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CONSUMER PERCEPTIONS AND BEHAVIOUR: A STUDY WITH SPECIAL REFERENCE TO CAR OWNERS IN NAMAKKAL DISTRICT Dr. S. SUBADRA,
Assistant Professor in Management Sciences S. N. S. College of Engineering Coimbatore. Pin Code – 641 107. Tamil Nadu State, India.

Dr. K. M. MURUGESAN,
Assistant Professor in Business Administration Alagappa Government Arts College Karaikudi. Pin Code – 630 003. Tamil Nadu State.

Dr. R. GANAPATHI,
Assistant Professor in Commerce Directorate of Distance Education Alagappa University, Karaikudi. Pin Code - 630 003. Tamil Nadu State.

Abstract
In recent days India is witnessing a change in consumerism. The market is now predominantly consumer driver. The focus is shifting for product based marketing to need based marketing. Consumer is given many options to decide. Passenger car segment is no exception to this general trend. An effective market communication is imperative for reaching the target audience. So it is important that we study the consumer perceptions and behaviour of the car owners which will give us feedback on how marketing strategies can be worked. Namakkal town in Tamil Nadu State, which is in the southern part of India, has a progressive and growing market for cars. This down was selected for this study. Pre-testing was done by an Interview schedule which was developed and administered to a convenient sample of twenty five car owners. A Simple Random sampling technique was adopted in the study to select the sample respondents. As the size of the universe is restricted, the study has been conducted on the respondents who are the owners of all the segments of passenger cars. A total of 350 Interview schedules were prepared and out of this, only 327 interview schedules were filled up and collected. Data were collected through an interview schedule regarding perception of the respondents on the usage of cars. The following tools were used in testing the hypotheses and in the analysis of the data. Descriptive statistical tools such as Percentage, Mean, Median and Standard deviation have been used to describe the profiles of consumers, preferred product attributes and level of satisfaction. ANOVA, t-Test and F-Test have been used to test the significant differences between the groups of respondents in their perception and satisfaction for selected independent variables like age, sex and income. Chi-Square test has been used to test the association between the consumer demographic characteristics and preferred product attributes and satisfaction. Multiple regression analysis has been used to study the influence of income and lifestyle on overall satisfaction level of the Sri Krishna International Research & Educational Consortium http://www.skirec.com -37-

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respondents. Correlation analysis has been used to establish the relationship between ‘the factors which influenced the purchase’ and ‘the factors which favoured the level of satisfaction’. Factor analysis is employed to identify the key factors responsible for the consumers’ purchase of cars and level of satisfaction after purchase. Cluster analysis has been used to identify the consumers with similar tastes and preferences with respect to purchase of car. The study throws light on various features that the manufacturers should concentrate on to attract the prospective buyers. This study concludes that consumer behaviour plays a vital role in marketing cars and there is more scope for extensive research in this area.

Introduction
Human beings, in general, are complex creatures who often do not seem even to know their own minds. It is seldom easy, and sometimes impossible, to generalize about human behaviour. Each individual is a unique product of heredity, environment and experience. Predicting such a strange behaviour of people is a difficult and complicated task, filled with uncertainties, risks, and surprises. Accurate predictions can yield vast fortunes and inaccurate predictions can result in the loss of millions of rupees. Today, business around the world recognizes that „the consumer is the king‟. Knowing why and how people consume products helps marketers to understand how to improve existing products, what types of products are needed in the market place, or how to attract consumers to buy their products. The era of liberalization, privatization and globalization has brought changes in society and lifestyle of people. Marketers can justify their existence only when they are able to understand consumers‟ wants and satisfy them. The modern marketing concept for successful management of a firm requires marketers to consider the consumer as the focal point of their business activity. Although it is important for the firm to understand the buyer and accordingly evolve its marketing strategy, the buyer or consumer continues to be an enigma - sometimes responding the way the marketer wants and on other occasions just refusing to buy the product from the same marketer. For this reason, the buyer‟s mind has been termed as a black box, which should be opened by the seller to be a successful marketer.The study of consumer behaviour also includes an analysis of factors that influence purchase decisions and product use. Understanding how consumers make purchase decisions can help marketing managers in several ways. For example, if a manager knows through research that fuel mileage is the most important attribute for a certain target market, the manufacturer can redesign the product to meet that criterion. If the firm cannot change the design in the short run, it can use promotion in an effort to change consumers‟ decision making criteria. For example, an automobile manufacturer can advertise a car‟s maintenance-free features while downplaying fuel mileage.

Passenger Car Industry in India and profile of the study area
The Indian Automobile Industry has got a tremendous market potential. With the growth of population and change in their pattern of life style as a result of urbanization, there has been a rapid increase in demand for Indian automobiles. The purpose of this chapter is to survey the growth of Automobile Industry in India and their role in economic development and to bring out the profile of the study area. The entire discussion has been divided into three main sections. The first section traces the growth of Automobile Industry. The second section discusses origin, growth and other aspects of Passenger Car Industry. The third section gives a brief profile of the study area. Sri Krishna International Research & Educational Consortium http://www.skirec.com -38-

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The Indian Automobile Industry has flourished like never before in the recent years. This extraordinary growth that the Indian automobile industry has witnessed is a result of a major factor namely, the improvement in the living standard of the middle class and an increase in their disposable incomes. Moreover, the liberalization steps, such as, relaxation of the foreign exchange and equity regulations, reduction of tariffs on imports, and refining the banking policies initiated by the Government of India, have played an equally important role in bringing the Indian Automobile Industry to great heights. The increased demand for Indian automobiles has resulted in a large number of multinational auto companies, especially from Japan, the U.S.A., and Europe, entering the Indian market and working in collaboration with the Indian firms. Also, the institutionalization of automobile finance has further paved the way to sustain a long term high growth for the industry. The Future Growth Drivers like higher GDP Growth, India‟s huge geographic spread – mass transport system, increasing road development, increasing disposable income with the service sector, cheaper (declining interest rates) and easier finance schemes, replacement of aging four wheelers, graduating from two wheelers to four wheelers, increasing dispensable income of rural agricultural sector, growing concept of second vehicle in urban areas. India produced about eight million two-wheelers, three million passenger cars and utility vehicles in 2009 - 2010. It ranks second in the world in the production of the twowheelers and thirteenth in the production of the passenger cars.

Statement of the Problem
Due to the emergence of globalization and liberalization there is a stiff competition among the variety of car industries which are focusing attention in capturing the Indian markets. Cars though considered as luxury once, now occupies a part of day-to-day life and has become a necessity. Namakkal, which is selected for the study, is one of the main growing markets for car manufacturers. People who were not ready to spend their money on luxuries have now changed their attitude that „yesterday‟s luxuries are today‟s necessities.‟ To be a successful marketer it is absolutely essential to read the minds and perceptions of the prospective buyers of cars. In addition to the above, the due weightage which is given by the Government for the growth of passenger car industry and the involvement of the consumers in the selection of a particular brand of car have also made the researcher to undertake a study on the passenger car industry with special reference to the perceptions, behaviour and satisfaction of owners of cars.

Review of Literature
Mandeep Kaur and Sandhu (2006) attempted to find out the important features which a customer considers while going for the purchase of a new car. The study covers the owners of passenger cars living in the major cities of the State of Punjab and the Union Territory of Chandigarh. The respondents perceive that safety and comfort are the most important features of the passenger car followed by luxuriousness. So the manufacturers must design the product giving maximum weightage to these factors. Chidambaram and Alfread (2007) postulates that there are certain factors which influence the brand preferences of the customers. Within this framework, the study reveals that customers give more importance to fuel efficiency than other factors. They believe that the brand name tells them something about product quality, utility, technology and they prefer to purchase the

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passenger cars which offer high fuel efficiency, good quality, technology, durability and reasonable price. Satya Sundaram (2008) analyzed how the competition makes the automobile manufacturer to launch at least one new model or a variant of the model every year. This survey also pointed out that diesel cars are becoming popular in India and the announcement of reductions in excise duties by the government has helped to some extent to boost the demand. Clement Sudhakar and Venkatapathy (2009) studied the influence of peer group in the purchase of car with reference to Coimbatore District. It was also found that the influence of friends is higher for the purchase of small sized and mid sized cars. Brown et al (2010) analyzed the consumers‟ attitude towards European, Japanese and the US cars. The country – of – origin plays a significant role in the consumers‟ behaviour. The brand name, lower price and distributor‟s reputation completely have a significant impact on the sale of passengers‟ car. However, the present study differs from the above, in that, the buyer behaviour in Namakkal in Tamil Nadu is sought to be analyzed here. The scope and the area of the study are unique in nature.

Objectives of the Study
The purpose of this research is to study the behaviour of consumers, their importance in the aspects of life style, perception of product attributes and level of satisfaction. Hence, the study is aimed at the following objectives. 1. To evaluate car owners‟ perception and behaviour pertaining to the purchase and use of cars. 2. To identify and analyze the factors influencing the purchase of cars. 3. To analyze the level of satisfaction among the respondents and to identify the switch over brand option, if any and 4. To make suggestions in the light of the findings of the study.

Scope of the Study
Nowadays, car has become a necessity and forms a part of life. Therefore, there is a significant scope to examine the perception and purchase behaviour of the consumers of cars. The study is restricted to Namakkal District of Tamil Nadu, which is economically the richest district famous both for lorry body building and poultry farming. Due to their increasing purchasing power, the people of this district have started to buy cars for business or personal use or the prestige and maintenance of social status. Namakkal District with a population of 14, 95,661 is a potential market for all consumer products and services. Knowledge of the buying behaviour of the different market segments helps a seller to select their target segment and evolve marketing strategies to increase the sales. Advertisers and marketers have been trying to discover why consumers buy and what they buy. This study tries to analyze the influence of perception in the consumers‟ mind and how this information can be used successfully by marketers to gain entry into the minds of the consumers. The scope of this research has a very good future.

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Methodology
Before beginning to carry out the present study, the researchers initially conducted a pilot study in order to find out the feasibility and the relevance of the study. The present study is based on the perceptions, behaviour and satisfaction of the consumers for passenger cars. Sources of the primary and the secondary data are discussed. The researchers has used Interview schedule for the purpose of collecting primary data. It took six months for the researchers to complete the process of collection in person. As the universe of the study is large, the researchers have decided to select sample respondents by adopting the Simple Random Sampling Technique. The secondary data have been collected from the companies‟ bulletins, annual reports and websites. Further, the researchers has used national and international journals in the field of management, as well as marketing, business magazines, business dailies, referred text books in marketing management as well as consumer behaviour and academic studies conducted in the related areas for the purpose of building a strong conceptual background including the review of literature for the study.

Sampling Design
This study was conducted among the car owners residing at Namakkal District, Tamil Nadu. A Simple Random sampling technique was adopted in the study to select the sample respondents. As the size of the universe is restricted, the study has been conducted on the respondents who are the owners of all the segments of passenger cars. A total of 350 Interview schedules were prepared and out of this, only 327 interview schedules were filled up and collected. A scrutiny of these schedules led to the rejection of 27 interview schedules on account of incomplete responses. Thus 300 completed interview schedules were used for the present study. Data were collected through an Interview Schedule regarding perception of the respondents on usage of cars. The collected data are analyzed through descriptive statistical tools such as Percentage, Mean, Median and Standard deviation have been used to describe the profiles of consumers, preferred product attributes and level of satisfaction. The ANOVA, t-Test and F-test have been used to test the significant differences between the groups of respondents in their perception and satisfaction for selected independent variables like age, sex and income. The Chi-Square test has been used to test the association between the consumer demographic characteristics and the preferred product attributes and satisfaction. Multiple regression analysis has been used to study the influence of income and lifestyle on the overall satisfaction level of the respondents. Correlation analysis has been used to establish the relationship between „the factors which influenced the purchase‟ and „the factors which favoured the level of satisfaction‟. Factor analysis is employed to identify the key factors responsible for the consumers‟ purchase of cars and level of satisfaction after purchase. Cluster analysis has been used to identify the consumers with similar tastes and preferences with respect to purchase of car.

Analysis and Interpretation of Data
The results of the analysis of the collected data are presented below:

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AVERAGE RATINGS FOR THE INFLUENCING FACTORS Sl. No. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. Standard Deviation Driving Comfort 3.5500 1.1247 Fuel Economy 3.3667 1.0275 Availability of Spare Parts 3.3167 1.1078 Price 3.3067 1.0816 Pick Up 3.3033 0.9562 Attractive Model 3.2867 1.2767 Road Grip 3.2733 1.0076 Brand Image 3.1733 1.2227 Internal Space 3.1033 1.1476 After Sales Service 3.0533 1.0492 Maintenance Cost 3.0333 1.0144 Status Symbol 2.9933 1.3111 Latest Technology 2.9100 1.2572 Resale Value 2.4100 1.0920 Source: Calculated from Primary Data Factors Mean Median 4.0000 3.0000 3.0000 3.0000 3.0000 3.0000 3.0000 3.0000 3.0000 3.0000 3.0000 3.0000 3.0000 2.0000 Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14

„Driving Comfort‟ indicates that most of the respondents have given their responses in the category of „Moderate influence‟ and „More influence‟. The factors of fuel economy, availability of spare parts, price, pick up, attractive model, road grip, brand image, internal space, after sales service and maintenance cost with their obtained mean values indicate that most of them have favoured for „Moderate influence‟. The obtained mean values of 2.9933, 2.9100 and 2.4100 for the factors status symbol, latest technology and resale value, which are close to the scale value of „Moderate influence‟ indicating that these factors moderately influenced the respondents in their purchase decision.

Factor Analysis – Factors influencing purchase
The general purpose of factor analysis is to find a method of summarizing the information contained in a number of original variables into a smaller set of new composite dimensions (Factors) with minimum loss of information. It usually proceeds from the correlations matrix formed out of the selected variables included in the study. The appropriateness of the factor model can also be calculated from this. Next, Factor extraction, the number of factors necessary to represent the data and the method of calculating them must be determined. At this step, how well the chosen model fits the data is also ascertained. Rotation focuses on transforming the factors to make them more interpretable and following this, scores for each factor can be computed for each case. These scores are then used for further analysis. For our study, it is interesting to study the factors which can be derived out of several variables which contribute in influencing the purchase of a car. There are 14 variables under the heading „factors influencing purchase‟. These variables were subject to correlation analysis first.

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TABLE 2
CORRELATION MATRIX
AVAILABILITY OF SPARE PARTS .097 .127 .080 .116 .044 -.100 .003 .011 .137 .228 .255 .193 .587 --INTERNAL SPACE -.168 -.015 .238 .040 .197 .245 .092 .204 .223 .313 .297 --STATUS SYMBOL FUEL ECONOMY RESALE VALUE MAINTENANCE COST BRAND IMAGE LATEST TECHNOLOGY SALES .212 .118 .275 .196 .166 .051 .095 .092 .139 .287 .321 .304 --AFTER SERVICE

ATTRACTIVE MODEL

Price Fuel Economy Driving Comfort Maintenance Cost Attractive Model Status Symbol Resale Value Latest Technology Brand Image Pick Up Road Grip Internal Space After Sales Service Availability of Spare Parts

---

.458 .260 --- .273 ---

.134 .248 .239 ---

.021 .136 .433 .222 ---

-.116 .076 .261 .081 .565 ---

.040 .199 .077 .169 .182 .313 ---

-.085 .119 .283 .165 .575 .407 .310 ---

.048 .247 .249 .184 .424 .257 .285 .524 ---

.136 .220 .361 .265 .213 .140 .159 .215 .381 ---

PICK UP

VARIABLES PRICE

.190 .258 .348 .250 .217 .098 .111 .199 .347 .674 ---

Source: Calculated from Primary Data

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ROAD GRIP

DRIVING COMFORT

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Correlation matrix for the variables from „price‟ to „availability of spare parts‟ (totally 14 items) was analyzed initially for possible inclusion in Factor Analysis.

TABLE 3
KMO AND BARTLETT'S TEST Kaiser-Meyer-Olkin Measure of Sampling Adequacy Approx. Chi-Square Bartlett's Test of Sphericity Degrees of Freedom Sig. .747 1211.497 91 **

Bartlett's test of sphericity is used to test whether the correlation matrix is an identity matrix. The test value (1211.497) and the significance level (P 55 years 31 63 103 65 38 15.48 15.00 14.60 14.74 14.34 SD 4.18 4.28 4.50 4.41 4.72 Technical Mean 12.39 13.13 13.34 13.49 13.34 SD 3.84 2.84 2.95 3.09 2.99 Cost Mean 9.87 9.67 9.78 9.55 9.71 SD 2.43 2.24 2.29 2.19 2.25 Service Mean 6.23 6.57 6.27 6.35 6.45 SD 2.29 1.88 1.79 2.01 1.93

Source: Calculated from Primary Data

TABLE 6
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ANOVA ON THE INFLUENCING FACTORS FOR DIFFERENT AGE GROUPS Sources Variation Between Groups External Within Groups Total Between Groups Technical Within Groups Total Between Groups Cost Within Groups Total Between Groups Service Within Groups Degrees of Sum of Mean F - Table of Sig. Squares Square Value Value Freedom 29.059 5791.528 5820.587 28.885 2770.245 2799.130 2.961 1517.225 1520.187 4.437 1099.493 4 295 299 4 295 299 4 295 299 4 295 299 NS - Not Significant 1.109 3.727 .298 2.402 NS .740 5.143 .144 2.402 NS 7.221 9.391 .769 2.402 NS 7.265 19.632 .370 2.402 NS

Factor

Total 1103.930 Source: Calculated from Primary Data

The Analysis of Variance test is applied to test for significant difference among the different age groups for each influencing factor separately. The results of the ANOVA are given in the above table. It is found from the results of ANOVA that influencing factors – external, technical, cost and service do not differ significantly among the respondents of the different age groups. Hence, the null hypothesis with respect to all the four influencing factors is accepted.

Educational Qualification and influencing factors
Table 7 & 8 bring out the results of the ANOVA conducted to test for significant difference if any, between the respondents of the different educational qualifications on the various influencing factors. Null Hypothesis: The average scores of the influencing factors among the respondents of the different educational qualifications do not differ significantly.

TABLE 7
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AVERAGE SCORES OF THE INFLUENCING FACTORS FOR DIFFERENT EDUCATIONAL QUALIFICATION Educational Qualification No Formal Education School Level Graduate Level Post Graduate Level Professional Qualification Influencing Factor External Technical Mean SD Mean SD 14.71 15.58 14.95 13.65 14.48 5.22 3.90 4.44 4.21 4.61 14.04 13.60 13.33 12.41 12.94 3.24 2.85 2.96 3.09 3.31

N 24 60 116 46 54

Cost Mean 8.88 9.55 9.83 9.87 9.85

SD 1.65 2.11 2.35 2.46 2.24

Service Mean SD 7.04 5.98 6.59 6.20 6.17 1.65 1.78 1.90 2.01 2.07

Source: Calculated from Primary Data

TABLE 8
ANOVA ON THE INFLUENCING FACTORS FOR DIFFERENT EDUCATIONAL QUALIFICATION Sources Variation Between Groups External Within Groups Total Between Groups Technical Within Groups Total Between Groups Cost Within Groups Total Between Groups Service Within Groups Degrees of Sum of Mean of Squares Square Freedom 105.439 5715.148 5820.587 60.234 2738.896 2799.130 22.128 1498.059 1520.187 29.292 1074.638 4 295 299 4 295 299 4 295 299 4 295 7.323 3.643 2.010 2.402 NS 5.532 5.078 1.089 2.402 NS 15.059 9.284 1.622 2.402 NS 26.360 19.373 1.361 2.402 NS F - Table Sig. Value Value

Factor

Total 1103.930 Source: Calculated from Primary Data

299 NS - Not Significant

From this ANOVA table, it is observed that the F ratios calculated are 1.361, 1.622, 1.089 and 2.010 for all the influencing factors which are less than the table value 2.402 and so it Sri Krishna International Research & Educational Consortium http://www.skirec.com -47-

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is not significant. Hence, the hypothesis formulated is accepted and it is inferred that there is no significant difference among the different educational qualification of the respondents on the influencing factors.

Occupational status and influencing factors
Table 9 & 10 analyze for the existence of any significant difference between the various occupational status and the influencing factors. Null Hypothesis: The average scores of influencing factors among the respondents of the different occupational status do not differ significantly.

TABLE 9
AVERAGE SCORES OF THE INFLUENCING FACTORS FOR DIFFERENT OCCUPATIONAL STATUS Occupational Status Agriculture Business Employed in Government Service Employed in Private Organization Professional House Wife Others Influencing Factor External Technical Mean SD Mean SD 15.92 4.09 11.85 2.27 14.91 4.55 13.57 3.09 14.00 15.34 4.92 3.74 12.29 13.13 2.90 3.08

N 13 159 34 47 24 16 7

Cost Mean 9.62 9.40 9.91 10.38

SD 1.56 2.07 2.73 2.63 2.41 1.52 1.73

Service Mean SD 6.54 1.33 6.42 1.89 6.53 6.02 5.88 6.69 7.43 1.83 2.12 1.96 2.12 1.99

13.63 4.53 12.75 3.26 9.63 14.44 4.27 13.75 2.38 10.81 14.14 3.44 13.86 3.98 9.00 Source: Calculated from Primary Data

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TABLE 10
ANOVA ON THE INFLUENCING FACTORS FOR DIFFERENT OCCUPATIONAL STATUS Degrees Sum of Mean F of Squares Square Value Freedom Between Groups 91.923 6 15.321 External Within Groups 5728.663 293 19.552 .784 Total 5820.587 299 Between Groups 85.731 6 14.289 Technical Within Groups 2713.399 293 9.261 1.543 Total 2799.130 299 Between Groups 60.967 6 10.161 Cost Within Groups 1459.220 293 4.980 2.040 Total 1520.187 299 Between Groups 22.706 6 3.784 Service Within Groups 1081.224 293 3.690 1.026 Total 1103.930 299 Source: Calculated from Primary Data NS - Not Significant Factor Sources of Variation Table Sig. Value

2.140

NS

2.140

NS

2.140

NS

2.140

NS

The above table highlights the results of the ANOVA for different occupational status of respondents on the influencing factors. The calculated F values of 0.784, 1.543, 2.040 and 1.026 for the External, Technical, Cost and Service factors are insignificant. Therefore, the stated hypothesis has been proved.

FAMILY INCOME AND INFLUENCING FACTORS
The ANOVA table 11 & 12 given below the mean table tests for any significant difference between the different family income of the respondents and the influencing factors. Null Hypothesis: The average scores of influencing factors among the respondents of the different family income do not differ significantly.

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TABLE 11
AVERAGE SCORES OF THE INFLUENCING FACTORS FOR DIFFERENT INCOME GROUPS Monthly family Income < Rs.10000 Rs.10000Rs.15000 Rs.15001Rs.20000 Rs.20001Rs.25000 > Rs.25000 Influencing Factor External Technical Mean SD Mean SD 14.43 4.55 12.95 2.60 13.67 4.27 12.53 3.24 14.87 15.11 4.36 4.86 12.80 13.48 3.31 2.95

N 21 55 60 63 101

Cost Mean 9.71 9.64 9.95 9.54

SD 2.61 2.61 2.42 2.07 2.00

Service Mean SD 6.10 1.76 6.05 2.08 6.53 6.43 6.47 1.75 1.97 1.95

15.18 4.18 13.77 2.90 9.70 Source: Calculated from Primary Data

TABLE 12
ANOVA ON THE INFLUENCING FACTORS FOR DIFFERENT INCOME GROUPS Sources of Degrees of Mean FTable Factor Sum of Squares Sig. Variation Freedom Square Value Value
Between Groups Within Groups Total Between Groups Within Groups Total Between Groups Within Groups Total Between Groups Within Groups Total 93.387 5727.200 5820.587 73.392 2725.738 2799.130 5.584 1514.603 1520.187 9.793 1094.137 1103.930 4 295 299 4 295 299 4 295 299 4 295 299 2.448 3.709 .660 2.402 NS 1.396 5.134 .272 2.402 NS 18.348 9.240 1.986 2.402 NS 23.347 19.414 1.203 2.402 NS

External

Technical

Cost

Service

Source: Calculated from Primary Data

NS - Not Significant

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From the above table, it is observed that the obtained F values for the influencing factors are 1.203, 1.986, 0.272 and 0.660. These values are less than the table value of 2.402. Hence, they are insignificant and so the above stated null hypothesis has been accepted.

FAMILY SIZE AND INFLUENCING FACTORS
Table 13 & 14 describe the results of ANOVA for significant difference between the various family sizes of the respondents on their influencing factors. Null Hypothesis: The average scores of influencing factors among respondents of different family sizes do not differ significantly.

TABLE 13
AVERAGE SCORES OF THE INFLUENCING FACTORS FOR DIFFERENT FAMILY SIZE Size of Family the Influencing Factor External Technical Cost N Mean SD Mean SD Mean 72 15.43 4.67 13.43 3.02 9.90 190 14.26 4.23 13.06 2.97 9.72 38 16.11 4.46 13.71 3.54 9.29 Source: Calculated from Primary Data

1 – 3 members 4 – 6 members Above 6 members

SD 2.26 2.29 2.05

Service Mean 6.11 6.48 6.32

SD 2.09 1.90 1.68

TABLE 14
ANOVA ON THE INFLUENCING FACTORS FOR DIFFERENT FAMILY SIZE Sources Variation Between Groups External Within Groups Total Between Groups Technical Within Groups Total Cost Between Groups Within Groups Degrees of Sum of Mean F - Table of Sig. Squares Square Value Value Freedom 148.992 5671.595 5820.587 17.298 2781.832 2799.130 9.399 1510.788 2 297 299 2 297 299 2 297 4.699 5.087 .924 3.026 NS 8.649 9.366 .923 3.026 NS 74.496 19.096 3.901 3.026 *

Factor

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Total

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1520.187 7.193 1096.737

299 2 297 299 NS - Not Significant 3.596 3.693 .974 3.026 NS

Between Groups Service Within Groups

Total 1103.930 Source: Calculated from Primary Data (* Denotes 5% level of significance)

The above table represents the ANOVA for significant difference between the various family sizes of the respondents with respect to the influencing factors. From the analysis it is found that the F value of 3.901 with respect to the external factor differs significantly at 5% level of significance. Therefore the null hypothesis is rejected. Hence it is concluded that there is significant difference between the various family sizes and the influencing external factor. The F values of the other three influencing factors Technical, Cost and Service of 0.923, 0.924 and 0.974 respectively have no significant difference. Hence the hypothesis with respect to these three factors is accepted.

Life style Dimensions and influencing factors
The ANOVA tables 15 & 16 analyze for significant difference if any between respondents of different life style dimensions on various influencing factors. The following hypothesis is framed for this purpose: Null Hypothesis: There is no significant difference among the groups of the respondents of the different life style dimensions in the average level of influence exhibited by the factors - external, technical, cost and service.

TABLE 15
AVERAGE SCORES OF THE INFLUENCING FACTORS FOR DIFFERENT LIFE STYLE DIMENSIONS Life Style N Dimensions Compact Drivers Travel Lovers Reserved Affluent Luxury Relishes Influencing Factor External Technical Cost Mean SD Mean SD Mean 110 14.71 4.29 13.29 2.93 9.53 42 14.12 4.35 12.83 2.97 9.93 69 15.30 4.42 13.14 2.91 9.67 79 14.75 4.63 13.43 3.43 9.87 Source: Calculated from Primary Data

SD 2.23 2.47 2.17 2.27

Service Mean 6.34 6.24 6.43 6.43

SD 1.97 1.85 1.94 1.89

TABLE 16
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ANOVA ON THE INFLUENCING FACTORS FOR DIFFERENT LIFE STYLE DIMENSIONS Degrees of Sum of of Squares Freedom Between Groups 37.946 3 External Within Groups 5782.641 296 Total Groups 5820.587 299 Between Groups 10.688 3 Technical Within Groups 2788.442 296 Total Groups 2799.130 299 Between Groups 7.915 3 Cost Within Groups 1512.271 296 Total Groups 1520.187 299 Between Groups 1.433 3 Service Within Groups 1102.497 296 Total Groups 1103.930 299 Source: Calculated from Primary Data FACTORS Sources Variation Mean F - Table Square Value Value 12.649 19.536 3.563 9.420 2.638 5.109 0.478 3.725 0.647 2.635

Sig.

NS

0.378

2.635

NS

0.516

2.635

NS

0.128

2.635

NS

NS - Not Significant

The Analysis of Variance test is applied to test for the significant difference among the life style dimensions for each influencing factor separately. The results of the ANOVA are given in the above table. It is found from the results of the ANOVA that influencing factors - external, technical, cost and service do not differ significantly among the respondents of the different life style dimensions. Hence, the hypothesis with respect to all the four influencing factors is accepted.

Brand of car and influencing factors
Tables 17 & 18 bring out the ANOVA results for significant difference between the various brands of cars possessed by the respondents and the factors which influenced the purchase of those brands among the respondents. Null Hypothesis: There is no significant difference between the different brands of cars owned by the respondents and the factors which influenced the purchase of that specific brand of car.

TABLE 17
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AVERAGE SCORES OF THE INFLUENCING FACTORS FOR DIFFERENT BRAND OF CAR Influencing Factor Brand of Car N External Technical Cost Service Mean SD Mean SD Mean SD Mean SD Hyundai 42 16.02 4.21 13.50 3.12 9.71 1.95 6.48 1.94 Maruti Udyog 108 13.11 3.96 12.71 2.98 10.42 2.53 6.71 2.26 Fiat 22 14.36 4.62 12.36 2.92 9.86 2.27 5.82 1.47 Tata 49 16.31 3.90 13.78 2.84 9.08 2.02 6.35 1.68 Hindustan 44 15.30 4.58 13.18 3.13 9.18 1.83 5.93 1.59 Motors Others 35 15.86 4.84 14.34 3.24 8.94 1.92 6.11 1.57 Source: Calculated from Primary Data

TABLE 18
ANOVA ON THE INFLUENCING FACTORS FOR DIFFERENT BRAND OF CAR Degrees Satisfaction Sources of Mean F - Table SS of Sig. Factor Variation Square Value Value Freedom Between 536.000 5 107.200 Groups 5284.587 294 17.975 Within 5820.587 299 External 5.964 3.080 ** Groups Total Groups Between 106.475 5 Groups 2692.655 294 Within 2799.130 299 21.295 Technical 2.325 2.245 * Groups 9.159 Total Groups Between 106.670 5 Groups 1413.517 294 Within 1520.187 299 21.334 Cost 4.437 3.080 ** Groups 4.808 Total Groups Between 30.639 5 Groups 1073.291 294 Within 1103.930 299 6.128 Service 1.679 2.245 NS Groups 3.651 Total Groups Source: Calculated from Primary Data NS - Not Significant (* Denotes 5% level of significance) (** Denotes 1% level of significance) Sri Krishna International Research & Educational Consortium http://www.skirec.com -54-

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The above table outlines the brand of car possessed by the respondents namely Hyundai, Maruti Udyog, Fiat, Tata, Hindustan Motors and other including brands of General Motors, Skoda, Ford, Honda and Daewoo Motors. From the above table, it is clearly known that the calculated value of the influencing factor „Service‟ of 1.679 is less than the table value of 2.245 at 5% level of significance. Therefore, the above formulated null hypothesis is accepted with respect to service only. It is inferred that there is no significant difference between the brand of car and the influencing factors with respect to Service. It is seen that the „F‟ values of 5.964 and 4.437 for the Influencing factors External and Cost are much higher than the table values. Therefore, the proposed null hypothesis is rejected at 1% level of significance and it is concluded that there is a highly significant difference between the brand of cars with respect to External feature of the car and the cost of car among the respondents. It is also observed that the „F‟ value of 2.325 for the influencing factor „Technical‟ is higher than the table value of 2.245. Hence the above stated null hypothesis is rejected at 5% level of significance and it is concluded that there is significant difference between the brand of car and the influence of Technical features of car on the purchase of a particular brand. * The analysis of influencing factor „External‟ highlights the respondents of Tata Brand with the highest mean value of 16.31. They think that Tata Brand is a successful one in effectively influencing the respondents on the purchase with respect to External features of car. The car owners of Maruti with least mean value of 13.11 feel that external features is less successful than the other brands in creating interest in purchasing Maruti Brand. * The analysis of influencing factor „Technical‟ indicates the respondents of various brands of General Motors, Skoda, Honda and Daewoo with the highest mean value of 14.34. They feel that the above brands are successful in influencing the respondents on their purchase with respect to the technical features of car. The Fiat car owners with the least mean value of 12.36 perceive that the technical features are not successful in creating interest in the purchase with respect to Fiat owners. * The analysis of influencing factor „Cost‟ represents the respondents of Maruti Brand with the highest mean value of 10.42. They judge that Maruti brand is much successful in effectively influencing the respondents on the purchase of car based on Cost. It is also highlighted that the owners of other brands like General Motors, Skoda, Honda and Daewoo with least mean value of 8.94 think that „Cost” is not successful in creating interest in the purchase of these brands. * The analysis of Influencing factor „Service‟ discloses the respondents of Maruti Brands with the highest mean value of 6.71. They perceive that Maruti brand is very much successful in effectively influencing the respondents on purchase with respect to the services available in the usage of cars. The car owners of Fiat with least mean value of 5.82 judge that Service factor is not encouraging the respondents in the purchase of Fiat brand.

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To ensure that a product finds a place in the minds of consumers, the manufacturers should position their products through sales promotional activities such as advertisement through the media. Indian youth / consumers are very strongly influenced by testimonials of sports personalities, film stars and celebrities. For positioning the consumer durables like cars, the manufacturers can utilize the endorsement of these celebrities. Majority of the respondents reported that they formed their expectations through the statement made by friends and relatives and therefore it would be beneficial if the extent of influence of such groups is studied. It may be found through closely studying the social interactions of the consumers. Experts believe the main driver of the Indian car market is the availability of car finance on easy installments and reasonable interest rates. Most of the respondents also reported that due to the easy availability of finance they buy cars. So the car dealers should have tie-up arrangements with the authorized financial institutions to boost sales. The demand for small car segment is increasing because of the growing number of nuclear families as well as parking problems. Hence the manufacturers should find out the needs, wants, tastes and preferences of the consumers in order to design the products. The respondents perceive that driving comfort and fuel economy are the most important features of the passenger car followed by availability of spare parts and price of the car, thus the manufacturers should design the product giving maximum weightage to these factors. A large component of a passenger car‟s cost is taxes such as excise duties, central and state sales taxes which push up the ex-factory price of a car by around 50%. The governments, both the central and the state should come forward to reduce these tax levels to enhance the demand for cars in the country. The study reveals that the middle class population has risen to 13 per cent of the total population. Hence the brand image and brand loyalty could be boosted by selling quality cars at a reasonable price to suit the needs of the middle income group. India is witnessing significant changes in the economic and social status of women. Many women are now becoming educated and they pose challenge in employment, once reserved for men. According to the observations made, it is stated by most of the female respondents that the automobile manufacturers should study the behaviour of women and should produce a car exclusively for women as the two wheeler manufacturers are doing. Car owners feel that the hospitality shown by the dealers is more during their visits to the places of dealers before and immediately after the purchase. But after some time they face a problem with their dealers regarding after sales service. Therefore, it is suggested that the services rendered or to be rendered should be properly explained, friendly approach and reliability in service are to be further improved. Sri Krishna International Research & Educational Consortium http://www.skirec.com -56-

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Most of the respondents expressed that they have technical problems in their existing car and some of them opined that they switch over to another brand because they would like to buy a new technology car. Hence the government should announce a National Award for the automobile companies which adopt the Research and Development measures so that Indian cars can really become world class quality.

Conclusion
Consumer Behaviour consists of all human behaviour that goes in making purchase decisions. An understanding of the consumer behaviour enables a marketer to take marketing decisions which are compatible with its consumer needs. There are four major classes of consumer behaviour determinants and expectations, namely, cultural, socioeconomic, personal and psychological. The socio-economic determinants of consumer behaviour consist of age, marital status, occupation, education, income, family size etc. Realizing the importance of passenger car industry in the present economic situation, the researcher has analyzed the perceptions, and behaviour of consumers related to this product. It is rightly said; yesterday‟s luxuries are today‟s necessities. Hence in this digital world, car is no longer a luxury. From the discussions made in the previous chapters, there are certain product attributes which are identified in the study as influencing the purchase decision and satisfying the consumers. The growth in the population of India and the increasing number of middle class consumers has attracted the attention of car manufacturers and marketers. The manufacturers and marketers who study the behaviour of consumers and cater to their needs will be successful. It may be concluded that consumer behaviour has a greater role to play in the LPG era of economic activities for which a necessary survey and research should be conducted in an efficient manner.

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Bennett, Rebekah, Rundle – Thiele, Sharyn, „Customer Satisfaction should not be the only goal‟, Journal of Services Marketing, Vol.18 (6&7), 2004, p.13. Bhargava S. C. „Passenger Car Industry: Maruti Maintains the Lead‟, Facts for You, April 2000, p.32. Bhasin T.M.„Channelising Retail Credit‟, Indian Banks’ Association (Monthly Journal), Vol. XXVII, No.8, August 2005, p.28. Bruner, Gordon C., “The Effect of Problem Recognition Style an Information Seeking”, Journal of the Academy of Marketing Science, Vol.15, Winter, 1987, p.67. Chidambaram and Alfread „A Study on Brand Preference of Passenger Car with Reference to Coimbatore City‟, Indian Journal of Marketing, Vol.34, No.9, September 2007, p.30. Churchill, Gilbert A., and Carol Suprenant, „An Investigation into the Determinants of Customer Satisfaction‟, Journal of Marketing Research, 14th November 1982, p.54. Clement Sudhakar J., and Venkatapathy R., „A Study on Automobile Purchase – Peer Influence in Decision Making‟, Indian Journal of Marketing, Vol.35, No.6, June 2009, p.16. Dornoff, R. J, Tanbersley, C. B and White, G. P (2008), “Consumers‟ Perceptions on Cars: A Market Segment Analysis”, Akron Business and Economic Review,3 (Summer), pp.26 – 29. Furse, David H, Girish N. Punj and David W.Stewart, “A Typology of Individual search strategies among purchasers of New Automobiles”, Journal of Consumer Research, Vol.10, March 1984, p.43. Gaedebe, R (2007), “Consumer Attitude towards Cars Made in Developing Countries”, Journal of Retailing, 49 (summer), pp. 13 – 24. George Homans, „Social Behaviour: Its Elementary Forms‟, Harcourt, Brace and World, New York, 1961, and Michael J. Ryan and E.H. Bonfield, „The Fishbein Extended Model and Consumer Behaviour‟, Journal of Consumer Research, Vol.2, 1975, p.28. Glenn B. Voss, Parasuraman A., and Dhruv Grewal, „The Roles of Price, Performance, and Expectations in Determining Satisfaction in Service Exchanges‟, Journal of Marketing, Vol. 62, No.4, October 1998, p.87.

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Guiles,M. G (2008), “Fuel Economy takes a hack seat as cars get faster and more Fun”, Wall Street Journal, October, p.33. Jacqueline J.Brown, C. Dvid Light and Gregory M. Gazda (2007),“Attitude towards European, Japanese and US cars”, European Journal of Marketing, 21 (5), pp.91 – 100. Joseph W. Newman, Richard Stalin, „Pre-purchase Information seeking for New Cars and Major Household Appliances‟, Journal of Marketing Research, Vol. IX, August 1972, p.20. Joseph W. Newman, Richard Werbel, „Automobile Brand Loyalty‟, Journal of the Academy of Marketing Science, Vol. 2 (4), (Fall), 1974, p.19. Lawrence A. Crosby, „Customer Loyalty has to be Earned and Not Bought‟, Pitch, Vol.11, Issue 11, August 15th – September 15th 2005, p.41. Madikonda Kishore Babu and Raghunatha Reddy, D., „A Study on Passenger Car Industry in India‟, Indian Journal of Marketing, Vol. 34, No.10, October 2004, p.30. Mandeep Kaur and Sandhu, H.S., „A Study on Factors Influencing Buying Behaviour of Passenger Car Market‟, Paradigm, Vol. 8, No.2, July – December 2006, p.69. Michael S. Garver, Gary B. Gagnon, „Seven Keys to Improving Customer Satisfaction Programmes‟, Business Horizons, Vol.45, No.5, September - October 2002, p.40. Nakanishi, M. and James R. Bettman, “Attitude Models Revised: An Individual Level Analysis”, Journal of Consumer Research, Vol.1, December 1974, p.52. Oliver, Richard, L., and Winer, R. S, „A Framework for the Formation and Structure of Consumer Expectations: Review and Propositions‟, Journal of Economic Psychology, 23(8), 1987, p.20. Peterson,Robert A.,Sridhar Balasubaramanian and Bart J. Bronnernberg,“Exploring the implications of internet for Consumer Marketing”, Journal of the Academy of Marketing Sciences, Vol.25, 1997, p.49. Punj, Girish N. and Richard Staelin, “A Model of Consumer Information Search behavior for New Automobiles”, Journal of Consumer Research, Vol.9, March 1983, p.51. Rama Prasad, M.V., „Passenger Cars: Surplus Production Will Lead to Higher Exports – Part I‟, Motorindia, Vol.48, No.6, January 2004, p.40. Sri Krishna International Research & Educational Consortium http://www.skirec.com -59-

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Spreng, Richard, A., Scott B. Mackenzie, and Richard W. Olshavsky, „A Reexamination of the Determinants of Consumer Satisfaction‟, Journal of Marketing, Vol.60, July 1996, p.12. Traylor, Mark and B.Benoy Joseph, “Measuring Consumer Involvement in products; Developing a General Scale”, Psychology and Marketing, Vol.1, (summer) 1984, p.16. Vikas Mehra, „Analysis of Consumer‟s Purchase Behaviour in Indian Mid-sized Car Segment‟, Apeejay Business Review, Vol.5, No.1, January – June 2004, p.19.

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