market research project report: footwear industry differentiation

Differentiation in consumer mind about

National v/s Foreign Brand

Project Report: Advanced Methods of Marketing Research

Submitted to: Prof. Atanu Adhikari

Submitted by:

Mangesh Patil | Riddhi Biswas | Mahtaab Kajla | Makwana Ravindra Govindbhai

Parimal Kumar Shivendu | Sachin Kumar | Sudipta Mandal

Date of Submission: August 26th, 2011

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2011 © Group I | Indian Institute of Management, Kozhikode | PGP II

Advanced Methods of Marketing Research

TABLE OF CONTENTS

Introduction, problem statement and objectives ..................................................................................... 5

Introduction ........................................................................................................................................ 5

Problem Statement and Objective of the study .................................................................................... 6

Rationale of the project ................................................................................................................... 6

Objective ......................................................................................................................................... 6

Market research Problem ................................................................................................................ 6

Approach to Problem & Scope of Study ........................................................................................... 6

Recent trends & developments ............................................................................................................... 6

Objectives and detailed methodology ..................................................................................................... 7

Literature Review ................................................................................................................................ 7

Research Design .................................................................................................................................. 8

Preparatory Research ...................................................................................................................... 8

Secondary Research ......................................................................................................................... 8

Information needs ................................................................................................................................... 9

Data Collection from Secondary resources ....................................................................................... 9

Data collection from Primary resources ........................................................................................... 9

Focus Group Discussion ......................................................................................................................... 10

Particulars of Focused Group Interview ............................................................................................. 10

Discussion Questions and Answer Summary ...................................................................................... 11

Findings ............................................................................................................................................. 12

Descriptive research .......................................................................................................................... 12

Scaling techniques ......................................................................................................................... 12

Questionnaire development and Pretesting ....................................................................................... 12

Pretesting ...................................................................................................................................... 13

Sampling Technique .......................................................................................................................... 13

Fieldwork .......................................................................................................................................... 13

Data analysis Procedure ........................................................................................................................ 13

Methodology and plan ...................................................................................................................... 13

Preprocessing the data ...................................................................................................................... 13

Editing ........................................................................................................................................... 13

Coding ........................................................................................................................................... 14

Analysis of data ..................................................................................................................................... 15

Cluster Analysis ..................................................................................................................................... 15

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National Footwear Brands ................................................................................................................. 15

Variables used ............................................................................................................................... 15

Hierarchical Clustering ................................................................................................................... 15

Defining the number of clusters: elbow rule .................................................................................. 17

Defining the number of clusters: Dendrogram ............................................................................... 17

ANOVA .......................................................................................................................................... 18

Post Hoc - Scheffe .......................................................................................................................... 21

Cluster Profiling ............................................................................................................................. 23

Foreign Footwear Brands ................................................................................................................... 23

Variables used ............................................................................................................................... 23

Hierarchical Clustering ................................................................................................................... 24

DEFINING THE NUMBER OF CLUSTERS: ELBOW RULE ..................................................................... 25

Defining the number of clusters: Dendrogram ............................................................................... 26

K-Means Clustering ........................................................................................................................ 27

Multiple Regression Analysis ................................................................................................................. 29

National Brands Footwear ................................................................................................................. 29

Dependent Variable ....................................................................................................................... 29

Independent variables ................................................................................................................... 29

Estimated multiple regression equation ......................................................................................... 30

Foreign Brands Footwear ................................................................................................................... 31

Dependent Variable ....................................................................................................................... 31

Independent variables ................................................................................................................... 31

Estimated multiple regression equation ......................................................................................... 32

Factor Analysis ...................................................................................................................................... 33

National Footwear Brands ................................................................................................................. 34

Variables considered ...................................................................................................................... 34


Variables considered ...................................................................................................................... 35

Structure Equation Modeling ................................................................................................................. 36

National Footwear Brand ................................................................................................................... 37


References ............................................................................................................................................ 39

Textbook References ..................................................................................................................... 39

Web References ............................................................................................................................ 39

Database References ..................................................................................................................... 39

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Forward 2 a.m., 25th August 2010.

“Just a final review and we can submit it”, announced Sachin as we all compiled

our research gathered in bits and pieces in the past two months on this project.

The work has been a combined effort of our team and all of us have tried our

best to gather the most accurate data and information. Analysis has been based

on the available facts and data gathered from various sources, research as well

as our intuitive understanding of the various aspects of the footwear industry.

We tried to incorporate the elements of our learning in our own approach of

working as a team so as to eliminate inefficiencies and bank upon the

competencies of each individual member while allowing everyone to explore the

marches of their comprehension and creativity. This project has been a

wholesome learning experience for us and we would be glad to extend the

learning process by welcoming criticism and suggestions on our work.

AMMR Group 1

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Acknowledgement

It gives us immense pleasure to acknowledge all those who have given their time

and energy to supply all valuable facts and opinions that has helped us in

bringing out this project to fruition.

We would like to express our gratitude and respectful thanks to Prof. Atanu

Adhikari for constantly supporting and guiding us in achieving the prescribed

objectives of the research.

Finally we would like to express our thanks to all our respondents and friends

who were instrumental in the successful competition of our project.

AMMR Group 1

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INTRODUCTION, PROBLEM STATEMENT AND OBJECTIVES

INTRODUCTION

Changing lifestyles and increasing affluence are seemly to prop up the faster growth rate. To tap these

trends, flourishing domestic and foreign brands such as Nike, Adidas, Puma, Reebok, Florsheim,

Rockport, etc. have also entered into the market and on the expansion mode. Currently, India is the 2nd

largest producer of footwear in the world after China and accounts for 12.2% of the Asia-Pacific

footwear market value. Indian footwear market is highly fragmented and products are sold through

variety of channels like supermarkets, hypermarkets, discount stores, single & multi branded

showrooms, variety stores etc. As the population of India is growing at a rapid pace, India is turning to

be a lucrative market for Indian as well as Foreign footwear brands

Strength of India in the footwear sector comes from its availability of reliable supply of resources in the

form of raw hides and skins, quality finished leather, large human capital with expertise and technology

base, skilled manpower and relatively low labour cost. So the key strengths can be listed as below:

� Availability of quality raw materials

� Low labor cost

� Skilled manpower

� Technology driven

The Indian footwear market has been very robust for recent years and the market is forecast to continue

at a steady rate. The Indian footwear market had clocked $4.10 billion in 2009, with a compound annual

growth rate (CAGR) of

9.3% for the period

spanning 2005-2009

while its arch-rival China

with a CAGR of 9.6%, and

the Japanese market

declined with a CARC of -

0.7%.Clothing, footwear,

sportswear and

accessories retailers’

sales top the table in

footwear market in 2009,

with total revenues of

$3.78 billion.

Market segmentation: % Share by Value(2009)

The market was forecast to accelerate, with an anticipated CAGR of 9.4% for the next five year period

2009-2014 with a total value of $6.43 billion by the end of 2014 while the Chinese market will go up with

a CAGR of 7.9%, and the Japanese market will see the decline with a CARC of -1%, over the same period.

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PROBLEM STATEMENT AND OBJECTIVE OF THE STUDY

RATIONALE OF THE PROJECT

� With the income level rising Indian consumers are becoming more brand conscious

� While it is brand, which one National or foreign ones?

� How do brand awareness and brand image affect one’s purchasing decision?

� What are the other factors influencing the people’s purchasing intention?

OBJECTIVE

The objective of the study is to determine the attitude of consumers towards national versus foreign

footwear brands & examine their purchasing behavior.

MARKET RESEARCH PROBLEM

� What are the perceptual factors that affect consumers’ buying decision of national brand and

foreign brand?

� Is there a significant difference of effect of these dimensions on consumers’ buying decision

between national brand and foreign brand?

� Do all segments have different perceptions about these two types of brands?

� Is cultural and demographic variable plays mediating role in buying decision.

APPROACH TO PROBLEM & SCOPE OF STUDY

� Development of clusters for national and foreign footwear brands

� Finding what drives the purchase decision of National and Foreign footwear brands.

� Finding the underling purchase Intension of National and Foreign footwear brand

� Understanding the causes of associated consumer satisfaction with National and Foreign

footwear brand

RECENT TRENDS & DEVELOPMENTS

Rise of organized retailing helped the footwear industry as well. Organized retailing chains is

helping the marketers to showcase their products properly and also target the premium

segment customer who often visit these newly developed malls and multi brand retail stores.

The right positioning of products and better lighting provided the marketers with an

environment that is further stimulating sales growth.

Styling has become more important as Indians showed willingness to buy the products that

are not only good in quality but also providing them world class styling. The market has

witnessed a lot of investment by footwear manufacturers to develop new styles of products

and market them either through multi-brand stores or their own stores. Players like Liberty

Shoes Ltd actively launched new products and promoted their footwear through different

retailing channels. The focus is on improving quality and design.

Footwear in sportswear category continued to gain ground due to increase presence of

international sportswear brands such as Adidas, Nike, Puma, Reebok and Kappa. International

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brands were more popular in urban India whereas Indian brands such as Liberty, Relaxo,

Lakhani were more popular in semi-urban and rural India. Price plays a big role in the market

penetration as Indian brands were as much as 50%-60% cheaper than international brands.

Changing purchase behavior of women where they preferred to often change their footwear

according to their clothing and enjoy browsing city markets to purchase footwear from

footpaths and smaller stores it is cheaper. Women also like to buy the latest footwear and the

smaller shops with private labels provided that opportunity at the best price possible.

OBJECTIVES AND DETAILED METHODOLOGY

LITERATURE REVIEW

BRAND AWARENESS

Brand awareness can be defined as the potential capacity that a consumer has of recognizing or

recalling the name of the brand while purchasing a certain category of product. The concept of

brand awareness broadly measure the following two dimensions

� the reminded that fits with the spontaneous recall about a particular brand sans a need of

any kind of external stimulus

� the recall attended that the brand name is knowledge as an offer of a category of products

amongst a set of suggested brands

Brand awareness is an effective tool that helps to make a predominant selection of product

consumers without experience of use of the product and stops experimentation with new products

and brands (Hoyer& Brown, 1990). Thus brand awareness acts just as an antecedent to the creation

of brand image are in the origin of (Keller, 1993). These two equally influence a consumer to build

an assured image in their minds and take a final call in purchase.

The following hypotheses are made:

H1a: The innovativeness dimension has a positive relationship with brand awareness in

footwear industry.

H1b: The design dimension has a positive relationship with brand awareness footwear

industry.

H1c: The prestige dimension has a positive relationship with brand awareness in the

footwear industry.

H1d: The workmanship dimension has a positive relationship with brand awareness in the

footwear industry

H1e: Brand awareness has a positive relationship with brand image and purchasing

intentions

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BRAND IMAGE

Kotler defined that “A brand is a name, term, design, symbol, or other feature that distinguishes

products and services from competitive offerings”. As per the Aaker’s definition, the brand is a

specific name or mark, and can be used for distinguishing with competitor's products and servers. A

research has shown that a brand image should be based on brand concept-image, which can be

built in the following three benefits:

� Functional: actual benefits from using a product or service, concentrating on satisfying

consumers’ basic needs.

� Symbolic: added value of a product or services, stressing the ability to fulfill consumers’

inner needs and self-image

� Experiential: subjective experience from using the product or service. The brand image is

important in marketing because the brand image is considered as the clue of a kind of

information

PURCHASE INTENTION

Purchase intention means probably attempting to buy a product. According to Kotler, “consumer

behavior occurs when consumers are stimulated by external factors and come to a purchase

decision based on their personal characteristics and decision making process.” These factors take

note of choosing a product, brand, a retailer, timing, and quantity. This means consumers’

purchasing behavior is triggered by their choice of product and brand. Consumers’ purchase

intentions are always preceded by consumer perceived value and perceived benefit. Hence, the

research chooses purchasing intention to be a good indicator of consumers making a buying

decision and help to understand whether or not the brand image will significantly influence

consumer’s purchasing intention. Study shown that people comparatively purchase those with

which they are familiar and the products with good brand image because the good brand image

can make one feel at ease and reliable.

RESEARCH DESIGN

PREPARATORY RESEARCH

The research was started with preparatory research. We have explored many resources about footwear

industry which included previous marketing research reports on footwear industry and prominent

websites from where we were able to get Macroeconomic Information, Demographic Information as

well as Company Profiles which has enabled us to build a quite accurate market overview.

SECONDARY RESEARCH

After the first step we conducted secondary research that ensured us that we were always fully up-to-

date with the latest industry events and trends, aggregates and analyzes a number of secondary

information sources during our research that includes:

� National/Governmental statistics

� International data (official international sources)

� National and International trade associations

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� Broker and analyst reports

� Company Annual Reports

� Business information libraries and databases

After the second step, which involved the collection of secondary data, we collected Primary data by

directly interviewing various segments of population and conducting a focus group discussion. The type

of questions asked while collecting primary data was mostly open ended.

After the above 2 steps, we designed a comprehensive Questionnaire which was going to be our primary

source of Data collection.

Link to questionnaire is

https://spreadsheets3.google.com/spreadsheet/viewform?hl=en_US&formkey=dHdpUkJWTGVFa1ZyRm

ZyR3BtMzZiVFE6MQ#gid=0

INFORMATION NEEDS

The information needed for the project is related to the essential factors for customers influencing their

purchasing behavior. We needed the importance they assign to each of those essential factors while

selecting a footwear brand. We also required the perceptions of customers about foreign brands and

national brands judging on those factors.

DATA COLLECTION FROM SECONDARY RESOURCES

A huge amount of secondary resources about the footwear sector were available on the web. We have

taken the help of previous marketing research reports on this industry to know the most essential

factors influencing the purchasing behavior.

This provided us a basic overview of the factors that play a significant role in buying behavior of

consumers.

DATA COLLECTION FROM PRIMARY RESOURCES

We have interviewed various segments of the people in depth to know their preferences regarding the

purchase decisions to select a footwear brand. We have also used an online spreadsheet to interview

people of various income groups and involved in various occupations. From FGD: Quality, Durability,

Availability, Price and Design/fashion came out to be important criterion on which people judge brands

whether National or Foreign.

Our objective of exploratory research is to find the questions that need to be included in the

questionnaire for descriptive research.

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FOCUS GROUP DISCUSSION

PARTICULARS OF FOCUSED GROUP INTERVIEW

THEME

We tried to understand whether consumers perceive any differentiation between Local and Foreign

brand. If yes on which parameters differentiation occurs.

MODERATOR

Parimal Kumar Shivendu (PGP/14/285)

PARTICIPANT DEMOGRAPHY

� Age Group: 25-30 years

� Occupation: Currently Students with some had prior work experience

� Gender: Male and Female

� Income: High to moderate

� Education: Graduates

PARTICIPANTS BRIEF PROFILE

1. Name: Kirti Saxena

Profession: Student, PGP15, IIM Kozhikode

2. Name: Arnab Guha Mallik


3. Name: Atul Sharma


4. Name: Mansi Vora


5. Name: Hersh Kenkare


6. Name: Sameer Ahmad


TIME-DATE-PLACE STAMP

• Date: 20/07/2011

• Time: 9:30-10:30 PM

• Place: IIM Kozhikode

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DISCUSSION QUESTIONS AND ANSWER SUMMARY

Q1. Is there any differentiation in the mind of consumers when it comes to foreign and National brand

(Apparel Brand)?

- All agreed that this kind of differentiation doesn’t occur at least in apparel brands. It’s more about

brand image that is not created by nationality.

Q2. Given that the price, quality and other parameters are same for two brands and you know that

one Brand is National and other is a foreign brand will you will go for National Brand?

- Respondents agreed that brand image rules and it doesn’t matter whether it’s a National or Foreign

brand. They said “Availability” is important criteria which influences their buying decision.

Q3. On what parameters do you decide to go for a particular brand?

- Following answers came out:

a. Quality : All agreed

b. Durability: All Agreed

c. Design/Fashion: All Female Respondents Agreed but Male respondent were Indifferent

d. Price: All Agreed.

One thing that came out was that a Brand is a package of all the above mentioned traits.

Q4. Does Occasions influence purchase of national or foreign brands?

- Here the important outcome was that respondents agreed that local brands rather national brands

as such are preferred in special occasions. Like in “Durga Puja”, people prefer to buy clothes from

local branded shops for traditional wear.

Q5. Do we repeat ourselves when it comes to purchasing form a particular brand?

- Respondents agreed that most often than not repeat doesn’t happen, people often look for

something new if they don’t find then they repeat themselves.

- Few agreed that the brand they like will be given first shot.

- What is near prevails (Availability) unless until it’s a very special occasion.

- High value Items get repeat purchase.

Q6. Do your parents (to get insight into purchasing decision of Old Aged people) show some kind of

Brand Loyalty?

- Mostly respondents agreed that parents were more quality and price conscious and brand

awareness itself is lacking in them leave apart the loyalty.

Q7. Do we associate ourselves National Brands with our patriotic feelings?

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- All Respondents said no.

Q8. Is there any difference when you purchase for yourself and when you purchase for others (Like

Gift)?

- All respondents agreed that they are very brand conscious when they purchase for others.

FINDINGS

Following were the important findings of the meeting:

� There is no differentiation as far as National and foreign brands are concerned especially in

Apparel segment.

� Quality, Durability, Availability, Price and Design/fashion came out to be important criterion on

which people judge brands whether National or Foreign.

� People don’t associate any patriotism with National Brand.

� People are more conscious about brands when they purchase for others.

� Repeat (Brand Loyalty) doesn’t happen as people often look for something new if they don’t find

then they repeat themselves. Sometime people do give the brand they like the first shot. But

then what is near prevails (Availability) unless until it’s a very special occasion.

� Certain occasion (Occasions with traditional value like “Puja”) do prompt purchase from local

brands but nothing about national brands.

DESCRIPTIVE RESEARCH We prepared a comprehensive questionnaire using the inputs of preparatory and exploratory research.

The soft copies of the surveys were mailed to various sections of the people. We have distributed the

hard copies of the questionnaire to the people by physical access like students of NIT, Calicut.

The questionnaire was a prepared exhaustively as this is the primary source of data collection for the

project. The questions were designed to do a comparative study between the footwear brands available

in. The questions helped us to know their perceptions about national and international footwear brands.

SCALING TECHNIQUES

For our questionnaire, we have asked the users to rank the factors in the order of importance. The users

were asked to rank their preference for Quality, Durability, Availability, Price and Design/fashion on

national and international footwear brands. This design facilitated us to do the comparative study easily.

QUESTIONNAIRE DEVELOPMENT AND PRETESTING

The primary objective behind the FGD was to know what factors influence consumers’ buying behavior

and the objective of questionnaire development was to carry the research further from the information

that we obtained from FGD summary i.e. how much each factor is responsible, later on to do a

comparative study of national and international footwear brands.

The questionnaire was prepared exhaustively .At the same time; we have kept in mind that it should not

be too lengthy. We have asked the users to rank the factors only on likert scale. We made all the

questions to be answerable by everybody. We have ensured that all the questions are easily

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understandable and simple. Ambiguous words in the questions were avoided. We have made sure that

the questions were framed in the most polite language possible.

PRETESTING

The pretesting was done with some selected contacts and friends. Minor modifications were done based

on the feedback provided by them. We have eliminated some questions, which were redundant and

reduced the size of the questionnaire. We made sure that the brand related information is at the first

page of questionnaire and second page consists of demographic information about consumers after the

feedback received.

SAMPLING TECHNIQUE

The target population comprises of all the online users that can be approached along with distributing

hard copies to individuals from NIT Calicut and IIM Kozhikode. We have selected our samples from

individuals residing pan India; accessibility was accomplished by uploading an online questionnaire.

We have used a combination of Quota sampling and convenience sampling. The convenience sampling

was adopted for ease of administering and analyzing. As majority of Indian population is below the age

of 30 years, we ensured that our samples comprise of that section in majority. Certain limitations were

also taken into consideration while selecting these two techniques.

We have taken care to reduce the bias arising out of these techniques .We have not only included our

friends in the samples but made sure that samples contain diversified set of people who are not our

friends. We have taken the help of social networking sites to do this.

FIELDWORK

We have mailed the soft copies of questionnaires to most of the contacts. We also made use of certain

social networking sites like orkut, face book to get the questionnaires answered. We have met the

people of IIM Kozhikode and NIT Calicut to distribute the hard copies of questionnaires filled.

DATA ANALYSIS PROCEDURE

METHODOLOGY AND PLAN The data collated from the survey was categorically input into data analytic software SPSS and AMOS.

Using the tool, specific feature variables were defined and details from the survey were transferred into

the software.

PREPROCESSING THE DATA

EDITING

We have eliminated the responses, which were obviously incorrect. To ensure consistency of the

responses we have considered the best five criteria selected by the users. (As some users entered

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inconsistent information corresponding to the criteria as essential or missed answering some of the

questions)

CODING

Users were asked to rank the factors in the order of importance. We have converted the rank into the

score. The scores are assigned according to the table below

RANK SCORE ASSIGNED

1 1

2 2

3 3

4 4

5 5

We have prepared a codebook, which contains the code we used for each variable and item of data in

each question

The codebook was used as reference while doing the data analysis.

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ANALYSIS OF DATA

CLUSTER ANALYSIS

Cluster analysis is a technique which is used to classify cases into groups which are relatively

homogeneous within themselves and heterogeneous between each other, on the given set of variables.

The formed groups are termed as clusters. We have chosen this technique as we wanted to:

• understand buyer behaviour

• identify the new product opportunities

• clustering of consumers according to their attribute preferences

• reduction of data

The clustering procedures that we have used are:

a) Hierarchical procedures

• Agglomerative (start from n clusters, to get to 1 cluster)

• Divisive (start from 1 cluster, to get to n cluster)

b) Non hierarchical procedures

• K-means clustering

NATIONAL FOOTWEAR BRANDS

VARIABLES USED

X3-What attributes do you consider most important while purchasing National Branded Footwear?

[Quality]


[Packaging]


[Price]


[Durability]


[Fashion]


[Availability]

HIERARCHICAL CLUSTERING

The purpose of hierarchical clustering is

to identify a cluster solution or small

number of cluster solutions that could be

analyzed by the hierarchical procedures

to identify a single final cluster solution.

In this approach, we would capitalize on

the strengths of hierarchical process that

is its ability to evaluate large number of

solutions & ease of comparison among

Case Processing Summarya,b

Cases

Valid Missing Total

N Percent N Percent N Percent

41 100.0 0 .0 41 100.0

a. Squared Euclidean Distance used b. Ward Linkage

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cluster solutions while leaving the final selection of the best cluster solution to none hierarchical

procedures.

Agglomeration Schedule

Stage

Cluster Combined

Coefficients

Stage Cluster First Appears

Next Stage Cluster 1 Cluster 2 Cluster 1 Cluster 2

1 15 29 .000 0 0 8

2 23 26 .000 0 0 16

3 25 34 .500 0 0 9

4 7 33 1.000 0 0 19

5 30 31 1.500 0 0 18

6 5 21 2.000 0 0 10

7 13 16 2.500 0 0 33

8 15 19 3.167 1 0 21

9 8 25 4.000 0 3 30

10 5 20 4.833 6 0 21

11 18 41 5.833 0 0 20

12 36 39 6.833 0 0 30

13 22 38 7.833 0 0 15

14 24 32 8.833 0 0 28

15 3 22 9.833 0 13 31

16 17 23 11.167 0 2 27

17 2 35 12.667 0 0 24

18 6 30 14.167 0 5 29

19 7 10 15.667 4 0 25

20 9 18 17.333 0 11 25

21 5 15 19.333 10 8 26

22 37 40 21.833 0 0 36

23 11 27 24.333 0 0 35

24 2 12 26.833 17 0 33

25 7 9 29.500 19 20 34

26 5 14 32.357 21 0 29

27 17 28 35.274 16 0 31

28 4 24 38.274 0 14 37

29 5 6 42.317 26 18 35

30 8 36 46.383 9 12 34

31 3 17 50.705 15 27 32

32 1 3 55.258 0 31 39

33 2 13 59.958 24 7 36

34 7 8 67.134 25 30 38

35 5 11 75.234 29 23 37

36 2 37 84.963 33 22 39

37 4 5 96.529 28 35 38

38 4 7 113.746 37 34 40

39 1 2 138.392 32 36 40

40 1 4 185.366 39 38 0

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DEFINING THE NUMBER OF CLUSTERS: ELBOW RULE

The agglomeration coefficient is particularly useful in determining the number of clusters. Small

coefficients indicate that fairly homogemous clusters are being merged. In contrast when the two

different clusters are joined it results in a large coefficient. Each combination of clusters results in

increased heterogenity, so we focus on large percentage in coefficient. There is a sudden kick in the

coefficients of agglomeration schedule which would help us to determine the number of clusters that

can be defined. Given below is the scree diagram plotted through MS Excel which shows that the

sudden jump in the values of coefficient is at 39th step. So, the number of clusters would be 41-39 = 2

clusters.

DEFINING THE NUMBER OF CLUSTERS: DENDROGRAM

� At the last 3 stages of dendrogram, the

clusters are being combined at large

distances.

� Therefore it appears that 3 cluster

solutions is appropriate.

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ANOVA

From the ANOVA table, we can conclude that for F test, there are three variables i.e.

� X4[Packaging]

� X5[Price]

� X8[Availability],

Which are not

significant, so our

assumption of two

clusters solution is

not the best.

So the numbers of

clusters in analysis

were increased to

3 and were

accepted when

the ANOVA was carried out because only the variable X5 was insignificant but rest were significant.

Hence below is given the ANOVA table for 3 clusters which clearly depicts that all the variables for F test

are significant.

ANOVA

Cluster Error

F Sig. Mean Square df Mean Square df

X3 7.062 2 .273 38 25.897 .000

X4 4.493 2 .617 38 7.281 .002

X5 1.678 2 .569 38 2.950 .064

X6 4.096 2 .404 38 10.127 .000

X7 17.887 2 .480 38 37.293 .000

X8 4.713 2 .434 38 10.870 .000

Once the clusters are joined, they are never separated in the clustering process. We have selected

Ward’s method to aggregate the clusters with minimum distances one by one, still the non-hierarchical

clustering methods hold the advantage of being able to optimize the clustering solution by reassigning

observations until minimum heterogeneity within the clusters is achieved. Thus the primary element of

using non-hierarchical technique is to improve the results from hierarchical procedure.

ANOVA

Cluster Error


X3 16.919 1 .194 39 87.182 .000

X4 1.873 1 .784 39 2.390 .130

X5 1.172 1 .610 39 1.920 .174

X6 6.669 1 .433 39 15.397 .000

X7 32.559 1 .550 39 59.222 .000

X8 .003 1 .664 39 .004 .947

The F tests should be used only for descriptive purposes because the clusters have been chosen to maximize the differences among cases in different clusters. The observed significance levels are not corrected for this and thus cannot be interpreted as tests of the hypothesis that the cluster means are equal.

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Number of Cases in each Cluster

Cluster 1 12.000

2 21.000

3 8.000

Valid 41.000

Missing .000

Final Cluster Centers

Cluster

1 2 3

X3 4 3 4

X4 4 3 2

X5 4 4 4

X6 4 3 4

X7 4 2 4

X8 4 4 3

Iteration Historya

Iteration

Change in Cluster Centers

1 2 3

1 2.306 2.616 2.093

2 .137 .172 .243

3 .180 .115 .277

4 .000 .000 .000

a. Convergence achieved due to no or small change in cluster centers. The maximum absolute coordinate change for any center is .000. The current iteration is 4. The minimum distance between initial centers is 5.292.

If we closely check the clusters, we can make the following observations,

1) Cluster 1consists of 12 people who give high emphasis on quality, durability, fashion & availability.

They give moderate emphasis on packaging.

2) Cluster 2 consists of 21 people who have high preference for quality & moderate preference for

fashion & low preference for packaging

3) Cluster 3 consists of 8 people who have high preference for durability & availability. But they have low

preference for packaging & fashion.

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The table is divided into between the group effects and within the group effects. The between the group

effect is overall experimental effect.

In this we can see that the SSM

(Total sum of squares for model) for

Quality is 5.364. The SSM gives the

total experimental effect whereas

mean square for the model has

average experimental effect. The

table tells us how unsystematic

variation exists.

The test whether the group means

are same or not are given as F-test

ratio which is computed as

F-ratio = 5.364/.362 = 14.814

The final value with significance

level tells us if this event can occur by chance, but here p ≤ .05. This we can say that the effect of quality

between three groups is significantly different. We don’t know which group mean is significantly

different, but that is indicated through Post-Hoc. X6 Durability, X7 Fashion, X8 Availability can be

analyzed on similar line. But consider X4 i.e. Packaging where the SSM (Total sum of squares for model)

is 2.260.

The test whether the group means are same or not are given as F-test ratio which is computed as

F-ratio = 2.260/.735 = 3.076

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The final value with significance level tells us if this event can occur by chance, but here p ≥.05. This we

can say that the effect of quality between three groups is not significantly different.

POST HOC - SCHEFFE

Multiple Comparisons

Scheffe Dependent Variable

(I) Ward Method

(J) Ward Method

Mean Difference (I-J) Std. Error Sig.

95% Confidence Interval

Lower Bound Upper Bound

X3 1 2 .625 .311 .147 -.17 1.42

3 1.279* .243 .000 .66 1.90

2 1 -.625 .311 .147 -1.42 .17

3 .654* .256 .050 .00 1.31

3 1 -1.279* .243 .000 -1.90 -.66

2 -.654* .256 .050 -1.31 .00

X4 1 2 1.089 .444 .061 -.04 2.22

3 .606 .347 .230 -.28 1.49

2 1 -1.089 .444 .061 -2.22 .04

3 -.484 .365 .424 -1.41 .45

3 1 -.606 .347 .230 -1.49 .28

2 .484 .365 .424 -.45 1.41

X6 1 2 1.196* .335 .004 .34 2.05

3 1.048* .262 .001 .38 1.72

2 1 -1.196* .335 .004 -2.05 -.34

3 -.148 .276 .866 -.85 .55

3 1 -1.048* .262 .001 -1.72 -.38

2 .148 .276 .866 -.55 .85

X7 1 2 .643 .360 .216 -.27 1.56

3 2.192* .281 .000 1.48 2.91

2 1 -.643 .360 .216 -1.56 .27

3 1.549* .296 .000 .79 2.30

3 1 -2.192* .281 .000 -2.91 -1.48

2 -1.549* .296 .000 -2.30 -.79

X8 1 2 1.500* .346 .000 .62 2.38

3 .462 .270 .245 -.23 1.15

2 1 -1.500* .346 .000 -2.38 -.62

3 -1.038* .284 .003 -1.76 -.31

3 1 -.462 .270 .245 -1.15 .23

2 1.038* .284 .003 .31 1.76

*. The mean difference is significant at the 0.05 level.

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Scheffe multiple comparisons show that:

� For Quality(X3) group means of cluster 1 and cluster 2 are insignificant.

� For Packaging(X4) the three group means are not significantly from each other

� For Durability(X6) except cluster 2 and 3 the other groups are significantly different from each

other

� For Fashion (X7) mean of cluster 3 is significantly different from 1 & 2 but means of cluster 1 & 2

are similar

ANOVA

Sum of Squares df Mean Square F Sig.

X33 Between Groups .345 2 .172 2.006 .039

Within Groups 3.265 38 .086 Total 3.610 40

X35 Between Groups .905 2 .453 1.485 .029


X36 Between Groups 3.873 2 1.936 2.811 .043


X37 Between Groups .014 2 .007 .278 .019

Within Groups .962 38 .025 Total .976 40

X38 Between Groups .384 2 .192 .656 .004


From Scheffe’s Test,

Group 1 corresponds to Best Attributes

Group 2 corresponds to Moderate Attributes

Group 3 corresponds to Low Attributes

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CLUSTER PROFILING

Group 1: 19.5% of the females who mostly are students who fall in the income bracket of 0-2 lakhs &

are single reside mostly in city

Group 2: 17% of the females who mostly are students but may also be employed who fall in the income

bracket of 0-2 lakhs & are single reside mostly in towns.

Group 3: 63% of the males who mostly are also employed who fall in the income bracket of greater than

4 lakhs & mostly are single reside in cities.

FOREIGN FOOTWEAR BRANDS

VARIABLES USED

X9-What attributes do you consider most important while purchasing Foreign Branded Footwear?

[Quality]


[Packaging]


[Price]


X13-What attributes do you consider most important while purchasing Foreign Branded Footwear? [Durability] X14-What attributes do you consider most important while purchasing Foreign Branded Footwear?

[Availability]

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HIERARCHICAL CLUSTERING

Agglomeration Schedule

Stage

Cluster Combined

Coefficients

Stage Cluster First Appears

Next Stage Cluster 1 Cluster 2 Cluster 1 Cluster 2

1 24 41 .500 0 0 14

2 12 20 1.000 0 0 27

3 7 14 1.500 0 0 24

4 37 40 2.500 0 0 16

5 36 39 3.500 0 0 19

6 15 38 4.500 0 0 31

7 25 31 5.500 0 0 17

8 4 30 6.500 0 0 22

9 23 28 7.500 0 0 26

10 10 18 8.500 0 0 20

11 6 11 9.500 0 0 18

12 2 5 10.500 0 0 21

13 13 26 12.000 0 0 23

14 19 24 13.500 0 1 33

15 3 22 15.000 0 0 26

16 35 37 16.667 0 4 32

17 25 29 18.333 7 0 20

18 6 9 20.000 11 0 24

19 16 36 22.333 0 5 35

20 10 25 24.667 10 17 27

21 2 21 27.000 12 0 29

22 4 8 29.333 8 0 33

23 13 17 31.833 13 0 30

24 6 7 34.667 18 3 28

25 1 32 37.667 0 0 39

26 3 23 40.917 15 9 30

27 10 12 44.702 20 2 31

28 6 34 48.536 24 0 34

29 2 33 52.452 21 0 36

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30 3 13 56.417 26 23 35

31 10 15 60.464 27 6 34

32 27 35 65.548 0 16 38

33 4 19 72.881 22 14 37

34 6 10 80.914 28 31 36

35 3 16 89.367 30 19 37

36 2 6 101.548 29 34 38

37 3 4 114.194 35 33 40

38 2 27 147.291 36 32 39

39 1 2 192.332 25 38 40

40 1 3 259.854 39 37 0

DEFINING THE NUMBER OF CLUSTERS: ELBOW RULE

Given below is the scree diagram plotted through MS Excel which shows that the sudden jump in the

values of coefficient is at 38th step. So, the number of clusters would be 41-38 = 3 clusters.

At the last two stages of dendrogram, the clusters are being combined at large distances. Therefore it

appears that 3 cluster solution is appropriate.

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031323334353637383940

The scree diagram

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DEFINING THE NUMBER OF CLUSTERS: DENDROGRAM

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K-MEANS CLUSTERING

We will now use K-Means Clustering technique is to improve the results from hierarchical procedure.

ANOVA

Cluster Error


X9 8.666 2 .502 38 17.279 .000

X10 11.880 2 1.005 38 11.820 .000

X11 16.129 2 .757 38 21.306 .000

X12 7.507 2 .495 38 15.180 .000

X13 9.165 2 .389 38 23.545 .000

X14 4.064 2 .669 38 6.072 .005

.

Final Cluster Centers

Cluster

1 2 3

X9 2 4 5

X10 2 3 4

X11 2 2 4

X12 2 4 4

X13 2 4 5

X14 2 3 4

If we closely check the clusters, we can make the following observations (considering post hoc test),

1) Cluster 1consists of 2 people who give low preference for all the attributes.

2) Cluster 2 consists of 24 people who have high emphasis for durability while moderate preference for

all other attributes.

3) Cluster 3 consists of 15 people who have moderate preference for availability but high preference for

all other attributes.

Number of Cases in each

Cluster

Cluster 1 2.000

2 24.000

3 15.000

Valid 41.000

Missing .000

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The table is divided into between the group effects and within the group effects. The between the group

effect is overall experimental effect. In this we can see that the SSM (Total sum of squares for model) for

Quality is 5.364. The SSM gives the total experimental effect whereas mean square for the model has

average experimental effect. The table tells us how unsystematic variation exists.


F-ratio = 5.364/.362 = 14.814

The final value with significance level tells us if this event can occur by chance, but here p ≤ .05. This we

can say that the effect of quality between three groups is significantly different. We don’t know which

group mean is significantly different, but that is indicated through Post-Hoc.X6 Durability, X7 Fashion, X8

Availability can be analyzed on similar line. But consider X4 i.e. Packaging where the SSM (Total sum of

squares for model) is 2.260.


F-ratio = 2.260/.735 = 3.076

The final value with significance level tells us if this event can occur by chance, but here p ≥.05. This we

can say that the effect of quality between three groups is not significantly different.

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MULTIPLE REGRESSION ANALYSIS

Regression produces a best-fit line to predict dependent variable from independent variable

The multiple regression model is:

y = b0 + b1x1 + b2x2 + . . . + bpxp + e

� b0, b1, b2, . . . , bp are the parameters.

� “e” is a random variable called the error term.

In the Simple Linear Regression, the conditional mean of Y depends on X. The Multiple Regression

Model extends this idea to include more than one independent variable.

- We have chosen different independent variables which can affect the buying decision of National and

Foreign brands footwear

NATIONAL BRANDS FOOTWEAR

DEPENDENT VARIABLE

X2-How often do you buy national brand footwear?

INDEPENDENT VARIABLES

1) X29: How much extra would you like to pay for Foreign Footwear brands as compare to National Footwear brands given that you perceive both has got no difference but price?

2) X32-On special occasions would you go for National Brand or Foreign Brand? 3) X33-Sex

4) X34-Age

5) X36-Income Bracket

6) X37-Marital Status

7) X38-Living In city/town/village?

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From the regression output we can see that regression between these independent and dependent

variable is significant (<5%)

ESTIMATED MULTIPLE REGRESSION EQUATION

E(y) = (-0.297)*X38+ (-0.14)*X33+ (0.009)*X34+ (-0.180)*X36+ (-0.531)*X37+ (-0.495)*X32+

(0.125)*X29+ e

Since only two independent variables (X32 and X36) are significant for this dependent variable, hence

the correct estimated multiple regression equation would be:

E(y) = (-0.180)*X36+ (-0.495)*X32 + e

Other factors are not much significant to consider into regression equation.

From coefficients table we can see that special occasions and Income bracket are the most dominant

factor in deciding the frequency of purchase of national brand.

We can see that there is a high amount of correlation exists between these variables.

• X36(Income) is -vely correlated with frequency of purchase of national branded footwear.

• X32(Special events) is –vely correlated frequency of purchase of national branded footwear.

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Points clustered closely around a line show a strong correlation. The line is a good predictor (good fit)

with the data. The more spread out the points, the weaker the correlation, and the less good the fit.

The line is a REGRESSSION line (Y = bX + a)

Hence we can see that there is a high amount of correlation exists between these two variables.

FOREIGN BRANDS FOOTWEAR

DEPENDENT VARIABLE

X2-How often do you buy foreign brand footwear?

INDEPENDENT VARIABLES

1) X29: How much extra would you like to pay for Foreign Footwear brands as compare to National Footwear brands given that you perceive both has got no difference but price?

2) X32-On special occasions would you go for National Brand or Foreign Brand? 3) Sex

4) Age

5) Income Bracket

6) Marital Status

7) Living In city/town/village?

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From the regression output we can see that regression between these independent and dependent

variable is significant (<5%)

ESTIMATED MULTIPLE REGRESSION EQUATION

E(y) = (-0.455)*X38+ (-0.405)*X33+ (0.013)*X34+ (0.115)*X36+ (-0.524)*X37+ (0.449)*X32+

(0.117)*X29+ e

Since only two independent variables (X32 and X36) are significant for this dependent variable, hence

the correct estimated multiple regression equation would be:

E(y) = (-0.455)*X38+ (0.449)*X32 + e

Other factors are not much significant to consider into regression equation.

From coefficients table we can see that special occasions and living in city/village or town (place) is the

most dominant factor in deciding the frequency of purchase of foreign brand.

We can see that there is a high amount of correlation exists between these variables.

• X38(Living in) is -vely correlated with frequency of purchase of foreign branded footwear.

• X32(Special events) is +vely correlated frequency of purchase of foreign branded footwear.

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We can see that there is a high amount of correlation exists between these two variables.

INFERENCE

� Income motivates consumers to buy foreign brands footwear

� On special occasions consumers prefer foreign brands instead of national brands footwear

� Location of consumers also motivates them to go for national or foreign brands

o Village/Town: Mostly go for National brands

o City: Large population go for Foreign brands

FACTOR ANALYSIS

It is statistical technique that analyzes the relationship among a large number of variables to determine

a set of common underlying dimensions

Conditions for Factor Analysis

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NATIONAL FOOTWEAR BRANDS

We will do factor analysis to find out the most critical factors which influences consumers purchasing

decision of national brands of footwear.

VARIABLES CONSIDERED

X3: [Quality of national brands]

X4: [Packaging of national brands]

X5: [Price of national brands]

X6: [Durability of national brands]

X7: [Fashion of national brands]

X8: [Availability of national brands]

X19: [Chances of recommending national brands to others]

X24: [Satisfaction with quality of national brands]

X25: [Satisfaction with purchase experience of national brands]

X26: [Satisfaction with usage experience of national brands]

X27: [Satisfaction with quality of national brands] [Price]

As from left-hand table we see The Bertlett’s

test passed, the Chi-square value is low and

KMO stats > 0.5 so we say that factor analysis

is feasible for the given dataset.

From Total Variance Explained table we find First four factors cumulative squared loading is higher than

60 so we consider four main factors exist.

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From right-hand table we conclude

� Factor 1 has high coefficients for variables

X24,X25,X26,X27 hence we can label this

factor as “product satisfaction”


X3,X6,X7 hence we can label this factor as

“value for money”



“economical”

� Factor4 has high coefficient for variable

X19 hence we can label this factor as

“brand loyalty”

From above analysis we conclude that consumers purchasing intention for national brand is influenced

by “value for money”, “product satisfaction”, “economical” and “brand loyalty”.


We will do factor analysis to find out the most critical factors which influences consumers purchasing

decision of foreign brands of footwear.

VARIABLES CONSIDERED

X9: [Quality of foreign brands]

X10: [Packaging of foreign brands]

X11: [Price of foreign brands]

X12: [Fashion of foreign brands]

X13: [Durability of foreign brands]

X14: [Availability of foreign brands]

X18: [Chances of recommending foreign brands to others]

X20: [Satisfaction with quality of foreign brands]

X21: [Satisfaction with purchase experience of foreign brands]

X22: [Satisfaction with usage experience of foreign brands]

X23: [Satisfaction with quality of foreign brands] [Price]

As from left-hand table we see The

Bertlett’s test passed, the Chi-square

value is low and KMO stats > 0.5 so we

say that factor analysis is feasible for

the given dataset.

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From above right-hand table we find First three factors cumulative squared loading is higher than 60 so

we consider four main factors exist.

From the left-hand table we conclude



“product satisfaction”



“value for money”



“brand image”

From above analysis we conclude that Consumers

purchasing intention for foreign brand is

influenced by “brand image”, “value for money”

and “product satisfaction”

STRUCTURE EQUATION MODELING

Structural equation modeling (SEM) is a statistical technique for testing and estimating causal relations.

SEM is a two- step process:

1. Confirm Measurement Model (CFA)

2. Evaluate Hypothesized Relationships (SEM)

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NATIONAL FOOTWEAR BRAND

Now we propose a model that

consumer’s product satisfaction (PS) for

national brand footwear is influenced by

product’s value for money (VFM) and

how economical (Eco) it is.

We will try to confirm this using CFA and

SEM.

THE ANALYSIS

From the goodness-of-fit test of the

model we find out

• Chi-square=35.3, CMIN/DF= .102

(<2) hence we can say the model

is a good fit

• GFI= .851, TLI= .965(>.9), CFI= .975

(>.9)and RMSEA= 0.05 (.08) hence it

confirms model is good fit

From test of validity we find out

• AVE for PS and VFM > .5 but for Eco <.5 ,so model is not convergent valid

• AVE for all constraints are greater than inter-construct correlation squared , so model is

discriminant valid

From test of reliability we find out

• CF for PS and VFM > .7 but for Eco <.7 , so model is not fully reliable

As there was no option of improving the model as all metrices for improvement were showing

good results already. Although model was a good fit and discriminant valid it was not

convergent valid or reliable.

We conclude consumer’s product satisfaction for national brands is strongly influenced by product’s

value for money but they are not so price sensitive for national brands.

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Now we propose a model that consumer’s

product satisfaction (PS) for foreign brand

footwear is influenced by product’s value

for money (VFM) and brand image (BI).

We will try to confirm this using CFA and

SEM.

THE ANALYSIS

From the goodness-of-fit test of the

model we find out

• Chi-square=24, CMIN/DF= 1.001 (<2)

hence we can say the model is a good fit

• GFI= .887(~.9), TLI= .778, CFI=

1.00(>.9)and RMSEA= 0.005 (.08) hence it

confirms model is good fit

From test of validity we find out

• AVE for PS and VFM > .5 but for BI <.5 ,so model is not convergent valid

• Both inter-construct correlation squared for BI are greater than AVE , so model is was not

discriminant valid

From test of reliability we find out

• CF for PS and VFM > .7 but for BI <.7 , so model is not fully reliable

As there was no option of improving the model as all metrices for improvement were showing

good results already. Although model was a good fit it was not convergent valid nor discriminant

valid nor reliable.

We conclude consumer’s product satisfaction for foreign brands is strongly influenced by product’s

value for money but brand image does not influence it.

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REFERENCES

TEXTBOOK REFERENCES

� Marketing Research – 6e, An Applied Orientation – Naresh K Malhotra, Satyabhushan

Dash

� Multivariate Data Analysis – 6e – Hair, Black, Babin, Anderson, Tatham

WEB REFERENCES

� A journal by Angel F. Villarej, Francisco J. Rondán, Manuel J. Sánchez

� http://www.slideshare.net/BiratSharma/cluster-spss-week7

� http://core.ecu.edu/psyc/wuenschk/MV/FA/FA.doc

� www.wikipedia.com

� Academic-papers.org/ocs2/session/Papers/G2/146.doc by Kuang-Wen Wu and Kun-

Chang Wu

DATABASE REFERENCES

� Data Monitor

� Euromonitor

market research project report: footwear industry differentiation

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