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International Journal of Mechanical Engineering and Technology (IJMET)
Volume 10, Issue 03, March 2019, pp. 1227-1237. Article ID: IJMET_10_03_125
Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=3
ISSN Print: 0976-6340 and ISSN Online: 0976-6359
© IAEME Publication Scopus Indexed
A STUDY ON PREFERENCES OF FEMALE
CUSTOMERS IN THE PURCHASE DECISION OF
CARS IN CHENNAI
Balaji Jayakrishnan and Dr. R. Aruna
VIT University,India
ABSTRACT
In the recent years, women’s driving four wheeler has become a very common sight
all over the India. According to a survey, 85% of women are in the driving seat for all
purchases. Yet, many independent marketing and communication agencies reveal that
80% of women believe that the automotive industry as a whole is not doing a good job
at representing women, and 88% of women do not see themselves represented in the
sector’s advertising or websites. For years, women have been considered as primary
decision makers for most household products and forward thinking companies have
found ways to capitalize on this by developing marketing plans that address women’s
multifaceted lifestyles, by evaluating and retraining existing sales and customer service
forces to better serve women’s needs and interests. Many studies show that women feel
advertising has made them aware of different cars in the market. Also many women
agree about the perceived exclusivity of car ads in the ads being aimed only at men.
This study employs Conjoint Analysis to ask to know the preference of Women in Cars.
Results of the study are discussed with future directions for research.
Keywords: Contextual Targeting, Automobiles, Women, Conjoint Analysis and
Consumer Behaviour.
Cite this Article: Balaji Jayakrishnan and Dr. R. Aruna, A Study on Preferences of
Female Customers in the Purchase Decision of Cars in Chennai, International Journal
of Mechanical Engineering and Technology, 10(3), 2019, pp. 1227-1237.
http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=3
1. INTRODUCTION
India has proved itself as one of the world’s largest and fastest growing automobile markets
over the years, with production in 2018 of 29 million vehicles and it is estimated to grow about
60 million vehicles in 2022 (Automobile sector report, IBEF, April 2017). Currently
contributing 7.1 percent to the GDP and around 3.2 crore people are employed directly or
indirectly by the Indian Automobile Industry. Since the purchase of car requires high
involvement, it is also equally important to promote the advertisement of cars to get the
attention of customers. Presently Indian ad industry contributes 0.4% of GDP. Advertising
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plays a pivotal role in increasing brand awareness as well as creating strong brand associations
(Yoo, Donthu, & Lee, 2000).
Understanding a consumer is complex as it is a blend of personal, economic, political,
social, cultural, technological, demographic, psychological, and natural factors. Some of these
factors are uncontrollable and hence an effective marketing strategy needs to be developed to
understand these complexities.
Hence it is time for advertising industry to implement new strategies and plans to implement
innovative developments. In this context both automobile and ad industry can jointly present
new avenues towards enhancing the business.
Unlike earlier times, a woman driving is hardly a rare sight nowadays. An interesting fact
is that, women in smaller cities start driving earlier than those in metros. Most women drive all
days of the week, with various purposes such as work commuting, shopping and ferrying kids.
Also, most women cover a weekly range of 25-50km, while a significant number manage to
clock around 50-100km in a week. Women are smart browsers of the social web and digital
world compared to men. When buying cars, women focus mainly on the advertisements, in
particular digital ads than print media, while men concentrate on vehicle’s technical
specifications.
Relatively it is now found that Contextual targeting can provide a clear advantage to
promote ads to in order to engage specific customer. Targeted automobile ads have neglected
women in their promotional campaigns.
There is a need to establish a finer communication between advertising and purchase
decision involvement when targeting female customers. This paper focuses primarily on
analysing the advertising cues and purchase behaviour cues related to female customers.
According to Barletta (2003), “Women are the world’s most powerful consumers. They are
the big spenders, whether that is goods purchasing for households, corporate purchasing, or
small businesses” (p. xix). Packaged goods companies and retailers have long recognized that
women form the core of their market, however, until recently the big businesses – automotive,
financial services, computers, consumer electronics, home improvements, and travel for
example – appear to have overlooked female customers almost entirely. Lots of advertisements
and marketing communications that resonate with men don’t simply hit the spot with women.
A company that is aware of consumers’ reaction to different characteristics of goods, prices
and advertisement tricks has advantage over its competitors. (Kotler & Keller 2009)
Gender- based differences in perceptions, attitudes and communication styles generate
gender-differentiated responses in priorities, decision processes, and purchase outcomes.
(Barletta, 2003)
Menon (2012); and Jacob and Khan (2010) reported in their studies that there was
considerable proportion of modern women car buyers, which had increased three fold in the
recent years. Companies have started to dig deep into the Indian women's psyche and attention
for details. Marketers may need to look at the needs of women customers, who are increasingly
growing in the segment.
Westbrook and Fornell (1979) classified the respondents based on the extent of physical
shopping, and the use of neutral sources versus personal sources while searching for pre
purchase information. Their findings show four segments objective shoppers, moderate
shoppers, store intense shoppers, and personal advice seekers. The buyer’s age and education,
her/his satisfaction with a previously purchased product and the working condition of the same,
the evoked set size, and joint husband-wife decision making are shown to influence the
information seeking process (Westbrook & Fornell, 1979).
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Targeted selling will have a direct. Positive impact and five ways to get women buyer’s
attention is to get the innovative selling strategies, diversification, a tailored approach,
Automotive Ad campaigns filling a wide range of professionals, dealership that fills her
framework for their purchases and a positive pre and post sales experience. (Anne Fleming,
2017)
Goswami (2007) segmented college-goers psychographically into five clusters life-loving
go-getters, politically-conscious positivists, independent-minded, destiny-believing pessimists,
and happy-go-lucky dependants.
Kumar and Sarkar(2008) segmented metropolitan consumers into six behavioural groups
well-settled, strugglers, enjoyers, conservatives, self-concerned, and realists in order to
understand their consumption patterns. The segments were profiled in terms of their product
ownership, activities and interests, financial investment avenues, and media habits.
Sesa Sen (2017) expresses that in the past five years, the percentage of women buying cars
has nearly doubled, from 10-12 per cent to 25 per cent. And, to tap this growing market,
automakers are increasingly making their products women friendly. While Korean carmaker
Hyundai Motors India attributes 20-25 per cent of sales to women drivers, nearly 20 per cent
of the demand for Renault’s Kwid is from women. For Maruti, the country’s largest car maker,
as much as 15 per cent of sales across brands are driven by women car buyer, and the company
expects that number to grow.
Nielsen India (2014) an end to end consumer insights company, reported interestingly on
how women are now having a greater say in car purchase decisions in India. According to the
report Safety and convenience are two such top areas that women consider important.
Dorsch, Grove and Darden (2000) studied consumer buying behaviour using the 5 step
process (need – information search – evaluation of alternatives – purchase – post purchase
evaluation) problem solving paradigm or through the progression of consumer choice from a
product class to brand choice and found that marketers can do a better segmentation and
targeting of their campaigns based on the terminal values customers desire when choosing a
service category. Another factor considered was the knowledge about prior experience on
intentions to use a service category.
White (2004) discussed the factors that affect car buyers ‘brand preference and he pointed
out that with an increase in multi-car households, car dealers and advertisers needed to target
the right audience, taking into account the pester power of children and the importance of life
stage. Despite the fact that women are the primary buyers of most new cars, he admits that the
motor trade has traditionally been contemptuous of women’s role in the car buying process.
Jacob and Khan (2010) reported in their studies that there is also a substantial influence of
women in the car purchase decision of the family.
The purpose of the study is to find the involvement, preference and influence of Women in
Chennai in the purchase decision of Automobiles.
1. To assess the feature preferences for the prospective women purchasers.
2. To assess the factors influencing the car purchasing behaviour of women.
2. METHODOLOGY
Simple random sampling and Primary data collection methodology will be used to collect data
and conjoint analysis will produce the relatively important features of women car
consumers.We contacted a total of 600 women customers from Chennai through email and
requested to respond to an online questionnaire. The purpose of the study was communicated
in the email and an informed consent was taken. Out of 600 customers contacted, 504 customers
responded to the questionnaire. Due to incompleteness of questionnaire, 4 of them were deleted
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and 500 respondents were chosen finally for the research. A self-constructed questionnaire with
the aim of exploring the influencing factors of car purchasing decisions was designed.
Necessary deletions, additions, and editions were made into the questionnaire after having
conducted a pre-test. Acceptable level of understanding was aimed while selecting the list of
attributes from both industry professionals and women consumers. The selection of attributes
was based on deductive approach and was irrespective of the aims or purpose of the reviewed
studies from all levels of detail and various terms were used to refer them.
Consumer preference modelling among multiattribute analysis has been one the major
activities in consumer research. Conjoint analysis places the participant in a hypothetical use
scenario and allows for the evaluation of preference for multi-attribute alternatives (Myung,
2003). Variables being examined within conjoint analysis are regarded as attributes. Each
attribute (e.g. point size, column width, etc.) is then broken down into variations regarded as
levels (e.g. 12 points, 4 points, etc.). The combinations of each attribute and the respective
levels are classified as profiles. Participants are given profiles to evaluate via rating or choosing.
Utility values are calculated for each level, based on the respondent’s choices. Upon calculating
utility values, importance scores can also be determined. These scores help illustrate the impact
the attributes have in the individual respondent’s selections. There are three main methods of
conjoint analysis: traditional, adaptive, and choice-based.
Kelly's (1955) repertory grid, focus group interviews, or judgments of product managers,
retailers and others knowledgeable about the product/service and its uses can be used for this
purpose. The more difficult and often subjective task is to reduce the number of attributes to a
manageable size so that the estimation procedures are reliable while at the same time accounting
for consumer preferences sufficiently well.
3. DEMOGRAPHIC CHARACTERISTICS
From the above figure 1,2 and 3 we could interpret that women who owned cars were more
in the age between 26- 35 and from the data we could also interpret that married women used
and owned cars more than single ladies. Many women used cars for commutation to work and
homemakers used cars for ferrying the kids and shopping. From the survey, even though many
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Indian women get their driving license by 20-25, still due to the heavy traffic in cities they
prefer using a two-wheeler in place of a car.
4. PREFERENCE FEATURES
The above figure gives the feature preferences of women in the purchase decision of cars.
Out of which automated manual transmission and Anti-lock Braking System (ABS) are two top
areas that women consider important. Even in the price conscious segments, automated manual
transmission is preferred for the comfort and ease of driving. The ABS which is a critical safety
feature is also considered important among the women buyers. GPS navigation is also
considered as must have car features. Rear parking camera is another additional safety and
comfort feature offered by many car dealers as an extra option with cost. Followed by the
feature called Cruise control, which is popular only in C-segment cars, opted by less number of
women. Then Rain sensing wipers, Road side assistance, Electric wing mirrors and flat tyres
are some of the features preferred by women. From this we conclude that they are keener on
the safety and comfort features.
4.1. Preference Models
First, let p = 1, 2,..., t (1)
denote the set of t attributes or factors that have been chosen. Next, let Yjp denote the level
of the pth attribute for the jth stimulus. We first consider the case where Yjp is inherently a
continuous variable (e.g., travel time or price). The case of categorical (or polytomous)
attributes will be considered later. The vector model of preference, referred to as the Composite
Criterion Model by Srinivasan and Shocker (1973b) and Parker and Srinivasan (1976), posits
that the preference Sj for the jth stimulus is given by
Sj = ∑𝑾𝒑𝒀𝒋𝒑
𝒕
𝒑=𝟏 , (2)
Where the {Wp} are the individual's weights for the t attributes. Thus, the vector model is
identical in mathematical form to the Fishbein-Rosenberg class of multiattribute models. As
remarked earlier, the weights
{Wp} will, in general, be different for different individuals in the sample. Geometrically,
the preference Sj can be represented as the projection of the stimulus point {Yjp} on the vector
{wp} in the t-dimensional attribute space.
The ideal-point model posits that the preference Sj is negatively related to the squared
(weighted) distance dl of the location {Yjp} of the jth stimulus from the individual's ideal point
{xp}, where dj is defined as