LI KAI

CUSTOMER DEMAND FOR FAST FASHION INDUSTRY: DEMAND ON

PRICES UPDATE RATE DESIGN AND BRAND

LI KAI

UNIVERSITI TEKNOLOGI MALAYSIA

PSZ 19:16 (Pind. 1/97)

UNIVERSITI TEKNOLOGI MALAYSIA

BORANG PENGESAHAN STATUS TESIS ּט

JUDUL : CUSTOMER DEMAND FOR FAST FASHION INDUSTRY:

DEMAND ON PRICES UPDATE RATE DESIGN AND BRAND

SESI PENGAJIAN : 2010/2011

Saya ___________________________LI KAI________________________

(HURUF BESAR)

Mengaku membenarkan tesis (PSM/Sarjana/Doktor Falsafah)* ini disimpan di Perpustakaan Universiti Teknologi

Malaysia dengan syarat-syarat kegunaan seperti berikut:

Tesis adalah hakmilik Universiti Teknologi Malaysia.

Perpustakaan Universiti Teknologi Malaysia dibenarkan membuat salinan untuk tujuan pengajian sahaja.

Perpustakaan dibenarkan membuat salinan tesis ini sebagai bahan pertukaran antara institusi pengajian tinggi.

**Sila tandakan ( )

SULIT

(Mengandungi maklumat yang berdarjah keselamtan atau kepentingan

Malaysia seperti yang termaktub di dalam AKTA RAHSIA RASMI 1972)

TERHAD

(Mengandungi maklumat TERHAD yang telah ditentukan oleh

organisasi/badan di mana penyelidikan dijalankan)

TIDAK TERHAD

Disahkan oleh

________________________________ _______________________________

(TANDATANGAN PENULIS) (TANDATANGAN PENYELIA)

Alamat Tetap: CHINA, HEBEI, SHIJIAZHUANG DR. HUAM HON TAT

QIAODONGQU,

DONG DAN TING YUAN Nama Penyelia

12-4-602

Tarikh: 11 MEI 2011 Tarikh: 11 MEI 2011

CATATAN: * Potong yang tidak berkenaan.

** Jika tesis ini SULIT atau TERHAD, sila lampirkan surat daripada pihak

berkuasa/organisasi berkenaan dengan menyatakan sekali sebab dan tempoh tesis ini

perlu dikelaskan sebagai SULIT atau TERHAD.

Tesis dimaksudkan sebagai tesis bagi Ijazah Doktor Falsafah dan Sarjana secara ּט

penyelidikan, atau disertasi bagi pengajian secara kerja kursus dan penyelidikan, atau

Laporan Projek Sarjana Muda (PSM).

“I hereby declare that I have read this thesis and in my

opinion this thesis is sufficient in term of scope and quality for the

award of Bachelor Degree in Management (Technology)”.

Signature : …………………………

Name of Supervisor : DR. HUAM HON TAT

Date : 11 MAY 2011

CUSTOMER DEMAND FOR FAST FASHION INDUSTRY: DEMAND ON

PRICES UPDATE RATE DESIGN AND BRAND

LI KAI

A report submitted in partial fulfillment of

the requirement for the award of the degree of

Bachelor of Management (Technology) Conferment

Faculty of Management and Human Resources Development

Universiti Teknologi Malaysia

MAY 2011

I declare that this thesis entitled “Brand Equity in Automotive Sector” is the result of my

own research except as cited in the references. The thesis has not been accepted for my

degree and is not concurrently submitted in candidature of any other degree.

Signature : _________________

Name : LI KAI

Date : 11 May 2011

This research is especially to my beloved mother and father and friends for their

kindness and support and everything they have done for me

Thanks

ACKNOWLEDGEMENT

There are many people helping me to complete this Bachelor of Management

(Technology) thesis writing. I would like to take this opportunity to express my gratitude

to all who have helped me during this thesis writing period.

First of all, I would like to express my thanks to my supervisor, Dr. Huam Hon

Tat. He always provided inspiration and encouragement for me during discussion

meetings. He also gives an opinion or comment on the works that I already done for

further improvement.

Secondly, I would like to express my thanks to all my respondents who Malaysia’

people. They are kindly spending their times to answering the questionnaire. I

appreciated with answers that give by all respondents. Their participation and

involvement in the research are highly appreciated.

Thirdly, I would like to express my thanks to all my friends and course mates

who are willing to helping and supporting me to complete this thesis writing. When I am

stressful doing the thesis writing, they are willing spend their times to talks with me. I

am very appreciated this supportive conservation with them.

Finally, I would like to express my thanks to my family. My family not only

financially support me doing the thesis writing, but the most important thing is they are

my strong background supported me during this difficulties time period.

ABSTRACT

In today’s world, fashion was become more and more important in people's life.

In lights of this observation, this study aims to study relationship between customers

loyalty with the factors which are price, design, update rate and brand in the city square

in order to better measure the demand level. Three objectives were developed to address

the purposes of the study which were (1) To identify the demand of customer for fashion

products. (2) To identify the factors that the fast fashion can attract the consumer. (3) To

identify the relationship between Customer loyalty and those factors. Review on other

literatures and previous researches on related matter were carried out to address these

objective. Descriptive Analysis (frequency, percentage and mean) and Linear Regression

Analysis was used in this research to measure the relationship among each dimension,

which dimension is most preferred to affect the customer’s loyalty by fast fashion. The

results show that design is dimensions that have most impact towards fast fashion. All

the four dimensions of customer demand have a direct relationship among each others.

And lastly the design and brand is highly affecting the customer’s loyalty.

ABSTRAK

Pada masa kini, dapat dilihat fesyen menjadi semakin penting dalam kehidupan seharian

manusia. Kajian ini adalah untuk mengkaji hubungan diantara kesetiaan pelanggan dengan beberapa

faktor lain seperti harga, rekabentuk, tahap pembaharuan dan jenama. Kajian ini telah dilakukan

dengan mengambil maklumat dari pasaraya City Square supaya boleh mengukur tahap keperluan

dengan lebih mendalam. Tiga objektif telah dibuat untuk mengukur tujuan kajian ini di mana objektif

pertama ialah untuk mengenalpasti permintaan pelanggan berkenaan dengan produk fesyen, objektif

kedua pula ialah untuk mengenalpasti faktor Fast Fashion yang boleh menarik perhatian minat para

pelanggan dan objektif yang ketiga ialah untuk mengenalpasti hubungan diantara kesetiaan

pelanggan dan faktor tersebut. Literatur dan kajian lepas yang dibuat oleh pengkaji lain telah dikaji

untuk dikaitkan dengan objektif berkenaan. Analisis deskripsi (kekerapan, peratusan dan purata), dan

regresi ganda telah digunakan dalam kajian ini untuk mengukur hubungan antara setiap dimensi dan

menentukan dimensi yang paling memberi kesan terhadap tahap kesetiaan pelanggan dalam

persekitaran fast fasyen. Hasil kajian menunjukkan bahawa rekabentuk merupakan dimensi yang

paling menyumbang kepada fast fesyen. Keempat-empat faktor bagi tahap permintaan pelanggan

mempunyai hubungan antara satu sama lain. Dan akhir sekali ialah rekabentuk dan jenama

mempunyai kesan yang paling tinggi terhadap tahap kesetiaan pelanggan.

TABLES OF CONTENT

CHAPTER TITLE PAGE

TITLE i

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENT iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS vii

LISTS OF TABLES xi

LISTS OF FIGURES xiii

LIST OF ABBREVIATIONS xiv

LIST OF APPENDICES xv

1 INTRODUCTION

1.1 Background of the study 1

1.2 Background of research place 4

1.3 Problem Statement of the Study 4

1.4 Research Question 6

1.5 Purpose of the study 6

1.6 Scope of the study 7

1.7 Significant of the Study 7

1.8 Scope of the study 8

1.9 Limitation of the study 8

2 LITERATURE REVIEW

2.1 Introduction 9

2.2 Defining Fast apparel industry 9

2.3 Leading time 10

2.4 The Fast apparel industry process 11

2.4.1 Zara fast imitation 12

2.4.2 H&M fast imitation 12

2.5 Fast apparel industry supply chain 13

2.5.1 Zara conformity Supply chain 14

2.5.1.1 Production line’s conformity 15

2.5.1.2 Physical distribution conformity 16

2.5.1.3 Retail sales conformity in the sale 17

2.5.1.4 Subtotal 17

2.5.2 H&M conformity Supply chain 18

2.5.2.1 ICTs introduction 19

2.5.2.2 ICTs advantage 19

2.5.2.2 ICTs conformity supply chain 20

2.6 Increase Cost Effective 22

2.6.1 Zara increase the cost effective strategy 22

2.6.2 H&M increase the cost effective strategy 24

2.7 Conclusion 25

3 METHODOLOGY

3.1 Introductions 26

3.2 Research Design 26

3.3 Research Framework 28

3.4 Data Collection Method 29

3.4.1 Primary Data Collection 29

3.4.2 Secondary Data Collection 29

3.5 Population and Sampling 30

3.6 Research Instrument 31

3.7 Data Analysis Method 31

3.7.1 Descriptive Analysis 32

3.7.2 Correlation Analysis 33

3.8 Conclusion 34

4 FINDINGS AND ANALYSIS

4.1 Introductions 35

4.2 Reliability Analysis 36

4.3 Demographic Data 37

4.3.1 Gender 37

4.3.2 Ethnic 38

4.3.3 Age 38

4.3.4 Occupation 39

4.4 Identify the demand of customer for fashion 40

4.4.1 Fashion Retailer 40

4.4.2 Budget of purchasing 41

4.4.3 Frequent of purchase 42

4.4.4 Clothing Store/ Brand of choose 43

4.5 Identify the factor that fast fashion can attract

the customer 44

4.6 Identify the relationship between customer loyalty

and those factor 47

4.7 Conclusion 49

5 CONCLUSION AND RECOMMENDATION

5.1 Introductions 50

5.2 Research Conclusion 50

5.2.1 Demand of customer for fashion product 51

5.2.2 Factors that the fast fashion can attract the

consumer 52

5.2.3 Relationship between Customer Loyalty and

those factors 53

5.3 Recommendation 54

5.3.1 Recommendation for marketers 55

5.3.2 Recommendation for future researcher 55

5.4 Conclusion of the study 56

REFERENCES 57

APPENDICES 63

LIST OF TABLES

TABLE NO. TITLE PAGE

3.1 Determining Sample Size from Population 3

3.2 Method of Analysis for Objective Research 31

3.3 Level of Mean Score 33

4.1 Reliability Analysis 36

4.2 Frequency Distribution of Respondent based on Gender 37

4.3 Frequency Distribution of Respondents based on Ethnic 38

4.4 Frequency Distribution of Respondents based on Age 39

4.5 Frequency Distribution of Respondents based on occupations 39

4.6 Frequency Distribution of Respondents based on aware

of fast fashion retailers 41

4.7 Frequency Distribution of Respondents based on

budget of purchasing 41

4.8 Frequency Distribution of Respondents based on times of

purchase 42

4.9 Frequency Distribution of Respondents based on Clothing

brand of choose 43

4.10 Summary means for all dimensions’ question 44

4.11 Summary result of consumer attract dimension level of

respondents towards Fast Fashion factors 46

4.12 Model Summary of Regression 47

4.13 Result of Multiple Regression Analysis 48

LIST OF FIGURES

FIGURE NO. TITLE PAGE

2.1 ZARA Supply Chain 14

2.2 H&M Supply Chain 18

3.1 Classification of Research Design 27

3.2 Flow Chart of Research Process 28

LIST OF ABBREVIATION

SPSS : Statistical Package for Social Science

UTM : Universiti Teknologi Malaysia

LIST OF APPENDICES

APPENDIX TITLE PAGE

A Questionnaire 63

B SPSS Data Analysis 69

CHAPTER I

INTRODUCTION

1.1 Background of the study

The principle underpinning fast fashion is the reduction of lead times to get

product from concept to consumer (Barnes and Lea-Greenwood, 2006; Sull and Turconi,

2008).

Fast fashion is a concept whereby retailers orientate their business strategies to

reduce the time taken to get fashion product into store, working on a system of in-season

buying so product ranges are consistently updated throughout the season. The fast

fashion approach also takes into account the nature of consumer demand representing a

move away from supply chains driven by manufacturer or designer “push” to demand

chains driven by consumer “pull” (Doyle et al., 2006). Therefore, underpins the fast

fashion concept the furtherance is lead time and consumer demand:

Fast fashion is a business strategy which aims to reduce the processes involved in the

buying cycle and lead times for getting new fashion product into stores, in order to

satisfy consumer demand at its peak (Barnes and Lea-Greenwood, 2006, p. 259).

The inclusion of consumer demand as a facet of fast fashion suggests a

broadened theory of fast fashion, building on the in season buying and reduced lead time

concept to incorporate “newness” as a key feature of fast fashion, in other words,

continual renewal and updating of ranges and merchandise delivered to the store.

Fast fashion has become a key feature of the UK fashion industry over the last

decade. Although it was initially regarded as a niche concept offered by a few key

players such as Zara and H&M, the concept has now been adopted in one form or

another by virtually all the key own-label retailers in the UK fashion market (Baker,

2008 and Just-Style, 2009), using improved and more efficient supply chains to be more

responsive to changing trends and consumer demand.

A combination of factors has taken place in the fashion market which has

contributed to the rise of fast fashion. Fashion trends work along the principle of product

lifecycle (PLC) management whereby products have a limited time in the market place

from their introduction to decline (Bruce and Barnes, 2005). There has been a decline in

the length of fashion PLCs which has put pressure on retailers to replenish more

frequently as they simply need more product ranges to keep up to date. The PLCs of

fashion products have decreased from months to weeks and even days (Barnes et al,

2007).

Consumers have become increasingly fashion “savvy” and are interested in

fashion and appearance for longer, therefore the size of the market for fashion product

has increased (Bruce and Daly, 2006; Mintel, 2009). It is suggested that the phenomenal

growth in media and magazine availability and its coverage of fashion has contributed to

this growth in the fashion aware consumer (Barnes et al., 2007; Doyle et al., 2006). As

consumers become more confident about fashion, the growth in demand for new fashion

product increases and in the UK fashion consumers now want ever changing styles

(Bruce and Daly, 2006; Barnes, 2008).

Mintel (2007) identified the importance of media in influencing trend searching

behavior on the high street whereby consumers look to magazines for ideas about the

latest trends and then actively search for these key pieces. Weekly glossy magazines in

particular have been identified as key information providers and increasingly television

shows also have a strong fashion focus. Indeed fashion pervades all aspects of the media

from broad sheets to tabloid newspapers, popular television shows to serious

documentaries and is a particular feature of the twenty first century zeitgeist. Catwalks

have traditionally been the drivers of fashion and Zara’s fast fashion proposition has

been based on the interpretation of catwalk trends (Doeringer and Crean, 2006; Sull and

Turconi, 2008).

However, celebrity driven trends are also phenomenally important at high street

level as fashion consumers look to celebrities (usually through the weekly magazines) as

style advisers (Crompton, 2004). This interest in fashion means that consumers are

shopping more frequently as demand is driven by weekly magazines and daily television

shows, so they expect to see new looks and the latest pieces every time they shop

(Barnes, 2008). Fast fashion is being driven by catwalk styles, celebrity looks and the

desire for newness, particularly those items identified in the media which create interest

and drive high levels of consumer demand.

1.2 Background of research place

Nowadays, younger love fashion and like to go shopping mall. Fashion has

become an integral part of them. City square strategically located right in the center of

the City of Johor Bahru state. City Square Shopping Mall offers an array of exciting

lifestyle shopping, food and entertainment. It is spoilt for choices with over 150 fashion

stores to choose from, and the average daily flow of more than 7,000 people (City

Square Statistics). Focus there a lot of people who love fashion. Here is a stylish

gathering place in the Johor Bharu. In this study, the city square huge flow of people

provided us with good samples.

1.3 Problems Statement of the Study

The theoretical underpinning of fast fashion is derived from the literature of

supply chain management. It is now a key concept for firm established within the

context of fast fashion with effective management of the supply chain. In order to

improve responsiveness of supply chains in the fashion industry, several concepts have

been made and introduced such as:

a) Just-in-time (JIT) – Bruce et al. (2004) addressed JIT in a fashion context to be

the delivery of finished goods to meet consumer demand rather than holding

expensive inventory.

b) Agile supply chains – Addressed by Christopher et al. (2004) and Bruce et al.

(2004), describing shorter, more flexible, demand driven supply chains. The key

difference in agile supply chains, according to Christopher et al. (2004) is that

they are driven by information such as market data and information-sharing

between businesses in the supply chain. To fulfil consumer demand for fast

fashion, attention has been paid to the ability to respond to dynamic fashion

consumer demand. Bergvall-Forsberg and Towers (2007) address this and

suggest that sourcing garments closer to consumer markets, particularly in

continental Europe creates agile supply networks.

c) Quick response – synonymous with the textile and apparel supply chain more

recently applied to fashion forward garments (Christopher et al., 2004; Giunipero

et al., 2001). Fernie and Azuma (2004) focused on the notion of integration and

collaboration in quick response to improve supply chain efficiency.

d) Demand chains – in a study outside the fashion industry, the concept of having

customer focused supply chains was defined by Treville et al. (2004) as

“efficient physical supply of the product”.

Fast fashion is about the ability to react to trends and improve response times

(Hayes and Jones, 2006), therefore fast fashion is linked with the concept of supply

chain management and quick response (Barnes and Lea-Greenwood, 2006; Sheridan et

al., 2006). Therefore, analyzing these supply chain concepts, the notion of fast fashion is

characterized by interrogation of supply chain theories with the fashion consumer at its

heart. Indeed, the paper by Barnes and Lea-Greenwood (2007) went some way to

provide a thorough review of the extant literature in this field, alongside empirical

evidence to develop a greater understanding of the fast fashion concept, developing a

research framework and concluding that at the crux of the fast fashion strategy was an

orientation which is responsive to consumer demand. Therefore, the natural extension of

empirical research would appear to be an exploration of fast fashion within the retail

environment where consumer demand meets the conclusion of the supply chain.

1.4 Research Questions

1. What is the demand of customer for fashion?

2. What factors that the fast fashion can attract the consumer?

3. Is there the relationship between Customer loyalty and those factors?

1.5 Purpose of the study

Recently there are increasing apparel companies compete in the market and

create closure environment, and all the apparel companies are offer different way to

attract the consumer base on own creativity. The purpose of the study is to identify the

demand of the customer for fashion. Moreover, this study also carried out in order to

identify the factors that the fast fashion can attract customer. Lastly, this study also

carried out to identify the relationship between customer loyalty and the relationship

with the factors that attract customers.

1.6 Objective of the study

Overall, there are three objectives for this study. There are:

1. To identify the demand of customer for fashion products.

2. To identify the factors that the fast fashion can attract the consumer.

3. To identify the relationship between Customer loyalty and those factors.

1.7 Significance of the study

The study is important in many ways, especially to understand people's views on

fashion. Besides that, it also provides the useful information for the marketer and

company. This can make the marketing process going smooth and help the company in

make the best decision to the company, find the best production and sales methods.

Through this study also, apparel companies can adjust their production patterns and

determine the suitable and appropriate marketing strategies to get more market share and

continue to compete in the competitive market.

1.8 Scope of the study

The studies will focus to the City Square Shopping Mall user. The entire

respondent is based on the finding that retrieved by the observation done in City Square

Shopping Mall. A survey was conducted and distributed at the shopping mall and

targeted on fashion customers by randomly selected.

1.9 Limitation of the study

When do the research, there are some limitation need to be draw attention to. The

sample for this research was only gathering the data from the consumer of City Square

Shopping Mall. The findings may not represent the same as others consumer perceptions

in fast fashion in Malaysia. Other than that, the result only show current situation, it may

change or different in the future research.

Besides that, the others limitation is the willingness of the respondents to answer

to questionnaire. Most of the respondents just simply fill up the answer and not even

have a clearly understanding of the question that being ask.

CHAPTER II

LITERATURE REVIEW

2.1 Introduction

This chapter consists of the definition of fast apparel industry and the leading

time, the fast apparel industry process, supply chain, the methods of increases Cost-

effective and fast apparel industry development.

2.2 Defining Fast apparel industry

Fast fashion is a contemporary term used by fashion retailers to acknowledge that

designs move from catwalk to store in the fastest time to capture current trends in the

market (Hines, Tony, and M. Bruce. 2001). This has developed from a product driven

concept based on a manufacturing model referred to as "quick response" developed in

the U.S. in the 1980 and moved to a market based model of "fast fashion" in the late

1990s and first part of the 21st century. Zara have been at the forefront of this fashion

retail revolution and their brand has almost become synonymous with the term but there

were other retailers who worked with the concept before the label was applied such as

Benetton (Hines, T. 2001). Fast fashion has also become associated with disposable

fashion because it has delivered designer product to a mass market at relatively low

prices. Fast fashion is a term used to describe clothing collections which are based on

the most recent fashion trends presented at Fashion Week in both the spring and the

autumn of every year (Muran, Lisa,2007). These trends are designed and manufactured

quickly and cheaply to allow the mainstream consumer to take advantage of current

clothing styles at a lower price. This philosophy of quick manufacturing at an affordable

price is used in large retailers such as H&M, Zara, and Topshop. According to the data

demonstrated that each consumer one year patronized ZARA equally 17 times, but the

profession had equally 3 to 4 times (S.G. Hayes and Nicola Jones, 2006).

2.3 Leading time

Now competes the intense commercial society, the efficiency and the speed is

getting more and more important to enterprise's success. If the enterprise has grasped the

efficiency and the speed, can grasp the market taking the initiative, the capture profit

opportunity. Famous clothing enterprise INDITEX and H& M is by the unique operation

pattern, reduces the leading time, to market demand change rapid reaction. Thus

succeeds in the clothing industry, leads the apparel industry the tidal current.

Actually what is the leading time? The leading time is refers to a clothing by to

design the time which the sell needs. What advantage reduces the leading time to be able

to bring for the enterprise? We may compare with the clothing the fruit, the fresh fruit

can sell good. Demonstrated according to the material that the computer product

depreciates every day about 0.1 percent, but the fashionable clothing daily rate of

depreciation reaches as high as 0.7 percent. (Lang Xianping, 2006).

The more fashionable clothing's demand is unstable, therefore the fast leading

time can let the clothing company to the market tidal current rapid reaction, this then

enhances clothing's value, but may also let the company not need to complete the

massive end product clothing in advance, reduces the goods in stock expense and the

goods in stock risk (Murphy, C., 2005). The short leading time may also cause the

company to reduce to the tidal current forecast question, avoids producing not the

clothing which is welcome the customer, thus avoids the company storing up because of

the predictable error the clothing, may also avoid the loss which promotes sales by the

discount causes, enhances the group overall finally the profit margin.

2.4 The Fast apparel industry process

ZARA and H& M is not an inventor, but is the fast reactor. They do not crave in

the creation tidal current, but to already exist in the tidal current carries on the rapid

reaction. ZARA and H&M the reason that the rapid reaction pattern the success, is really

because they can just appeared in the fashion trend, the accurate recognition and

promotes the corresponding clothing design rapidly, thus fast response tidal current. In

fact, they will only choose most receive the tidal current clothing which the customer

will welcome, will improve, will thus create massively the clothing design which in a

short time is welcome the customer.

2.4.1 ZARA fast imitation

ZARA will send for from all over the world the special record young fashionable

leaders to put on is dressing up, also from media and so on profession association,

fashionable clothing release conference will collect each kind about the fashion

information. Guaranteed that oneself can grasp the customer personal status rapidly the

transformation. ZARA is having 200 people of design teams in Spain, the huge design

team obtains the design spirit lid from the regional collection's fashionable clothing

information, and this causes ZARA to be possible to produce the extremely numerous

designs every year the fashionable clothing.

In 2004, ZARA then promoted has surpassed 12,000 model of fashionable

clothing. ZARA entire team in INDITEX headquarters work, therefore discusses, the

verification, the authorization to be very rapid. Once the design is approved to pass, the

production instruction may issue the factory immediately. From the design to the

production, may two days complete most quickly (Carmen Lopez and Ying Fan, 2009).

But the body for fashionable clothing designer's GAP, solely is the design usually also

achieves 2 to 3 months (Wells, J.R. and Raabe, E.A., 2005). But ZARA had already

produced in this period of time many in 6 model of fashionable clothing.

2.4.2 H& M fast imitation

Is the same with ZARA, H& M has also adopted the fast imitation strategy. It not

places the main energy and the resources on the self-style clothing which how to create

most passes through, but how concentrates the majority of resources to absorb fast the

newest tidal current information, the goal is must the best creativity quickest duplication.

Does not need to create the tidal current not to represent personally does not need

to find out by secret inquiry the customer personal status. H& M invested many

resources in this aspect. Depends upon information system's auxiliary, H&M designer

may grasp very quickly to receives the design which the customer welcome, thus

strengthens this series the design. Thus the designer may obtain the regional tidal current

trend to design their main source fast (Larenaudie and S.R., 2004). This procedure's

advantage reduces the design time, achieves reduces the leading time the goal, moreover

may reduce produces is not welcome the customer the design the risk.

Thus it can be seen, ZARA and H& M is not the tidal current inventor, but is the

fast reactor. Through the choice fast imitation tidal current fashion, causes them not to

need to guess the fashionable clothing tendency, in reduces the inventory risk in the

situation, reduces the design greatly the fermentation time, thus achieves the fast

imitation, the rapid reaction, satisfies the consumer by the quickest speed to the fashion

need.

2.5 Fast apparel industry supply chain

This section we will study the fast apparel industry supply chain, we use two

different company’s supply chain which is ZARA and H&M.

2.5.1 ZARA conformity Supply chain

ZARA has not depended upon the high tech the information system, is mainly

through the conformity, the highly effective nimble supply chain reduces the leading

time highly. It has her textile mill and the clothing processing factory, moreover in the

European some main area establishment independent physical distribution transportation

enterprise, nearly has also controlled the dress designing, the production, the physical

distribution as well as the sales entire supply chain(D’Andrea, G. and Arnold, D., 2002).

Design Department Production

Retail sales conformity in the sale Physical distribution conformity

Figure 2.1: ZARA Supply chain

1. Fast imitation 1. Material supply

2. Coordinate cooperate production

3. Concentrates European

1. Automation physical distribution

allocation center

2. Speed supreme transportation

3. Open new physical distribution center

4. Establishes the workshop in the Americas

1. POINT OF SALES

2. Feedback

2.5.1.1 Production line's conformity

In the purchase aspect, INDITEX has freedom cotton material company

COMDITEL, COMDITEL produces 89 percent the cotton material is for should ZARA,

not only like this may speed up the ZARA purchase the speed, but may also coordinate

ZARA the production. At the same time, ZARA also has more than 260 cotton material

suppliers momentarily to await orders (Ghemawat, P. and Nueno, J.L. 2003). Such huge

supplier quantity besides weakens they respective bargaining power, also has

safeguarded raw material stability, fast and low price supply.

In the production aspect, ZARA has more than 20 to be responsible for highly the

automated working procedure specially located at Spain's capital crowded innate factory.

Except the manpower crowded tailoring work, the ZARA 50 percent clothes are by the

innate plant production, hit confirms a guarantee with the guarantor has proven fast, the

nimble characteristic(Ghemawat, P. and Nueno, J.L. 2003).

The ZARA purchase raw material and the production concentrate in Europe. In

purchases, 95 percent cotton materials are come from Europe, this reduces the time

which greatly the purchase needs. In produces, the ZARA production base also

concentrates in Europe, the majority fashionable clothing producers can based on the

cost consideration, shift the production line to some labor cost low country. But ZARA

about 80 percent fashionable clothing can in the European area production, only then

about 20 percent fashionable clothing only then in the low cost area production.

Concentrates Europe's purchase and the production speeds up ZARA the production and

the allocation speed (Mazaira, A., Gonzalez, E. and Avendan˜ o, R., 2003).

2.5.1.2 Physical distribution conformity

ZARA has a huge physical distribution allocation center in LA CORUNA. This

physical distribution center located at transportation key position. In there, some about

200 kilometers underground conveyer belts connect LA CORUNA the physical

distribution allocation center and the ZARA factory, moreover there also has the most

advanced optics read tool, each hour can choose and sort surpasses 60,000 clothes.

ZARA through the reduction to the artificial dependence, the goods transportation error

ratio is only 0.5percent (Tiplady, R., 2006).

The ZARA production program surpasses 80 percent to carry on Europe, may

arrive at the European staple market fast, but the basic design, and may from Asia and so

on low cost local production. Because of geographical position's superiority, 75 percent

goods are transport to Europe's each chain store by the freight transportation contractor

from the physical distribution center with the truck, guarantees in two days to arrive, not

only ships the cost to be low, moreover the speed is quick(Liz Barnes and Gaynor Lea-

Greenwood, 2006). Transports to the far sale point the cargo by Europe's yieldly, for

example US and Japan chain-like, ZARA will do not hesitate the cost, will transport to

this area directly by the airplane. But other competitor based on the cost consideration,

only will often use the ship to transport, in the middle of this already phase difference

many days. The ZARA physical distribution efficiency in the apparel industry already

was best.

When ZARA expands, its cargo productivity in the growth, the physical

distribution capacity will be also saturated, thus has delayed its fast leading time. Before

the crisis has not appeared, ZARA already spent 100,000,000 Euros to open a new

physical distribution center in Spain's ZARAGAOZA. ZARAGOZA is the railroad and

road's key position, is also very near to the international airport. The advantageous

position raised the physical distribution efficiency (Lang 2006).

Because of the north and south hemisphere season's difference, so ZARA in

Americas' Argentina, Brazil and Mexico sets up the warehouse (D’Andrea, G. and

Arnold, D., 2002). The coordinate north and south ball's season difference, saves the first

end product in the Americas. When season change, South America ZARA has the tidal

current fashionable clothing's store first.

2.5.1.3 Retail sales conformity in the sale

ZARA has used POINT OF SALES. This system through the goods bar code's

scanning, may real-time collection data and so on store each kind of sale, inventory, and

stock. Moreover, it may also feed in customer's personal status information the

headquarters (Liz Barnes and Gaynor Lea-Greenwood, 2006). The ZARA design

department work's designer obtains these information, thus grasps the market tidal

current fast, designs fashionable clothing which the customer likes.

2.5.1.4 Subtotal

ZARA to the leading time's control is the apparel industry maximum level. Its

leading time's reduction relies on supplies chain's high conformity. From designs the

retail sales, ZARA makes the altitude control. In the production, the outsourcing

production and the automated innate factory cooperates mutually highly the coordination,

causes the production to be faster, and is more nimble. The physical distribution aspect,

the highly effective physical distribution allocation center and the transportation pattern,

raised the allocation speed, POINT OF SALES to the information transmission, causes

the designer to grasp the fashion trend rapidly. The fast nimble supply chain enables

ZARA to respond customer's demand by the quickest speed.

2.5.2 H&M conformity supply chain

H&M mainly places the attention in information system's conformity. H&M

takes ICTs. ICTs can connect the entire supply chain, reduces the time which each

procedure needs, causes the procedure the engagement to be smoother. H&M insisted

that self-management all branch stores, make the information the circulation to be

quicker, enable ICTs the effect to obtain a fuller display (Larenaudie, S.R. 2004).

Figure 2.2: H&M Supply chain

Retail Stores

Design

Department

ICTs Platform Physical

distribution

Department

Procurement

Department Manufacturer

Goods

Information

Customer

preference

information

Sales records

Inventory records

Design

samples

Sales records

Inventory records

Order

Inventory

records

2.5.2.1 ICTs introduction

ICTs is Information and Communication Technologies, is mainly refers to applies

each kind of communication software and the equipment provides each kind of

application and the service. Main application in long-distance study, long-distance work,

video frequency conference, management information system and inventory control.

Perhaps you will discover that these so-called communication technology will be very

actually similar with our commonly used computer communication tool. Actually the

science and technology is not a key, more importantly ICTs was H&M has brought

anything. ICTs were at least H&M has brought the information and the communication.

2.5.2.2 ICTs advantage

The information aspect, may share various shops each model of clothing's sold

note with the aid of the ICTs, H&M department, the design department may act

according to these information to obtain customer's fondness, the physical distribution

department may act according to the goods in stock information prompt supplement

goods, the purchase department may increase the customer according to the sold note to

welcome the design the output. The information causes the decision-making to be more

accurate smoothly and quickly. According to the customer demand decided that

increases production some designs is very difficult, if the leading time is not very short,

after the production increase clothing completes, maybe this design already was not

popular(Bruce, M., Daly, L. and Towers, N. 2004).

The communication aspect, ICTs is connecting each department's information

communication. This is very important to entire supply chain's connection. Each

department's work relates in together. ICTs can enable them a better communication,

this to reduces the leading time to have the very major function.

2.5.2.3 ICTs conformity supply chain

ICT can be the real-time transmission sold note help the designer to obtain

customer's fondness, thus enhances them to the tidal current reaction time. Reduces time

taken to design fashionable clothing's. This and ZARA is the same, how do they take

seriously to grasp the customer to like. Draws support from the advanced science and

technology again, the time which the H&M design clothing uses may reduce.

The new development's fashion design can transmit to the purchase department;

the purchase department primary cognizance gives these designs and production

quantity the production department to contact the appropriate producer. The purchase

department will also give the production department according to the sold note issuing

production increase order (Larenaudie, S.R. 2004). These are complete through ICT.

Had this technical auxiliary, may save the time which between the department

communicates.

H&M has 22 Production departments distribute in the world. 10 are distributed

Asia, 10 in Europe, other two in Africa and Americas. Production department primary

cognizance coordinated and monitoring clothing producer. These 700 producers have 60

percent are located at Asia; close 40 percent are located at Europe, other distributions in

the world (S.G. Hayes and Nicola Jones, 2006).

H&M has 40 percent producers to be located at Europe, they mainly produce the

fashion the clothing, like this may let tidal current design fast arriving at staple market

Europe. Other basic designs by 60 percent Asian producer production, because the basic

design to the leading time's demand is not very big, therefore may through produce as

well as the water transportation in Asia reduces the cost. And communication between

the transnational departments must certainly realize through ICT, H&M also give dual

attention to the leading time and the cost with the aid of ICT.

Reviews ZARA, its producing area distribution and H&M are different. It has

surpasses 80 percent production program is carries on Europe, although the leading time

further reduces, the cost will actually rise. ZARA thought that controls the leading time

to be more important than the control cost.

The producer's clothing general first transport delivers the physical distribution

center to carry on the classification, after undergoing automated the local divergence

procedure, ships again after the outsourcing pick-up service company to the regional

divergence center. The H&M physical distribution center is very effective. Because its

plenary powers control entire supply chain's each link, but also has ICT auxiliary, the

overall system processes every day equally the cargo achieves 1,640,000, each link is by

surpasses 2300 staffs to control(Lang Xianping,2006). H&M processes every day cargo

quantity is huge, the cargo process's procedure is complex, and mass data

communication which between departments involves all carries on by the ICT system.

After the cargo arrives at the branch store, branch store POINT OF SALES will

collect the sold note, the ICT terminal feeds in the sold note the headquarters the ICT

platform. Hence the entire supply chain undergoes a circulation, passes through each

procedure by ICT (Larenaudie, S.R. 2004).

2.6 Increases Cost-effective

ZARA and H&M Wants achievement “the inexpensive fashion”, they must

reduce the cost, like this can create the huge profit for them. How to give dual attention

to the leading time to reduce enterprise's operation cost.

2.6.1 ZARA increases the Cost-effective the strategy

Reduces the leading time to cause the cost the enhancement, to make up this loss,

ZARA has mainly adopted four methods.

1. ZARA each design's output little drinks does not stop promotes the new product,

enables customer's shopping desire to obtain the promotion, only then little the

partial commodities will store up, the majority goods can sell by the positive

valance. Generally, ZARA are most only then 18 percent clothing’s not to

conform to customer's taste, needs to discount the sale, this is only half

profession average (S.G. Hayes and Nicola Jones, 2006). In addition, to save the

cost, ZARA will not use the expensive designer, because they only will be the

tidal current fast with the follower, will not be unnecessary to invite the name

brand the designer (Tiplady, R. ,2006).

2. They will not have the huge propaganda, its propaganda cost will only account

for the total sales volume 0.3 percent, will be lower than the profession

horizontal 3.5 percent (Tiplady, R. 2006). Does not use the expensive propaganda

strategy is not gives up communicating, they increase customer's feedback

channel through the different method, collects customer's opinion. Strengthens

using the email with customer's communication. These are the low cost and the

high efficiency propaganda and the communication strategy. Moreover, ZARA

the commodity demonstrates and the display window design to the shop in is

fastidious. The superior geographical position and in the characteristic shop

designs, lets ZARA have the attraction (Lang Xianping, 2006).

3. In the production process, they do not have the laborer crowded factory, but will

produce the clothing next life with Spanish and Portugal's some small processing

factory conclude and sign contract, will be quite weak because of the small

factory's bargaining power, like this will be more advantageous to the control

product cost(Lang Xianping,2006). The factory majority staffs are the non-inside

helpers, these people mostly live in the small town or the village has not

requested too high to the wages.

4. ZARA uses the information system is UNIX, relative present quite universal

Microsoft windows or the LINUX operating system, the UNIX system operates

Chen this to be obviously low, every year only needs 200,000 Euros(Tiplady,

R. ,2006). The ZARA dependence is not the advanced operating system, but is

the simple system can coordinate the effective information communication.

Reduces the leading time the strategy is the ZARA main superiority.

2.6.2 H&M increases the Cost-effective the strategy

Sells the cheap fashionable clothing is the H&M important competitive power.

Therefore to reduce the cost, H&M has mainly used the reduced middle link, in the low

cost area production and the economies of scale strategy.

1. H&M is an importer, is also the retail merchant, nearly plenary powers has

controlled the entire supply chain's operation, reduced the business agent to earn

the profit the opportunity. H&M was only the outsourcing has produced and

ships the procedure, but the outsourcing production might reduce the non-core

business the expenditure, the choice outsourcing shipped may also reduce the

cost(Liz Barnes and Gaynor Lea-Greenwood, 2006). H&M through controls

supplies the chain majority, gains more profits.

2. In the H&M 700 contract producer has 60 percent to be located at Asia (S.G.

Hayes and Nicola Jones, 2006). Asia is the production cost quite low area,

because the commodity main supply comes from the low production cost area,

therefore the cost control is quite relaxed.

3. Through uses ICT, many producers may obtain the production increase

information fast from the production department, will be also easier to the future

demand to grasp. The H&M producer only makes the very few productions in

advance, main production after sale data analysis increases production. This kind

of pattern only then the very short leading time only then may carry on. The

producer is only comes according to the information to purchase the cotton

material massively in advance, later working procedure for example dyeing and

tailor before obtaining the order form to confirm will not carry on. Like this both

may control the cost, and may maintain the flexibility.

2.7 Conclusion

From the previous study, we can conclude that the nature of fast fashion industry

is a fast reaction. For quick response, it must integrate processes, a rapid, efficient and

flexible supply chain to reduce lead time. In reducing the lead time, we must also

consider the cost-effectiveness and lead time of balance.

CHAPTER III

METHODOLOGY

3.1 Introduction

In this chapter, the whole methodology concept of the research will be discussed.

Throughout this chapter, researcher will discuss about research design, conceptual

framework of the study, population and sampling procedure, data collection method,

research instrument and data analysis.

3.2 Research Design

The research design is a roadmap for conducting the marketing research project

(Naresh and Mark. 2006). It provides details for each step in the marketing research

project. Implementation of the research design will lead to all the information needed to

structure or solve the research problem. The research design is based on the results of the

problem definition and the approach. There are two broad types of research design:

exploratory and conclusive. Conclusive design can be either descriptive or causal.

Descriptive design is further divided into cross-sectional and longitudinal. These will be

shown in the Figure 3.1.

Figure 3.1: Classification of Research Design

(Source: Adapted from Naresh and Mark, 2004)

According to Naresh and Mark (2004), exploratory is defined as the research

conducted to explore the problem situation, to gain idea or insight into the problem

facing by the researchers. Exploratory research has to be flexible and unstructured.

Conclusive research is designed to help the researcher in determining, evaluating and

select the best action in a certain situation. In this research, the researcher used the

descriptive research. Descriptive research is type of conclusive research that has its

major objective or description of something, normally market characteristic or functions

(Naresh and Mark, 2004).

Descriptive research uses many data collection techniques such as secondary

data analyzed quantitatively, surveys which are interviews with a large number of

respondents using a predesigned questionnaire, panels, observational and other data.

Descriptive research using these methods can be divided again into cross sectional and

longitudinal research as shown in Figure 3.1. According to Naresh and Mark (2004),

sample survey involving one-time collection of information from any given sample of

population elements. Longitudinal design involving a fixed sample of population

elements that is measured repeatedly on the same variables. The sample remains the

same over all the time, giving a sequence of picture which represents both the situation

and the changes that take place.

3.3 Research Framework

Independent variable Dependent variable

Figure 3.2: Flow Chart of Research Process

Factors that affect the fast

fashion industry

Update rate

Price

Design

Customers’

Loyalty

Brand

3.4 Data Collection Method

There were two types of data collection method being used in this research that

primary data and secondary data. In this research, both sources were use to collect data

for the study.

3.4.1 Primary Data Collection

Primary data is defined as the data observed or collected directly from first-hand

experience. The primary data can be obtained by using many quantitative ways such as

surveys using the questionnaire, or even by the qualitative ways such as using interviews,

observation, experience or discussions. Quantitative measurement is more valuable than

the qualitative data. Quantitative measurement is objective that involves a huge number

of respondents for the research.

3.4.2 Secondary Data Collection

According to Norazman Abdul Majid & et al., (2007), “secondary data

come from reading what others have experienced and written”. In this research,

secondary data come from journals, electronic resources, previous study, books, and

newspapers. Secondary data is use to support the results of the study.

3.5 Population and Sampling

The population of study is the customers in city square. For this research, random

sampling method will be use on this study. The selection of the number of respondents in

the population was based on Krejcie and Morgan (1970) method that shown in table 3.1

as below.

Table 3.1: Determining Sample Size from a given Population

N S N S N S N S N S

10 10 100 80 280 162 800 260 2800 338

15 14 110 86 290 165 850 265 3000 341

20 19 120 92 300 169 900 269 3500 246

25 24 130 97 320 175 950 274 4000 351

30 28 140 103 340 181 1000 278 4500 351

35 32 150 108 360 186 1100 285 5000 357

40 36 160 113 380 181 1200 291 6000 361

45 40 180 118 400 196 1300 297 7000 364

50 44 190 123 420 201 1400 302 8000 367

55 48 200 127 440 205 1500 306 9000 368

60 52 210 132 460 210 1600 310 10000 373

65 56 220 136 480 214 1700 313 15000 375

70 59 230 140 500 217 1800 317 20000 377

75 63 240 144 550 225 1900 320 30000 379

80 66 250 148 600 234 2000 322 40000 380

85 70 260 152 650 242 2200 327 50000 381

90 73 270 155 700 248 2400 331 75000 382

95 76 270 159 750 256 2600 335 100000 384

Note: “N” is population size

“S” is sample size.

(Source: Krejcie, Robert V., Morgan, Daryle W., “Determining Sample Size for Research

Activities”, Educational and Psychological Measurement, 1970).

The population of city square is more than 7000 customers every day. For this

research, 364 customers were randomly selected from the city square.

3.6 Research Instruments

In the research, the instrument being used was questionnaire. A questionnaire is a

formalized set of questions for obtaining information from respondents (Naresh and

Mark, 2004). Based on the study's objectives, questionnaires have been designed to

collect data and needs to get feedback from the respondents.

3.7 Data Analysis Method

Statistical package for social science (SPSS) for windows will be used to

analyze the data. After the data is collecting from the questionnaire, it will be analyzed,

processed and transformed into useful information. The information that we get will is

expected to meet the objective of the study. After that, the conclusion can be made. In

this study, there are three methods that will be used. They are the descriptive analysis,

correlation analysis.

Table 3.2: Method of Analysis for the Objectives Research

No Research Objective Method of Analysis

1 To identify the demand of customer for fast

fashion

Descriptive Analysis:

Frequency

2 To identify the factors that the fast fashion can

attract the consumer

Descriptive Analysis:

Mean Score / Median Score

3 To identify the relationship between Customer

loyalty and those factors

Correlation Analysis:

Pearson / Spearman

3.7.1 Descriptive Analysis

Descriptive analysis is the analysis, which is concerned with obtaining,

organizing and summarizing the collected data and information. In this study, descriptive

statistics in the form of mean score, percentage and frequency were used to analyze Part

A and Part B of the questionnaires. The outcome of the mean computed are then used to

determine the rankings of the respected categories from the most to the least favored

items.

The formula to calculate mean is as below:

Where X = Mean

Xi = Sample number i

n = Sample size

The mean score will use to analyze the questionnaire’s answer of Part B into

three mean range which are high significant, moderate significant and low significant

(Table 3.3). The mean range is computed by the formula below:

Mean score = Highest scale –Lowest scale/Number of range

Table 3.3: Level of Mean Score

Source: Schafter et al. (1990)

3.7.2 Linear regression analysis

According to Berenson et al (2010), multiple regression models with two

independent variables represent the change in the mean of Y per unit change in X1,

taking into account the effect of X2.

Below is the calculation to calculate the multiple regression models with two

independent variables:

γi= β0+ β1X1i+ β2X2i+ β3X3i+ β4X4i+εi

β0 = Y intercept

β1 = slope of Y with variable X1, holding variable X2, X3, X4 constant

β2 = slope of Y with variable X2, holding variable X1, X3, X4 constant

β3 = slope of Y with variable X3, holding variable X1, X2, X4 constant

β4 = slope of Y with variable X3, holding variable X1, X2, X4 constant

εi = random error in Y for observation i

Mean Score Significant

1.00 –2.33 Low

2.34 –3.67 Moderate

3.68 –5.00 High

In this research, γi refer to the customer loyalty, and X1 to X4 refer to dimension

which are:

γi = Customer loyalty

X1 = Dimension 1 (Price)

X2 = Dimension 2 (Design)

X3 = Dimension 3 (Update rate)

X4 = Dimension 4 (Brand)

Regression coefficients in multiple regressions are called net regression

coefficients; they estimate the mean change in Y per unit change in a particular X,

holding constant the effect of the other X variable.

3.8 Conclusion

This chapter is discussed methodology used in the study in order to

systematically collect and analyze the data. In addition, design and instrument of

questionnaire, data collection methods, and data analysis methods using in next chapter

are discussed accordingly in this chapter. Primary data obtained from questionnaire and

secondary data obtained from books, journals, online articles and previous study. Finally,

all findings are presented and discussed in following chapter which data analysis.

CHAPTER 4

FINDINGS AND ANALYSIS

4.1 Introduction

This chapter discusses the data analysis of the research. The data analysis was

carried out by using the Statistical Package for Social Science (SPSS) software based on

the questionnaire returned by the shopping mall. A total of 364 sets of questionnaire

were distributed, and the analysis is based on the 364 sets of questionnaire. The analysis

of the data will be aimed to meet the objective proposed in Chapter 1, which are:

a) To identify the demand of customer for fashion.

b) To identify the factors that the fast fashion can attract the consumer.

c) To identify the relationship between customer loyalty and those factors.

4.2 Reliability Analysis

Reliability is a statistical method that uses for measuring the level of reliability

data and variables in the questionnaire of the study. Cronbach’s alpha is a measure of

internal consistency. It will shown how closely related a set of items are as a group. A

high value of alpha is often used as evidence that the items measure an underlying

construct. If the score of the reliability analysis for data or variables is above 0.6, the

data and variables are considered as high reliability. In order to identify the reliability

score, statistical calculation formula which is the Cronbach’s coefficient alpha is used

with SPSS. The table 4.1 below shows that the reliability analysis results for the five

different variables which is price, design, update rate, brand and loyalty.

Table 4.1: Reliability Analysis

Variables Cronbach’s Alpha N of Item

Price 0.842 6

Design 0.701 5

Update Rate 0.762 4

Brand 0.901 3

Loyalty 0.802 4

In the table above, it shown the results of the reliability test that have been test on

10 respondents, where the price variable have Cronbach’s Alpha of 0.842, next is the

design with 0.701 Cronbach’s Alpha. Followed by the update rate with 0.762 score and

brand with 0.901score. Lastly is the loyalty with the 0.802 Cronbach’s score.

4.3 Demographic Data

This section will describe the demographic background of the respondents of

City Square Shopping Mall. The demographic information of the respondents includes

ethnic, gender, age, occupations. The demographic data will provides with basic

background information about the respondents.

4.3.1 Gender

The frequency and percentage for the respondents’ gender are shown as

in table 4.2.

Table 4.2: Frequency Distribution of Respondents based on Gender

Gender Frequency Percent (%)

Female 174 47.8

Male 190 52.2

Total 364 100

Table 4.2 showed that out of 364 respondents, there were 52.2 percent male

respondents and female respondents were 47.8 percent.

4.3.2 Ethnic

The frequency and percentage for the respondents’ ethnic are shown as in

table 4.3.

Table 4.3: Frequency Distribution of Respondents based on Ethnic

Ethnic Frequency Percent (%)

Chinese 268 73.6

India 3 0.8

Malay 93 25.5

Total 364 100

Table 4.3 shows that vast majority of the respondents of shopping mall are

Chinese, in which they cover 73.6 percent of the total respondents. This is followed by

Malay, covering 25.5 percent, and the India covering 0.8 percent. These results show

that City Square Shopping Mall customer is mostly Chinese.

4.3.3 Age

The frequency and percentage for the respondents’ age are shown as in table 4.4.

Table 4.4: Frequency Distribution of Respondents based on Age

Age Frequency Percent (%)

Below 20 years old 16 4.4

20 – 35 years old 284 78

36 – 50 years old 57 15.7

Above 50 years old 7 1.9

Total 364 100

Referring to the above table, there were a majority 78 percent respondents under

the category of 20-35 years old. Followed by the category of 35 – 50 years old have 15.7

percent. And the category of Below 20 years old has 4.4 percent, the category of above

50 years old have 1.9 percent. This means that the respondent of the research was more

to 20– 35 years old.

4.3.4 Occupations

The frequency and percentage for the respondents’ occupations are shown as in

table 4.5.

Table 4.5: Frequency Distribution of Respondents based on occupations

Occupation Frequency Percent (%)

Business 15 4.1

Government 7 1.9

Professional 238 65.4

Students 104 28.6

Total 364 100

Referring to the above table, there were a majority 65.4 percent respondents are

professional. Followed by the category of students have 28.6 percent. And the category

of business people have 4.1 percent, the category of government sector have 1.9 percent.

This means that the respondent of the research was more to professional.

4.4 Identify the demand of customer for fashion

This part will discuss the demand of the customer for fashion among the

respondents in the City Square Shopping Mall. In order to achieve the first objective, the

descriptive analysis was used in this study.

4.4.1 Fashion Retailer

The frequency and percentage for the respondents’ aware of fast fashion retailers

are shown as in table 4.6.

Table 4.6: Frequency Distribution of Respondents based on aware of fast

fashion retailers

Fashion Retailer Frequency Percent (%)

Yes 175 48.1

No 189 51.9

Total 364 100

Referring to the above table, there were a 48.1 percent respondents are aware of

fast fashion retailers. And there were 51.9 percent respondents are not.

4.4.2 Budget of purchasing

The frequency and percentage for the respondents’ budget of purchasing are

shown as in table 4.7.

Table 4.7: Frequency Distribution of Respondents based on budget of

purchasing

Budget of Purchasing Frequency Percent (%)

Under 1000 68 18.7

1000 – 1500 172 47.5

1500 – 2000 108 29.7

2000 – 3000 11 3.0

Over 3000 4 1.1

Total 364 100

Referring to the above table, there were majority 47.3 percent respondents

budgets of purchasing between RM1000 to RM1500. Followed by the category of

between RM1500 to RM2000 that is 29.7 percent. And the category of under RM1000

has 18.7 percent, the category of between RM2000 to RM3000 has 3.0 percent, the

category of over RM3000 has 1.1 percent. This means that the respondent of the

research was more to budget of purchasing between RM1000 to RM1500.

4.4.3 Frequent of purchase

The frequency and percentage for the respondents’ times of purchase are shown

as in table 4.8.

Table 4.8: Frequency Distribution of Respondents based on times of purchase

Frequent of purchase Frequency Percent (%)

4 – 6 times per month 10 2.7

2 – 4 times per month 94 25.8

Less than 2 times per month 260 71.4

Total 364 100

Referring to the above table, there were a majority 71.4 percent respondents

times of purchasing less than 2 times per month. Followed by the category of 2-4 times

per month have 25.8 percent. And the category of 4-6 times per month have 2.7 percent.

This means that the respondent of the research was more to times of purchase less than 2

times per month.

4.4.4 Clothing Store/ Brand of choose

The frequency and percentage for the respondents’ Clothing Brand of choose are

shown as in table 4.9.

Table 4.9: Frequency Distribution of Respondents based on Clothing Brand of

choose

Clothing Store Frequency Percent (%)

Foreign 338 92.9

Local 26 7.1

Total 364 100

Referring to the above table, there were majority 92.9 percent respondents

usually choose the foreign brand. And there were only 7.1 percent respondents usually

choose the local brand. This means that the respondent of the research was more to

choose foreign brand.

4.5 Identify the factors that fast fashion can attract the consumer

This part will discuss the overall consumer attract dimension level of

respondents towards fast fashion. In order to achieve the second objective, mean score

and descriptive analysis was used in this study. In the data analysis method, mean was

used to analyze the data. Table 4.10 below showed that the summary of mean for all

dimension question.

Table 4.10: Summary mean for all dimensions’ question

N Minimum Maximum Mean Std. Deviation

Price1 364 2.00 5.00 3.7445 .93189

Price2 364 2.00 5.00 3.7555 .79468

Price3 364 2.00 5.00 3.7060 .72641

Price4 364 2.00 5.00 3.3956 .87360

Price5 364 1.00 5.00 3.2445 .91999

Design1 364 2.00 5.00 4.1044 .81317

Design2 364 2.00 5.00 4.1044 .76066

Design3 364 3.00 5.00 3.9148 .67697

Design4 364 1.00 5.00 3.5962 .85865

Design5 364 2.00 5.00 3.9780 .77464

Update1 364 2.00 5.00 3.8984 .62377

Update2 364 2.00 5.00 3.6374 .83010

Update3 364 2.00 5.00 3.5522 .74228

Update4 364 2.00 5.00 3.2198 .63942

Brand1 364 2.00 5.00 3.1016 1.06178

Brand2 364 1.00 5.00 2.7418 .88720

Brand3 364 2.00 5.00 3.9121 .76275

Valid N

(list wise) 364

From the table 4.10 above, it shown that the price dimension have the minimum

score between 1 and 2, and the maximum score between 4 and 5. In the others hand, the

design have minimum score of 1 until 3, and all maximum score is 5. Next is the update

rate, where the update rate is majority having the minimum score of 2 and all the

maximum score is 5. Last is the brand dimension, where most of the minimum score

between 1 and 2, the maximum score at 5.

Below is the calculation for the mean score for each dimension:

1. Price

=𝐴1 + 𝐴2 + 𝐴3 + 𝐴4 + 𝐴5

𝑁

= 3.74 + 3.76 + 3.71 + 3.40 + 3.24

5

= 17.85

5

= 3.57

2. Design

= B1 + B2 + B3 + B4 + B5

N

= 4.10 + 4.10 + 3.91 + 3.60 + 3.98

5

= 19.69

5

= 3.938

3. Update rate

= 𝐶1 + 𝐶2 + 𝐶3 + 𝐶4

𝑁

= 3.90 + 3.64 + 3.55 + 3.22

4

= 14.31

4

= 3.5775

4. Brand

= D1 + D2 + D3

N

= 3.10 + 2.74 + 3.91

3

= 9.75

3

= 3.25

The summary of the result of analysis is stated on Table 4.11.

Table 4.11: Summary result of consumer attract dimension level of respondents

towards Fast Fashion factors

Dimension Mean Score Descriptive Level

Price 3.57 Moderate

Design 3.94 High

Update Rate 3.58 Moderate

Brand 3.25 Moderate

In order to achieve the second objective in this research which is identify the

most preferred dimension level of the fashion. Therefore, the highest mean score will be

the main factor that affecting on the fast fashion.

Table 4.11 showed that the design was getting the highest mean score which is

3.94 This indicated that the respondents are more concern about the design of the

fashion offer than others dimension. The second higher mean score was update rate

which obtained 3.58, followed by price with mean score 3.57 and lastly the lowest mean

score among the four dimensions was brand where only obtained 3.25 score.

As a conclusion from the result above, the design was the most preferred

dimension on the fast fashion and the brand was the least preferred dimension on the fast

fashion.

4.6 Identify the relationship between customer loyalty and those factors

The method of regression technique with significance level of 0.05 is used to

identify the most dominant predictor in explaining the customer loyalty. The dimensions

which were not significant were removed based on the significant level of regression

technique. The independent variables have 4 dimensions, there are price, design, update

rate and brand. While, the overall question of overall customer loyalty of fast fashion

was dependent variable. Below is the model that used in this research:

γi= β0+ β1X1i+ β2X2i+ β3X3i+ β4X4i+εi

γi = Customer loyalty

X1 = Dimension 1 (Price)

X2 = Dimension 2 (Design)

X3 = Dimension 3 (Update rate)

X4 = Dimension 4 (Brand)

εi = Constant

Table 4.12 Model Summary of Regression

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 0.516a 0.266 0.258 0.39917

Table 4.12 showed the R value of this regression model is 0.516. That meant 51.6%

of the overall customer loyalty (dependent variable) could be predicted from the

dimensions of price, design, update rate and brand. Besides, the R square was 0.266. The

R square showed that 26.6% of the variation in the overall customer loyalty was

influenced by price dimension, design dimension, update rate dimension and brand

dimension.

Table 4.13 Result of Multiple Regression Analysis

Beta( 𝛽) Significant

Price 0.135* 0.019

Design 0.373** 0.000

Update rate 0.142** 0.008

Brand 0.224** 0.000

Adjuster R2 0.258

32.509

0.000

F Statistic

Sig. F

* p-value ＜ 0.05

** p-value ＜ 0.01

All of dimensions was used in this multiple regression analysis because its

significant level was smaller than 0.05.

In the regression model, the dimension with the highest beta value is the main

predictor that brings the greatest influence to the overall customer loyalty of fast fashion.

As a result, the major predictor is design (B=0.373) dimension , followed by brand

(B=0.224) dimension and update (B=3.540) dimension, finally by price (B= 0.135)

dimension.

4.7 Conclusion

At the end of this chapter, the data is successfully evaluated, presented and

interpreted accordingly into useful information. All the 364 respondents are City

Square’s shopping customer. First of all, the demografic data of the respondents, such as

the gender, ethnic origin, age and occupation will be collected through part a of the

questionnaire.

Furthermore, the mean score will use to identify the factors that the fast fashion

can attrack the consumer. The dimensions included is price, design, update rate, and

brand. as in the part B in the questionnaire. More than that, the last objective in this

chapter is to identify the relationship between customer loyalty and those factor, the

Linear regression analysis is used to analysis the data that have been collected in part C.

Conclusion which based on finding and observation in this chapter will be discussed at

the following chapter.

CHAPTER 5

CONCLUSION AND RECOMMENDATIONS

5.1 Introduction

This chapter summarizes the findings of this research. Conclusion was drawn

according to the data that were being analyzed. Other than that, recommendations and

implications of this research for fast fashion, limitation of the research and suggestion

for further future research will be discussed throughout this chapter.

5.2 Research Conclusion

The conclusion to this research can be drawn based on the objectives of the study.

The objectives of this study are:

1. To identify the demand of customer for fashion products.

2. To identify the factors that the fast fashion can attract the consumer.

3. To identify the relationship between Customer loyalty and those factors.

Based on the data analysis results described in Chapter 4, the objectives of this

research can be achieved.

5.2.1 Demand of customer for fashion products

The first objective of the study is to identify the demand of customers for fashion

products. This study focused on the customers background of budget on purchasing,

Frequent of purchase, Clothing Brand of choose, the respondents are giving their own

information on this issues.

From the study result there are 48.1% of respondents are aware of fast fashion

retailers. And there were 51.9 percent respondents are not. This result is not high,

because the fast fashion is new industries. Fast fashion has developed from a product

driven concept based on a manufacturing model referred to as "quick response"

developed in the U.S. in the 1980s, and moved to a market based model of "fast fashion"

in the late 1990s and first part of the 21st century (Lowson, B., R. King, and A. Hunter.

1999).

Result of the finding, it is showed that majority respondents budget for

purchasing are between RM 1000 to RM 1500 that is 47.8 percent. Followed by the

second higher percent which is 29.7 percent where the budget for purchase is between

RM 1500 to RM 2000. The average Malaysia household salary in 2010 was roughly

2550 Ringgit Malaysia per month according to figures issued by the government of

Malaysia. According to the research result that has been carried out at American, most

probably the society will spend 6 percent of their total income to make their purchase on

clothes, so the budget for purchase in Malaysia is about RM 1836 annually. That amount

is more than study result, because many of the respondents are students, they are not

afforded to make purchase compare to others.

In the frequent of purchase there were majority 71.4 percent respondent’s of

purchasing less than 2 times per month. The fast fashion lead time is 4 to 6 week (Hines,

Tony. 2001), the research shows that fast fashion enough to meet the customers demand.

On the other side, there were 92.9 percent respondents choose the foreign brand.

Consumers are more prefer to foreign brand compare to local brand because they

perceive that foreign branded products are high quality products (Forney, et. al., 2006).

According to Gamble, et al. (2010), well-known and well-respected brand name is one

of key success factors for company to capture the market share. According to Power &

Whelan (2005), brand reputation represents certain performance and quality of product

and others will believe that brand is good and trustworthy.

5.2.2 Factors that the fast fashion can attract the consumer

The first objective of the study is to identify the factors that the fast fashion can

attract the consumer. A set of question have been create and test under each factors

which are price, design, update rate and brand dimensions in order to find out the result.

The average mean score are obtained and the result will indicate the degree of agreeable

of respondents toward each factor of fast fashion.

From the result, the average mean score showed that the design have a higher

score among the others dimension in the fast fashion which is 3.94. Design is an

important element of innovation that is often overlooked. It helps determine how we

interact with, and experience, products and services and this, in turn, will affect which

products or services we will buy and what we are prepared to pay for them. Design can

affect the profitability and user satisfaction “Design, as I see it, is arguably the number

one determinant of whether a product-service-experience-brand proposition stands

out.”(Tom Peters, 2004)

Understanding the user’s actual needs, anticipating their future or hidden needs

and ensuring they have greater and deeper satisfaction is the key to sustainable

profitability. Good design takes the user’s requirements and shapes the product or

service to take into account what is affordable, useful, accessible and pleasurable. By

developing something that combines these elements, they will have a product or service

that will sell and give continuing satisfaction. “At Sony, we assume all products of our

competitors will have basically the same technology, price performance and features.

Design is the only thing that differentiates one product from another in the marketplace.”

(Norio Ohaga, former Chairman and CEO, Sony, ) Good design differentiates a product

or service, turning insights into customer preference. Properly applied, design can give

industry a sustainable advantage, help them command a premium price, gain market

share and even reduce production costs. For design to provide the profitability, customer

satisfaction, competitive advantage and return on investment that is possible, it has to be

given a high priority, no matter how large or small the firm is. Design has to be

effectively managed, and embedded into all aspects of the firm’s activities.

5.2.3 Relationship between Customer loyalty and those factors

The third objective of the study is to identify the relationship between the

customer loyalty and those factors which are the price, design, update rate and brand.

From the result in the finding, it shows that all the four factors have a

relationship among the four factors with the customers’ loyalty. According to the result

in chapter 4, it shows that the factor design was positively associated with the customer

loyalty with the Beta value of 0.373. The second strong correlation was among the brand

factor and the customer loyalty which obtained a Beta of -0.224. The β (Beta) value

indicated the partial correlation coefficient value and design factors with the strong β

(Beta) value was the most dominant factors for overall effect customers loyalty. Besides,

more higher the β (Beta) value, the more validity of the factor. Thus, design was the

most validity factor of customers’ loyalty on purchase.

The t value for the factor design is 7.391 while the t-value for the brand is -3.752.

In brief, the relationship among the two factors was significant because the significant

value is 0.000 is less than 0.05.

For the conclusion, there was had a positive relationship between the two factors

which is design and brand to the customers loyalty, the design is the most important

factors that influences customers loyalty.

5.3 Recommendation

This section includes recommendations for Fast Fashion Industry.

Recommendations were drawn based on the findings of the research. Individual opinions,

ideas and biases are not included in recommendation suggestions.

5.3.1 Recommendation for marketers

In today competitive marketplace, Design is the most important in the fashion

industry, fashion design and fast updates to attract customers. Brand awareness is also

important to increase customer loyalty. Other than the four factors which is price, design,

update rate and brand, the marketers need access more information of the others factors.

Marketers need establish a competitive advantage in order to continue competes,

develop and increase their level in the marketplace. Marketer need to monitor and

review the customer needs and wants from time to time. In order to get the information

about that, marketers can conduct a survey to get feedback and opinion from the

customers on current preference. Moreover, the marketer also can do the industry

scanning where admittance more information about the competitor, how the same level

competitor promotes and positioning their product and service. Besides that, the

marketers also can identify the condition in the current marketplace, like the availability

of product in the market, promotion and discount of the fast fashion product.

Besides that, the fast fashion is very common in the European country because

the consumption level is high, and Europe is leading the fashion around the world, so

their demand toward the fashion product is higher compare than the Asia country.

Compare to the already saturated European Market, the Asia country still have huge

potential for development.

5.3.2 Recommendation for future researcher

There are several shortcomings in this research. Few recommendations are given to

future researchers in order to improve their future research quality by obtain better or

more accurate result. First of all, this study focused on Johor Bharu customers who like

fashion‚ the result is only true for this particular customer only. Future researchers are

suggested to carry out same or similar research on other city‚ customer in order to

determine there are any similarities between two researches. If possible, the future

researchers are suggested widen their sample size which cover customer come from

different city rather that just focus on particular city only doing the research.

5.4 Conclusion of the study

As a conclusion, three objectives of the study have been achieved. Firstly, the

demand of customer for fashion have been identified. Secondly, the analysis shows that

factor of design is the main factor that will influence purchase intention of customer on

fashion product. price, brand, and update rate are moderate influence purchase intention

of customer on fashion products. Thirdly, there have strength relationship between all

the four factors with customers loyalty, these factors affect the customer loyalty together.

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APPENDIX A

SURVEY QUESTIONNAIRE

UNIVERSITI TEKNOLOGI MALAYSIA

FACULTY OF MANAGEMENT AND HUMAN RESOURCE

DEVELOPMENT

BACHELOR OF MANAGEMENT (TECHNOLOGY)

TOPIC: CUSTOMER DEMAND FOR FAST FASHION INDUSTRY

The objectives of this study are:

4. To identify the demand of customer for fashion

5. To identify the factors that the fast fashion can attract the consumer.

6. To identify the relationship between Customer loyalty and those factors.

Prepared by: Supervised by:

LI KAI Dr. Huam Hon Tat

Tel: 014-9115624

Email: [email protected]

Note: All information collected will be used for research purpose only and all

information will be treated with strictest confidentially.

PART A: DEMOGRAPHY OF RESPONDENT

Instruction: Please tick (√) and fill in the appropriate information below.

1. Gender:

Male Female

2. Ethnic Origin:

Malay India

Chinese Others

3. Age:

Below 20 Years Old 36 – 50 Years Old

20 – 35 Years Old Ab Over 50 Years Old

4. Occupations:

Students Business people

Government Sector Professional

Not working Others: __________(Please Specify)

PART B: BACKGROUND OF CUSTOMERS DEMAND

Instruction: Please answer the following questions by ticking √ the appropriate Box.

1. Are you aware of any fast fashion retailers?

Yes

No

2.What is your budget of purchasing clothes? (per year in RM)

Under 1000 1000-1500

1500-2000 2000-3000

Over 3000

3.How often do you purchase clothes?

More than 10 times per month

7-10 times per month

3-6 times per month

less than 2 times per month

4.What clothing store/brand do you usually choose?

Foreign

Local

PART C: DETERMINATION THE FACTOR EFFECT THE FAST FASHION

Instruction: Please state your opinion by ticking √ the appropriate box based

on the given scale.

Strongly

Disagree

Disagree Neutral

Agree

Strongly

Agree

1 2 3 4 5

No. Statement 1 2 3 4 5

Price

1. Consider price of products before purchasing.

2. Income level is very important for my

fashion

3. Price decided to brand quality

4. Relative to expensive fashion brand I prefer

to

choose inexpensive fashion

5. Consider the price more than other factors

6. I will buy discount fashion, although they

may not be popular

Design

7. Design is the most important factor about

fashion

8. I prefer diversity design rather than a single

style

9. Designed to focus on fashion, rather than

different from others

10. Relative to the design style, I focus on

whether it is fashion

11. Customer's idea is very important to design

Update Rate

12. Fashion need to quickly update

13. If it is updated enough fast, I would often

visit it

14. Quick update may affect the frequency of my

patronage

15. In Malaysia. Updated the sooner the better

Brand

16. The brand will affect my choice

17. Brand is important to my social

18. I would choose a fixed brand, if it meets my

needs

PART D: DETERMINATION OF CONSUMERS’ LOYALTY

Instruction: Please state your opinion by ticking √ the appropriate box based

on the given scale.

Strongly

Disagree

Disagree Neutral

Agree

Strongly

Agree

1 2 3 4 5

NO. Statement 1 2 3 4 5

1. I will recommend the fast fashion brand to

my friends

2. I believe fast fashion brand is the best

3. I will use fast fashion products

4. Fast fashion can meet for my needs

APPENDIX B

Reliability Test - Price

Reliability Statistics

Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items

.842 .841 6

Reliability Test - Design

Reliability Statistics

Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items

.748 .759 4

Reliability Test - Update rate

Reliability Statistics

Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items

.762 .738 4

Reliability Test - Brand

Reliability Statistics

Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items

.901 .926 3

Reliability Test - Loyalty

Reliability Statistics

Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items

.802 .788 4

Statistics

Gender Ethnic Age Occupations B1 B2 B3 B4

N Valid 364 364 364 364 364 364 364 364

Missing 0 0 0 0 0 0 0 0

Gender

Frequency Percent Valid Percent Cumulative Percent

Valid Female 174 47.8 47.8 47.8

Male 190 52.2 52.2 100.0

Total 364 100.0 100.0

Ethnic

Frequency Percent Valid Percent Cumulative Percent

Valid Chinese 268 73.6 73.6 73.6

India 3 .8 .8 74.5

Malay 93 25.5 25.5 100.0

Total 364 100.0 100.0

Age

Frequency Percent Valid Percent Cumulative Percent

Valid Below 20 yeard old 16 4.4 4.4 4.4

20-35 years old 284 78.0 78.0 82.4

36-50 years old 57 15.7 15.7 98.1

Above 50 years old 7 1.9 1.9 100.0

Total 364 100.0 100.0

Occupations

Frequency Percent Valid Percent Cumulative Percent

Valid Business 15 4.1 4.1 4.1

Government 7 1.9 1.9 6.0

Professional 238 65.4 65.4 71.4

Students 104 28.6 28.6 100.0

Total 364 100.0 100.0

B1

Frequency Percent Valid Percent Cumulative Percent

Valid yes 175 48.1 48.1 48.1

no 189 51.9 51.9 100.0

Total 364 100.0 100.0

B2

Frequency Percent Valid Percent Cumulative Percent

Valid under 1000 68 18.7 18.7 18.7

1000-1500 173 47.5 47.5 66.2

1500-2000 108 29.7 29.7 95.9

2000-3000 11 3.0 3.0 98.9

over 3000 4 1.1 1.1 100.0

Total 364 100.0 100.0

B3

Frequency Percent Valid Percent Cumulative Percent

Valid 4-6 times per month 10 2.7 2.7 2.7

2-4 times per month 94 25.8 25.8 28.6

Less than 2 times per month 260 71.4 71.4 100.0

Total 364 100.0 100.0

B4

Frequency Percent Valid Percent Cumulative Percent

Valid Foreign 338 92.9 92.9 92.9

Local 26 7.1 7.1 100.0

Total 364 100.0 100.0

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

Price1 364 2.00 5.00 3.7445 .93189

Price2 364 2.00 5.00 3.7555 .79468

Price3 364 2.00 5.00 3.7060 .72641

Price4 364 2.00 5.00 3.3956 .87360

Price5 364 1.00 5.00 3.2445 .91999

Design1 364 2.00 5.00 4.1044 .81317

Design2 364 2.00 5.00 4.1044 .76066

Design3 364 3.00 5.00 3.9148 .67697

Design4 364 1.00 5.00 3.5962 .85865

Design5 364 2.00 5.00 3.9780 .77464

Update1 364 2.00 5.00 3.8984 .62377

Update2 364 2.00 5.00 3.6374 .83010

Update3 364 2.00 5.00 3.5522 .74228

Update4 364 2.00 5.00 3.2198 .63942

Brand1 364 2.00 5.00 3.1016 1.06178

Brand2 364 1.00 5.00 2.7418 .88720

Brand3 364 2.00 5.00 3.9121 .76275

Loyalty1 364 3.00 5.00 4.1951 .57292

Loyalty2 364 1.00 4.00 2.8626 .50652

Loyalty3 364 2.00 5.00 3.7857 .61944

Loyalty4 364 2.00 5.00 3.6319 .66114

Valid N (listwise) 364

Model Summaryb

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .516a .266 .258 .39917

a. Predictors: (Constant), MEANBRAND, MEANDESIGN, MEANUPDATE, MEANPRICES

b. Dependent Variable: MEANDLOYALTY

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 1.982 .225 8.793 .000

MEANPRICES .111 .047 .135 2.355 .019

MEANDESIGN .306 .041 .373 7.391 .000

MEANUPDATE .128 .048 .142 2.648 .008

MEANBRAND -.130 .035 -.224 -3.752 .000

a. Dependent Variable: MEANDLOYALTY