“A STUDY ON BRAND PREFERENCE FOR BAJAJ TWO WHEELER’S

AMONG CUSTOMERS IN VELLORE”

PROJECT REPORT

Submitted to

DRAVIDIAN UNIVERSITY

In the partial fulfillment for the award of

MASTER DEGREE IN BUSINESS ADMINISTRATION

Submitted by

MR. MATHAN RAJ P.K.

REG NO: 22205409010

Under the guidance of

MRS. P. RAJESWARI M.B.A. M.Phil.

OSCAR MANAGEMENT COLLEGE

#A-2, Near Collectorate,Sathuvachari, Vellore – 9.

2009-2011

OSCAR MANAGEMENT COLLEGE

(Approved by DRAVIDIAN UNIVERSITY)

#A-2, Near Collectorate,Sathuvachari, Vellore – 9

BONAFIDE CERTIFICATE

This is to certify that this project entitled “A STUDY ON BRAND

PRFERENCE FOR BAJAJ TWO WHEELER’S AMONG CUSTOMERS

IN VELLORE” submitted by MR.MATHAN RAJ.P.K (Reg No:

22205409010) in partial fulfillment of the requirement for the award of Master

of Business Administration from DRAVIDIAN UNIVERSITY, is the original

work of the candidate and has not been submitted for awarding any degree of

either this university or any other university either in full or in part.

Signature of the Guide

(RAJESWARI.P)

OSCAR MANAGEMENT COLLEGE

(Approved by DRAVIDIAN UNIVERSITY)

#A-2, Near Collectorate,Sathuvachari, Vellore – 9

EXTERNAL CERTIFICATE

This is to certify that this project entitled “A STUDY ON BRAND

PRFERENCE FOR BAJAJ TWO WHEELER’S AMONG CUSTOMERS

IN VELLORE” submitted by MR.MATHAN RAJ.P.K (Reg No:

22205409010) for viva voce Examination held on ______________ in partial

fulfillment of the requirement for the award of Master of Business

Administration from DRAVIDIAN UNIVERSITY.

External Examiner Internal Examiner

Principal

OSCAR MANAGEMENT COLLEGE

(Approved by DRAVIDIAN UNIVERSITY)

#A-2, Near Collectorate,Sathuvachari, Vellore – 9

DECLARATION

I, Mathan Raj.P.K. hereby declare that the project entitled “A STUDY ON

BRAND PRFERENCE FOR BAJAJ TWO WHEELER’S AMONG

CUSTOMERS IN VELLORE” submitted to DRAVIDIAN UNIVERSITY in

partial fulfillment of the degree in Master of Business Administration is a record

of original work done by me. This project work has not previously formed the

basis for the award of any degree, diploma, associateship, fellowship or other

similar title.

Place: (MATHAN RAJ.P.K.)

Date: Reg No: 22205409010

ACKNOWLEDGMENT

First and foremost, I thank GOD for the blessings and guidance at all stages in the

completion of this project.

I take this opportunity to express my deep sense of gratitude to

Mr. JAI CHANDRAN, Founder Chairman, of our college for his good wishes for this

project. I express my immense gratitude to my Principal Mr. P. PETER for his support and

encouragement for the completion of my project.

I extend the immense gratitude to the Project Guide Mrs. P. RAJESWARI who

provided her guidance and inspiration in doing this project and without her guidance,

motivation and support, this project will not be possible. I take immense pleasure in

conveying my thanks and deep sense of gratitude to my faculty and my mentor

Mrs. IDA SELVARANI, for her exhilarating supervision, timely suggestions, motivation

and encouragement during all phases of this project work.

I also thankful to all other faculty members of the department for the constant

co-operations and encouragement in pursuing my project work.

I also very much thankful to Mr. SARAVANAN, Sales Manager of Shree Lakshmi

Motors, Mr. RAVI, General Manager of Shree Lakshmi Motors and Mr. S. RAJA GURU,

General Manager of Aakash Motors, who has provided me with the customer database and

lots of information which is helpful for the project.

I specially thank Dr. R. RAVANAN, Associate Professor of Statistics, Presidency

College, Chennai for his teaching and guidance in the SPSS Package and in different

Statistical tools. Without his guidance it is not easy to complete the data analysis part.

I would like to thank all my friends for their constant encouragement, support and

help to make this project a success. I specifically thank to my friends, Mr. R. SARAN RAJ

and Mr. S. SIVAPRAKASAM who helped me a lot in the data collection process and

Mr. JAISON SAMUEL who helped me in the initial analysis process of this project.

Finally, I would like to convey my gratitude to my loveable parents & relatives

whose prayers and blessings were always there with me.

TABLE OF CONTENTS

CHAPTER NO TITLE PAGE NO

1 INTRODUCTION

1.1 Introduction 1

1.2 Statement of the Problem 3

1.3 Need for the Study 3

1.4 Objectives of the Study 4

1.5 Scope of the Study 4

1.6 Limitations of the Study 4

1.7 Company Profile 5

2 RESEARCH METHODOLOGY

2.1 Field of the Study 9

2.2 Research Design 9

2.3 Sample Design 11

2.4 Source of Data 12

2.5 Tool of Data Collection 12

2.6 Data Analysis 13

3 REVIEW OF LITERATURE

3.1 Theoretical Framework 21

3.2 Research Studies 34

4 DATA ANALYSIS AND INTERPRETATION 43-87

5 FINDINGS, SUGGESTIONS AND CONCLUSION

5.1 Findings 88

5.2 Suggestions 91

5.3 Conclusion 92

AnnexureQuestionnaire 93

Bibliography 96

LIST OF TABLES

TABLE NO TABLE NAME PAGE NO

1.1 Key People of Shree Lakshmi Motors 8

1.2 Key People of Aakash Motors 8

2.1 Address of Dealers 9

3.1 Black Box Model 26

4.1 Details of Age Group 43

4.2 Details of Educational Qualification 45

4.3 Occupation Information about the Respondents 47

4.4 Details of Monthly Income 49

4.5 Need for buying the bike 51

4.6 Frequency table for factors affecting the Purchasing Decision 53

4.7 Friedman Test 54

4.8 Personal Source of Information 55

4.9 Commercial Source of Information 57

4.10 Experimental Source of Information 59

4.11 Medium of Communication that influences the Brand Preference 61

4.12 Mode of Purchase 63

4.13 Role in Decision Making 64

4.14 Period took to choose the Bajaj Brand 65

4.15 Frequency table showing the reason for Brand preference 67

4.16 Percentage of Product Features 69

4.17 ANOVA – Total Features 70

4.18 Descriptive Statistics 70

4.19 Percentage of Showroom Attributes 71

4.20 ANOVA – Total Showroom Attributes 72

4.21 Descriptive Statistics 72

4.22 Role of availability in the selection of brand 73

4.23 Trust Level on the Bajaj Brand 74

4.24Reaction of customer when Bajaj Brand is not available during

the purchase75

4.25 Percentage of Satisfaction on the given attributes 76

4.26 Correlation between Level of Satisfaction of Safety and Comfort 77

4.27 ANOVA – Total Price 78

4.28 Descriptive Statistics 78

4.29 Rating of Overall Service Experience 79

4.30 Overall Satisfaction level with regards to the Bajaj bike 80

4.31 Correlation between Overall Satisfaction and Service Experience 81

4.32 Future Purchase Decision 82

4.33 Level of Promoting the Bajaj Brand 83

4.34 One Sample T-Test for the Level of Promotion at 1% level 84

4.35 Level of Recommendation of dealer to others 85

4.36Crosstabs between Educational Qualification and Brand

Preference Level86

4.37 T-Test for difference of two mean 87

LIST OF FIGURES

FIGURE NO FIGURE NAME PAGE NO

1.1 Organizational Structure of Shree Lakshmi Motors 7

1.2 Organizational Structure of Aakash Motors 8

3.1 Project Study Analysis Process 24

3.2 Buying Decision Process 30

3.3 Steps between Purchase Intention & Purchase Decision 32

4.1 Percentage of respondents based on Age Group 44

4.2 Percentage of respondents based on Education 46

4.3 Percentage of respondents based on Occupation 48

4.4 Percentage of respondents based on Income Level 50

4.5 Percentage of Need for buying the bike 52

4.6 Percentage of Personal Source of Information 56

4.7 Percentage of Commercial Source of Information 58

4.8 Percentage of Experimental Source of Information 60

4.9 Percentage of Influence of Communication Medium 62

4.10 Percentage of Period took to choose the Bajaj Brand 66

4.11 Percentage of Preference Reason 68

CHAPTER 1

INTRODUCTION

1.1 Introduction

Brand Preference is the measure of Brand Loyalty in which a consumer will choose a

particular brand in presence of competing brands, but will accept substitutes if that brand is

not available. Brand Loyalty refers to the extent of the faithfulness of consumers to a

particular brand, expressed through their repeat purchases, irrespective of the marketing

pressure generated by the competing brands.

In every product category, consumers have more choices, more information and higher

expectations than ever before. To move consumers from trial to preference, brands need to

deliver on their value proposition, as well as dislodge someone else from the consumer's

existing preference set.

Preference is a scale, and brands move up, down and even off that scale with and without a

vigilant brand management strategy. Pricing, promotional deals and product availability all

have tremendous impact on the position of brand in the consumer’s preference set. If all

things are equal, the best defense is to make the brand more relevant to consumers than the

competition.

The brands potential can only be fulfilled by continually reinforcing its perceived quality,

upmarket identity and relevance to the consumer. The same branding activities that drive

awareness also drive preference. And, while awareness alone will not sustain preference, it

will improve the brand’s potential for building and maintaining preference.

With a great story and a large enough investment, awareness can be attained rather quickly. It

takes time, however, and constant revaluation to build brand preference. Aristotle professed,

“We are what we repeatedly do. Excellence then is not an act, but a habit.” Attaining and

sustaining preference is an important step on the road to gaining brand loyalty. The ability to

generate more revenue, gain greater market share and beat off the competition is the reward

given by consumer toward particular brand.

Brand preference is the Selective demand for a company's brand rather than a product; the

degree to which consumers prefer one brand over another. In an attempt to build brand

preference advertising, the advertising must persuade a target audience to consider the

advantages of a brand, often by building its reputation as a long-established and trusted name

in the industry. If the advertising is successful, the target customer will choose the particular

brand over other brands in any category.

The frequency of repeat purchase in case of two wheeler market is very low. So, the measure

of Loyalty is not easy. The brand loyalty of the customer can be identified with the help of

how they promote the brand to others, i.e. Word of Mouth Communication. Even though

competitors are low in the two wheeler’s segment, competition is very high due to the

availability of different product categories under different brands.

The Customers preference among these brands also not easy as the product possesses similar

features in all the brands. So, the customer satisfaction determines the loyalty. Customer will

get satisfied only when their expectations met or exceed. It is an after purchase behavior. To

analyze the Brand Preference and Loyalty, it is necessary to study both the consumer’s

buying behavior and after purchase behavior.

1.2 Statement of the Problem

The changing customer perception because of the availability of variety of products in two

wheeler segment along with the growing number of competitors had a major impact in the

preference of a particular brand. The customers’ decision making process also changes as

their buying pattern changes.

The players in the two wheeler market in the Vellore are Bajaj, Hero Honda, TVS, Yamaha,

Suzuki, Mahindra, BSA, Ultra Motors and Royal Enfield. Each and every company has

different varieties of product category in the two wheelers, which gives lot of options for the

customers in Vellore. The fast developing technology and the growing economic status of the

people in the Vellore city drive their preference decision.

Bajaj held the most of the market share in the two wheeler segment in Vellore after the

launch of CT 100 model which gave good mileage and Pulsar which attracted most of the

young customers. Later after the launch of TVS Apache, Yamaha FZ, the preference of brand

among customers varied a lot with the availability of various options. So, this study was

undertaken to analyze the above mentioned issues.

1.3 Need for the Study

1. The first and foremost need for this study is due to the increasing brand variety in the

Vellore two wheeler’s market which is eroding the Brand Loyalty of the customers.

2. The increasing media clutter and the changing consumer preferences.

3. The more number of split loyal and shifting loyal customers are available in the

market.

4. Brand Loyalty of a customer is influenced by the customer’s perceived value which is

the basic belief results in the action. So, to analyze the preference of brand and to find

the factors influencing the Brand Preference of the customer in the two-wheeler

segment.

1.4 Objectives of the Study

1. To study the perception and buying behavior of customers in two wheelers.

2. To measure the Brand Loyalty of Bajaj.

3. To study the customers view on features of two wheeler’s and the impact of the

communication medium.

4. To study the factors that influence decision-making in choosing the brand.

5. To suggest factors to retain the customers.

1.5 Scope of the Study

The study is only on Brand Preference so the other aspects such as Brand

Recognition, Brand Image, Brand Equity and other branding concepts are not

covered.

Brand Loyalty, Perception and Buying Behavior of respondents are also studied in

this research.

This study covered only the area of the Vellore city. So, the information and the

conclusion derived from the study are only relevant to this area alone.

1.6 Limitations of the Study

The duration of the project was one of the primary constraints for the project.

This study is confined only among the Bajaj customers in the Vellore city.

It was an academic effort and limited to cost, time and geographical area.

Numbers of respondents were restricted due to the time factor.

1.7 Company Profile

Bajaj Auto is a major Indian automobile manufacturer started by a Rajasthani merchant. It is

based in Pune, Maharashtra, with plants in Chakan (Pune), Waluj (near Aurangabad) and

Pantnagar in Uttaranchal. The oldest plant at Akurdi (Pune) now houses the R&D centre

ahead. Bajaj Auto makes and exports motor scooters, motorcycles and the auto rickshaw.

Over the last decade, the company has successfully changed its image from a scooter

manufacturer to a two wheeler manufacturer. Its product range encompasses scooterettes,

scooters and motorcycles. Its real growth in numbers has come in the last four years after

successful introduction of a few models in the motorcycle segment.

The Bajaj Group is amongst the top 10 business houses in India. Its footprint stretches over a

wide range of industries, spanning automobiles (two-wheelers and three-wheelers), home

appliances, lighting, iron and steel, insurance, travel and finance. The group comprises of 34

companies. The group's flagship company, Bajaj Auto, is ranked as the world's fourth largest

two- and three- wheeler manufacturer and the Bajaj brand is well-known across several

countries in Latin America, Africa, Middle East, South and South East Asia. Founded in

1926, at the height of India's movement for independence from the British, the group has an

illustrious history. Jamnalal Bajaj was the founder of the Bajaj group.

Bajaj Auto came into existence on November 29, 1945 as M/s Bachraj Trading Corporation

Private Limited. It started off by selling imported two- and three-wheelers in India. In 1959, it

obtained license from the Government of India to manufacture two- and three-wheelers and it

went public in 1960. In 1970, it rolled out its 100,000th vehicle. In 1977, it managed to

produce and sell 100,000 vehicles in a single financial year. In 1985, it started producing at

Waluj near Aurangabad. In 1986, it managed to produce and sell 500,000 vehicles in a single

financial year. In 1995, it rolled out its ten millionth vehicles and produced and sold 1 million

vehicles in a year.

According to the authors of Globality: Competing with Everyone from Everywhere for

Everything, Bajaj has grown operations in 50 countries by creating a line of value-for-money

bikes targeted to the different preferences of entry-level buyers.

His son, Kamalnayan Bajaj, then 27, took over the reign of business in 1942. Kamalnayan

Bajaj not only consolidated the group, but also diversified into various manufacturing

activities. The present Chairman of the group, Rahul Bajaj, took charge of the business in

1965. Under his leadership, the turnover of the Bajaj Auto the flagship company has gone up

from INR.72 million to INR. 120 billion, its product portfolio has expanded and the brand has

found a global market. He is one of India’s most distinguished business leaders and

internationally respected for his business acumen and entrepreneurial spirit. The Vice

Chairman of Bajaj Auto is Madhur Bajaj.

In early March 2010, Bajaj Auto Ltd. once again demonstrated its commitment to green

technology by achieving Bharat Stage-III norm compliance for its range of products-the first

company to do so. The Bharat Stage III norms were notified by Government of India on

recommendation by Dr. R.A. Mashelkar committee for the control of pollution in the country

and are applicable across all states.

Products

Bajaj has made a number of motorcycles, scooters and cars. Motorcycles in current

production are the XCD, Platina, Discover, Pulsar and Avenger. Bajaj also produces many

motorcycles for other manufacturers, such as the Kawasaki Ninja 250R, Yamaha YZF-R15

(Unsure), and new for 2011, the KTM Duke 125, Cars include the Bajaj ULC ultra-low-cost

car.

Low Cost Cars

Bajaj Auto says its $2,500 car, which it is building with Renault and Nissan Motor, will aim

at a fuel-efficiency of 30 kilometres per litre (85 mpg-imp; 71 mpg-US) (3.3 L/100 km), or

twice an average small car, and carbon dioxide emissions of 100 g/km. The car is scheduled

to be launched in 2012. It is a Tata Nano competitor. The Bajaj venture will have an initial

capacity of 400,000 units, while Tata expects eventual demand of 1 million Nanos.

Shree Lakshmi Motors

The journey with Bajaj was started from January 2009 after purchasing the Susee Motors

Dealership. Previously the dealership in the Katpadi and the surrounding area was taken care

by Susee Motors. But, in 2009 Shree Lakshmi Motors bought the dealership with Bajaj for

that area. It was started by Mr.Ravi, Sole Proprietor for the company. They are taking care of

both the sales and service of Bajaj two wheelers in their area successfully.

This is a separate business unit for the organization which totally has 5 business units. The

other business units are unrelated to each other and covering many other sectors, and

targeting different market segment in Vellore district. The following are the five businesses

which come under this organization.

1. Ravi Electricals

2. Hotel Shree Lakshmi

3. KRR Group Real Estate

4. Ravi Auto Consultancy

5. Shree Lakshmi Motors

Totally 15 employees are working in the company, among which 5 are front office staffs and

the remaining 10 are service mechanics.

Fig 1.1: Organizational Structure of Shree Lakshmi Motors

Table 1.1 Key People of Shree Lakshmi Motors

Name Position

GM

MD

Sales Manager Service Manager

Front Office Staffs Service Mechanics

Mr. Ravi General Manager

Mr. Saravanan Managing Director

Mr. Naveen Sales Manager

Mr. Guru Service Manager

Aakash Motors

The company joined their hands with Bajaj from July 2009 covering the area of

Sainathapuram and Bagayam of Vellore District. The owner of the company Mr. S.RajaGuru

began the company with 12 workers and the business is running successfully in that particular

area. The yearly turnover of the company is around Rs. 3 crores. This dealer is taking care of

both the sales and service of Bajaj two wheelers.

Fig 1.2: Organizational Structure of Aakash Motors

Table 1.2 Key People of Aakash Motors

Name Position

Mr. S. RajaGuru General Manager

Mr. Saravanan Sales Manager

Mr. Ramkumar Service Manager

CHAPTER 2

GM

Sales Manager Service Manager

Front Office Staffs Service Mechanics

RESEARCH METHODOLOGY

2.1 Field of the Study

The study was conducted among the customers of two Bajaj dealers in Vellore. They are

Shree Lakshmi Motors in Katpadi Road and Aakash Motors in Sainathapuram.

Table 2.1 Address of Dealers

Address of Dealer 1: Address of Dealer 2:

Shree Lakshmi Motors

Chittor High Road,

Near Vijay Sales, Katpadi,

Vellore – 632 007.

Aakash Motors

No. 83, Arani Road,

Sainathapuram,

Vellore – 632 001.

2.2 Research Design

A Research design is the arrangement of conditions for collection and analysis of data in a

manner that aims to combine relevance to the research purpose with economy in procedure.

A Research design could be defined as the blue print specifying every stage of action in the

course of research. Such a design would indicate whether the course of action planned will

minimize the use of resources and maximize the outcome.

Descriptive Research Design

The Research design used in this study was Descriptive Research Design. Descriptive studies

come under formal research, where the objectives are clearly established. It is concerned with

the research studies with a focus on the portrayal of the characteristics of a group or

individual or a situation. The main objective of this type of study is to acquire knowledge.

For example, to identify the use of a product to various groups, a research study may be

undertaken to question whether the use varies with income, age, sex or any other

characteristics of population. Similarly, such studies are used to examine the characteristics

of the corporate sector or consumer behavior, etc.

Descriptive Approach

In this approach, a problem is described by the researcher using questionnaire or schedule.

This approach enables the researcher to explore new areas of investigation. A researcher

develops the hypothesis based on the knowledge about the subject matter of study. When this

approach is adopted, the researcher should be intelligent and alert to elicit the information

required from the respondents as accurately as possible.

Merits of Descriptive Approach

This approach helps to test the conclusions and findings arrived at on the basis of

laboratory studies. By using this approach, it is possible to substantiate existing

theories and conclusions or modifying them.

Direct contact between the researcher and the respondent is brought about in this

approach. This is very significant because, the researcher would be able to understand

himself clearly the problem being studied.

With the possibility of direct contact with the respondent, the researcher is able to

elicit all the relevant information and eliminate irrelevant facts.

Limitations of Descriptive Approach

Unless a researcher is experienced, there is every possibility of this approach being

misused. Hurried conclusions and generalizations may be formed based on the

inaccurate field data.

As this approach involves collection of field data, enormous time and efforts are

required to plan and execute the field survey.

This approach also involves incurring heavy cost on data collection.

Unless the respondents are cooperative, it is not possible to collect data through this

approach.

Since this approach requires considerable time for data collection, by the time the data

collection is complete and analysis are undertaken, conclusions arrived at may not

have any relevance.

2.3 Sample Design

A Sample Design is a definite plan for obtaining a sample from a give population. It refers to

the technique or the procedure the researcher would adopt in selecting items for the sample.

The sampling technique which was used in this research was Systematic Random Sampling.

It is one of the Probability Sampling techniques. Probability Sampling is the sampling

technique in which every unit of the population has given equal chance to be included in the

study. A Systematic Random Sampling is a technique which contains every ‘i’ th element of

the population. The first element is chosen randomly, the rest systematically.

Merits of Systematic Random Sampling

1. It is very convenient and simple to adopt.

2. The time and cost involved are relatively less.

3. With a large population, this method of sampling is easy to use.

4. Random selection of items is ensured, once the sampling interval is determined.

5. Sampling interval is determined scientifically depending upon the size of sample

desired.

Limitations of Systematic Random Sampling

1. It is less representative, as once the first item is selected at random, subsequent items

are all lying at uniform interval. So, the selected items may lack complete

representativeness.

2. This method requires correct understanding of the methodology as otherwise, the

sample selected will not be correct.

3. The first item selected should be strictly at random. If there is any bias in this first

stage, this will influence the items selected at subsequent stages.

Population: N = 240

Sample Size: n = 120

Sampling Interval: k = N/n

k = 240/120, therefore, k = 2

2.4 Source of Data

Primary Data

Primary data is known as the data collected for the first time through field survey. The

important source for the primary data collection is through Questionnaire and other source is

through Sales force opinion.

Secondary Data

Secondary data refers to the information or facts already collected. Such data are collected

with the objective of understanding the past status of any variable. Secondary sources include

the following.

Books

Journals

Research Thesis

Foot notes

Internet

2.5 Tool of Data Collection

The primary tool which was used for data collection was Questionnaire. It was a Structured

Questionnaire which consists of series of questions related to the objective of the study. In the

prepared questionnaire, eighteen closed-end questions with one open-ended question were

designed. The questionnaire was prepared with the help of different Scaling Techniques and

Measurement Scales.

2.6 Data Analysis

Primary data generated by the study were cleaned to ensure consistency and transcribed in

coded form (pre and post-coded) into the computer using the Statistical Package for Social

Sciences (SPSS). There are five different Statistical tools are used in this project to analyze

the data effectively. It includes the advanced statistical tools also. The Statistical tools used to

analyze are mentioned as follows.

1. T-Test for Single Mean

2. T-Test for difference of two mean

3. ANOVA – One Way ANOVA

4. Chi-Square test for independence of attributes

5. Correlation Coefficient

6. Friedman Test

In the analysis, the Ordinal Scale for the questionnaire, ‘Features of the product’, the scale

value was set as follows: 1 – 1 point, 2 – 2 points, 3 – 3points, 4 – 4 points and 5 – 5 points.

So, the highest mean value is considered while writing the inference for this questionnaire.

Other than this, for all other questionnaire which involves the rating scale, the scale value

was set least for higher rating and greater for lower rating. For example, Very High – 1, High

– 2, Average – 3, Low – 4, Very Low – 5. So, the least mean value is considered while

writing inference for the other questionnaires.

T-Test for Single Mean:

The t- test is the most powerful parametric test for calculating the significance of a small

sample mean. A one sample t-test has the following null hypothesis:

Where, the Greek letter μ (mu) represents the population mean and c represents its assumed

(hypothesized) value. In statistics it is usual to employ Greek letters for population

parameters and Roman letters for sample statistics. The t-test is the small sample analog of

the z test which is suitable for large samples. A small sample is generally regarded as one of

size n<30.

A t-test is necessary for small samples because their distributions are not normal. If the

sample is large (n>=30) then statistical theory says that the sample mean is normally

distributed and a z test for a single mean can be used. This is a result of a famous statistical

theorem, the Central limit theorem.

A t-test, however, can still be applied to larger samples and as the sample size n grows larger

and larger, the results of a t-test and z-test become closer and closer. In the limit, with infinite

degrees of freedom, the results of t and z tests become identical.

In order to perform a t-test, one first has to calculate the "degrees of freedom." This quantity

takes into account the sample size and the number of parameters that are being estimated.

Here, the population parameter, mu is being estimated by the sample statistic x-bar, the mean

of the sample data. For a t-test the degrees of freedom of the single mean is n-1. This is

because only one population parameter (the population mean) is being estimated by a sample

statistic (the sample mean).

Formula for calculating the t value:

T-Test for difference of two mean:

The Independent Samples T Test compares the mean scores of two groups on a given

variable. One of the frequently used t-test is a two sample location test of the null hypothesis

that the means of two normally distributed populations are equal. All such tests are usually

called Student's t-tests, though strictly speaking that name should only be used if the

variances of the two populations are also assumed to be equal; the form of the test used when

this assumption is dropped is sometimes called Welch's t-test. These tests are often referred to

as "unpaired" or "independent samples" t-tests, as they are typically applied when the

statistical units underlying the two samples being compared are non-overlapping.

Independent two-sample t-test for Unequal sample size and equal variance

This test is used only when it can be assumed that the two distributions have the same

variance. The t statistic to test whether the means are different can be calculated as follows:

Where,

Note that the formulae above are generalizations for the case where both samples have equal

sizes (substitute n1 and n2 for n).

is an estimator of the common standard deviation of the two samples: it is defined in

this way so that its square is an unbiased estimator of the common variance whether or not

the population means are the same. In these formulae, n = number of participants, 1 = group

one, 2 = group two. n − 1 is the number of degrees of freedom for either group, and the total

sample size minus two (that is, n1 + n2 − 2) is the total number of degrees of freedom, which

is used in significance testing.

ANOVA:

In statistics, one-way analysis of variance (abbreviated one-way ANOVA) is a technique

used to compare means of two or more samples (using the F distribution). This technique can

be used only for numerical data.

The ANOVA tests the null hypothesis that samples in two or more groups are drawn from the

same population. To do this, two estimates are made of the population variance. These

estimates rely on various assumptions. The ANOVA produces an F statistic, the ratio of the

variance calculated among the means to the variance within the samples. If the group means

are drawn from the same population, the variance between the group means should be lower

than the variance of the samples, following central limit theorem. A higher ratio therefore

implies that the samples were drawn from different populations.

The degrees of freedom for the numerator is I-1, where I is the number of groups (means).

The degrees of freedom for the denominator is N - I, where N is the total of all the sample

sizes.

Typically, however, the one-way ANOVA is used to test for differences among at least two

groups, since the two-group case can also be covered by a t-test (Gosset, 1908). When there

are only two means to compare, the t-test and the F-test are equivalent; the relation between

ANOVA and t is given by F = t2.

Grand Mean

The grand mean of a set of samples is the total of all the data values divided by the total

sample size. This requires that you have all of the sample data available to you, which is

usually the case, but not always. It turns out that all that is necessary to find perform a one-

way analysis of variance are the number of samples, the sample means, the sample variances,

and the sample sizes. Another way to find the grand mean is to find the weighted average of

the sample means. The weight applied is the sample size.

Total Variation

The total variation (not variance) is comprised the sum of the squares of the differences of

each mean with the grand mean.

There is the between group variation and the within group variation. The whole idea behind

the analysis of variance is to compare the ratio of between group variance to within group

variance. If the variance caused by the interaction between the samples is much larger when

compared to the variance that appears within each group, then it is because the means aren't

the same.

Between Group Variation

The variation due to the interaction between the samples is denoted SS(B) for Sum of

Squares Between groups. If the sample means are close to each other (and therefore the

Grand Mean) this will be small. There are k samples involved with one data value for each

sample (the sample mean), so there are k-1 degrees of freedom.

The variance due to the interaction between the samples is denoted MS(B) for Mean Square

Between groups. This is the between group variation divided by its degrees of freedom. It is

also denoted by .

Within Group Variation

The variation due to differences within individual samples, denoted SS(W) for Sum of

Squares Within groups. Each sample is considered independently, no interaction between

samples is involved. The degrees of freedom is equal to the sum of the individual degrees of

freedom for each sample. Since each sample has degrees of freedom equal to one less than

their sample sizes, and there are k samples, the total degrees of freedom is k less than the total

sample size: df = N - k.

The variance due to the differences within individual samples is denoted MS(W) for Mean

Square Within groups. This is the within group variation divided by its degrees of freedom. It

is also denoted by . It is the weighted average of the variances (weighted with the degrees

of freedom).

F test statistic

Recall that a F variable is the ratio of two independent chi-square variables divided by their

respective degrees of freedom. Also recall that the F test statistic is the ratio of two sample

variances, well, it turns out that's exactly what we have here. The F test statistic is found by

dividing the between group variance by the within group variance. The degrees of freedom

for the numerator are the degrees of freedom for the between group (k-1) and the degrees of

freedom for the denominator are the degrees of freedom for the within group (N-k).

Chi-Square Test for Independence of Attributes:

The test is applied when you have two categorical variables from a single population. It is

used to determine whether there is a significant association between the two variables.

Suppose N observations are considered and classified according two characteristics say A and

B. We may be interested to test whether the two characteristics are independent. In such a

case, we can use Chi square test for independence of two attributes.

It has to be noted that the Chi square goodness of fit test and test for independence of

attributes depend only on the set of observed and expected frequencies and degrees of

freedom. These two tests do not need any assumption regarding distribution of the parent

population from which the samples are taken.

Since these tests do not involve any population parameters or characteristics, they are also

termed as non-parametric or distribution free tests. An additional important fact on these two

tests is they are sample size independent and can be used for any sample size as long as the

assumption on minimum expected cell frequency is met.

Degrees of freedom: The degrees of freedom (DF) is equal to: DF = (r - 1) * (c - 1)

where r is the number of levels for one categorical variable, and c is the number of

levels for the other categorical variable.

Expected frequencies: The expected frequency counts are computed separately for

each level of one categorical variable at each level of the other categorical variable.

Compute r * c expected frequencies, according to the following formula.

Er,c = (nr * nc) / n

where Er,c is the expected frequency count for level r of Variable A and level c of

Variable B, nr is the total number of sample observations at level r of Variable A, n c is

the total number of sample observations at level c of Variable B, and n is the total

sample size.

Test statistic: The test statistic is a chi-square random variable (Χ2) defined by the

following equation.

Χ2 = Σ [ (Or,c - Er,c)2 / Er,c ]

where Or,c is the observed frequency count at level r of Variable A and level c of

Variable B, and Er,c is the expected frequency count at level r of Variable A and level

c of Variable B.

P-value: The P-value is the probability of observing a sample statistic as extreme as the test

statistic. Since the test statistic is a chi-square, use the Chi-Square Distribution Calculator to

assess the probability associated with the test statistic. Use the degrees of freedom computed

above.

Correlation Coefficient:

Correlation is one of the statistical tools very widely applied as a tool of analysis in every

subject. It is a statistical measure of establishing qualitative relationship between two or more

variables. Through correlation, it is possible to indicate the direction of relationship between

variables. In research, whenever qualitative variables are used, their relationship is studied

through correlation. Correlation is measured applying different methods in statistics. They

are, Graphical method, Scatter diagram method, Karl Pearson’s coefficient of correlation and

Spearman’s Rank correlation. A very important point to note is that correlation value for any

set of values should not exceed +1 or -1.

The formula for Pearson's correlation takes on many forms. A commonly used formula is

shown below.

A simpler looking formula can be used if the numbers are converted into z scores:

where zx is the variable X converted into z scores and zy is the variable Y converted into z

scores.

Friedman Test:

The Friedman test is a non-parametric test for testing the difference between several related

samples. The Friedman test is an alternative for repeated measures analysis of variances

which is used when the same parameter has been measured under different conditions on the

same subjects.

CHAPTER 3

REVIEW OF LITERATURE

3.1 Theoretical Framework

Brand and branding defined

It is widely acknowledged amongst both practitioners and academics that branding has

become a tool of strategic importance. Various definitions of branding appear in literature.

The American Marketing Association (1994) defines a brand as a “name, term, sign, symbol

or design, or a combination of them intended to encourage prospective customers to

differentiate a producer’s product (s) from those of competitors”.

A primary function of the brand is to provide convenience and clarity in decision making by

providing a guarantee of performance and communicating a set of expectations thereby

offering certainty and facilitating the buying process. On the emotional side, the function of a

brand is to evoke a set of associations and furthermore symbolize the consumer’s persona

through brand imagery.

However, this and other definitions of a brand fail to capture the essence of what branding

involves or achieves (Marketing in a Global Economy Proceedings, 2000). In order to be

successful, images and symbols must relate to and indeed exploit the needs, values and

lifestyles of consumers in such a way that the meanings involved give added values, and

differentiate the brand from other brands (Broadbent and Cooper, 1987).

In its totality, a brand can be described as a “trademark that communicates a promise

(Phillips, 1988). This promise involves a set of symbolic and functional attributes that the

market place associates with the brand. Symbolic attributes are those that fulfill internally

generated needs for self-enhancement, role position, group membership or ego identification

(Park et al., 1996) whereas functional brand attributes solve an externally generated

consumption related problem.

Ambler and Styles (1996) describe two different views of defining a brand. The first is the

product plus view, when the brand is seen as an addition to the product, and in this view a

brand is also called an identifier. The second is the holistic view that communicates the focus

on the brand itself that is considered to be much more than just the product. The brand is said

to be the sum total of all elements of the marketing mix. Brands can also be explained based

on their elements-“those trademarkable devices that serve to identify and differentiate the

brand (ego, brand names, logos, symbols, characters, slogans, jingles and packages (Keller,

2002).

DeChernatony and MacDonald (1998) in an attempt to emphasize the increased value that

accrues to the consumer by buying the established brand rather than a generic or commodity

product, offer the following definition of a brand: “A successful brand is an identifiable

product, service, person or place, augmented in such a way that the buyer or user perceives

relevant, unique added values which match their needs most closely. Furthermore, its success

results from being able to sustain those added values in the face of competition”.

Some people distinguish the psychological aspect of a brand from the experiential aspect. The

experiential aspect consists of the sum of all points of contact with the brand and is known as

the brand experience. The psychological aspect, sometimes referred to as the brand image,

is a symbolic construct created within the minds of people and consists of all the information

and expectations associated with a product or service.

People engaged in branding seek to develop or align the expectations behind the brand

experience, creating the impression that a brand associated with a product or service has

certain qualities or characteristics that make it special or unique. A brand is therefore one of

the most valuable elements in an advertising theme, as it demonstrates what the brand owner

is able to offer in the marketplace. The art of creating and maintaining a brand is called brand

management whereas orientation of the whole organization towards its brand is called brand

orientation.

Careful brand management seeks to make the product or services relevant to the target

audience. Brands should be seen as more than the difference between the actual cost of a

product and its selling price - they represent the sum of all valuable qualities of a product to

the consumer. There are many intangibles involved in business, intangibles left wholly from

the income statement and balance sheet which determine how a business is perceived. The

learned skill of a knowledge worker, the type of mental working, the type of stitch: all may

be without an 'accounting cost' but for those who truly know the product, for it is these people

the company should wish to find and keep, the difference is incomparable. A brand which is

widely known in the marketplace acquires brand recognition. When brand recognition

builds up to a point where a brand enjoys a critical mass of positive sentiment in the

marketplace, it is said to have achieved brand franchise.

One goal in brand recognition is the identification of a brand without the name of the

company present. Consumers may look on branding as an important value added aspect of

products or services, as it often serves to denote a certain attractive quality or characteristic

(see also brand promise). From the perspective of brand owners, branded products or services

also command higher prices. Where two products resemble each other, but one of the

products has no associated branding (such as a generic, store-branded product), people may

often select the more expensive branded product on the basis of the quality of the brand or the

reputation of the brand owner.

Brand Awareness

Brand awareness refers to customers' ability to recall and recognize the brand under different

conditions and link to the brand name, logo, jingles and so on to certain associations in

memory. It helps the customers to understand to which product or service category the

particular brand belongs to and what products and services are sold under the brand name. It

also ensures that customers know which of their needs are satisfied by the brand through its

products. (Keller) 'Brand love', or love of a brand, is an emerging term encompassing the

perceived value of the brand image. Brand love levels are measured through social media

posts about a brand, or tweets of a brand on sites such as Twitter. Becoming a Facebook fan

of a particular brand is also a measurement of the level of 'brand love'.

Brand Preference

Brand Preference is the measure of Brand Loyalty in which a consumer will choose a

particular brand in presence of competing brands, but will accept substitutes if that brand is

not available. Brand Loyalty refers to the extent of the faithfulness of consumers to a

particular brand, expressed through their repeat purchases, irrespective of the marketing

pressure generated by the competing brands.

Analysis Process

Fig 3.1: Project Study Analysis Process

Brand Preference (BP)

Brand Loyalty (BL)

Repeat Purchases (RP)

Customer Satisfaction (CS)

Customer Expectation

Customer Experience the product

Purchase the product

BP is a measure of BL

BL expressed thru RP

RP is based on CS

Cust will get satisfied when CE met or exceed

After Purchase

To analyze the purchasing process, it is necessary to analyze the buying behavior

Consumer Buying Behavior

Consumer behavior as a body of knowledge emphasizes on the study of both physical

activities and decision-making processes that occur in the process of search, evaluation,

acquiring, use and disposal of products. Consumer behavior encompasses vast areas of

human activities that have direct interface with technology. Borrowing heavily from diverse

sweep and come in handy to adapt technology to everyday needs of society. Backed by

abundant wealth of information on areas such as consumers’ tastes, shopping habits, store

patronage and life style, it has become possible for many marketing research firms to come

up with reliably accurate work on many aspects of marketing including product demand

forecast, perception of brand image, brand preference, brand loyalty and brand equity

position. This approach to problems in marketing management seems to have been well

established and therefore, is the popular means adopted in the area of consumer product

whether it is physical product or services.

Consumer behavior is the study of when, why, how, and where people do or do not buy a

product. It blends elements from psychology, sociology, social anthropology and economics.

It attempts to understand the buyer decision making process, both individually and in groups.

It studies characteristics of individual consumers such as demographics and behavioral

variables in an attempt to understand people's wants. It also tries to assess influences on the

consumer from groups such as family, friends, reference groups, and society in general.

Customer behaviour study is based on consumer buying behavior, with the customer playing

the three distinct roles of user, payer and buyer. Relationship marketing is an influential asset

for customer behaviour analysis as it has a keen interest in the re-discovery of the true

meaning of marketing through the re-affirmation of the importance of the customer or buyer.

A greater importance is also placed on consumer retention, customer relationship

management, personalisation, customisation and one-to-one marketing. Social functions can

be categorized into social choice and welfare functions.

Each method for vote counting is assumed as social function but if Arrow’s possibility

theorem is used for a social function, social welfare function is achieved. Some specifications

of the social functions are decisiveness, neutrality, anonymity, monotonicity, unanimity,

homogeneity and weak and strong Pareto optimality. No social choice function meets these

requirements in an ordinal scale simultaneously. The most important characteristic of a social

function is identification of the interactive effect of alternatives and creating a logical relation

with the ranks. Marketing provides services in order to satisfy customers. With that in mind,

the productive system is considered from its beginning at the production level, to the end of

the cycle, the consumer (Kioumarsi et al., 2009).

Factors influencing Consumer Behavior

The starting point for understanding consumer buying behavior is the stimulus – response

model. It is generally known as Black Box Model. As this model shows, both marketing and

environmental stimuli enter the buyer’s consciousness. In turn, the buyer’s characteristics and

decision process lead to certain purchase decisions. The marketer’s task is to understand what

happens in the buyer’s consciousness between the arrival of outside stimuli and the buyer’s

purchase decisions. This model indicates, a consumer’s buying behavior is influenced by

cultural, social, personal, and psychological factors. Knowledge of such factors that influence

consumer behavior can help to predict how consumers will respond to their products.

Table 3.1: Black box model

ENVIRONMENTAL FACTORS BUYER'S BLACK BOXBUYER'S

RESPONSEMarketing

Stimuli

Environmental

Stimuli

Buyer

CharacteristicsDecision Process

Product

Price

Place

Promotion

Economic

Technological

Political

Cultural

Demographic

Natural

Attitudes

Motivation

Perceptions

Personality

Lifestyle

Knowledge

Problem

recognition

Information search

Alternative

evaluation

Purchase decision

Post-purchase

behavior

Product choice

Brand choice

Dealer choice

Purchase timing

Purchase amount

The black box model shows the interaction of stimuli, consumer characteristics, and decision

process and consumer responses. It can be distinguished between interpersonal stimuli

(between people) or intrapersonal stimuli (within people). The black box model is related to

the black box theory of behaviorism, where the focus is not set on the processes inside a

consumer, but the relation between the stimuli and the response of the consumer. The

marketing stimuli are planned and processed by the companies, whereas the environmental

stimulus is given by social factors, based on the economical, political and cultural

circumstances of a society. The buyer’s black box contains the buyer characteristics and the

decision process, which determines the buyer’s response.

The black box model considers the buyers response as a result of a conscious, rational

decision process, in which it is assumed that the buyer has recognized the problem. However,

in reality many decisions are not made in awareness of a determined problem by the

consumer.

Culture

Culture encompasses the values, arts, customs and skills of people in a given society. Cultural

trends reflect the social values of the population and, as such, have important implications for

market segmentation, product development, advertising and other aspects of marketing

strategy. Social class categories can be identified by income, education level and occupation.

The relationship between social class and purchasing patterns, nevertheless, provides an

important link for marketers in strategy planning.

Culture includes the basic values, perceptions, preferences, and behaviors that a person learns

from family and other key institutions. Subcultures are “cultures within cultures” that have

distinct values and lifestyles. People with different cultural, subcultural and social class

characteristics have different products and brand preferences.

Social Factors

Social factors also influence a buyer’s behavior. A person’s reference groups such as, family,

friends, social organizations, professional associations strongly affect product and brand

choices. The person’s position within each group can be defined in terms of role and status. A

buyer chooses products and brands that reflect his or her role and status.

Demographic Factors

The buyer’s age, life-cycle stage, occupation, economic circumstances, lifestyle, personality

and other personal characteristic influence his or her buying decisions. Young consumers

have different needs and wants from those who are old; consumers with higher incomes buy

differently from those who have less to spend. Consumer lifestyles have also an important

influence on buyer’s choices.

TYPES OF BUYING BEHAVIOR

The following are the several types of buying behavior that resides with everyone.

Dissonance-Reducing Buying Behavior

It occurs when consumers are highly involved with an expensive, infrequent, or risky

purchase, but see little difference among brands. For example, consumers buying carpets may

face a high-involvement decision because carpet is expensive and self-expressive. In this

case, because perceived differences are not large, buyers may shop around to learn what is

available, but buy relatively quickly. They may respond primarily to a good price or to a

purchase convenience. After the purchase, consumers might experience post-purchase

dissonance (after-sale discomfort) when they notice certain disadvantages of the purchased

carpet brand or hear favorable things about brands not purchased. To counter such

dissonance, the marketer’s after-sale communications should provide evidence and support to

help consumers feel good about their brand choices.

Habitual Buying Behavior

It occurs under conditions of low consumer involvement and little significant brand

difference. For example, take salt. Consumers have little involvement in this product

category; they simply go to the store and reach for a brand. If they keep reaching for the same

brand, it is out of habit rather than strong brand loyalty. Consumers appear to have low

involvement with most low-cost, frequently-purchase products. Because they are not highly

involved with the product, consumers may not evaluate choice after purchase. Thus, the

buying process involves brand beliefs formed by passive learning, followed by purchase

behavior, which may not evaluate the choice even after purchase behavior, which may or may

not be followed by evaluation. As buyers are not highly committed to any brand, marketers of

low involvement products with few brand differences often use price and sales promotions to

stimulate product trail.

Variety Seeking Buyer Behavior

Consumers undertake variety-seeking buying behavior in situations characterized by low

consumer involvement, but significant perceived brand differences. In such cases, consumers

often do a lot of brand switching. For example, when purchasing cookies, a consumer may

hold some beliefs, choose a cookie brand without much evaluation, then evaluate that brand

during consumption. But the next time, the consumer might pick another brand out of

boredom or simply to try something different. Brand switching occurs for the sake of variety

rather than because of dissatisfaction. The market leader will try avoiding out-of-stock

conditions, and running frequent reminder advertising. Challenger firms will encourage

variety seeking by offering lower prices, deals, coupons, free samples and advertising that

presents reasons for trying something new.

Impulse and Planned Buying

The purchase of an ice cream may be planned or made on impulse. In some cases, a purchase

may be planned in advance, but the timing of the actual purchase may be decided on the

impulse of the moment. Impulse buying is sometimes classified into reminder buying or

suggestion buying. National advertisers try through displays in retail stores to remind the

buyer of products he has seen advertised. Toothpaste is an example.

Suggestion buying occurs when the consumer’s sees a product displayed and realizes that he

could use it. An example would be a cigarette lighter. Impulse buying has grown particularly

with the development of the self-service retail store.

BUYING DECISIONS

Consumer buying behavior is influenced by the buyer’s decision making process. The buying

situation can vary from one of routine-response behaviors to limited problem solving to

extensive problem solving. Buying is not a single act but a multi-component decision on the

need class, generic class, product class, product form, brand, vendor, quantity, timing and

method of payment. The buyer goes through a process consisting of need arousal,

information search, evaluation behavior, purchase decision and post-purchase feelings. At

each decision stage, characteristics of the buyer, product, seller and selling situation interact

to influence the buying outcome. A person’s buying behavior is the result of the complex

interplay of all these cultural, social, personal, and psychological factors. More complex

decision usually involve more buying participants and more buyer deliberation. Consumers

undertake complex buying behavior when they are highly involved in a purchase and

perceive significant differences among brands. Marketers of high-involvement products must

understand the information gathering and evaluation behavior of high-involvement

consumers.

Fig 3.2: Buying Decision Process

Need Recognition

Information Search

Evaluation of Alternatives

Purchase Decision

Post Purchase Behavior

Need Recognition

The buyer senses a difference between his or her actual state and some desired state. The

need can be triggered by internal stimuli when one of the person’s normal needs – hunger,

thirst, sex, etc. rise to a high enough to become a drive. From previous experience, the person

has learned how to cope with this drive and is motivated toward objects that he or she knows

will satisfy it.

Information Search

The consumer can obtain information from any of several sources. These include: personal

sources (family, friends, neighbors, and acquaintances), commercial sources (advertising,

salespeople, dealers, packaging and displays), public sources (mass media, consumer-rating

organizations) and experimental sources (handling, examining and using the product).

The relative influence of these information sources varies with the product and the buyer. The

most effective sources, however, tend to be personal. Personal sources appear to be even

more important in influencing the purchase of services. Commercial sources normally inform

the buyer, but personal sources legitimize or evaluate products for the buyer. The marketer

should carefully identify consumer’s sources of information and the importance of each

source.

Consumers should be asked how they first heard about the brand, what information they

received, and the information is critical in preparing effective communication strategies

aimed at target markets. Word-of-mouth communication can have a significant impact on

purchase decisions. The search for information usually leads to the establishment of criteria

for choosing among specific brands. Consumers are usually aware of some brands and

unaware of others. Those they are aware of fall into an inert set, an inept set or an evoked set.

The final choice will be made from the latter. The costs involved in searching for

information, sometimes outweigh the benefits.

Evaluation of Alternatives

The marketer needs to know about the alternative evaluation, that is, how the consumer

processes information to arrive at brand choices. Each consumer is trying to satisfy some

need and is looking for certain benefits that can be acquired by buying product or service.

Further, each consumer sees a product as a bundle of attributes with varying capacities for

delivering these benefits and satisfying the need. Marketers should be more concerned with

attribute importance than attribute salience.

The consumer’s beliefs held about a particular attribute are based on his or her experience

and the effect of selective perception, selective distortion and selective retention. The utility

function shows how the consumer expects total product satisfaction to vary with different

levels of different attributes.

Purchase Decision

Purchase decisions often begin with trial purchases of limited quantities. Repeat purchases

are closely related to brand loyalty. Store choice is an important factor in purchase decisions.

The bulk of consumer spending occurs in stores, but catalog sales comprise an increasing

percentage of retail sales. The purchase decision includes decisions on financing, installation,

related products and services. The marketing implications of purchase decisions depend on

whether a mass-marketing approach or market-segmentation approach is adopted. Generally,

the consumer’s purchase decision will be to buy the most preferred brand, but two factors can

come between the purchase intention and the purchase decision. They are attitudes of others

and unexpected situational factors.

Fig 3.3: Steps between Purchase Intention & Purchase Decision

Purchase Decision

Unexpected Situational FactorsAttitude of others

Purchase Intention

EVALUATION OF ALTERNATIVES

A consumer’s decision to change, postpone, or avoid a purchase decision is influenced

heavily by perceived risk. Many purchases involve some risk taking. Anxiety results when

consumers cannot be certain about the purchase outcome. The amount of perceived risk

varies with the amount of money at stake, the amount of purchase uncertainty, and the

amount of consumer self-confidence. A consumer takes certain actions to reduce risk, such as

avoiding purchasing decisions, gathering more information, and looking for national brand

names and products with warranties. The marketer must understand the factors that provoke

feelings of risk in consumers and must provide information and support that will reduce the

perceived risk.

Post-Purchase Behavior

In the post-purchase evaluation, consumers compare the product’s performance against their

expectations. Cognitive dissonance occurs when consumers feel a discrepancy between their

expectations of a product and its performance. Follow-up advertising can be designed to

reassure consumers that they have made the right choice. Consumers base their expectations

on messages they receive from sellers, friends and other information sources. If the seller

exaggerates the product’s performance, consumer expectations will not be met, a situation

that leads to dissatisfaction. The larger the gap between expectations and performance, the

greater is the consumer’s dissatisfaction. On the other hand, every purchase involves

compromise. Consumers feel uneasy about acquiring the drawbacks of the chosen brand and

about losing the benefits of the brands not purchased. Thus, consumers feel at least some

post-purchase dissonance for every purchase. A satisfied customer buys again, talks

favorably to others about the product, pays less attention to competing brands and advertising

and buys other products from the company.

3.2 Research Studies

Niedrich Ronald W. and Swain Scott D (2003), in their article titled, “The Influence of

Pioneer Status and Experience Order on Consumer Brand Preference: A Mediated-

Effects Model” found: Within the behavioral literature, two basic explanations of the

pioneering advantage had been offered. Early work focused on order-based explanations.

More recently, schema-based explanations had also been suggested. The authors proposed a

mediated-effects model of the pioneering advantage and test the model in two separate

longitudinal studies. Both experiments support the proposed model. The authors found that

experience order and pioneer-status have additive effects on brand preference such that

perceptions of first-in-market and first-experienced brands are more favorable, suggesting

that both explanations are operative. The authors also provide evidence that the effects of

pioneer status on brand preference are mediated by attitude toward the brand and company

credibility, while the effects of experience order on brand preference are mediated by attitude

toward the brand and attribute recall. These data support the notion that the effect of pioneer

status on brand preference was the result of both brand-level and company-level

associations.

Dr. Rajagopal (2009), in his article titled, “Conational Drivers Influencing Brand

Preference Among Consumers” discussed: Consumers recognize brands by building

favorable attitude towards them and through the purchase decision process. Brand preference

is understood as a measure of brand loyalty in which a consumer exercises his decision to

choose a particular brand in presence of competing brands. The study aimed at discussing the

cognitive factors that determine brand preference among consumers based on empirical

research. Brand attributes including emotions, attitudes, personality, image, reputation and

trust which influence consumer perceptions and temporal association with brands are

critically examined in the study. The study revealed that higher brand relevance and trust

build strong the association of consumers with brand in long-run.

Purohit H.C (2008), in his article titled, “Customer Relationship Management and Brand

Loyalty Through Word Of Mouth (WOM) Communication” discussed: Customer loyalty

is not a choice any longer with business; it is the only way of building a sustainable

competitive advantage. Building loyalty with key customers had become a core marketing

objective shared by key players in all industries catering to business customers.

Communication with customer partners is a necessary process of relationship marketing. It

helps in relationship development, foresters trust, and provides the information and

knowledge needed to undertake cooperative and collaborative activities of relationship

marketing. CRM refers to a conceptually broad phenomenon of business activity; if the

phenomenon of cooperation and collaboration with customers become the dominant

paradigm of marketing practice the satisfaction level of the consumers goes high up to the

level of delight. The building of customer relationship was a fundamental business of every

enterprise and it requires a holistic strategy and process to make it successful. The proposed

study will focus on the issues related with customer satisfaction, repeat purchase behavior,

building consumer relationship management through customer loyalty and suggest the

measures to minimize the challenges of a highly competitive global market.

Sha Yang, Gerg M. Allenby and Geraldine Fennel (2002), in their article titled,

“Modeling Variation in Brand Preference: The Roles of Objective Environment and

Motivating Conditions” discussed: People consume products in a variety of environments.

They drink beer, for example, by themselves, with close friends, on the beach, when playing

cards, at tailgate parties, and while having dinner with their boss. Within these environments,

an individual may prefer Schaefer beer when drinking alone, Budweiser when having a party,

Corona when lying on the beach, and Heineken when dining out. Preferences change across

environments because the benefits sought by the consumer change. Consumers may feel

thirsty while lying on the beach, and they may want to display refined tastes while dining out.

Moreover, the effect of environment may not be homogeneous, as some people enjoy meeting

new people in social gatherings while others may prefer to visit with those who are more

familiar. Even though consumers face the same objective environment, different motivating

conditions and brand preferences may arise.

It is important for marketing managers to understand how brand preferences change across

people, environments, and motivating conditions and, more importantly, which product

attributes are associated with these changes. Communication and positioning decisions are

more likely to be effective if the relationships among objective environment, motivating

conditions, and preferences for brand attributes are known. If motivating conditions are

uniquely associated with individuals across environments or with environments across

individuals, then the basis of marketing analysis is at the individual or environmental level. If,

however, motivating conditions arise from the intersection of individuals and their

environments, then analysis conducted at the individual or environmental level will be

insufficient to understand human behavior. In such a case, firms may want to view different

environments as distinct markets, each with its own pattern of heterogeneous wants and

competitive environment.

The paper investigated on the influence of objective environments and motivating conditions

on brand preference. The mathematical model is based on the economic framework of utility

maximization and discrete choice, and it accommodates three challenges that arise in

modeling variation in brand preference. First, consumer consideration sets and purchase

histories can vary widely across individuals in a relevant universe. Because brand preferences

are the dependent variables in our analysis, our method must be able to accommodate a large

number of brands to avoid restricting its measured variation as the objective environment and

motivating conditions change. The authors proposed a method using partial ranking data,

combined with pairwise trade-off data, to obtain estimates of brand preference for all brands

in their study. Second, the model must allow for multiple effects, leading to both within-

person and across-person heterogeneity in preferences. Variation in brand preference is

investigated within a hierarchical Bayes model in which motivating conditions are related to

brand preference through a regression model in the random effects specification. Third, it is

often counterintuitive for respondents to express preferences for attribute combinations that

do not actually exist. A statistical method model is proposed for decomposing aggregate

brand preferences into preferences for core and extended product attributes.

Data were collected from a national survey of consumer off-premises beer consumption. A

total of 842 respondents from six different geographic markets participated. Data include

preferred brand sets under different objective environments, brand choice rankings, product

attributes, and motivating conditions. Effect sizes for respondent and objective environment

are both large. Researchers found that the level of explained variance in brand and attribute

preference attributable to motivating conditions is greater than that accounted for by a simple

interaction of respondent and environmental effects, suggesting that motivations provide a

more sensitive description of variation in brand preference. The findings indicate that 1)

across individuals the objective environment is associated with heterogeneous, not

homogeneous, motivating conditions; 2) within an individual, motivating conditions may

change with variation in the objective environment; and 3) motivating conditions are related

to preferences for specific attributes.

Their results implied that the unit of analysis for marketing was properly a person-activity

occasion. Brands, for example, are used in individual instances of behavior—a brand

performs well or poorly on individual occasions of use. The relevant universe was enumerated

in person-activity occasions rather than in respondents. For some activities, such as doing the

laundry, the occasions may typically occur in relatively unchanging environments, and it may

be appropriate to allow respondents to summarize over occasions of the activity. For other

activities, such as snacking or drinking beer, the activity may occur in distinct kinds of

environment. In the case of such activities, it was appropriate to allow for the effect of

changing environments to manifest themselves, if present. Doing so may require sampling

from the relevant universe of person-activity occasions over an appropriate time frame. The

design must be such as to record intra-individual variability due to changes in the

environment for action.

S. Sriram, K. Pradeep Chintagunta and Ramya Neelamegham (2005), in their article titled,

“Effects of Brand Preference, Product Attributes, and Marketing Mix Variables in

Technology Product Markets”, discussed: The authors developed a demand model for

technology products that captures the effect of changes in the portfolio of models offered by a

brand as well as the influence of the dynamics in its intrinsic preference on that brand’s

performance. In order to account for the potential correlation in the preferences of models

offered by a particular brand, researcher’s used a nested logic model with the brand (e.g.,

Sony) at the upper level and its various models (e.g., Mavica, FD, DSC, etc.) at the lower

level of the nest. Relative model preferences were captured via their attributes and prices.

Researcher’s allowed for heterogeneity across consumers in their preferences for these

attributes and in their price sensitivities in addition to heterogeneity in consumers’ intrinsic

brand preferences. Together with the nested logic assumption, this allows for a flexible

substitution pattern across models at the aggregate level. The attractiveness of a brand’s

product line changes over time with entry and exit of new models and with changes in

attribute and price levels. To allow for time-varying intrinsic brand preferences, the

researcher’s used a state-space model based on the Kalman filter, which captures the

influence of marketing actions such as brand-level advertising on the dynamics of intrinsic

brand preferences. Hence, the proposed model accounts for the effects of brand preferences,

model attributes and marketing mix variables on consumer choice. First, researcher’s carried

out a simulation study to ensure that their estimation procedure is able to recover the true

parameters generating the data. Then, the researcher’s estimated their model parameters on

data for the U.S. digital camera market. Overall, it was found that the effect of dynamics in

the intrinsic brand preference was greater than the corresponding effect of the dynamics in

the brand’s product line attractiveness. Assuming plausible profit margins, researcher’s

evaluated the effect of increasing the advertising expenditures for the largest and the smallest

brands in this category and find that these brands can increase their profitability by increasing

their advertising expenditures. Researcher’s also analyzed the impact of modifying a camera

model’s attributes on its profits. Such an analysis could potentially be used to evaluate if

product development efforts would be profitable.

Denford Chimboza and Edward Mutandwa (2007) in their article titled, “Measuring the

determinants of brand preference in a dairy product market” discussed: Branding is

increasingly being used as a strategy for managing markets in developed countries while

developing countries still lag behind. The objective of the study was to assess the level of

brand awareness and factors underlying brand preference of dairy brands in Chitungwiza and

Harare urban markets in Zimbabwe. A total of 90 respondents who included individual and

institutional consumers were selected using judgmental and simple random sampling

respectively. Primary data was collected using structured interview schedules developed for

each category of consumers. Consumer product awareness indices, cluster analysis and factor

analysis were the main tools used in the analysis. The findings of the study showed that 52%

of the respondent consumers were aware of ARDA dairy brands despite having come across

few ARDA DDP advertisements. Four factors were identified as key determinants of dairy

product choice namely promotion, price and availability of product, attractive packaging and

product quality.

Adeolu B. Ayanwale, Taiwo Alimi and Matthew A. Ayanbimipe (2005) in their article titled,

“The Influence of Advertising on Consumer Brand Preference” discussed: The

proliferation of assorted brands of food drinks in the country has led to cut-throat competition

for increased market share being witnessed among the operators in the food drink industry.

When competition is keen and the consumers are faced with brand choice in the market, it

becomes imperative for the manufacturers to understand the major factors that can attract the

attention of buyers to his own brand. These then form the basis for marketing planning and

action. The study, which was based on a survey of 315 randomly selected consumers of food

drinks in Lagos, Ibadan and Ile-Ife, cities in Southwestern Nigeria, examined the role played

by advertising in influencing consumers’ preference for Bournvita, which is one of the

leading food drinks in the Food and Beverage industry in Nigeria. Results revealed that both

male and female and different age groups were equally influenced by advertising in their

preference for the brand. 38.73% of the consumers showed preference for Bournvita out of

the various brands of the food drink studied. The major reasons advanced for the preference

are its captivating advertising (42.62%) and rich quality (40.16%). TV advertising was most

preferred by 71.43% of the respondents of all the media used in advertising Bournvita.

The need for high preference to advertising is therefore highlighted for companies that want

to not only retain their market but take positive steps to increase their market share.

Dr. G.Sridhar, Dr. N.Ramesh Kumar and Dr. G. Narasimha Murthy (2010), in their article

titled, “Susceptibility to reference group influence among rural consumers”, discussed:

The diversity in the reference group influence on consumer purchase in general and with

reference to rural consumers was examined. The literature on reference groups’ influence on

rural consumer behavior reveals the role and importance of opinion leaders and the

susceptibility of consumers on reference groups for any purchase. Many findings in rural

marketing domain concur with the literature on the reference group influence construct done

elsewhere. Consumers who are susceptible to interpersonal influence will try to satisfy

reference groups' expectation by complying with groups' norms. Reference groups in all had

been found to have profound influence on consumers' decision making. This influence is

different for several sub cultures and situations. Consumers may accept a reference group

influence because of its role in providing informational, utilitarian and value expressive

influences.

Factors affecting brand preference

Brand adoption or preference has been receiving increased attention in extant literature.

Cooper (1993) noted that most new innovations come with high risks as most of them failed

in the marketplace creating the need for marketers to have a clear understanding of success

factors in brand adoption. Theories of adoption have often been used to explain how

consumers form preferences for various goods and services (Rogers, 1995; Tornasky and

Klein, 1982; Mason, 1990; Charlotte, 1999). Generally, these theories emphasize on the

importance of complexity, compatibility, observability, triability, relative advantage, risk,

cost, communicability, divisibility, profitability, social approval, and product characteristics

in brand preference (Wee, 2003). The relative importance of each factor depends on the

nature of industry under consideration, location and social characteristics of the consumers of

the different brands.

Consumer choice behavior has also been studied using the five-step process step (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 (Dorsch et al., 2000).

Discrete choice models (Chintagunta, 1999; Bockenholt and Dillon, 2000) or neural networks

to model selection decisions (Papatla et al., 2002) have also been used in brand choice

research. Wee (2003) conducted a study to identify the factors affecting adoption of new

product innovations in the consumer electronic industry of Singapore using qualitative (focus

group discussions) and quantitative research techniques (survey with 151 respondents in the

16 - 35 year age group). The researcher considered two brands, the Mini Disc and the MP3

Portable player. Using factor analysis, seven factors were identified as critical in effecting

adoption of a player: relative advantage, perceived risk, complexity, compatibility,

observability, image and trialability. Of these factors, relative advantage conferred by the

player was the most important factor that consumers valued in their adoption decisions.

Li and Houston (1999) employed a sample of 1200 consumers in Taiwan to determine factors

underlying choice of market innovations. Price level, product variety and marketing

communications factors were identified as promoters of choice. The promotional (marketing

communications) mix has various elements – advertising, sales promotion, direct marketing,

exhibittions, sponsorship, personal selling, word of mouth, merchandising, public relations,

relationship marketing, corporate image and reputation etc.

Karjaluoto et al. (2005) investigated the consumer choice in the context of the mobile phone

industry in Finland using a sample of 196 respondents. Twenty-four questions were used to

assess consumer motivations in mobile phone choice. Seven estimated factors influencing

mobile phone choice were Innovative services, multimedia, design, brand and basic

properties, outside influence, price, and reliability explain and these accounted for about 70%

of the total variance. Some of the important product decisions in any marketing context are

product, variety, product performance, product features, product design, product presentation,

sizes etc (Doyle, 2002).

Consumer surveys often reveal that quality is one of the most important decision factors for

consumers, if not the most important (Keller, 2000). Product quality stands for the ability of a

product to perform its functions (Kotler, 2003).

Consumer Behavior Analysis

Proctor et al. (1982) noted that the principle aim of consumer behavior analysis is to explain

why consumers act in particular ways under certain circumstances. It tries to determine the

factors that influence consumer behavior, especially the economic, social and psychological

aspects which can indicate the most favored marketing mix that management should select.

Consumer behavior analysis helps to determine the direction that consumer behavior is likely

to make and to give preferred trends in product development, attributes of the alternative

communication method etc. consumer behaviors analysis views the consumer as another

variable in the marketing sequence, a variable that cannot be controlled and that will interpret

the product or service not only in terms of the physical characteristics, but in the context of

this image according to the social and psychological makeup of that individual consumer (or

group of consumers).

Source of Influence

Zacharias et al. (2009) found that irrespective of the occupation, respondents of their study

felt that friends and relatives strongly influence a consumer decision.

Erda (2009) found those personal sources; especially family and friends' influence consumer

decision making in rural markets. He found that about 29% of the sample was influenced by

family and 18% by friends while taking a decision to purchase products.

Dhumal et al. (2009) observed that peer group has a significant effect on the purchasing

pattern of rural consumers especially branded products.

Gupta and Mittal (2009) observed that head of the family has the highest influence on the

purchase of products followed by retailers, family members and relatives.

Velayudhan (2009) found that the influence of personal sources of information is higher in

rural areas when compared to urban areas. He also found that informal referent groups largest

sources of information in rural markets. Incidentally, more educated consumers also used

informal referent groups.

CHAPTER 4

DATA ANALYSIS AND INTERPRETATION

4.1 Demographic Factors

The major demographic factors which influence the consumer buying behavior are analyzed

based on descriptive analysis. The factors which are discussed and analyzed are Age,

Education, Occupation and Monthly Income. These factors fall under the two major

classification which affects the consumer buying behavior known as Personal and Social

Factors.

AGE:

Table 4.1

Details of Age Group

The Table 4.1 showed that the majority 67.5% of the respondents were under 18 – 30 age

group and the minority of 15% were the age of above 43. The obvious implications of this

finding are the dominance of youths in the market for the products of the Bajaj brand.

S.No Age group Frequency Percent

1 18 – 30 81 67.5

2 31 – 43 21 17.5

3 44 & above 18 15.0

4 Total 120 100.0

Figure 4.1

Percentage of respondents based on Age group

18 - 30 31 - 43 44 & above.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

Percent

Percent

Age Group

Percentage

EDUCATIONAL QUALIFICATION:

Table 4.2

Details of Educational Qualification

S.No Qualification Frequency Percent

1 Below +2 25 20.8

2 +2 or Diploma 35 29.2

3 UG 35 29.2

4 PG & Professionals 25 20.8

5 Total 120 100.0

The Table 4.2 shows that the majority 29.2% of the respondents was +2 or Diploma or UG

qualified and the minority 20.8% of the respondents was below +2 or PG & Professionals.

Figure 4.2

Percentage of respondents Education

Percent

Below +2+2 or DiplomaUGPG & Professionals

OCCUPATION:

Table 4.3

Occupation Information about the Respondents

S.No Occupation Frequency Percent

1 Self Employed 19 15.8

2 Private Sector 55 45.8

3 Public Sector 23 19.2

4 Student 21 17.5

5 Others 2 1.7

6 Total 120 100.0

The Table 4.3 shows that the majority 45.8% of the respondents was working in the private

sector and the minority 1.7% was working in other than the given occupation.

Figure 4.3

Percentage of respondents Occupation

Percent

Self EmployedPrivate SectorPublic SectorStudentOthers

MONTHLY INCOME:

Table 4.4

Details of Monthly Income

S.No Income Level Frequency Percent

1 5000 & below 8 6.7

2 5001 - 10000 37 30.8

3 10001 - 15000 31 25.8

4 15001 - 20000 18 15.0

5 20000 & above 26 21.7

6 Total 120 100.0

The Table 4.4 shows that the majority 30.8% of the respondents was earning between 5001

and 10,000 rupees per month and the minority 6.7% of the respondents were earning between

5000 and below. This suggests that the medium income level person prefers the Bajaj brand

more than the others.

Figure 4.4

Percentage of respondents Income Level

5000 & below 5001 - 10000 10001 - 15000 15001 - 20000 20000 & above

0

5

10

15

20

25

30

35

Percent

Percent

Income Level

Percentage

4.2 Buying Decision Process

Consumer buying behavior is influenced by the buyer’s decision-making process. Marketers

have to go beyond the various influences on buyers and develop an in-depth understanding of

how consumers actually make their buying decisions. Specifically, marketers must identify

who makes the buying decision, the types of buying decision, and the stages in the buying

process. So, the five stage model of the typical buying process was analyzed.

NEED RECOGNITION:

Table 4.5

Need for buying the bike

S.No Need Frequency Percent

1 Workhorse 73 60.8

2 Run Errands 37 30.8

3 Routine Long Trips 10 8.3

4 Total 120 100.0

The Table 4.5 shows that the majority 60.8% of the respondents was buying the bike for the

purpose of using it for the regular work and the minority 8.3% was buying the bike for

routine long trips.

Figure 4.5

Percentage of Need for buying the bike

Percent

WorkhorseRun ErrandsRoutine Long Trips

PURCHASE DECISION:

Table 4.6

Frequency Table Showing the Factors affecting the Purchasing Decision

S.No Factors R1 R2 R3 R4 R5 R6 R7 R8 R9

1 Advertisement 4 2 7 2 11 11 15 30 38

2 Power 5 18 23 13 26 12 11 8 4

3 Safety 5 14 16 29 15 15 13 11 2

4 Comfort 4 13 25 26 19 20 7 3 3

5 Price 11 30 16 21 14 16 6 6 0

6 Service 2 3 13 12 21 25 23 15 6

7 Mileage 51 26 8 7 7 4 7 8 2

8 Resale 2 1 2 3 2 5 18 28 59

9 Style 36 13 10 7 5 12 19 11 7

The above Frequency Table 4.6 shows that the majority of 51 respondents ranked the

Mileage as the major factor which affects the purchasing decision of the bike followed by the

Style and the majority of 59 respondents ranked the Resale Value as the minor factor which

affects their purchasing decision followed by the Advertisement. This suggests that the

majority of the customer prefer the Bajaj brand for mileage.

Friedman Test for Testing the Difference between the Factors:

For testing the difference between several related samples, Friedman test was used. Here, the

test was applied to test the significant difference between the nine different factors which

affects the purchasing decision of the bike. These factors are measured among respondents as

a ranking based measure. So, the factors which affects the purchasing decision of bike are

identical was used as a null hypothesis.

H0: The factors affecting the purchasing decision of bike are identical

H1: Atleast one factor is different from atleast one other factor

The result of the Friedman Test is given in Table 4.7

Table 4.7

Friedman Test

S.No FactorsMean Rank

Std. Deviation

RankChi-

SquareP value

1 Advertisement 7.04 2.171 8

321.926 .000**

2 Power 4.51 2.070 5

3 Safety 4.66 2.015 6

4 Comfort 4.37 1.791 4

5 Price 3.83 1.965 2

6 Service 5.71 1.858 7

7 Mileage 2.88 2.396 1

8 Resale Value 7.85 1.702 9

9 Style 4.17 2.836 3 Note: ** denotes significance at 1% level

Since p value is less than 0.01, the null hypothesis is rejected at 1% level of significance.

Hence, it is concluded that atleast two of the factors are significantly different from each

other. From the mean rank values, the mileage factor mean rank value is 2.88 which is the

lowest mean and thus it is the highest ranking factor among all. Thus, it is inferred that the

mileage factor is the major factor which affects the purchasing decision of the bike which is

followed by the price factor of the bike.

INFORMATION SEARCH:

PERSONAL SOURCE

Table 4.8

Personal Source of Information

S.No Personal Source Frequency Percent

1 Family 45 37.5

2 Friends 62 51.7

3 Neighbors 9 7.5

4 Acquaintances 4 3.3

5 Total 120 100.0

The Personal Source of Information about the brand depicted by Table 4.8 shows that the

majority 51.7% of respondents obtain information from friends and the minority 3.3% obtain

from other sources.

Figure 4.6

Percentage of Personal Source of Information

Percent

FamilyFriendsNeighborsAcquaintances

COMMERCIAL SOURCE

Table 4.9

Commercial Source of Information

S.No Commercial Source Frequency Percent

1 Advertisement 63 52.5

2 Sales People 26 21.7

3 Dealers 23 19.2

4 Displays 8 6.7

5 Total 120 100.0

The Table 4.9 shows that the majority 52.5% of respondents obtain information from the

advertisement and the minority 6.7% from displays. This suggests that the advertisement

plays the major mode in the Commercial Source of Information.

Figure 4.7

Percentage of Commercial Source of Information

Percent

AdvertisementSales PeopleDealersDisplays

EXPERIMENTAL SOURCE

Table 4.10

Experimental Source of Information

S.No Experimental Source Frequency Percent

1 Handling 50 41.7

2 Examining 36 30.0

3 Using the product 34 28.3

4 Total 120 100.0

The Table 4.10 shows that the majority of 41.7% of respondents obtain information about the

brand by handling the product and the minority 28.3% obtain by using the product. This

suggests that the Experimental Source of Information about the brand is higher with the

person who handles the product prior to the purchase.

Figure 4.8

Percentage of Experimental Source of Information

Percent

HandlingExaminingUsing the product

4.3 Influence of Communication Medium

Table 4.11

Medium of Communication that influences the Brand Preference

S.No Communication Medium Frequency Percent

1 Print Media 12 10.0

2 Electronic Media 21 17.5

3 Word of Mouth 77 64.2

4 Sales Promotion 10 8.3

5 Total 120 100.0

The above Table 4.11 shows that the majority 64.2% of respondents got influenced towards

the Bajaj brand through the medium of Word of Mouth Communication and the minority

8.3% of respondents influenced through Sales Promotion. It suggests that the Word of Mouth

communication medium influences the Brand Preference much higher than the other medium

of communication.

Figure 4.9

Percentage of Influence of Communication Medium

Percent

Print MediaElectronic MediaWord of MouthSales Promotion

4.4 Purchase Mode

Table 4.12

Mode of Purchase

S.No Purchase Mode Frequency Percent

1 By Full Cash 62 51.7

2 EMI 58 48.3

3 Total 120 100.0

The Table 4.12 shows that the majority 51.7% of respondents preferred to buy the bike by

full cash and the minority 48.3% of respondents preferred EMI. It suggests that the majority

of the customer preferred to buy the bike by paying full cash rather than going for EMI.

4.5 Major Role Player in Decision Making

Table 4.13

Role in Decision Making

S.No Decision Maker Frequency Percent

1 Father 19 15.8

2 Mother 1 .8

3 Friends 8 6.7

4 Self 90 75.0

5 Others 2 1.7

6 Total 120 100.0

The Table 4.13 shows that the majority 75% of respondents was the final decision maker for

purchasing the bike and the minority 0.8% of respondents’ opinion was Mother. It suggests

that the respondents are the ultimate decision maker in buying the bike.

4.6 Period took to choose the Bajaj Brand

Table 4.14

Period took to choose the Bajaj Brand

S.No Period Frequency Percent

1 One week 44 36.7

2 One month 32 26.7

3 Two months 26 21.7

4 More than 2 months 18 15.0

5 Total 120 100.0

The Table 4.14 shows that the majority 36.7% of respondents took only one week to choose

the Bajaj brand to buy the bike and the minority 15% of respondents took more than two

months to choose the Bajaj brand.

Figure 4.10

Percentage of Period took to choose the Bajaj Brand

Percent

One weekOne monthTwo monthsMore than 2 months

4.7 Reason for preferring the Bajaj Brand

Table 4.15

Frequency Table Showing the Reason for preferring the Bajaj Brand

S.No Reason Frequency Percent

1 Quality 83 69.2

2 Availability 20 16.7

3 Price 15 12.5

4 Service 2 1.7

5 Total 120 100.0

The Table 4.15 shows that the Quality plays the major reason in preferring the Bajaj brand

for 69.2% of customers followed by the Availability of the product (16.7%).

Figure 4.11

Percentage of Preference Reason

Percent

QualityAvailabilityPriceService

4.8 Satisfaction towards the Product Features

Table 4.16

Percentage of Product Features

S.No Points Price Style Color MileageLess

MaintenancePower Performance Technology

1 1 point 2.5 3.3 0 0.8 2.5 0 0.8 3.3

2 2 points 6.7 5.0 3.3 4.2 10.0 12.5 11.7 18.3

3 3 points 34.2 28.3 35.8 34.2 37.5 35.0 35.8 35.0

4 4 points 43.3 35.0 37.5 45.0 33.3 37.5 38.3 32.5

5 5 points 13.3 28.3 23.3 15.8 16.7 15.0 13.3 10.8

6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Note:

1 point refers to Highly Dissatisfied

2 points refers to Dissatisfied

3 points refers to Neutral

4 points refers to Satisfied

5 points refers to Highly Satisfied

The Table 4.16 shows that the majority 43.3%, 35%, 37.5%, 45%, 37.5% and 38.3% of

respondents are satisfied with the price, style, color, mileage, power and performance of their

bike respectively. The table also shows that the majority 37.5% and 35% of respondents are

neither satisfied nor dissatisfied with the less maintenance and technology of their bike

respectively.

4.9 Test of Finding the Significant Difference

To test the significant difference between age group with regard to the satisfaction with the

total features of the bike, one way ANOVA test also known as F test was used.

H0: There is no significant difference between age group with regard to the

satisfaction with the total features of the bike

H1: There is a significant difference between age group with regard to the satisfaction

with the total features of the bike

The result of the ANOVA analysis is given in Table 4.17

Table 4.17

ANOVA – Total Features

S.No Groups Sum of Squares df Mean Square F value P value

1 Between Groups 368.572 2 184.286

10.844 .000**2 Within Groups 1988.353 117 16.994

3 Total 2356.925 119 Note: ** denotes significance at 1% level

Since P value is less than 0.01 the null hypothesis is rejected at 1% level of significance on

age group. Hence, there is a significant difference between age group with regard to the

satisfaction with the total features of the bike. Hence, descriptive statistics was used to find

the age group who are more satisfied with the bike features. The Table 4.18 shows the

Descriptive Statistics.

Table 4.18

Descriptive Statistics

S.No Age Group N Mean Std. Deviation

1 18 – 30 81 28.21 4.309

2 31 – 43 21 27.43 3.641

3 44 & above 18 32.89 3.740

4 Total 120 28.78 4.450The Table 4.18 indicates that the variable ’44 & above’ has the highest mean value of 32.89.

This suggests that the respondents under the age group 44 and above are more satisfied with

the features of the bike than the other age group respondents.

4.10 Rating of Showroom Attributes

Table 4.19

Percentage of Showroom Attributes

S.No Rating Infrastructure Availability Response Knowledge Service

1 Excellent 3.3 4.2 3.3 5.0 10.0

2 Good 50.0 50.8 24.2 38.3 28.3

3 Average 42.5 32.5 55.0 45.8 41.7

4 Poor 3.3 11.7 16.7 9.2 15.8

5 Worse .8 0.8 0.8 1.7 4.2

6 Total 100.0 100.0 100.0 100.0 100.0

The Table 4.19 shows that the majority 50% and 50.8% of respondents rated the

infrastructure of the showroom and the product availability in the showroom was good

respectively. The table also shows that the majority 55%, 45.8% and 41.7% of respondents

rated the after sales response of the dealer, knowledge of the salesman and the service of the

dealer was average respectively.

4.11 Test of Difference between the Recommendation of Dealer and Showroom

Satisfaction

H0: There is no significant difference between levels of recommendation of dealer

with regard to the satisfaction with the total showroom attributes

H1: There is a significant difference between levels of recommendation of dealer with

regard to the satisfaction with the total showroom attributes

The result of the ANOVA analysis is given in Table 4.20

Table 4.20 ANOVA – Total Showroom Attributes

S.No Groups Sum of Squares df Mean Square F value P value

1 Between Groups 257.100 4 64.275

12.526 .000**2 Within Groups 590.100 115 5.131

3 Total 847.200 119 Note: ** denotes significance at 1% level

Since P value is less than 0.01 the null hypothesis is rejected at 1% level of significance on

level of recommendation of dealer. Hence, there is a significant difference between levels of

recommendation of dealer with regard to the satisfaction with the total showroom attributes.

Hence, descriptive statistics was used to find the level of recommendation best described by

the respondents. The Table 4.21 shows the Descriptive Statistics.

Table 4.21 Descriptive Statistics

S.No Level of Recommendation N Mean Std. Deviation

1 Highly Recommend 13 10.9231 3.27774

2 Recommend 31 12.5806 1.91092

3 Neutral 57 13.4211 2.22765

4 Not Recommend 15 14.8667 2.26358

5 Highly Not Recommend 4 19.0000 .81650

6 Total 120 13.3000 2.66821

The Table 4.21 indicates that the variable ‘Highly Recommend’ has the least mean value of

10.9. This suggests that the respondents highly recommend the showroom because of their

satisfaction with the attributes of the showroom.

4.12 Role of Availability of Product during Purchase in the Selection of Brand

Table 4.22

Role of availability in the selection of brand

S.No Role of availability Frequency Percent

1 Very High 25 20.8

2 High 62 51.7

3 Average 33 27.5

4 Low 0 0

5 Very Low 0 0

6 Total 120 100.0

The Table 4.22 shows that the majority 51.7% of respondents’ opinions was high about the

role of availability of product in the selection of brand and the no response in the last two

rating shows that the importance of availability is always higher in the selection of brand.

4.13 Trust Level on the Bajaj Brand

Table 4.23

Trust Level on the Bajaj Brand

S.No Trust Level Frequency Percent

1 Very High 23 19.2

2 High 49 40.8

3 Average 46 38.3

4 Low 2 1.7

5 Very Low 0 0

6 Total 120 100.0

The Table 4.23 shows that the majority 40.8% of respondents’ opinions was high about their

trust level on the Bajaj brand and the no response on the ‘Very Low’ rating of the Trust Level

shows that all the respondents possess atleast some Trust on the Bajaj Brand.

4.14 Customer Reaction during the Unavailability of Product during Purchase

Table 4.24

Reaction of customer when Bajaj brand is not available during the purchase

S.No Reaction of the customer Frequency Percent

1 Wait for sometime 37 30.8

2 Going to the other dealer in another region 49 40.8

3 Choosing the other product category under Bajaj 19 15.8

4 Choosing other brand with the same features of the product 15 12.5

5 Total 120 100.0

The Table 4.24 shows that the majority 40.8% of respondents will go to the other dealer in

another region for buying the Bajaj bike if the required brand is not available during the

purchase with a particular dealer and only the 12.5% of respondents agreed that they will

change the brand if the brand is not available during the purchase.

4.15 Satisfaction towards Some Significant Attributes

Table 4.25

Percentage of Satisfaction on the given Attributes

S.No Satisfaction Level Safety Comfort AvailabilityProduct

Price

Spare Parts Price

1 Highly Satisfied 8.3 7.5 6.7 1.7 5.0

2 Satisfied 63.3 68.3 29.2 45.0 27.5

3 Neutral 27.5 24.2 58.3 41.7 53.3

4 Dissatisfied .8 0 5.8 11.7 14.2

5 Highly Dissatisfied 0 0 0 0 0

6 Total 100.0 100.0 100.0 100.0 100.0

The Table 4.25 shows that the majority 63.3%, 68.3% and 45% of respondents were satisfied

with the safety, comfort and the price of their bike respectively. The table also shows that the

majority 58.3% and 53.3% of respondents were neither satisfied nor dissatisfied with the

availability of the spare parts and the price of the spare parts of their bike respectively.

4.16 Test of Significant Relationship between Satisfaction on Safety and Comfort

To test the relationship between the level of satisfaction with regard to safety and comfort of

the bike, Correlation test was used. So, the test variables were the level of satisfaction on

safety and the level of satisfaction on comfort. Correlation test was applied to establish the

qualitative relationship between these two variables and thereby it is possible to find the

direction of relationship between the variables.

H0: There is no relationship between the level of satisfaction with regard to safety and

comfort of the bike

H1: There is a relationship between the level of satisfaction with regard to safety and

comfort of the bike

The result of Correlation Analysis is given in Table 4.26

Table 4.26

Correlation between Level of Satisfaction of Safety and Comfort

S.No

Variable Correlation Value (Pearson Correlation) P value

1 Safety0.521** 0.000

2 Comfort ** Correlation is significant at the 0.01 level (2-tailed).

Since p value is less than 0.01, the null hypothesis is rejected at 1% level of significance.

Hence, there is a relationship between the level of satisfaction with regard to safety and

comfort of the bike. The Correlation square between the safety and comfort satisfaction level

is 0.521 which indicates 52% positive relationship between them.

4.17 One Way ANOVA Test for Finding the Significant Difference between the

Variables

To test the significant difference between age group with regard to the satisfaction with the

total price of the bike and its spare parts, one way ANOVA test also known as F test was

used.

H0: There is no significant difference between age group with regard to the

satisfaction with the total price of the bike and its spare parts

H1: There is a significant difference between age group with regard to the satisfaction

with the total price of the bike and its spare parts

The result of the ANOVA analysis is given in Table 4.27

Table 4.27 ANOVA – Total Price

S.No Groups Sum of Squares df Mean Square F value P value

1 Between Groups 15.484 2 7.742

5.109 .007**2 Within Groups 177.316 117 1.516

3 Total 192.800 119 Note: ** denotes significance at 1% level

Since P value is less than 0.01 the null hypothesis is rejected at 1% level of significance on

age group. Hence, there is a significant difference between age group with regard to the

satisfaction with the total price of the bike and its spare parts. Hence, descriptive statistics

was used to find the satisfaction of total price and its spare parts best described by the

respondents. The Table 4.28 shows the Descriptive Statistics.

Table 4.28 Descriptive Statistics

S.No Age Group N Mean Std. Deviation

1 18 – 30 81 5.5802 1.12765

2 31 – 43 21 5.4286 1.43427

3 44 & above 18 4.5556 1.42343

4 Total 120 5.4000 1.27286The Table 4.28 indicates that the variable ’44 & above’ has the least mean value of 4.55. This

suggests that the respondents of age group 44 and above are satisfied with the total price of

the bike and its spare parts than other age group respondents.

4.18 Overall Service Experience of Respondents

Table 4.29

Rating of overall service experience

S.No Rating Frequency Percent

1 Excellent 5 4.2

2 Very Good 16 13.3

3 Good 62 51.7

4 Okay 31 25.8

5 Poor 6 5.0

6 Total 120 100.0

The Table 4.35 shows that the majority 51.7% of respondents rated their overall service

experience with regards to their bike was Good and the minority 4.2% of respondents rated

their overall service experience with regard to their bike was Excellent.

4.19 Overall Satisfaction of the Bajaj bike of the Respondents

Table 4.30

Overall satisfaction level with regards to the Bajaj bike

S.No Satisfaction Level Frequency Percent

1 Highly Satisfied 15 12.5

2 Satisfied 62 51.7

3 Neutral 40 33.3

4 Dissatisfied 3 2.5

5 Highly Dissatisfied 0 0

6 Total 120 100.0

The Table 4.30 shows that the majority 51.7% of respondents were satisfied with their Bajaj

bike after purchase. This suggests that the majority of the customers don’t experience the

post-purchase dissonance (after-sale discomfort). It is because of the marketer’s after-sale

communications which provide evidence and support to help customers feel good about their

brand choices.

4.20 Test of Significant Relationship between the Satisfaction of Bike and the Service

Experience

To test the relationship between the overall satisfaction with regard to the Bajaj bike and the

overall service experience of the bike, Correlation test was used. So, the test variables were

the overall satisfaction and the service experience. Correlation test was applied to establish

the qualitative relationship between these two variables and thereby it is possible to find the

direction of relationship between the variables.

H0: There is no relationship between the overall satisfaction with regard to the Bajaj

bike and the overall service experience of the bike

H1: There is a relationship between the overall satisfaction with regard to the Bajaj

bike and the overall service experience of the bike

The result of Correlation Analysis is given in Table 4.31

Table 4.31

Correlation between Overall Satisfaction and Service Experience

S.No Variable Correlation Value (Pearson Correlation) P value

1 Overall Satisfaction0.285** 0.002

2 Service Experience ** Correlation is significant at the 0.01 level (2-tailed).

Since p value is less than 0.01, the null hypothesis is rejected at 1% level of significance.

Hence, there is a relationship between the overall satisfaction with regard to the Bajaj bike

and the overall service experience of the bike. The Correlation square between the overall

satisfaction with regard to the Bajaj bike and the overall service experience of the bike is

0.285 which indicates 28% positive relationship between them.

Since the relationship is positive, if the Overall Satisfaction of the Bajaj bike increases then

the Satisfaction in the Service Experience of the bike also increases.

4.21 Decision regarding Buying One More Bike

Table 4.32

Future Purchase Decision

S.No Future Purchase Decision Frequency Percent

1 Choosing the same Bajaj brand 77 64.2

2 Choosing the other brand 43 35.8

3 Total 120 100.0

The decision regarding buying one more bike was depicted in the Table 4.32. It shows that

64.2% of respondents will buy the same Bajaj brand. This suggests that the maximum of

current Bajaj customers are showing the Brand Loyalty and the remaining 35.8% of

respondents are tend to possess the variety seeking buying behavior. So, this brand switching

may occurs among the customers for the sake of variety rather than because of

dissatisfaction.

4.22 Respondents’ Level of Promoting the Bajaj Brand to Others

Table 4.33

Level of promoting the Bajaj brand

S.No Level of Promotion Frequency Percent

1 Very High 15 12.5

2 High 40 33.3

3 Average 58 48.3

4 Low 4 3.3

5 Very Low 3 2.5

6 Total 120 100.0

The Table 4.33 shows that on an average 48.3% of respondents will promote the Bajaj brand

to others and the minority 2.5% of respondents will never promote the brand to others. This

result not only shows the Brand Loyalty of the customers but also shows the impact in the

word of mouth communication medium.

4.23 Test of Level of Promotion of Bajaj Brand to Others

To test the level of promoting the Bajaj brand to others is above average level at 1% level of

significance, T-Test for Single Mean was applied.

H0: The level of promoting the Bajaj brand to others is equal to average level

H1: The level of promoting the Bajaj brand to others is not equal to average level

The result of T-Test is given in Table 4.34

Table 4.34

One Sample T-Test for the level of promotion at 1% level

Test value = 3

S.No Test Variable N Mean Std. Deviation T value df P value

1 Level of Promotion 120 2.50 .850 -6.443 119 .000** Note: ** denotes significance at 1% level

Since P value is less than 0.01, the null hypothesis is rejected at 1% level of significance.

Hence it is concluded that the level of promoting the Bajaj brand to others is not equal to

average level. The Table 4.34 indicates the mean value for the variable ‘Level of Promotion’

is 2.5. It suggests that the respondent’s level of promoting the Bajaj brand is higher.

4.24 Respondents’ Level of Recommendation of Dealer to Others

Table 4.35

Level of recommendation of dealer to others

S.No Level of Recommendation Frequency Percent

1 Highly Recommend 13 10.8

2 Recommend 31 25.8

3 Neutral 57 47.5

4 Not Recommend 15 12.5

5 Highly Not Recommend 4 3.3

6 Total 120 100.0

The Table 4.35 shows that the majority 47.5% of respondents remains neutral in

recommending their dealer to others and the minority 3.3% of respondents will never ever

recommend the dealer to others.

4.25 Level of Brand Preference with respect to Educational Qualification

To test the association between the educational qualification and the level of brand

preference, Chi-Square test was applied.

H0: There is no significant association between the Educational Qualification and the

Level of Brand Preference

H1: There is a significant association between the Educational Qualification and the

Level of Brand Preference

The result of the Chi-Square Cross tabulation Analysis is given in Table 4.36

Table 4.36

Crosstabs between Educational Qualification and Brand Preference Level

S.NoEducational Qualification

FrequencyLevel of Brand Preference

TotalChi-Square

ValueP value

Low Moderate High

1 Below +2Observed 5 15 5 25

4.036 .672

Expected 6.9 11.9 6.3 25

2 +2 or DiplomaObserved 12 13 10 35

Expected 9.6 16.6 8.8 35

3 UGObserved 8 17 10 35

Expected 9.6 16.6 8.8 35

4PG & Professionals

Observed 8 12 5 25

Expected 6.9 11.9 6.3 25

5 TotalObserved 33 57 30 120

Expected 33 57 30 1200 cells (.0%) have expected count less than 5. The minimum expected count is 6.25.

Since p value is greater than 0.05 the null hypothesis is accepted at 5% level of significance.

Hence, there is no significant association between the Educational Qualification and the

Level of Brand Preference.

4.26 Level of Brand Preference with respect to the Adulthood

To test the significant difference between the adulthood with regard to the level of Brand

Preference, t-test for difference of two mean was applied. The Hypothesis was set as follows.

H0: There is no significant difference between the adulthood with regard to the level

of Brand Preference

H1: There is a significant difference between the adulthood with regard to the level of

Brand Preference

The result of Independent Sample t-Test is given in Table 4.37

Table 4.37

t-Test for Level of Brand Pref and adulthood

S.No Adulthood N Mean Std. Deviation t value p value

1 Young Adult 103 14.28 2.4753.143 .002**

2 Older Adult 17 12.24 2.562Note: ** denotes significance at 1% level

Since p value is less than 0.01 the null hypothesis is rejected at 1% level of significance on

adulthood. Hence, there is a significant difference between the adulthood with regard to the

level of Brand Preference.

The Table 4.37 indicates that the mean value of the variable ‘Older Adult’ 12.24 is the least

value. It suggests that the Brand Preference towards the Bajaj is higher with the Older Adults

than the Younger Adults.

CHAPTER 5

FINDINGS, SUGGESTION AND CONCLUSION

5.1 Findings

1. The majority 67.5% of the respondents were under 18 – 30 age group and the

minority of 15% were the age of above 43.

2. The majority 29.2% of the respondents was +2 or Diploma or UG qualified and the

minority 20.8% of the respondents was below +2 or PG & Professionals.

3. The majority 45.8% of the respondents was working in the private sector and the

minority 1.7% was working in other than the private sector, public sector, self-

employed.

4. The majority 30.8% of the respondents was earning between 5001 and 10,000 rupees

per month and the minority 6.7% of the respondents were earning between 5000 and

below.

5. The majority 60.8% of the respondents was buying the bike for the purpose of using it

for the regular work and the minority 8.3% was buying the bike for routine long trips.

6. The majority of 51 respondents ranked the mileage as the major factor which affects

the purchasing decision of the bike followed by the style and the majority of 59

respondents ranked the resale value as the minor factor which affects their purchasing

decision followed by the advertisement.

7. From the Friedman Test, it was found that atleast two of the factors which affect the

purchasing decision of the bike are significantly different from each other among the

nine different factors which includes mileage, price and style.

8. The majority 51.7% of respondents obtain information about the brand from friends

and the minority 3.3% obtain from other personal sources.

9. The majority 52.5% of respondents obtain information about the brand from the

advertisement and the minority 6.7% from displays.

10. The majority of 41.7% of respondents obtain information about the brand by handling

the product and the minority 28.3% obtain by using the product.

11. The majority 64.2% of respondents got influenced towards the Bajaj brand through

the medium of Word of Mouth Communication and the minority 8.3% of respondents

influenced through Sales Promotion.

12. The majority 51.7% of respondents preferred to buy the bike by full cash and the

minority 48.3% of respondents preferred EMI.

13. The majority 75% of respondents was the final decision maker for purchasing the bike

and the minority 0.8% of respondents’ opinion was Mother.

14. The majority 36.7% of respondents took only one week to choose the Bajaj brand to

buy the bike and the minority 15% of respondents took more than two months to

choose the Bajaj brand.

15. The Quality plays the major reason in preferring the Bajaj brand for 69.2% of

customers followed by the Availability of the product (16.7%).

16. The majority 43.3%, 35%, 37.5%, 45%, 37.5% and 38.3% of respondents are satisfied

with the price, style, color, mileage, power and performance of their bike respectively.

I was also found that the majority 37.5% and 35% of respondents are neither satisfied

nor dissatisfied with the less maintenance and technology of their bike respectively.

17. From the One Way ANOVA Test, it was found that there is a significant difference

between age group with regard to the satisfaction with the total features of the bike.

18. The majority 50% and 50.8% of respondents rated the infrastructure of the showroom

and the product availability in the showroom was good respectively. It was also found

that the majority 55%, 45.8% and 41.7% of respondents rated the after sales response

of the dealer, knowledge of the salesman and the service of the dealer was average

respectively.

19. The majority 51.7% of respondents’ opinions was high about the role of availability

of product in the selection of brand and the no response in the last two rating shows

that the importance of availability is always higher in the selection of brand.

20. The majority 40.8% of respondents’ opinions was high about their trust level on the

Bajaj brand and the no response on the ‘Very Low’ rating of the Trust Level shows

that all the respondents possess atleast some Trust on the Bajaj Brand.

21. The majority 40.8% of respondents will go to the other dealer in another region for

buying the Bajaj bike if the required brand is not available during the purchase with a

particular dealer and only the 12.5% of respondents agreed that they will change the

brand if the brand is not available during the purchase.

22. The majority 63.3%, 68.3% and 45% of respondents were satisfied with the safety,

comfort and the price of their bike respectively. The table also shows that the majority

58.3% and 53.3% of respondents were neither satisfied nor dissatisfied with the

availability of the spare parts and the price of the spare parts of their bike respectively.

23. From the Correlation Test, it was found that there is a relationship between the level

of satisfaction with regard to safety and comfort of the bike and it also indicates 52%

positive relationship between them.

24. From the One Way ANOVA Test, it was found that there is a significant difference

between age group with regard to the satisfaction with the total price of the bike and

its spare parts.

25. The majority 51.7% of respondents rated their overall service experience with regards

to their bike was Good and the minority 4.2% of respondents rated their overall

service experience with regard to their bike was Excellent.

26. The majority 51.7% of respondents were satisfied with their Bajaj bike after purchase.

27. From the Correlation Test, it was found that there is a relationship between the overall

satisfaction with regard to the Bajaj bike and the overall service experience of the bike

and it also indicates 28% positive relationship between them.

28. It was found that the 64.2% of respondents will buy the same Bajaj brand if they

involve in future purchase and the remaining 35.8% of respondents’ opinion were

buying bike from other brand.

29. It was found that on an average 48.3% of respondents will promote the Bajaj brand to

others and the minority 2.5% of respondents will never promote the brand to others.

30. From the One Sample T-Test, it was found that the level of promoting the Bajaj brand

to others is not equal to average.

31. The majority 47.5% of respondents remains neutral in recommending their dealer to

others and the minority 3.3% of respondents will never ever recommend the dealer to

others.

32. From the One Way ANOVA Test, it was found that there is a significant difference

between levels of recommendation of dealer with regard to the satisfaction with the

total showroom attributes.

33. From the Independent Sample T-Test, it was found that there is a significant

difference between the adulthood with regard to the level of Brand Preference.

34. From the Chi-Square Test, it was found that there is no significant association

between the educational qualification and the level of brand preference.

5.2 Suggestions

The study revealed that the Brand Preference for Bajaj Two Wheeler’s among

Customers in Vellore is higher among the Older Adults and the maximum of current

Bajaj customers are showing the Brand Loyalty.

The study also revealed that the major factor which influences the preference of Bajaj

brand is Mileage followed by Style and Price of the product. Bajaj brand is already

famous for its mileage and the style of the product. But, the study shows that the price

factor is only satisfied, not even with 50% of the respondents. It is because of the

higher cost of the Bajaj two wheelers. The Sales of the Bajaj two wheelers can be

increased by reducing the cost of the product which is the third major factor which

influences the Brand Preference.

Since, Style is the second major factor which influences the Brand Preference among

the customers in Vellore; Bajaj can launch its Probike ‘Ninja 250R’ in the Vellore

Showroom. The Sale of that particular product may increase in Vellore because of its

Style and the dominance of the youths in the market for the products of Bajaj brand.

Apart from budget, two most important factors in a bike are Safety and Comfort.

From the study it was discovered that more than 50% of the respondents are satisfied

with the Safety and Comfort Level of the Bajaj bike. But there are still some issues

which need to be look over in the Safety and Comfort aspects. From the open-ended

suggestion also, most of the customer’s opinion was that the Bajaj two wheelers are

lacking in those two aspects. The main aspects which the Bajaj has to concentrate are

‘Powerful Headlights’ and ‘Braking’.

The Bajaj should concentrate on the after-sale communications which provide

evidence and support to help customers feel good about their brand choices. It helps

in reducing the after-sale discomfort.

From the study, 35.8% of respondents are switching to the other brand which is only

because of variety seeking behavior rather than expressing the disloyalty. Bajaj should

launch two wheelers with different innovative features by studying the competitive

products to reduce its customer from switching to the competitive brands.

5.3 Conclusion

After the completion of this project, I’ve gained some new experience in the Field Research.

During survey, I’ve met a large number of people with different perception and behavior. It

was a great opportunity for me to learn about the customer behavior and I utilized it properly

to learn the same. From this study, it is concluded that the Brand Preference for Bajaj two

wheelers among customers is higher in Vellore. However, Bajaj may improve into a highly

trustful and preferable brand if the suggestions are incorporated. It is difficult to acquire new

customers and it is more difficult to retain the existing customers. In the case of two

wheelers, purchase is an expensive and infrequent or risky purchase where customers will

face a high-involvement decision. So, not only for the initial purchase but also to ensure the

future purchase, it is advisable to implement the suggestions to retain the customers.

A Study on Brand Preference for Bajaj Two Wheeler’s among Customers in Vellore

Name: Contact No: Age:

Educationo Below +2 o +2 or Diploma o UG o PG & ProfessionalsOccupationo Self employed o Private Sector o Public Sector o Student o OthersMonthly Income (If Student, mention your family income)o 5000 & below o 5001- 10000 o 10001-15000 o 15001-20000 o 20000 & above

1. What is the need for you to buy the bike?o Workhorse (for regular

work)o Run Errands (to do odd

jobs)o Routine Long

trips

2. Prioritize the options that affect your purchasing decision of bike.1 being the most important and 8 being the less important

□ Advertisement □ Comfort □ Mileage□ Power □ Price □ Resale Value□ Safety □ Service □ Style

3. Select the source which plays a major role in obtaining information about the brand.Source Select one from eachPersonal Source Family

FriendsNeighborsAcquaintances

Commercial Source AdvertisementSales PeopleDealersDisplays

Experimental Source HandlingExaminingUsing the product

4. What is the medium of communication that influences your brand preference?o Print Media o Electronic Media o Word of Mouth o Sales Promotion

5. Which mode of purchase do you prefer?o By Full Cash o EMI

6. Who plays the major role in decision making for purchasing the bike?o Father o Mother o Friends o Self o Others

7. What is the period you took to choose the Bajaj brand?

o One Week o One Month o Two Months o More than 2 Months8. What is the reason for preferring the Bajaj brand?

o Quality o Availability o Price o Service

9. Give points to the following features of your Bajaj product.Attribute 5 4 3 2 1PriceStyleColorMileageLess MaintenancePowerPerformanceTechnology

10. Rate the showroom attributes.Attributes Excellent Good Average Poor WorseInfrastructureAvailabilityAfter Sales ResponseKnowledge of Sales manService

11. Rate your bike on the basis of following attributes.Attribute Very High High Average Low Very Low

Role of availability in the selection of brandTrust Level on the Bajaj brand

12. What will be your reaction when Bajaj brand is not available during the purchase?o Wait for sometime o Choosing the other product category

under Bajajo Going to the other Bajaj dealer in

another regiono Choosing other brand with the same

features of the product

13. Rate your bike on the basis of following attributes.Attribute Highly

SatisfiedSatisfied Neutral Dissatisfied Highly

DissatisfiedSafetyComfortAvailability of spare partsPrice of the productPrice of the spare parts

14. How do you rate the overall service experience of your Bajaj bike?o Excellent o Very Good o Good o Okay o Poor

15. What is your overall satisfaction level with regards to the Bajaj bike?o Highly

Satisfiedo Satisfied o Neutral o Dissatisfied o Highly

Dissatisfied

16. What is your decision regarding buying one more bike?o Choosing the same Bajaj brand o Choosing the other brand

17. What is the level that you promote the Bajaj brand to others?o Very High o High o Average o Low o Very Low

18. Do you recommend your dealer to others?o Highly

Recommendo Recommend o Neutral o Not

Recommendo Highly Not

Recommend

19. What do you expect more from your bike? (Eg: New Features or other recommendations)

Date: Mode: (Signature of the Respondent)

BIBLIOGRAPHY

Books:

1. Govindarajan M, “Marketing Management – Concepts, Cases, Challenges and

Trends”, Second Edition, New Delhi, PHI Learning Private Limited, May 2009, Page

no: 89-110.

2. Kotler, Philip, “Marketing Management Millennium Edition”, New Jersey, Pearson

Education Company, 2002.

3. Ravilochanan P, “Research Methodology”, Chennai, Margham Publications, 2002,

Page no: 22.1-23.87.

Journals:

1. Niedrich, Ronald W. and Swain, Scott D, “The Influence of Pioneer Status and

Experience Order on Consumer Brand Preference: A Mediated-Effects Model”,

Journal of the Academy of Marketing Science, Volume 31, October 2003, Page no:

468-480.

2. Dr. Rajagopal, “Conational Drivers Influencing Brand Preference Among

Consumers”, 2009.

3. Purohit H C, “Customer Relationship Management and Brand Loyalty through Word

Of Mouth (WOM) Communication”, The Journal of Indian Management & Strategy,

Volume 13, Issue 3, 2008, Print ISSN: 0973-9335, Online ISSN: 0973-9343.

4. Yang, Sha, Allenby, Gerg M. and Fennel, Geraldine, “Modeling Variation in

Brand Preference: The Roles of Objective Environment and Motivating Conditions”,

Volume 21, No 1, Winter 2002, Page no: 14-31.

5. Sriram S, Chintagunta, Pradeep K and Neelamegham, Ramya, “Effects of Brand

Preference, Product Attributes, and Marketing Mix Variables in Technology Product

Markets”, 2005.

6. Chimboza, Denford and Mutandwa, Edward, “Measuring the determinants of brand

preference in a dairy product market”, African Journal of Business Management,

Volume 1, No 9, December 2007, Page no: 230-237, ISSN 1993-8233.

7. Ayanwale, Adeolu B, Alimi, Taiwo and Ayanbimipe, Matthew A, “The Influence of

Advertising on Consumer Brand Preference”, Journal of Social Science, Volume 10,

No 1, 2005, Page no: 9-16.

8. Dr. Sridhar. G, Dr. Kumar, Ramesh N and Dr. Murthy, Narasimha G, “Susceptibility

to reference group influence among rural consumers”, Metamorphosis, Volume 9, No

1, 2010.

9. Dr. Reddy, Mallikarjuna K, “Consumer behavior towards two-wheeler motor bikes”,

Department of Business Management, Osmania University, Hyderabad.

Websites:

1. http://www.lets-talk-sales.com

2. http://www.insidermedicine.com

3. http://www.udel.edu

4. http://www.brandcameo.org

5. http://en.wikipedia.org

6. http://auto.indiamart.com

7. http://business.mapsofindia.com

8. http://www.medcalc.org

9. http://www.itl.nist.gov

10. http://onlinestatbook.com

11. http://people.richland.edu

12. http://www.wellesley.edu

13. http://www.experiment-resources.com

14. http://people.richland.edu

15. http://davidmlane.com