 37.938) and Maruthi (Chi-square = 19.453) are

significantly associated with level of awareness. The possession of

brands Hindustan, Tata, Chevrolet, Ford and Reva are not associated

54

with level of awareness of the cars they possess. It can be concluded

that the possession of popular brands that are well acquainted with

them for more than 5 years alone are well associated with level of

awareness on the products.

Number of cars used by the customers

The car customers in Chennai city use one, two (or) more number

of cars based on their utility, need and recognition. The following table

presents the frequency distribution of number of cars used by the

customers.

Table 4.16


No. of cars Frequency Percentage

One 380 83.3

Two 48 10.5

Three 20 4.4

Four and above 8 1.8

Total 456 100

The frequency distribution clearly indicated that in Chennai city

83.3 percent of customers possess single car for their personal and

family use. It is also found 10.5 percent and 4.4 percent have 2 and 3

cars respectively for them and their family. A minimum of 1.8 percent

55

possess four and above number of cars for their personal, business and

family use. The possession of number of cars and level of awareness

on cars is tested in the following section.

Association between number of cars and customers level of

awareness

The number of cars with different brand name possessed by

customers would pave them a way to know the characteristic features

and awareness of particular brands. The performance of chi-square

analysis yields the following results.

Table 4.17

Association between number of cars and customers level of awareness


Fiat 117.422 0.000

Hindustan 21.341 0.046

Hyundai 35.668 0.000

Mahindra 31.290 0.002

Tata 27.662 0.006


Ford 21.171 0.048

Reva 65.800 0.000

Maruthi 60.675 0.000

56

From the above-consolidated table it is found that number of cars

possessed by customers in Chennai city is well associated with the

brand awareness on Fiat (Chi-square 117.422), Hindustan (Chi-square

= 21.341), Hyundai (Chi-square = 35.688) and Mahindra (Chi-square =

31.290). It is also found that car brands Tata (Chi-square 27.662),

Chevrolet (Chi-square = 40.311), Ford (Chi square = 21.171), Reva

(Chi-square = 65.800) and Maruthi (Chi square = 60.675) are

significantly associated to number of cars possessed by Chennai city

car customers. Therefore it can be concluded that possession of many

number of cars divided the customer’s variety of depth in the awareness

of cars and its famous characteristic features. The number of cars

increased awareness for easy maintenance, mileage and spare parts

availability.

Nature of finance

The car customers in Chennai city purchase their cars through

own financial supports (or) other commercial financial sources. The

customers also materialize their purchase by the contribution of own as

well as borrowed finance. The following frequency distribution

establishes the nature finance to car purchase in Chennai city.

57

Table 4.18

Nature of finance

Frequency Percent Valid

Percent

Cumulativ

e Percent

1 Own

Finance 191 41.9 41.9 41.9

2 Borrowed

Finance 130 28.5 28.5 70.4

3 Both 135 29.6 29.6 100.0

Total 456 100.0 100.0

From the above table, it is found that 41.9 percent (191) purchase

their cars through own finance followed by 28.5 percent and 29.6

percent materialize their purchase by borrowing from banks, and private

financers.

Association between nature of finance and customers satisfaction

K-means cluster analysis classified the car customers in Chennai

city into three types namely comfort seekers, gratified customers and

subsistent customers. The nature of finance always steadfastly fix in

their minds until they get their desired satisfaction. The association

between nature of finance and customer satisfaction is hypothesized

and the cross tab chi square analysis is performed and presented in the

table below.

58

Table 4.19


Cluster Number of Case Total

1 2 3 1

1.00

2.00

3.00

Own Finance 84 54 53 191

Borrowed Finance 41 37 52 130

Both 40 42 53 135

Total 165 133 158 456

Table 4.20

Chi-Square Tests for Association between nature of finance and

customers satisfaction

Value df

Asymp.

Sig. (2-

sided)

Pearson Chi-Square 10.362(a) 4 .035

Likelihood Ratio 10.401 4 .034

Linear-by-Linear Association 8.218 1 .004

N of Valid Cases 456

0 cells (.0%) have expected count less than 5. The minimum expected

count is 37.92.

From the above tables (4.19 & 4.20) it is found that in the group’s

comfort seekers, gratified and subsistent customers, the maximum

percentage uses their own finance. The Pearson chi-square value

59

10.362, p-value 0.0035 is statistically significant at 5 percent level.

Therefore it is concluded that there is a deep association between

nature of finance and customer satisfaction., The perceptional

difference among Chennai city car customers is well influenced by the

nature of finance they used to purchase the cars.

Borrowing Sources

The car customers in Chennai city borrow their finance from

banks, non-banking institutions and other private financers. The

percentage analysis expressed the contribution of financial sources.

From the above table it is found that out of 265 (51.54 percent ) out of

456 borrow from different sources.

Table 4.21

Borrowing Sources

Sources Frequency Percentage

Banks 180 67.92

Non banking 15 05.66

Private 70 26.42

Total 265 100

The frequency distribution indicates, banks are the most popular

financial sources (67.92 percent) for Chennai city car customers

followed by 26.42 percent of private financers. It is also found a meagre

60

5.66 percent customers are supported by other non-banking financial

institutions. It is concluded that bank finance is the most popular one.

Customers opinion on interest rate and road tax

The car users in Chennai city are hampered by the high rate of

interest on their borrowing and excess road tax to get their high level of

satisfaction. The enormity of interest and road tax makes them to

bewilder in the purchase decision process. The response of customers

is presented in Likert’s five-point scale, which ranges from very high to

very low. The application of t-test of company for which the mean value

is applied and the results are presented below.

Table 4.22

One-Sample Statistics for Customers opinion on interest rate and road tax

N Mean Std.

Deviation

Std. Error Mean

Rate of interest

charges 456 1.5614 1.45124 .06796

Road tax 456 1.9561 1.07225 .05021

61

Table 4.23

One-Sample Test for Customers opinion on interest

rate and road tax

Test Value = 3

T df Sig. (2-

tailed)

Mean

Difference

95% Confidence

Interval of the

Difference


Rate of

interest

charges

-

21.168 455 .000 -1.43860 -1.5722 -1.3050

Road tax -

20.789 455 .000 -1.04386 -1.1425 -.9452

From the above tables, (4.22 & 4.23) it is found that the mean

values for interest rate (mean = 1.56) and road tax (mean = 1.95) are

very near to 2, which is assigned as high in Likert’s five-point scale.

The t-values are –21.168 and –20.789 are statistically significant at

percent level. This shows that the Chennai city car users have

profoundly realized that high interest rate is charged by the financial

institutions to purchase their cars. It is also realized that the

Government imposed road tax is high and they found it difficult to pay

their loans.

62

Research Proposition 1

Product awareness does not predict brand awareness and

experience with the product.

The product awareness is a general phenomenon whereas brand

awareness is a particular concept. The research issue highlights the

possible relationship with level of awareness and brand choice and

experience with the brand. The use of chi-square analysis of

association established significant association between awareness level

of customers on various brand and their experience with products (ref.

Table no 4.13, 4.15 and 4.17). Therefore it is concluded that the

awareness level of car purchasers in Chennai city is predicted from

brand name, product usage and proximity with the brand. Therefore it

is concluded that brand name, brand attributes predict their level of

awareness.

Factors influencing the customers towards the purchase of cars

In literature review chapter, researcher clearly identified the type

of fuel. Purpose of car purchase, factors influencing to materialize the

purchase, purchase decision and reason for selecting the particular

brand are the predominant factors influencing the car customers in

Chennai city. This section aimed at exploring the above-mentioned

factors in detail.

63

1. Type of fuel

In the present technological augmentation customers are very

meticulous about fuels, petrol, diesel, LPG and Battery, used in the

cars. The percentage analysis is applied on the various type of fuel

used in the cars and the following results are presented.

Table 4.24

Type of Fuel influences the customers towards the purchase of

cars

Exd Frequency Percent Valid

Percent

Cumulative

Percent

1 Petrol 269 59.0 59.0 59.0

2 Diesel 118 25.9 25.9 84.9

3 LPG/Battery 9 2.0 2.0 86.9

4 Battery 5 1.1 1.1 88.0

5 LPG/Petrol 55 12.0 12.0 100.0

Total 456 100.0 100.0

From the above table, it is found that the maximum of 59 percent

(269) of customers use petrol and this fuel is more popular among

Chennai city car users. Diesel is also preferred by 25.9 percent (118)

and 12.0 percent (55) of customers Prefer LPG and Petrol. The

minimum percentage (2%, 1.1%) of customers use LPG and battery for

the mobility of their cars.

64

Purpose of using car

The car users explicitly answered the options personal and social

cause office and business for the usage of cars. The percentage

analysis revealed the purpose of frequent use of cars.

Table 4.25

Purpose of using car influences the customers towards

the purchase of cars

Frequency Percent Valid

Percent

Cumulative

Percent 1 Personal and Social 266 58.3 58.3 58.3

2 Office and Business 45 9.9 9.9 68.2

3 Both 145 31.8 31.8 100.0

Total 456 100.0 100.0

From the above table of percentage analysis it is found that 58.3

percent (266) customers use their cars for personal and social causes

followed by 9.9 percent (45) customers found cars are useful for office

and business purpose. It is ascertained that 31.8 percent (145)

customers use their cars for personal, social, office and business

purposes. It is concluded that people mostly use the case for personal &

Social purposes.

65

Reasons for buying a present car:

In Chennai city customers materialize their purchase due to the

reasons prestige and status, luxury, comforts and high technology.

They responded to the reasons in orderly manner. The ranking analysis

is applied and the following results are obtained.

Table 4.26

Reasons for buying a present car

Reasons Ranks Ranks

Prestige and status 2.1878 2

Luxury 2.4773 3

Comfort 1.1622 1

High tech 2.8966 4

The ranks of reasons clearly showed comfort is the primary

reason for car purchase in Chennai city followed by prestige and status.

The analysis also revealed luxury and high tech are the subsequent

reasons to materialize the car purchase in Chennai city.

Factors influencing to buy the car

The purchase of car is generally influenced by variable style and

design, brand name and fuel efficiency. The customers also consider

seating capacity, Price and appearance of cars before making their

purchase decision. The responses of customers to these reasons are

66

analyzed though factor analysis and presented below. This helps to

identify the predominant reasons replete in the minds of customers.

Table 4.27

KMO and Bartlett's Test for influencing to buy the car

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .442

Bartlett's Test of Sphericity Approx. Chi-Square 107.512

Df 21

Sig. .000

The KMO and Bartlett’s test for sampling adequacy value is .442

and chi-square value of Bartlett’s test of sphericity is 107.512 are

statistically significant at 5 percent level. The following total variance

table obviates the emergence of number of factors.

Table 4.28

Total Variance Explained for influencing to buy the car

Component Initial Eigenvalues Rotation Sums

of Squared Loadings

Total % of

VarianceCumulative

% Total

% of Variance

Cumulative %

Style and Design

2.481 35.444 35.444 2.084 29.771 29.771

Brand Name

1.792 25.600 61.044 1.886 26.946 56.717

67

Fuel Efficiency 1.569 22.408 83.452 1.871 26.735 83.452

Seating Capacity .564 8.053 91.505

Price .416 5.944 97.448

Appearance .139 1.985 99.433

Others .040 .567 100.000

Extraction Method: Principal Component Analysis.

From the above table it is found that three factors emerged that of

seven reasons influencing the customers to buy the car. These seven

variables explained 83.452 percent variance. The three Eigen values

2.084, 1.886 and 1.871 and individual variances 29.771, 26.735 percent

indicated the emergence of 3 significant factors. The three factors are

subject to varimax rotation for the suitability of variable loadings as

presented below.

Table 4.29

Rotated Component Matrix for influencing to buy the car:

Component

1 2 3 Brand Name -.933

Others .892 Seating capacity .910

Appearance -.822 Fuel efficiency .821

Style and Design -.801 Price .684

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Rotation converged in 5 iterations.

68

From the above table it is found that the first factor comprises

three variables style and design (.933), brand name (.801) and

appearance (.822). Therefore this factor is named “Product attraction”.

The second factor comprises two variables fuel efficiency (.910) and

seating capacity (.821). Therefore the factor extracted is “product

suitability”. The third factor is “cost approach” because of the two

variable loadings car price (.892) and maintenance expenditure (.684).

It is concluded that the customers in Chennai city are influenced

by the attractiveness of cars and its suitability of usage with comforts

and conveniences. At the same time their perception is entwined with

cost of buying cars.

Purchase decision making

The purchase decision is not a unilateral phenomenon, but it is

accomplished through consultation with family members. (Hawkins

Best and Coney , 2003). A customer generally discusses with spouse,

children and head of the family after they convince themselves. The

following table gives the percentage of decision makers in the family of

car customers in Chennai city.

Influence in decision making

The customers take ultimate decision and they decide to

materialize the car purchases. But certain degree of influence by family

69

members is definitely found in the purchase decision of cars. The

previous result identified 272 (59.6) percent. Customers take their own

decision with certain well-defined degree of influence from spouse,

children and elders in the family.

Table 4.30


Influences Frequency Percentage

Spouse 149 51.83

Children 89 32.72

Elders 42 15.45

Total 272 100.00

From the above table it is found that, where the customers take

their own decision, it is predominantly influenced by the spouse. A

maximum of 51.83 percent spouses influence the customers during

decision making followed by 32.72 percent influence of children and

15.45 percent of elders. The seemingly autocratic decision makers also

are influenced by the family members significantly.

Reasons for brand selection

The intensified exploration literature reviews identified price,

quality, mileage, comforts and convinces are the major issues

addressed by the car customers during their purchase decision process.

70

The first conceived the notions of seating capacity, less maintenance

and facilities provided before they take profound decision on purchase

(Heinemann Oliver R , 1997). In this study the customers of car

purchase in Chennai city expressed their reasons for selecting one

particular brand of car in order. At this time the factors influencing the

brand selection must be identified to underpin the reasons for selecting

the brand through factor analysis. The results are as follows.

Table 4.31

KMO and Bartlett's Test as Reasons for brand selection

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. .421

Bartlett's Test of

Sphericity

Approx. Chi-

Square 133.981

Df 28

Sig. .000

From the above table it is found that KMO measure of sampling

adequacy .421, Bartlett’s test of sphericity chi-square value 133.981 are

statistically significant at 5 percent level, It indicates the possibility of

meaningful data reduction eight reasons for brand selection. The

number of factors is ascertained through the following total variance

table.

71

Table 4.32

Total Variance Explained as Reasons for brand selection

Component Initial Eigenvalues Rotation Sums of Squared

Loadings

Total % of

VarianceCumulative

% Total

% of Variance

Cumulative %

Price 2.753 34.415 34.415 2.419 30.237 30.237

Quality 1.950 24.379 58.794 2.011 25.132 55.369

Mileage 1.622 20.281 79.075 1.896 23.706 79.075

Comforts

and

Convenience

.912 11.399 90.474

Seating

capacity .373 4.656 95.130

Less

Maintenance .175 2.192 97.321

Facilities

Provided .145 1.808 99.130

Other

reasons .070 .870 100.000


From the table the three Eigen value 2.419, 2.011, 1.896 and

individual variance 30.237 percent, 25.132 percent and 1.896 percent

indicates the formation of three meaningful factors. The following

explains the variable loadings.

72

Table 4.33

Rotated Component Matrix a Reasons for brand selection

Component

1 2 3

Facilities provided -.881

Other reasons .751

Mileage .655

Comforts and convenience .901

Price -.732

Less maintenance -.655

Quality -.920

Seating capacity .909

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.Rotation converged in 12 iterations.

The first factor is obviated as “Cost Orientation” due to the

variable loadings. Price (.881), mileage (.751) and less maintenance

(.655). It is found the factor “Comfortability” emerged as a composition

of the variable loadings comforts and convenience (.901) and seating

capacity (.732). The third factor formed is “Qualitative facilities”

because of the variable inclusions quality (.920) and facilities provided

(.909). Therefore it is concluded that the brand selection of Chennai

city car customers lean upon cost oriented factor of price and

maintenance and customers realized comfortability. The quality of cars

and facilities offered in cars make them to prefer specific brand.

73

Research Proposition

The customers explicitly explained factors influencing the

purchase of car as well as reasons for selecting the brand. Factor

analysis clearly extracted three factors each from influences and brand

selection respectively. The factors extracted have the names similar to

each other. The product and brands are very closely associated.

Purchase of product is same as purchase of a particular brand. This

leads to the following research proposition.

There is a deep association between purchase influencers of cars

and brand selection reasons.

Proof:

Factor analysis by principal component method extracted three-

purchase influencers product attraction. Product suitability and cost

approach, similarly the three factors cost orientation, comfortability and

qualitative facilities represented for brand selection reasons. The factor

scores of influencers of cars and brand selection became continuous

variables. The selection of factors for relationship is done through

underlying variables. The first factor “Product attraction” of purchase

influencer is well related to “Qualitative approach” because of the

underlying variable quality. It is obvious to relate product suitability to

comfortability and cost approach to cost orientation. But this

74

hypothecated relationship need to be established empirically. K-means

cluster analyses are applied on these factors of influencers and brand

selection reason separately and following results are obtained.

Clusters of influencers

The two clusters are formed for the three factors product

attraction, product suitability and cost approach in the following

manners.

Table 4.34

Final Cluster Centers for product attraction, product suitability and

cost approach

Cluster

1 2

Price 3.02 .62

Quality 2.83 .52

Mileage 2.81 .82

Comforts and Convenience 3.57 .70

Seating capacity 4.43 .42

Less Maintenance 4.03 .78

Facilities Provided 4.89 .14

Other reasons 1.85 .01

75

Table 4.35

Number of Cases in each Cluster

Cluster Moderators 129.000

sensitive customers 327.000

Valid 456.000

Missing .000

The first cluster consists 129 (28.29 percent) with moderate

influence of all these factors to purchase the cars. Therefore this

cluster is called moderators. The second cluster with .327 (71.71

percent) of customers highly influenced by attraction, suitability and

cost, so they are called sensitive customers. Similarly the same K-

means cluster analyses is applied on three factors cost orientation,

comfortability and qualitative facilities of brand selection reasons, the

results are presented as follows:

Table 4.36

Final Cluster Centers for cost orientation, comfortability and

qualitative facilities of brand selection reasons

Cluster

1 2 Style and Design .56 3.90

Brand Name .71 3.16 Fuel Efficiency .62 2.37

Seating capacity .75 3.64 Price .68 3.01

Appearance .33 4.27 Others .01 1.09

76

Table 4.37


Cluster Transcendental analysors 335.000

Superfluous customers 121.000

Valid 456.000

Missing .000

The first cluster comprises 335 (73.46 percent) customers with

strong analytical reasons for brand selection and the group is named

Transcendental analysors”. The other groups with 121(26.54 percent)

of customers who moderately apply the reasons to select the brand

“Superfluous customers”. The customers in Chennai city have two

strong perceptions in reasoning the brand selection before they

purchase.

After the formation of two clusters each for the factors of

influencers and brand selection, the association can be achieved

through cross tabs with chi-square through cross tabs with chi-square

test.

77

Table 4.38

Clusters for factors of influencers and brand selection

Cluster Number of Case Total

1 2 1 Cluster Number of Case

Transcendental analysors

24 311 335

Superfluous customers 105 16 121 Total 129 327 456

Table 4.39

Chi-Square Tests for factors of influencers and brand selection

Value df

Asymp.

Sig. (2-

sided)

Exact

Sig. (2-

sided)

Exact

Sig. (1-

sided)

Pearson Chi-

Square 277.730(b) 1 .000

Continuity

Correction(a) 273.819 1 .000


Fisher's Exact

Test .000 .000

Linear-by-Linear

Association 277.120 1 .000


Computed only for a 2x2 table, 0 cells (.0%) have expected count less

than 5. The minimum expected count is 34.23.

78

From the above tables it is found that the maximum of 68.2

percent customers (311) are sensitive to the influence of purchase and

transcendental in analysis I the brand selection. The chi-square value

277.730 is statistically significant at 5 percent level. Therefore the

research proposition is proved to say there is an association between

influencers and analytical reasons for brand selection. It is concluded

that they apply the Chennai city car customers influencing factors during

the appropriate brand selection.

SWOT Analysis

This sector is intended to ensure the SWOT factors perceived by

car users in Chennai city. They responded to SWOT factors and

expressed their opinion through numerical ranks. The extensive

literature reviews identified maintenance cost, availability of spares.

Service facilities, availability of multi brand and loan facilities

strengthened the product characteristics and purchase decision of the

customers. It is also ascertained that variables high cost, increase in

fuel price competition from low segment, low mileage and seating

capacities weaken the purchaser to think twice before they purchase.

The economic liberalization and customer awareness pave the way for

several opportunities for car business in Chennai city. At the same time

the dimension of threat to the car sales is projected from two- wheeler

demands cabs/call taxi, changing technology, offer for high segment

79

cars and poor road conditions in Chennai city. These SWOT factors are

examined through ranking in technique to identify the crucial factors

influencing customers and leading to ultimate customer satisfaction.

The ranking analysis clearly revealed

Table 4.40

SWOT Ranking analysis for strength factors for purchase of cars

Variable Numerical

Value

Ranks

Maintenance Cost 1.6321 1

Availability of spares 2.2615 3

Service facilities cars 1.9699 2

Availability of multi-brands 3.4629 5

Loan facilities 3.3881 4

From the above table the least numerical value indicates the

maximum occurrence of rank 1 and it was given first rank. In this way

the maintenance cost factor plays a vital role to create strength for the

car business in Chennai city followed by service facilities and availability

of spares. The availability of loans from Public, Private sector banks

and other financial institutions created more viability for car purchasing.

The customers noticed the availability of numerous brands of cars

allowed them to select and purchase a car at their own convenience

80

created a conducive environment for car business in Chennai city. On

the other hand customers are able to realizes

the weakness in the following manner:

Table 4.41

SWOT Ranking analysis for weakness factors for purchase of cars

Weakness factors Numerical

Value

Ranks

High cost 1.9962 2

Increase in fuel price 1.7994 1

Competition from low segment 2.9792 5

Low mileage 2.3945 3

Seating capacities 2.9283 4

The ranking analysis ascertained that continuous increase in the

fuel price followed by high cost of cars are the major weakness factors

for purchase of cars affecting the customers and make them to

procrastinate the purchase. The low mileage, seating capacity and

competition from low segment hamper the customer consumption in

Chennai city. But with the above-mentioned prevailing strength, the car

business in Chennai city possesses good opportunities for the

successful venture of customer maximization. The following ranking

analysis table elucidates the opportunity factors.

81

Table 4.42

SWOT Ranking analysis for opportunity factors for purchase of

cars

Variables Numerical

Value

Ranks

Draw backs of small cars 2.4354 3

Entry of MNCs 2.6995 5

Price of high segment cars 2.1835 2

Effective advertisement 2.1166 1

Attractive offer 2.4903 4

The ordering ranks clearly indicated prospective opportunities for

purchasing of cars are abundantly found in effective advertisement and

price of high segments cars. These two reasons attract the customers

to materialize the purchase dynamically. The drawbacks of small cars

open a fascinating opportunity for purchase of cars in Chennai city. The

entry of MNC’s and price of high segments cars create a conducive

business environment in Chennai city for the purchase of cars.

The futuristic threats analogously occur in the purchase of cars,

demand for two wheelers and availability of cabs/call taxi in abundance

pose threat to purchase of cars in Chennai city. The following ranking

analysis identified the threat factors.

82

Table 4.43

SWOT Ranking analysis for threat factors for purchase of cars

Variables Numerical Value

Ranks

Demand for two wheelers 2.8377 4

Cab/Call taxi 2.8900 5

Changing technology 1.8660 1

Offer for high segment cars 2.4495 3

Poor records 2.1151 2

The criterion for ranking high lights that changing technology is

the primary threat to purchase of cars in Chennai city followed by poor

road condition in the Chennai city. It is also found that offer for high

segment cars and demand for two wheelers reduces the enthusiasm of

purchasers and widens the threat for car purchase. Easy accessibility

of cabs/call taxi also increased the weightage of threat to car purchase

in Chennai city.

The relationship between personal factors and SWOT factors of

car purchase

The opinion of car purchasers regarding strength, weakness,

opportunity and threat factors arise from their demographic

segmentation, which affects their perception on SWOT factors. In the

present study the independent demographic variables gender, age,

education, occupation, number of earning members, monthly income

83

and family size are considered to verify their effectiveness on SWOT

factors.

1. Relationship between gender and SWOT factors.

The different perceptions of male and female car purchasers on

SWOT factors are presented below.

Table 4.44

ANOVA for relationship between gender and SWOT factors

Sum of Squares

df Mean

SquareF Sig.

Strength factor availability of multi brand

Between Groups

11.315 1 11.315 5.893 .016

Within Groups

332.193 173 1.920

Total 343.509 174 Strength factor

loan facility Between Groups

14.904 1 14.904 3.892 .050

Within Groups

831.105 217 3.830

Total 846.009 218 Weakness factors high

cost

Between Groups

8.488 1 8.488 6.929 .009

Within Groups

318.508 260 1.225

Total 326.996 261 Opportunity factor draw

backs of small cars

Between Groups

15.423 1 15.423 6.911 .009

Within Groups

461.955 207 2.232

Total 477.378 208

84

The Analysis of variable revealed that the male and female

customers differ in the strength factors availability of multi brand (F =

5.893) and loan facility (F = 3.892) significantly at 5 percent level. The

post hoc test identified the female consumers profoundly believe

availability of multibrand (mean rank = 2.824) and loan facility (mean

rank = 2.73) and strengthen of car purchases in Chennai city. The male

consumers have less belief over these strength factors. Further it is

also identified that weakness factor high cost (F = 6.929) and

opportunity factor draw backs of small cars (F = 6.929) differ

significantly with respect to gender. The mean ranks indicate that male

car consumers in Chennai city aware of high cost (mean = 1.9364) as

the primary reason for weakness. In the case of opportunity factors the

female customers of cars purchasers in Chennai city realized the draw

backs of small cars (mean = 1.7586) create more opportunity for car

purchase...

Influence of Age

The three age group of car purchasers 25-40 years and above 55

years and their perceptional levels on SWOT is displayed in the ANOVA

Table below.

85

Table 4.45

ANOVA for Influence of Age

Sum of Squares

df Mean

Square F Sig.

Strength factor availability of multi

brand

Between Groups

34.554 2 17.277 9.618 .000

Within Groups

308.955 172 1.796

Total 343.509 174

Strength factor loan facility

Between Groups

30.232 2 15.116 4.002 .020

Within Groups

815.777 216 3.777

Total 846.009 218

Weakness factor low milege

Between Groups

9.860 2 4.930 3.220 .042

Within Groups

387.293 253 1.531

Total 397.152 255

Opportunity factor price of high

segments cars

Between Groups

18.354 2 9.177 5.355 .005

Within Groups

471.290 275 1.714

Total 489.644 277

Threat factor demand for two

wheelers

Between Groups

33.855 2 16.927 7.575 .001

Within Groups

420.114 188 2.235

Total 453.969 190

Threat factor offer for high segment

cars

Between Groups

9.654 2 4.827 3.957 .021

Within Groups

262.291 215 1.220

Total 271.945 217

86

It is found that the strength factors availability of multi brand

(F=9.618), loan facility (F = 4.002), the weakness factor low mileage (F

= 3.220) differ significantly. The mean use comparison of ranks of

these factors deduced that the customers in the age group 25-40 (mean

= 2.80) have good inclination towards the availability of multibrand cars

in the market and this perception added strength to car purchase in

Chennai city. The customers in the age group above 55 (mean =

2.7407) are able to trace the strength of car purchase lie in the loan

facility. They feel car purchases in Chennai city can be materialized

rapidly when loans for purchase of cars are available freely.

Similarly the aged customers in the group above 55 (mean =

2.11) perceived the low mileage of their cars impedes the car purchases

in Chennai city. The analysis of variance ascertained that price of high

segments cars (F=5.355) creates optimistic environment in the

perception of customers in different age group. It is also observed that

the customers differ in the perception regarding threat factors demand

for two-wheelers (F = 7.525) and offer for high segment cars (F = 3.957)

significantly at 5 percent level. The post hoc descriptive imply that the

customers in the age group 25-40 (mean = 2.0833) feel the price of high

segment cars pose good opportunity for them to purchase new cars.

The other customers in the age group above 55 (mean = 1.9048)

perceived the demand for two wheelers in a threat diminish the frequent

87

car purchase in Chennai city. The threat observed by the customers in

the age group 40-55 (mean = 2.2899)

Influence of Education

The car purchasers in Chennai city with UG level and PG level

education have their notions and they are extracted microscopically

through analysis of variance.

Table 4.46

ANOVA for influence of education

Sum of

Squares df

Mean

Square F Sig.

Strength factor

service facilities

cars

Between

Groups 10.899 2 5.450 4.915 .008

Within

Groups 364.800 329 1.109

Total 375.699 331

Strength factor

loan facility

Between

Groups 108.227 2 54.114 15.843 .000

Within

Groups 737.782 216 3.416

Total 846.009 218

Weakness factor

increase in fuel

price

Between

Groups 7.809 2 3.904 3.341 .037

Within

Groups 380.951 326 1.169

Total 388.760 328

88

Sum of

Squares df

Mean

Square F Sig.

Weakness factor

low milege

Between

Groups 18.587 2 9.293 6.211 .002

Within

Groups 378.565 253 1.496

Total 397.152 255

Threat factor

demand for two-

wheelers

Between

Groups 15.679 2 7.839 3.363 .037

Within

Groups 438.290 188 2.331

Total 453.969 190

The F-values in table shows that the strength factors service

facilities of car (F = 4.915), loan facility (F = 15.843) and weakness

factors increase in fuel price (F = 3.341) and low mileage (F = 6.211)

differ significantly at 5 percent level. The mean wise comparison

deducted that the customers with PG qualification (mean = 1.9056) and

UG qualification (mean = 2.6957) realized the strength of car purchase

prevailing proper service facilities and easy availability of loan facilities

in Chennai city. The PG qualified car purchase customers (mean =

1.7319) found increase in fuel price is the primary weakness and UG

qualified car purchase customers (mean = 1.9250) feel the low mileage

as the predominant weakness factor for car purchase. The further

analysis revealed demand for two-wheeler (F = 3.363) differs

89

significantly at 5 percent level with respect to educational qualification.

The mean wise analysis revealed that PG qualified customers (mean =

2.7215) perceived the demand for two wheelers as major threat to

purchase of cars in Chennai city.

Influence of occupational status

The car purchasers in Chennai city are segmented by their

occupational status and their perceived notions regarding SWOT are

analyzed through ANOVA and Presented below.

Table 4.47

ANOVA for Influence of occupational status

Sum of Squares df Mean

Square F Sig.

Strength factor maintenance cost

Between Groups 18.476 4 4.619 5.487 .000

Within Groups 263.477 313 .842


availability of spares Between Groups 12.409 4 3.102 3.305 .011

Within Groups 300.360 320 .939


availability of multi brand

Between Groups 40.461 4 10.115 5.674 .000

Within Groups 303.047 170 1.783

Total 343.509 174 Strength factor loan

facility Between Groups 38.082 4 9.520 2.522 .042

Within Groups 807.927 214 3.775

Total 846.009 218

90

Sum of

Squares df Mean Square F Sig.

Weakness factor high cost

Between Groups 14.034 4 3.508 2.881 .023

Within Groups 312.962 257 1.218

Total 326.996 261 Weakness factor

increase in fuel price Between Groups 17.485 4 4.371 3.815 .005

Within Groups 371.275 324 1.146

Total 388.760 328 Weakness factor

competition from low segment

Between Groups 45.327 4 11.332 6.449 .000

Within Groups 328.589 187 1.757

Total 373.917 191 Weakness factor low

milage Between Groups 45.430 4 11.357 8.105 .000

Within Groups 351.722 251 1.401

Total 397.152 255 Weakness factor seating capacity

Between Groups 46.610 4 11.652 6.045 .000

Within Groups 420.243 218 1.928

Total 466.852 222 Opportunity factors draw backs of small

cars

Between Groups 42.008 4 10.502 4.921 .001

Within Groups 435.370 204 2.134

Total 477.378 208 Opportunity factor

attractive offer Between Groups 24.303 4 6.076 3.426 .009

Within Groups 450.423 254 1.773

Total 474.726 258 Threat factor offer for

high segment cars Between Groups 19.485 4 4.871 4.110 .003

Within Groups 252.460 213 1.185

Total 271.945 217

91

Application of analysis of variable revealed that the strength

factors maintenance cost (F = 5.487), availability of spares (F = 3.305),

availability of multi-brand (F = 5.674) and loan facility (F = 2.522) differ

significantly at 5 percent level. The descriptive of means implies that

the central government employees consistently feel (mean ranks = 1.00,

2.00, 2.50 and 2.33) strength of car purchases depend upon

maintenance cost, availability of spares, multi brand cars and loan

facilities. Occupational status identified the importance of all weakness

factors of car purchase significantly. It is found that industrial sector

employees (mean ranks = 1.7095) perceived high cost is the major

weakness of car purchase in Chennai city.

The State Government employee’s perceived (mean=1.56)

increase in fuel price and Central Government employees (mean =

2.00) feel competition from low segment cars are the major weakness of

car purchase. The Central Government employees possess same

opinion on low mileage (mean = 1.8462) and seating capacity (mean =

1.8571) are also considered as the weakness factors of car purchase.

The two opportunity factors draw backs of small cars (F = 4.921) and

attractive offer (F = 3.426) differ significantly at 5 percent level with

respect to occupation. The unique threat factor offers for high segment

cars (F = 4.110) also differ significantly based on occupation. The

mean usage comparison revealed that State Government employee’s

92

feel draw backs of small cars (mean = 2.0722) and Central Government

employee’s perceived attractive offer (mean = 1.7143) are the possible

opportunities for purchase of cars. The industrial sector employees do

not feel offer for high segment cars (mean = 3.1429) is not a major

threat to car purchase in Chennai city.

Influence of Number of earning members in the family

The car purchasers in Chennai city with different earning

members in the family have different perceptions about SWOT in

Purchase cars, the results are presented below.

Table 4.48

ANOVA for Influence of Number of earning members in the family

Sum of Squares df

Mean Square F Sig.

Strength factor availability of

spares

Between Groups

6.513 2 3.256 3.424 .034

Within Groups

306.257 322 .951

Total 312.769 324 Strength factor service facilities

cars

Between Groups

7.315 2 3.658 3.267 .039

Within Groups

368.384 329 1.120

Total 375.699 331 Weakness factor increase of fuel

price

Between Groups

10.196 2 5.098 4.390 .013

Within Groups

378.564 326 1.161

Total 388.760 328

93

Sum of Squares df

Mean Square F Sig.

Weakness factor competition from

low segment

Between Groups

14.388 2 7.194 3.782 .025

Within Groups

359.529 189 1.902

Total 373.917 191 Weakness factor seating capacity

Between Groups

31.769 2 15.885 8.032 .000

Within Groups

435.083 220 1.978

Total 466.852 222 Opportunity factors draw

backs of small cars

Between Groups

19.366 2 9.683 4.355 .014

Within Groups

458.012 206 2.223


price of high segments cars

Between Groups

19.679 2 9.839 5.758 .004

Within Groups

469.965 275 1.709


attractive offer Between Groups

11.428 2 5.714 3.157 .044

Within Groups

463.298 256 1.810

Total 474.726 258 Threat factor cabs/call taxi

Between Groups

20.649 2 10.325 4.787 .009

Within Groups

424.931 197 2.157

Total 445.580 199 Threat factor

changing technology

Between Groups

17.161 2 8.580 7.421 .001

Within Groups

350.346 303 1.156

Total 367.507 305

The significant difference in the mean values of strength factors is

found in the variables service facilities (F= 3.267), availability of spares

94

(3.424). The weakness factors increase in fuel price (F = 4.390),

competition from low segment cars (F = 3.782) and seating capacity (F

= 8.032) differ significantly at 5 percent level. The mean wise analysis

already indicated the customers in Chennai city with 2 earning members

in family. Perceived availability of spares mean = 2.2171) and service

facilities (mean = 1.883) create strength from car purchasers in Chennai

city. The same category customers feel increase in fuel price (mean =

1.6543) is the major weakness for car purchase. The customers with

unique earning member in the family identified competition from low

segment (mean = 2.824) and seating capacity (mean = 2.7209) are the

predominant weakness for car purchase in Chennai city.

In the case of opportunity and threat factors drawbacks of small

cars (F= 4.355), Price of high segments cars (F = 5.758), attractive offer

(F = 3.157), Cabs/Call taxi (F = 4.787) and changing technology (F =

7.421) differ significantly with respect to number of earning members.

On comparing the mean values, it is found the car purchasers in

Chennai city with unique earning members in the family realized draw

backs of small cars (mean = 2.27) and attractive offer (mean = 2.3434)

create conducive opportunity for car purchasers. The customers with 3

or 4 earning members in the family do not feel price of high segment

cars (mean = 2.50) is a main opportunity for car purchase. The 3 or 4

earning member customers feel cabs/call taxi (mean = 3.6333) and

95

changing technology (mean = 2.400) are not a major threat to car

business in Chennai city.

Influence of family Income

It is expected to identify the perceptional difference among

Chennai city car customers with respect to income segmentation. The

analysis is done by exploiting ANOVA and presented below.

Table 4.49

ANOVA for Influence of family income

Sum of

Squares df

Mean

Square F Sig.

Strength factor

maintenance cost

Between

Groups 9.666 2 4.833 5.591 .004

Within

Groups 272.287 315 .864

Total 281.953 317

Weakness factor

increase in fuel

price

Between

Groups 13.570 2 6.785 5.896 .003

Within

Groups 375.189 326 1.151

Total 388.760 328

Oportunity factor

draw backs of

small cars

Between

Groups 87.606 2 43.803 23.150 .000

Within

Groups 389.772 206 1.892

96

Sum of

Squares df

Mean

Square F Sig.

Total 477.378 208

Opportunity

factor price of

high segments

cars

Between

Groups 15.274 2 7.637 4.427 .013

Within

Groups 474.369 275 1.725

Total 489.644 277

Threat factors

cabs/call taxi

Between

Groups 11.451 2 5.725 2.598 .077

Within

Groups 434.129 197 2.204

Total 445.580 199

Threat factors

offer for high

segment cars

Between

Groups 20.966 2 10.483 8.980 .000

Within

Groups 250.979 215 1.167

Total 271.945 217

From the above table it is found that the strength factor

maintenance cost (F = 5.591) and weakness factor increase in fuel price

(F = 56.896) differ significantly with respect to income of the customers.

The post hoc test revealed that the customers with above Rs.30000

income perceived maintenance cost (mean = 1.5660) is the

predominant strength and increase in fuel price (mean = 1.6761) is the

weakness for the car purchase in Chennai city. The two opportunity

97

factors draw backs of small cars (F = 23.150), price of high segment

cars (F=4.427) and a unique threat factor offer for high segment cars (F

= 8.980) differ significantly with respect to income. The mean

comparison indicates the customers with income Rs.10000 to 20000

declined to say draw backs of small cars and price of high segment cars

is a major threat to purchase of cars in Chennai city.

Influence of family size

The parametric influence of family size on the SWOT factor is

extracted through ANOVA and presented below.

Table 4.50

ANOVA for influence of family size

Sum of

Squares df

Mean

Square F Sig.

Strength factor

maintenance

cost

Between

Groups 11.643 3 3.881 4.508 .004

Within

Groups 270.310 314 .861

Total 281.953 317

Strength factor

availability of

spares

Between

Groups 20.635 3 6.878 7.558 .000

Within

Groups 292.135 321 .910

Total 312.769 324

98

Sum of

Squares df

Mean

Square F Sig.

Strength factor

service facilities

cars

Between

Groups 13.915 3 4.638 4.205 .006

Within

Groups 361.783 328 1.103

Total 375.699 331

Strength factor

availability of

multi brands

Between

Groups 20.594 3 6.865 3.635 .014

Within

Groups 322.915 171 1.888

Total 343.509 174

Strength factor

loan facility

Between

Groups 54.752 3 18.251 4.959 .002

Within

Groups 791.257 215 3.680

Total 846.009 218

Weakness factor

High cost

Between

Groups 11.349 3 3.783 3.092 .028

Within

Groups 315.647 258 1.223

Total 326.996 261

Weakness factor

increase in fuel

price

Between

Groups 27.521 3 9.174 8.253 .000

Within

Groups 361.239 325 1.112

Total 388.760 328

Weakness factor

competition from

Between

Groups 41.288 3 13.763 7.779 .000

99

Sum of

Squares df

Mean

Square F Sig.

low segment Within

Groups 332.629 188 1.769

Total 373.917 191

Weakness factor

low mileage

Between

Groups 17.246 3 5.749 3.813 .011

Within

Groups 379.906 252 1.508

Total 397.152 255

Weakness factor

seating capacity

Between

Groups 14.192 3 4.731 2.289 .079

Within

Groups 452.660 219 2.067

Total 466.852 222

Opportunity

factor draw

backs of small

cars

Between

Groups 25.863 3 8.621 3.914 .010

Within

Groups 451.515 205 2.203

Total 477.378 208

Opportunity

factor effective

advertisement

Between

Groups 13.756 3 4.585 3.560 .015

Within

Groups 359.396 279 1.288

Total 373.152 282

Opportunity

factor attractive

offer

Between

Groups 31.830 3 10.610 6.109 .000

Within

Groups 442.896 255 1.737

100

Sum of

Squares df

Mean

Square F Sig.

Total 474.726 258

Threat factor

demand for two-

wheelers

Between

Groups 24.397 3 8.132 3.540 .016

Within

Groups 429.572 187 2.297

Total 453.969 190

Threat factor

cabs/call taxi

Between

Groups 25.815 3 8.605 4.018 .008

Within

Groups 419.765 196 2.142

Total 445.580 199

The comparison of mean values through variables revealed the

significant difference in all the strength factors maintenance cost (F =

4.508) availability of spares (F = 7.558), service facilities cars (F =

4.205), availability of multi brand (F = 3.635) and loan facility (F =

3.092). The customers with three members in the family profoundly

believe maintenance cost (mean = 1.3580) is the greatest strength in

car purchase of cars and also realized least strength exercised from the

factor loan facility (mean = 4.00). Family size clearly makes different

perceptions over the weakness factors high cost (F = 3.092), increase in

fuel price (F = 8.253), competition from low segment (F = 7.779) and

low mileage (F = 3.813) significantly at 5 percent level. The mean

101

usage comparison indicates the three family members customers

identified high cost (mean = 1.6912) and increase in fuel

Price (mean = 2.1875) is the major and minor weakness of car

purchase in Chennai city. IT is also found the customers with big family

size are not able to realize the weakness of car purchase factors

competition from low segment (mean 3.35) and low mileage (mean =

3.00).

In the case of opportunity factors draw backs of small cars (F +

3.914), effective advertisement (F = 3.560) and attractive offer (F =

6.109) differ significantly at 5 percent level. Similarly the threat factors

demand for two wheelers (F = 3.540) and cabs /call taxi (F = 4.018)

differ significantly with respect to number of family members. It is found

that three family member customers find more opportunities for car

purchase in Chennai city due to the factor draw backs of small cars

(mean = 1.8571) but two members family customers are not able to

accept the opportunities of car purchase through effective

advertisement (mean = 2.6087). The single customers consistently

expressed attractive offer (mean = 1.1538) is best opportunity for car

purchase. There is contrast opinion of threats for the factors, demand

for two wheelers (mean = 3.5774) is a least threat and emergence of

cabs/call taxi (mean = 1.5385) is a great threat.

102


Influencing factors of car purchase do not differ significantly.

The customer’s preference and purchase decision are influenced

by the product attributes and strength factors. These influential factors

differ with respect to product attributes and SWOT factors (Roger D.

Blackwell, Paul W. Miniard and James F. Engel ,2007). The application

of factors analysis, cluster analysis and discriminant analysis exposed

the perceptional difference among customers (Churchill.Jr.GA

(1979).The SWOT factors have direct incidental impact over the

purchase of the products. (Subhash C. Metha,1973). In fact the SWOT

factors opinion depends upon demographic characteristics of customers

(Michael R. Solomon,2003). The use of rigorous one-way analysis of

variance showed the impact of demographic on SWOT factors. These

pieces put together proved that the influencing purchase factors

depend upon SWOT analysis. It is also clear from chi-square analysis

of variance (Bagozzi R.P (1994) there is a deep association between

product influence and brand selection criterion. It profoundly proves

that the factors influencing purchase decision segmented significantly.

The above analysis provides research information relating to pre

– purchase behavior of car consumers and fill the gaps in the existing

literature.

103

CHAPTER –V

AN EMPRICAL ANALYSIS OF CUSTOMER ATTITUDE,

EXPECTATION AND SATISFACTION OF CAR PURCHASE

INTRODUCTION

Customer’s posses valuable attitudes towards any durable

product to analogically analyse the product characteristics, utility and its

appearance (Jagadish N. Sheth and Banwai Mittal, 2003). They

expect more qualitative products with appreciable durability. In this

research the Chennai city car customers transparently present their

attitude and expectations about the cars they possess in Likert’s five

point scale raising from strongly agree to strongly disagree. In order to

ascertain the customer’s opinion the t-test with test value 3 is applied

and presented below.

Table 5.1

One-Sample Statistics for Customers attitude and expectations

N Mean Std.

Deviation

Std. Error

Mean

Quality 456 4.2127 .86490 .04050

Prestige 456 3.1206 1.04447 .04891

Official/business use 456 3.3158 1.01908 .04772

Family members 456 3.5570 1.01258 .04742

104

N Mean Std.

Deviation

Std. Error

Mean

Price 456 4.0789 .86844 .04067

Appearance 456 2.9079 1.17308 .05493

Mileage 456 4.2390 .77452 .03627

Sales promotional

offer 456 3.2675 1.03069 .04827

Advertisements 456 3.4079 .83354 .03903

Satisfied customers 456 3.7697 .92916 .04351

More information 456 3.3838 .93273 .04368

Better services 456 3.1930 1.03459 .04845

Dealers 456 3.1031 .86717 .04061

Decisions 456 3.0680 1.10433 .05171

Table 5.2

One-Sample Test for Customers attitude and expectations

Test Value = 3

t Df Sig. (2-

tailed)

Mean Difference

95% Confidence

Interval of the Difference


Quality 29.942 455 .000 1.21272 1.1331 1.2923

Prestige 2.466 455 .014 .12061 .0245 .2167

105

Official/business

use 6.617 455 .000 .31579 .2220 .4096

Family

members 11.747 455 .000 .55702 .4638 .6502

Price 26.530 455 .000 1.07895 .9990 1.1589

Appearance -1.677 455 .094 -.09211 -.2001 .0159

Mileage 34.161 455 .000 1.23904 1.1678 1.3103

Sales

promotional

offer

5.543 455 .000 .26754 .1727 .3624

Advertisements 10.450 455 .000 .40789 .3312 .4846

Satisfied

customers 17.690 455 .000 .76974 .6842 .8552

More

information 8.786 455 .000 .38377 .2979 .4696

Better services 3.983 455 .000 .19298 .0978 .2882

Dealers 2.538 455 .011 .10307 .0233 .1829

Decisions 1.315 455 .189 .06798 -.0336 .1696

From the t-test table it is found that the mean values range from

2.90 to 4.21 with standard deviations .774 to 1.10 for all the 14

variables. The t-values for quality role (t=29.942) prestige show

(t=2.466) car usage (t=6.617) and family member domination (t=11.747)

are significant at 5 percent level. Therefore it is concluded that the

Chennai city car users strongly agree with the role of quality and

importance for price they have moderate agreeability on prestige

106

exposure and usage of cars. The insignificant t-value 1.677 for the

valuable appearance and colour indicate that the customers expect

appearance and colours of the car to be important before they

materialize the purchase of cars. It is found highly significant of the

variables mileage (t=34.161), advertisement for cars (t=10.450),

satisfied customers (t=17.690) are statistically significant at 5 percent

level. It is found that the car users in Chennai city profoundly agreed

the mileage efficiency advertisement and repeated purchase due to

satisfaction are important attitudes for purchase.

Factors customer attitude and expectations:

The 14 variables attitude and expectations need to be reduced

into meaningful predominant factors. This would help to exactly

understand the Chennai city car users attitude and expectations. In this

content the application of factor analysis by Principal component

method yielded the following results.

Table 5.3

KMO and Bartlett's Test for customer attitude and expectations

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .694

Bartlett's Test of

Sphericity

Approx. Chi-Square 1509.235

Df 91

Sig. .000

107

The KMO and Bartlett’s test measure of sampling adequacy .694,

Bartlett’s test of sphericity is 1509.235 are statistically significant at 5

percent level. This indicates the suitability of 14 variables to emerge in

the form of five factors. The following total variance table indicates the

existence of five predominant factors.

Table 5.4

Total Variance Explained for customer attitude and expectations

Component Initial Eigenvalues Rotation Sums of Squared

Loadings

Total % of

Variance

Cumu-

lative %Total

% of

Variance

Cumu-

lative

%

Quality 3.245 23.175 23.175 2.532 18.089 18.089

Prestige 2.023 14.453 37.628 2.199 15.708 33.797

Official/

business use 1.410 10.072 47.700 1.567 11.195 44.992

Family

members 1.127 8.049 55.749 1.327 9.481 54.472

Price 1.028 7.342 63.092 1.207 8.619 63.092

Appearance .979 6.990 70.082

Mileage .832 5.940 76.022

Sales

promotional

offer

.713 5.093 81.115

Advertisements .622 4.445 85.560

108

Satisfied

customers .507 3.623 89.183

More

information .487 3.480 92.663

Better services .429 3.064 95.727

Dealers .367 2.624 98.350

Decisions .231 1.650 100.000


The Eigen values 2.532, 2.199, 1.567, 1.327 and 1.207 with

individual variance 18.089, 15.708, 11.195, 9.481 and 8.619. The total

variance explained by these 14 variables is 63.092. The individual

variable loading in each factor is presented below:

Table 5.5

Rotated Component Matrix for customer attitude and expectations

Component

1 2 3 4 5

Price .832

Mileage .827

Quality .691

Satisfied customers .631

Better services .866

Dealers .804

Information .618

Decision .784

109

Promotional offer .724

Advertisement .447

Family members .829

Prestige .560

Official/business .794

Appearance .511

Extraction Method: Principal Component Analysis.Rotation Method: Varimax with Kaiser Normalization.Rotation converged in 6 iterations.

The first factor comprises four variables. Price is the most

important factor which influences the customers in the purchase of car

(0.832), mileage efficiency is a factor which the customer considers very

important (.827), quality play a major role in the purchase of car by

customers (.691), Those customers who buy the same brand of car

second/third time can be called as satisfied customer (.631), Therefore

the factor is “product characteristics”. The second factor is a

composition of three variables, dealers provide better services to

customers (.866), dealers provide better services to customers (.804)

and dealers provide lot of information to customers about the car (.618),

hence the factor is realized as “Dealers Service”. Thethird factor

emerged is “Sales Promotion” because it is replete with the variables.

Customers change their derivation after interacting with sales person in

the car show room (.784), Sales promotional offer influence the

customer significantly in buying the car (.724) and the advertisements

for cars are brought adequately (.447). The fourth factor “Intrinsic

110

purchase influence” consists of two meaningful variables family

members dominated the customers in buying car (.829), customers buy

car for showing prestige (.560). Finally the fifth factor emerged out of

two variables mostly customers buy car for official/business use (.794)

appearance and colours of car are less important for customers (.511),

hence the factor is known as usage and appearance.

On the whole it is concluded that product characteristics and

usage, appearance of car are the important attitude before and after

purchase of cars. They expect optimistic dealer’s service attracted

towards effective sales promotion. The purchase of cars is materialized

due to the compulsion of family members and exposes their prestige.

Different types of attitude and customer expectation

Factor analysis by principal component method extracted five

factors product characteristics, sales promotion, product usage and

appearance, dealers service and intrinsic purchase influence these

factors explicitly explained attitude and expectations of Chennai city car

users. The t-test predicted fluctuating mean values and standard

deviations which implies different perceptional levels of customer’s

attitude and expectations. K-means cluster analysis is exploited at

these situations to identify the existence of major groups with different

111

attitudes and expectations. The following are the results of cluster

analysis.

Table 5.6

Final Cluster Centers for Different types of attitude and customer

expectations

Cluster

1 2 3

Product characteristics 4.42 3.41 4.44

Dealers service 3.81 2.88 3.01

Sales promotion 3.88 2.92 2.97

Intrinsic Purchase influence 4.37 3.17 4.17

Usage and appearance 3.58 3.30 2.44

Table 5.7


Cluster Bumptious customers 149.000

Unscathed customers 159.000

Unsaturated customers 148.000

Valid 456.000

Missing .000

From the above table it is found that first group comprises (149)

32.68 percent of customer with strong and intrinsic influence from the

family members and their prestige in the society, this group is called

112

“Bumptious customers”. The second group (34.87 percent) is

“Unscathed customers” who are not persuaded and attracted by the

sales promotional activities and services of the dealers. Third cluster

with 32.45 percent if customers demanding good quality and

characteristics hence this group is known as “Unsaturated

customers”.

The cluster analysis revealed three types of car users in Chennai

city with bumptious reasons for car purchase and another is perfectly

unmoved by the sales promotional activities. The third group is always

seeking qualities.

Cluster Justification

Discriminant analysis is used to justify the classification of

sampling domain through cluster analysis (Jay D.Lindquist and

JoesphSirgy M, 2003). In this analysis the clusters are taken as

dependent and five factors as independent in nature. The following are

the results of discriminant analyses.

113

Table 5.8

Tests of Equality of Group Means for Cluster Justification

Wilks'

Lambda F df1 df2 Sig.

Product characteristics .445 282.769 2 453 .000

Dealers service .715 90.415 2 453 .000

Sales promotion .624 136.262 2 453 .000

Intrinsic Purchase influence

.440 288.177 2 453 .000

Usage and appearance

.639 128.226 2 453 .000

Table 5.9

Test Results for Cluster Justification

Box's M 242.958

F Approx. 7.971

df1 30

df2 645245.666

Sig. .000

Tests null hypothesis of equal population covariance matrices.

Test of equality of group means and Wilk’s lambda for product

characteristics (.445), dealers service (.715), sales promotion (.624),

Intrinsic purchase influence (.440) and usage and appearance (.639)

are statistically significant at 5 percent level and concluded that five

factors form the basis for perfect discrimination. In fact it is

114

consolidated by the significant Box’s M test value 242.958. It is

intended that true group discrimination is well defined and acceptable

for the sample. The following Eigen values and chi-square table values

indicate the tool for discrimination.

Table 5.10

Eigen values for Cluster Justification

Function Eigenvalue % of

Variance Cumulative

% Canonical Correlation

1 2.810(a) 64.2 64.2 .859

2 1.566(a) 35.8 100.0 .781

First 2 canonical discriminant functions were used in the analysis.

Table 5.11

Wilks' Lambda for Cluster Justification

Test of Function(s) Wilks' Lambda Chi-square df Sig.

1 through 2 .102 1028.281 10 .000

2 .390 424.981 4 .000

The Eigen value 2.810, 1.566 individual variance 64.2 and 35.8,

canonical correlation (.859) and (.781), chi square values 1028.281 and

424.981 for two discriminant functions justify. The formation of three

clusters, which are created by the discriminant functions perfectly as

presented below.

115

Table 5.12

Structure Matrix for Cluster Justification

Function

1 2

Intrinsic purchase influence .657(*) -.192

Product characteristics .619(*) -.331

Sales promotion .376(*) .362

Dealers service .322(*) .262

Usage and appearance .036 .599(*)

Pooled within-groups correlations between discriminating

variables and standardized canonical discriminant functions Variables

ordered by absolute size of correlation within function. Largest absolute

correlation between each variable and any discriminant function.

The two functions

Z1 = .657(IPI) + .619 (PC) + .376(SP) + .322(DS)

Z2 = .599 (UA)

Are perfect in segmenting the sample domain into three groups is

perfect. In particular intrinsic purchase influence, product

characteristics, sales promotion and dealers service are essential for

Chennai city car users to segment themselves. The product usage and

116

appearance is also highly influencing the customers and make them to

distinguish themselves.

Influence of Demographic variables on the factors of customers

attitude and expectations

Demographic variables segment the sample domain to ascertain

the consumer behaviour towards any product (Keller K.L, 1998). The

segmentations is found useful to find its influence on consumer

preference, purchase decision, attitude, expectation and satisfaction

(Leon G. Shiffman, Leslie lazar Kanuk ,2008). Therefore it becomes

indispensable to determine the impact of the demographic variable

gender, age, education, occupation, number of earning members,

family income and family size on the five factors product characteristics,

dealers service, sales promotion, intrinsic purchase influence and usage

of attitude and expectation. Since the situation replete with multiple

independent variables and dependent variables multivariate general

lineal model is used to find the multiple and individual impact of

independent variables. The multivariate test results are presented

below.

From the above table it is found that Pillai’s trace, Wilk’s lambda,

Hotelling’s trace and Roy’s largest root are statistically significant to fit a

multiple regression model.

117

Table 5.13

Multivariate Tests for the customers attitude and expectations

Effect Value F Hypothe

sis df Error df Sig.

Intercept Pillai's

Trace .575 119.920(a) 5.000 444.000 .000

Wilks'

Lambda .425 119.920(a) 5.000 444.000 .000

Hotelling

's Trace 1.350 119.920(a) 5.000 444.000 .000

Roy's

Largest

Root

1.350 119.920(a) 5.000 444.000 .000

Gender Pillai's

Trace .087 8.506(a) 5.000 444.000 .000

Wilks'

Lambda .913 8.506(a) 5.000 444.000 .000

Hotelling

's Trace .096 8.506(a) 5.000 444.000 .000

Roy's

Largest

Root

.096 8.506(a) 5.000 444.000 .000

Age Pillai's

Trace .031 2.851(a) 5.000 444.000 .015

Wilks'

Lambda .969 2.851(a) 5.000 444.000 .015

Hotelling

's Trace .032 2.851(a) 5.000 444.000 .015

118

Roy's

Largest

Root

.032 2.851(a) 5.000 444.000 .015

Education Pillai's

Trace .129 13.159(a) 5.000 444.000 .000

Wilks'

Lambda .871 13.159(a) 5.000 444.000 .000

Hotelling

's Trace .148 13.159(a) 5.000 444.000 .000

Roy's

Largest

Root

.148 13.159(a) 5.000 444.000 .000

Occupation Pillai's

Trace .044 4.126(a) 5.000 444.000 .001

Wilks'

Lambda .956 4.126(a) 5.000 444.000 .001

Hotelling

's Trace .046 4.126(a) 5.000 444.000 .001

Roy's

Largest

Root

.046 4.126(a) 5.000 444.000 .001

Earningme

mbers

Pillai's

Trace .080 7.727(a) 5.000 444.000 .000

Wilks'

Lambda .920 7.727(a) 5.000 444.000 .000

Hotelling

's Trace .087 7.727(a) 5.000 444.000 .000

Roy's

Largest

Root

.087 7.727(a) 5.000 444.000 .000

119

Family

monthly

income

Pillai's

Trace .110 11.023(a) 5.000 444.000 .000

Wilks'

Lambda .890 11.023(a) 5.000 444.000 .000

Hotelling

's Trace .124 11.023(a) 5.000 444.000 .000

Roy's

Largest

Root

.124 11.023(a) 5.000 444.000 .000

Family size Pillai's

Trace .055 5.157(a) 5.000 444.000 .000

Wilks'

Lambda .945 5.157(a) 5.000 444.000 .000

Hotelling

's Trace .058 5.157(a) 5.000 444.000 .000

Roy's

Largest

Root

.058 5.157(a) 5.000 444.000 .000

a. Exact statistic,

b. Design

Intercept+Gender+Age+Education+Occupation+Earningmembers+Fami

lymonthlyincome+Familysize

Y = Bo + B1 (Gender) + B2 (Age) + B3 (Education) + B4 (occupation) + B5

(earning members) + B6 (Family income) + B7 (Family size).

The multiple linear regression model significantly fit to explain the

influence of demographic variables.

120

Table 5.14

Tests of Between-Subjects Effects for the customer’s attitude and

expectations

Source Dependent

Variable

Type III Sum of Squares

df Mean

Square F Sig.

Corrected

Model

Product

characteristics 77.957(a) 7 11.137 42.109 .000

Dealers service 33.887(b) 7 4.841 9.290 .000

Sales promotion 24.672(c) 7 3.525 7.492 .000

Intrinsic Purchase

influence 81.185(d) 7 11.598 35.048 .000

Usage&appearance 27.233(e) 7 3.890 6.663 .000

Intercept Product

characteristics 68.935 1 68.935

260.65

2 .000

Dealers service 21.573 1 21.573 41.400 .000

Sales promotion 50.587 1 50.587

107.52

5 .000

Intrinsic Purchase

influence 68.421 1 68.421

206.76

3 .000

Usage&appearance120.878 1

120.87

8

207.03

7 .000

Gender Product

characteristics 2.565 1 2.565 9.698 .002

Dealers service 4.441 1 4.441 8.523 .004

Sales promotion .200 1 .200 .426 .515

Intrinsic Purchase

influence 3.770 1 3.770 11.393 .001

Usage&appearance 4.181 1 4.181 7.161 .008

121

Age Product

characteristics .040 1 .040 .152 .697

Dealers service 3.254 1 3.254 6.246 .013

Sales promotion .370 1 .370 .786 .376

Intrinsic Purchase

influence 1.444 1 1.444 4.365 .037

Usage&appearance .034 1 .034 .058 .810

Education Product


Dealers service 7.262 1 7.262 13.937 .000

Sales promotion 3.275 1 3.275 6.960 .009

Intrinsic Purchase

influence 9.603 1 9.603 29.019 .000


Occupati

on

Product

characteristics .011 1 .011 .042 .837

Dealers service 5.342 1 5.342 10.252 .001

Sales promotion 3.532 1 3.532 7.507 .006

Intrinsic Purchase

influence .926 1 .926 2.799 .095


Earning

members

Product

characteristics .370 1 .370 1.397 .238

Dealers service .043 1 .043 .082 .775

Sales promotion 6.366 1 6.366 13.531 .000

Intrinsic Purchase

influence .323 1 .323 .977 .323


Family

monthly

income

Product


122

Dealers service 2.621 1 2.621 5.030 .025

Sales promotion 3.013 1 3.013 6.405 .012

Intrinsic Purchase

influence 17.130 1 17.130 51.766 .000


Family

size

Product


Dealers service 3.613 1 3.613 6.933 .009

Sales promotion 5.246 1 5.246 11.151 .001

Intrinsic Purchase

influence .136 1 .136 .412 .522


Error Product characteristics

118.483 448 .264

Dealers service 233.446 448 .521

Sales promotion 210.770 448 .470

Intrinsic Purchase influence

148.249 448 .331

Usage&appearance 261.563 448 .584

Total Product characteristics

7764.938 456

Dealers service 5010.469 456

Sales promotion 5045.444 456

Intrinsic11 Purchase1 influence1

7119.250 456

Usage&appearance 4704.500 456

Corrected

Total

Product characteristics 196.440 455

Dealers service 267.332 455

Sales promotion 235.442 455

Intrinsic Purchase

influence 229.434 455

Usage&appearance 288.796 455

123

a. R Squared = .397 (Adjusted R Squared = .387)

b. R Squared = .127 (Adjusted R Squared = .113)

c. R Squared = .105 (Adjusted R Squared = .091)

d. R Squared = .354 (Adjusted R Squared = .344)

e. R Squared = .094 (Adjusted R Squared = .080)

The demographic variables gender influences product

characteristics (F = 9.698), dealer’s service (F = 8.523), Intrinsic

purchase influence (F = 11.393) and usage and appearance (F = 7.161)

significantly. This implies male and female customers in Chennai city

have different perceptions about characteristics of cars and dealers

service. The influence of family members differs on male and female

customers when they purchase cars. Usage and appearance is

perceived differently by the male and female customers of Chennai city.

Influence of Age

The average segmentation 25-40 years, 40-55 years and above

55 years influence the factor dealers service (F=6.246) and intrinsic

purchase influence (F=4.365) significantly at 5 percent level. The car

customers in Chennai city in different age groups have different opinion

about various services offered by the dealers. Similarly in the intrinsic

purchase influence, the domination of family members are different on

different age of the customers, in showing their prestige. The old and

using customers make their show-off in different numbers.

124

Influence of Educational qualification

The multivariable general linear model identified product

characteristics (F=51.150), dealers service (F=13.937), sales promotion

(F =6.960) and intrinsic purchase influence (F = 29.019) significantly at

5 percent level. The car users in Chennai city with UG level

qualification differ in their opinion with PG level customers regarding

characteristics of cars and service offered by the dealers. There is a

significant difference between customers with UG level qualification and

PG level qualifications in conceding the sales promotional strategies to

materialize the purchase of cars and exposing the prestige to others.

Influence of Occupations

The occupational status of car customers in Chennai city creates

significant impact on attitude and expectation factors. It is found that

dealer’s service (F = 0.252) and sales promotion (F = 7.507) is

influenced by state government employees, central government

employees and quasi government employees. It also identified that the

employees in service sector and industrial sector differ in their opinion

about car dealer’s service in Chennai city as well as their sales

promotional strategies.

125

Influence of number of earning members in the family

The increase and decrease in the family income due to number of

earning members create incidental effects over sales promotion (F =

6.405) and usage and appearance of four wheelers (F=22.932). The

number of earning members in the family affects the sales promotion

notion perceived by them. The results show that the customers with

more number of earning members have different notions about sales

promotional activities of dealers.

Influence of Income

Family income and education segments are analogous in making

influence over the continuous factors product characteristic (F =

17.202), dealers service (F=5.030), sales promotion (F = 6.405) and

Intrinsic purchase influence (F = 51.766) significantly. It is also found

that the customers with different range of income Rs.10000 – 20000,

Rs.20000-30000 and above Rs.30000 differ in their perception about

characteristic features mileage aid price of cars. They have different

opinions about dealer’s service and sales promotional advertisement.

The prestige of owing car entirely depends on the family income.

126

Influence of Family size

Family size of customers also depend on their attitude and

expectations, the multi variant analysis revealed family size influence

Characteristics of cars (F = 7.556) dealers service (F=6.933) sales

promotion (F = 11.151) and usage and appearance (F = 5.454) differ

significantly at 5 percent level. Therefore it is concluded that the

customers of car in Chennai city with different family size demanded

product characteristics of cars in different manner and their absorption

of sales promotional strategies are also different. They have peculiar

segmentation of feelings towards usage and appearance of cars they

use.


The factors of customer’s attitude and expectation significant

differ with respect to segmentation.

The buying behaviour of car customer obtains its momentum due

to their attitude towards the product and expectations in attributes and

benefits (Fiore, A.M. and Damhorst, M.L 1992). It is an important

research issue that the customers perceived their attitude and expect

the attributes from products based on their notions of the product and

demographic background. The customers develop their product

knowledge through their experience and information search (Belch,

127

G.E. and Belch, M.A 1998). The application of factor analysis, principal

component method followed by K-means cluster analysis and

discriminant analysis (Ref table nos.5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 5.11,

5.12)

The Parametric segmentation based on the perception is justified

mathematically to conclude that the factors of customer’s attitude and

expectation differ significantly. Another important segmentation in

marketing is demographics (Assael, H Assael’s) which segments the

dependent variables and compare the group mean values. This

mechanism is found suitable in multiple general linear model. This tool

simultaneously deal with multiple factors of customers attitude and

expectation as well as all possible demographic segmentation involved

in the research (Ref table nos 5.13,5.14). This indicates all the

demographic variables influence the factors of attitude and expectation

which forces to conclude that the customer’s attitude and expectation

differ with respect to segmentation.

Customer Satisfaction

This section aims at ascertaining the level of satisfaction of car

purchasers in Chennai city. The gaps in the literature identified price,

quality, mileage, seating comforts and convenience are predominant

determinants of customer satisfaction. Seating quality, less

128

maintenance, facilities provided, best space are the meticulously

identified reasons pertaining to customer satisfaction. The notions of

safety, availability of spares and driving comforts are focused to

empirically estimate the satisfaction level of customers. These variables

of customer satisfaction were responded by car customers in Chennai

city in Likert’s five-point scale which range from very high satisfaction to

very low satisfaction. In order to examine the level of satisfaction t-test

with Bonferroni correction is found appropriate with test values 3

assigned as moderate satisfaction. The application t-test for 11

variables is presented below.

Table 5.15

One-Sample Statistics for Customer Satisfaction

N Mean Std.

Deviation Std. Error

Mean Price 456 3.5066 .73527 .03443

Quality 456 3.7325 .71922 .03368

Mileage 456 3.6404 .76319 .03574

Seating

comforts and

Convenience

456 3.5899 .74467 .03487

Seating Quality 456 3.5811 .76316 .03574

Less 456 3.6886 .85393 .03999

129

maintenance

Facilities

provided 456 3.2939 .74217 .03476

Boot space 456 3.2346 .82261 .03852

Safety 456 3.4518 .79964 .03745

Availability of

spares 456 3.6623 .80655 .03777

Driving comforts 456 3.8048 .80333 .03762

Others 456 3.0110 .35993 .01686

Table 5.16

One-Sample Test for Customer Satisfaction

Test Value = 3

T Df Sig. (2-tailed)

Mean Difference

95% Confidence

Interval of theDifference

Lower Upper Lower Upper Lower UpperPrice 14.712 455 .000 .50658 .4389 .5742Quality 21.747 455 .000 .73246 .6663 .7986Mileage 17.917 455 .000 .64035 .5701 .7106Seating comforts and Convenience

16.916 455 .000 .58991 .5214 .6584

Seating Quality

16.261 455 .000 .58114 .5109 .6514

Less maintenance

17.220 455 .000 .68860 .6100 .7672

Facilities provided

8.455 455 .000 .29386 .2256 .3622

Boot space 6.091 455 .000 .23465 .1589 .3104

130

Safety 12.064 455 .000 .45175 .3782 .5253Availability of Spares

17.534 455 .000 .66228 .5881 .7365

Driving comforts

21.394 455 .000 .80482 .7309 .8788

Others .651 455 .516 .01096 -.0222 .0441

From the above table it is found that the mean values range from

3.23 to 3.80 and standard deviations are bridged by the lower value

.7192 and upper value .8226. The standard error of estimation is in the

compact set of real numbers .03368 to .03852. These parametric

values sharply estimated the t-statistics for 11 variables 14.712, 21.747,

17.917, 16.916, 16.261, 17.220, 8.4555, 6.091, 12.064, 17.534 and

21.394 respectively. These t-values are statistically significant at 5

percent level. Since all the mean values are greater then 3, it can be

concluded that the car customers are highly satisfied with driving

comforts of their car (mean = 3.80) followed by quality (mean=3.688)

and availability of spares (mean=3.66). The analysis also ascertained

high satisfaction is abundantly found among the Chennai city car

customers on these aspects. Mileage, comforts and safety of their cars

on the whole it can be concluded that the customers of cars in Chennai

city are highly satisfied with driving comfort, quality but expect more

satisfaction in price aspect. (Mahajan B.M., 1980)

131

Factors of customer satisfaction:

The 11 variables of customer satisfactions are dependent in

nature and purely based on customer perception. The relationship

between independent and dependent variables are required to

anatomically analyze the primary data for innovative findings.

Establishing the parametric relationships for 11 variables become

tremendous and heustic in nature. Therefore the systematic data

reduction for the underlying eleven variables becomes indispensable for

the researchers. In this content the exploitation of factor analysis is a

success for the researcher to systematically downsize the numerous

variables into few predominant factors. The application of factor

analysis by the principle component method, groups the 11 variables

into the meaningful representation of the underlying variables in the

following manner.

Table 5.17

KMO and Bartlett's Test for customer satisfaction

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. .782

Bartlett's Test of

Sphericity

Approx. Chi-Square 1884.258

Df 66

Sig. .000

132

From the above table it is found that KMO measure of sampling

adequacy is .782 and Bartlett’s test of sphenicity is 1884.258 are

statistically significant at 5 percent level. The extracted factors are

loaded with the variables explicitly presented in the table below

Table 5.18

Communalities for customer satisfaction

Initial Extraction

Price 1.000 .563

Quality 1.000 .651

Mileage 1.000 .434

Seating comforts and

Convenience 1.000 .631

Seating Quality 1.000 .693

Less maintenance 1.000 .629

Facilities provided 1.000 .536

Boot space 1.000 .564

Safety 1.000 .487

Availability of spares 1.000 .704

Driving comforts 1.000 .561

Others 1.000 .668


This implies that the sample domain is normally distributed and

conducive to apply principle component analysis methods. The

correlated communality values range from 0.434 to 0.704. It foretells

133

that the variance of sample ultimately vary from 43.4 to 70.4 percent to

transform into meaningful factors significantly. The following total

variance table explains the number of extracted factors.

Table 5.19

Total Variance Explained for customer satisfaction

Component Initial Eigenvalues

Rotation Sums of Squared

Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

Price 4.274 35.616 35.616 3.062 25.515 25.515

Quality 1.674 13.947 49.563 2.749 22.908 48.423

Mileage 1.173 9.776 59.339 1.310 10.915 59.339

Seating comforts and Convenience

.922 7.687 67.026

Seating Quality

.837 6.972 73.998

Less maintenance

.650 5.421 79.419

Facilities provided

.592 4.934 84.353

Boot space .514 4.286 88.639 Safety .462 3.854 92.493 Availability of spares

.367 3.055 95.548

Driving comforts

.305 2.539 98.087

Others .230 1.913 100.000


134

From the table it is observed that 3 factors emerged out of 11

variables with Eigen values 3.062, 2.749 and 1.310. The numerical

values of the Eigen values are greater than 1, if profoundly justifies the

extraction of price factors. The factors possess the individual variances

25.515 percent, 22.908 percent and 10.915 percent respectively. The

11 variables of customer satisfaction exhibited 59.339 percent of total

variance. Since the variance is greater then 50 percent it can ascertain

that factors extraction will be meaningful in representing the 11

underlying variables of customer satisfaction.

Table 5.20

Rotated Component Matrix for customer satisfaction

Component

1 2 3

Seating quality .797

Seating comforts and convenience .786

Boot space .710

Facilities provided .663

Safety .521

Less maintenance .753

Price .734

Availability of spares .721

Quality .644

Mileage .558

Driving comforts .526

Others .809

Extraction Method: Principal Component Analysis. Rotation Method:

Varimax with Kaiser Normalization. Rotation converged in 4 iterations.

135

The first factor consists of five factors Driving comforts (.797),

Seating comforts and convenience (.786), Best space (.710), facilities

provided (.663) and safety (.521),. Hence this factor is justified to call

“Comfortability”. The under lying variables Price (.753), Mileage

(.734), Availability of spares (.721), less maintenance (.644) constitute

the second factor “cost and maintenance”. The third factor comprises

three factors Quality (.809), Seating quality (.558) and other reasons

(.526), hence this factor is realized as “quality orientation”.

The factor analysis concludes that the customer satisfaction of

purchasing cars in Chennai city is decided by the three predominant

factors that prevails among the customers are comforts and

convenience as well as cost and maintenance. The quality orientation

of cars plays the key role to measure the customer satisfaction. (Matin

Khan , 2001)

Brand comparison

Customer psychology for durables leans upon the brand

comparison phenomenon. They compare the brands of durable they

possess with other brands on the basis of cost, quality, maintenance,

convenience and comforts. In the present research customers

responded to question brand comparison to conclude over the lines of

136

superiority. The frequency distribution presents the brand comparison

psychology of car purchases in Chennai city.

Table 5.21

Brand of car used is superior to other brands of cars

Frequency Percent

Valid

Percent

Cumulative

Percent

Valid Yes 310 68.0 68.0 68.0

No 146 32.0 32.0 100.0

Total 456 100.0 100.0

The simple percentage analysis identified that out of 456 car

purchases 310 (68 percent) compare their brands of cars with others

and concluded their cars are always superior to other brands of cars,

remaining 32 percent (146) customers do not have the comparative

psychology on the cars they possess. The reasons for superiority of car

brands are perceived Chennai city can purchase in the following

manner.

Reasons for superiority of Brands

The Chennai city car purchasers decide their brand, superiority

based on the reasons low price, better mileage, less maintenance and

technology advancement. They expressed the ranking reasons

analogous to ascending order of the numericals starting from 1. This

137

technique implies the least number one denotes the primary reason for

brand comparison followed other numbers ascending order. The

weighted average ranking analysis is found suitable to order the specific

reasons for brand superiority.

Table 5.22

Reasons for superiority of Brands

Reasons Weighted average Rank

Low price 2.24 3

Better mileage 1.97 1

Less maintenance 2.04 2

Technology advancement 2.45 4

The weighted average ranking analysis identifies better mileage

(1.97 rank 1) followed by less maintenance (2.04 rank 2), Low price

(2.24 rank 3) and at last technology advancement (2.45 rank 4). This

indicates the brand comparison and superior quality of cars are

identified by Chennai city car customers through comparing mileage

given by four wheelers and less maintenance cost. They give least

importance to price, and technology advancement of the cars they

purchase. The customers of cars always expect low price, more

comfort and conveniences from the manufacturers. They always seek

for the new brands to offer a culminating point of satisfaction. (Michael

R. Solomon , 2003)

138

This phenomenon leads to brand shift notions in marketing

theories. The car purchasers of Chennai city expressed their notions of

future purchase in the next section.

Choice of future purchase

The respondents transparently expressed the purchase of the

same brand or different brands in future. The frequency distribution of

their choice clearly presents future purchase.

Table 5.23

Choice of purchase of car in future


Percent

Cumulative

Percent

Valid Same

Brand 180 39.5 39.5 39.5

Different

brand 276 60.5 60.5 100.0

Total 456 100.0 100.0

Simple percentage analysis revealed that 39.5 percent of

consumers planned to purchase the same brand if it exists and 60.5

percent have the inclination to purchase different brands of cars in

future.

139

Brand shift

Brand shift is an out growth of customer’s dissatisfaction (Radha

Krishna, 2005). When the customer’s expectations are not fulfilled in a

brand. They have the tendency to mechanize the brand shift. The

Chennai city car purchasers also expressed their brand shift notions.

The frequency distribution is presented below.

Table 5.24

Idea of shifting the present brand of car to other brand

Frequency Percent

Valid

Percent

Cumulative

Percent

Valid Yes 178 39.0 39.0 39.0

No 278 61.0 61.0 100.0

Total 456 100.0 100.0

The primary data ascertained 178 (39 percent) of car customers

in Chennai city plans for brand shift and 278 (61 percent) of them are

loyal and plan to materialize the same brand of car next time also.

Reasons for Brand shift

The car consumers of Chennai city highlighted predominant

reasons heavy fuel consumption, high maintenance cost, non

availability of spares, service center problems and payment of high tax

140

for their cars give rise to brand shift. The opinion of 178 customers on

brand shift is computed through ranking analysis. The result of ranking

analysis is presented below:

Table 5.25

Reasons for Brand shift

Reasons Numerical

value Rank

Heavy fuel consumption 1.579 2

High maintenance cost 1.469 1

Non availability of spares 1.645 3

Service center problems 1.930 4

Higher Tax 2.193 5

The ranking analysis identified the high maintenance cost and

heavy fuel consumption is the subsequent reasons prevailing among

car consumers in Chennai city. These reasons actually induce them for

the brand shift. Besides this, the 39 percent of consumers quoted non

availability of spares, service center problems, higher tax are severely

influencing them for brand shift.

Frequent problems encountered by car users in Chennai city

The car users in Chennai city experience the problem pertaining

to their cars. In particular they frequently realized problems regarding

141

starting trouble, battery down, non availability of spares and costly

spares. The following purchase analysis reveals the frequency of the

problems.

Table 5.26

Experience of frequent problems in Using cars


Percent Cumulative

Percent Valid Yes 52 11.4 11.4 11.4

No 404 88.6 88.6 100.0

Total 456 100.0 100.0

From the above table it is found that 11.4 percent (52) consumers

encountered problems in their cars and most of the car consumers

(88.6 percent) do not face frequent problems of their cars. The 11.4

percent consumers with problems of their car reduced the reasons

systematically in the following manner.

Table 5.27

Problems encountered by car users in Chennai city

Reasons Numerical value Rank

Starting trouble 1.491 3 Battery down 1.206 1

Non availability of spares 1.886 4

Costly spares 1.360 2

142

From the above table it is found that the problems occurred due

to battery down followed by costly spares. They also experienced the

problems of starting trouble as well as non availability of spares. These

orders of reasons were perceived as the reasons for the frequent

problem in the cars of Chennai city customers.

Brand Recommendation

Brand knowledge and brand experience of customers lead to

either brand loyalty or brand shift (Reference). The loyal customers

have inclination towards brand recommendation and also share the

satisfaction over the brand they possess to others. The Chennai city

car users expressed their brand recommendation notion through the

dichotomous options as follows.

Table 5.28

Customers recommending others to buy their brand of car


Percent Cumulative

Percent Valid Yes 274 60.1 60.1 60.1

No 182 39.9 39.9 100.0

Total 456 100.0 100.0

Purchase analysis explicitly expressed that 60.1 percent (274)

consumers have a optimistic experience of the brand of car they

possess and they are enthusiastic to recommend their brands to others.

143

The remaining 39.9 percent (182) consumers are not satisfied with their

brands and decided not to recommend to friends and relatives.

The car consumers in Chennai city are able to transparently

express the reasons for non-recommendation. They profoundly believe

that the brand they possess not worth to the recommended and have

the opinion that others should take their own decision. The consumers

also feel that the preference and satisfaction will vary from person to

person, so they do not want to recommend their brands. The ranking

analysis is done on these options and presented below.

Table 5.29

Reasons for Brand Recommendation

Reasons Numerical

value

Rank

Not worth to recommend 1.031 1

Let others take their own decision 1.864 3

Preference and satisfaction will vary from

person to person

1.623 2

From the ranking analysis it can be concluded that the dissatisfied

customers expressed the negations of brand unworthy to recommend.

Some customer’s non recommendation is due to non interference

144

psychology of unambitiousness to recommend as they feel preference

and satisfaction is individual feeling and it should not be persuaded.

Different levels of customer satisfaction

The application of factor analysis by principal component method

ascertained the existence of three predominant factors comfortability,

cost and maintenance and quality impact. The test also revealed

satisfaction of car customers in Chennai city is determined by the three

factors, therefore classifying the customers based on their perception of

factors become indispensable at this function to identify the customer

characteristics towards cars. K-means cluster analysis is found suitable

to segment the customers using the parametric scores obtained from

customers through Likert’s five point scale. The following are the

results of cluster analysis.

Table 5.30

Final Cluster Centers

Cluster

1 2 3

Comfortability 2.97 3.78 3.80

Cost and maintenance 3.16 3.41 4.25

Quality impact 3.01 3.52 3.63

145

Table 5.31


Cluster Comfortability 165.000

Cost and maintenance 133.000

Quality impact 158.000

Valid 456.000

From the above parametric values of the factors, it is found that

first cluster consists of 36.18 percent (165) customers with weak

satisfaction over comfortability. Hence this heterogeneous group, can

be named as “Comfort seekers”.

The second segment of sample unit comprises 29.17 percent

(133) customers with high satisfaction in “Cost and maintenance” there

for this group of customers can be called “Gratified customers”

The third group with 34.65 percent customer is made rarely

satisfied with comforts, cost maintenance and quality, this forces to

identify them as subsistent customers. On the whole cluster analysis

revealed there are three types of car users in Chennai city. They hetero

generously expect comfortability, less product cost, and less

maintenance cost with good quality from the car they purchase.

146

Association between customer satisfaction and customer post

purchase behaviour

K-means cluster analysis identified three different types of car

users in Chennai city and percentage analysis as well as ranking

analysis explicitly presented their behaviour through post purchase

behaviour elements brand comparison, future purpose, brand shift,

problem experience and brand recommendation. It is closely observed

and hypothesized that the cluster classification is deeply association of

various purchase behaviour elements. The following research

propositions are identified and formed using chi-square analysis of

association, There is on association between different levels of

customer satisfaction and brand comparison behaviour of customers.

The association is performed through cross tables between 3 cluster

and dichotomous opinion of brand comparison of car users in Chennai

city.

Table 5.32

Association between different levels of customer satisfaction and brand comparison behaviour of customers

Recommend others to buy your brand car Total

Yes No 1.00 Cluster Number of Case

Comfortability 70 95 165 Cost and maintenance

78 55 133

Quality impact

126 32 158

Total 274 182 456

147

Table 5.33

Chi-Square Tests

Value df Asymp. Sig.

(2-sided) Pearson Chi-Square 47.043(a) 2 .000


Linear-by-Linear



0 cells (.0%) have expected count less than 5. The minimum expected

count is 53.08.

From the cross tab frequency distribution table it is found that the

maximum frequency is replenished at the cell (3,1) (126) and minimum

is loaded at cell (3,2) (32). This implies even the subsistent customers

are ready to compare their brands of cars with others. The chi square

value 47.043, p=0.000 indicates that the hypothesis is rejected at 5

percent level. Therefore it is concluded that there is a association

between different levels of customers satisfaction and brand

comparison behaviour. Customer satisfaction of car users also lead to

purchase of same brand in future or dissatisfaction influences the brand

shift. This forces to develop the following proposition.

There is no association between different levels of satisfaction of

car users and their choice of purchase of car in future.

148

The frequency distribution followed by chi-square analysis of

association is presented below:

Table 5.34

Choice of Purchase of car in future

Choice of purchase of car in future Total

Same brand

Different Brand 1.00

Cluster Number of Case

Comfortability 30 135 165 Cost and maintenance

52 81 133

Quality impact

98 60 158

Total 180 276 456

Table 5.35

Chi-Square Tests

Value df Asymp. Sig. (2-sided)



Linear-by-Linear Association 64.767 1 .000


a 0 cells (.0%) have expected count less than 5. The minimum

expected count is 52.50.

From the above table it is found that the maximum frequency

(135) and minimum frequency (30) are formed at the cells (1,2) and

(1,1) respectively. The comfort seekers in Chennai city have the

inclination towards different brand purchase. The Chi-square value

149

64.949, p-value=0.000 are significant at 5 percent level. Therefore the

proposition is rejected at 5 percent level and concluded that there is a

deep association between satisfaction levels and choice of purchase of

cars in future. The satisfied customers also inclined to purchase

different brands by expecting more product features.

The brand shift is found maximum among the car users in

Chennai city. The customer’s satisfaction also depends upon the

problems faced by the customers during post purchase behaviour. This

leads to the following proposition.

There is no association between different levels of satisfaction and

experience of frequent problems in using the car.

The cross tab formulation and frequency dumping are found in

the following tables.

Table 5.36

Experience frequent problems in using cars

Total

Yes No 1.00

Cluster Number

of Case

Comfortability 24 141 165

Cost and maintenance

11 122 133

Quality impact 17 141 158

Total 52 404 456

150

Table 5.37

Chi-Square Tests

Value df Asymp. Sig.

(2-sided)



Linear-by-Linear



0 cells (.0%) have expected count less than 5. The minimum expected count is 15.17.

It is found that (24) comfort seekers, (11) gratified customers and

(17) subsequent customers have experienced the problems of their

cars. The chi square analysis value 2.969, p-value=.227 are not

statistically significant at 5 percent level, therefore the proposition is

average and concluded that the different levels of customers

satisfaction is not decided by the frequent problems they face in the

post purchase period.

The saturated satisfaction also decides the Chennai city car

customer enthusiasm for brand recommendations. The following table

gives the frequency distribution of cross tables pertaining to different

levels of satisfaction.

151

Table 5.38

As the title of the customers recommending others to buy their

brand of car

Recommend others Total

Yes No 1.00

Cluster

Number

of Case

Comfortability 70 95 165

Cost and

maintenance 78 55 133

Quality impact 126 32 158

Total 274 182 456

Table 5.39

Chi-Square Tests

Value df Asymp. Sig. (2-sided)



Linear-by-Linear



0 cells (.0%) have expected count less than 5. The minimum expected count is 53.08.

The frequency table revealed the pleasant experience of car

users in Chennai city and their desire to recommend. It is found (70)

comfort seekers, (78) gratified customers and (126) subsistent

customers recommend their car to others. The chi-square value 47.043

152

p-value = 0.000 are statistically significant and concluded that the

association exists between different levels of satisfaction and

recommend of the brands. The satisfied customers are more

enthusiastic in recommending their brands of cars to others.

This section completely are anatomically analysed the level of

satisfaction of car users in Chennai city in different aspects. The

associations between brand loyalty, brand shift and brand

recommendations and different levels of satisfaction are analysed to

establish the customers satisfaction among car users in Chennai city.

Opinion about dealers services

Customer satisfaction not only based on products utility and

performance but also influence by the service providers. (Ramesh

Kumar S., 2004). The car users in Chennai city expressed their opinion

on leaders in terms of employees’ behaviour in show rooms and service

centers, role of dealers in the sale of car, promotion offer strategies of

dealers and opinion on dealers services. The opinion was sought in

Likert’s five-point scale and application of t-test, measure of central

tendency and dispersion brought out the following results.

153

Table 5.40

One-Sample Statistics for Opinion about dealers services

N Mean Std.

Deviation

Std. Error Mean

Opinion about service 456 3.6952 .75684 .03544

Behaviour of employee

working with dealers 456 3.6075 .74529 .03490

Role of dealers in sale of

car 456 3.6206 .80297 .03760

Extent of influence 456 3.0746 .38506 .01803

Table 5.41

One-Sample Test

Test Value = 3

T Df Sig. (2-

tailed)

Mean Difference

95% Confidence Interval of the

Difference

Lower Upper Lower Upper Lower Upper Opinion about service

19.614 455 .000 .69518 .6255 .7648

Behaviour of employee working with dealers

17.405 455 .000 .60746 .5389 .6760

Role of dealers in sale of car

16.505 455 .000 .62061 .5467 .6945

Extent of influence

4.135 455 .000 .07456 .0391 .1100

154

From the above table t-test tables, it is found that the mean

values and standard deviations are service (mean values and standard

deviations are services (mean 3.69, Standard deviation = .756)

employees behaviour (mean = 3.617, Standard deviation = .745). The

role of dealers (mean = 3.62, Standard deviation = .802) and

promotional offers (mean = 3.07. standard deviation =.385). The t-

values obtained as comparison with test values 3 are 19.614, 17.405,

16.505 and 4.135 statistically significant at 5 percent level. Hence it is

concluded that car purchasers in Chennai city agreed the services of

dealers range from moderate to good. They are also attracted towards

good behaviour employees working in showrooms and service centers.

The customers feel the role of dealers in the sale of car is significant

and they moderate influence of the promotional offers. The car users in

Chennai city give an optimistic and moderate satisfaction over

dealers/service providers of the cars they purchase.

Availment of Services

The car services providers in Chennai city avail free services as

well as paid services. The opinion survey expressed the frequency

distribution of free services and paid services.

155

Table 5.42

Availing of Services


Percent

Cumulative

Percent

Others 71 15.6 15.6 15.6

Free Service only 87 19.1 19.1 34.6

Both free and paid

service 298 65.4 65.4 100.0

Total 456 100.0 100.0

The frequency distribution indicated 15.6 percent of cars do not

avail services from their dealers and 19.1 percent (87) customers obtain

free services only. A minimum of 65.4 percent (298) customers avail

both free and paid services of dealers. This shows that good free and

paid services are offered by dealers to customers in Chennai city.

Behaviour of car users after free service period

The car customers in Chennai city think twice to give their cars to

dealers for paid service after the free service period. They have good

analytical reasons delay in service, high cost of services, high cost of

spares and quality of service to avoid their dealers for service. Ranking

analysis is applied to identify the critical reasons of customers on

service dissatisfaction. The following are results of ranking analysis

156

Table 5.43


Reasons Mean value Rank

Delay in services 2.9101 3

High cost of services 1.8925 2

High cost of spares 1.7105 1

Quality of service 2.9737 4

From the above table it is found that high cost of spares quoted

by dealers lead to primary dissatisfaction (rank1) among Chennai city

car users. They expressed dissatisfaction over high cost of service

(rank 2) and procrastination in services (rank 3) provided by the dealers.

They also feel poor quality of service, impeding them to give service

after free period.

Sales Promotion

Sales promotion is one of the elements in the consumer

behaviour to ascertain the customer’s reaction. The car dealers in

Chennai city employ various sales promotional strategies reduction in

price, free gifts, extension of warrants periods, bearing of road tax and

insurance to attract many customers and to materialize their sales. The

following frequency distribution arises with opinion of customers on

promotional offers of dealers.

157

Table 5.44

Sales Promotion

Promotional offers Frequency Percentage

Reduction in price 211 46.27

Free gifts 83 18.20

Extension of warrants periods 75 16.45

Bearing of road tax insurance 87 19.08

Total 456 100.00

From the above table it is found that 46.27 percent (211)

customer’s are given price reduction in the price of car and 18.20

percent (83) customers are offered free gifts by the dealers. It is also

observed 16.45 percent (75) and 19.08 percent (87) customers

obtained extension of warrants period and road tax insurance

respectively. It is concluded that dealers offer reduction in the prices as

a promotional offers to catch hold of customers and to render

satisfaction.

Influence of sales promotional offer

The car users in Chennai city responded to a dichotomous

question with option yes or No to explain the influence of sales

promotional offers of car dealers. The frequency percentage analysis is

presented below.

158

Table 5.45


Opinion Frequency Percentage

Yes 102 22.37

No 354 77.63

Total 456 100.00

The dichotomous responses indicated that a maximum of 77.63

percent (354) customer are not at all influenced by sales promotional

offers of dealers and the remaining 22.37 percent (102) are easily

persuaded by the sales promotional activities of dealers. It is also

ascertained that Chennai city car users are meticulous about the

characteristics of the products rather than sales promotional offerings.

Though Majority of car users in Chennai city deemed the

influence of sales promotional activities of dealers and the influence is

found among minimum number of car user, it is indispensable to

determine the sales promotional variables influencing the customers.

The dichotomous response regarding sales promotion ascertains the

success of sales promotion, therefore this variable is considered as

dependent and other variables sales promotional, offer price deduction,

free gifts warrants extension and bearing of road tax and insurance as

independent variables. The application of logistic regression is

appropriate to handle the dichotomous dependent variables to predict

159

most influential variables (Roger D. Blackwell, Paul W. Miniard and

James F. Engel, 2007) The results are presented below.

Table 5.46

Omnibus Tests of Model Coefficients

Chi-square df Sig.

Step 1 Step 43.075 4 .000

Block 43.075 4 .000

Model 43.075 4 .000

Table 5.47

Model Summary

Step -2 Log

likelihood Cox &Snell R

Square Nagelkerke R

Square 1 441.681(a) .090 .138

Estimation terminated at iteration number 5 because parameter

estimates changed by less than .001.

The omnibus tests of model co-efficient indicate the chi-square

value for the steep block independent variables and model fit is 43.075

respectively, which is statistically significant at 5 percent level.

Therefore it is concluded that the dependent variables is suitably

explained by independent variables of sales promotion. The Cox and

Snell R-square .090 and Nazelker R-square (.38) are also statistically

160

significant to support regression fit. The contribution of sales

promotional activities influences the dichotomous variables. The

individual impact of independent variables is presented below:

Table 5.48

Variables in the Equation

B S.E. Wald df Sig. Exp(B)

Step

1(a)

Sales promotional

offer-Reduction in

Price

-

1.388.234 35.256 1 .000 .250

Sales promotional

offer-Free gifts .879 .329 7.148 1 .008 2.409

Sales promotional

offer-Extension of

Warranty period

.448 .274 2.679 1 .102 1.565

Sales promotional

offer-Bearing road tax

& insurance

-.639 .236 7.314 1 .007 .528

Constant 1.875 .186 101.981 1 .000 6.524

a Variable(s) entered on step 1: SPOa, SPOb, SPOc, SPOd.

The co-efficient for reduction in price (35.256), free gifts

(m=2.679) and bearing of road tax (7.314) are statistically significant

and extension of warrants is not significantly influencing. Hence it is

concluded that the success of sales promotion of car depends upon

price reduction, free gifts and bearing of road tax are the primary reason

to manage the customers based on sales promotional activities.

161

Cluster Justification

The classification of Car purchases in Chennai city into 3

heterogeneous groups need to be justified mathematically. It is

indispensable to prove that the existence of three clusters is necessary

as well as sufficient. It is also important to prove the factors

comfortability, quality and cost and convenience are basis for cluster

formation and nature of factors discrimination. The analysis is exploited

in this function to identify the perfect discrimination of the factors; the

following results justify the cluster classification.

Table 5.49

Tests of Equality of Group Means

Wilks'

Lambda F df1 df2 Sig.

Comfortability .490 235.829 2 453 .000

Quality and cost .353 414.498 2 453 .000

Convenience .533 198.097 2 453 .000

From the above table it is found that comfortability (F=235.829),

cost and convenience (F=414.498) and quality (F=198.097) are

statistically significant to form the cluster. They perfectly act as a basis

for cluster formation.

162

Table 5.50

Eigen values

Function Eigen value

% of Variance

Cumulative %

Canonical Correlation

1 2.977(a) 88.1 88.1 .865

2 .402(a) 11.9 100.0 .536

First 2 canonical discriminant functions were used in the analysis.

Table 5.51

Wilks' Lambda

Test of Function(s)

Wilks' Lambda

Chi-square df Sig.

1 through 2 .179 776.847 6 .000

2 .713 152.800 2 .000

The two linear discriminant functions f 1and f 2 with Eigen values

2.977, 0.402, with individual variances 88.1 percent and 11.9 percent.

The canonical correlation values .865 and .536 are all significant to

enter the perfect heterogeneous classifications. The Wilk’s lambda

values and chi square values of two functions indicate the significant

difference in each group characteristics of clusters. The following

structure matrix segregates the influence of factors in the cluster

formation.

163

Table 5.52

Structure Matrix

Function

1 2

Quality and cost .745(*) -.667

Convenience .519(*) .424

Comfortability .536 .682(*)

The structure matrix revealed the 3 factors are grouped through

two linear functions Z1 and Z2. Therefore Z1 is the composition of cost

convenience and quality factors of customers and Z2 comprises

comfortability alone. It can be concluded that comfortability plays a vital

role in classifying customers based on their level of satisfaction. The

functions and implicitly constructed as

Z1 = .745 (Cost & Convenience) + .519 (Quality)

Z2 = .682 (Comfortability)

These two Eiganations are linear and they justify the formation of

three cluster based on the level of satisfaction by the car users in

Chennai city.

Research propositions 4

The car customers do not differ in their satisfaction level

Research question regarding customer satisfaction identified

several factors influencing the satisfaction level of customers and

164

customers have various perception of the affective factors. The wide

literature survey ascertained the various perceptions are due to Brand

comparison, future purchase, Nature of finance, Problems of products

and opinion of customers on dealers (Kotler, P 1997). This leads to the

research proposition and need to be verified.

To verify this proposition, it is indispensable to classify the

customers of cars in the sample domain. The classification should be

done on the basis of factors. Factor analysis by Principal component

method (Ref Table No.5.18, 5.19, 5.20) followed by K-means cluster

analysis (Ref Table No 5.30, 5.31.) segmented the sample domain into

3 different groups. This classification is the sufficient condition for

perceptional difference among the customers. Now the necessary

condition for customer satisfaction of car customers can be checked

through the affective factors.

The non-parametric chi-square analysis is exploited here to find

the association between different customers groups and brand

comparison future purchase, experience of frequent problems and

nature of finance. (Ref Table No 5.32,5.33,5.34, 5.35, 5.36,5.37,5.38

and 5.39). This profoundly concludes the customer’s classification is

justified statistically and the car customers in Chennai city differ in their

level of satisfaction.

165

Derived buyer behaviour model

In order to verify this conceptual model, the following research

propositions are considered indispensable. The research proposition set

out to determine the buyer behaviour of car purchases. The elements

of buyer behaviour, awareness, factors influencing purchase,

customer’s attitude and satisfaction that were tested clearly presented

in the form of the following derived model.

Although the Chennai city car users had some limited product

awareness, which is predicted by their brand usage and brand

acquaintance. The research proposition 2 clearly ascertained that the

influencer obtain the collective momentum due to moderators brand

selection, SWOT factors of the product. Customer attitude expectation

and dealers service are uniquely determined by the verification of

research proposition 3. The developed research proposition 4

considered that post purchase satisfaction is considered as the

predominant output of buyer behaviour which has the incidental impact

of attitude and dealers service.

The above analysis fills the gaps in the existing literature relating

to post purchase behavior of car consumers.

166

CHAPTER - VI

SUMMARY OF FINDINGS, SUGGESTIONS

AND CONCLUSIONS

Several researchers in the field of buyer behaviour have followed

different attitudes and used different rules in making decisions. Studies

have been conducted to find the influence of various factors on buyer

behaviour. It is increasingly seen that people of the same demography

behave differently based on their awareness of the product. The

persons of different attitude and expectation hold different beliefs about

what is the right choice. This fact has led the researcher to probe the

inner thinking of consumer and attempt a classification of consumers

with almost similar satisfaction on the products they buy.

In this study, the researcher has emphasized the importance of

awareness, SWOT and its influence on the purchase behaviour of the

consumer. This involves evaluating the attitudes, interests and opinions

manifested by them and co-relating these to their purchasing and

consuming patterns. Since the activities, interests and opinions are

externally exhibited attributes, it is possible to classify attributes, and

classify people according to them

167

FINDINGS

Awareness of customers

The customers obtain the awareness of cars through attractive

advertisements dealers sales person’s interactions, explanation of

friends and relatives. The percentage analysis reveled that

advertisements (38.6 percent) plays highest role as source of

awareness followed by 32.7 percent obtain their awareness through

their friends and relatives. It is found that the various combinations of

advertisement, dealers/sales person and friends and relatives influence

18.8 percent consumers.

Media specification

It is found 41.22 percent customers are influenced by TV followed

by news papers and magazines (22.52 percent) and websites in the

internet (21.37) percent are considered as significant awareness

creating media.

Brand awareness

It is found customers have moderate awareness on Mahindra and

Ford. The parametric t-values indicate Hyundai, Tata are more popular

and customers in Chennai city possess high awareness on those

brands. The study revealed Maruthi is the most popular brand and the

168

Chennai city customers have very high awareness on Maruthi brand

cars.


It is concluded that Maruthi has more proximity with Chennai city

car customers and in recent years the new brand induced the

anxiousness of car customers in Chennai city.

Brand of car used

It is found that Maruthi (46.05%) is a popular brand in Chennai

city used by maximum number of customers. Hyundai (17.98%) and

Tata (13.61%) come next in the popularity list in Chennai city. Besides

these three cars, the Chennai city customers use Ford (6.36%) and

Mahindra (5.04%) sporadically


It can be concluded that the possession of popular brands is well

acquainted with them for more than 5 years alone are well associated

with level of awareness on the products.


It is also found 10.5 percent and 4.4 percent have 2 and 3 cars

respectively for them and their family. A maximum of 1.8 percent

169

possess four and above number of cars for their personal, business and

family use.

Association between number of cars and customers level of

awareness

It can be concluded that possession of many number of cars

divided the customer’s variety of depth in the awareness of cars and its

famous characteristic features. The number of cars increased they

possess increase their awareness for easy maintenance, mileage and

spare parts availability.

Nature of finance

The cars customers in Chennai city purchase their cars through

own financial supports (or) other commercial financial sources. The

customers also materialize their purchase by the contribution of own as

well as borrowed finance. It is found that 41.9 percent purchase their

cars through own finance followed by 28.5 percent and 29.6 percent

materialize their purchase by borrowing from banks, and private

financiers.

Borrowing sources

The car customers in Chennai city borrow their finance from

banks, non-banking institutions and other private financers. It is found

170

that 51.54 percent borrow from different sources and meager 5.66

percent customers are supported by other non-banking financial

institutions. The customers feel that the Government imposed road tax

is high and they found it difficult to pay their loans.

Factors influencing the customers towards purchase of cars

Type of fuel

In the present technological augmentation customers are very

meticulous about fuels, petrol, diesel, LPG and Battery, used in the

cars. It is found that 50 percent of customers use petrol and this fuel is

none popular among Chennai city car users. Diesel is also preferred by

25.9 percent and 12.1 percent Prefer LPG and Petrol.

Purpose of using car

The car users explicitly answered the options personal and social

cause office and business for the usage of cars. It is found that 58.3

percent customers use their cars for personal and social causes

followed by 9.9 percent customers found cars are useful for office and

business purpose. It is ascertained that 31.8 percent customers use

their cars for personal, social, office and business purposes.

171

Reasons for buying a present car

In Chennai city customers materialize their purchase due to the

reasons prestige and status, luxury, comforts and high technology. The

ranks of reasons clearly showed comfort is the primary reason for car

purchase in Chennai city followed by prestige and status. The analysis

also revealed luxury and high tech are the subsequent reasons to

materialize the car purchase in Chennai city.

Factor influencing to buy the car

The purchase of car is generally influenced by variables style and

design, brand name and fuel efficiency. It is found that three factors

emerged that of seven reasons influencing the customers to buy the

car. It is found that the first factor is named “Product attraction”. The

second factor extracted is “product suitability”. The third factor is “cost

approach” It is concluded that the customers in Chennai city are

influenced by the attractiveness of cars and its suitability of usage with

comforts and conveniences. At the same time their perception is

entwined with cost of buying cars.

Purchase decision making

The purchase decision is not a unilateral phenomenon, but it is

accomplished through consultation with family members. A customer

172

generally discusses with spouse, children and head of the family after

they convince themselves.


The customers take ultimate decision and they decide to

materialize the car purchasers. It is found where the customers take

their own decision; it is predominantly influenced by the spouse. A

maximum of 51.83 percent spouses influence the customers during

decision making followed by 32.72 percent influence of children and

15.45 percent of elders. The seemingly autocratic decision makers also

influenced by the family members significantly.

Reasons for brand selection

The brand selection of Chennai city car customers lean upon cost

orientation price and maintenance and customer’s emphasized comfort

is primary reason for brand selection. The quality of car and facilities

offered in cars make them to prefer specific brand. It is found that the

maximum of 68.2 percent customers are sensitive to the influence of

purchase.

SWOT factors

Offer for high segment cars and demand for two wheelers

reduces the enthusiasm of purchasers and widens the threat for car

173

purchase. Easy accessibility of cabs/call taxi also increased the

weightage of threat to car purchase in Chennai city.

The relationship between personal factors and SWOT factors of

car purchase

The male car consumers in Chennai city aware of high cost as

the primary reason for weakness, in the case opportunity factors the

female customers of cars in Chennai city realized the draw backs of

small cars create more opportunity for car purchase.

It is also observed the customers differ in the perception

regarding threat factors demand for two-wheelers and offer for high

segment cars with respect to their age. It is found that industrial sector

employees perceived high cost is the major weakness of car purchase

in Chennai city.

It is found the car purchasers in Chennai city with unique earning

members in the family realized draw backs of small cars and attractive

offer increase conducive opportunity for car purchasers. The customers

with 3 or 4 earning members in the family do not feel price of high

segment cars is a main opportunity for car purchase. The 3 or 4

earning member customers feel cabs/call taxi and changing technology

are not a major threat to car business in Chennai city.

174

It is found that the strength factor maintenance cost and

weakness factor increase in fuel price differ significantly with respect to

income of the customers. The customers with income Rs.10000 to

20000 declined to say draw backs of small cars and price of high

segment cars is a major threat to purchase of cars in Chennai city.

It is also found the customers with big family size are not able to

realize the weakness of car purchase factors competition from low

segment and low mileage. The three family member customers find

more opportunities for car purchase in Chennai city due to the factor

draw backs of small cars but two members family customers are not

able to accept the opportunities of car purchase through effective

advertisement. The single customers consistently expressed attractive

offer is best opportunity for car purchase. There is a contrast opinion of

threats for the factors demand for two wheelers is a least threat and

emergence of cabs/call taxi is a great threat.

Opinion about dealers services

Car purchasers in Chennai city agreed the services of dealers

range from moderate to good. They are also attracted towards good

behaviour employees working in showrooms and service centers. The

customers feel the role of dealers in the sale of car is significant and

they moderately influence the promotional offers. The car users in

175

Chennai city give an optimistic and moderate satisfaction over

dealers/service providers of the cars they purchase.

Availment of services

It is found 15.6 percent of cars do not avail services from their

dealers and 19.1 percent customers obtain free services only. A

minimum of 65.4 percent customers avail both free and paid services of

dealers. Good free and paid services are offered by dealers to

customers in Chennai city.


It is found that high cost of spares quoted by dealers lead to

primary dissatisfaction among Chennai city car users. They expressed

dissatisfaction over high cost of service and procrastination in services

provided by the dealers. They also feel poor quality of service,

impeding them to give service after free period.

Sales promotion

It is found that 46.27 percent customer’s given price reduction in

the price of car and 18.20 percent customers are offered free gifts. It is

also observed 16.45 percent and 19.08 percent customers obtained

extension of warrants period and road tax insurance respectively.

176

Dealers also offer reduction in the prices as promotional offers to catch

hold of customers and to render satisfaction.


A maximum of 77.63 percent customer are not at all influenced by

sales promotional offers of dealers and the remaining 22.37 percent are

easily persuaded by the sales promotional activities of dealers. The

success of sales promotion of car depends upon price reduction; free

gifts and bearing of road tax are the primary reason to manage the

customers based on sales promotional activities.

Customers’ attitude and expectations

The Chennai city car users strongly agree with the role of quality

and importance for price they have moderate agreeability on prestige

exposure and usage of cars. The valuable appearance and colour

indicate that the customers expect appearance and colours of car to be

important before they materialize the purchase of cars. The car users in

Chennai city profoundly agreed the mileage efficiency advertisement

and repeated purchase due to satisfaction are important attitudes for

purchase.

Product characteristics and usage, appearance of car are the

important attitude before and after purchase of cars. They expect

177

optimistic dealers service and attracted towards effective sales

promotion. The purchase of cars is materialized due to the compulsion

of family members and it exposes their prestige.

Different types of attitude and customer expectation

There are three types of car users in Chennai city with bumptious

reasons for car purchase and another is perfectly unmoved by the sales

promotional activities. The third group is always seeking qualities of the

cars.

Influence of demographic variables on the factors of customers

attitude and expectations.

The male and female customers in Chennai city have different

perceptions about characteristics of cars and dealers service. The

influence of family members differs on male and female customers

when they purchase cars. Usage and appearance is perceived

differently by the male and female customers of Chennai city.

The car customers in Chennai city in different age groups have

different opinion about various services offered by the dealers. Similarly

in the intrinsic purchase influence, the domination of family members is

different on different age of the customers, in showing their prestige.

178

The car users in Chennai city with UG level qualification differ in

their opinion with PG level customers regarding characteristics of cars

and service offered by the dealers. There is a significant difference

between customers with UG level qualification and PG level

qualifications in conceding the sales promotional strategies to

materialize the purchase of cars and exposing the prestige to others.

It is found that dealer’s service and sales promotion are

influenced by state government employees, central government

employees and quasi government employees. It is also identified the

employees in service sector and industrial sector differ in their opinion

about car dealers service in Chennai city as well as their sales

promotional strategies.

The increase and decrease in the family income due to number of

earning members create incidental effects over sales promotion and

usage and appearance of four wheelers. The number of earning

members in the family affects the sales promotion notion perceived by

them. It is also found that the customers with different range of income

Rs.10000 – 20000, Rs.20000-30000 and above Rs.30000 differ in their

perception about characteristic features mileage aid price of cars. They

have different opinions about dealer’s service and sales promotional

advertisement. The prestige of owing car entirely depends on the family

income. The customers of car in Chennai city with different family size

179

demanded product characteristics of cars in different manner and their

absorption of sales promotional strategies are also different. They have

peculiar segmentation of feelings towards usage and appearance of

cars they use.

Customer satisfaction

The customer satisfaction of cars in Chennai city is decided by

the three predominant factors that prevail among the customers are

comforts and convenience as well as cost and maintenance. The

quality orientation of cars plays the key role to measure the customer

satisfaction

Brand comparison

It is found that 68 percent of customers compare their brands of

cars with others and concluded their cars are always superior to other

brands of cars, and remaining 32 percent customers do not have the

comparative psychology on the cars they possess. The customers in

Chennai city perceive the reasons for superiority of car brands

meticulously.

Reasons for superiority of brands

Brand comparison and superior quality of cars are identified by

Chennai city car customers through comparing mileage given by four

180

wheelers and less maintenance cost. They give least importance to

price, and technology advancement of the cars they purchase. The

customers of cars always expect low price, more comfort and

conveniences from the manufacturers. They always seek for the new

brands to offer a culminating point of satisfaction.

Choice of future purchase

Among the Chennai city car customers 39.5 percent of

consumers planned to purchase the same brand if it exists and 60.5

percent have the inclination to purchase different brands of cars in

future.

Brand shift

The primary data ascertained 39 percent of car customers in

Chennai city plans for brand shift and 61 percent of them are loyal and

plan to materialize the purchase of same brand of car next time also.

Reasons for brand shift

The ranking analysis identified the high maintenance cost and

heavy fuel consumption is the subsequent reasons prevailing among

car consumers in Chennai city. These reasons actually induce them for

the brand shift. It is found 39 percent of consumers quoted non

181

availability of spares, service center problems, and higher taxes are

severely influencing them for brand shift.

Frequent problems encountered by car users in Chennai city

It is found that 11.4 percent consumers encountered problems in

their cars and most of the car consumers (88.6 percent) do not face

frequent problems of their cars. Only 11.4 percent consumers with

problems of their car reduced the reasons systematically. They also

experienced the problems of starting trouble as well as non availability

of spares.

Brand recommendation

Percentage analysis explicitly expressed that 60.1 percent

consumers have a optimistic experience of the brand of car they

possess and they are enthusiastic to recommend their brands to others.

The remaining 39.9 percent consumers are not satisfied with their

brands and decided not to recommend to friends and relatives. The car

consumers in Chennai city are able to transparently express the

reasons for non-recommendation.

It can be concluded that the dissatisfied customers expressed the

negations of brand unworthy to recommend. Some customer’s non

182

recommendation is due to non interference psychology of

unambitiousness.

Different levels of customer satisfaction

There are three types of car users in Chennai city. They hetero

generously expect comfortability, less product cost, and less

maintenance cost with good quality from the car they purchase.

Association between customer satisfaction and customer post

purchase behaviour

It is concluded that there is an association between different

levels of customer’s satisfaction and brand comparison behaviour.

Customer satisfaction leads to purchase of same brand in future and

dissatisfaction influences the brand shift. There is a deep association

between satisfaction levels and choice of purchase of cars in future.

The satisfied customers also inclined to purchase different brands by

expecting more product features.

The brand shift is found maximum among the car users in

Chennai city. The customer’s satisfaction also depends upon the

problems faced by the customers during post purchase behaviour. The

different levels of customers satisfaction is not decided by the frequent

problems they face in the post purchase period. The saturated

183

satisfaction also decides the Chennai city car customer enthusiasm for

brand recommendations. .

The association exists between different levels of satisfaction and

recommendation of the brands. The satisfied customers are more

enthusiastic in recommending their brands of cars to others.


There are three groups car users namely comfort seekers,

gratified and subsistent customers in Chennai city, the maximum

percentage uses their own finance. There is a deep association

between nature of finance and customer satisfaction, the perceptional

difference among Chennai city car customers is well influenced by the

nature of finance they used to purchase the cars.

MARKETING IMPLICATIONS/SUGGESTIONS

The study establishes the relevance of lifestyle influence on the

behaviour of the consumers. This implies that the marketing managers

are likely to benefit considerably in targeting and positioning and in their

media communication by focusing their attention on the ongoing

changes in the lifestyle patterns of their consumers.

The purchase-interested cluster members are people who are

very loyal to the car sellers. They buy only from car showrooms on

184

which they can count on the vehicle guarantee. Marketer in this case

can use promotional appeals, discounts credit periods and the like to

motivate the consumers towards purchase of cars in Chennai city.

Family members are active information seekers. They tend to buy

cars for their families by visiting more frequently a various car

showrooms to compare the product, style, quality, price before they

make their final choice. Hence display of cars in showrooms must match

the lifestyle of the consumer’s of car purchasers whom the marketer

intends to approach.

The salesmen should have sound information regarding various

brands sold by them and their selling prepositions. They should be well

trained to handle consumers who are well informed.

Innovative cluster are people who are very interested in trying

new brands of cars. They always want to be the trendsetters. This

would always lead to make them opinion leaders who in turn would

influence the buying patterns of their peers, friends and relatives. Hence

marketers must always keep this segment members abreast of the new

branded cars introduced and try to motivate this segment to spread a

favorable word of mouth for their new branded cars to supplement their

selling efforts.

185

CONCLUSION

Car purchasers in Chennai city have been greatly influenced by

the attributes of cars and they are meticulous at their awareness levels.

The study revealed customers of cars have very high awareness on

various brands, products attributes and characteristics. The strength

factor spare availability, maintenance cost are the factors influencing

the buying behaviour of car customers. The other factors cabs/call taxi

and changing technology create serious threat to car purchasers.

Dealer’s service and interaction with customers are vital to

determine the satisfaction among car purchasers. Customers expect

free gifts, discounts during their purchase of the costly durable product.

The customer’s attitude towards car learns upon the mileage,

maintenance cost and comfortability. The attitude and expectation of

customers radically differ with respect to need recognition, sales

promotion and quality of the product.

The customer satisfaction of car users depends upon the factors

cost orientation, attractive features, conceited orientation, product

quality and service expectation. If these five factors are found

satisfactory in their purchase of cars then the customer satisfaction

exists definitely. Customers compare the brands of durable they

186

possess with other brands on the basis of cost, quality, maintenance,

convenience and comforts

SCOPE FOR FURTHER RESEARCH

Buyer behaviour is a highly dynamic area of research. Though a

number of researches have been carried out in this area, it still holds its

own importance. There are more elements like awareness,

preferences, purchase decision and post purchase behaviour which

reveal the nature of customers and lifestyle characteristics of

individuals. Research can further be carried out using these buyer

behaviour elements independently, which can define different

behavioural aspects and clusters of customers.

There may be a lot of distinction in the behavioural patterns, the

perception exhibited by the people living in rural, urban and semi urban

areas due to their difference in their buyer behaviour and

demographics. There is a scope to compare the behaviour of these

three groups with respect to their different cluster pattern.

As the study is confined to the Chennai Environment, there is a

scope for comparing the lifestyle and behavioural patterns exhibited by

the people staying in different metros and cities.

187

An in-depth study of impact of the factors influencing behaviour

patterns on the purchase decision characteristics of each cluster can be

further carried out.

188

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197

QUESTIONNAIRE

Profile of Customer : I

1.1 Name and Address (Optional) :

1.2 Gender : Male / Female

1.3 Age : Between 25 – 40 Years

Between 40 – 55 Years

Above – 55 Years

1.4 Educational Qualification (a) School Level

(a) UG – Level

b) PG – Level

1.5 Educational Qualification : a) UG – Level

b) PG – Level

1.6 Occupational Status : a) State Govt Employed

b) Central Govt Employed

c) Quasi Govt Employed

d) Service Sector Employed

e) Industrial Sector Employed

1.7 Number of earning members in the

Family : a) 1

b) 2

c) 3, 4 Above

1.8 Family Monthly Income : a) Rs. 10000- 20000

b) Rs. 20000- 30000

c) Rs. 30000 – Above

1.9 Family Size : a) Single

b) Two

c) Three

d) Four and Above

198

AWARENESS OF CONSUMERS - II

2.1 State the source of awareness about the cars

a. Advertisements

b. Dealers / Sales Persons

c. Friends / Relatives

d. Others – Please specify

2.2 If it is through of advertisements, specify the media

a. News papers and Magazines

b. Notices, Pamphlets, Hoardings

etc.

c. Television / Radio

d. Internet

e. Others – Please Specify

2.3 State your level of awareness about the following brands

Brands of

Car

Very High

Awareness

High

Awareness

Moderate

Awareness

Low

Awareness

Very Low

Awareness

Fiat

Hindustan

Motors

Hyundai

Mahindra

Tata

Chevrolet

Ford

Reva

Maruti

199

2.4 State how long you are aware of the following brands of cars.

Brands of Car More than 5

Years

1 – 5 years Recently

Fiat

Hindustan Motors

Hyundai

Mahindra

Tata

Chevrolet

Ford

Reva

Maruti

2.5 State the brands of cars that you and your family use

a. Fiat

b. Hindustan Motors

c. Hyundai

d. Mahindra

e. Maruti

f. Tata

g. Chevrolet

h. Ford

i. Reva

j. Any Other

2.6 State the number of cars that you / your family use

a. 1

b. 2

c. 3

d. 4 and above

200

2.7 State the nature of finance to purchase car

a. Own Finance

b. Borrowed Finance

c. Both

2.8 If Borrowed finance, or both state the source of finance

a. Banks

b. Non – banking institutions

c. Private Financiers

d. Others – Please specify

2.9 State the level of opinion about the rate of interest charged on

borrowed amount

a. Very high

b. High

c. Moderate

d. Low

e. Very Low

2.10 State the level of opinion about road tax for cars

a. Very high

b. High

c. Moderate

d. Low

e. Very Low

201

FACTORS THAT INFLUENCE THE CONSUMERS - III

3.1 State the type of fuel used in your car

a. Petrol

b. Diesel

c. LPG / Battery

d. Battery

e. LPG & Petrol

3.2 State the Purpose of using the car

a. Personal and Social

b. Office and Business

c. Both

3.3 Rank the reasons (as 1, 2, 3 etc) for buying the present car you are using

now

a. Prestige and status

b. Luxury

c. Comfort

d. High Tech

e. Other reasons – Please

specify

3.4 Rank the factors (as 1, 2, 3 etc) that influenced you to buy the car

a. Style and Design

b. Brand Name

c. Fuel Efficiency

d. Seating Capacity

e. Price

f. Appearance

g. Others – Please Specify

202

3.5 Specify the decision maker regarding the purchase of car

a. Yourself

b. Spouse

c. Children

d. Others – Please Specify

3.6 If the decision is taken by you, who influenced you significantly?

a. Spouse

b. Children

c. Elders

d. Others – Please Specify

3.7 Rank the reasons as (1, 2, 3 etc) for selecting the brand

a. Price

b. Quality

c. Mileage

d. Comforts and Convenience

e. Seating capacity

f. Less Maintenance

g. Facilities Provided

h. Other reasons – please

Specify

3.8 Have you considered other brands of car before you buy the present

brand?

Yes / No

203

3.9 If Yes, Specify the brand name

a………………………b………………..c……………..

4. Rank (As, 1, 2, 3 etc) the strength, weakness, opportunities and threat

factors relating to purchase of cars

Strength Factors Weakness Factors

a. Maintenance Cost a. High Cost

b. Availability of Spares b. Increase in Fuel Price

c. Service facilities Cars c. Competition from

low

segment

d. Availability of multi brand d. Low Mileage

e. Loan Facility e. Seating

Capacity

Opportunity Factors Threat Factors

a. Draw backs of small Cars a. Demand for two

wheelers

b. Entry of MNC’s b. Cabs / Call Taxi

c. Price of high segments cars c. Changing technology

d. Effective advertisement d. Offer for high

segment cars

e. Attractive offer e. Poor Roads.

204

OPINION ABOUT DEALER SERVICES - V

5.1 Give your opinion about the services of your dealers during the sales

a. Very Good

b. Good

c. Normal

d. Poor

e. Very Poor

5.2 Regarding car servicing provided by the dealer, you avail –

a. Free Service Only

b. Both free and paid service

5.3 Rank the reason (as 1,2,3 etc) for not giving your car to your dealer after

free service period is over

a. Delay in services

b. High Cost of Services

c. High Cost of Spares

d. Quality of services is bad

e. Other reasons – Please specify

5.3.1 State the behavior of the Employees working in the showrooms and

service centers of your dealer

a. Very Good

b. Good

c. Normal

d. Poor

e. Very Poor

205

5.4 In your opinions, the role of dealers in the sale of car is

a. Very Significant

b. Significant

c. Normal

d. Not Significant

e. Not at all Significant

5.5 When you purchase the car, what type of sales promotional offer is given to

you by the dealers?

a. Reduction in price

b. Free gifts

c. Extension of Warranty period

d. Bearing of road tax & insurance

e. Others – Please specify

5.6 Do you feel that the sales promotional offer influenced you in buying

particular brand of car?

Yes / No

5.7 If Yes, state the extent of its influence

a. Very high influence

b. High Influence

c. Moderate Influence

d. Low influence

e. Very low influence

206

CONSUMER SATISFACTION - VI

6.1 State your level of satisfaction towards the following aspects of your car

Various Aspects

Very High

Satisfactio

n

High

Satisfacti

on

Moderate

Satisfactio

n

Low

Satisfacti

on

Very Low

Satisfacti

on

Price

Quality

Mileage

Seating

Comforts &

Convenience

Seating Quality

Less

Maintenance

Facilities

Provided

Boot Space

Safety

Availability of

Spares

Driving Comfort

Others – Please

Specify

6.2. Do you feel that the brand of car you use at present is superior to other

brand of car?

Yes / No

207

6.3 If Yes, Rank the reasons (as 1, 2, 3 etc)

a. Low Price

b. Better Mileage

c. Less Maintenance

d. Technology advancement

e. Other reasons – Please Specify

6.4. State your choice of purchase of car in future

a. Same Brand

b. Different Brand

6.5. At present, do you have any idea to shift from the usage the present

brand of car to other brand of car?

Yes / No

6.6.1 If yes, rank the reasons (as 1,2,3 etc)

a. Heavy fuel consumption

b. High Maintenance cost

c. Non availability of spares

d. Service center problems

e. Higher Tax

f. Other Reasons – Please Specify

6.7 Have You experienced frequent problems in using the car?

Yes / No

6.8 If yes, rank the problems (as 1,2,3 etc)

a. Starting Trouble

b. Battery Down

c. Non availability of spaces

d. Costly spares

208

e. Others – Please specify

6.9 Would you prefer to recommend to others to buy your brand of car?

Yes / No

6.10 If No, State the reasons a. Not Worth to be recommended b. Let others take their own decision c. Preference and satisfaction will vary

from person to person d. Other reason – lease specify

7.1 GIVE YOUR LEVEL OF AGREEABILITY ON THE FOLLOWING

STATEMENTS (PLEASE TICK THE APPROPRIATE COLUMN)

SA – Strongly Agree, A – Agree

N – Normal, SDA - Strongly Disagree, DA – Disagree

Statements SA

A N SDA DA

Quality plays a major role in the purchase of

car by customers

Customers buy car for showing prestige

Mostly customers buy car for official / business

use

Family members dominated the customers in

buying car

Price is the most important factor which

influences the customers in the purchase of car

Appearance and colour of car are less

important for customer

Mileage efficiency is a factor which the

customer considers very important

209

Sales promotional offer influences the

customer significantly in buying the car

The advertisements for cars are brought

adequately

Those customers who buy the same brand of

car second / third time can be called as

satisfied customers

Dealers provide lot of information to customers

about the car

Dealers provide better services to customers

Customers change their decision after

interacting with sales persons in the car show

room.

pre and post purchase behaviour of four wheeler … · pre and pos whee vin doct und vin t pur ler...

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