PRE AND POST PURCHASE BEHAVIOUR OF FOUR WHEELER … · PRE AND POS WHEE VIN DOCT Und VIN T PUR LER...
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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
No TITLE OF THE 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
No TITLE OF THE 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
4.37 Number of Cases in each Cluster 76
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
No TITLE OF THE 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
5.7 Number of Cases in each Cluster 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
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Table
No TITLE OF THE 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
5.31 Number of Cases in each Cluster 145
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
5.35 Chi-Square Tests 148
5.36 Experience frequent problems in using cars 149
5.37 Chi-Square Tests 150
5.38 As the title of Recommend others top buy your
brand of car
152
5.39 Chi-Square Tests 152
7
Table
No TITLE OF THE 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
Frequency Valid Percent Cumulative Percent
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
From the above table it is found that 36.16 % of the respondents
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
Frequency Valid Percent Cumulative Percent
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
From the above table it is found that 12.7 % of the respondents
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 acquaintances (or) proximity
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
Association between brands of cars used and level of awareness
Brand Chi-square Significance
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
Chevrolet 3.423 0.490
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
Number of cars used by the customers
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
Brand Chi-square Significance
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
Chevrolet 40.311 0.000
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
Association between nature of finance and customers satisfaction
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
Lower Upper Lower Upper Lower Upper
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
Influence in decision making
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
Extraction Method: Principal Component Analysis.
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
Number of Cases in each Cluster
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
Likelihood Ratio 275.951 1 .000
Fisher's Exact
Test .000 .000
Linear-by-Linear
Association 277.120 1 .000
N of Valid Cases 456
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
Total 281.953 317 Strength factor
availability of spares Between Groups 12.409 4 3.102 3.305 .011
Within Groups 300.360 320 .939
Total 312.769 324 Strength factor
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
Total 477.378 208 Opportunity factor
price of high segments cars
Between Groups
19.679 2 9.839 5.758 .004
Within Groups
469.965 275 1.709
Total 489.644 277 Opportunity factor
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
Research Proposition 2
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
Lower Upper Lower Upper Lower Upper
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
Extraction Method: Principal Component Analysis.
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
Number of Cases in each Cluster
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
characteristics 13.528 1 13.528 51.150 .000
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
Usage&appearance .569 1 .569 .975 .324
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
Usage&appearance 1.549 1 1.549 2.653 .104
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
Usage&appearance 13.389 1 13.389 22.932 .000
Family
monthly
income
Product
characteristics 4.571 1 4.571 17.282 .000
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
Usage&appearance .245 1 .245 .420 .517
Family
size
Product
characteristics 1.998 1 1.998 7.556 .006
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
Usage&appearance 3.184 1 3.184 5.454 .020
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.
Research Proposition 3
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
Extraction Method: Principal Component Analysis.
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
Extraction Method: Principal Component Analysis.
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
Frequency PercentValid
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
Frequency PercentValid
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
Frequency PercentValid
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
Number of Cases in each Cluster
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
Likelihood Ratio 48.915 2 .000
Linear-by-Linear
Association 46.707 1 .000
N of Valid Cases 456
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)
Pearson Chi-Square 64.949(a) 2 .000
Likelihood Ratio 67.514 2 .000
Linear-by-Linear Association 64.767 1 .000
N of Valid Cases 456
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)
Pearson Chi-Square 2.969(a) 2 .227
Likelihood Ratio 2.977 2 .226
Linear-by-Linear
Association 1.176 1 .278
N of Valid Cases 456
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)
Pearson Chi-Square 47.043(a) 2 .000
Likelihood Ratio 48.915 2 .000
Linear-by-Linear
Association 46.707 1 .000
N of Valid Cases 456
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
Frequency PercentValid
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
Behaviour of car users after free service period
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
Influence of sales promotional offer
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.
Brand acquaintances (or) proximity
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
Association between brands of cars used and level of awareness
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.
Number of cars used by the customers
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.
Influence in decision making
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.
Behaviour of car users after free service period
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.
Influence of sales promotional offer
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.
Association between nature of finance and customers satisfaction
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
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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
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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.