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A Study on the Product Designing of

Formal ApparelsBIRLA INSTITUTE OF MANAGEMENT TECHNOLOGY

Submitted By:

GROUP 2

Manmeet Walia (084)

Neha Aggarwal (099)

Neha Mittal (100)

Nikita Saraiwala (106)

Nisha Maurya (107)

Pratibha Tatia (117)

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ACKNOWLEDGEMENT

We are thankful to Prof. A.K. Dey, Distinguished professors of Research Methodology at

BIMTECH and Prof. Tuhin Chattopadhyay, Guest faculty at BIMTECH for giving us the

opportunity to work on this project. It was a great learning experience for us and we could

actually put in practice, the learning acquired in the classroom. Also the project helped us in

understanding the customer perspective for the apparel industry.

We are also thankful to the all the respondents of the survey who helped us throughout the

course of the project.

GROUP 2

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ABSTRACT

Objective: The objective of this research is to evaluate the factors influencing the buying

decision of consumers of the formal apparel industry.

Apparel is the second largest retail category in India. The major factors contributing to its

growth are greater purchasing power of the young generation, access to fashion trends outside

the country, and the superior quality of fabrics. Moreover, due to globalization there has been

tremendous rise in the foreign institutional investments which has led to a boom in the

corporate sector. Seeing the drastic demand for the western formal apparels marketers are

eager to know about the buying behaviour of consumers. Therefore, our research mainly

focuses on understanding the apparel industry by studying the various motivational factors

influencing the purchase or selection decisions for formal apparels. To achieve the objective a

descriptive research was conducted and the data was collected through surveys using

structured questionnaire. Factor analysis was performed through SPSS tool to analyse the

data and find the major factors influencing the buying behaviour of customers. After the

analysis we found six major factors which will help the marketers to understand the

consumer purchase intentions and accordingly position their products which in turn will

satisfy the consumer needs for western formals.

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INDEX

S. No. Title Page No.

1 Acknowledgement 2

2 Abstract 3

3 Introduction 5

4 Literature Review 8

5 Research Design 14

6 Findings & Discussions 31

7 Conclusion 33

8 Limitations & Future Research 34

9 List of Tables 35

10 List of Figures 35

11 Appendix 36

12 Bibliography 41

13 References 41

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INTRODUCTION

Introduction to Apparel Industry

Apparel is one of the basic necessities of human civilization along with food, water and

shelter. The Apparel Industry reflects people’s lifestyles and shows their social and economic

status. The Apparel and Textile industry is India’s second largest industry after IT Industry.

At present, it is amongst the fastest growing industry segment and is also the second largest

foreign exchange earner for the country.

The concept of readymade garments was relatively new for the Indians. Traditionally, Indians

preferred dresses stitched by local tailors, who had tailoring units in townships or cities and

catered exclusively to local demand. The growing fashion consciousness during the 1980s

and the convenience offered by ready-to-wear garments were largely responsible for the

development of the branded apparel industry in India. Over the years there have been

sweeping changes in the apparel industry. Once strictly a made-to-order market for clothing

is now transforming into a ready-to-wear market. The growth of the domestic demand for

clothing in India is also linked with the success of the retailing sector. Other factors which

contributed to its growth were: greater purchasing power in the hands of the youth, access to

fashion trends outside the country, and the superior quality of fabrics. Today most of the

international brands have found their way into some of the best malls in the country. Brands

like Mango, Armani and Diesel were unheard of in India till a few years back but today these

brands are found in almost all Indian cities. 

Apart from providing one of the basic necessities of life, the textile industry also plays a

pivotal role through its contribution to industrial output, employment generation, and the

export earnings of the country. Currently, it contributes about 14 percent to industrial

production, 4 percent to the GDP, and 30 percent to the country’s export earnings. It provides

direct employment to over 35 million people.

It is said that in the last ten years the fashion industry in India has moved from a very nascent

stage to a full-fledged booming industry. The value of the apparel market in India is

estimated at around Rs.20, 000 crore. The branded apparel market's size is Rs.5, 000 crore

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which is a quarter of the total share. The apparel market is India is categorized into branded

and non-branded. The Top Apparel Brands in India are Madura Garments, Arvind Mills,

Provogue Zodiac Clothing, and Raymond. Giving a closer look it was found that Men’s

apparel market include 46% of the total apparel market in India followed by 17% of the

market size by women and 37% by kids.

Consumer spending on apparel in India has grown over the last five years, touching the

global benchmark of 5 per cent of the total income, according to Consultancy firm McKinsey.

It continues to stimulate consumer demand for apparels and is estimated to grow at the rate of

12-15 per cent annually in terms of growth in rupee value. The Indian government has

targeted the apparel and textiles industry segments to reach $50 billion by the year 2015. One

of the most interesting features of the apparel industry is that, it migrates from high cost

nations to the low cost nations.

TABLE 1: Indian Apparel Industry Value Forecast

YEAR $ BILLION INR BILLION % GROWTH

2005 18.3 806.0 12.10%

2006 20.2 891.3 10.60%

2007 22.3 982.5 10.20%

2008 24.4 1078.4 9.80%

2009 26.7 1179.3 9.40%

2010 29.2 1288.9 9.30%

CAGR: 2005-2010: 9.8%

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Formal Apparel Industry

Formal wear or formal dress is a general term used to describe men’s clothing suitable for

formal events, including weddings, debutante balls, etc. Since, the world is simultaneously

fashion oriented, every women desire to be donned in formal and stylish outfits. In this

commercial world, even women are contributing to the business sector which increases the

demand for women's formal dresses. The reason why it is important to be donned in

impressive formal outfits is that it does not only make you look good during office hours but

also creates a good impression at your workplace and gets you exposure. To meet this

requirement of the female population, the fashion industry has contributed numerous

magnificent formal attires to serve the ladies also along with the men.

Evidently, formal wear is something that is in demand throughout the year, irrespective of

season and climate. This is the reason why most trend setters include formal attires in their

designer collection for outfits. Many national and international brands have come up with

exclusive formal range of collections like Blackberrys, Allen Solly, Van Heusen, Wills

Lifestyle, Marks and Spencers, etc. and have captured a major market share in the industry.

And with the growth of western culture in the Indian corporate and businesses and the entry

of Foreign Institutional Investor (FII) the industry expected to grow in future as well.

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LITERATURE REVIEW ON FORMAL APPARELS

Apparel Industry

The global apparel industry is one of the most important sectors of the economy in terms of

investment, revenue, and trade and employment generation all over the world. Apparel

industry has short product life cycles, tremendous product variety, volatile and unpredictable

demand, long and inflexible supply processes.

The clothing and apparel industry produces finished clothing products made from both

natural and manmade fibbers like cotton, silk, wool, Lenin, polyester, rayon, Lycra and

denim. The important segments covered in apparel industry include kids clothing, men’s

clothing, clothing for women and intimate apparel.

Word Of Mouth' Biggest Influence on Apparel Buyers - Survey, USA

When it comes to buying apparel and electronics, shoppers are most interested in hearing

from their peers about products, retailers and past shopping experiences. In a recent survey,

conducted for the Retail Advertising and Marketing Association by BIG research, consumers

say that word of mouth is still the number one influencer in their apparel (34.3%) and

electronics (44.4%) purchases.

In addition to first-hand knowledge, product reviews (36.8%) and retail advertising inserts

(29.2%) – or circulars – will also resonate with consumers in their electronics purchases this

holiday season. Shoppers looking for the best deal on apparel items, from new jeans to winter

coats, will check out circulars (33.3%) and in-store promotions (30.4%).

“Retailers offering great deals will use many channels this holiday season to make sure their

customers aren’t left in the dark.” said Mike Gatti, Executive Director, Retail Advertising and

Marketing Association. “If retailers can’t get the word out to shoppers about their sales and

promotions this holiday season, the lowest prices in the world won’t bring customers into the

stores.”

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Product placement is another huge driver in adults’ purchase decisions. When it comes to

apparel purchases 11.5 percent say it influences their purchase decision. Blogging also

influences 3.3 percent of their apparel purchases.

Many apparel studies were found to investigate the relationship between an individual

stimulus cue and consumers’ perception of product quality. Many researchers found that

price is often interpreted as an important cue by consumers in perceiving apparel quality.

Davis (1987) used white blouse to investigate how consumers use label information in ratings

of clothing quality, and found that price was one of the five cues that most subjects selected

to assess the product quality. Hatch and Roberts (1985) used socks and sweaters, and Render

and O’Vonnor (1976) used shirts to investigate the influence of price on consumers’

perception of product quality. Both studies found that the higher the price, the higher the

perceived quality.

Author(s): Hye-Shin Kim, (Assistant Professor in the Department of Consumer Studies at the

University of Delaware (USA)), Mary Lynn Damhorst, (Associate Professor of

Textiles and Clothing at Iowa State University in Ames)

Citation: Hye-Shin Kim, Mary Lynn Damhorst, (1993) "Environmental attitude and

commitment in relation to ad message credibility", Journal of Fashion Marketing

and Management, Vol. 3 Iss: 1, pp.18 – 30

Publisher: MCB UP Ltd

The product Management in apparel Industry is done through following steps-

Design- Innovate new design by constantly iterating across your global product development

team.

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Development and pre-production Streamline your product development processes from idea

capture to specification development, sampling, lab dips, testing, approvals and ultimately,

product launch.

Material management Unify and communicate the material information that your global

team needs for production.

Sourcing and production Collaborate with vendors to provide the right compliant materials

and facilitate timely production, thereby ensuring that you stay on trend and meet committed

in-store dates.

Quality assurance Ensure quality soft lines, hard lines and footwear products.

Distribution and logistics Model fully landed costs and track delivery through seamless

supply chain system integration, thereby ensuring that your product assortment reaches the

right customers on a cost effective basis.

Sales and marketing Centrally manage information and images to facilitate optimal store.

Owner’s experience catalog merchandising incorporate customer feedback captured through

social media or store input into future seasonal development.

Seasonal and line planning Assign templates for go-to-market styles and product

assortments across multiple seasons, based on hot trends, past sales and optimal cost.

Finally, Goals of Apparel Industry are-

- Accelerate launch

- Increase profitable growth

- Re-use best practices

- Reduce design costs

Formal Apparel- Formal dressing means dressing well, to be presentable to others. A person

may want to give a little more attention to how he/she dress at work because what you wear

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may be substantially influencing your career path. Looking your professional best in the

workplace can give you a competitive advantage and is also a code of conduct in almost all

the corporate all over the world. It simply means dressing in a way that projects an image of

the sophisticated, successful working individual is or would like to become.

Company's objective in establishing a formal work dress code is to enable our employees to

project the professional image that is in keeping with the needs of our clients and customers

to trust us. Because our industry requires the appearance of trusted business professionals and

we serve clients at our site on a daily basis, a more formal dress code is necessary for our

employees. You must project the image of a trustworthy, knowledgeable business

professional for the clients who seek our guidance, input and professional services.

For Men Formal dressing (Western) includes-

- Suit (Well Tailored)

- Shirts ( Both full and half sleeved)

- TROUSERS

- Tie

For Women formal dressing (Western) includes-

- Formal pant suite

- Skirt

- Formal shirt or Blouse

- Scarf or a tie

Factors important in Apparel industry

(Source- research papers by Bonnie D. Belleau, (Professor at the School of Human Ecology,

Louisiana State University), Jacqueline Didier, (Instructor in the Department of Counselling,

Family Studies and Educational Leadership, at South Eastern Louisiana University), Lori

Broussard, (Based at Louisiana State University), Teresa A. Summers, sources-

OPpapers.com, Emerald Research Papers)

Promotion and Offers- Apparel advertising has evolved from selling a product to selling an

image. Various forms of media play a significant role in shaping attitudes towards apparel.

Two hundred and twenty nine men and women were surveyed about their attitudes

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concerning apparel and media. A reliability analysis of the instrument was conducted. A

discriminant analysis indicated that, of the 56 items on the apparel and media scales, seven

items significantly discriminated between the two groups. There were few differences

between age groups, which suggested that Men and women between ages 25 to 40 held

similar attitudes towards apparel, media and promotional offers. This age group was more

influenced by the Promotional offers, discounts, seasonal sales, brand name and image. Men

and women of age group 45years and above were found to be less influenced by the same

kinds of marketing strategies. They were found to be more tolerant to the ads and

promotional offers and tended to be loyal to the Brand of apparel that they have been buying

and switched rarely.

Comfort- The same survey also suggested that Men and women between ages 25 to 40 were

more experimental with fashions and fads and were less influenced by degree of comfort of

apparels .Older men and women who are 45+ were more resistant of social appearance errors

and more concerned with comfort versus fashion. Older generation also seemed to recognize

the magnitude and penetration of media and short fashion lifecycles in the apparel arena more

than younger women, and was less satisfied with apparel currently available. Results have

implications for apparel manufacturers and retailers, as well as advertising executives.

Brand Image- Today's global market witnesses a cut-throat competition. Many new products

enter the market, stay for a while, and then go obsolete. Fads come into existence and vanish

even quicker than they appear. Rapid changes in the consumers' choices, increase in their

disposable income, globalization, media exposure, and influence of global and psychological

trends attribute to this behaviour. In order to sustain them in the market, it is necessary for

every manufacturer to build a 'brand image' for his product in the market. This is more

important for apparel makers as garments have a short life cycle and trends keep changing

every now and then. Brands create the strongest competitive advantage for the manufacturer,

and the retailer.

Branded apparels not only add a stylish image to the apparel, but it also gives something

extra to the consumers. It enables them to create perceptions about the value of the apparel

and the brand itself. The value of the brand or the 'brand equity' is the difference of cash the

customer pays for a non-branded garment, and a branded one. The customer can buy similar

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apparel somewhere else; without the label and for a lesser price as well. But, branded apparel

with a label on it gives a status symbol to the customer thus satisfying his ego. The reputation

that the brand image carries helps in promoting the product among status savvy consumers.

Private Labels are also one of the category killers and many of the prominent apparel

industries like Ralph Lorren, GAP Inc., etc. are found to be struggling and more focused on

brand image building in order to counterattack.

Price- From the data collected and compiled from many countries across globe research

papers- “Exploring globe for differences between apparel purchasers, browsers and non-

purchasers & their attitudes” and “An investigation of competitive pricing among apparel

retailers and brands” were published. The study reveals that the concept of price tiers is

applicable to apparel retailers and brands. Price tiring is a vehicle for market positioning for

the retail apparel industry. Retailers are enacting a price tier strategy by branding their retail

store formats or engaging store brands as a vehicle of differentiation for a tier. Retailers and

brands can be successful with a price tier strategy, unless they fail to differentiate between

tiers on factors other than on price alone.

It was also found that consumers in south pacific and Asian parts of the world were more

price and discount sensitive than in the other parts of the world.

Apparel retailers operate in an intensely rivalries and highly saturated market environment,

with slow sales growth and high price competition. When many firms are competing for the

same consumer with homogeneous product offerings, price defines the competitive position,

and is as a powerful competitive weapon. However, if a firm is not accustomed to having to

compete on price, it is often hard for firms to adjust to that notion. Competing solely on price

requires a business model that allows for significant cost cutting measures below those of

their competitors. Notably, price alone can rarely build or sustain marketing strategy. Unless

committed to this strategy, through cost models and sourcing strategies, this model is

potentially highly unstable.

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RESEARCH DESIGN

A research design is a framework or blueprint for conducting the marketing research project.

It details the procedures necessary for obtaining the information needed to structure or solve

marketing research problems. Although a broad approach to the problem has already been

developed, the research design specifies the details - the nuts and bolts – of implementing that

approach. A research design lays the foundation for conducting the project. A good research

design will ensure that the marketing research project is conducted effectively and efficiently.

Figure 1

Descriptive Research was used to study the perceptions of product characteristics. As the

name implies, the major objective of descriptive research is to describe something- usually

market characteristics or functions. Descriptive research is conducted for the following

reasons:

1. To describe the characteristics of relevant groups, such as consumers, salespeople,

organizations, or market areas.

2. To estimate the percentage of units in a specified population exhibiting a certain

behaviour.

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3. To determine the perceptions of product characteristics.

4. To determine the degree to which marketing variables are associated.

5. To make specific predictions.

Sampling Design Process

The sampling design process includes five steps. These steps are closely interrelated and

relevant to all aspects of the marketing research project, from problem definition to the

presentation of the results. Therefore, sample design decisions should be integrated with all

other decisions in a research project.

Defining the Target Population

Sampling design begins by specifying the target population. The target population is the

collection of elements or objects that possess the information sought by the researcher and

about which inferences are to be made.

The target population for our project was defined as follows:

Gender: Females

Age Group: 18-35 years

Geographic Area: Delhi/ NCR

Determining the Sampling Frame

A sampling frame is a representation of the elements of the target population. It consists of a

list or set of directions for identifying the target population.

The sampling frame for our research was defined as follows:

Target Sample: a) BIMTECH students

b) Young women at random in the street

c) Other friends and relatives

Problems: The selected sample may be unwilling, unable and biased.

Selecting a Sampling Technique

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Selecting a sampling technique involves several decisions of a broader nature. In probability

sampling, sampling units are selected by chance. It is possible to pre-specify every potential

sample of a given size that could be drawn from the population, as well as the probability of

selecting each sample. Every potential sample need not have the same probability of

selection, but it is possible to specify the probability of selecting any particular sample of a

given size.

Stratified Sampling is a two-step process in which the population is partitioned into sub-

populations, or strata. The strata should be mutually exclusive and collectively exhaustive in

that every population element should be assigned to one and only one stratum and no

population elements should be omitted.

For our research purpose, we chose the following sampling technique:

Probability Sampling – the probability of selection is nonzero and is known in

advance for each population unit

Stratified Sampling – Population is divided into mutually exclusive and exhaustive

strata based on gender, age and geographic area. Simple random samples are then

drawn from each stratum.

Determining the Sample Size

Sample size refers to the number of elements to be included in the study. Determining the

sample size is complex and involves several qualitative and quantitative considerations.

The sample size for our research problem was 158.

DATA COLLECTION DESIGN

1. Data Collection Method: The data was collected from two sources:

Secondary Data: Data from research papers, business magazines, websites of the

companies, etc.

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Primary Data: The survey method of obtaining information was used. Respondents

were asked a variety of questions regarding their behaviour, intentions, attitudes,

awareness, motivations and demographic and lifestyle characteristics. These questions

were asked verbally, in writing or via computer.

2. Data Collection Instrument: Questionnaire, a formalized set of questions for

obtaining information from respondents, was selected for collecting the data.

Structured questions specifying the set of response alternatives and the response

format was significantly used. Multiple choice questions, dichotomous questions and

Likert scale of 5 were used.

Unstructured questions, open-ended questions that respondents answer in their own

words, were used as well.

STATISTICAL DESIGN:

1. Statistical Techniques: Multivariate techniques which are suitable for analyzing

data when there are two or more measurements of each element and the variables are

analyzed simultaneously were used. Both dependence and interdependence

techniques were used.

Factor Analysis, variable interdependence technique, in which the interrelationships

among large number of variable (questionnaire responses) are analyzed and then they

are represented in terms of common underlying dimensions (factors). It brought out

the hidden or latent dimensions relevant in the relationships among product

preferences.

2. Statistical Software: SPSS is a comprehensive and flexible statistical analysis and

data management solution. SPSS can take data from almost any type of file and use

them to generate tabulated reports, charts, and plots of distributions and trends,

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descriptive statistics, and conduct complex statistical analyses. SPSS is available from

several platforms; Windows, Macintosh, and the UNIX systems.

FACTOR ANALYSIS

Factor analysis is a general name denoting a class of procedures primarily used for data

reduction and summarization. In marketing research, there may be a large number of

variance, most of which are correlated and which must be reduced to a manageable level.

Relationships among sets of many interrelated variables are examined and represented in

terms of a few underlying factors. For example, store image may be measured by asking

respondents to evaluate on a series of items on a semantic differential scale. These item

evaluations may then be analyzed to determine the factors underlying store image. It is an

independence technique in that an entire setoff interdependent relationship is examined.

Factor Analysis Model

Mathematically, factor analysis is somewhat similar to multiple regression analysis, in that

each variable is expressed as a linear combination of underlying factors. The amount of

variance a variable shares with all other variables included in the analysis is referred to as

communality. The co-variation among the variables is described in terms of a small number

of common factors plus a unique factor for each variable. These factors are not overtly

observed.

The unique factors are uncorrelated with each other and with the common factors. The

common factors themselves can be expressed as linear combinations of the observed

variables.

It is possible to select weights or factors score coefficients so that the first factor explains the

largest portion of the total variance. Then a second set of weights can be selected, so that the

second factor accounts for most of the residual variance, subject to being uncorrelated with

the first factor. This same principle could be applied to selecting additional weights for the

additional factors. Thus, the factors can be estimated so that their factor scores, unlike the

value of the original variables, are not correlated. Furthermore, the first factor accounts for

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the highest variance in the data, the second factor the second highest, and so on. Several

statistics are associated with factor analysis.

Statistics associated with factor analysis:

Bartlett’s test of sphericity: It is a test statistic used to examine the hypothesis that the

variables are uncorrelated in the population. In other words, the population correlation

matrix is an identity matrix, each variable correlates perfectly with itself (r=1) but has

no correlation with the other variables (r=0).

Correlation matrix: A correlation matrix is a lower triangle matrix showing the

simple correlations, r, between all possible pairs of variables included in the analysis.

The diagonal elements, which are all 1, are usually omitted.

Communality: It is the amount of variance of variable shares with all the other

variables being considered. This is also the proportion of variance explained by the

common factors.

Eigen value: It represents the total variance explained by each factor.

Factor loadings: Factor loadings are simple correlations between the variables and

the factors.

Factor loading plot: It is a plot of the original variables using the factor loadings as

coordinates.

Factor matrix: It contains the factor loadings of all the variables on all the factors

extracted.

Factor scores: Factor scores are the composite scores estimated for each respondent

on the derived factors.

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Kaiser –Meyer-Olkin (KMO) measure of sampling adequacy: The Kaiser –Meyer-

Olkin (KMO) measure of sampling adequacy is an index used to examine the

appropriateness of factor analysis. High values (between 0.5 and 1.0) indicate factor

analysis is appropriate.

Percentage of variance: It is the total variance attributed to each factor.

Residuals: They are the differences between the observed correlations, as given in the

input correlation matrix, and the reproduced correlations, as estimated from the factor

matrix.

Scree plot: It is a plot of the Eigen values against the number of factors in order of

extraction.

Cronbach’s alpha test: One of the most commonly used indicators of internal

consistency is Cronbach’s alpha coefficient. Ideally, the Cronbach alpha coefficient of

a scale should be above .7. Cronbach alpha values are, however, quite sensitive to the

number of items in the scale. With short scales (e.g. scales with fewer than ten items),

it is common to find quite low Cronbach values (e.g. .5). In this case it may be more

appropriate to report the mean interterm correlation for the items. Briggs and Cheek

(1986) recommend an optimal range for the inter-item correlation of .2 to .4. The

cronbach’s alpha value is .717 (greater than 0.5) as shown in Table 2

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Case Processing Summary

Table 2

N %

Cases Valid 154 98.1

Excludeda 3 1.9

Total 157 100.0

a. List-wise deletion based on all variables

in the procedure.

Reliability Statistics

Table 3

Cronbach's

Alpha N of Items

.717 19

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CONDUCTING FACTOR ANALYSIS

The steps involved in conducting factor analysis are as follows:

1. Define the factor analysis problem and identify the variables to be factor analyzed.

2. Construct a correlation matrix of these variables and select a method of factor

analysis.

3. Decide on the number of factors to be extracted and the method of rotation.

4. Interpretation of rotated factors.

5. Depending upon the objectives, calculate the factor scores, or surrogate the selected

variables.

6. Finally, determine the fit of the factor analysis model.

FORMULATION OF THE PROBLEM

Problem formulation includes several tasks. First, the objectives of factor analysis should be

identified. The variables to be included in the factor analysis should be specified based on

past research, theory, and judgement of the researcher. It is important that the variables be

appropriately measured on an interval or ratio scale. An appropriate sample size should be

used.

To illustrate factor analysis, we wish to determine the underlined factors which affect

consumers while purchasing formal apparels. A sample of 158 respondents was surveyed

using structured questionnaire. The respondents were asked to indicate the degree of influence

with the following 20 factors.

1. Price 2. Comfort3. Fabric Quality 4. Novelty5. Sizes Available 6. Durability7. Brand image 8. Service Quality9. Accessibility of brand outlets 10. Brand Ambassador11. Colours 12. Stitch/Tailoring Component13. Promotions & offers 14. Customization15. Designs 16. Latest Trends17. Outlet type 18. Brand Logo19. Proper Fitting 20. Family & Friends opinions

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CONSTRUCTION OF THE CORRELATION MATRIX

The analysis process is based on a matrix of correlations between the variables. Valuable

insights can be gained from an examination of this matrix. For the factor analysis to be

appropriate, the variables must be correlated. If the correlations between all the variables are

small, factor analysis may not be appropriate.

Formal statistics are available for testing the appropriateness of the factor model. Bartlett’s

test for sphericity can be used to test the null hypothesis which is that the variables are not

correlated in the population; in other words, the population correlation matrix is an identity

matrix. The test statistic for sphericity is based on a chi-square transformation of the

determinant of the correlation matrix. A large value of the test statistic will favour the

rejection of the null hypothesis. If the hypothesis cannot be rejected, then the appropriateness

of the factor analysis should be questioned. Another useful statistic is the Kaiser-Meyer-

Olkin (KMO) measure of sampling adequacy. This index compares the magnitudes of the

observed correlation coefficients to the magnitudes of the partial correlation coefficients.

Small values of the KMO statistic indicate that the correlations between pairs of variables

cannot be explained by other variables and that factor analysis may not be appropriate.

Generally, a value greater than 0.5 is desirable.

The Null hypothesis, that the population correlation matrix is an identity matrix, is rejected

by the Bartlett’s test of sphericity. The approximate chi square statistics is 483.856 with 171

degrees of freedom, which is significant at the 0.05 level. The value of the KMO statistic

(0.677) is also large (greater than 0.5) as shown in Table 3. Thus, factor analysis will be

considered an appropriate technique for analysing the correlation matrix.

DETERMINATION OF THE METHOD OF FACTOR ANALYSIS

Once it has been determined that factor analysis is an appropriate technique for analyzing the

data, an appropriate method must be selected. The approach used to derive the weights or

factor score coefficients differentiates the various methods of factor analysis. The two basic

approaches are principals component analysis and common factor analysis. In principals

component analysis, the total variance in the data is considered. The diagonal of the

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correlation matrix consists of unities, and full variance is brought into the factor matrix.

Principal components analysis is recommended when the primary concern is to determine the

minimum number of factors that will account for maximum variance in the data for use in

subsequent multivariate analysis. The factors are called principal components.

In common factor analysis, the factors are estimated based only on the common variance.

Communalities are inserted in the diagonal of the correlation matrix. This method is

appropriate when the primary concern is to identify the underlying dimensions and the

common variance is of interest. This method is also known as principal axis factoring.

We have used principal component analysis. Under communalities, initial column, it can be

seen that the communality for each variable from 1 to 20 is 1 as unities were inserted in the

diagonal of the correlation matrix. The table labelled initial Eigen values gives the Eigen

values. The Eigen values for the factors are as expected, in decreasing order of magnitude as

we go from factor1 to factor 20.The Eigen value for a factor indicates the total variance

attributed to that factor. The total variance accounted for by all 20 factors is 20, which is

equal to the number of variables. Factor 1 account for a variance of 3.387 which is (3.287/20)

or 16.43% of the total variance. Likewise second factor accounts for 2.021 which is

(2.021/20) or 10.1% of the total variance. Several considerations are involved in determining

the number of factors that should be used in the analysis.

Table 4: KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .671

Bartlett's Test of

Sphericity

Approx. Chi-Square 483.856

Df 171

Sig. .000

25

Table 5 : Communalities

Initial Extraction

Price 1.000 .615

Fabric quality 1.000 .539

Sizes available 1.000 .423

Brand image 1.000 .666

Accessibility 1.000 .632

Colours 1.000 .457

Promotions and offers 1.000 .582

Designs 1.000 .634

Fitting 1.000 .522

Comfort 1.000 .584

Novelty 1.000 .602

Durability 1.000 .558

Quality of service 1.000 .492

Brand ambassador 1.000 .617

Stitch or tailoring 1.000 .509

Customization 1.000 .486

Latest trends 1.000 .496

Brand logo 1.000 .616

Family and friends 1.000 .506

Extraction Method: Principal Component

Analysis.

26

Table 6: Total Variance Explained

Compo

nent

Initial Eigen values Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %

1 3.287 17.300 17.300 3.287 17.300 17.300

2 2.021 10.639 27.939 2.021 10.639 27.939

3 1.688 8.886 36.825 1.688 8.886 36.825

4 1.253 6.595 43.420 1.253 6.595 43.420

5 1.208 6.356 49.776 1.208 6.356 49.776

6 1.080 5.687 55.462 1.080 5.687 55.462

7 .949 4.994 60.456

8 .882 4.644 65.100

9 .839 4.418 69.517

10 .796 4.192 73.709

11 .765 4.027 77.737

12 .714 3.756 81.492

13 .677 3.566 85.058

14 .595 3.131 88.189

15 .542 2.852 91.042

16 .482 2.539 93.581

17 .456 2.401 95.982

18 .420 2.211 98.192

19 .343 1.808 100.000

27

DETERMINATION OF THE NUMBER OF FACTORS

It is possible to compute as many principal components as there are variables, but in doing so,

no parsimony is gained. In order to summarize the information contained in the original

variables, a smaller number of factors should be extracted. The question is, how many?

Several procedures have been suggested for determining the number of factors. These include

approaches based on Eigen values, scree plot, percentage of variance accounted for, etc.

Determination Based on Eigen values: In this approach, only factors with Eigen values

greater than 1.0 are retained; the other factors are not included in the model. An Eigen value

represents the amount of variance associated with the factor. Hence, only factors with a

variance greater than 1.0 are included. Factors with variance less than 1.0 are no better than a

single variable, because, due to standardization, each variable has a variance of 1.0. If the

number of variables is less than 20, this approach will result in a conservative number of

factors.

Based on the Eigen value criterion first six factors (factor1 to factor 6) are selected.

Determination based on Scree Plot: A scree plot is a plot of the Eigen values against the

number of factors in order of extraction. The shape of the plot is used to determine the

number of factors. Typically, the plot has a distinct break between the steep slope of factors,

with large Eigen values and a gradual trailing off associated with the rest of the factors. This

gradual trailing off is referred to as the scree. Experimental evidence indicates that the point

at which the scree begins denotes the true number of factors. Generally, the number of factors

determined by a scree plot will be one or a few more than that determined by the Eigen value

criterion. From the scree plot shown in Figure 2, a distinct break occurs at 4 factors.

Determination Based on Percentage of Variance: In this approach, the number of factors

extracted is determined so that the cumulative percentage of variance extracted by the factor

reaches a satisfactory level. What level of variance is satisfactory depend upon the problem.

However, it is recommended that the factors extracted should account for at least 60 percent

of the variance.

28

Finally from the cumulative percentage of variance accounted for, we see that the first 6

factors account for 55.46% of the variance. So finally from the above criterion we have

selected 6 factors.

Rotate factors:

An important output from factor analysis is the factor matrix, also called the factor pattern

matrix. The factor matrix contains the coefficients used to express the standardized variables

in terms of the factors. These coefficients, the factor loadings, represent the correlations

between the factors and the variables. A component with a large absolute value indicates that

the factor and variable are closely related. The coefficients of the factor matrix can be used to

interpret the factors.

The most commonly used method for rotation is varimax procedure. This is an orthogonal

method of rotation that minimizes the number of variables with high loadings on a factor,

thereby enhancing the interpretability of the factors. Orthogonal rotation results in factors that

are uncorrelated.

Figure 2

29

Table 7: Component Matrixa

Component

1 2 3 4 5 6

Price .122 .453 .417 .316 .239 -.253

Fabric quality .385 .289 -.425 .185 -.137 -.271

Sizes available .434 .030 -.279 .125 -.374 .025

Brand image .320 -.542 -.339 .377 -.084 .070

Accessibility .517 -.194 .202 .149 -.416 -.302

Colours .302 .176 .304 .155 -.323 .339

Promotions and offers .361 .156 .590 .166 -.162 -.156

Designs .417 .013 .267 .413 .279 .375

Fitting .452 .491 -.117 .134 -.146 .155

Comfort .356 .422 -.158 -.059 .101 .491

Novelty .452 -.034 .347 -.453 -.217 -.155

Durability .494 .245 -.149 -.302 .337 -.167

Quality of service .576 -.001 -.240 -.248 -.056 -.194

Brand ambassador .365 -.638 .161 -.057 -.065 .210

Stitch or tailoring .510 .108 -.391 -.204 .053 .200

Customization .526 -.068 .211 -.365 .165 .012

Latest trends .385 -.305 .294 -.128 .375 .109

Brand logo .366 -.574 -.151 .224 .250 -.128

Family and friends .328 .135 -.127 .306 .413 -.316

Extraction Method: Principal Component Analysis.

a. 6 components extracted.

30

Table 8: Rotated Component Matrixa

Component

1 2 3 4 5 6

Price -.264 -.024 -.111 .380 .112 .613

Fabric quality -.020 .026 .680 -.010 .040 .270

Sizes available .177 .023 .575 .150 .159 -.115

Brand image .745 -.138 .295 -.050 .015 -.039

Accessibility .295 .150 .356 .609 -.157 -.015

Colours -.011 -.034 .072 .474 .448 -.158

Promotions and offers -.044 .134 -.036 .718 .086 .195

Designs .347 .014 -.160 .241 .580 .306

Fitting -.166 .079 .452 .169 .485 .141

Comfort -.139 .189 .189 -.124 .691 .014

Novelty -.053 .602 .070 .433 -.085 -.193

Durability -.079 .603 .233 -.137 .118 .319

Quality of service .132 .502 .470 .020 -.011 .032

Brand ambassador .640 .259 -.124 .193 .038 -.295

Stitch or tailoring .114 .392 .413 -.221 .348 -.038

Customization .122 .654 -.033 .163 .127 .018

Latest trends .376 .463 -.311 .102 .137 .122

Brand logo .729 .144 .061 -.061 -.126 .203

Family and friends .156 .106 .186 -.046 .020 .658

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 13 iterations.

31

Table 9: Component Transformation Matrix

Component 1 2 3 4 5 6

1 .383 .596 .462 .343 .359 .194

2 -.821 -.036 .250 .051 .390 .327

3 -.126 .124 -.642 .744 .020 .049

4 .362 -.730 .113 .244 .191 .476

5 .129 .283 -.480 -.486 .125 .649

6 .122 -.121 -.260 -.175 .816 -.453

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

Interpretation of Factors

Interpretation is facilitated by identifying the variables that have large loadings on the

same factor. That factor can then be interpreted in terms of the variables that load high on

it. Another useful aid in the interpretation is to plot the variables using the factor loadings

as coordinates. Variables at the end of an axis are those that have high loadings on only

that factor, and hence describe the factor. Variables near the origin have small loadings on

both the factors. Variables that are not near any of the axes are related to both the factors.

Now, the factors are being extracted according to the highest loading in each column. Like in

first column the highest loading is at brand image i.e. .745, second factor is customization

with highest loading of .654, third factor is fabric quality with highest loading of .680, fourth

factor is promotion and offers with highest loading of .718, fifth factor is comfort with

highest loading of .691 and the sixth factor is family and friends with highest loading of .658.

FINDINGS AND DISCUSSIONS

After conducting the consumer survey and performing factor analysis on data collected we

were able to come out with the six major factors by which the consumers were most

influenced while purchasing the western formal apparels.

32

These six factors are listed below:

1. Brand Image

2. Customization

3. Fabric Quality

4. Promotion and offers

5. Comfort

6. Family and friends

Now let’s discuss each of the factors in details as to how do they influence the purchase

decisions of the consumers.

First one is Brand Image. It is an impression in the mind of the consumer about a brand's

total personality (real and imaginary qualities and shortcomings). It is developed over time

through advertising campaigns with a consistent theme, and is authenticated through the

consumers' direct experience. In the case of formal apparels too it plays a major role.

Consumers do make a choice according to the image of the brand they are having in their

mind.

Second is Customization which means marketers can differentiate products by making them

customized to an individual. As companies have grown proficient at gathering information

about individual customers and business partners, and as their factories are being designed

more flexibly, they have increased their ability to individualize their market offerings,

messages and media. Western formal apparel industry is also not lagging behind. With

increasing trends, customers will demand customization for western formals as well.

Next is the Fabric Quality. Our results have shown that consumers do care about the fine

quality of the fabric they are buying. Fabric should be durable and of premium quality.

Therefore, brands should be concerned of the quality and standards of their clothing.

Another important factor found by our research is Promotion and offers. Promotion is

advancement of a product through publicity and/or advertising and offers are the special

incentives like discount, coupons, rebates, gifts, sweep stakes etc. given by the companies to

encourage buyers to purchase their products. Seeing this as the major factor influencing the

33

consumer buying behaviour the marketers should indulge in good amount of promotion and

offers to retain and enhance the customer base.

The fifth factor is comfort. So the brands should keep in mind that the apparels should be

designed and styled in such a way that excels in providing the maximum comfort to the

consumers.

Finally, family and friends are also one of the major factors that influence the buying

behaviour of the costumers. So companies cannot ignore the social factors as their opinions

too matter in the decision making of the consumer. Therefore the brands should be

appropriately positioned to target the opinion leaders.

CONCLUSIONS

From the findings, we get a clear insight on the priority consumers give to various factors in

the process of decision making while shopping for formal apparels. If one excepts the

definition of brand image by Reynolds and Gutman (1984), they have defined brand image in

terms of the stored meaning that an individual has in memory, suggesting that what is called

up from memories provided meaning we attribute most basically to image, (Dawn and

George, 1990), then as founded by our research “brand image is in the eye of the consumer”.

Other factors found in the priority list of the consumer while deciding on the formal apparel

in decreasing order of priority are – Customization, fabric quality, promotion and offers,

comfort, and family and friends. From a theoretical point of view apparel products are seen as

having, in the first place, intrinsic physical properties (such as design, materials, construction

and finishes), specifying what the item is, and, second, behavioural properties (functional and

aesthetical), specifying what the product can achieve (Brown and Rice, 1998; Gersak, 2002).

34

Limitations and Future Research

Due to multi-dimensionality of the concept, a qualitative research design has been and

therefore the sample size is small. Conjoint analysis could not be carried out due to the

statistical constraint of having more than 3 factors. Findings in this study could be used to

direct future quantitative studies with a lager sample size that would ensure better

representation and further conjoint analysis can be carried out with less number of factors to

identify the most sort after attribute that might influence the decision making of the consumer

of apparel industry. Similar and more comprehensive research could be carried out for the

entire apparel industry.

35

LIST OF TABLES

Table No. Title Page No.

1 Indian Apparel Industry 6

2 Case Process Summary 21

3 Cronbach Alpha Results 21

4 KMO and Bartlett’s Test 24

5 Communalities 25

6 Total Variance 26

7 Component Matrix 29

8 Rotated Component Matrix 30

9 Component Transformation Matrix 31

LIST OF FIGURES

Figure No. Title Page No.

1 Research Design 14

2 Scree Plot 28

36

APPENDIX

Survey Form for Formal Apparel

* Required

1. Name

2. Age *

3. Marital Status *

Single

Married

4. Place *

5. Profession *

Student

Service

Self-Employed

Other:

6. How often do you shop for formal Apparels? *

Frequently (Once in a month)

Occasionally (Once in Six Month)

Seldom (Once in a Year)

7. Which brand comes to your Mind FIRST while shopping for Formals? *

37

8. How much importance do you give to price factor while going for formals? * 1.Least

influenced & 5.Highly influenced

1 2 3 4 5

9. To what extent do fabric quality matters? * 1.Least influenced & 5.Highly influenced

1 2 3 4 5

10. Rate the importance given to sizes available in brands? * 1.Least influenced & 5.Highly

influenced

1 2 3 4 5

11. How much role does the brand image play in making your purchase decisions? * 1.Least

influenced & 5.Highly influenced

1 2 3 4 5

12. To what extent does the accessibility of brand outlets influence your brand preferences *

1.Least influenced & 5.Highly influenced

1 2 3 4 5

13. How much are you influenced by colours while going for western formals? * 1.Least

influenced & 5.Highly influenced

38

1 2 3 4 5

14. How much are you influenced by the promotions and offers given by the brands? *

1.Least influenced & 5.Highly influenced

1 2 3 4 5

15. How much does the design provided by the brand influence your purchase decision? *

1.Least influenced & 5.Highly influenced

1 2 3 4 5

16. From where do you prefer to buy formals? *

Retail Outlets

Exclusive Showrooms

Factory Outlets

Other:

18. How much importance do you pay to the proper fitting of formal clothing? * 1.Least

influenced & 5.Highly influenced

1 2 3 4 5

19. What rank will you give to the comfort factor of formal clothing? * 1.Least influenced &

5.Highly influenced

39

1 2 3 4 5

20. How much are you influenced by the novelty in apparels provided? * 1.Least influenced

& 5.Highly influenced

1 2 3 4 5

21. To what extent do the durability matters? * 1.Least influenced & 5.Highly influenced

1 2 3 4 5

22. What priority will you give to the quality of service provided? * 1.Least influenced &

5.Highly influenced

1 2 3 4 5

23. To what extent does brand ambassador matters while purchasing the formals? * 1.Least

influenced & 5.Highly influenced

1 2 3 4 5

24. What importance will you give to the stitch/tailoring component of the formal apparels? *

1.Least influenced & 5.Highly influenced

1 2 3 4 5

40

25. What role does customization play while buying formals? 1. Least influenced & 5.Highly

influenced

1 2 3 4 5

26. to what extent does latest trends matters in case of formal clothing? * 1.Least influenced

& 5.Highly influenced

1 2 3 4 5

27. How much does brand logo attract you? * 1.Least influenced & 5.Highly influenced

1 2 3 4 5

28. How much does the opinion of your friends and family matter to you? * 1.Least

influenced & 5.Highly influenced

1 2 3 4 5

0

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BIBLIOGRAPHY

1. Kotler Keller Koshi Jha: Marketing Management-A south Asian perspective, 13th

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