Fashion Branding and Consumer Behaviors

International Series on Consumer Science

For further volumes: http://www.springer.com/series/8358 Tsan-Ming Choi Editor

Scientific Models

1 3 Editor Tsan-Ming Choi Business Division Institute of Textiles and Clothing The Hong Kong Polytechnic University Hung Hom, Kowloon Hong Kong SAR

ISSN 2191-5660 ISSN 2191-5679 (electronic) ISBN 978-1-4939-0276-7 ISBN 978-1-4939-0277-4 (eBook) DOI 10.1007/978-1-4939-0277-4 Springer New York Heidelberg Dordrecht London

Library of Congress Control Number: 2014930099

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Springer is part of Springer Science+Business Media (www.springer.com) Preface

Effective branding is a critical success factor for all kinds of fashion brands and affects consumer welfare. By effective branding strategies, fashion brands can create equity, foster consumer brand loyalty, and enhance profitability. Essentially, consumers buying branded fashion products enjoy not only the functional needs of the products but also the excitement and other social needs (e.g., self-image projection, showing desirable lifestyle and social status etc). Proper branding strategies can enhance both dimensions and create a win-win situation in which consumers are more satisfied and the fashion brands make more profit. In the long run, both the fashion brands and consumers will be much benefited. Despite being an important and timely topic, there is currently an absence of a comprehensive reference source that provides the state-of-the-art findings on both theoretical and applied scientific research on fashion branding and consumer behaviors. In view of the above, I have edited this Springer handbook. This handbook contains three parts, with Part I including mainly literature review and introductory works, and Parts II and III including original research studies. The details are listed below: Part I: Introduction and Literature Review • Fashion Branding and Consumer Behaviors: An Introduction • Luxury Fashion Branding: Literature Review, Research Trends, and Research Agenda • Fashion Brand Personality and Advertisement Response Part II: Analytical Modeling Research • Optimizing Fashion Branding Strategies: Management of Variety of Items and Length of Lifecycles in a Stochastically Fluctuating Market • An Analysis of Fashion Brand Extensions by Artificial Neural Networks Part III: Empirical Studies • A Comparative Investigation Between Status and Non-Status Seeking Teenagers for Luxury Fashion • Co-branding in Fast Fashion: the Impact of Consumers’ Need for Uniqueness on Purchase Perception v vi Preface

• How Brand Awareness Relates to Market Outcome, Brand Equity and the Mar- keting Mix • Consumer Perceived Risks Towards Online Group Buying Service for Fashion Apparel Products I am pleased to see that this handbook contains new analytical and empirical results with valuable insights, which will contribute to the literature on consumer science and fashion marketing. To the best of my knowledge, this research handbook is the first one which specifically examines fashion branding and consumer behaviors with a focal point on scientific research. It can be used as a textbook for senior un- dergraduate and postgraduate students in fashion marketing, marketing, branding, and consumer science. It is also a good reference book to the academics, researchers, scholars, and practitioners in fashion marketing and branding. Thus, it is a pioneering text focusing on this important topic. As a remark, all featured papers are peer-refereed by two reviewers who are knowledgeable in the respective domain. I would like to take this opportunity to thank Jing Jian Xiao and Jennifer Hadley for their support and advice along the course of carrying out this book project. I am grateful to all the authors who have contributed their interesting research to this handbook. I am indebted to the reviewers who reviewed the papers and provided me with all the constructive and timely comments. I also acknowledge the editorial assistance of Dr. Bin Shen and Ms Hau-Ling Chan. Last but not least, I am grateful to my family, colleagues, and students, who have been supporting me during the development of this important research book.

The Hong Kong Polytechnic University Tsan-Ming Choi October 2013 Contents

Part I Introduction and Review

1 Fashion Branding and Consumer Behaviors: An Introduction �� 3 Tsan-Ming Choi

2 Luxury Fashion Branding: Literature Review, Research Trends, and Research Agenda �� 7 Tsan-Ming Choi

3 Fashion Brand Personality and Advertisement Response: Incorporating a Symbolic Interactionist Perspective �� 29 Hye-Shin Kim and Martha L. Hall

Part II Analytical Modeling Research

4 Optimizing Fashion Branding Strategies: Management of Variety of Items and Length of Lifecycles in a Stochastically Fluctuating Market �� 49 Y. Fujita

5 An Analysis of Fashion Brand Extensions by Artificial Neural Networks �� 63 Tsan-Ming Choi and Yong Yu

Part III Empirical Studies

6 “Domestic-Made” or “Foreign-Made” Luxury Brands? �� 77 Ian Phau

7 Co-branding in Fast Fashion: The Impact of Consumers’ Need for Uniqueness on Purchase Perception �� 101 Bin Shen, Jaehee Jung, Pui-Sze Chow and Szeman Wong

vii viii Contents

8 How Brand Awareness Relates to Market Outcome, Brand Equity, and the Marketing Mix �� 113 Rong Huang and Emine Sarigöllü

9 Consumer Perceived Risks Towards Online Group Buying Service for Fashion Apparel Products �� 133 Yik-Hin Chui, Pui-Sze Chow and Tsan-Ming Choi

Index �� 147 Contributors

Bin Shen Glorious Sun School of Business and Management, Donghua University, Shanghai, China Emine Sarigöllü Faculty of Management, McGill University, Montreal, QC, Canada Hye-Shin Kim Department of Fashion and Apparel Studies, University of Delaware, Newark, DE, USA Ian Phau The School of Marketing, Curtin University, Perth, Western Australia Jaehee Jung Department of Fashion & Apparel Studies, University of Delaware, Newark, DE, USA Martha L. Hall Department of Fashion and Apparel Studies, University of Delaware, Newark, DE, USA Pui-Sze Chow Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Rong Huang School of International Business Administration, Shanghai University of Finance and Economics, Shanghai, China Szeman Wong Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Tsan-Ming Choi Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Y. Fujita Department of Economics, Keio University, Tokyo, Japan Yik-Hin Chui Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Yong Yu Business Division, Institute of Textiles and Clothing, Faculty of Applied Science and Textiles The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

ix Part I Introduction and Review Chapter 1 Fashion Branding and Consumer Behaviors: An Introduction

Tsan-Ming Choi

Nowadays, effective branding is a critical success factor for all kinds of fashion brands and it also affects consumer welfare. By effective branding strategies, fashion brands can create equity, foster consumer brand loyalty, and enhance profitability. Essentially, consumers buying branded fashion products enjoy not only the functional needs of the products but also the excitement and other social needs (e.g., self-image projection, showing desirable lifestyle and social status etc). Proper branding strategies can enhance both dimensions and create a win-win situation in which consumers are more satisfied and the fashion brands make more profit. In the long run, both the fashion brands and consumers will be much benefited. Motivated by the importance of scientific research for fashion branding, this book project is organized and it features a collection of papers which present introductory and review materials, theory based analytical models, and empirical models with statistical analyses. In the following, I introduce each featured paper. In Chap. 2, Choi reviews systematically the extensive literature on luxury fashion branding. He classifies related research into three major types, namely qualitative empirical-based analysis, quantitative empirical-based studies, and analytical modeling research. Based on this classification, he further classifies each type of research into different categories and presents the scope, topics and core insights from each reviewed paper. From this extensive and original literature review, research trends on the evolution of “luxury fashion branding research” and timely topics of research on luxury fashion branding are identified. Finally, he proposes a future research agenda with topics such as counterfeiting, supply chain management on luxury fashion brands, and environmental sustainability. He also advocates that more theoretical scientific research should be done, especially on topics related to consumer welfare and supply chain management. Brand personality reflects the identity of the brand and the way consumers relate to the brand. Unlike human personality, brand personality is more dynamic and fluid for fashion brands due to its constant need to refresh and reinvent its

T.-M. Choi () Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong e-mail: [email protected] T.-M. Choi (ed.), Fashion Branding and Consumer Behaviors, 3 International Series on Consumer Science, DOI 10.1007/978-1-4939-0277-4_1, © Springer Science+Business Media New York 2014 4 T.-M. Choi identity in today’s marketplace. The symbolic interaction theory offers a way to understand the process of negotiating brand meaning within a social context for fashion brands. Using the classical three environment (marketing, social, and individual) framework, Kim and Hall offer in Chap. 3 a perspective on the dynamic processes related to consumers’ acceptance and negotiation of brand meanings. Al- though brand meanings may originate creatively from the marketer, they address the social process where the meanings accepted by the consumer are socially constructed and mutually defined. The propositions developed in Chap. 3 are derived from a review of literature that addresses the importance of advertising as an effective brand communication tool. Within the paper, fashion brand personality is explained as resulting from a dynamic process that includes creative advertising of marketers and consumers’ understanding of brand meaning. Kim and Hall discuss that impressions of brand personality may vary among consumers and negotiation of brand meaning can be a continuous process. They also examine the consumer welfare-related issues. The fashion and apparel industry is characterized by huge demand fluctuation. It is widely observed that there is an increasing number of clothing retailers which offer a greater number of products in smaller lines. As a result, the products in their storefronts are changing dynamically. In Chap. 4, Fujita constructs, by utilizing the optimal stopping theory, a stochastic dynamic consumer marketing model to investigate how a clothing retailer should introduce and withdraw the fashion products. More precisely, he formulates market fluctuation as a stochastic process and attempts to identify how to manage the number of “seasons” in a fluctuating market. His analysis reveals that consumer welfare will be enhanced because the clothing retailers will increase the variety of items with short lifecycles if (1) the clothing retailer is vulnerable to other clothing retailers’ introductions of new items or (2) the market as a whole is certain. Since these results identify the effect of each factor, they are valuable for fashion retailers who consider the difference between product vulnerability and market uncertainty. In studying fashion marketing and branding problems empirically, the traditional method is the statistical analysis. However, many statistical methods would require the satisfaction of various restrictive assumptions (e.g., on the specific distribution of the underlying process) or else they will fail to perform. To overcome this limitation, Choi and Yu employ the artificial neural network (ANN) approach in Chap. 5 to study the fashion brand extension problem. They suggest that the ANN method can provide an alternative way for identifying empirical patterns and trends in a scientific manner when the traditional statistical methods fail. Based on the new evidence generated by the ANN analysis, they discuss the implications of their findings on consumer welfare. To be specific, they reveal that the consumer welfare as related to brand extension does vary in different period of time. In addition, they point out that consumers buying European and North American brands would enjoy more variety of products of the respective fashion brands with respect to their line extensions during the earlier periods of time. This is different from the consumers who love the Asian brands because there are more line extensions for Asian brands in the later periods of time. 1 Fashion Branding and Consumer Behaviors: An Introduction 5

In Chap. 6, Phau investigates if there is a difference between status and non-status seeking Australian teenage consumers in their attitudes toward buying domestic and foreign (i.e. Italy, Japan, China)-made luxury fashion branded apparel. The classical multi-attribute attitude model is used to measure and compare attitudes of 663 teenagers. Conducting statistical analysis with the collected empirical data, the author finds that status seeking teenagers have a more positive attitude toward foreign luxury brand apparel as compared to Australian luxury brands, with the exception of Chinese brands. The non-status seeking teenagers, on the contrary, are more positive towards Australian brands than foreign brands, and they consider Australian luxury brands as superior to all three foreign brands in the dimensions of ease of care and comfort. Phau argues that the Australian fashion industry should focus its marketing strategy on enhancing the attributes of “fashionable” and “brand name” of the Australian apparel because it can help attract both status and non- status seeking teenagers. This proposed strategy can enhance the consumer welfare and utility for Australian consumers. Co-branding is a popular strategy in the fashion industry. For example, the fast fashion brand H&M has launched many co-brands with luxury designer fashion brands including Karl Lagerfeld, Stella McCartney, Jimmy Choo, Lavin, Marni and Maison Martin Margiela since the latest decade. In Chap. 7, Chow et al. explore how the consumer’s need for uniqueness affects purchase perception towards fast fashion co-branding. They conduct a self-administered questionnaire survey in Hong Kong. Their empirical results show that consumers have significantly different need for uniqueness on the fast fashion brands. Thus, from the perspective of the consumers, their level of satisfaction with respect to product uniqueness depends on the type of fashion brands. They hence argue that how the product uniqueness affects consumer welfare and utility depends on the specific type of fashion brands. In addition, their findings on the impacts of consumers’ need for uniqueness on purchase perception of fast fashion co-brand provide several insights. First, they argue that the fast fashion brand as a host brand should collaborate with a designer fashion brand which has a high degree of need for uniqueness for the consumers. Second, when the strategy of fast fashion co-branding is launched, enhancing the designer brand’s uniqueness level in marketing communication can attract more consumers to purchase the co-brand. Third, the uniqueness of fast fashion brand is significant to attract more consumers to purchase the fast fashion co-brand product. Combining survey data with real-market data, Huang and Sarigöllü investigate in Chap. 8 brand awareness, which relates highly to consumer welfare, from three critical perspectives. First, they examine the relation between brand awareness and market outcome. Second, they discuss the relationship between brand awareness and brand equity. Third, they study the effects of marketing mix elements on brand awareness. Their analysis shows that consumer’s brand usage experience will contribute to brand awareness, which reveals the important insight on “experience precedes awareness” in some contexts. Their results also confirm the existence of a positive association between brand awareness and brand equity. The findings in their paper have demonstrated the importance of distribution and price promotion in building brand awareness which can also enhance consumer welfare. 6 T.-M. Choi

Table 1.1 Type of each Paper Type chapter paper Chapter 1 Introduction Chapter 2 Literature review Chapter 3 Conceptual discussion Chapter 4 Original research Chapter 5 Original research Chapter 6 Original research Chapter 7 Original research Chapter 8 Original research Chapter 9 Original research

Risk is a critical issue affecting consumer welfare. In the last chapter, Chui et al. examine the consumer perceived risks towards online group buying service for fashion apparel. Group buying refers to a buying event participated by a group of customers who may not know each other and is usually organized by some electronic means, such as the Internet. Under group buying, customers can approach retailers together in order to get discounts for a particular product or service. Obvi- ously, the collective bargaining power of a group of customers will lead to a more favorable price for the products. Despite being attractive with more favourable price, consumers are exposed to a variety of risks under group buying for fashion apparel products. In Chap. 9, Chui et al. identify and propose six perceived risks, namely performance risk, financial risk, privacy risk, time risk, source risk, and psychological risk, that customers may face when purchasing apparel through online group buying companies. By collecting 202 valid online questionnaires via an online survey method, statistical analysis is conducted. Their statistical results find that there are relationships between perceived risks and influential factors, and there are also correlations between influential factors and risk-reducing methods. Based on the results, suggestions which can enhance online group purchasing are discussed. Table 1.1 shows the type of each paper featured in this book. As introduced above, the papers featured in this book examine different facets of fashion branding and consumer behaviors. The issues related to consumer welfare are also explored. Many timely topics are investigated scientifically and various promising future research directions are also identified. I believe that this book has generated many new research results with valuable insights on the scientific branding strategies and consumer behaviours related to fashion. To the best of my knowledge, this book is the first research hand book which devotes specifically to fashion branding and consumer behaviors. Thus, it is a pioneering text focusing on this important topic. Chapter 2 Luxury Fashion Branding: Literature Review, Research Trends, and Research Agenda

Tsan-Ming Choi

1 Introduction

The luxury fashion industry is very important in terms of its monetary sales volume (more than US$ 252 billion annually in 2011 (The Economist 2011)). The global luxury industry has seen steady growth over the past 16 years (Kim et al 2012) and it is commonly believed to be one of the most appealing and profitable industries in the world. In addition to its economic value, luxury fashion brands help develop the best fashion products for the market. They are leaders in the fashion world and drive a lot of mass-market imitators. Undoubtedly, luxury fashion is a critical part of modern fashion world and luxury fashion branding is a timely and important topic (Emond 2009; Ko and Megehee 2012). Motivated by the importance of luxury fashion industry in practice and the popularity of luxury fashion branding related studies in the recent literature, I extensively and systematically reviewed the related literature in this paper. I classified the research types into three categories, namely: (1) qualitative empirical research (QLE), (2) quantitative empirical research (QTE), and (3) analytical modeling research (AM). From the examination of the vast literature, I identified the research trend in the area and proposed new research directions in a “research agenda.” When preparing this literature review paper, I extensively searched the following portals from 25 February 2013 to 4 March 2013: Google Scholars, ScienceDi- rect.com, EBSCO Business Source Complete databases with the following set of keywords: luxury fashion, luxury clothing, luxury apparel, luxury fashion brand, conspicuous fashion, conspicuous clothing, conspicuous apparel, and conspicuous brand. I focused only on the peer-refereed papers in archival journals written in English. My initial search identified 215 papers. After initial screening, only 68 of them were retained as the majority of the other papers were not in peer-refereed archival journals written in English. After further checking of the titles and

2 Qualitative Empirical Analysis

I divide the qualitative empirical research literature on luxury fashion branding into two major subsections with respect to whether the studies focus on company (e.g., luxury fashion brands) case study or not. For those focusing on company case studies, I further classify them into a single case study scenario and multiple cases scenario.

2.1 Company Case Study Research

2.1.1 Case Studies on a Single Brand

In a very popular paper, Moore and Birtwistle (2004) explored the performance of the British luxury fashion brand Burberry. They studied the development and brand revitalization of Burberry with reference to many publicly available official documents published by Burberry. They evaluated Burberry’s repositioning strategy and critically investigated Burberry’s revised business model at that time. Moore and Birtwistle (2005) focused on Gucci to study the nature of “parenting advantage” in luxury fashion. They reviewed Gucci’s annual reports and other secondary information sources, and identified the “ten-year renaissance” in Gucci. They argued that there is an intrabusiness group synergy in Gucci and this synergy is crucial for saving Gucci from the financial crisis that it faced at that time. They also established a multidimensional luxury fashion branding model which identifies various critical components and their interactions for luxury fashion brands. They believed that their proposed model can help luxury fashion brands to better shape the branding strategies and develop a competitive edge. Recently, Savelli (2011) conducted a case study on an Italian luxury fashion firm called Aeffe. She collected data from two means. First, she studied the reports, documents, and publications that she had found from publicly available source. Second, she conducted face-to-face interviews with several marketing managers of Aeffe. She proposed three interrelated critical dimensions which are necessary for effective brand management for luxury fashion companies similar to Aeffe. She argued that these dimensions could assist luxury fashion brands to succeed by, e.g., enhancing the brand awareness. 2 Luxury Fashion Branding 9

2.1.2 Case Studies on Multiple Brands

Brun et al. (2008) studied the Italian luxury fashion industry with a multiple-case study approach. They explored 12 Italian luxury fashion retailers. They revealed the main operational features of these companies and identified their critical supply chain management strategies. They argued that for the Italian luxury fashion companies to move up the “brand ladder” so as to be even higher ranked in the “brand tier,” marketing efforts alone are insufficient. They hence further derived the list of critical success factors, including those from supply chain management, for this purpose. Fionda and Moore (2009) adopted a qualitative multiple-case study approach to investigate the most important dimensions for the success of luxury fashion brands. They studied 12 international luxury fashion retailers and collected data via both semistructured interviews with managers of the target companies and reviews of some secondary sources such as internal documents and media reports. They successfully obtained nine interrelated attributes which are critical to the success of luxury fashion branding. They concluded their study with a comment on the fact that luxury fashion brand management is complex in general, and the luxury fashion brands should adopt a coherent approach in order to succeed. Later on, Moore et al. (2010) investigated the use of flagship stores as a market entrance strategy in luxury fashion retailing. They studied 12 luxury fashion retailers and obtained the primary data via semistructured interviews. From the collected data and observed industrial strategies, they proposed several characteristics of the flagship stores of the luxury fashion retailers. They revealed that luxury fashion retailing flagship stores can be treated as a strategy which can provide substantial support for the development of luxury fashion retailing in a foreign market. In other words, these flagship stores play a crucial role in helping the luxury fashion retailers to enter another market and go international. They also interestingly showed the interdependence of flagship stores and the wholesaling method for luxury fashion brands. Stankeviciute and Hoffmann (2010) explored brand extension strategy in luxury fashion. They examined several famous international luxury fashion brands, namely Giorgio Armani, Calvin Klein, and Jimmy Choo. They found that luxury fashion brands can collaborate with nonluxury brands to develop an extended co-brand. This extension can achieve a positive impact on themselves if the co-brand possesses the luxury fashion’s features, and the nonluxury brands have good reputation. They further revealed that a downward brand extension can enhance the parent luxury brands if the extension keeps the parent brands’ luxury fashion elements and other critical core brand elements. They also studied the brand dilution effect and argued that the luxury fashion brands have to continuously improve themselves so as to yield a successful portfolio of their brands under the brand extension strategies. Recently, Nobbs et al. (2012) explored the essential elements of the luxury fashion flagship store’s format. They revealed that the luxury fashion flagship store’s scale and size in practice are more than sufficient compared to its functional requirements. They argued that the luxury fashion flagship stores treasure exclusivity and uniqueness most and help attract customers’ visit. They explored the characteristics of the luxury flagship store format and demonstrated how the flagship store helps generate and communicate differentiation. Table 2.1 shows a summary of the case study research reviewed in Sect. 2.1. 10 T.-M. Choi brand

the

format and demonstrating how flagship store helps generate and communicate differentiation luxury fashion brands have to continuously improve themselves so as to yield a successful portfolio of their brands under the brand extension strategies success of luxury fashion branding fashion retailers to enter foreign market and go international brand success brand’s supply chain management, for successful luxury branding Identifying the characteristics of luxury flagship store Studying the brand dilution effect and proposing that the Studying the brand dilution effect Confirming the role played by flagship stores in helping luxury Research focus in saving the The importance of intrabusiness group synergy Identifying the three interrelated critical dimensions for Revitalization Choo

2.1

Jimmy

Klein,

Calvin

Armani,

Giorgio Gucci M Seven related fashion companies M international luxury fashion retailers Twelve M Deriving nine interrelated attributes which are critical to the luxury fashion retailers Twelve Type Details of the brands S Aeffe M Italian luxury fashion retailers Twelve Developing a list of critical success factors, especially those in 2004 )2005 )S S Burberry 2010 ) 2008 ) The summary of the company case studies research reviewed in Sect.

al. ( al. ( 2012 )

) 2011 al. (

single-brand case study, M multiple-brand case study S single-brand case study, Nobbs et Moore et ( 2010 )MStankeviciute and Hoffmann Savelli ( Brun et Moore and Birtwistle ( Moore and Birtwistle ( Fionda and Moore ( 2009 ) Paper Table 2.1 Table 2 Luxury Fashion Branding 11

2.2 Non-Company Case Study Research

Crane (1997) examined the production of culture theory, and conducted a study on the French luxury fashion market. He showed that a few large companies controlled by conglomerates dominate the French luxury fashion market in terms of sales but have little influence on styles. He found that rather than cooperating with the smaller firms, the large firms can benefit from the global expansion of their market to sell products other than fashionable clothing. Heine (2010) explored luxury fashion brand’s personality traits. He employed the repertory grid method which has specified certain guidelines and selection criteria on brand personality. He conducted in-depth interviews with 50 fashion luxury consumers to learn about their associations with luxury fashion brands based on the repertory grid method. He then identified 49 personality traits and five major personality dimensions which include modernity, eccentricity, opulence, elitism, and strength. After that, he conducted further face-to-face interviews with about 60 luxury fashion insiders. Finally, he concluded that there are 52 important luxury brand personality traits and argued that these findings help lay the foundation for future research on luxury fashion brand personality. Morace (2010) studied the dynamics to a new sensibility which is positioned in-between “simplicity” and “luxury.” He believed that this new sensibility involves the parallel processes of luxury. Issues such as exclusivity, creativity, authenticity, and craftsmanship are also found to be related to luxury fashion. Counterfeiting is a timely issue and challenging problem faced by luxury fashion brands. Wall and Large (2010) discussed the counterfeiting issues and examined some related issues for criminologists, policy makers, and luxury fashion brand owners. They explored the topic from different perspectives and proposed to locate the public interest in a different way. They argued that one has to thoroughly understand the rationale behind having counterfeit goods before shaping the optimal strategy to fight it. Venkatesh et al. (2010) qualitatively investigated how the consumer attitudes and preferences of females related to their bodily appearance are associated with their perceptions of the aesthetics of luxury fashion. They developed their theoretical framework based on research in aesthetics of production, aesthetics of reception and aesthetic labor. They revealed that bodily appearance and luxury fashion brands are closely linked together. This gives important implications to explore luxury fashion branding from the consumer behavior perspective. Amatulli and Guido (2011) explored the determinants of Italian consumers’ purchasing intention for luxury fashion products. They conducted 40 in-depth interviews with consumers in a luxury fashion retailer in Italy. They employed the laddering technique in data collection. They carried out the means-end chain analysis and uncovered that Italian consumers who buy luxury fashion products mainly aim to match their lifestyle and satisfy their inner drives. They further revealed that self-confidence and self-fulfillment are the two core hidden values in their mind when they buy luxury fashion products. They hence proposed that luxury fashion brands may focus on these inner drives in designing their own branding strategies. In the scope of conspicuous consumption Edgell (1992), Souiden et al. (2011) investigated the conspicuous consumer behaviors towards the purchase of 12 T.-M. Choi branded fashion accessories. They explored the problem with the consumers in Canada and Tunisia. They revealed that the conspicuous consumer behaviors in both cultures are positively influenced by social status display associated with the consumption. They also found that consumers in both cultures reckon that their social status may affect their self-image which leads to their conspicuous consumer behavior. They argued that conspicuous consumption appears to be more significant in individualist culture than in collectivist culture. Woodside (2012) explores consumer choice and firm profitability by combining theories in economics, fashion, marketing, and psychology perspectives. He employed an empirical approach to find evidence from available literature to verify the hypotheses. He found that different pricing points which maximize firm’s profitability may vary for different product designs which are in the scope of conspicuous consumption. He also revealed that the impacts brought by fashion marketing schemes and price highly depend on the chronic desires of consumers. Carrigan et al. (2013) theoretically extended the “harm chain” study with the incorporation of the institutional forces. They identified a number of harms occurring throughout the luxury fashion supply chains. They found that luxury fashion brands need to enhance their corporate social responsibility and they should no longer focus only on the economic benefits. Al-Mutawa (2013) studied the Muslim female consumers’ behaviors towards western luxury fashion brands. She conducted a preliminary qualitative study consisting of 12 in-depth interviews in Kuwait. Her findings revealed that in Kuwait, Muslim female consumers generate “modestly sexy” image that can help recreate certain symbolic meaning for western luxury fashion brands. She argued that luxury fashion brands should recognize the importance of managing “consumer-generated representations.” She further illustrated that the construction of consumer representations can be created by advertisement scheme or based on the “actual social users” of the luxury fashion brand. In a different perspective, Arrigo (2011) explored the brand enhancement policies of luxury fashion. He focused on Milan, a renowned fashion city in Italy. He demonstrated by a qualitative study on how different luxury fashion companies adopt fashion brand enhancement policies in Milan. Table 2.2 shows a summary of the case study research reviewed in Sect. 2.2.

3 Quantitative Empirical Analysis

In this section, I explore the survey-based quantitative empirical studies on luxury fashion branding. The majority of studies in this category employ the consumer survey as the data collection method and derive findings based on statistical analysis of the consumer inputs. I put these consumer survey-based studies in Sect. 3.1, in which I further organize the literature into various areas, namely the counterfeiting issues, social media marketing, Chinese consumers, and others. In Sect. 3.2, I present the company survey-based study. 2 Luxury Fashion Branding 13

fashion brand enhancement policies in Milan tions can be created by advertisement scheme or based on the “actual social users” of luxury fashion brand corporate social responsibility and should not just focus on the economic benefits schemes and price highly depend on the chronic desires of consumers inner drives in designing their own branding strategies in individualist culture than collectivist rationale behind having counterfeit goods before shaping the optimal strategy to fight it brands are closely linked together processes of luxury personality traits which are influential for luxury fashion branding conglomerates dominate the French luxury fashion market in terms of sales but have little influence on styles Revealing how different luxury fashion companies adopt Revealing how different Illustrating that the construction of consumer representa- Finding that luxury fashion brands need to enhance their Proving that the impacts brought by fashion marketing Proposing that luxury fashion brands may focus on these Conspicuous consumption appears to be more significant Proposing that one has to thoroughly understand the Revealing that bodily appearance and luxury fashion Showing that a few large companies controlled by Showing that a few large Core findings 2.2

fashion towards western luxury fashion brands the incorporation of institutional forces firm profitability are related in conspicuous consumption affect luxury fashion branding affect towards the purchase of branded fashion accessories of females related to their bodily appearance fashion Brand enhancement policies of luxury Muslim female consumers’ behaviors Muslim female consumers’ Extending the “harm chain” study with Exploring how consumer choice and How consumer lifestyle and inner drives Conspicuous consumer behaviors Counterfeiting issues How consumer attitudes and preferences A new sensibility for luxury fashionA Revealing that this new sensibility involves the parallel Luxury fashion brand’s personality traitsLuxury fashion brand’s Revealing that there are 52 important luxury brand Research focus sources Kuwait literature fashion, marketing, and psychology Tunisia in Italy literature literature ers and 60 luxury fashion insiders Luxury fashion consumers Data source

2010 ) Consumer studies 2013 ) Multiple sources including the )2011 Consumers in Canada and Guido al. (

al. ( al. (

The summary of the noncompany case studies research reviewed in Sect.

and

) 2011 ( )Arrigo ( 2011 Case studies from various Al-Mutawa ( 2013 ) Muslim female consumers in Carrigan et Souiden et ( 2012 )Woodside Literature of economics, Venkatesh et Venkatesh Amatulli Wall and Large ( 2010 ) and Large Wall Multiple sources including the Morace ( 2010 ) Multiple sources including the Heine ( 2010 ) 50 fashion luxury consum- Crane ( 1997 ) French luxury fashion market Production of culture theory for luxury Paper Table 2.2 Table 14 T.-M. Choi

3.1 Consumer Survey-Based Studies

3.1.1 Counterfeiting Issues

Yoo and Lee (2009) explored the consumer purchase intention of luxury fashion brands and their counterfeits. They identified three important dimensions, namely the past experience-based behavior, the attitudes towards buying counterfeits, and the individual characteristics. They collected data from 300 and 24 Korean female students. Their statistical analysis proved that the three dimensions are determinants of consumer purchase intention of counterfeits and originals. They specifically illustrated that the consumer purchase intention of counterfeits is positively correlated to the consumer purchase intention of the original luxury fashion brands. In addition, they revealed that the consumer purchase intention of counterfeits is negatively correlated to the consumer purchase intention of original luxury fashion products. Later on, Yoo and Lee (2012) evaluated the business risk associated with fashion counterfeit consumption behavior by examining the effect of past experiences with counterfeit luxury fashion brands and original real luxury fashion brands. Based on the consumer survey data from five luxury fashion product categories, they found that an asymmetrical effect existed in which past experiences with real original luxury fashion brands are negatively correlated to consumer purchase intention of counterfeits. They showed that past experiences with counterfeits do not correlate to consumer purchase intention of original real luxury fashion brands. They further conducted another study, which was based on experimental data from two luxury handbag brands, and confirmed the results to be valid.

3.1.2 Social Media Marketing

Kim and Ko (2010) studied the use of social media marketing for supporting luxury fashion brands. They conducted a self-administrated questionnaire with visual stim- uli to collect data from luxury fashion brands’ consumers in Korea. They confined the qualified respondents to be those who had purchased a luxury fashion brand item within 2 years (at the time of survey). They received 133 valid inputs for de- tailed analysis. Their statistical data analysis confirmed the significance of using social media marketing for luxury fashion brands in enhancing customer relationships and purchase intention. They further proposed a strategy to improve the performance of the luxury fashion brands. Under their study, all properties associated with the social media marketing of the luxury fashion brand can improve customer relationships and purchase intention, with the entertainment element being most substantial. They argued that using social media marketing is a proper way of retaining old customers and attracting new customers. Later on, Kim and Ko (2012) identified the critical attributes of social media marketing for luxury fashion branding. They examined the relationships among the perceived activities: Value equity, relationship equity, brand equity, customer equity, and consumer purchase intention. They studied the problem by using the structural equation modeling approach. 2 Luxury Fashion Branding 15

In their study, the five constructs of perceived social media marketing activities of luxury fashion brands include entertainment, interaction, trendiness, customization, and word of mouth. They found that the effects of these five constructs on value equity, relationship equity, and brand equity are positive. They derived that the brand equity has a significantly negative effect on customer equity. They showed that the value equity and relationship equity do not exhibit any statistically significant effect. They also proved that the relationship between purchase intention and customer equity is significant. They concluded by arguing that their research findings can provide a practical guide to help luxury fashion brands better forecast the future consumer purchasing behavior of their customers more accurately. Most recently, Kamal and Chu (2013) studied whether materialism is a consequence of social media usage, and how it influenced consumer attitude towards social media advertising. They conducted the study with respect to American and Arab young social media users with a goal of revealing the relationship between materialism and consumer purchase intention of luxury fashion goods of these consumers. Their studies indicated that the Arab social media users possessed a higher level of materialism and social media usage than the American users; they also exhibited a more favorable attitude towards social media advertising than the American counterparts. For both groups of consumers, they found that a positive relationship existed between materialism and consumer purchase intention towards the luxury fashion products.

3.1.3 Chinese Consumers

For luxury fashion brands, nowadays, one most important target group of consumers are the Chinese people (see Choi et al. 2008; Liu et al. 2011 for more details). It is hence not surprising to see many studies on luxury fashion branding focus on Chinese consumers. For example, Gao et al. (2009) explored market segmentation scheme of the affluent Chinese consumers. They developed systematic pro- files of the identified segments for luxury fashion products. They obtained data by surveying a representative sample of affluent consumers from 12 largest cities in China. They employed a psychographic segmentation approach to classify these consumers. They found that there are five distinct market segments of these affluent Chinese consumers. They argued that luxury fashion brands can employ these market segmentation results to better formulate their branding strategies. Jung and Shen (2011) conducted an empirical study to examine brand equity of luxury fashion brands and its relationships with cultural orientation. They focused on exploring the consumer groups who are college women from a university in China and a large public university in the USA. They found that the Chinese sample has a greater degree of collectivism and power distance than the American sample. Interestingly, they revealed that the US sample shows a higher degree of uncertainty avoidance. For the consumer-based brand equity dimensions, they further identified the cultural differences in which the American sample possesses higher score in perceived quality, brand awareness, and brand association than the Chinese counterpart. Li et al. (2012) examined Chinese consumers’ “willingness 16 T.-M. Choi to pay” for luxury fashion branded products in association with their own fashion lifestyle. They revealed that fashion lifestyle, perceived social and emotional value, perceived utilitarian value, and perceived economic value are all significantly influencing the willingness of Chinese consumers to pay for luxury fashion. Chen and Kim (2013) explored how strongly consumers’ personal values and attitudes influence their purchase intentions towards luxury fashion brands. They formu- lated personal values as a dimension which included materialism, hedonism, face saving, and social connections. They collected data from 201 Chinese consumers for statistical regression analyses. They proved that that hedonism positively influences consumer intention to purchase luxury fashion brands for self-use. Interestingly, they found that face saving and social connection, two important dimensions in Chinese culture, do not have a significant impact on consumer purchase intentions for both self-use and gift giving purposes. Most recently, Zhang and Kim (2013) investigated the factors that influence the Chinese consumers’ attitude towards purchasing luxury fashion goods and their purchasing intent. They collected consumer inputs in three major cities in China and received 161 valid inputs. Their statistical analysis indicated that brand consciousness, social comparison, and fashion innovativeness all have statistically significant impact on consumer attitude towards purchasing luxury fashion goods. They also confirmed that the purchasing intention of Chinese consumers for luxury fashion products is strongly influenced by their attitude towards purchasing luxury fashion goods.

3.1.4 Other Consumer Survey-Based Studies

In addition to the above three subsections, there are also various interesting studies on luxury fashion brands which employ consumer-based data for a quantitative analysis. For example, Kim et al. (2010a) investigated how customer–salesperson relationship influences sales effectiveness. They examined whether individuals’ self-monitoring would moderate the customer–salesperson relationship. They conducted an analysis by collecting 167 valid consumer inputs via the help of the sales managers of 21 luxury fashion retail stores in Korea. They revealed that when customers are “high self-monitors,” the perceived effect of a social relationship is reduced. They also proved that if the consumers have a good social relationship with the salesperson, they would give “credits” to the salesperson for his effort in helping them with their purchase decision. They argued that, based on their research findings, luxury fashion retailers should advise their salespeople to build a stronger social relationship with low self-monitors rather than high self-monitors. Furthermore, since their research findings indicated that high self-monitors tend to have lower levels of interpersonal commitment and less stable social bonds than low self-monitors, they proposed that luxury fashion brands have to realize the difficulty in establishing long-term loyalty from high self-monitors even if there is a strong social relationship between these consumers and the salesperson. Kim et al. (2010b) studied via a quantitative empirical consumer survey the consumer brand value and brand loyalty towards foreign luxury fashion brands in Korea. 2 Luxury Fashion Branding 17

They also explored the impact of channel diversification on consumers’ brand value and brand loyalty towards foreign luxury fashion brands. They found that consumers evaluated brand value differently depending on the type of distribution channel. They also noticed that how different brand values affect brand loyalty depends on the type of distribution channel being used. Kim et al. (2011) conducted a web-based tool to survey 316 American consumers who had purchased at least a luxury fashion branded product within 3 years at the time of survey. They aimed at exploring what personal luxury values are sought by American consumers. They argued that their research findings help luxury fashion brands to formulate and implement effective advertising, publicity, and other marketing strategies to build appealing brand images for the American market. Kim et al. (2012) investigated consumer attitude towards luxury brands and the relationship among consumer attitude towards luxury brands, drivers of customer equity and customer lifetime value. They conducted consumer survey in Korea. They showed that the factors such as the experiential need and fashion involvement are critical in affecting the consumers’ attitude towards luxury fashion brands. They showed the intuitive result that customer equity positively influences customer lifetime value. They also confirmed that consumer attitude towards luxury fashion brands would positively influence luxury fashion brand’s equity and value equity. They surprisingly found that there is no statistically significant relationship between consumer attitude towards luxury brand and relationship equity. Most recently, Miller and Mills (2012) investigated the preeminent luxury fashion brands and developed a conceptual model. They tested three specific fashion categories of the “brand luxury model” and revealed several important insights such as providing convincing evidence to confirm the importance of strong brand leadership.

3.2 Company Survey-Based Studies

In the literature, company survey-based quantitative studies on luxury fashion brands are rare. The only exception is Matthiesen and Phau (2010) in which they examined via a triangulation approach (both qualitative and quantitative approaches) on whether brand perceptions differ across supply chain channel members of a luxury fashion brand. They employed the buyer–seller exchange situation model. They focused on Hugo Boss and the Australian market. They collected data in a two-stage process in which a self-administered mail survey was first sent out to 3,592 individuals, and then in-depth interviews were conducted with 22 retail buyers. They found that there is evidence to support the claim that brand perceptions differ across channel members for luxury fashion brands. They also argued that there is a mismatch in the perceptions of wholesalers and retailers which may lead to brand image inconsistencies. Table 2.3 summarizes the quantitative empirical research reviewed in Sect. 3. 18 T.-M. Choi

mouth”

word

and

customization,

, relationship equity, and brand equity are , relationship equity, trendiness,

important dimensions in Chinese culture, do not have a significant impact on consumer purchase intentions value, perceived utilitarian and economic value are all significantly influencing the willingness of Chinese consumers to pay for luxury fashion consumers possess higher score in perceived quality, brand consumers possess higher score in perceived quality, awareness, brand association than the Chinese counterparts these affluent Chinese consumers these affluent materialism and consumer purchase intention towards the luxury fashion products interaction, on value equity positive fashion branding and it is a proper way of retaining old customers and attracting new experiences with real original luxury fashion brands are negatively correlated to consumer purchase intention of counterfeits consumer purchase intention of counterfeits and originals Showing that face saving and social connection, two Proving that fashion lifestyle, perceived social and emotional Showing the cultural differences in which the American in which the Showing the cultural differences Identifying that there are five distinct market segments of Showing that a positive relationship exists between Revealing that the effects of the constructs “entertainment, Revealing that the effects Proposing that social media marketing is important for luxury Revealing that an asymmetrical effect exists in which past Revealing that an asymmetrical effect Core findings Proving that three important dimensions are determinants of 3

values and attitudes influence their purchase intentions towards luxury fashion brands to pay” for luxury fashion branded products and its association with their own fashion lifestyle brands and its relationships with cultural orientation the affluent Chinese consumers for the affluent luxury fashion consumption and consumer purchase intention of luxury fashion goods marketing for luxury fashion branding supporting luxury fashion brands counterfeit consumption behavior fashion brands and their counterfeits The brand equity of luxury fashion The relationship between materialism The use of social media marketing for Research focus university in China and public university a large in the USA social media users consumers in Korea Data source 2013 )Arab young American and 2012 ) Consumer survey Business risk associated with fashion 2009 ) Korean female students Consumer purchase intention of luxury 2009 ) Chinese consumers The market segmentation scheme of The summary of the quantitative empirical research reviewed in Sect. (

2012 ) Chinese consumers “willingness The Chinese consumers’ al.

al. ( et

Chen and Kim ( 2013 ) Chinese consumers personal How strongly consumers’ Li et )Jung and Shen ( 2011 College women from a Gao Kamal and Chu ( Kim and Ko ( 2012 ) Consumer survey The critical attributes of social media Kim and Ko ( 2010 ) Luxury fashion brands’ Yoo and Lee ( Yoo Yoo and Lee ( Yoo Paper Table 2.3 Table 2 Luxury Fashion Branding 19

the

realize

have

brands

fashion

luxury

that

ficulty in establishing long-term loyalty from high brand perceptions differ across supply chain channel mem- brand perceptions differ bers for luxury fashion brands strong brand leadership in the luxury model fashion involvement are critical in affecting the consumers’ the consumers’ fashion involvement are critical in affecting attitude towards luxury fashion brands which can help luxury fashion brands to formulate and and other advertising, publicity, implement effective marketing strategies depends on the type of distribution channel dif self-monitors even if there is a strong social relationship between these consumers and the salesperson fashion innovativeness all have statistically significant impact on consumer attitude towards purchasing luxury fashion goods Revealing that there is evidence to support the claim Providing convincing evidence to confirm the importance of Proving that the factors such as experiential need and Uncovering the elements that American consumers treasure Uncovering the elements that Revealing that how different brand values affect brand loyalty brand values affect Revealing that how different Proposing Indicating that brand consciousness, social comparison and Core findings channel members of luxury brands branding model brands and the relationship among consumer attitude towards luxury brands, drivers of customer equity, and customer lifetime value are sought by American consumers are sought by loyalty towards foreign luxury fashion brands in Korea influences sales effectiveness nese consumers’ attitude towards nese consumers’ purchasing luxury fashion goods and their purchasing intent Whether brand perceptions differ across Whether brand perceptions differ Research focus with self-administered mail survey and then in-depth interviews with retail buyers A triangulation approach A Data source 2012 ) Consumer survey The preeminent luxury fashion 2013 ) Chinese consumers The factors that influence the Chi- continued) 2012 ) Korean consumers The consumer attitude towards luxury )2011 American consumers Identifying what personal luxury values 2010b ) Korean consumers The consumer brand value and 2010a ) Korea consumers How customer–salesperson relationship (

al. ( al. ( al. ( al. (

( 2010 ) Matthiesen and Phau Miller and Mills ( Kim et Kim et Kim et Kim et Zhang and Kim ( Table 2.3 Table Paper 20 T.-M. Choi

4 Analytical Modeling Research

Among all the identified literature on luxury fashion branding, only very few of them apply the analytical modeling approach. In fact, in classical economics studies and the marketing science literature, analytical modeling studies are a kind of mainstream research methodology for generating theoretical results by mathematical approaches such as game theory and optimization. In the area related to luxury fashion branding and conspicuous consumption, Amaldoss and Jain (2005) is one of the pioneers who studied the optimal pricing decision for conspicuous products in the presence of social effects and social influences (between the fashion follower and the fashion leader). They found that the conspicuous consumers exhibit an upward sloping demand curve only in a heterogeneous market. Rather recently, under a newsvendor model setting, Tereyagoglu and Veeraraghavan (2012) studied the pricing, production and sourcing decisions when consumers exhibit different characteristics. They modeled both the homogeneous and heterogeneous markets and compared the equilibrium decisions when the consumers are strategic and the consumers are conspicuous. They derived many important insights such as the retailer may offer higher equilibrium inventory availability even if the consumers are conspicuous. Notice that the issue of social influence is not examined in Tereyagoglu and Veeraraghavan (2012). Motivated by the importance of social needs in affecting the consumer purchase of conspicuous fashion products, Zheng et al. (2012) analytically studied the optimal advertising and pricing decisions for luxury fashion brands in a market that includes two consumer groups with different social needs. They termed these two groups as the leader group and the follower group, respectively. By building a novel and formal analytical model, they specifically examined the scenario where the leader group consumers wish to distinguish themselves from the follower group consumers. On the contrary, the follower group consumers would like to assimilate themselves with the leader group consumers. They developed the optimal solution scheme and conducted extensive sensitivity analyses. They interestingly found that it is optimal for the luxury fashion brands to focus its own advertisement effort and resource on only one group even though it is selling to both groups. Most recently, Zheng et al. (2013) extended Zheng et al. (2012) with the consideration of the presence of a penalty cost associated with insufficient advertising. To be specific, they argued that if a luxury fashion brand does not pay enough attention to either the fashion leader group or the fashion follower group, a penalty cost to its brand value may be incurred. Under this setting, they derived the new optimal solution scheme and obtained new insights on the strategic advertising decision for luxury fashion brands. Table 2.4 shows the summary of the quantitative empirical research reviewed in Sect. 3. 2 Luxury Fashion Branding 21

Table 2.4 The summary of the quantitative empirical research reviewed in Sect. 3 Paper Research focus Core findings Amaldoss and The optimal pricing decision for con- Proving the conspicuous consum- Jain (2005) spicuous products in the presence of ers exhibit an upward sloping social effects and social influences demand curve only in a heterogeneous market Tereyagoglu and The equilibrium pricing, production and Deriving many important manage- Veeraraghavan sourcing decisions with conspicuous rial insights such as the retailer (2012) consumers may offer higher equilibrium inventory availability even if the consumers are conspicuous Zheng et al. The optimal advertising and pricing Deriving the optimal policy and (2012) decisions for luxury fashion brands revealing an interesting fact with social influences that it is optimal for the luxury fashion brands to focus its own advertisement effort and resource on only one group even though it is selling to both groups Zheng et al. The optimal advertising and pricing Deriving a new optimal policy (2013) decisions for luxury fashion brands and generating insights on the with social influences in the presence strategic advertising decision for of a penalty cost associated with luxury fashion brands insufficient advertising to any one social group (which affects consumer welfare)

5 Research Trends

From the literature review above, some trends in the literature of luxury fashion brands can be identified. I present the research trends in two subsections in which Sect. 5.1 presents the evolution of luxury fashion branding research with respect to the types of research whereas Sect. 5.2 shows the trend with reference to the research topics.

5.1 Evolution of Luxury Fashion Branding Research: Types of Research

In Table 2.5, I show the publication figures across time. We can see that peer refereed research in archival English journals on luxury fashion branding only appears as a popular topic in recent years in which only 6 papers were published in or before 2008 while there were 32 papers published in the period of 2009–2013 (as of 4 March 2013). In addition, we can also observe that in the earlier time, most research studies were exploratory in nature and hence they employed mainly the qualitative approach (e.g., single company case studies). Over the past 5 years, the scenario has changed in which more and more quantitative research emerged which include both empirical-based and analytical modeling-based research. Overall speaking, the 22 T.-M. Choi

Table 2.5 Evolution of luxury fashion branding research: number of papers published under each research methodology over the past decade Year Method 2003 and 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 All years before QLE 2 1 1 0 0 1 1 6 4 2 2 20 QTE 0 0 0 0 0 0 2 5 2 5 3 17 AM 0 01000000214 TOTAL 2 1 2 0 0 1 3 11 6 9 6 41 majority of studies on luxury fashion branding still focus on empirical-based research which occupy 37/41 = 90.2 % of all the reviewed related literature.

5.2 Evolution of Luxury Fashion Branding Research: Topics

In Table 2.6, I show the distribution of topics related to luxury fashion branding research over the past decade. As expected, consumer attitude and preference related studies were the main stream among all topics. The other popular topics included Chinese consumer-based studies, counterfeiting, critical success factors, and optimal pricing. The brand revitalization topic was a relatively old topic while Chinese consumer-based studies, social media marketing, counterfeiting were some relatively popular topics in recent years (after 2010).

6 Research Agenda and Conclusion

I reviewed systematically the literature on luxury fashion branding. I identified three major types of related research, namely qualitative empirical-based analysis, quantitative empirical-based studies, and analytical modeling research. I further classified each type of research into different categories and presented the scope, topics, and core insights from each reviewed paper. From this extensive review, research trends on the evolution of types of research and topics of research on luxury fashion branding were identified. In addition, from the research trends the following areas are identified as important areas for future research and more in-depth explo- rations should be carried out.

6.1 More Scientific Research

Research on a topic is always evolving when time passes and researchers seek more and more objective evidence to support their arguments and research propositions. As we see from Sect. 5, in the earlier years, most research on luxury fashion 2 Luxury Fashion Branding 23 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 5 5 3 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 1 0 1 0 1 0 0 0 0 0 0 2 1 0 0 0 0 0 0 1 1 1 2 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 3 1 0 0 ear Y 2003 and before 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 0 0 0 0 0 1 Evolution of luxury fashion branding research: number papers published under each topic over the past decade

Revitalization

preference Table 2.6 Table Topic Brand Consumer attitude and Salesperson related issue 0 Counterfeiting Critical success factors 0 Optimal pricing Chinese consumers 0 Social media marketing 0 Flagship stores Other topics 24 T.-M. Choi branding focused on qualitative exploratory case study research. In recent years, I have seen the publication of more quantitative “scientifically sound” research. In particular, there were also some analytical modeling research which employed the classical economics approach in deriving scientifically solid theories in luxury fashion branding. I believe that it is an important and promising direction to proceed.

6.2 Counterfeiting

Counterfeiting is an interesting problem for both practitioners and academicians. The current literature only lightly touched the topic but had not yet uncovered fully the mysteries and challenges behind this topic. It hence calls for more research, in all dimensions, on this topic. In particular, it will be interesting to study this issue scientifically from the perspective of luxury fashion brands and other supply chain channel members because no prior study has examined the topic from this point of view.

6.3 Company Survey Based Scientific Research

As mentioned in Sect. 5, most current quantitative studies focused on examining luxury fashion branding problems from consumer perspectives. Despite having some qualitative case studies, there is a genuine need to look at the problem from the perspective of the companies. This applies to all topics that are important to luxury fashion branding (such as counterfeiting that I mentioned in Sect. 6.2). The use of secondary data, such as the ones from company’s financial reports, may be one way to reveal insights from the company perspective given that it can be tremendously difficult to get access to private data from luxury fashion companies.

6.4 Environmental Sustainability

One timely industrial topic in fashion branding is related to environmental sustainability. Surprisingly, in all the reviewed studies, this issue is missing and remains unexplored (the closest work to this topic is Carrigan et al. (2013), who examined corporate social responsibility issues related to luxury fashion brands). It is thus important to conduct research on how the level of environmental sustainability associated with luxury fashion affects consumer behaviors and preference. From the company perspectives, how they take environmental sustainability as a measure to establish the elements of their luxury fashion brands is also an important topic to explore further. 2 Luxury Fashion Branding 25

6.5 Supply Chain Management

It is commonly believed that a luxury fashion brand needs to reconcile the potential trade-offs between exclusivity and accessibility (Fionda and Moore 2009). In many cases, it is difficult for a luxury brand to manage its optimal distribution strategies in its supply chain network. In the current luxury fashion branding literature, supply chain management has only been examined rarely in a few studies. As a result, more research, especially the quantitative one, should be conducted to reveal more scientifically sound insights from this underexplored area.

6.6 Consumer Welfare

As shown by the review conducted in this paper, the majority of current studies on luxury fashion branding do not put enough emphasis on consumer welfare. To be specific, how the branding strategies and measures affect consumer welfare is not yet well explored in the literature. As a consequence, there is big room for future research for luxury fashion branding problems with respect to the consumer science related affairs. For example, how consumer welfare relates to the fashion brand’s tier in terms of its “level of luxury,” how consumer well-being is affected by the presence of conspicuous consumer behaviors towards luxury fashion brands.

The above proposal forms the research agenda which I believe to be promising for future research. I reckon that this literature review paper and research agenda help lay the foundation for further studies on luxury fashion branding. I also wish they can stimulate new research in other closely related topics.

References

Notation for the types of research that are reviewed: [Editorial], [QLE = Qualitative Empirical], [QTE = Quantitative Empirical], [AM = Analytical Modeling]

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Hye-Shin Kim and Martha L. Hall

1 Introduction

Brad Pitt appears in a black and white commercial wearing an untucked casual shirt with the top buttons open. He has an unrefined look with hair to the shoulders and facial hair. He says quietly, “It’s not a journey. Every journey ends, but we go on…Dreams take over. But wherever I go, there you are…my luck, my fate, my for- tune…Chanel No. 5” ( an image of the perfume bottle fades in). A full screen shot of the actor flashes back again and he says “Inevitable.” Premiering the first male spokesman for the luxury perfume brand, the Chanel No. 5 commercial went viral with millions of people viewing the commercial on YouTube (“There you are”, 2012). When aired, it was one of the most talked about commercials in the media with most people wondering about its ambiguous message and others poking fun at it. Whether consumers are left pondering about the intent of the commercial or are pleased to see the sex appeal of the popular actor, the commercial has successfully generated a lot of buzz and captured much media attention. Fashion brands are laden with intangible attributes in which consumers use to express preference. Apart from its functional attributes, advertisements for fashion brands are engineered to trigger a personal response where emotional appeal and personal connections differentiate brands from competitors. The stylistic design and creative marketing strategies position each brand to appeal to consumers in specific ways. How each brand embodies symbolic meanings to consumers and the way it is received and processed by consumers offer a point of brand differentiation in today’s competitive environment. Symbolic products differ in brand personality meaning over utilitarian products, in part due to the affective versus cognitive needs fulfilled by consumption (Ang and Lim 2006). Consumers are influenced not only by the function or quality of the product or brand, but more importantly by the symbolic meanings associated with the brands (Veryzer 1995). In particular, fashion

H.-S. Kim () · M. L. Hall Department of Fashion and Apparel Studies, University of Delaware, Newark, DE 19716, USA e-mail: [email protected] T.-M. Choi (ed.), Fashion Branding and Consumer Behaviors, 29 International Series on Consumer Science, DOI 10.1007/978-1-4939-0277-4_3, © Springer Science+Business Media New York 2014 30 H.-S. Kim and M. L. Hall products are commonly highlighted as “symbolic products” (e.g., Aaker 1997; Ang and Lim 2006). Through the years, brand personality has been noted as an important variable in building strong brands (e.g., Aaker 1997; Keller 2013). Brand personality is defined as “the set of human characteristics associated with a brand” (Aaker 1997, p. 347). Aaker (1997) notes that the dynamics of brand personalities do not necessarily correspond to human personalities and that different dimensions of brand personality must be examined independently. A widely noted study in the marketing literature is a study by Aaker (1997) which conceptualized the symbolic uses of brands and developed a generalizable scale to measure brand personality. Based on human personality research, the five dimensions and corresponding subdimensions derived by Aaker (1997) are sincerity (down-to-earth, honest, wholesome, and cheerful), excitement (daring, spirited, imaginative, up-to-date), competence (reliable, intelligent, successful), sophistication (upper class, charming), and ruggedness (out- doorsy, charming). Using Aaker’s scale (1997), Kim (2000) found consumers to have positive attitudes toward apparel brands high in the “competence” brand personality dimension. Kim (2000) notes that in addition to the image promoted for the brand, product attributes such as apparel product category, apparel line style characteristics, and target market are related to specific brand personality dimensions. For example, when compared to other brands, Victoria Secret ranked high in brand personality dimension “exciting,” Nike was ranked high in “rugged,” and JC Penney was ranked high in “sincere.” Although some brand personality dimensions (e.g., sincerity, excitement, competence) may be universal human traits in which consumers can universally relate, advertisers can focus on other personality traits (e.g., sophistication, ruggedness) which may tap into the aspirational image of the consumer (Aaker 1997). It is fair to note that Aaker’s (1997) trait-based approach to explaining brand personality has been critiqued by several scholars. A fundamental limitation to a trait-based approach is that trait-based scales are useful in describing attributes most commonly seen among people but does not cover unique attributes (Batra et al., n.d.; Lee and Rhee 2008; Romaniuk and Ebrenberg 2012). Through consumer experience or marketing activities, consumers may assign brands personality traits which are reflective of human values. Consumers use the personalities associated with particular brands for self-expression. The brands may support various dimensions of the consumer’s self, ranging from a realistic aspect of oneself to an ideal self (Belk 1988; Klein et al. 1993; Malhotra 1988). Consum- ers imbue brands with human personality traits and consider brands as celebrities or famous figures (Rook 1985). Consumers are able to develop preference for the brand based on how they personally relate to the brand. The greater consumers perceive the similarity of the brand to their selves (actual and ideal), the greater the preference for the brand (Malhotra 1988; Sirgy 1982). Brand personality serves as a symbolic or self-expressive function compared to “product-related attributes” (Aaker 1997). Unlike human personality traits, brand personality traits are formed through various exposures and experiences a consumer has with the brand (Plummer 1985). As such, perceptions of brand personality can be influenced by any direct or indirect 3 Fashion Brand Personality and Advertisement Response 31 contact the consumer has with the brand. For example, brand personality can be formed by personality impressions created by people who use the brand or the brand’s endorsers. Also, brand personality can be based on a variety of factors related to the product, marketing and communications strategy, distribution and pricing, publicity within the media, etc. In addition to personality traits, demographic traits are commonly associated with brands which can be associated with consumers who use the brand (Levy 1959). For example, upscale department stores such as Saks Fifth Avenue or Bloomingdales can be associated with the upper class whereas mass merchandisers or discounter such as Kmart or Walmart may be considered as blue collar (Aaker 1997). Building brand personality is important in marketing because brand personality can be equated to the public identification of the brand which can lead to strong brand loyalty by consumers (Marconi 2000). According to Khan (2010), brand personality is a well-recognized contemporary marketing tool because the concept of personality reflects the importance of relationships in society. Belongingness, love, and esteem are basic consumer needs central to personal relationships (Khan 2010). Companies use creative ways to communicate brand personalities as a means to influence consumers’ evaluation of the product or brand bringing personal relevance to the consumer. As a communication tool, advertisements carry an important role in imbuing brands with personality traits. As such, the use of brand personality in product advertising allows marketers to create market differentiation, build consumer attachment to brands (Biel 1993), and foster brand loyalty (Fournier 1998). An interesting aspect of brand personality is that there is a more dynamic and fluid aspect of its image compared to the relative stability of human personalities. This is a key distinction for the fashion industry, since for most fashion brands, success is determined by whether the brand can change with the customer and create fresh product offerings, often resulting in changes in impressions. As even “classic” brands need to change their strategic direction and modernize their image, brands cycle through different personas through the years. Consumers have to renegotiate their associative perceptions of a brand, based on past product experience, in con- cert with any new marketing or advertising direction being undertaken. The symbolic interaction theory can be used to explain this process of negotiating meaning within the social context. Ligas and Cotte (1999) incorporates this theory through the identification of the three environments—marketing environment, individual environment, and social environment—that interact in the development of brand meanings (see Fig. 3.1). The three environment framework offers an explanation of how meanings in one environment influence the receptivity and negotiation of meanings in another environment with each environment having a potentially impactful role in the development of brand meaning. Ligas and Cotte’s (1999) three environment framework holistically brings together two dominant ways of understanding how brand meaning is understood by consumers. First, marketers are viewed as creators of symbolic meaning for a product or brand and contextualize it into a culturally constituted world (McCracken 1986). The brand acquires a stable meaning and consumers accept the meaning associated with the product or brand and develops preferences based on how the brand is compatible 32 H.-S. Kim and M. L. Hall

Fig. 3.1 Ligas and Cotte’s (1999) framework for brand negotiation (p. 611)

with their self-identity, personality, or values (e.g., Aaker 1997; Fournier 1998; Holt 1997; Kleine et al. 1993; Kleine et al. 1995). Second, consumers are considered to be more participatory in the brand building process by adapting the meanings based on personal situation and relevance, resulting in individual consumers possessing varied meanings associated with the brands. Consumers understand and develop preferences for the brand based on shared meaning that occurs within the context of the individual’s social situation and self (Holt 1997; Scott 1994; Thompson and Haytko 1997). Based on Ligas and Cotte’s (1999) framework for understanding how brand meaning is generated, this chapter examines how fashion brand personality can be created by marketers, but only accepted and adapted by consumers based on a combination of strategic creative advertising and consumers’ acceptance of brand meaning. The chapter is organized in the following way: first, the chapter presents an overview of symbolic interaction within the context of fashion consumption. Second, the chapter discusses how symbolic meanings have been instilled in products by marketers to create brand personalities in fashion brands. Third, how consumers choose brands based on brand personality and symbolic meanings incorporated in the brands are discussed. Fourth, based on symbolic interactionism, our discussion focuses on how consumers negotiate and change brand meaning (and brand personality). Throughout the section, propositions are presented that apply to fashion brands. Development of these propositions is supported by academic literature that has strongly influenced the advancement of knowledge in the related areas of brand personality and advertisement. A summary and directions for future research are offered. 3 Fashion Brand Personality and Advertisement Response 33

2 Symbolic Interaction, Fashion, and Brand Meanings

The symbolic interaction theory originates in sociology and is found on the understanding that people interact with one another based on shared meanings. These meanings take the form of physical objects that symbolize sociological, psychological, and cultural constructs. Clothing behavior has long been linked to expressions of self and interpretation based on shared meanings (e.g., Kaiser 1997). As Eicher and Roach-Higgins (1992) define dress as “an assemblage of body modifications and/or supplements displayed by a person in communicating with other human be- ings” (p. 5), fashion products and brands serve as a vehicle or tool for communication and shared meanings within the social environment. Fashion brands, as symbolic media of expression for consumers, can be used to explain the underlying principle of the symbolic interaction theory: that fashion and its brands are a mode of communication grounded in social context and informed meaning. Along with fulfilling the utilitarian and aesthetic needs of the individual wearer, fashion brands express the social psychology of the individual, and thus communicate individual identity, values, personality, and normative influence (Orth and Kahle 2008). Individuals express aspects of the self through brand decisions which is a part of how consumers manage their appearance. “Self-concept can be conceptualized as an organization (structure) of various identities and attributes, and their evaluations, developed out of the individual’s reflexive, social and symbolic activities” (Lee 1990, p. 389). In addition to communicating aspects of the self, individuals can manipulate brands (and styles) in creative ways to present the self. Fashion brands as inherent tools in appearance management and self-expression offer ways for consumers to communicate information salient to his/her identity, or to assert a constructed self. Although brand meanings may originate creatively from the marketer, a social process must exist where the meanings conveyed through consumer usage are socially constructed and mutually defined. According to Ligas and Cotte (1999), “The way in which the marketer constructs a brand and presents it to a specific consuming segment will be less effective if various perspectives exist for what the brand stands for or means” (p. 609). Within a fashion context, brand cues are not only used to express one’s identity and preferences but also to interpret characteristics and qualities about others. Social interaction can be stimulated by appearance perception laden with brand cues invested with brand symbolisms. But note that the visual communication intended by the individual can either be in alignment or conflict with the meaning communicated to the perceiver and thus a socially constructed meaning (also referred to as negotiated meaning) is required. In contemporary society, “what you wear” is not a simple communication tool between the wearer and the perceiver. In the form of fashion, dress is rife with culturally defined meanings. These meanings are partially informed by the marketing environment, subject to the capitalist motivations of consumer adoption. Marketers use advertising to engage consumers, both as individuals and as a social group. In this way, consumers are in an active relationship with brands to communicate 34 H.-S. Kim and M. L. Hall information salient to the individual identity. Advertising media can directly or indi- rectly impact the ascribed meaning of fashion styles. Thus, marketers can cause flux in the social environment as to the latent appearance cues of fashion. These changes are inherent to the fashion system; a system based on evolving aesthetics and ulti- mately evolving shared meanings. This cycle defines the ongoing reinterpretation of brand meanings and the multiple influences for informing negotiated meanings.

3 Building Fashion Brand Personality via Advertisements

An aged English country estate fades in with classical music followed by glamorous female models dressed in contemporary vintage inspired designs from the early 1900s. American designer Ralph Lauren speaks, “I create a world beyond fashion… I want to conjure a feeling of romance and vintage glamour…This is how fashion becomes timeless and tradition becomes forever.” The Ralph Lauren Corporation has signed on as a national sponsor of PBS’ Mas- terpieces series, which airs popular period dramas such as Downton Abbey and Up- stairs Downstairs. As reported in the PBS press release, David Lauren, Executive Vice President of Advertising, Marketing, and Corporate Communication (Ralph Lauren Corporation) says of designer Ralph Lauren, “He has always had a true appreciation for the heritage and romance of England and reflects this through his fall 2012 collection which is about modern glamour inspired by timeless character and refined elegance” (Ralph Lauren to Sponsor 2012). As a globally recognized American luxury brand and leader of lifestyle merchandising, Ralph Lauren draws consumers into the world of American aristocracy and sophistication. Over four decades, the Ralph Lauren brand has been built into a classically iconic brand with a distinct identity. Brand personality is one of the most challenging product attributes to foster, thus enabling brand differentiation in the marketplace and supporting brand loyalty (Ang and Lim 2006). Brand personality is developed through implementation of various marketing programs and activities such as the Ralph Lauren brand’s recent marketing program. Through an integrated communications program, companies are able to create a focused brand persona through advertising, promotions, and public relations and publicity. Advertisements carry an important role in imbuing brands with personality traits as advertising allows marketers to creatively deliver messages and position their products in a way that is appealing to certain market segments through marketing imagery, advertising copy, product mix, and product symbolism. It is considered an important source of brand-related information where consumers are more readily able to form new personality trait inferences or modify initial trait inferences (Hayes et al. 2008; Johar et al. 2005). Through advertisements, consumers are able to understand the brand meanings and symbols that define the brand personality and creatively relate the brand symbolism to particular social situations (Scott 1994; Shepard 1997). Hayes et al. (2008) notes that various brand associations for different kinds of products and brands vary in how 3 Fashion Brand Personality and Advertisement Response 35 they influence consumer perceptions. The following propositions reflect the role of advertisements in the introduction and formation of brand personality. Proposition 1 Fashion advertisements play an important role in presenting consumers with brand meanings and symbols that can be used to form impressions of brand personality. Hayes et al. (2008) explain consumers may make brand associations based on how brand meanings in “the culturally constituted world” (McCracken 1986, p. 313) are transferred to consumer goods. Advertisers will “identify cultural symbols that connote meanings they wish to associate with their brands and employ those symbols in their advertisements to create the desired linkage in the minds of consumers” (Hayes et al. 2008, p. 97). Symbolic products differ in brand personality meaning over utilitarian products, in part due to the affective versus cognitive needs fulfilled by consumption (Ang and Lim 2006). Cultural messaging using symbolic products is based on a shared code. In a study of Nike advertisements, Armstrong (1999) observed Nike’s ads to be positivistic cultural depictions which aligned with the self-concept and personalities of the intended target market. Positive consumer response within the African American community toward brand personality is reli- ant on precise and accurate cultural depictions. The second proposition reflects the importance of employing relevant cultural meanings that are shared by consumers. Proposition 2 Brand personality is most effectively communicated when advertisements communicate the salient cultural meanings associated with the product category (i.e., fashion) and brands. Many fashion brands have changed creative direction as a necessary means to reposition a mature brand in a competitive market. For example, in order to escape its traditional image as old-fashioned, Burberry transformed its product look, re- flected in the brand’s advertisements, to being contemporary, rebellious, and street- wise (Keller 2013). Target has successfully raised its image from a typical discount retailer such as Wal-Mart and K-Mart by offering exclusive designer apparel and merchandise through co-branding with well-known fashion designer brands such as Issac Mizrahi, Missoni, Fiorucci, Jason Wu, and Prabal Gurung to name a few. With change in style and marketing, fashion brands can take on personas that make its former image barely recognizable. As fashion’s innate nature is change, few fashion brands are able to enjoy long-term success without adjusting and reinvent- ing their personality over time. Consumers’ evolving tastes in fashion as well as the competitiveness of the industry require fashion brands to constantly differentiate themselves in a unique way. Thus, the following proposition was developed to reflect the moving dynamics of fashion brands. Proposition 3 Fashion brand personalities evolve and change over time. Fashion brands strategically make deliberate actions to change the brand meanings and symbols associated with their brand personality in advertisements. Consumers are able to imbue human personalities to brands from the symbolic representation of brands created by advertisers. Consumers are able to give a “human face” to brands or relate brands to their own selves (Fournier 1998). For 36 H.-S. Kim and M. L. Hall example, the application of anthropomorphization or animism is used to describe how consumers are readily inclined to prescribe human characteristics to nonhuman objects (Aaker 1997; Puzakova et al. 2009). Ang and Lim (2006) found the use of metaphors in ad copy and imagery to help facilitate brand personality messaging. In a comparison study of symbolic versus utilitarian products, Ang and Lim (2006) found symbolic products (cologne and designer watch) to be more sophisticated and exciting compared to utilitarian products (mineral water and toothpaste). Interest- ingly, however, in their study comparing the two product types (symbolic versus utilitarian), “the metaphors enhanced perceptions of sophistication and excitement, particularly for utilitarian (versus symbolic) products, and reduced perceptions of sincerity and competence for symbolic (versus utilitarian) products” (Ang and Lim 2006, p. 50). Based on the fashion products used in this particular study, metaphors add more value to utilitarian products but do not appear to enhance the positive personality traits of symbolic products. Other studies examining perceptions of brand personality and advertising within the context of fashion products offer insight into how brand symbolism influence consumer perceptions of brand personality within a specific product category. User imagery, which refers to the type of person who is portrayed as using the brand (Keller 2000), can be used to imbue brands with human personality traits. Consum- ers draw a strong connection between the personality of the user in advertisements and brand personality (Kressman et al. 2006). In particular, information about the brand’s demographic characteristics such as gender, age, social class, etc. can be directly inferred from user imagery (Aaker 1997). Hayes et al. (2008) found in a study of student perceptions of sunglasses user imagery to be the most powerful in- fluencer of brand perceptions. User imagery is considered to be an easier way consumers can transfer personality traits from the user to the brand whereas other types of brand associations (e.g., manufacturer, product attribute) require consumers to make inferences about the brand personality’s traits. Also, user imagery associated with the brand allows consumers to easily identify how they can use the brand to communicate themselves to others. In fact, in fashion products where the function is less of an issue, user imagery may be the most effective advertising type to generate the desired personality (Hayes et al. 2008). The relationship between the visual appeal of the user presented in the advertisement and perceived brand personality is noted in Aagerup’s (2011) study of mass-market fashion brand for jeans and shirts. Aagerup (2011) found consumers’ perceptions of fashion brands, when measured by Aaker’s (1997) five-brand personality dimensions, to be more negative with an overweight model (compared to a thin or obese model). In a related way, using celebrities or attractive models within fashion advertisements can draw positive attention to the brands and help build brand personality (e.g., Rook 1985; Keel 2012). Proposition 4 User imagery which depicts prototypical users of brands is an effective way to imbue human personality traits in fashion brands. 3 Fashion Brand Personality and Advertisement Response 37

4 Fashion Brand Personality and the Consumer

For many years, the Gap suffered from a personality disorder and their identity problems as the namesake Gap brand have been widely covered in the business literature. The Gap had lost its edge as the leader in the fashion industry as the casual hip cool brand with great TV advertisements such as “Khakis Rock” featuring the music of Crystal Method. It fell short of offering a clear merchandise direction and was described as “a tired cliché” and “listless” (Walters 2007). In addition, although their advertisements have created buzz within the fashion media, it had less to do with showing the relevance of its styles to real consumers. Fast forward to 2012, the brand is receiving positive reviews and signs of “a turnaround” for their “Be Bright” global marketing platform highlighting their skinny jeans. Their TV ads with Indie singers and dancers, “lively” technology infused in their stores, and digital catalog (Styld.by) with noted fashion bloggers are targeting the millennial consumers (Zmuda 2012). The consumer can be viewed as a creative participant in the brand personality building process. This understanding parallels Ligas and Cotte’s (1999) discussion of how brand meanings can be developed based on an individual’s interpretation. Consumers can hold varying impressions of brand personalities for a particular brand depending on their own personal life situation (Holt 1997; Scott 1994; Thompson and Haytko 1997). The meanings depicted for the brands may be adapted or adjusted based on the consumer’s individual situation such as “personal goals, life history, context-specific interests, and a multitude of countervailing cultural meanings” (Thompson and Haytko 1997, p. 6). Individuals may consider certain aspects of a brand’s personality to be of personal relevance and create individualized impressions of brand personalities. Here, the individual environment in reference to the self is emphasized, although it is recognized that both the marketing environment and social environment influences a consumer’s self (Ligas and Cotte 1999). In addition, the way consumers are able to discern what aspects of brand personality they like will allow consumers to make choices based on their consumption motiva- tion. Proposition 5 Consumers can form varying impressions of brand personality from advertisements based on their own individual situation. The relationship between self-concept and brand image has been of interest in the marketing literature for many decades (e.g., Aaker 1999; Grubb and Grathwohl 1967; Hong and Zinkhan 1995; Kleine et al. 1993; Sirgy 1982). Self-concept is defined as the “totality of the individual’s thoughts and feelings having reference to him as an object” (Rosenberg 1979, p. 7). In this way, the individual contextual- izes his or her self within the social environment (Onkvisit and Shaw 1987). Within consumer behavior scholarship, the domain “self-concept” comprises four interrelated aspects: the actual self (the individual’s real perception of self), the social self (the individual’s self as perceived by others), the ideal self (the individual’s desired perception of self), and the ideal social self (the individuals’ desired self as perceived by others) (Sirgy 1982). Self-congruity is “the degree of similarity between 38 H.-S. Kim and M. L. Hall consumer’s self-image or self-concept and that of a brand” (Khan 2010, p. 9). When consumers’ perceive a match between their self-image and brand image, they are more likely to form favorable impressions of the brand and feel a higher level of satisfaction with their brand/product choices (Aaker 1999; Malär et al. 2011; Sirgy 1982; Johar and Sirgy 1991). Although it is noted that self-image and brand personality are not always in agreement in purchase situations, brand personality and consumers self-image are more likely to be stronger in consumption situations in which the product category is more involved in constructing the consumer’s self- image (Keller 2013). Fashion (or apparel) products are well-known vehicles of nonverbal communication for individuals about oneself (e.g., Kaiser 1997) and thus, identifying congruity relationships between a fashion brand’s image and consumer’s self-image is important for marketers to better position their brands with their target market (Khan 2010). In advertising and various communication efforts, it is important to project symbolic meanings associated with brand personality that corresponds to the specific personality traits of consumers including self-concept. In a study of 15 fashion and lifestyle brands, Khan (2010) found consumer personality to predict brand preferences. Also, Khan (2010) found the brand with the highest rating in all brand personality dimensions had high aspirational appeal as depicted in the brand and advertisement. This supports self-congruence as being the main strategy behind transformational advertising, compared to informational advertising where the functional utilities of a product are emphasized (Rossiter and Percey 1987). Proposition 6 Due to the role of fashion products in communicating the consumers’ image, it is important in advertising to communicate the symbolic meanings of brand personality that corresponds to consumers’ own personality to garner consumer support for the brand.

5 Interpretation and Negotiation of Brand Personality

Megan is a graduate student attending a fashion program in the northeast region of the USA. She shares her story of the Coach brand: “I have always thought of Coach products to signal financial success and fashionability. Advertising had featured prototypical users and celebrity endorsers which aligned with my sense of ideal self. Recently, I purchased my first Coach bag, thinking I had something special. However, during a class discussion, a fellow graduate student said that Coach bags reminded her of an older target market with conservative tastes. That comment made me re-think my image of Coach bags.” ( December 15, 2012, personal communication) For the most part, in fashion products, brand ownership and brand usage occurs in a very visual and public way. Consumers use the visibility of fashion products to communicate symbolically something about themselves to others, but consumers also receive feedback about their impressions and ideas from others. According to 3 Fashion Brand Personality and Advertisement Response 39

Lee (1990), “product conspicuousness can be conceptualized in light of interpersonal relationships in social process and also links the product to the concept of self” (p. 387). As such, social influence is an important aspect of building brand image where shared understanding of symbolic meanings and experiences develop. A traditional view of advertising is the promotion of brand personality based on a marketer driven image that is holistically accepted by the consumer. Ligas and Cotte (1999) state consumers are inundated with both visual and verbal communication campaigns that appeal to this notion of the brand as a meaningful entity. In this way, marketing plays a major role in the creation of brand meaning, because advertisements and promotions tend to inject certain beliefs about the brand into the marketplace. However, a brand’s meaning is considered to be effective when it is “capable of provoking personally relevant components within the individual” (Ligas and Cotte 1999, p. 609). In a content analysis of Nike advertisements, Arm- strong (1999) found the advertisements to be presented in a way which allowed for “optimal communication with Black consumers” (p. 283). The Nike advertisement is able to tap into the self-concept of African American consumers by using symbols and images that the consumer base can relate to which in turn can reinforce positive attitudes about the brand. Hence, advertisements must be able to connect the consumers and brand through communication with symbolically shared meanings. Negotiated meaning originating from the individual environment includes the adoption or creative adaption and manipulation of shared brand meanings through appearance management. In this way, appearance management includes holistic adoption of a single brand identity or the use of visual bricolage. By choosing to wear a particular brand, individuals are using the brand identity to communicate personal identity. Consumers are adopting the brand personality, and using the marketing instilled meaning to communicate personal identity, essentially becoming a communication tool for the marketing environment and thus transferring the marketing prescribed meaning to the social environment. Alternatively, individuals can manipulate dress and the marketing prescribed meaning of brands via visual bricolage. Visual bricolage of dress is the mixing of aesthetic elements to assert a unique personal style. The mix can include various products and brands each laden with symbolic meaning. The subsequent juxtaposition of brand personalities, via the combination of worn dress, illustrates distinctive personal and cultural expression. Fashion advertising can inform individuals as to both the intended brand meaning originating in the marketing environment as well as stimulate creative interpretation. As noted by Kaiser (1997), fashion designers and advertisers can purpose- fully “step out of the existing ideological framework” (p. 51) and co-create new cultural codes for clothing and appearance-related objects. As advertising imagery illustrates brand personality, this information can facilitate the brand’s adoption or adaption as a tool for personal self-expression. Proposition 7 In terms of fashion products, consumers are able to creatively adapt various brands (and associated personalities) in a symbolic way to create and communicate their own personal identities and new social interpretations. 40 H.-S. Kim and M. L. Hall

In the social environment, appearance perception is meditated by the symbolism of brands. As a shared medium, fashion advertising enables socially constructed meanings in fashion. Moreover, the negotiated meaning of fashion is further subject to the multiple individuals comprising the social environment, as weall as the social context and reference group of said context. Advertising can have a multitude of meanings governing appearance perception in the social environment, and is dependent on each individual perceiver. In addition, the wearer’s reference group further influences shared meaning, as the individual is motivated to align with the referent group meaning and conform. From this point of view, consumers can choose to adopt, adapt or reject brand personalities interpreted through fashion advertising based on the anticipated social response. The symbolic interactionist perspective can in this way predict or explain purchase decisions (Lee 1990). An interaction of all components of the self (actual, ideal, social, and ideal social) can be evidenced in the social environment. The individual adopts dress (fashion) based on congruence with the actual and/or ideal self. When in the social environment, the identities of the social self and ideal social self are added. These identities thus combine to inform the negotiated meaning of fashion. However, the individual only has control over the actual, ideal, and ideal social. In the social environment, the individual may assert brand congruence with the ideal social self to confirm or deny reference group membership. Hence, from the symbolic interactionist perspective, brands will be chosen based on the ability to reflect the desired aspect of self. Proposition 8 Social influence is important in consumers’ acceptance of brand personality of fashion products. Finally, we note the ambiguous relationship that can form between brand personality and consumer behavior, especially in cases where brands are advertised with extreme messaging and provocative visuals. As marketers use advertisements to bring brand personality to consumers, consumers add their own personal interpretation to how they view the brand generating possible variations in how a particular brand is perceived. For example, Malär et al. (2012) found the singularity of the brand’s personality profile and consumer’s prior brand attitude, among other things, influenced the match between consumers’ realized brand personality and intended brand personality. As such, perceived brand personality and user imagery may not always agree (Keller 2013, p. 305). Further, brand personality and user imagery may not necessarily correspond to consumer attitude toward the brand or purchase intentions. For example, in the fashion industry, it is not uncommon to see advertisements with provocative or sexually suggestive visual and verbal communication. One can assume that such strategies would work toward developing brand meanings contributing to a certain image as part of brand personality. Schol- ars report conflicting evidence of the effectiveness of such brand building strategies. In a study of provocative fashion advertising, Vézina and Paul (1997) note provocation is a strategy to attract attention but does not necessarily lead to negative consequences in terms of brand attitude or purchase intentions. On the other hand, in a study of American Apparel advertisements, Hyllegard et al. (2009) found 3 Fashion Brand Personality and Advertisement Response 41 sexual intensity in apparel advertisements to negatively influence brand attitude and purchase intentions. They also note that US consumers are more likely to be independent in their feelings and less likely to be influenced by others when evaluating such advertisements. In addition, in our own observations, we find that some female college students are able to separate their positive experiences with American Ap- parel products while acknowledging the offensive nature of the brand’s advertising past and personae. Although the social environment offers a place for individuals to negotiate meanings associated with visual and verbal symbols from advertisements, we see that consumers’ feelings about a particular brand’s personality may not fully explain brand attitude or purchase intentions in an intuitive way. Also, the social environment does not necessarily serve as compass for guiding consumer attitude and behavior. Proposition 9 The relationship of consumers’ evaluation of advertisements, brand personality, and consumer behavior (brand attitude and purchase intentions) can be conflicting.

6 Summary and Conclusion

A strong recognizable brand personality is critical to establishing brand equity as personality traits offer assets that consumers value. Both Biel (1993) and An and Lim (2006) note brand personality is unlike singular product attributes and can be less constrained by the product’s physical attributes. Thus, brand personality can be personally more meaningful to consumers, difficult to imitate, and holds a “sus- tainable advantage” over its competitors (An and Lim 2006; Biel 1993). Effective communication of brand personality in product advertising allows marketers to grab consumers’ attention, create market differentiation, build consumer affective attachment to brands, and foster brand loyalty. Advertisements have a strong role in building brands due to its ability to con- vey brand meanings with symbolic value, creative leverage, or realistic appeal. As brand personality allows consumers to form relationships and bond with brands similar to that would occur in human relationships, advertisements not only offer the first impression, but can also help sustain and reinforce the relationship between the brand and consumer. We find that not all aspects of a brand’s personality are stable and continuous through time, but somewhat similar to humans, brands evolve through time in a more dynamic way. However, the pace of change in brand personality may be more deliberate and swift with the goal of appealing to their target market base (i.e., human friends). Advertisements offer colorful and effective ways of strategically instilling new meanings in brands and a “fresh” look. Consumers are constantly interpreting brand meanings as depicted in advertising. These interpretations may be commonly understood within society or be subject to interpretation holding subjective appeal to individuals. 42 H.-S. Kim and M. L. Hall

The social environment validates the brand personality as communicated by advertising and understood by the individual. It is acknowledged that the shared meaning that is derived from negotiation among the marketer, individual, and society can be seen as the brand’s “social self”. However, we do see “brand events” such as unique marketing programs implemented by the marketer, consumers’ personal experiences with brands that are embraced as “defining moments” for individuals, or changes in a relevant reference group’s attitudes on a brand due to negative media coverage may all influence perceptions of brand personality. The symbolic interaction perspective on how impressions of brand personality are formed is based on a process that involves negotiated and commonly shared meanings among the marketer, consumer, and social groups. The propositions presented outline this process relative to fashion brands, highlighting the importance of self-brand congruity with brand personality as it is transmitted from the marketing environment to the individual/social environments. A strong brand personality allows consumers to use brands to effectively communicate with others and consumers are able to form unique relationships with the brand (Ligas and Cotte 1999). Advertisements have a persuasive role in the negotiating process. Advertisements can reinforce the glamorous and sophisticated personae of brands appealing to the current status quo of classical loyalists or introduce a “brand makeover” in order to develop new social ties with consumers. On the other hand, brands can confuse consumers about who they are. As such, negotiation of brand meaning leading to defining “who the brand is” can be a continuous process for consumers where they can stay loyal, abandon, or develop new relationships depending on how they relate to the brand’s personality. The propositions presented in this chapter offer ideas for future empirical studies. Future studies may address the dynamic nature of brand personality of fashion brands. As a fundamental trait of fashion concerns the continuous cycle of refresh- ing brand image, studies may address how fashion brand personalities evolve and the role of advertisements as well as other marketing programs in defining, refining, and recreating the images of fashion brands. In relation, also of interest would be how companies engage in brand personality building that resonate to consumers and how various brand strategies may be prompted based on market conditions and consumer environments. A deeper analysis on how branding strategies affect consumer welfare can also be explored. Finally, social and individual environments are influential in how consumers interpret brand meaning and perceive brand image. As noted in the study by Malär et al. (2012), consumers do not perceive the brand’s personality in the same way as it is intended by managers. Future research may tackle this “gap” in brand perception and identify various factors that moderate or support brand personality building and management strategies. 3 Fashion Brand Personality and Advertisement Response 43

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Y. Fujita

1 Introduction

In the fashion and apparel industry, which is characterized by demand fluctuation,1 increasing number of clothing retailers offer a greater number of products in smaller lines, continuously changing the products in their storefronts. A relevant example is Zara, a Spanish clothing retailer, which achieves 15 days magic. That is, it takes only 15 days for Zara to carry out the entire process, from conceptual design to well-produced and packaged products in the retail stores. Ac- cording to Ferdows et al. (2004), Zara has also hit on a formula for supply chain success by dividing each year into 20 seasons, each featuring five to six colors with five to seven sizes. This retailing model, which is called fast fashion, is also adopted by Sweden-based H&M, Japan-based World Co., and Spain-based Mango (see Passariello 2008; Rohwedder and Johnson 2008). Key features of fast fashion lie in product development and supply chain design which rely more heavily on lo- calized cutting, dyeing, and/or sewing than on outsourcing to developing countries (see Caro and Gallien 2010). According to Cachon and Swinney (2011), two features distinguish fast fashion: (1) short lead time in production and distribution, (2) highly fashionable product design. For short lead times, they enable close matching of supply with fluctuating demand. Short lead times are made possible by frequent inventory monitoring and efficient distribution methods. Highly fashionable product design, on the other hand, is enabled by careful monitoring of consumers’ tastes for ever-changing trends. Demand fluctuation gives rise to numerous problems concerning forecasting, production planning, inventory management, production system management, and

1 As Harrison et al. (1999); Christopher (2000); Christopher and Towill (2001), and Christopher et al. (2004) mention, customers’ tastes are rarely stable and demands for products fluctuate over time.

Y. Fujita () Department of Economics, Keio University, 2-15-45 Mita Minato-ku, Tokyo, Japan e-mail: [email protected] T.-M. Choi (ed.), Fashion Branding and Consumer Behaviors, 49 International Series on Consumer Science, DOI 10.1007/978-1-4939-0277-4_4, © Springer Science+Business Media New York 2014 50 Y. Fujita timely distribution. Therefore, information systems such as Quick Response (QR) systems, Electronic Data Interchange (EDI), Point of Sale (POS) systems, and Man- agement Information Systems (MIS) have been implemented to monitor demand fluctuation. Although these techniques have been applied to forecast consumers’ wants for products, it is difficult for clothing retailers to organize and analyze the collected data, that is, to integrate data with theory and make quantitative decisions. Consequently, forecasting demand for fashion products still relies heavily on clothing retailers’ intuition. The present study attempts to lay out a stochastic dynamic model to investigate how a clothing retailer should introduce and withdraw the products. More precisely, we formulate market fluctuation as a stochastic process and attempt to make clear how to manage the number of “seasons” in a fluctuating market. In academic research, it is of growing interest to investigate how firms should overcome the fluctuation of markets with pioneering works such as Eisenhardt (1989); Williams (1994); Fines (1998), and Choi and Cheng (2010). Eisenhardt (1989) demonstrated that firms must embed flexibility in strategic actions in order to survive in fast- changing markets. Williams (1994) and Fines (1998) further revealed that firms’ strategies in fast-changing markets must be characterized by rapid product changes. Choi and Cheng (2010) focused on QR and made clear the latest applications of QR in business, as well as how to improve the effectiveness of QR using innovative methods. The purpose of the present chapter is to push forward these analyses. The theory we will utilize is optimal stopping theory, which emphasizes the importance of flexibility and has been used to develop strategies in various stochastically fluctuating markets. McDonald and Siegel (1986) demonstrate that firms should “wait and see” until uncertainty is resolved. Dixit (1989) examines the strategies of a firm that intends to enter a foreign market. Farzin et al. (1988) investigate the timing of IT investment. Bentolila and Bertola (1990) consider the management of employment and lay-off. Leahy (1993); Caballero and Pindyck (1996), and Baldursson and Karatzas (1997) analyze the effect of stochastic fluctuations on the economy. Although the above articles successfully developed optimal stochastic strategies, their focus was on the one shot move of a single firm and no interaction with competitors.2 The present chapter, which develops stochastic sequential product switching, is an extension of this. The most relevant analysis is Fujita (2007c, 2008b). Fujita (2007c) constructed a stochastic dynamic model and developed optimal strategies for a fashion retailer who is a “market leader” (in the sense that the other retailers intend to imitate her/his products). Fujita (2008b) extends Fujita (2007c) by emphasizing the difference between product vulnerability and market uncertainty. The present study expands the scope of Fujita (2008b) by introducing “obsolesce proofness” and examines whether a clothing retailer should increase the variety of items with short life cycles or stick to items with long life cycles.

2 Fujita (2007a, b, 2008a) extended these analyses by incorporating firms’ sequential decision makings that interact with other firms in the market. 4 Optimizing Fashion Branding Strategies 51

The structure of this chapter is as follows. Section 2 lays out the basic model and Sect. 3 describes the objective function of clothing retailers in a stochastic market. Based on these definitions, Sect. 4 determines the optimal stochastic product switching strategy of the clothing retailer. Section 5 examines the properties of the optimal strategy, that is, how parameters affect optimal values. Concluding remarks are made in Sect. 6.

2 Basic Analytical Model

As Christopher et al. (2004) revealed, the clothing market exhibits the following characteristics: 1. Short life cycles: The product is often ephemeral. Demands are often influenced by the mood of the moment. Consequently, the period in which the product is saleable is very short and seasonal, measured in months or even weeks. 2. High volatility: Demands are likely to be affected by the vagaries of weather, films, or even pop stars and athletes. As a result, demands for products are rarely stable. 3. Low predictability: Because of the volatility of demands, it is difficult to forecast even total demand within a period, let alone week-by-week or item-by-item demand. 4. High impulse purchasing: Consumers’ decisions are often made at the point of purchase. That is, it is often the case that the consumers are stimulated to buy products when confronted with them. Paying attention to the above four characteristics, we assume that the clothing retailer in the present chapter exists in a stochastically fluctuating market and periodi- cally introduces new items and exits old items. More precisely, the clothing retailer in this model determines the timing of product in and out, as well as the degree of “obsolesce proofness” of old items. Throughout this chapter, we define the degree of obsolesce proofness as high if one item keeps selling well after introducing the next item. We will introduce its mathematical definition later in this section.

Without loss of generality, we let Ti denote the interval between the introduction of the ( i − 1)th item and the ith item, and let ti denote the interval between introduction of the ( i + 1)th item and exit of the ith item. That is, the clothing retailer i i+1 introduces the ith item at period ∑ Tk and continues selling until period ∑+Ttki. k=1 k=1 We define the ith item as new until the ( i + 1)th item is introduced and as old after the ( i + 1)th item is introduced. That is, the ith item is new during the interval of i i+1  i+1 i+1    ∑∑TT, + t ∑∑TTk , k and old during the interval of  k ki. For the conveniences k==11k  k =1 k =1  of exposition, concerning the ith item, we call it as the ith new item while it is new and as the ith old item while it is old. 52 Y. Fujita

Considering the above four characteristics and letting Ri ( t) denote the ith new item’s revenue at t, we assume that Ri ( t) follows the geometric Brownian motion of Eq. (4.1).

dRi=−µσ R i dt + R ii dZ − R dq, (4.1) where μ, σ, dZ, and dq are mean, variance, Wiener process, and Poisson process, respectively. Throughout this chapter, we interpret μ and σ as competitive advantage and market uncertainty. More specifically, larger μ means that the competitive advantage decreases more quickly and larger σ means that the market as a whole is more uncertain. Wiener process is the random movement which is among the simplest continuous-time stochastic processes, and has several real-world applications. Often quot- ed examples are stock market fluctuations, exchange rate fluctuations, and so on. It is often mathematical convenience rather than the accuracy of the models that motivates their use. Recently, Wiener process has been used to formulate firms’ revenues (see Dixit and Pindyck 1994 for example).

We also assume other clothing retailers are in the market and that Ri( t) falls by a fixed percentage η (with 0 < η < 1) if other clothing retailers succeed in developing new items. We interpret η as degree of resistance to imitation. More specifically, larger η means that the item is more vulnerable to other clothing retailers’ introduction of new items. In the following, we let λ (with 0 < λ < 1) denote the probability of other clothing retailers’ success in developing new items. Since the model in the present chapter is stochastic, optimal timing is expressed by cut-off values of revenues, not by the exact time points. To be precise, we assume that the clothing retailer introduces the ( i + 1)th item if the profit from the ith item decreases to Ri* and continues selling the ith item until its profit decreases to ri*. Relationships between the items are assumed as follows. First of all, as for the relationship between new items, impact of introducing new item is larger if the profit of current product remains higher. To express mathematically, at the moment of introduction of the ( i + 1)th item, the initial profit of the ( i + 1)th item becomes gRi*, where g is a positive constant that is greater than 1. Secondly, as for the relationship between new item and old item, we assume that profit of the ith item drops down to θiRi* and then fluctuates according to (4.1). We assume θi satisfies 0 < θi < 1 and interpret θi as the degree of obsolesce proofness at the moment of introducing the next item. In the present chapter, extending Fujita (2008b), we assume that the clothing retailer is able to control θi with cost, that is, more cost is required to produce items that is harder to obsolete. This cost includes every cost that is necessary to prevent the item from obsolescing when introducing the ( i + 1)th item, such as costs to keep the brand value and popularity of the ith item. In the following, we define this cost as life-extension cost and letting γ be a positive constant, we specify the life- extension cost as γ . 1 −θi 4 Optimizing Fashion Branding Strategies 53

Fig. 4.1 Time series of profits

The other cost we explicitly formulate is introduction cost, which is necessary when introducing new items. As for this cost, we assume that the quicker introduction of new items requires more cost and specify the introduction cost for the ith item as cR *ε, where c is a positive constant and ε is a constant that is larger than 1. i i

We assume that the clothing retailer incurs this cost at ∑ Tk . k =1 Time series of the profit is depicted in Fig. 4.1.

Summing up the discounted values of Ri( t) and ri( t) over time minus the sum of the discounted values of costs for life-extension and introduction establishes the net present value, as we will see in the next section. Importance of the future diminishes with time, which we capture by the discount rate ρ.

In what follows, we derive the optimal values of Ri*, ri*, and θi, assuming the clothing retailer’s objective is maximization of the net present value.

3 Description of the Objective Function

This section describes the net present value, that is, the objective function of the clothing retailer. Since the market we consider is stochastic, the situation is more complicated than for a deterministic one, and the solution is derived following the standard procedure for the optimal stopping problem (e.g., Dixit and Pindyck 1994). To begin with, as a prerequisite, let us calculate the expected value of one unit i+1 i of the profit of the ith item at ∑ Tk, evaluated at ∑ Tk. This is the expected value of i+1 k =1 k =1 i −∑ρ Tk k=1 e evaluated at ∑ Tk. k=1

Let G( gRi*) denote this value. Then, the general solution to G( gRi*) is expressed as

αα12 G()()() gRii*=+ A gR * B gR i *, (4.2) 54 Y. Fujita

Fig. 4.2 Determination of α

1 x where α > 0 and α < 0 are solutions to σ2 xx()()()−−1 µ x − ρλ + + λ1 − η = 0, 1 2 2 which can be determined graphically as follows. If we define F( x) and f( x) as

1 Fx() =σµ2 xx() −−1 x 2 and

x fx()()()=+−ρλ λ1, − η then both intersect at two points, and hence, α1 and α2 are determined as in Fig. 4.2.

Since G() gRi * satisfies G()∞=0 and GR(*i ) = 1, it follows that A = 0 and α α 1 2 gR * 2 G gR * i−1 B = . Substituting these equations into (4.2) yields ()i = . R1 * Ri *

Letting α denote −α2, we obtain

α R * G gR *.i (4.3) ()i =  gRi−1 *

Next, by making use of (3), we will describe the sum of the discounted values of the instantaneous profits from the ith item. First, let us describe the sum of the discounted values of instantaneous profits from the ith new item, which is obtained by integrating Ri( t) over the relevant time i interval. For the convenience of analysis, let NTik∑ denote this sum evaluated at k=1

Ni+1 i i i ( ) i   −ρt ∑ Tk. That is, NTik∑ is defined as Nik∑≡ T e R() t dt, where Ni()≡∑ Tk k=1 k=1 k=1 ∫ k=1 Ni( ) i+1 and Ni(+ 1) ≡∑ Tk. By making use of (3), we have k=1 4 Optimizing Fashion Branding Strategies 55

α i  1 Ri * (4.4) Nik∑= T gRi−1 * − Ri*. k=1 µρ+ gR i−1

Similarly, let us describe the sum of the discounted values of instantaneous profits from the ith old item, which is obtained by integrating Ri( t) over the relevant time i+1 interval. For the convenience of analysis, let OTik∑ denote this sum evaluated at k=1 Oi+1 i+1 i+1 i+1 ( ) i+1   −ρt ∑ Tk. That is, OTik∑ is defined as Oik∑≡ T e R() t dt, where Oi()≡∑ Tk k=1 k=1 k=1 ∫ k=1 Oi( ) i+1 and Oi(+ 1) ≡∑ Tki + t. By making use of (3), we have k=1

α i+1  1 ri * OTik∑=θ1 Ri** − ri (4.5) k=1 µρ+  θR * ii

i As for the introduction cost of the ith new item, evaluated at ∑ Tk yields cRi* and k=1 i+1 T γ the ith life-extension cost evaluated at ∑ k yields 1 −θ . k=1 i For the sake of simplicity in analysis, let us assume symmetric solutions, that is,

R1*= R 2 * == Rr *,12 * = r * == r *, and θθ12=== θ. Hence, the net present value, VR()*, r *,θ , is described as

α 1Rr *ε 11 * γ V() R*, r *,θθ=gR** −− cR +R ** −r − ggαα  R*1 µρ+ µρ +− θ θ

α 11Rr *ε  11 * γ +gR** −− cR  +θR **−r  − gα gg αα2  R*1 µρ+ µρ +− θ θ

gRα 1* gR** cR ε += αα− − gg−+1µρ

α 11r * γ +θRr* −− *. gRα 1 *1 −+µρ θ −θ (4.6) 4 Determination of the Optimal Strategy

Now, we are ready to determine the clothing retailer’s optimal stochastic product switching strategy, that is, the optimal values of R*, r*, and θ. In order to determine the optimal values of R*, r*, and θ, let us differentiate V ( R*, r*, θ) with respect to R*, r*, and θ. 56 Y. Fujita

Fig. 4.3 Determination of R*B and θB

∂V First of all, since ∂r* < 0 , we get r* = 0, which means that the clothing retailer should keep selling the old item till its instantaneous profit decreases to zero. Sub- stituting r* = 0 into (6) and differentiating V( R*, θ) with respect to R* and θ yields the two first order conditions R* and θ must satisfy as,

θ=+ gαε( ρε cR *−1 –) g 1 (4.7)

1 γρ 2 θ =−1 (4.8) R*

In order to assure 0 < θ < 1, we assume

1 −<1gαε (ρε cR*− – g )< 0. (4.9)

Now, the optimal values of R* and θ, R*B, and θB, are determined graphically at the point E, the intersection of F1( θ) and F2( θ), which correspond to (7) and (8), respectively (Fig. 4.3). From the above, we can summarize the clothing retailer’s optimal stochastic product switching strategy, the optimal stopping rule, as follows. The clothing retailer should introduce the ( i + 1)th item when the instantaneous profit from the ith new item decreases to R*B and keep selling the ith old item till the instantaneous profit from the ith old item decreases to zero. As for the degree of obsolesce proofness at the moment of introducing the next item, the clothing retailer should set it at θB. With this, the model closes. 4 Optimizing Fashion Branding Strategies 57

Fig. 4.4 Effect of an increase in η

5 The Optimal Strategies and Consumer Welfare

Based on the above analysis, here we examine the effects of increases in η and σ on R*B and θB. Effects of an increase in η are shown graphically as follows. First of all, an increase in η increases α (see Lemma (1) in the Appendix for the proof). From (9), on the other hand, we see ρε cR*–ε−1 g< 0. Thus, in response to an increase in η,

αF1( θ) shifts downward, while F2( θ) remains unchanged as in Fig. 4.4. Therefore, B B B B ∂R*B ∂θ B R* and θ increase to R* ′ and θ ′. That is, ∂η > 0 and ∂η > 0. (These relationships are derived also by totally differentiating (7) and (8) and rearranging the terms.) Since larger η means that the clothing retailer is more vulnerable to other clothing retailers’ introductions of new items, we have: Property 1 If a clothing retailer is vulnerable to other clothing retailers’ introductions of new items, the clothing retailer should (1) introduce new items while the profits are high and (2) slow down the obsolescence of old items. In other words, the consumer welfare is benefited by the introduction of new items under the case when the profits are high as the clothing retailer will offer more new products. In the setting of this chapter, the introduction of a new item while the item is generating high profits means frequent introduction. Moreover, the frequent introduction of new items together with low speed of the obsolescence of old items is equivalent to a wide variety of the items. Thus, Property 1 implies that the clothing retailer should increase the variety of the items of short life cycles if a clothing retailer is vulnerable to other clothing retailers’ success in the development of new items. Similarly, effects of an increase in σ are shown graphically as follows. In response to an increase in σ, α decreases (see Lemma (2) in the Appendix for the proof), so that, F1( θ) shifts upward and F2( θ) remains unchanged as in Fig. 4.5. 58 Y. Fujita

Fig. 4.5 Effect of an increase in σ

B B B B ∂R*B ∂θ B Therefore, R* and θ decrease to R* ′ and θ ′. That is, ∂η > 0 and ∂η 0 >. (These relationships are derived also by totally differentiating (7) and (8) and rearranging the terms.) Larger σ in this model means that the market as a whole is more uncertain. Thus, Property 2 If a consumer market as a whole is uncertain, the clothing retailer (1) should wait to introduce the new items and (2) does not have to slow down the obsolescence of old items. These may hurt the consumer welfare as fashion consumers treasure more trendy clothing. Property 2 means that if a consumer market as a whole is uncertain, the clothing retailer should introduce new items less frequently and decrease the item variety, that is, the clothing retailer should stick to items with longer life cycles. Numerical Examples Some numerical examples will help to illustrate the results and show how the optimal stochastic product switching strategy depends on parameters. 7 8 8 For this purpose, first of all, let us assume that ρ = 8 , λ = 0.75, c = 7 , γ = 7 , ε = 1.5, and g = 2. As a bench mark case (Case1), let us specify the variables as σ = 0.5 and η = 0. Then, we have α = 2 since α is the absolute value of the negative solution to xx()−−16= 0. Therefore, (7) and (8) reduce to

7 θ = R* – 3; (4.7′) 4

1 1 2 θ =−1 (4.8′) R* 4 Optimizing Fashion Branding Strategies 59

Table 4.1 Dependence of α, R*, and θB on σ and η σ η α R*B θB Case1 0.5 0 2 1.425 0.162 Case2 0.5 1 3 1.607 0.211 Case3 1 1 2 1.425 0.162 2

Solving these equations with respect to R* and θ, we have R* = 1.425 and θ = 0.162. Similarly, we can calculate R*B and θB for ( σ,η) = (0.5,1) and 1 ,1 as Table 4.1 ()2 shows. By combining Case 1 with Case 2, we see that R*B and θB increase in accordance with an increase in η, which confirms Property 1. Similarly, by comparing Case 2 and Case 3, we find that an increase in σ decreases R*B and θB, which corresponds to Property 2.

6 Concluding Remarks

In the present chapter, by utilizing optimal stopping theory, we outlined a stochastic dynamic model and derived the optimal stochastic product switching strategy for clothing retailers. The analysis revealed that clothing retailers should increase the variety of items with short life cycles if (1) the clothing retailer is vulnerable to other clothing retailers’ introductions of new items or (2) the market as a whole is certain. Since these results identify the effect of each factor, they are of use when clothing retailers consider the difference between product vulnerability and market uncertainty. In the present chapter, for the sake of simplicity, we assumed away inventory costs. That is, we assumed that the clothing retailer can purchase items from wholesalers when necessary. Thus, it is necessary to reformulate the model to incorporate inventory costs. It is also of interest to examine the robustness of our results in a more general setting. We will undertake such analysis in future research.

Appendix

Effects of increases in η and σ on α are shown as follows. If η increases, as Fig. A.1 shows, F does not shift while f shifts upward, and hence α2 decreases to α2′, which is equivalent to say that α increases. If σ increases, F does not shift while f shifts as Fig. A.2 shows, and hence α2 increases to α2′, which is equivalent to say that α decreases. As a result, the next lemma follows. 60 Y. Fujita

Fig. A.1 Effect of increase in η

Fig. A.2 Effect of increase in σ

Lemma: (1) If η increases, α increases. (2) If σ increases, α decreases.

References

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Tsan-Ming Choi and Yong Yu

1 Introduction

The fashion industry is one of the fastest-moving industries. It is highly competitive due to its features such as short product life cycle, low predictability of demand (Bruce and Daly 2011; Ni and Fan 2011; Yu et al. 2011a), and high impulse purchase rate (Christopher and Peck 1990). In order to capture market share and increase brand equity, brand extension is a well-established strategy in the fashion industry (Hergeth 2004; Liao et al. 2008; Sullivan 1992). There are two kinds of brand extensions, namely category extension and line extension. Here, category extension refers to the case when the mother brand launches new product categories as extensions; line extension occurs when the mother brand introduces new product lines (within the same category) as extensions with different attributes such as color. Both types of brand extensions are in principle beneficial to the consumers because they will enjoy the availability of a larger variety of products under the respective brand. While fashion brand extensions in different domains are common strategies for business growth, there are very few prior scientific studies which explore the number of category and line extensions in different regions over different periods of time. An exception appears in the recent literature in which a cross-region cross- cluster analysis is conducted on fashion brand extensions by employing a statistical approach (Choi et al. 2011b). However, in Choi et al. (2011b), many important hypotheses are not found to be statistically significant by standard methods such as ANOVA, and many more sophisticated statistical analysis tools, such as Poisson

This research is partially supported by the funding provided by the Hong Kong Polytechnic University.

T.-M. Choi () · Y. Yu Business Division, Institute of Textiles and Clothing, Faculty of Applied Science and Textiles The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong e-mail: [email protected] T.-M. Choi (ed.), Fashion Branding and Consumer Behaviors, 63 International Series on Consumer Science, DOI 10.1007/978-1-4939-0277-4_5, © Springer Science+Business Media New York 2014 64 T.-M. Choi and Y. Yu regression, failed to help (because of the special features of the dataset). Motivated by the importance of the topic as well as the failure of the standard statistical tools in conducting analysis, this chapter scientifically studies how different fashion retail brands adopt category and line extensions in different regions over different periods of time by using artificial neural network (ANN). As such, this chapter can be taken as an extension of Choi et al. (2011b). In studying marketing and branding problems for fashion companies, the traditional methods include mathematical modeling (Chiu et al. 2009; Choi et al. 2011a), empirical statistical analysis, and cases (Jin 2004). However, many statistical methods would require various restrictive assumptions (e.g., on the specific distribution of the underlying process) which will limit their applicability. To overcome this limitation, there is an increasing research interest in exploring the use of artificial intelligence (AI) schemes (Yu et al. 2011b) to extract patterns and detect trends that traditional statistical methods are unable to identify. For instance, the use of neural networks in a cross-national study of brand image perception problem has been reported in Setiono et al. (2005). Not only the proposed neural networks approach can provide a better understanding of the consumer perceptions toward brand images across countries, it can also lead to higher prediction accuracy. In Fleming and Pashkevich (2007), a modified multiobjective genetic algorithm has been developed to find good solutions for a TV advertising campaign problem for multiple brands. Real data have been employed and the efficiency of the proposed algorithm is well verified. Moreover, in Liao and Wen (2009), the application of a data mining technique for extracting knowledge for new product marketing and development has been investigated with real data from a company in Taiwan. Based on the reviewed literature on using AI methods for marketing and branding problems above, we apply ANN to reveal scientifically the interesting fashion brand extension patterns using the same dataset as in Choi et al. (2011b). Our results suggest that ANN can provide a way for identifying patterns and trends in a scientific manner when the traditional statistical methods fail.

2 A Review: Data Description and Hypotheses

In Choi et al. (2011b), 48 samples of fashion brands were chosen from the Apparel Stores Company Index along with a few criteria listed below: (1) The brand’s history is provided on the brand’s webpage; (2) the brand extension strategy is provided on the brand’s webpage or an online fashion portal; and (3) the brands are from Asia, Europe, or North America (there are three regions in this analysis). See Table A.1 in the Appendix for the specific brands for these 48 samples. The publicly available data on brand extension strategies of these brands over a 90-year period were employed for the analysis. As we mentioned earlier, we explore in this chapter the same research problems and hypotheses as proposed in Choi et al. (2011b), but we use different methods (this chapter employs ANN while Choi et al. (2011b) employed standard statistical tools such as ANOVA) with a hope of generating new 5 An Analysis of Fashion Brand Extensions by Artificial Neural Networks 65

Table 5.1 Definition of Cluster 1 Mass basic clusters Cluster 2 Premium basic Cluster 3 Premium fashion Cluster 4 Mass fashion

Table 5.2 Definition of Period 1 1918–1932 periods Period 2 1933–1947 Period 3 1948–1962 Period 4 1963–1977 Period 5 1978–1992 Period 6 1993–2007

Table 5.3 Hypotheses H1 (interregion analysis) Fashion brands adopt different levels of category/line extensions over different time periods H2 (intraregion analysis) European and North American brands have more category/ line extensions in earlier time periods, while Asian brands have more category/line extensions in later periods H3 (intercluster analysis) Fashion brands in different clusters adopt different numbers of category/line extensions over different time periods H4 (intracluster analysis) Premium brands have more category/line extensions in the earlier periods, while mass brands have more category/line extensions in the later periods insights. We first review the basic research hypotheses and definitions of clusters and periods of Choi et al. (2011b) as follows (Tables 5.1–5.3).

3 Analysis by Artificial Neural Network (ANN)

The statistical results presented in Choi et al. (2011b) show a partial statistically significant support for the above hypotheses H1 through H4. However, owing to the very specific data features, statistical methods such as Poisson regression failed to get statistically significant results. In order to explore further about the line extension and category extension strategies adopted by different clusters of fashion brands in different regions over time, we employ ANN as a tool to analytically derive the 66 T.-M. Choi and Y. Yu

Table 5.4 ANN analysis Hidden neuron number MSE with different number of 2 2.00 hidden layer neurons in training 10 2.07 15 1.98 20 1.80 25 2.08 30 1.99 100 3.02 patterns and observable trends that the traditional statistical methods failed to identify. To be specific, ANN tests are conducted to explore the relationships between the dependent variable “number of extension (line and category, respectively)” and the independent variables of “region, period, and cluster.” For the ANN, we employ the typical feed-forward ANN with one hidden layer to analyze the number of line extensions over time. The number of hidden layer neurons of such an ANN can vary and different number of hidden layer neurons would affect the corresponding ANN’s learning and generalization capability. Since by the theory of neural network, finding an optimal structure can be difficult (Hecht-Nielsen 1989). In this chapter, for simplicity, we employ a simple method to determine the optimal number of hidden layer neurons. As a remark, notice that a larger number of hidden neurons in general would yield better learning capability of the ANN until the overfit phenomenon occurs (after which the learning capability becomes worse). Table 5.4 presents the experimental results by using ANN with different numbers of neurons. From Table 5.4, the ANN output’s quality in training is given by the mean- squared error (MSE), and its minimum is 1.80 which is achieved by having 20 hidden layer neurons in the ANN structure. We take the hidden neuron number with which the minimum MSE is obtained as the point where the overfitting occurs, consequently, we use a “20 hidden layer neurons ANN” structure to explore the numbers of line extensions for different clusters of brands in different regions over time. Figure 5.1 shows the actual number of line extension (top) compared to the ANN outputs (bottom). As we can observe, the ANN can somewhat capture the relationship, and this ANN with 20 nonlinear hidden layer neurons can be expressed by Eq. 5.1, where the estimated ANN weight parameters for modeling line extension are shown in Tables 5.5 and 5.6. A three-layer feed-forward back-propagation ANN model can be given as:

20   4   (5.1) yf=   ∑∑ xwij12,i  + bwjj + b2 j=1   i=1  

where wj,i denotes the weight of the connection from node i in the input layer to node j in the hidden layer, w2j denotes the weight of the connection from node j in the hidden layer to the single output node in the output layer, bj denotes the bias 5 An Analysis of Fashion Brand Extensions by Artificial Neural Networks 67

Fig. 5.1 The actual number 15 of line extension and ANN output of line extension at 20 10 hidden layer neurons

5 Actual line extention 0 0 50 100 150 200 250 300 4

ANN output of line extention 0 50 100 150 200 250 300

Table 5.5 The ANN hidden i w1 b layer weight matrix w1 and i,j j i,j j bias matrix bj 1 − 0.61 1.67 − 1.50 2.49 − 2.61 2 − 0.45 0.77 − 1.30 − 3.40 2.93 3 2.38 − 1.74 0.89 2.18 − 2.60 4 − 1.93 − 0.96 1.16 − 1.00 1.98 5 1.13 − 0.31 2.14 − 1.23 − 1.74 6 2.24 − 1.56 0.85 0.57 − 1.58 7 0.49 0.42 2.26 2.41 1.08 8 0.17 − 1.41 1.92 2.01 0.50 9 − 1.80 1.85 0.68 2.11 0.33 10 1.83 0.47 2.10 − 1.49 − 0.32 11 1.89 − 1.64 − 1.03 − 1.07 − 0.30 12 − 0.05 1.92 2.06 − 1.21 − 0.19 13 − 0.64 − 0.75 − 2.52 − 2.51 − 0.99 14 − 1.99 − 1.14 − 0.44 1.93 − 0.96 15 1.58 − 0.84 − 2.24 − 0.86 1.50 16 − 2.83 0.81 − 1.11 1.06 − 1.32 17 − 2.30 0.31 − 1.98 − 1.16 − 2.16 18 − 0.77 − 2.30 − 0.61 − 1.09 − 2.50 19 − 1.83 − 2.20 − 1.21 0.51 − 2.35 20 − 2.06 − 1.19 1.01 3.35 − 2.51

connection to the hidden layer nodes, and b2 is the bias connection to the single  1  output node. f is the sigmoid function which is given by  − x  . 1+ e  68 T.-M. Choi and Y. Yu 0.46 0.40 0.21

− 0.33 0.59 0.33

0.52 −

0.59 −

0.21 −

0.57 −

− 0.31 0.84

− 0.18 0.36

− 0.63 0.12

0.57 −

0.40 −

− ANN output layer weight matrix The

0.12

j =

2 able 5.6 T b 2 w 0.43 0.19 5 An Analysis of Fashion Brand Extensions by Artificial Neural Networks 69

7 4 Premium Fashion Premium Fashion 6 Mass Fashion 3.5 Mass Fashion Premium Basic Premium Basic 3 5 Mass Basic Mass Basic 2.5 4 2 3 1.5 Line extension Line extension 2 1 1 0.5 0 0 1 2 3 4 5 6 1 2 3 4 5 6 Period Period Asia Europe 3.5 Premium Fashion 3 Mass Fashion Premium Basic 2.5 Mass Basic

1.5

Line extension 1

0.5

0 1 2 3 4 5 6 Period North America

Fig. 5.2 Number of line extensions estimated by the ANN model

We also use ANN to model the number of category extensions over time. To avoid repetition, the details are omitted here. To study the effect of the independent variables of “region, period, and cluster” on the number of line and category extensions, all combinations of these independent variables are fed into the ANN. The ANN outputs of the numbers of line and category extensions for different regions are depicted in Figs. 5.2 and 5.3, respectively. Figures 5.2 and 5.3 reveal that different clusters of brands adopt different numbers of line and category extensions over different time periods with very few ex- ceptions. Hence, this ANN model supports hypothesis H1. Figure 5.2 suggests that more line extensions occur in Asia during later periods than other regions. Thus, hypothesis H2 is supported for the case of line extension. However, for the case of category extension, it is not clear if Asian brands extend their categories more than other regions. Therefore, hypothesis H2 is not clearly supported for the category extension. Hypothesis H3 is partially supported in which the number of line/category extensions of different clusters of brands in different regions do vary a lot over time; 70 T.-M. Choi and Y. Yu

3.5 4.5 Premium Fashion Premium Fashion 4 3 Mass Fashion Mass Fashion Premium Basic 3.5 Premium Basic 2.5 Mass Basic Mass Basic 3 2 2.5

1.5 2 1.5 1 Category extension Category extension 1 0.5 0.5 0 0 1 2 3 4 5 6 1 2 3 4 5 6 Period Period Asia Europe 2 1.8 Premium Fashion Mass Fashion 1.6 Premium Basic Mass Basic 1.4 1.2 1 0.8 0.6 Category extension 0.4 0.2 0 1 2 3 4 5 6 Period North America

Fig. 5.3 Number of category extensions estimated by the ANN model however, some clusters of brand do not extend much. For example, as shown in Fig. 5.2, the premium fashion cluster does not appear to employ the line extension in North America. Finally, hypothesis H4 is partially supported by our ANN analysis because: It is true that the mass basic cluster of brands has more line/category extensions in the later periods, but it is unclear that the premium fashion cluster of brands has more line/category extensions in the earlier periods. Based on our ANN analysis, we can conclude that H1 is supported, H2 is supported for the case of line extension, and H3 and H4 are partially supported. As a comparison, the results of this chapter and Choi et al.’s (2011b) are shown in Table 5.7. From Table 5.7, we can see that by using ANN, we can provide scientific evidence to support the hypotheses (with good literature support). To be specific, for both hypotheses H1 and H2, ANN can support more of these two theory-based hypotheses in which the statistical tools failed (because of the limitations of these tools and the specific feature of the dataset). For hypotheses H3 and H4, ANN and the statistical tools give similar conclusion. This direct comparison shows that the use of ANN can provide an alternative way of scientifically proving some empirical hypotheses in which the standard statistical tools fail to help owing to the respective conditions and assumptions for applying them. 5 An Analysis of Fashion Brand Extensions by Artificial Neural Networks 71

Table 5.7 Hypotheses testing Statistical tools (Choi et al. ANN (this chapter) results—comparisons 2011b) H1 Supported only for period 5 Supported H2 Supported for the line exten- Supported for the sion case only with (1) case of line European brands for period extension 5 and (2) Asian brands for period 6 H3 Partially supported Partially supported H4 Partially supported Partially supported

4 Discussions on Consumer Welfare

From the hypothesis testing results from the ANN analysis and the literature’s statistical analysis, we have a good reason to believe that the following two findings are valid: Finding 1: Fashion brands adopt different levels of category/line extensions over different time periods. Finding 2: European and North American brands have more line extensions in earlier time periods, while Asian brands have more line extensions in later periods. From Finding 1, we notice that at different periods of time, fashion brands implement both kinds of brand extensions at different rate and level. Since more brand extension implies more product variety for consumers, which directly leads to higher consumer welfare (both consumer satisfaction and a better quality of life from the variety of products offered), Finding 1 means that the consumer welfare as related to brand extension does vary in different periods of time. In addition, consumers buying European and North American brands would enjoy more variety of products of the respective fashion brands with respect to their line extensions during the earlier periods of time. This is different from the consumers who love the Asian brands as there are more line extensions for Asian brands in the later periods of time. In terms of consumer welfare, we hence also notice the differences.

5 Conclusion

In this chapter, we have used ANN to examine category and line extensions in the fashion industry over a 90-year period. We followed Choi et al. (2011b) and tested the respective four hypotheses by using publicly available data collected from 48 fashion brands in Europe, North America, and Asia. To explore about the underlying patterns and trends of line/category extensions of fashion brands in different regions over time, our ANN analysis enabled us to provide support for certain hypotheses that the traditional statistical methods would have failed to confirm. This result reveals that ANN can be a useful tool for exploring other fashion business issues in a scientific manner. 72 T.-M. Choi and Y. Yu

Appendix

Table A.1 The 48 sampled brands as shown in Choi et al. (2011b) Cluster Brand (country of origin) Brand (country of origin) Cluster 1 Abercrombie & Fitch (North America) American Eagle Outfitters (North America) Backle (North America) Baleno (Asia) Bossini (Asia) Crocodile (Asia) Esprit (Europe) G2000 (Asia) Gap (North America) Giordano (Asia) Levi’s Strauss & Co. (North America) Limited Brands (North America) U-Right (Asia) Uniqlo (Asia) Urban Outfitters (North America) Cluster 2 Bauhaus (Asia) Chevignon (Europe) Diesel (Europe) Lacoste (Europe) Miss Sixty (Europe) United Colors of Benetton (Europe) Cluster 3 Agnes b. (Europe) Anna Sui (North America) Calvin Klein (North America) Dolce & Gabbana (Europe) Donna Karan (North America) Givenchy (Europe) Jil Sander (Europe) Max Mara (Europe) Michael Kors (North America) Missoni (Europe) Paul Smith (Europe) Ralph Lauren (North America) Sonia Rykiel (Europe) Stella McCartney (Europe) Tommy Hilfiger (North America) Viktor & Rolf (Europe) Yohji Yamamoto (Asia) Cluster 4 F.C.K. (Asia) H&M (Europe) Izzue (Asia) Morgan (Europe) Mango (Europe) I.T (Asia) Two percent (Asia) Veeko (Asia) Victoria Secret (North America) Zara (Europe)

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A Comparative Investigation Between Status- and Non-status-Seeking Teenagers

Ian Phau

1 Introduction

Many studies have reported that younger Australian consumers prefer foreign-made clothing to domestic ones (for example, Brewer and Chen 2007; Chinen and Sun 2011; Jin et al. 2010; Jin and Ji 2010), and purchase more foreign-made than domestic-made clothes (Jin and Ji 2011; Kumar et al. 2009; Patterson and Tai 1998). The Australian Bureau of Statistics (2010) has indicated that there is a large deficit in the textiles, clothing, footwear, and leather manufacturing trade. Industry data for 2000–2010 showed a 23.5 % decrease from the same period in 2005–2006. This was accompanied by a rise in terms of trade, indicating that Australia could purchase a greater volume of imports with a given volume of exports; and vice versa. In 2010, textile and apparel imports rose to a record $ 2,452 million, whereas exports of textiles and apparel fell to $ 1,958 million (Australian Bureau Statistics 2010). Further inquiry is therefore required to help explain why Australians buy more foreign-made garments as opposed to domestically produced ones. This phenomenon seems to be a global trend whereby foreign products seem to be preferred over domestically manufactured products (e.g. Madahi et al. 2012; Samiee et al. 2005; Gurhan-Canli and Maheswaran 2000; Häubl 1996; Javalgi et al. 2001). Prior studies, such as Beaudoin et al. (1998), have found that overall fashion leaders in America have had more positive attitudes toward buying imported apparel than domestic apparel. Given that fashion-conscious consumers as well as status-seeking consumers in America have a great impact on the luxury goods sales across the world (The Economist 2004), it is assumed that there is an affiliation between consumers who are fashion and status conscious. In addition, both fashion leaders (Goldsmith et al. 2010; Latter et al. 2010; Shukla 2010; Phau and Cheong 2009; Silverstein et al. 2008) and status-seeking consumers purchase apparel to

I. Phau () The School of Marketing, Curtin University, GPO Box U1987, 6845 Perth, Western Australia e-mail: [email protected] T.-M. Choi (ed.), Fashion Branding and Consumer Behaviors, 77 International Series on Consumer Science, DOI 10.1007/978-1-4939-0277-4_6, © Springer Science+Business Media New York 2014 78 I. Phau

satisfy symbolic needs. This study aims to set a precedent in investigating the attitudes of status- and non-status-seeking consumers with regards to apparel purchase. It is interesting to note that previous studies on consumers’ attitudes toward purchasing domestic versus foreign apparel were mostly focused on specific but older demographic age group of consumers (e.g. Phau and Cheong 2009; Beaudoin et al. 1998; Kaynak and Kara 2002; O’Cass and Lim 2002), and have found significant patterns. Only a few studies have focused on the teenager segment, and it represents an inherent gap in the literature (Phau and Leng 2008; Beaudoin and Lachance 2009). The 2001 Census indicated that teenagers from the age range of 15–19 have increased by 1 % between 1991 and 2001 to more than 1.2 million. The median income of a teenager increases with age, from $ 16 to 162 per week among 15–19 year olds, and that income is essentially derived from part-time employment. This age segment is an attractive one due to its growing purchasing power (Solka et al. 2011; Seock and Hathcote 2010). The relevance of using teenagers in this study is further attributed to Piacentini and Mailer’s (2004) revelation that teenagers often use clothing, which is a socially consumed product, to symbolize status. Teenagers are often in stages of uncertainty, where they are more likely to rely on luxury brands to assist them in performing their desired role (Bevan-Dye et al. 2012; Gil et al. 2011; Piacentini and Mailer 2004). They have a valuable impact on the fashion industry (Gil et al. 2011; Phau and Leng 2008; Coelho and McClure 1993; O’Cass and Frost 2002) with regards to their purchase of luxury brand apparel. Thus, their attitudes toward buying foreign luxury brand apparel as compared to Australian luxury brand apparel should be evaluated. Many questions need to be answered. Do young status-seeking consumers have a different attitude toward purchasing foreign and Australian luxury brand apparel? Are there some specific apparel attributes that lead young status-seeking consumers to believe that foreign luxury brand apparel represent a better acquisition than their Australian counterparts? With regards to choice of foreign luxury apparel, would the choice vary from one country to another (i.e. Italy, Japan, and China) when compared to domestic luxury apparel? In this study, foreign brand apparel is specifically chosen by country, namely Italy, Japan, and China, instead of listing them as imports in general. Further, Pat- terson and Tai (1991) and O’Cass and Lim (2001) noted that a particularly strong bias exists toward brands made in developing countries. This finding is supported by more recent studies on country of origin (e.g. Zhou et al. 2010; Lee et al. 2010; Samiee et al. 2005; Opoku and Akorli 2009). Thus, a comparative study on luxury brand apparel from different countries is necessary to explore such bias. It is also important to understand that the objective of the present study is not to compare preferences among the four countries, but rather to analyse the choice between Aus- tralian made and foreign made. This report will be structured as follows. Specifically, the literature review describes how teenagers may relate to status-seeking consumption and the effects of culture of brand origin toward status consumption. This will lead to the formulation of the hypotheses. The Fishbein’s Model is next described in relevance to the methodology of this study. The results and the analysis will next be presented. Finally, 6 “Domestic-Made” or “Foreign-Made” Luxury Brands? 79 the concluding comments are presented with suggested future research directions radiating from this study.

2 Relevant Literature

Previous studies comparing consumers’ attitudes toward purchasing domestic or foreign apparel have found that most consumers prefer foreign rather than domestic clothes if it is more expensive (Drozdenko and Jensen 2009; Mohamad et al. 2000), luxury brands (Phau and Cheong 2009; Phau and Leng 2008; Mohamad et al. 2000; Beaudoin et al. 1998), more fashionable brands (Souiden et al. 2011; Beaudoin and Lachance 2009; Beaudoin et al. 1998), and of favourable country of origin (Gold- smith et al. 2010; Latter et al. 2010; Phau and Cheong 2009; Phau and Leng 2008; O’Cass and Lim 2002). Thus, it is important to examine the fashion context in relation to status consumption.

2.1 Status Consumption and Teenagers

Researchers have defined status consumption as the driving force in enhancing social standing through conspicuous consumption (Goldsmith and Clarke 2012; Shukla 2010; Heaney et al. 2005; Eastman et al. 1999; Deeter-Schmelz et al. 2000; O’Cass and Frost 2002; Piacentini and Mailer 2004; Tanner and Roberts 2000). Conspicuous consumption involves the public consumption of luxury products that signal wealth, status, and power (Goldsmith and Clarke 2012; Shukla 2010; Bag- well and Bernheim 1996; Eastman et al. 1999; Vigneron and Johnson 1999). Con- sumption of status or symbolic products also assists in enhancing social recognition and self-concept (Shukla 2010; Eastman et al. 1999; Deeter-Schmelz et al. 2000; Piacentini and Mailer 2004). Heaney et al. (2005) and O’Cass and Frost (2002) pointed out that status-oriented consumers will only purchase products that represent status in the eyes of others whom they feel are significant. At some stage, status consumption is viewed as materialism (Goldsmith et al. 2012; Eastman and East- man 2011; Tanner and Roberts 2000; Wong and Ahuvia 1998). Thus, it is arguable that status consumers are more likely to buy luxury apparel than non-status-seeking consumers, as it satisfies their symbolic needs (Goldsmith et al. 2012; Shukla 2010; Eastman et al. 1999; Goldsmith and Stith 2011). Many researchers have explored the trend of status, symbolic or prestige consumption for different purposes. For instance, Eastman et al. (1999), Deeter- Schmelz et al. (2000), and Vigneron and Johnson (1999) were interested in the development and validation of a consumption scale, whereas O’Cass and Frost (2002) looked to broaden the understanding toward status brands and the behaviours associated with it. On the other hand, Frijters (1998) and Coelho and McClure (1993) 80 I. Phau focused on the fashion industry by analysing status consumption from an economic perspective. The teenage market is a vigorous and extremely competitive environment. It represents a broad market that can be generalised (Piacentini and Mailer 2004; Toote- lian and Gaedeke 1992). While the teenage market offers plenty of opportunities for new entrants, and a great scope for innovations, it is also notoriously hard to please (Parker et al. 2004; Taylor and Cosenza 2002). All facets of the media (i.e. fashion, television, the Internet, and music) form significant influences, and make teens savvy toward what they want (Naderi 2011; Yoo and Kim 2010). Also, many of the researchers have suggested that teenagers are lavish spenders when it comes to branded and luxury products (Gil et al. 2011; Stankeviciut and Hoffmann 2010). Further, researchers such as Bevan-Dye et al. (2012) and Gil et al. (2011) have shown evidence in their research that younger consumers are driven by the need to possess and display status brands. Piacentini and Mailer (2004) have also indicated that teenagers from wealthier families having more disposable money are less likely to be involved in status consumption. On the other hand, teenagers from the lower and middle social classes are more likely to be involved in status consumption to display their “wealth”. Con- sistent with studies from Goldsmith et al. (2012) and Eastman and Eastman (2011), status-seeking consumers can come from any income or social class level. On the contrary, Chao and Schor (1998) demonstrated in a study on cosmetics that the status-seeking consumers are mostly Caucasian, higher in education and income, and live in urban communities. Further, Amatulli and Guido (2011), Husic and Cicic (2009), and Deeter-Schmelz et al. (2000) ascertain that consumers’ income have minimal impact on prestige concept. The study of apparel is appropriate in this instance, as the act of purchasing apparel satisfies the various needs of the consumer, which signals status (e.g. Gold- smith et al. 2010; Shukla 2010), expression of identity (e.g. Shukla 2010; Piacentini and Mailer 2004), self-concept (e.g. Shukla 2010; Wong and Ahuvia 1998), self- esteem (e.g. Khare et al. 2011; Souiden et al. 2011), as well as gives individuals a way to impress others (e.g. Khare et al. 2011; Souiden et al. 2011). Noble and Walker (1997) and Piacentini and Mailer (2004) observed that teenagers are often in stages of role transitions and uncertainties. These consumers, therefore, rely on status consumption and the needs mentioned above to assist them in performing desired roles and showing maturity (Piacentini and Mailer 2004). Similarly, Gil et al. (2011) and Podoshen et al. (2010) suggested that material possessions such as apparel are seen as an important source of status for teenagers. Thus, the term luxury brand apparel is very applicable to this study. O’Cass and Frost (2002) indicated that consumers may recognise the brand name and image associated with a status brand. However, these same consumers may not necessarily be familiar with other features of the brand. Grace and O’Cass (2002), Phau and Cheong (2009), and Phau and Leng (2008) determined that a status product possesses good quality and a favourable brand name. Thus, country-of-origin image or association impacts consumers’ perceptions or beliefs toward particular 6 “Domestic-Made” or “Foreign-Made” Luxury Brands? 81 brands (Samiee et al. 2005; Veale and Quester 2009; Phau and Cheong 2009; Phau and Leng 2008; Mohamad et al. 2000). Wong and Ahuvia’s (1998) study on luxury consumption ascertains that western consumers are more likely to judge each product independently regardless of the brand, manufacturer, and country of origin as compared to Asian consumers. This finding contradicts many other studies on country of origin (Brewer and Chen 2007; Beaudoin et al. 1998; Gurhan-Canli and Maheswaran 2000; Häubl 1996; Javalgi et al. 2001; Laroche et al. 2002; Ahmed and d’Astous 1993; Ulgado and Lee 1998). However, recent research on materialism can offer an explanation for this. Work- man and Lee (2010) suggest that Western consumers perceive status in the ability to acquire luxury items for themselves and emphasised quality and style. In contrast, Asian consumers demonstrated a more conspicuous orientation, considering luxury goods as indicators of success and necessary for happiness.

2.2 Country of Origin

According to Morello (as cited in Javalgi et al. 2001), the term country of origin has been widely used for more than a 100 years. Country of origin, country of manufacture, or country of brand origin have been considered as extrinsic cues of a product, and there has been a large amount of evidence supporting their significant effects on consumers’ product evaluation (e.g. Chan and Tung 2011; Magnusson et al. 2011; Gurhan-Canli and Maheswaran 2000; Ulgado and Lee 1998). Koschate- Fischer et al. (2012), Chinen and Sun (2011), and Jin et al. (2010) have also proved that these cues have a significantly direct effect on attitudes and beliefs toward a product. The goal of these researchers was to investigate consumer images of countries and brands, and to measure the relative importance of certain attributes when consumers buy these products. However, these terms are becoming increasingly misleading or confusing in the current market, where hybrid products typically comprise more than one country’s contribution toward the completed product (Jung and Yoon 2012; Henderson and Hoque 2010; Phau and Cheong 2009; Häubl 1996; O’Cass and Lim 2001, 2002). As a result, “Country of brand origin may be the reason consumers still attach certain cultural characteristics to a brand when specific information about the foreign country is not available” (O’Cass and Lim 2002, p. 763). Therefore, it is assumed that country of brand origin (Ahmed et al. 2012; O’Cass and Lim 2002) would be a more appropriate term to use in the examination of consumers’ perceptions on brand origins. Many studies have focused on consumers’ perceptions of domestic versus foreign-made products or brands in relation to ethnocentrism (Tabassi et al. 2012; Lwin et al. 2010; Kaynak and Kara 2002; O’Cass and Lim 2002; Supphellen and Rittenburg 2001; Ulgado and Lee 1998). As previously discussed, although most studies on the fashion industry in Australia found that the consumers have strong propensities to buy Australian-made apparel, more foreign-made rather than domes- 82 I. Phau tic-made apparel is still being purchased. Consumer ethnocentrism is displayed in this instance, where consumers believe that the purchase of foreign-made products is unpatriotic and harmful to the local economy, and imports can result in the loss of local jobs (e.g. Bi et al. 2012; Lwin et al. 2010). Researchers also found that younger Australians are more likely to purchase foreign-made apparel, which means that they have lower consumer ethnocentrism (Phau and Cheong 2009; Phau and Leng 2008; Fischer and Byron 1997; Patterson and Tai 1991). Furthermore, ethnocentrism is also a cultural dimension besides country of brand origin. Hence, a product or brand from a highly ethnocentric country with a strong culture can be a more successful global brand than from a less ethnocentric country. For instance, apparel from Australia, New Zealand, and the UK are preferred by Australians than apparel from China and Southeast Asia on every product attribute except for price (Phau and Leng 2008; Mohamad et al. 2000; Patterson and Tai 1991). This observation is supported by Kaynak and Kara (2002) and O’Cass and Lim (2002), who have indicated that products from developed countries were perceived as expensive luxury items that have a well-known brand name and are tech- nologically superior. This proves that Australians prefer apparel from developed countries, and that bias on apparel from developing countries may be compensated by price concessions (Wong et al. 2008; Phau and Leng 2008; Mohamad et al. 2000; Patterson and Tai 1991). Mohamad et al. (2000) ascertain that consumers’ positive attitudes toward more expensive designer products appear to be influenced by country of origin and brand status rather than price and availability. Also, country of origin has a positive relation with product quality (Godey et al. 2011; Chung et al. 2009; Mohamad et al. 2000). It is also a vehicle for creating an emotional bond with the consumer. It is therefore necessary to conduct a comparative study to investigate such biases. Hence, for this study, foreign luxury apparel was classified into three countries with different economic backgrounds; with Italy and Japan being considered as the developed countries, and China as the developing country. This was so as to identify the differences in attitudes toward luxury clothes from these foreign countries as compared to the domestic offerings.

3 Hypotheses

The aim of the study is to determine if status- and non-status-seeking Australian teenagers differ in their attitudes toward buying luxury brand apparel that are Made in Australia, as compared to those (a) Made in Italy, (b) Made in Japan, and (c) Made in China. Based on the review in the preceding section, the following hypotheses are presented: H1: There is no difference in non-status-seeking teenagers’ attitudes toward buying Australian luxury brand apparel and foreign luxury brand apparel. H2: Status-seeking teenagers have a more positive attitude toward buying luxury brand apparel that is 6 “Domestic-Made” or “Foreign-Made” Luxury Brands? 83 a. Made in Italy rather than Made in Australia, b. Made in Japan rather than Made in Australia, and c. Made in Australia rather than Made in China. H3: There is no difference between status-seeking teenagers’ and non-status-seeking teenagers’ attitudes toward luxury brand apparel that are Made in Australia. H4: There is no difference between status-seeking teenagers’ and non-status- seeking teenagers’ attitudes toward luxury brand apparel that are a. Made in Italy, b. Made in Japan, and c. Made in China.

4 Conceptual Framework

Fishbein’s (1967) multi-attribute attitude model was used as the theoretical framework for this study due to its analytical value in clarifying attitudes (Be- audoin et al. 1998). This model is used to measure and compare attitudes between buying domestic and foreign products. Beaudoin et al. (1998) explained the model with the assumption that, in order to access a person’s attitude, the salient beliefs that person has about an object, people, or issue needs to be measured. These salient beliefs are combined to give an overall evaluation about the behaviour under consideration. According to this model, an individualƞ’s attitude toward certain behaviour can be predicted by adding all the products that result from the multiplication of the beliefs of that person and the evaluation of each consequence the person associates with an act. In this context, the term “consequence” refers to any belief about the behaviour, including its perceived consequences, and effort to perform the behaviour. The following equation describes this integration process:

n AbBi= ∑ ei (6.1) i=1 Where:

AB attitude toward the behaviour (attitudes toward buying foreign or domestic apparel products). bi the belief that performing behaviour. AB leads to consequence Ai ≈. In this research, the Abi ≈ refers to the beliefs that a domestic (foreign) apparel product will possess a certain attribute(s). ei = the evaluation of consequence, “i” refers to the importance of the attribute. n = number of key consequences. 84 I. Phau

5 Methodology

5.1 Instrument

The first part of the survey instrument measures status consumption through Eastman et al.’s (1999) status consumption scale (SCS). The scale has been evaluated by the authors for its dimensionality, test–retest reliability, discriminant validity, criterion validity, nomological validity, internal consistency, and freedom from response bias (i.e. social desirability). It has five Likert-type items (one item reverse coded) and is rated on a seven-point scale ranging from “strongly disagree” to “strongly agree”. A median split was used to separate status-seeking and non-status-seeking teenagers. In the next section, the attitudes toward buying foreign luxury brand apparel and Australian luxury brand apparel are measured by the Fishbein’s (1967) multi- attribute attitude model. Participants in this study were asked to give their opinions about foreign luxury brands from specific countries chosen namely Italy, Japan, and China. They were also asked to give their opinions about foreign and domestic luxury clothing in general, without any type or brand specifics. This is to avoid bias through stereotyping certain brands and types of apparel. In the context of this research, by replicating Beaudoin et al.’s (1998) method, the variables which are in Fishbein’s formula are defined as follows:

AB attitude toward the purchase of foreign versus domestic luxury brand apparel. bi the belief that purchasing of foreign versus domestic luxury brand apparel will lead to a certain attribute. ei the evaluation of the importance of the attribute. In order to calculate the overall attitude toward foreign (i.e. Italy, Japan, and China) and Australian luxury brands of apparel for each participant, the same methods used by Beaudoin et al. (1998) were utilised. Since Beaudoin et al. (1998) suggested that the apparel attributes used were ascertained by a review of past research and experts in that field, the 12 attributes were replicated in the present study. These are: appro- priateness for occasion, attractiveness, brand name, choice of colour, choice of style, comfort, durability, ease of care, fashionableness, good fit, good price, and quality.

To calculate the “ei”, participants were asked to specify how important each of the 12 attributes is when they purchase luxury brand apparel (Beaudoin et al. 1998). A seven-point Likert-type scale was utilised in this study from 0 = very unimportant to 6 = very important. Again, participants were asked how they expected to find each of the same 12 apparel attributes when considering (a) Italy, (b) Japan, (c) China, and Australian luxury brands of apparel to measure the “bi”. The inclusive attitude toward both Australian and foreign luxury brands was then computed for each participant by multiplying the evaluation score ( ei) and the belief score ( bi), and sum- mating the scores of the 12 apparel attributes (Beaudoin et al. 1998). The final part of the questionnaire includes demographic questions (such as gender, age, ethnicity/race, allowance per week, and postal code). In addition, one open- ended question that related to apparel purchase behaviour was included in this section: 6 “Domestic-Made” or “Foreign-Made” Luxury Brands? 85

On the average, how much money do you spend each month for your own clothes?

5.2 Sample

The sample consisted of early and middle teens aged 13–17 and late teens aged 18–19. Particular attention was paid to the 15–19-year-old group due to their desire to fully express themselves, their higher maturity in the sense of interpretation and knowledge, and their high desirability on maturity transition (Piacentini and Mailer 2004; Taylor and Cosenza 2002). High school students were selected for the sample for several reasons. Firstly, they are (generally) in their teens. Secondly, they form the bulk of consumers for teen products. Thirdly, high school students in general are Australian citizens even though they may vary in ethnicity. A total of 900 survey forms were distributed through 11 senior high schools, technical and further education (TAFE) campuses, and colleges in the city of Perth, Western Australia. The principals of these institutions have agreed to grant permission for these surveys to be done during school hours. A total of 710 questionnaires were returned (79 %); however, 47 were unusable. In total, 663 were usable, representing a more than 70 % (74 %) response rate.

6 Results and Discussion

6.1 Characteristics of the Sample

The participants’ age ranged from 13 to 19 years. Half of the participants were in the 15–17 age group (47.2 %), and the other 42.4 % were in the 18–19 age group. There was an approximately equal distribution of allowances received per week by participants; 31 % received more than $ 100 per week (Table 6.1). This shows they were not from any distinct social class. Consistently, the results show a fairly equal spread of postal codes provided by participants.

6.2 Determination of Status-Seeking and Non-status-Seeking Groups

Status-seeking teenagers and non-status-seeking teenagers were separated by the al- location of the SCS scores. A total of 315 respondents (47.5 %), with scores of 4.3 and above by the median split on the scale, were designated as status-seeking teenagers; whereas 348 (52.5 %) participants were categorised as non-status-seeking teenagers. The median of 4.2 approximately separated the natural break in the data with a mean of 4.1 (SD = 1.45). Since using the median split of 4.2 to separate the status-seeking teenagers and non-status-seeking teenagers may seem subjective, an open-ended question related 86 I. Phau

Table 6.1 Frequency Variables Absolute frequency Relative frequency distribution of demographic ( N = 663) (%) variables Gender Male 323 49.0 Female 340 51.0 663 100.0 Age 13–14 69 10.4 15–17 313 47.2 18–19 281 42.4 663 100.0 Allowance per week (AUS Dollar) Under $ 50 232 35 $ 51 to $ 100 226 34 Over $ 100 205 31 663 100.0 to status-pertinent behaviour was added to the questionnaire to certify the robustness and the validity of the method of determining status-seeking participants. A t-test was used to compare status- and non-status-seeking teenagers for this variable. As discussed earlier, status-seeking consumers tend to spend more money on apparel than non-status-seeking consumers. Hence, status-seeking participants should have a higher mean than non-status-seeking participants regarding this fashion behaviour. This was also used as a criterion to ensure that the group chosen was status-seeking consumers. The test reported that status-seeking teenagers (mean of $ 162.05) significantly ( p < 0.001) spent more than non-status-seeking teenagers (mean of $ 105.10).

6.3 Hypothesis 1

H1 was tested with repeated measure ANOVA on each comparison. H1 with reference to Italian-made luxury brands, was supported. The result for Australian luxury brands (mean = 28.16) versus Italian luxury brand apparel (mean = 28.23) was not significant; non-status-seeking teenagers reported the same overall attitude toward both Australian and Italian luxury brands (MS = 121.67, F = 0.43, p = 0.543).

H1 with reference to Japanese-made luxury brands was also supported. The results showed that Australian luxury brand apparel (mean = 28.16) versus Japanese luxury brands (mean = 28.35) was not significant; non-status-seeking teenagers reported the same overall attitude toward both Australian and Japanese luxury brands (MS = 1322.15, F = 3.32, p = 0.081). Hence, there is no difference in non-status-seeking teenagers’ attitudes toward buying Australian luxury brands and Japanese luxury brands.

However, H1 on Chinese-made luxury brands was rejected. The results for Aus- tralian brand apparel (mean = 28.16) versus the Chinese brands (mean = 23.15) was 6 “Domestic-Made” or “Foreign-Made” Luxury Brands? 87 significant; non-status-seeking teenagers had overall a more positive attitude toward Australian luxury brands than the Chinese luxury brands (MS = 13404.25, F = 39.04, p = 0.0001).

Overall, the result for H1 on Australian luxury brands of apparel (mean = 28.16) versus foreign luxury brands (mean = 25.15) was significant; non-status-seeking teenagers had an overall more positive attitude toward Australian brands (MS = 13804.55, F = 43.056, p = 0.0001) than foreign brands (MS = 189.34, F = 9.17, p = 0.004). There- fore, H1 on Australian-made versus foreign-made luxury brand apparel was accepted. In order to have a better justification of the findings, the 12 apparel attributes were analysed separately with 12 repeated measures ANOVA to determine if non- status-seeking teenagers gave the same evaluation toward Australian and foreign luxury brands on each of the 12 apparels attributes (i.e. non-status-seeking teenagers may have given a higher evaluation of Australian luxury brands for some attributes as compared to their evaluations of foreign luxury brands and vice versa). Beau- doin et al. (1998) suggested that in order to avoid type I error (falsely accepting a hypothesis) on the 12 attributes, which are not independent, one could use the Bonferroni inequality to determine the critical F values. In order to replicate Be- audoin et al.’s (1998) method of multiple comparisons, the significance level was divided by the number of comparisons to fix the new level of significance. There- fore, the significance level, which was fixed originally at 0.05, was reduced to 0.004 (0.05/12 = 0.004). The results of the 12 additional repeated measures ANOVA are shown in Tables 6.2a and 6.2b. Non-status-seeking teenagers gave significantly higher evaluations to Australian luxury brands over Italian brands on three attributes—ease of care, good price, and comfort. However, they considered Italian luxury brand apparel to be significantly better than Australian luxury brand apparel on three attributes— quality, fashionableness, and brand name. Regarding the other attributes, non-status- seeking teenagers considered Australian luxury brands as good as Italian brands. Conversely, non-status-seeking teenagers gave significantly higher evaluations to Australian luxury brands over Japanese brands on five attributes—good fit, durability, ease of care, comfort, and quality. Nevertheless, they considered Japanese luxury brands to be significantly better than Australian luxury brands on two attributes—good price and being fashionable. There were no differences in the other attributes for Australian and Japanese luxury brands. Lastly, non-status-seeking teenagers gave significantly better evaluations of Aus- tralian luxury brands over Chinese ones on six attributes—good fit, durability, ease of care, comfort, quality, and appropriate for occasion. In contrast, non-status-seeking teenagers gave significantly higher evaluations to Chinese luxury brands of apparel over Australian luxury brands for good price. Regarding the other attributes, non- status-seeking teenagers considered Australian brands as good as Chinese brands. To conclude, non-status-seeking teenagers overall have a more positive attitude toward luxury brand apparel from Italy, Australia, and Japan. In contrast, they do not have positive attitudes toward luxury brand apparel from China. However, non-status-seeking teenagers had a more positive overall attitude toward Australian-made luxury clothing than foreign-made brands. This could be due to the fact that when 88 I. Phau

Table 6.2a Attitude of Attributes Brand Mean MS F value pr > Fa non-status seeking teenagers Appropriate for Australia 27.30 toward buying Australian occasion and Foreign luxury brands of (a) Italy 28.48 169.22 3.15 0.0789 apparel. Attributes 1–6 (b) Japan 24.88 460.86 7.49 0.0087 (c) China 23.65 788.31 12.42 0.0001 Attractiveness Australia 28.89 (a) Italy 27.04 306.28 4.28 0.0523 (b) Japan 27.68 38.66 0.58 0.5490 (c) China 23.15 1270.11 19.65 0.0001 Brand name Australia 19.23 (a) Italy 22.18 540.64 17.54 0.0001 (b) Japan 18.23 223.21 5.40 0.0301 (c) China 11.80 4322.59 105.54 0.0001 Choice of styles Australia 27.80 (a) Italy 29.83 320.25 4.87 0.0444 (b) Japan 29.28 9.39 0.32 0.7921 (c) China 26.00 329.26 5.52 0.0290 Colour Australia 27.33 (a) Italy 31.20 292.60 4.29 0.0432 (b) Japan 29.30 0.16 0.00 0.9830 (c) China 27.83 16.28 0.35 0.7250 Comfort Australia 35.00 (a) Italy 33.16 732.34 13.03 0.0001 (b) Japan 32.59 1265.23 22.09 0.0001 (c) China 29.11 3439.42 49.87 0.0001 a The Bonferroni inequality was used to determine the critical value of F to be considered as significant the probability should be smaller than 0.04 ( p < 0.004). Mean scores could range from 1 to 49 a comparison between the three foreign countries was made, the results indicated that the opinions of Chinese luxury brand apparel were much lower. Overall, non- status-seeking teenagers still considered Australian-made luxury brands to be better.

6.4 Hypothesis 2

H2 was tested with a repeated measure of ANOVA. The result for H2a on Ital- ian luxury brand apparel (mean = 31.75) versus Australian luxury brand apparel (mean = 27.22) was significant. Status-seeking teenagers had a more positive overall attitude toward Italian-made luxury brand apparel than Australian-made luxury brand apparel (MS = 17305.14, F = 83.90, p = 0.0001). Thus, H2a was accepted. The 12 attributes were analysed separately again with 12 repeated measures of ANOVA to determine which attributes made this difference significant. Table 6.3a and 6.3b presents the results. Status-seeking teenagers gave significantly higher 6 “Domestic-Made” or “Foreign-Made” Luxury Brands? 89

Table 6.2b Attitude of Attributes Brand Mean MS F value pr > Fa non-status seeking teenagers Durability Australia 31.88 toward buying Australian and Foreign luxury brands of (a) Italy 32.58 273.10 4.67 0.0389 apparel. Attributes 7–12 (b) Japan 29.22 1739.40 24.14 0.0001 (c) China 21.56 13222.44 167.72 0.0001 Ease of care Australia 29.98 (a) Italy 25.53 648.44 10.67 0.0001 (b) Japan 28.12 607.39 10.25 0.0001 (c) China 25.88 1398.13 19.53 0.0001 Fashionableness Australia 25.12 (a) Italy 28.14 590.63 8.75 0.0001 (b) Japan 29.67 1634.91 23.54 0.0001 (c) China 22.48 490.21 7.83 0.0421 Good fit Australia 34.53 (a) Italy 33.60 19.87 0.35 0.5655 (b) Japan 31.11 792.47 11.13 0.0001 (c) China 29.58 1197.98 13.91 0.0001 Good price Australia 24.10 (a) Italy 19.39 2052.73 27.00 0.0001 (b) Japan 27.83 1478.28 17.92 0.0001 (c) China 37.98 15911.60 198.36 0.0001 Quality Australia 32.28 (a) Italy 36.88 1998.32 46.14 0.0001 (b) Japan 27.89 1180.65 14.83 0.0001 (c) China 19.56 15785.60 226.28 0.0001 a The Bonferroni inequality was used to determine the critical value of F to be considered as significant the probability should be smaller than 0.04 ( p < 0.004). Mean scores could range from 1 to 49 evaluations to Italian-made luxury brands over Australian-made on five attributes— good fit, quality, fashionableness, brand name, and appropriate for occasion. Yet, they considered Australian-made luxury brand apparel to be significantly better than Italian-made luxury brand apparel on three attributes—ease of care, good price, and attractiveness. Regarding the other attributes, status-seeking teenagers considered Italian-made luxury brands as good as Australian-made luxury brands.

As for H2b, a non-significant difference between Japanese luxury brand apparel (mean = 28.02) and Australian luxury brand apparel (mean = 27.22) was not expected. Status-seeking teenagers demonstrated the same overall attitude toward both Japanese and Australian luxury brand apparel (MS = 664.96, F = 1.69, p = 0.1950).

Thus, H2b was rejected. On the other hand, status-seeking teenagers gave significantly higher evaluations to Japanese-made luxury brands over Australian made on two attributes—fashionableness and brand name. It was also not expected that there were no significant higher evaluations of Australian-made luxury brands over Japanese-made luxury brands. There were no differences for other attributes of Australian- and Japanese- made luxury brands as well. 90 I. Phau

Table 6.3a Attitude of status Attributes Brand Mean MS F value pr > Fa teenagers toward buying Appropriate Australia 29.80 Australian and Foreign for occasion luxury brands of apparel. (a) Italy 32.85 888.36 19.00 0.0001 Attributes 1–6 (b) Japan 28.13 95.90 1.76 0.1890 (c) China 23.86 689.70 10.50 0.0010 Attractiveness Australia 30.03 (a) Italy 28.77 2080.05 29.80 0.0001 (b) Japan 31.87 140.96 1.70 0.3022 (c) China 29.18 644.16 7.59 0.0100 Brand name Australia 19.54 (a) Italy 39.44 39880.76 542.96 0.0001 (b) Japan 28.00 7251.68 79.58 0.0001 (c) China 13.02 4870.28 69.42 0.0001 Choice of Australia 27.44 styles (a) Italy 33.86 1930.65 25.23 0.0001 (b) Japan 30.23 206.15 2.18 0.1230 (c) China 27.80 31.98 0.38 0.6021 Colour Australia 30.02 (a) Italy 32.33 579.23 6.80 0.0230 (b) Japan 30.02 54.50 0.50 0.4823 (c) China 28.88 6.56 0.08 0.7980 Comfort Australia 33.90 (a) Italy 33.80 13.48 0.29 0.5960 (b) Japan 33.45 310.59 5.29 0.0280 (c) China 29.23 1259.68 19.90 0.0001 a The Bonferroni inequality was used to determine the critical value of F to be considered as significant the probability should be smaller than 0.04 ( p < 0.004). Mean scores could range from 1 to 49

On the contrary, the result for H2c on Australian luxury brands of apparel (mean = 27.22) versus Chinese luxury brands of apparel (mean = 22.47) was significant. Status-seeking teenagers had an overall more positive attitude toward Australian-made luxury brands than Chinese-made luxury brands (MS = 12224.58,

F = 37.68, p = 0.0001). Thus, H2cwas accepted. Status-seeking teenagers gave significantly better evaluations to Australian- made luxury brands over Chinese made on six attributes—durability, ease of care, comfort, quality, brand name, and appropriate for occasion. Status-seeking teenagers gave significantly higher evaluations to Chinese luxury brand apparel over Australian brand apparel on good price. Overall, status-seeking teenagers generally had a more positive attitude toward Italian, Japanese, and Australian luxury brand apparel. They too, gave significantly higher evaluations to Australian luxury brands over Chinese luxury brands. On the other hand, status-seeking teenagers had a significantly more positive attitude toward foreign-made luxury brand apparel than Australian made. 6 “Domestic-Made” or “Foreign-Made” Luxury Brands? 91

Table 6.3b Attitude of status Attributes Brand Mean MS F value pr> Fa teenagers toward buying Durability Australia 29.79 Australian and Foreign (a) Italy 31.61 140.27 3.53 0.0780 luxury brands of apparel. Attributes 7–12 (b) Japan 27.45 418.68 7.86 0.0083 (c) China 23.78 5790.65 63.48 0.0001 Ease of care Australia 29.44 (a) Italy 25.29 332.10 11.23 0.0010 (b) Japan 27.42 348.40 8.56 0.0086 (c) China 22.98 1940.53 32.04 0.0001 Fashionableness Australia 25.12 (a) Italy 28.14 590.63 8.75 0.0001 (b) Japan 29.67 1634.91 23.54 0.0001 (c) China 22.48 490.21 7.83 0.0421 Good fit Australia 34.53 (a) Italy 33.60 19.87 0.35 0.5655 (b) Japan 31.11 792.47 11.13 0.0001 (c) China 29.58 1197.98 13.91 0.0001 Good price Australia 24.10 (a) Italy 19.39 2052.73 27.00 0.0001 (b) Japan 27.83 1478.28 17.92 0.0001 (c) China 37.98 15911.60 198.36 0.0001 Quality Australia 32.28 (a) Italy 36.88 1998.32 46.14 0.0001 (b) Japan 27.89 1180.65 14.83 0.0001 (c) China 17.56 15785.60 226.28 0.0001 a The Bonferroni inequality was used to determine the critical value of F to be considered as significant the probability should be smaller than 0.04 ( p <0.004). Mean scores could range from 1 to 49

6.5 Hypothesis 3

H3 relates to the difference between the attitudes of status-seeking teenagers and non-status-seeking teenagers toward Australian luxury brands. A t-test was used to determine whether status-seeking and non-status-seeking teenagers had the same attitudes toward Australian-made luxury brands. The results showed that there is no significant difference between status-seeking and non-status-seeking teenagers’ attitudes toward Australian luxury brand apparel ( T = 0.94, p = 0.4240). The mean attitude toward Australian-made luxury brands for status-seeking teenagers was 27.32 and 28.47 for non-status-seeking teenagers. In order to have a better justification of the results, the 12 apparel attributes were analysed separately. Table 6.4 presents the results of the findings. Status-seeking teenagers gave higher evaluations than non-status-seeking teenagers to “Made in Australia” apparel on fashionableness. In contrast, non-status-seeking teenagers gave significantly higher evaluations than status-seeking teenagers to good price. These results also showed that there was no difference between the two groups with 92 I. Phau

Table 6.4 T-test comparison Attributes Status mean Non-status t value Pr > Ta between status and non-status mean teenagers’ attitude toward Appropriate for 29.80 27.30 − 0.38 0.6844 Australian luxury brands of occasion apparel by attributes Attractiveness 30.03 28.89 − 1.15 0.3433 Brand name 19.54 19.23 − 0.91 0.4230 Choice of styles 27.44 27.80 0.52 0.5940 Colour 30.02 27.33 − 0.48 0.5910 Comfort 33.90 35.00 0.92 0.2960 Durability 29.79 31.88 2.38 0.0075 Ease of care 29.44 29.98 0.74 0.5233 Fashionableness 28.88 25.12 − 2.23 0.0001 Good fit 32.00 34.53 0.78 0.2520 Good price 14.80 24.10 9.01 0.0001 Quality 32.00 32.28 0.23 0.8954 a The Bonferroni inequality was used to determine the critical value of F to be considered as significant the probability should be smaller than 0.04 ( p < 0.004). Mean scores could range from 1 to 49 regards to the attributes of good fit, durability, ease of care, comfort, quality, colour, attractiveness, brand name, appropriate for occasion, and choice of styles.

6.6 Hypothesis 4

H4 was concerned with the difference between the attitudes of status-seeking teenagers and non-status-seeking teenagers toward foreign luxury clothing. A t-test was used to determine that status-seeking teenagers (mean = 31.85) overall had a significantly ( T = − 3.82, p < 0.004) more positive attitude than non-status-seeking teenagers (mean = 27.75) toward Italian luxury brand apparel. H4a was rejected. Table 6.5 presents the results of the 12 additional t-tests that compared both groups’ attitudes toward Italian apparel on each attribute separately. The results showed that status-seeking teenagers gave significantly higher evaluations compared to non-status-seeking teenagers for Italian luxury brand apparel on three of the 12 apparel attributes—attractiveness, fashionableness, and brand name. Unex- pectedly, non-status-seeking teenagers gave considerably higher evaluations than status-seeking teenagers on good price. Other attributes such as good fit, durability, ease of care, comfort, quality, colour, appropriate for occasion, and choice of styles had no significant differences between the two groups.

For H4b, a t-test showed that there were no significant differences ( T = − 1.35, p = 0.1845) between status-seeking teenagers’ (mean = 28.52) and non-status-seeking teenagers’ (mean = 27.28) attitudes toward Japanese luxury brand apparel. Con- sequently, H4b was accepted. 6 “Domestic-Made” or “Foreign-Made” Luxury Brands? 93

Table 6.5 T-test comparison Attributes Status mean Non-status t value Pr > Ta between status and non-status mean seeking teenagers’ attitude Appropriate for 32.85 28.48 − 1.62 0.0920 toward Italian luxury brands occasion of apparel by attributes Attractiveness 28.77 27.04 − 3.35 0.0001 Brand name 39.44 22.18 − 16.79 0.0001 Choice of styles 33.86 29.83 − 2.57 0.0090 Colour 32.33 31.20 − 0.87 0.2530 Comfort 33.80 33.16 − 1.54 0.0800 Durability 31.61 32.58 0.19 0.7930 Ease of care 25.29 25.53 0.10 0.9450 Fashionableness 34.34 28.14 − 4.84 0.0001 Good fit 35.23 33.60 − 1.25 0.2000 Good price 12.35 19.39 6.58 0.0001 Quality 38.65 36.88 − 1.38 0.2010 a The Bonferroni inequality was used to determine the critical value of F to be considered as significant the probability should be smaller than 0.04 ( p < 0.004). Mean scores could range from 1 to 49

Table 6.6 presents the results of the 12 additional t-tests that compared both groups’ attitudes toward Japanese apparel on each attribute separately. The results showed that status-seeking teenagers gave significantly higher evaluations than non-status-seeking teenagers to Japanese luxury brand apparel on two of the 12 apparel attributes— fashionableness and brand name. In contrast, non-status-seeking teenagers gave significantly higher evaluations than status-seeking teenagers to good price. The other nine attributes had no significant differences in the responses from the two groups. A t-test was also used to determine the difference between the attitudes of status- seeking teenagers (mean = 24.28) and non-status-seeking teenagers (mean = 25.35) toward Chinese luxury brands apparel. The results indicated that there is no significant difference ( T = 0.49, p = 0.5330) between both groups’ attitudes toward Chinese luxury brand apparel. As a result, H4c was accepted. Table 6.7 illustrates the results of the 12 additionalt-tests that compared both groups’ attitudes toward Chinese luxury brand apparel on each attribute separately. The results showed that status-seeking teenagers gave significantly higher evaluations than non-status-seeking teenagers to Chinese luxury brand apparel on fashionableness; whereas non-status-seeking teenagers gave significantly higher evaluations than status-seeking teenagers to good price. In addition, the other ten attributes had the same overall attitude between both groups. Thus, status-seeking teenagers, overall, had a more positive attitude than non- status-seeking teenagers toward foreign luxury brand apparel, particularly those that are Made in Italy. However, both groups gave the highest evaluations to Italian-made luxury brands. Both groups also gave the lowest evaluations to Chinese luxury brands. 94 I. Phau

Table 6.6 T-test comparison Attributes Status mean Non-status t value Pr> Ta between attitudes of status mean and non-status seeking Appropriate for 28.13 24.88 − 1.32 0.1880 teenagers toward Japanese occasion luxury brands of apparel by Attractiveness 31.87 27.68 − 2.53 0.0120 attributes Brand name 28.00 18.23 − 9.86 0.0001 Choice of styles 30.23 29.28 − 1.44 0.1500 Colour 30.02 29.30 − 1.15 0.2520 Comfort 33.45 32.59 − 0.58 0.5620 Durability 27.45 29.22 0.76 0.4470 Ease of care 27.42 28.12 0.15 0.8790 Fashionableness 34.16 29.67 − 3.48 0.0010 Good fit 32.18 31.11 − 0.81 0.4170 Good price 16.11 27.83 9.20 0.0001 Quality 30.30 27.89 − 1.16 0.2470 a The Bonferroni inequality was used to determine the critical value of F to be considered as significant the probability should be smaller than 0.04 ( p < 0.004). Mean scores could range from 1 to 49

7 Concluding Comments

Overall, status-seeking teenagers were found to have a more positive overall attitude toward foreign luxury brand apparel than local luxury brand apparel, with the exception of Chinese brands. Similar results were obtained for Beaudoin et al. (1998) with fashion leaders instead. It seems that there may be a correlation between fashion leaders and status-seeking consumers’ attitudes toward foreign versus local products as documented by many other previous studies (Goldsmith et al. 2010; Latter et al. 2010; Shukla 2010; Phau and Cheong 2009; Deeter-Schmelz et al. 2000; Goldsmith et al. 2010). The results of this study also shows evidence that status-seeking teenagers are more likely to believe that foreign luxury brand apparel are of better fit, better quality , more fashionable, have a better brand name, and are more appropriate for classy occasions than Australian luxury brand apparel (especially products from Italy and Japan). Although respondents prefer Australian luxury brands to Chinese luxury brands, status-seeking teenagers gave significantly high evaluations on good price to Chinese luxury brands as good value for money. This finding on good price was consistent with those of Phau and Leng (2008), Wong et al. (2008), and Mohamad et al. (2000) on consumer perception of country of origin. Consumers perceived that apparel from developing countries, especially China, is inferior in quality but is compensated for by good price concessions. This, from the total consumer satisfaction and welfare perspective, means there is a trade-off between product quality and price. However, focusing on these attributes is not a good strategy to market luxury or prestige brand apparel. According to previous findings, (e.g. Goldsmith et al. 2010; Mai and Smith 2012; Deeter-Schmelz et al. 2000), the signal of status on fashion goods is 6 “Domestic-Made” or “Foreign-Made” Luxury Brands? 95

Table 6.7 T-test comparison Attributes Status Non-status t value Pr > Ta between status and non-status Mean Mean seeking teenagers’ attitude Appropriate for occasion 23.86 23.65 − 0.53 0.7340 toward Chinese luxury brands of apparel by attributes Attractiveness 29.18 23.15 − 1.94 0.0650 Brand name 13.02 11.80 − 0.65 0.8550 Choice of styles 27.80 26.00 − 1.49 0.1380 Colour 28.88 27.83 − 0.58 0.5350 Comfort 29.23 29.11 − 0.88 0.3870 Durability 23.78 21.56 − 0.64 0.5870 Ease of care 22.98 25.88 1.25 0.2220 Fashionableness 27.70 22.48 − 3.48 0.0001 Good fit 29.38 29.58 − 0.23 0.8780 Good price 22.03 37.98 11.88 0.0001 Quality 17.99 19.56 0.05 0.9590 a The Bonferroni inequality was used to determine the critical value of F to be considered as significant the probability should be smaller than 0.04 ( p < 0.004). Mean scores could range from 1 to 49 that apparel must be more expensive to suggest higher quality or higher status. These intangible aspects are in fact well treasured by consumers. On the other hand, non-status-seeking teenagers reported that they had more positive attitudes toward Australian brands than foreign brands, with regards to ease of care and comfort. However, when compared separately, the results were only significant for luxury brands from China but not for Italian and Japanese luxury brands. When compared to Italian brands, Australian luxury brands have a better price; whereas with Chinese and Japanese produced brands, the value is seen in better fit, more durability, and better quality. The Australian apparel industry should focus its marketing strategy on enhancing the attributes of “fashionableness” and “brand name” of Australian apparel that both status-seeking and non-status-seeking teenagers preferred in foreign apparel. This not only helps enhance the consumer satisfaction for those who purchase Australian apparel, but also increases the societal welfare for the Australian fashion industry. When compared to Italian luxury brand apparel particularly, Australian brands were evaluated as being of poorer quality. Brand name is important in the luxury goods market because status-seeking consumers only purchase products that represent status in the eyes of people who they deem to be significant (e.g. Goldsmith and Clarke 2012; Shukla 2010; Eastman et al. 1999; O’Cass and Frost 2002). Grace and O’Cass (2002) and Mohamad et al. (2000) also determined that status products possess good quality and a good brand name. Undeniably, status-seeking consumers are more likely to buy luxury apparel from countries with a good brand name. With the Australian luxury brand industry still in its infancy, not only is it important to produce stylish and quality products, but also a good branding strategy is necessary in creating the perception of quality. Kapferer (2012) suggests that the notion of luxury is a by-product of historical as well as artistic legacy; it is about building artistic incomparability. Perceptions of uniqueness can therefore be created 96 I. Phau through strong narratives about where the brand came from and the artistic value of its products. However, relatively newer brands can overcome the lack of heritage by emphasising the unique talents of the brand’s craftsmen and the creative value of the product. Newer Australian brands can therefore capitalise on the artistic qualities of their products to create a sense of uniqueness and rarity which would make them more desirable to status-seeking teenagers. Japanese luxury brands were perceived to be slightly superior to Australian luxury brands. Therefore, manufacturers or retailers should place more emphasis on the design, brand name, and quality in order to be more competitive in the Austra- lian luxury garments market especially in direct competition with Japanese brands. Moreover, fashion-conscious consumers have a great impact on a quarter of the world’s luxury goods sales. Therefore, the major concern is the changing market that status-seeking consumers, especially teenagers, are now longing for more fashionable apparel. One other alternative would be to encourage a joint effort with members of the Italian luxury clothing industry, capitalising on the favourable attitudes from the consumers. The Australian textile industry should commence the import of more Italian textiles and designs to reposition its brand name and image in the local luxury market. Another alternative would be to export textiles, especially Australian wool, to Italy to gain association with Italian brand names. This study is not devoid of limitations which form the basis for some future directions that should be considered. First, the construct of ethnocentrism should be incorporated into the study using the same methodology. Previous research has shown that younger Australians exhibit lower consumer ethnocentrism (Fischer and Byron 1997; Patterson and Tai 1991). However, the influence of status consumption is not known. Second, a study of more diverse sub-cultures within the Australian population is needed. In addition, this comparative study between Australia and three foreign countries (Italy, Japan, and China) could be constrained by negative stereotyping. Different foreign countries from different economic backgrounds should be included in future studies to verify whether the results can be generalised. The research paradigm should be expanded beyond multiple country comparisons, given that it is assumed that there might be a connection between fashion leaders and status-seeking consumers. Similar studies should be conducted in future on both fashion leadership and status consumption, as well as be used to prove the relationship of both concepts. Finally, future studies could also be conducted for older segments of status-seeking and non-status-seeking consumers. Age differences may also have vital implications for future marketing strategies.

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Bin Shen, Jaehee Jung, Pui-Sze Chow and Szeman Wong

1 Introduction

Fashion industry has seen much of partnerships between fast fashion and designer fashion brands launching a special co-branded line. This kind of popular strategy of brand development is recognized as “fast fashion co-branding.” For example, H&M, a popular fast fashion brand from Sweden, is highly involved in collaboration with various luxury designer fashion brands. H&M initiated designer collaborations starting with Karl Lagerfeld in 2004. Collaborations in subsequent years include those with Stella McCartney, Viktor & Rolf, Madonna, Roberto Cavalli, Comme des Garcons, Matthew Williamson, Jimmy Choo, Sonia Rykiel, Lanvin, Versace, and Marni. Co-brands of H&M receive high popularity and are always under spotlight. Consumers are willing to queue up for a whole night to buy co- branded items, and the products are usually sold out in a very short time (Fitzsimons 2011; Chilvers 2012). Taking the latest collaboration between Marni for H&M as an example, the whole collection of Marni for H&M was sold out by lunchtime of the first day of opening in London (Milligan 2012). Uniqlo, a Japanese fast fashion brand, had collaborated with the German luxury designer brand Jil Sander for 2

B. Shen () Glorious Sun School of Business and Management, Donghua University, Yan An Road (West) 1882, Shanghai 200051, China e-mail: [email protected] J. Jung Department of Fashion & Apparel Studies, University of Delaware, 304 Alison Hall West, Newark, DE 19716, USA e-mail: [email protected] P.-S. Chow · S. Wong Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong e-mail: [email protected] S. Wong e-mail: [email protected] T.-M. Choi (ed.), Fashion Branding and Consumer Behaviors, 101 International Series on Consumer Science, DOI 10.1007/978-1-4939-0277-4_7, © Springer Science+Business Media New York 2014 102 B. Shen et al. years and their collaborative collections (+ J) were also highly accepted by the market (Kachi 2011). By collaborating with luxury designer fashion brands, the brand equity as well as the image of fast fashion brands is increased (Okonkwo 2007). At the same time, the collaborated designer fashion brands can also get benefits from this co-branding. For example, Lavin, one of the oldest Paris designer brands, received a wider audience appeal from the mass market after expanding its market with new products and retail outlets through co-branding with H&M (Horyn 2010). As illustrated by the above examples, fast fashion co-branding has shown an incredible marketing response and it can create a win-win situation for the brands involved. It is interesting to explore why consumers have this response, as well as what kind of consumer behavior is related to this phenomenon. It is essential for brand owners to understand the effect of branding on consumers’ behavior, particularly for new brands such as fast fashion co-brands. Keller (2001) states that consumers’ brand perceptions are driven by their knowledge and the need for uniqueness towards brand, which are derived from personal experience. Consumers’ need for uniqueness is defined as the trait of pursuing differences relative to others so that it can develop and enhance one’s self-image as well as social image (Tian et al. 2001). A common feature of fast fashion brands and designer fashion brands is that they both provide the trendiest items and create uniqueness in the fashion market: the former by producing scarcity with small quantities (Barnes and Lea-Greenwood 2006) whereas the latter by creating exclusivity with high price (Okonkwo 2007). Thus, consumers of these two types of fashion brands share the same characteristic of having a strong desire for uniqueness. However, according to a marketing report by Labbrand (2011), an Asia-based marketing and brand-consulting firm, fast fashion consumers and designer-label consumers are different in terms of their perception to brand equity and pricing of the brands. After collaboration, fast fashion co-brands attract pur- chases from both consumer groups as the co-branding strategy has brand spillover effect in marketing (Desai and Keller 2002). In other words, co-branding enables one brand to benefit from the “halo of affection” that belongs to another. Walchli (2007) indicates that co-branding should consider not only the good synergy- generating relationship, but also consumer assessment concerning the association between brands. She noticed that all these previous studies concern traditional brands whereas the consumers’ need for uniqueness and perception of fast fashion co-brands are still unknown. As an attempt to bridge such research gap, this chapter empirically examines the relationship between the consumers’ need for uniqueness and purchase perception of fast fashion co-brands. In particular, the research objectives are identified as follows: 1. To examine the difference in the need for uniqueness among consumers of fast fashion brands, designer fashion brands, and fast fashion co-brands; 2. To investigate the impact of such need for uniqueness on purchase perception of fast fashion co-brands. To the best of our knowledge, this is the first study on consumer behavior of fast fashion co-branding. Due to the increasing popularity of co-branding in the fashion 7 Co-branding in Fast Fashion 103 market, it is important to study consumers’ purchase perception of fast fashion co- brands. Our results reflect that there are significant differences in consumers’ need for uniqueness from different types of fashion brands and that their need for uniqueness has an impact on the purchase perception of fast fashion co-brands. This study will also provide managerial insights to the collaborative brands as to how they can attract consumers and select appropriate co-branding partners. This chapter is organized as follows. In Sect. 2, we review the literature in co-branding, need for uniqueness, and purchase perception, as well as present our hypotheses. Section 3 describes our methodology. Results are discussed in Sect. 4. Section 5 concludes the chapter with remarks and managerial implications. Limitations and recommendations for further research are discussed in Sect. 6.

2 Literature Review and Hypothesis Formulation

2.1 Co-branding in Fashion

Park(1996 et) al. define co-branding as “the pairing of two or more branded products (constituent brands) in forming a separate and unique product.” Co-branding between two brands for making a joint effort in a new marketing venture is popular in many industries, particularly in the fashion industry. As an effective strategy of brand development, co-branding facilitates parent brands to access to a broader consumer base as well as to form a new relationship with the clients. The co-brands can attract attention from consumers of both parent brands (Desai and Keller 2002), and a new relationship with these two groups of consumers is then built up (Walchli 2007). Spethmann and Benezra (1994) indicate that co-branding strategy is increasingly appealing to brand owners as a measure to gain more exposure in the market, mitigate the threat from private label brands, and lessen the cost of promotion (since it is shared with the partner brand or brands). It is reported by Simonin and Ruth (1998) that consumers’ attitudes towards co-brands would influence the subsequent consumers’ attitudes towards individual brands that comprise that alliance. Brands and branding are important in fashion business. Okonkwo (2007) points out that a brand name or brand logo attracts consumers to create a relationship with it. A well-known fashion designer name (such as Karl Lagerfeld and Jimmy Choo) is an important branding element that helps form a commercial strategy of the associated brand. Similarly, for fast fashion co-brands, the collaborated luxury designer fashion brand not only is understood as an important and central means of marketing and product differentiation, but it also serves as a constructed idea and lifestyle which the consumers not only desire, but also identify (Ferrero-Regis 2008). A fast fashion co-brand as a new fashion brand is thus able to change consumers’ attitudes regarding its collaborated brands. 104 B. Shen et al.

2.2 Need for Uniqueness

Consumers’ need for uniqueness is grounded by Snyder and Fromkin (1980)’s uniqueness theory. For a person who has a high need for uniqueness, he/she tends to experience positive emotions in the low similarity condition and negative emotions in the high similarity condition, as a result, engages mostly in changes towards dissimilarity relative to others. Tian et al. (2001) classify the need for uniqueness into three types: (1) creative choice counter-conformity, (2) avoidance of similarity, and (3) unpopular choice counter-conformity. For consumers seeking for creative choice counter-conformity, the products they would purchase are those that not only can reflect their uniqueness, but also are accepted by others. Knight and Kim (2007) state that brand names offer the distinguishing attributes, such as unique features, exclusivity and prestige, which appeal to consumers who seek for creative choice counter-conformity. Consumers seeking for avoidance of similarity would select products that are not likely to become too popular so that they can be distinguished from others. On the contrary, consumers seeking for unpopular choice counter-conformity would select products with tastes that are deviated from the group norms. Clothing selection is a uniqueness-seeking behavior (Snyder and Fromkin 1980; Snyder 1992; Workman and Kidd 2000). In the fashion industry, a high degree of uniqueness is the common feature shared by luxury designer fashion brands, fast fashion brand, and fast fashion co-brands; yet they focus on different types of uniqueness according to their industrial practices. Luxury designer fashion brands are usually associated with differentiation, exclusivity, and innovation (Okonkwo 2007). Consumers of luxury designer fashion brands use the brands to classify themselves or to distinguish themselves from others (Vigneron and Johnson 2004). In other words, luxury designer fashion brands are closely related to conspicuous consumption—people’s perceived use of brands in conveying consumer’s social status (Li et al. 2012). From this aspect, luxury designer brands appear to emphasize uniqueness in terms of avoidance of similarity. On the other hand, fast fashion consumption is driven by the desire for newness which is related to creative choice counter-conformity (Barnes and Lea-Greenwood 2010). Fast fashion apparels are produced in small quantities and without replenishment (Barnes and Lea-Greenwood 2006); they are quickly changing and highly accepted by consumers (Sheridan et al. 2006). According to the case study on Zara, a famous fast fashion retailer from Spain, Tokatli (2008) maintains that the need for newness and uniqueness of fast fashion drives the change of the culture from haute couture and ready-to-wear to fast fashion. Fast fashion co-brands combine the strategies adopted by their parent brands. On the one hand, fast fashion co-brands usually exist in the form of limited edition collections which will be discontinued after a period of time (Ferrero-Regis 2008). On the other hand, products of the co-brands, which usually carry the designers’ names, are created by the collaborated designers and emphasize trendiness and newness (Fitzsimons 2011; Milligan 2012). All the aforementioned H&M co-brands are good examples of fast fashion co-brands in which their features are highly matched to the needs for the creative choice counter-conformity and avoidance of similarity. 7 Co-branding in Fast Fashion 105

In light of the focuses on different types of uniqueness by the three types of fashion brands, we develop the following hypothesis: Hypothesis 1 Consumers expect different levels of need for uniqueness from fast fashion brands, luxury designer fashion brands, and fast fashion co-brands.

2.3 Purchase Perception

The willingness of consumers to purchase a product or service reflects their perception of purchase. Yoo et al. (2000) assert that product quality is one of the determi- nant factors for the consumers’ subjective judgment about a brand’s overall value or superiority. Apart from quality, a vast amount of literature shows that purchase decision is significantly affected by consumers’ need for uniqueness of a product or service (e.g., Simonson and Nowlis 2000; Wu et al. 2012). Consumption of luxury goods appears to have a strong social function. The social dimension of luxury value perception refers to the perceived utility that individuals acquire by consuming products or services recognized within their own social group(s); such goods may confer conspicuousness and prestige value, which may significantly affect a consumer’s evaluation and propensity to purchase luxury brands (Wiedman et al. 2007). These results demonstrate the importance of the perceived value of luxury brands with respect to potential purchasing decisions. Possessing products from a designer fashion brand as people’s desire may serve as symbolic markers of group membership (Kim et al. 2010; Vigneron and Johnson 2004). Keller (1993) also finds that uniqueness as a type of brand value positively affects consumer’s willingness to pay premium prices. On the other hand, fast fashion brands have been increasing its share in the fashion market and become more capable of gaining loyal consumers. This might be due to the fact that latest fast fashion apparels are produced in limited quantities that ensure a sort of exclusivity (Barnes and Lea-Greenwood 2010). Apparently, there is no existing literature exploring fast fashion co-brands as an individual type of brands, and how their customers’ needs for uniqueness in their products affect their purchase perception. Adopting mixed strategies from their parent brands, fast fashion co-branding should be able to create synergy. Based on arguments from previous research, we have developed the following hypotheses and depicted our conceptual framework as shown in Fig. 7.1: Hypothesis 2 Consumers having higher need for uniqueness on fast fashion have higher favorable purchase perception of fast fashion co-brand. Hypothesis 3 Consumers having higher need for uniqueness on designer fashion brand have higher favorable purchase perception of fast fashion co-brand. Hypothesis 4 Consumers having higher need for uniqueness on fast fashion co- brand have higher favorable purchase perception of fast fashion co-brand. 106 B. Shen et al.

Fig. 7.1 Conceptual framework of Hypotheses 2–4

3 Methodology

We employed empirical research methodology in the form of survey questionnaire in this study. A self-administered questionnaire was designed to include five sections: (a) the general recognition of fast fashion co-branding, (b) the need for uniqueness in fast fashion brand; (c) the need for uniqueness in designer fashion brand; (d) the need for uniqueness in and purchase perception of fast fashion co- brand; and (e) demographic information. Specifically, the questionnaire items regarding needs for uniqueness in various types of fashion brands and their purchase perception are mainly adapted from previous literature (Knight and Kim 2007; O’ Cass 2000; Tian et al. 2001). New items generated from in-depth interviews with industrialists are also included to reflect their views of factors that affect consumer behaviors of fast fashion co-branding. In the first section of the questionnaire the respondents were asked whether they have the general fast fashion co-branding recognition. By doing so, we could ensure the respondents are suitable for this study. A pilot survey was carried out in order to ensure that the survey questions and research instruments operate well. We employed convenient sampling approach under which the questionnaire survey was conducted in various main shopping areas in Hong Kong, using a random delivery procedure during both weekdays and weekends.

4 Statistical Results

Similar to the sample sizes collected in existing literature in consumer behavior of fashion (Knight and Kim 2007; Liu et al. 2011; Shen et al. 2012), 200 sets of questionnaires were collected, among which 175 were valid. The final sample consisted 7 Co-branding in Fast Fashion 107

Table 7.1 Results of the reliability test Cronbach’s alpha (CR) Construct No. of items Reference(s) 0.76 The need for uniqueness in 5 Knight and Kim 2007; the luxury designer fashion Tian et al. 2001 brand (LD) 0.83 The need for uniqueness in the 5 Knight and Kim 2007; fast fashion brand (FF) Tian et al. 2001 0.87 The need for uniqueness in the 5 Knight and Kim 2007; fast fashion co-brand (CB) Tian et al. 2001 0.91 The purchase perception of the 7 O’ Cass 2000 fast fashion co-branding

Table 7.2 Consumers’ need for uniqueness Luxury designer fashion Luxury designer fashion Fast fashion brand vs. brand vs. fast fashion brand vs. fast fashion fast fashion co-brand brand co-brand Mean 4.38 vs. 3.13 4.38 vs. 4.15 4.15 vs. 3.13 Mean difference 1.253 (1.176) 0.233 (1.288) 1.01 (1.16) t-value 14.0** 2.394* 11.6** Note. Standard deviations are reported in parentheses. **<0.01 *<0.05 tof 58 male and 117 female respondents. About 74.8 % of the respondents were in the age from 19 to 25, 21.7 % were from 26 to 30, and the rest of them were above 30 years old. Reliability test is employed in order to test the internal consistency of the various constructs under investigation. The values of Cronbach’s alpha (CR) for all constructs are greater than 0.7 (see Table 7.1), which imply that the internal consistency of our data is good for further analysis. Next, we compared the differences of the respondents’ need for uniqueness in fast fashion brands, designer fashion brands, and fast fashion co-brands. The results of the paired sample t-test (Bryman and Bell 2007, pp. 347–372) depicted in Table 7.2 provide an evidence to support Hypothesis 1. Specifically, respondents’ need for uniqueness in the three types of brands were significantly different, with that in luxury designer fashion brands the highest (mean = 4.38), followed by fast fashion co-brands (mean = 4.15). Respondents’ need for uniqueness in fast fashion brands was the lowest (mean = 3.13). Next, we conducted linear regression analysis to investigate the proposed relationships between respondents’ need for uniqueness in different types of fashion brands and their purchase perception of fast fashion co-brands. As shown in Table 7.3, Hypotheses 2–4 are all supported. Specifically, there was statistically significant evidence that a higher need for uniqueness in any of the three types of fashion brands leads to a higher purchase perception of the fast fashion co-brands. Comparing the impact of the uniqueness level on purchase perception, we found that respondents’ need for uniqueness in fast fashion co-brands itself had the largest impact on their purchase perception on fast fashion co-brands (Beta = 0.865 in 108 B. Shen et al.

Table 7.3 Regression results for Hypotheses 2–4 Hypothesis R square F-value Beta T-value Sig Hypothesis results Hypothesis 2 0.163 33.64 0.404 5.807 0.000 Supported Hypothesis 3 0.061 11.258 0.247 3.355 0.001 Supported Hypothesis 4 0.748 514.2 0.865 22.67 0.000 Supported

Hypothesis 4), followed by fast fashion brands (Beta = 0.404 in Hypothesis 2). The need for uniqueness in luxury designer brands had the smallest impact among the three types of brands (Beta = 0.247 in Hypothesis 3).

4.1 Discussion of Findings: Consumer Preference, Welfare, and Utility

In, this study the hypothesized theoretical framework comprises two parts. The first part (Hypothesis 1) examines the difference in consumers’ need for uniqueness among three types of associated brands (fast fashion brands, luxury designer fashion brands, and fast fashion co-brands). The second part (Hypotheses 2–4) examines the impact of consumers’ need for uniqueness for each of the three associated brands on purchase perception of fast fashion co-brands. For Hypothesis 1, the statistical results imply that consumers’ needs for uniqueness are significantly different among the three types of associated fashion brands. Comparing the mean scores of the need for uniqueness among these three types of fashion brands, fast fashion brands scored the lowest. Fast fashion brands can be easily and affordably possessed by the consumers and are of comparatively lower quality. Therefore, consumers might feel them as less unique. This explanation is also justified by Wu et al. (2012) that both high price and good quality associate scarce products with the purpose of differentiating them from others, or in other words, the need for uniqueness. By contrast, our results also showed that luxury designer fashion brands scored the highest among the three types of fashion brands. Since luxury designer fashion brand always leads the fashion trend, target consumers with a high need for uniqueness are deemed as the fashion opinion leaders (Goldsmith and Clark 2008; Zheng et al. 2013). Hypotheses 2–4 investigate the impact of consumers’ need for uniqueness on their purchase perception of fast fashion co-brands. Based on the statistical results of Hypotheses 2–4, we find that when consumers make purchase decision on fast fashion co-brands, the need for uniqueness in fast fashion co-branding is the most important when comparing with both parent brands. In view of the two parent brands, consumers’ need for uniqueness in the fast fashion brands is more important than that in the luxury designer fashion brands when they need to make purchase decision on the fast fashion co-brands. As such, from the perspective of the consumers, their level of satisfaction with respect to product uniqueness depends on the type of fashion brands. Thus, how the product uniqueness affects consumer welfare and utility depends on the specific type of fashion brands. 7 Co-branding in Fast Fashion 109

5 Remarks and Managerial Implications

This study explored consumers’ need for uniqueness and purchase perception of fast fashion co-brands. We first investigated the differences in consumers’ need for uniqueness in fast fashion co-brands and their parent brands (namely: fast fashion brands and luxury designer fashion brands). Our empirical results show that consumers have significantly different needs for uniqueness in these types of fashion brands. In addition, our findings on the impact of consumers’ need for uniqueness on purchase perception of fast fashion co-brands provide the following insights for fast fashion co-branding with respect to its business development. First, fast fashion as a host brand should collaborate with a luxury designer fashion brand which induces a high degree of need for uniqueness for their consumers. It is a meaningful implication for co-branding partnership as there must be a strategic purpose behind the co-branding alliance (Beezy 2007; Helmig et al. 2008). Walchli (2007) indicates that consumer assessment concerning the association between collaborative brands in co-branding strategy is largely related to the choice of the strategic partner. Real examples can be found in H&M who collaborated with Karl Lagerfeld and Stella McCartney as an attempt to address consumer’s changing needs and to expose them to luxury fashion in anticipation of “trading up”. This study thus offers a clear picture that consumers’ need for uniqueness on the collaborative brands is an important factor in brand selection for developing fast fashion co-branding. Second, when the strategy of fast fashion co-branding is launched, enhancing the uniqueness level of both parent brands helps attracting more consumers to purchase co-brands. In particular, a fast fashion brand should try harder to increase its uniqueness level for higher consumers’ purchase perception of its co-branded products since it has a larger impact than that of a luxury designer fashion brand. It is especially important if the fast fashion co-brand will run for several seasons. Take + J as an example, Uniqlo should reinforce its own uniqueness through marketing and branding after collaborating with Jil Sander, so that consumers can be attracted to purchase + J repeatedly. Third, to increase consumers’ purchase perception, the most effective way is to improve the uniqueness level of the fast fashion co-brand itself. It can be improved not only by marketing and branding, but also operational strategies such as quick response with small quantities, no replenishment, and higher retail prices (Cachon and Swinney 2011; Chow et al. 2012).

6 Limitations and Recommendations for Further Research

With the adoption of convenience sampling, the findings of the present study should be interpreted with caution as the study sample is quite limited with the size and demographic characteristics. Another limitation is that the data were collected in 110 B. Shen et al.

Hong Kong only; there may be different findings when a similar study is to be conducted in other countries and areas with different cultural backgrounds. For future research, it is interesting to conduct a cross-cultural study (Choi et al. 2008; Jung and Lee 2009; Choi et al. 2011; Liu et al. 2011; Jung and Shen 2011) on the topic. Further research can expand the scope of this study to explore other areas, for instance, the problem of fast fashion co-branding from the supply chain context with issues such as supply chain coordination and incentive alignment schemes between involved brands (Chiu et al. 2011; Chiu et al. 2013; Shen et al. 2013).

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Rong Huang and Emine Sarigöllü

1 Introduction

Brand awareness refers to whether consumers can recall or recognize a brand, or simply whether or not consumers know about a brand (Keller 2008). Brand awareness precedes brand equity. The brand name provides the memory nodes in consumers’ minds (Aaker 1991), and consumers link the brand knowledge to the brand name, which culminates in brand equity (Aaker 1991; Keller 1993). Hence, brand awareness provides learning advantage for the brand (Keller 2008) and influences consumer decision making. Brands that consumers know are more likely to be included in their consideration set (Hoyer and Brown 1990; MacDonald and Sharp 2000). Consumers may use brand awareness as a purchase decision heuristic (Hoyer and Brown 1990; MacDonald and Sharp 2000). Thus, brand awareness is likely to increase brand market performance. Surprisingly, research on brand awareness is scarce. For instance, the influence of brand awareness on decision making is explored using only lab experiments at the individual consumer level (MacDonald and Sharp 2000). The relation between brand awareness and actual market outcome is studied primarily in the context of service industry (Kim and Kim 2005; Kim et al. 2003). Furthermore, the direction of causality between brand awareness and brand market outcome remains unexplored. Finally, the question of how to build and enhance brand awareness has been investigated only partially: While the impact of advertising or distribution intensity on brand awareness was studied, the impact of price promotions was overlooked, with the exception of two studies with conflicting findings (Srinivasan et al. 2008; Yoo et al. 2000).

R. Huang () School of International Business Administration, Shanghai University of Finance and Economics, 777 Guoding Road, 200433 Shanghai, China e-mail: [email protected] E. Sarigöllü Faculty of Management, McGill University, 1001 Sherbrooke St. West, Montreal, QC H3A1G5, Canada e-mail: [email protected] T.-M. Choi (ed.), Fashion Branding and Consumer Behaviors, 113 International Series on Consumer Science, DOI 10.1007/978-1-4939-0277-4_8, © Springer Science+Business Media New York 2014 114 R. Huang and E. Sarigöllü

The current research contributes to literature on brand awareness in three ways. First, it provides a comprehensive study of the relationship between brand awareness and market outcome. In so doing, it addresses marketing’s accountability issues (Webster et al. 2003). Specifically, by using both correlational and causal analysis, the current study relates brand awareness to several real market outcomes, including sales and brand market share. Second, this research links brand awareness to overall brand equity, using both customer mindset and product market outcome measures of brand equity (Keller and Lehmann 2003). Although previous research demonstrates a positive association between brand awareness and customer mindset brand equity (Kim and Kum 2004; Yoo and Donthu 2001; Yoo et al. 2000), this finding was based solely on survey data. In contrast, the present study utilizes real market time-series data. In addition, this research also explores the association between brand awareness and several brand equity market outcome measures, including revenue premium, share premium, and price premium. Finally, the present study investigates the association between marketing mix elements and brand awareness. Specifically, this study examines price promotion’s impact on brand awareness, shedding light on inconsistent results in extant literature. The next section reviews literature on brand awareness’s relationship with market outcome, brand equity, and marketing mix elements. The latter sections propose research hypotheses, methodology, and results as well as a discussion of implications and future research directions.

2 Literature Review

2.1 Association Between Brand Awareness and Market Outcome

Brand awareness significantly impacts consumer decision making; consumers generally use brand awareness as a decision heuristic. A known brand has a much better chance of being chosen by consumers over an unknown brand (Hoyer and Brown 1990). This well-known brand likely performs better in the marketplace compared to a lesser known brand. A recent study of consumers’ incidental encounter of brands in their daily life indicates that the frequency of exposure to brands significantly enhances the probability of the brand being chosen, even if consumers are not aware of such exposure (Ferraro et al. 2009). fMRI studies indicate that familiar brands have better information retrieval in brain areas than unfamiliar brands (Esch et al. 2012). Table 8.1 provides a literature overview on the relationship between brand awareness and market outcome. In general, the literature indicates a positive relationship between the two. For instance, Kim et al. (2003) find brand awareness positively associates with sales in the hotel industry. Silverman et al. (1999) find a weak correlation between brand awareness and market outcome (as measured by sales or brand valuations by Financial World), however, this could be due to a sampling error. The respondents (students) in the study, who are familiar with well-known corporate brands 8 How Brand Awareness Relates to Market Outcome, Brand Equity… 115

Table 8.1 Extant research regarding brand awareness and market outcome Market outcome Industry/product Findings category Baldauf et al. (2003) Profit sales Tile Brand awareness is antecedent of brand profitability and sales Homburg et al. (2010) Sales Cross-industry Brand awareness impacts study market performance positively Kim et al. (2003) Sales Hotel industry Brand awareness has a positive relationship to market performance. Significant differences in brand awareness are found between high and low market performance hotels Kim and Kum (2004) Sales Restaurant Brand awareness has a positive relationship to market performance Kim and Kim (2005) Sales Hotel restaurant Brand awareness has a positive relationship to market performance Krasnikov et al. (2009) Cash flow, Tobin’s Cross industry The stock (i.e., total number) q, return on of brand-association trade- assets, stock marks in period t increases returns and cash- a firm’s cash flow, Tobin’s flow variability q, return on assets, and stock returns and reduces their cash-flow variability in period t + 1 Rego et al. (2009) Firm risk Cross industry Customer based brand equity (including brand awareness) predicts firm risks and protects firm from unsystematic risks Silverman et al. (1999) Sales brand Brands valuated by Brand awareness has a weak valuation financial world correlation to sales and brand valuations Srinivasan et al. (2008) Sales Consumer-pack- Brand awareness explains aged goods 3 % of the variations in sales Tolba and Hassan (2009) Sales Automobile Brand awareness and familiarity are positively associated with brand market performance such as, GE or Cisco, are not necessarily customers of those brands. High corporate brand awareness does not necessarily translate directly into sales. In the B2B context, Homburg et al. (2010) found a significant positive relationship between brand awareness and market performance. Utilizing brand trademark as indicator of brands’ effort to build brand awareness and associations, Krasnikov et al. (2009) identified a 116 R. Huang and E. Sarigöllü positive relationship between a firm’s financial performance and its total number of associations related to the trademark. Tolba and Hassan (2009) identified a positive association between brand awareness and familiarity and brand market performance. The literature linking brand awareness to market outcome is limited and lacks external generalizability. Most studies are examining the service industry (Kim and Kim 2005; Kim et al. 2003; Kim and Kim 2004) and principally rely on perceptual data from surveys or experiments, with the exception of Srinivasan et al. (2008). Furthermore, previous research typically measures brand market outcome in terms of sales. Only Silverman et al. (1999) consider brand equity as a market outcome. Fi- nally, the direction of causality between brand awareness and brand market outcome has not been explicitly explored. Theoretically, previous studies treat brand awareness as an antecedent to brand market outcome (Keller and Lehmann 2003). How- ever, in product categories involving low financial risk and little time investment for purchase (e.g., convenience goods), consumers may not necessarily go through the “cognition–affection–action” procedure (Mowen and Minor 2001). Other factors, such as the shopping environment, product placement, and on-the-spot promotion, are likely to influence the decision to purchase and consequently, market outcome. Consumers’ purchase and subsequent usage experience may predict brand awareness better, rather than the vice versa (Olshavsky and Granbois 1979). In fact, they may not even need brand awareness prior to purchase. Previous empirical research does not investigate a causal relationship between brand awareness and brand market outcome; instead, these studies contend with only correlational association (e.g., Baldauf et al. 2003; Kim and Kim 2005; Kim et al. 2003; Silverman et al. 1999). One exception is Baldauf et al. (2003) study which finds brand awareness is an antecedent to brand market outcome (measured as profitability and sales). However, they do not explicitly test for the causality relationship between brand awareness and market outcome. Their study does not reveal whether brand awareness predicts brand market outcome or brand market outcome improves brand awareness. The causality relationship between brand awareness and brand performance requires empirical confirmation, and the current research takes on this challenge. The following hypothesis advances the extant theory (Keller and Lehmann 2003). H1: Brand awareness predicts product market performance.

2.2 Association Between Brand Awareness and Overall Brand Equity

Brand equity measures are generally classified into three subsets: customer mindset measures, brand performance measures, and shareholder value measures (Keller and Lehman 2003). Customer mindset measures gauge customers’ general attitude toward a brand and include two important components: brand awareness and brand association. Brand association refers to any brand knowledge relating to the brand in the customer’s mind. This knowledge represents overall brand equity in the customer ’s mind. The following discussion considers customer mindset brand equity as synonymous to brand association. The second group of brand equity 8 How Brand Awareness Relates to Market Outcome, Brand Equity… 117

measures, called product market performance measures, assesses the brand market performance resulting from customer-mindset measures and include dollar sales, volume sales, revenue premium, price premium, volume premium, and share premium. Finally, firm-level performance measures assess the value created by the brand to the overall corporation. The current study examines the association of brand awareness with both customer mindset and product market outcome measures. Previous research finds a positive association between brand awareness and overall customer mindset brand equity (Kim and Kum 2004; Yoo and Donthu 2001; Yoo et al. 2000), with the exception of Gil et al. (2007)’s work. These past studies generally treat brand awareness as a component of overall brand equity and suffer a few shortcomings. Some past studies consider brand awareness and brand associations as a joint dimension, causing difficulty in untangling the effect of brand awareness from brand association (e.g., Gil et al. 2007; Yoo et al. 2000). Furthermore, past studies use only survey research to explore the relationship between brand awareness and mindset brand equity, calling their external generalizability into question. In contrast, the present study uses real time-series dataset including market outcome metrics, brand equity, and marketing mix information for 11 brands of consumer-packaged goods over a period of 3 years. In addition to mindset measures of brand equity, the current research also considers market outcome measures, including revenue premium, share premium, and price premium, and explores their association with brand awareness.

2.3 Marketing Mix Elements and Brand Awareness

Past research does not investigate fully the question of how to build and enhance brand awareness. While most research focuses on advertising’s or distribution intensity’s impact on brand awareness, only two studies consider price promotion; but they produce inconsistent findings (see below). The current study explores how to build and enhance brand awareness through marketing mix elements. Advertising Advertising creates and enhances brand awareness by exposing brands to customers (Aaker 1991; Batra et al. 1995; Keller 1993; Rossiter and Percy 1987; Yoo et al. 2000). Advertising also increases the brand’s likelihood of being included in consumers’ consideration set, thereby improving market performance of the brand (Krishnan and Chakravarti 1993). Brand association (brand awareness) positively relates to advertising expenditure invested in the brand (Yoo et al. 2000). In summary, evidence indicates a positive relationship between advertising expenditure and brand awareness. However, the evidence is largely based on consumer perceptions obtained through either surveys or laboratory experiments, thus its external generalizability is questionable. The present study addresses this deficiency by validating previous research findings on real market data. The present work therefore tests the following hypothesis in keeping with previous literature: H2: Advertising positively effects brand awareness. Distribution Anything causing exposure of a brand to consumers contributes to the establishment of brand awareness (Keller 2008). Repeat brand exposure in 118 R. Huang and E. Sarigöllü stores improves consumers’ ability to recognize and recall the brand. In addition, since stores organize products by categories, consumers gain exposure to brands by category. The store environment naturally facilitates the linkage between brand and the related product category. Therefore, distribution helps to establish brand and product category linkages. Distribution (shelf visibility) alone generates brand awareness and trial for frequently purchased products (Smith and Park 1992). Trials provide consumers with personal experience of products; and in turn, consumers’ usage experience further improves brand awareness. Previous studies confirm a positive association between brand awareness and distribution intensity (Yoo et al. 2000; Srivinasan et al. 2008). Keeping with previous research, the present work hypothesizes the following relationship: H3: Distribution positively affects brand awareness. Price Promotion Price promotions induce brand switchers and create product trials. Such product experiences enhance brand awareness (Keller 2008). Only a few researchers empirically explore the association between brand awareness and price promotions, and their findings are inconsistent. Yoo et al. (2000) find a negative relationship between price promotion and brand awareness. However, Sriniva- san et al. (2008) identify a positive relationship between brand awareness and price promotion, as well as advertising and distribution. Contradictory findings may be due to the use of different brand awareness measures and different research contexts in two studies. While Yoo et al. (2000) jointly measure brand awareness and brand association for durable goods, Srinivansan et al. (2008) assess pure brand awareness (e.g., whether customers know the brand) for convenience goods. The current study measures brand awareness, by asking whether customers know the brand and tests the hypothesis: H4: Price promotion positively affects brand awareness. Price Although past literature finds a positive association between price level and perceived quality (Tellis and Wernerfelt 1987; Yoo et al. 2000), the relationship between price and brand awareness remains unexplored. On one hand consumers may use high price as a quality signal to achieve decision efficiency, but on the other hand a low-priced product may offer consumers more value. Hence, “consumers might be equally aware of both the high-priced product and the low-priced product” (Yoo et al. 2000, p. 199). This research is an initial attempt to explore the relationship between price and brand awareness.

3 Method

3.1 Data

This study’s data are gathered from several sources. A consumer-packaged goods company provided the brand awareness and brand equity data. This company tracked 11 important brands in a consumer-packaged good for household use in the USA. The sales revenue of the 11 brands constitutes around 90 % of the total category 8 How Brand Awareness Relates to Market Outcome, Brand Equity… 119 sales in the USA during the data collection period, from January 2004 to December 2006. This company conducted a weekly equity scan survey with 75 samples per week and summarized monthly. Respondents were recruited from a panel from one of the company’s lead suppliers. The company calculated and tracked the overall brand equity every half year from 2004 to 2006. Information on the four marketing mix elements (advertising, price, price promotion, and distribution intensity) for the same 11 brands is obtained from Information Resources, Inc. (IRI) and TNS media intelligence for the same period (2004–2006). To match with the customer mindset brand equity measures, the marketing mix data also was measured every half year.

3.2 Operationalization of Variables

Brand Awareness The current study measures brand awareness by asking respondents: “Have you ever heard of or seen Brand X?” for each of the 11 brands. The percentage of respondents who checked “yes” for a brand provides the overall measure of brand awareness. Customer Mindset Brand Equity Keller’s (2001) findings constitute the theoretical background of the customer mindset brand equity measures. The current research considers four types of brand equity measures; namely, brand performance, brand image, brand judgment, and brand feelings. Brand performance, image, and judgment are each measured by nine items. Brand feelings are measured by ten items. Each item describes how a customer might feel/think about a brand. For instance, the brand image items include, “allows me to present my family at their very best,” “helps me to always make a good impression with my appearance,” “is currently a leading brand,” “a brand I grew up with,” “a family favorite for years,” “a brand my mother used,” “has been a leading brand in this category for years,” “is dependable and trustworthy,” and “will be a leading brand in the future.” The brand judgment items include: “makes life easier,” “makes the usage experience more en- joyable than I would expect,” “helps me feel in control in the process,” and “makes me feel confident.”. In summary, brand image and performance constructs inquire about brand meaning and brand feelings; and brand judgment constructs assess response based on brand meaning (Keller 2001). Cronbach’s alpha statistic applied to these proportions (averages) shows excellent internal consistency, exceeding 0.98 for each construct. The questionnaire lists all the items and the 11 brands, and asks respondents to check the items that describe how they feel or think about a certain brand. Respon- dents only consider the brands they know. Hence, the percentage of respondents who check “yes,” out of all the respondents who know the brand, constitutes the measure of the brand’s performance, image, judgment, and feelings. The average ratings of all statements indicate the overall brand equity. In general, the four constructs identify the major brand associations in customers’ minds. Market Outcome Measures Brand sales and market share gauge the market outcome. 120 R. Huang and E. Sarigöllü

Table 8.2 Definition of market performance variables and data source Definitions of variables Variable Definition Source Price Net selling price per unit volume IRI Brand volume Volume of the brand sold IRI Price premium charged Brand’s price—private label’s price IRI Percentage market share (Brand’s unit volume sold)/(category’s unit volume sold) IRI Market share premium Brand’s market share—private label’s market share IRI Volume premium Brand’s unit volume—private label’s unit volume IRI Sales Dollar sales of the brand IRI Revenue premium (Brand’s unit volume × brand’s net price per unit vol- IRI ume)—( private label’s unit volume × private label’s net price per unit volume) Distribution ACV IRI Price promotion Percent of brand’s dollar sales made on a price promotion IRI Advertising Total advertising expenditure (millions of dollars) across TNS ten media, computed by monitoring advertisements in each medium/program and applying a relevant rate to each advertisement

Brand Market Performance and Brand Equity This research considers several measures of brand market performance; namely, revenue premium (Ailawadi et al. 2003), price premium (Bello and Holbrook 1995; Holbrook 1992), volume premium (Ailawadi et al. 2003), and share premium (Ailawadi et al. 2003). Table 8.2 provides descriptions of these variables and their respective data sources. As the principal performance measure, the current study employs revenue premium (Ailawadi et al. 2003), because it offers a more complete view than other brand market performance measures. Other measures, such as market share or price premium may be misleading. For instance, a brand may obtain a big market share due to a deep price cut or brand price premium may represent only a small market segment. However, revenue premium considers both the price and sales of a brand. Revenue premium considers competitors’ performance which symbolizes the brand’s strength in the marketplace relative to competitors. Ailawadi et al. (2003) confirm this measure’s reliability and validity. Revenue premium is a convenient method for computing brand equity since the necessary data readily are available. A potential shortcoming of the revenue premium measure is the requirement of a private label as a benchmark. However, it is not a concern here, because our dataset includes private labels. Information on Private Label Since price premium, market share premium, and volume premium are measured relative to the private label, basic information on the private label is provided in Table 8.3. While some stores might carry multilevels of private labels, all private labels in this product category are grouped together to calculate the average price and distribution intensity. The sales value and sales volume are the total value of all private labels in this product category. The average price of private label is around US$ 0.47 per unit volume with a very small variance. The average net price of the branded products is US$ 0.90. The 8 How Brand Awareness Relates to Market Outcome, Brand Equity… 121

Table 8.3 Descriptive information of private label Variable Mean Std. dev. Min Max Variance Net price (US$/ 0.47 0.009 0.46 0.49 0.00009 unit volume) Distribution 84.7 6.4 70.9 89.6 41.2 intensity (ACV) Market share in 2.5 0.14 2.3 2.7 0.02 dollar value (%) Sales in dollars 43,518,711.7 3,174,651.3 38,755,170 48,203,700 1.00784E13 private label’s distribution intensity is high with an average all commodity volume (ACV) percentage around 85 %, which is higher than some branded products in the dataset. Since a private label generally carries the retailer’s name, the distribution intensity reflects a retailer’s tendency to promote the private label. The average market share of the private label is around 2.5 % which is higher than some national brands’ shares. Finally, as the private label’s market position developed, its dollar market share grew 19 % and sales grew 24 % from 2004 to 2006. By comparison during this period of time, the entire category grew only about 5 % in total market dollar sales. Marketing Mix Elements This research adopts the standard operationalization of marketing mix variables. Advertising is measured as brand’s advertising expenditure from TNS media intelligence. Price, price promotion, and distribution data are obtained from Information Resources, Inc. (IRI). Average regular price (e.g., the non-promotion price) measures the price. Percentage of sales made on price promotion assesses price promotion. Finally, the average percentage of ACV measures distribution intensity.

4 Findings

4.1 Descriptive Statistics of Brand Awareness

Table 8.4 summarizes descriptive information on brand awareness. The average brand awareness of the overall dataset is 76 %, with a minimum value of 38 % and a maximum value of 96 %. Brand I has the highest brand awareness at 96 %, while Brand K has the lowest (42 %). Interestingly, Brand D has the lowest market share and sales, but the product has moderate brand awareness (67 %). The standard deviation of each brand is relatively small (a range of 0.5–2.6 %), indicating that brand awareness is rather stable, at least in the time interval covered by the data. 122 R. Huang and E. Sarigöllü

Table 8.4 Brand awareness: descriptive analysis Brand N Mean Std. dev. Min Max Variance (%) overall 66 76 13.50 38 96 183.7 A 6 72 1.97 69 75 3.9 B 6 76.8 1.30 75 79 1.7 C 6 89.2 1.47 88 91 2.2 D 6 66.7 1.63 65 69 2.7 E 6 73.2 2.22 71 76 4.9 F 6 84.5 1.05 83 86 1.1 G 6 75.5 1.40 74 77 2.0 H 6 72.6 1.90 71 76 3.6 I 6 95.5 0.54 95 96 0.3 J 6 84.2 2.20 82 87 4.8 K 6 42.2 2.60 38 45 6.8

4.2 Change in Brand Awareness over Time

Table 8.5 provides a closer look at changes in brand awareness over the 3 years covered by the dataset. In general, very little change occurs in awareness of the ten brands. Only Brand K exhibits an 18 % increase in awareness over time. This change may be due to increased investment in promotions (see further). The median percentage change in brand awareness is zero.

4.3 Correlation of Brand Awareness and Market Outcome

Overall, the results indicate a positive correlation between brand awareness and brand market outcome (Table 8.6). Specifically, the correlation between brand awareness and sales is 0.50 ( p < 0.001). And the correlation between brand awareness and market share is also 0.50 ( p < 0.001). These findings confirm previous literature; brand awareness has a positive relationship with the brand’s performance in the marketplace (e.g., Kim et al. 2003). The present study also explores the relation between brand awareness and brand equity and confirms a positive association between them; the correlation between brand awareness and customer mindset brand equity is 0.56, and the correlation between brand awareness and the revenue premium brand equity is 0.50. The correlation of brand awareness with sales is a bit lower than its correlation with customer mindset. Similarly, brand awareness’s correlation with brand performance equity measure, i.e., revenue premium, is also lower than its correlation with customer mindset. These findings suggest brand awareness closely relates to customers’ overall attitude toward a brand. Since both brand awareness and customer mindset measures assess customer mindset directly, the finding that brand awareness has higher correlation with customer mindset equity as opposed to other market outcome measures is reasonable. 8 How Brand Awareness Relates to Market Outcome, Brand Equity… 123

Table 8.5 Change in brand Brand Percentage change in brand awareness over time awareness (%) A 4 B 0 C − 3 D 6 E − 5 F 1 G 3 H − 7 I 0 J − 5 K 18 Median of percentage change in 0 brand equity measure

Table 8.6 Correlation of Brand awareness customer mindset measures Customer mindset brand equity 0.56*** and other product market Price premium 0.49* performance measure Volume premium 0.33** Revenue premium 0.50*** Market share 0.50*** Share premium 0.50*** Sales 0.50*** *p < 0.05; **p < 0.01; ***p < 0.0001

Finally, the current work finds that price premium relates positively to brand awareness ( r = 0.49, p < 0.001). Price premium measures brand equity. As proposed, a high-equity brand is able to charge a higher price than competitors, ceteris paribus (Bello and Holbrook 1995; Holbrook 1992). This finding confirms a positive relation between brand awareness and overall market outcome of brand equity.

4.4 Brand Awareness as Antecedent of Market Outcome

The present study also tests whether brand awareness is an antecedent of market outcome. That is, the brand awareness measure of the previous time periods is used to forecast current revenue premium. And vice-versa, the revenue premium of the previous periods is used to predict current brand awareness. The first five time periods in the dataset are used to obtain the parameter estimates in regression, and then these parameter estimates predict the value in time 6. Tables 8.7 and 8.8 present the results. The model is significant and produces better fit when brand awareness is regressed on the lagged revenue premium (estimated on 124 R. Huang and E. Sarigöllü

Table 8.7 Regress brand awareness on lag values of revenue premium Dependent variable Model fit Parameter Estimate P Value Brand awareness R-square = 0.27 Intercept 0.72 < 0.0001 F = 15.20 ( p = 0.02, d.f. = 1) Lag revenue 3.31E−10 < 0.0003 premium R-square = 0.27 Intercept 0.72 < 0.0001 F = 11.5 ( p = 0.009, d.f. = 1) Lag 2 revenue 3.30E−10 0.0019 premium R-square = 0.30 Intercept 0.71 < 0.0001 F = 8.5 ( p = 0.008, d.f. = 1) Lag 3 revenue 3.48E−10 < 0.0085 premium R-square = 0.29 Intercept 0.71 < 0.0001 F = 3.8 ( p = 0.08, d.f. = 1) Lag 4 revenue 3.49E−10 0.085 premium d.f. degrees of freedom

Table 8.8 Regress revenue premium on lag values of brand awareness Dependent variable Model fit Parameter Estimate P Value Revenue premium R-square = 0.23 Intercept − 458,289,972 0.0065 F = 13.0 ( p = 0.0008, Lag customer mind- 751,318,629 0.0008 d.f. = 1) set measure R-square = 0.22 Intercept − 434,177,244 0.0276 F = 8.7 ( p = 0.006, d.f. = 1) Lag 2 customer 715,717,222 0.0006 mindset measure R-square = 0.22 Intercept − 420,437,296 0.08 F = 5.5 ( p = 0.03, d.f. = 1) Lag 3 customer 700,747,400 0.03 mindset measure R-square = 0.18 Intercept − 378,845,788 0.31 F = 2.0 ( p = 0.19, d.f. = 1) Lag 4 customer 645,384,682 0.19 mindset measure d.f. degrees of freedom the previous five periods). That is, the lagged revenue premium is a better predic- tor of brand awareness than vice versa. This finding conflicts the extant literature which suggests that brand awareness is antecedent of product market outcome. This finding will be discussed later. This study further investigates the predictive relationship between brand awareness and market outcome by cross prediction. The revenue premiums of the last one, two, and three time periods predict current brand awareness. Similarly, brand awareness from the last one, two, and three time periods predict the current revenue premium. Then, the mean absolute percent error (MAPE) compares prediction accuracy and provides a unit-free scale of evaluation (Farnum and Stanton 1989). Specifically, each absolute forecasting error converts into a percentage error relative to the corresponding actual value. The average magnitude of all resulting percentages is the final measure of the MAPE, as expressed in the following equation: 8 How Brand Awareness Relates to Market Outcome, Brand Equity… 125

Table 8.9 MAPE measures of prediction accuracy MAPE Lag brand awareness to predict current revenue premium 0.62 Lag revenue premium to predict current brand awareness 0.52 Lag 2 brand awareness to predict revenue premium 0.60 Lag 2 revenue premium to predict current brand awareness 0.52 Lag 3 brand awareness to predict current revenue premium 0.65 Lag 3 revenue premium to predict brand awareness 0.52

n e ∑ t t =1 Yt (8.1) MAPE = n

Where, et is the forecast error in time period t; Yt is the actual value in time period t; n is the number of forecast observations in the estimation period. Since this research considers two dependent variables (i.e., customer mindset and revenue premium), the standardized deviation of the two measurements, respectively, constitute Yt. As Table 8.9 illustrates, prediction accuracy of the revenue premium (0.52) is better than brand awareness. If the brand awareness measure from a previous time period forecasts the current revenue premium value, the MAPE is 0.62. However, if the revenue premium measure from the previous time period predicts the current brand awareness, the MAPE is 0.52. Findings from regression and cross-prediction analyses consistently demonstrate that product market performance predicts brand awareness better than vice versa. These findings do not support H1.

4.5 Impact of Marketing Mix Elements on Brand Awareness

Regression is used to explore the association between marketing mix elements and brand awareness. Table 8.10 summarizes the analysis results between brand awareness and marketing mix variables. The overall regression is significant ( p < 0.001) and the model explains 68 % of the data’s variance (R-square = 0.68). Three independent variables, distribution, price promotion, and price, significantly predict brand awareness, confirming H3 and H4. The findings, also confirmed by a step- wise regression, support the proposition that a more intensive brand distribution leads to greater awareness (e.g., Srinivasan et al. 2008; Yoo et al. 2000). Similarly, the higher a brand spends on price promotion, the greater the awareness. Finally, the higher a brand’s price, the greater is the awareness. Surprisingly, the results indicate advertising does not predict brand awareness; hence, this finding does not support H2. This finding contradicts theoretical literature, thus requires an explanation. The product category in this study is mature 126 R. Huang and E. Sarigöllü

Table 8.10 Regression of brand awareness on marketing mix elements Brand awareness as dependent variable R-square = 0.68 F = 26.22 ( p < 0.0001, d.f. = 5) Regression coefficient Independent variables Unstandardized Standardized Intercept 0.026 (0.08) 0 Advertising expenditure 0.000002 (0.000) 0.13 Distribution 0.004 (0.001)*** 0.43 Price 0.21 (0.04)*** 0.50 Price promotion 0.02 (0.003)*** 0.42 Time 0.004 (0.006) 0.05 The standard errors are in parentheses; d.f. degrees of freedom *p < 0.05; **p < 0.01; ***p < 0.0001 and includes established brands with high awareness. Thus, increasing advertising is unlikely to improve their already high brand awareness significantly. Typically, market share leaders have higher advertising expenditures and may experience di- minishing returns unless their advertising provides some unique/new information about products, such as new product development.

5 Discussion

The current research demonstrates a positive association between brand awareness and consumer preference for the brand, as well as brand market outcome. This study provides important implications for managers. First, it provides empirical evidence that brand awareness is important for consumer decision making. Second, it offers insights on the nature of the relationship between brand awareness and market outcome. Finally, it provides direction on how to build and enhance brand awareness. This research for the first time tests the direction of causality between brand awareness and market outcome. Brand equity literature (e.g., brand value chain model) proposes brand awareness as an antecedent of brand market outcome. However, the current research finds evidence to the contrary; market outcome is an antecedent of brand awareness. Specifically, revenue premium predicts brand awareness better than brand awareness predicts revenue premium. This finding is in the context of frequently purchased consumer-packaged goods involving little financial or social risk. Consumers generally do not invest much time and effort searching for product information, comparing brands and making purchase decisions. Thus, consumers do not seem to go through the process of “cognition  affect  behavior” when they make a purchase among such products. Instead, they follow the awareness  trial  reinforcement sequence of Ehrenberg (1974; originally proposed for the effect of advertising). This finding, also in the context of brand equity area, further confirms the general belief that consumers rarely follow the cognition–affection–behavior 8 How Brand Awareness Relates to Market Outcome, Brand Equity… 127 sequence.1 Sometimes, consumers do not go through an elaborate decision-making process before purchasing (Olshavsky and Granbois 1979), instead, they may follow the “beliefs-behavior-affect” hierarchy (Mowen and Minor 2001). This finding implies that purchase does not necessarily require brand awareness prior to a consumer’s visit to the distribution outlet, at least for frequently purchased consumer-packaged goods. The purchase decision could be made right on the spot. Even when consumers do not know the brands before their visit to the store, shelf visibility may induce purchase behavior. This behavior supports the proposition that consumers may form behavior directly given situational or environmental conditions, such as physical environment (Mowen and Minor 2001; Nord and Peter 1980). Product usage experiences enhance brand awareness. In other words, the more people buy a product, the higher their brand awareness for the product. The current regression results also corroborate the significance attributed to distribution by cross-prediction analysis, where distribution turns out to be the most important element establishing brand awareness. The current findings have important implications for enhancement of brand awareness and brand market performance. Brand awareness includes brand recognition and brand recall. Brand recognition refers to whether consumers are able to recognize the brand. Brand recall means consumers can recall a certain brand during their decision-making process without priming. Brand recognition requires consumers to know the brand prior to their purchase. Brand recall assumes that consumers go through decision-making process prior to the purchase. Previous studies about brand awareness focus on enhancing brand recognition or brand recall by utilizing advertising, public relation, or promotion. These studies propose what consumers think about brands during their decision-making process. On the contrary, the current study suggests that brand awareness is driven by consumers’ brand purchase and usage. Accordingly, brand awareness creation and enhancement can be accomplished by utilizing various on-the-spot factors in retail outlets. Distribution and in-store promotion induce consumers to purchase the brand in the first place. Managers should design and implement marketing activities, such as distribution, promotion, and personal selling to stimulate the purchase behavior directly. Firstly, increasing distribution intensity is imperative; managers should utilize the distribution element to its full potential in order to improve brand awareness and brand market performance, especially for brands with relatively low awareness and tight advertising budgets. In addition, improving the product placement quality in retail outlets increases the odds that consumers will choose the brand. Attractive brand packaging aides display effectiveness. Clear and easy-to-read product instructions and explanations support this recommendation. Both price and non-price promotions help to generate brand sales which in turn induce brand usage experience and thus increase brand awareness. At the same time, managers are advised to treat the brand-building process differently according to different product category. On one hand, brand awareness is essentially important for fashion brands. Jung and Sung (2008) found that brand awareness of fashion brands will increase purchase

1 The authors thank a referee for providing suggestions for the theory background for discussion. 128 R. Huang and E. Sarigöllü

intention positively. On the other hand, for fashion products (e.g., apparels), consumers may have to go through the “cognition  affect  behavior” process to make purchase decision. For instance, Kim (2012) investigated the three fashion- brand experience, namely, cognitive, affective, and behavioral experience. This found that brand awareness does not predict brand feelings and brand judgment for the brand of Polo, but brand awareness impacts brand judgment positively for the brand of Giordano. Therefore, mere presence in the distribution outlets is not enough for consumers to purchase fashion brands. Managers are advised to build brand awareness for their fashion brands before the consumers’ purchase decision. The development of social networking service such as Twitter or Facebook provides ample opportunities for managers to enhance brand awareness. Secondly, managers are advised to use price promotions to create brand awareness. Specifically, price promotion encourages brand switching and provides consumers with an incentive to try those brands which they would not purchase other- wise at full price. The price promotion induces brand usage and creates awareness. A final managerial implication involves sustaining brand awareness. High brand awareness remained rather stable over the time interval covered by the data (with the exception of Brand H and K, which are addressed later). This finding is consistent with that of the Boston Consulting Group study where the leading brands in 19 out of 22 product categories were the same in 1985 as in 1925 (Aaker 1991). Fur- thermore, well-established brands are able to benefit from the awareness they have created for a reasonably long time, even if advertising support drops (Aaker 1991). Of the two brands whose brand awareness is less stable, Brand H’s awareness declines whereas Brand K’s improves. Brand H’s distribution intensity decreases from 77 to 59 % over time, which may account for the decrease in its brand awareness. As for Brand K, the increase in brand awareness accompanies an investment in promotions over time. As promotion generates product experience, brand awareness might be enhanced due to product usage experience. This study’s product category is mature with several already well-established brands. Improving awareness is difficult due to the saturation effect. Hence, price promotions should be used with caution. Frequent price promotions may negatively influence overall brand equity (Angel and Manuel 2005; Darke and Chung 2005; Yoo et al. 2000) and perceived brand quality. Furthermore, price promotions may also decrease the internal reference price in the customer’s mind. Hence, brands with very high brand awareness should implement price promotions prudently. Marketing managers should focus on improving the brand’s distribution intensity, which is likely to produce positive synergies with advertising and/or previous usage experience.

6 Conclusions and Limitations

This study provides an in-depth investigation of brand awareness, a scarcely re- searched topic, and makes three contributions. First, it explores the relation between brand awareness and desirable market outcomes, such as sales and market share, and finds a positive association. 8 How Brand Awareness Relates to Market Outcome, Brand Equity… 129

Second, it investigates the link between brand awareness and overall brand equity (which also relates to consumer value and welfare). By using the customer mindset and the product market outcome measures, this study demonstrates a positive association between brand awareness, customer mindset brand equity, and brand equity market outcome measures, including revenue premium, share premium, and price premium. The current findings support the importance of brand awareness on market outcome metrics for low involvement, consumer-packaged goods and generalize the past literature beyond the context of the service industry and survey- based methodology. However, this research also finds that consumers’ brand usage experience contributes more to brand awareness than vice versa. Experience precedes awareness in some cases. These findings are important for us to better understand how brand awareness relates to consumer experience which in turns reflects consumer welfare. Finally, the present work investigates the association between marketing mix elements and brand awareness, and finds that price promotions have a positive impact on brand awareness. Price promotions increase brand awareness by creating brand exposure and usage experience for consumers. The current research confirms past literature that distribution intensity has the largest positive impact on brand awareness. This research has limitations providing challenges for further research. Firstly, future research should replicate these results in other consumer-packaged goods categories, particularly fast-growing sectors with high levels of new product and advertising activities. To generalize the results, high-involvement decision products should also be tested. Since consumers typically invest time and energy when gath- ering product information prior to purchase in high-involvement categories, brand awareness may predict revenue premium (rather than vice versa) contrary to this study’s findings. Furthermore, future research should compare the impact of brand awareness and brand liking, or brand image on sales.2 The impact of different brand equity constructs may be different across different product categories. Secondly, brand awareness includes both brand recall and brand recognition (Keller 1993) but this study did not examine them separately. Future research should develop separate measures to assess brand recall and brand recognition— further exploring their relationship with market outcomes. For different product categories, the impact of brand recall and brand recognition on market outcome may be different. The effects of marketing mix elements may also show differences on brand recall and brand recognition constructs. Thirdly, future research could improve the operationalization of the price promotion variable. The measure used in the present work, “percentage of sales made on price promotion,” neglects the depth and frequency of price promotion. Although managers were provided insight into the association between price promotion and brand equity, specifics on how to utilize price promotion in terms of the depth and frequency to improve brand awareness are lacking. Fourthly, the current study measures brand market performance by sales, revenue premium, and price premium. Future research could further investigate the association between brand awareness and the brand’s performance in the financial

2 The authors thank an anonymous referee who offered this suggestion. 130 R. Huang and E. Sarigöllü market. An interface between marketing activities and financial performance war- rants future research. In addition, although the current work use brand sales or revenue premium as dependent variables and uses secondary measures to capture branding efforts of firms, the analysis is prone to endogeneity concerns. Future research might look for instruments to circumvent such issues. Finally, a longitudinal research should explore the causal relationship between brand awareness and brand usage experience, the brand awareness and brand market performance. A longitudinal study might help to determine the time lag between brand awareness and brand market performance.

Acknowledgment This research was supported by funds from McGill Institute of Marketing and by the 211 Project (phase III) of Shanghai University of Finance and Economics. Send corre- spondence to Rong Huang, Marketing, School of International Business Administration, Shanghai University of Finance and Economics, 777 Guoding Road, Shanghai, China, 200433. Tel: 86-21- 6590-4699, Fax 86-21-6511-2354 (email: [email protected]). Emine Sarigöllü, Fac- ulty of Management, McGill University, 1001 Sherbrooke St. West, Montreal, Quebec, Canada, H3A 1G5. Tel: (514) 398-4662, Fax: (514) 398-3876 (e-mail: [email protected]). The authors thank Demetrios Vakratsas (Faculty of Management, McGill University), Georges Zac- cour (HEC Montréal), George Alex Whitmore (Faculty of Management, McGill University) and Yoshio Takane (Department of Psychology, McGill University) for their insightful comments and constructive suggestions.

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Yik-Hin Chui, Pui-Sze Chow and Tsan-Ming Choi

1 Introduction

In recent years, electronic commerce has been gaining its popularity and a new type of online shopping model called online group buying has got much attention. Group buying is defined as a buying event participated by a group of customers who may not know each other and is usually organized by some electronic means, such as the Internet, to approach retailers together in order to get discounts for a particular product or service. Obviously, the collective bargaining power of a group of customers has implied a more favorable price for the product. Nowadays, this type of online shopping model is very popular. Take Hong Kong as an example. Group buying websites have only appeared in Hong Kong for several years, but there are already around 30 such websites in Hong Kong’s online shopping market (Lee 2011). For instance, uBuyiBuy.com, one of the biggest group buying websites in Hong Kong, got more than 280,000 registered members, selling out over 173,000 group buying vouchers to around 70,000 consumers within six months from its first launch in June 2010 (Yu 2010). It offers discounts and various products choices including fashion garments, beauty products, and accessories to attract customers. Due to the rapid growth of group buying, many business challenges and new sources of uncertainties have also arisen. Although group buying websites can offer a lower price or discounts to attract customers, some companies may not manage their business well so the number of complaints about group buying has been

P.-S. Chow () · Y.-H. Chui · T.-M. Choi Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong e-mail: [email protected] Y.-H. Chui e-mail: [email protected] T.-M. Choi e-mail: [email protected] T.-M. Choi (ed.), Fashion Branding and Consumer Behaviors, 133 International Series on Consumer Science, DOI 10.1007/978-1-4939-0277-4_9, © Springer Science+Business Media New York 2014 134 Y.-H. Chui et al.

escalating recently. According to a recent report by the Hong Kong Consumer Council, a total of 1,214 complaints related to online group purchase were received in the year 2011–2012 whereas there were only 13 cases in the previous year (Hong Kong Consumer Council 2012). Meanwhile, the Hong Kong Police received 623 reports of suspected Internet commercial frauds in 2010 (Yeung 2011). All these statistics reflect that shopping at group buying websites may incur a certain level of risk, which in turn influences customers’ decision making (Liebermann 2002) and the consumer welfare. In the literature, it is commonly believed that customers perceive a higher level of risk in Internet shopping than the traditional bricks-and-mortar store shopping (Biswas and Biswas 2004) and the level of perceived risk depends on various factors. If companies can reduce customers’ perceived risk level, there will be a higher possibility that customers buy more in quantity and frequency through the Internet (Doolin et al. 2005). As a consequence, for the long-term development of group buying, group purchase companies should find ways to reduce customers’ perceived risk in order to increase their buying intention. Motivated by the observed industrial practices in group buying, this chapter contributes to the literature by achieving the following research objectives: (1) to understand different types of customers’ perceived risk when they purchase apparel through group buying companies, (2) to identify the critical factors that will influence the different types of customers’ perceived risks, (3) to reveal the relationship between various risk-reducing strategies adopted by customers and individual influential factors that affect their perceived risks, and (4) to provide suggestions to group buying companies on how they could reduce customers’ perceived risks. The remaining parts of this chapter are organized as follows. Section 2 presents the literature review. Section 3 describes the data-collection process. Section 4 shows the data analysis. Section 5 discusses the findings and the implications. Section 6 concludes the chapter.

2 Literature Review

2.1 Group Buying

Group buying is the “collective bargaining” with multiple customers buying as a group together. Due to the advance in the Internet technology, group buying is now facilitated by electronic means. The central idea of online group buying is the aggre- gation of geographically dispersed customers’ purchasing power via the group buying website to get price discounts from sellers (Rezabakhsh et al. 2006). The group buying pricing mechanism permits customers to increase their purchasing power and obtain greater discounts than what they are able to get individually (Kauffman and Wang 2002). The lower price is resulted from reducing the transaction cost between customers and companies with a bigger volume (Li et al. 2002). Online group buying, despite being a new shopping model, is still a purchasing activity 9 Consumer Perceived Risks Towards Online Group Buying Service … 135 which is associated with risks. For example, consumers under group purchase are unable to view the products before they purchase; the after-sale service is usually less comprehensive, and some probable chances of being cheated (e.g., some customers pay more than others). In addition, there are reports on cases in which the companies do not deliver products after getting money, and customers need to wait for a longer time than usual. Thus, group buying is associated with a lot of sources of uncertainty and risk (Lin 2006).

2.2 Perceived Risks Related to Online Group Buying of Apparel Products

In the literature, Cox and Rich (1964) construct the concept of perceived risk as a function of two variables: the individual’s feeling of subjective certainty of success or failure (uncertainty) and the amount at stake (consequences). Combining the research of Jacoby and Kaplan (1972) and Stone and Gronhaug (1993), functional, financial, time, and psychological risks are identified. Moreover, privacy risk and source risk of online shopping are further suggested by Harris and Goode (2004) based on the reported cases in which leakage of personal and credit-card information occurs. It is also claimed that risk is deemed to be even higher in online transactions because the lack of physical contact curtails customers’ opportunities to exert control. Among different kinds of risk, functional risk is highly related to group buying. In fact, functional risk is also known as performance risk, and it can be defined as the perceived risk associated with the disappointment that online buyers may experience when the products purchased online do not meet their expectations (Forsythe et al. 2006; Torkzadeh and Dillion 2002). As we mentioned above, higher functional risk is created online due to the inability to physically examine the product and the lack of personal contact during the shopping process. The level of functional risk associated with online shopping also depends on the type of products. For example, it may be less risky to buy books, computers, and electronic products which are more standardized (Bhatnagar et al. 2000) than products like fashion products which in- volve experiential value through fitness, color, fabric, and quality of the product (Bhatnagar et al. 2000; Forsythe et al. 2006; Fram and Grady 1997). Another dimension of risk is the financial risk. In online group buying context, it is related to the risk of losing money during online transactions with credit card or bank account information being stolen (Fram and Grady 1997). This risk also exists in traditional in-store buying but it is more serious with the online shopping (Bhatnagar et al. 2000) because credit card fraud is a major concern. Researchers have also attributed financial risk associated with online shopping to the lack of trust in retailers. For example, customers may be worried about not being able to receive the purchased apparel products on time, having their personal information being stolen, and credit card being overcharged (Forsythe et al. 2006). This risk will also arise due to the direct financial loss, such as the failure to get the money back if customers want to cancel the transaction. Moreover, if customers discover that the same apparel is at a lower price in other places, financial loss is also incurred. 136 Y.-H. Chui et al.

The term privacy is defined as the individual information belonging to personal asset legally and ethically (Miyazaki et al. 2001). Privacy relates to risk as well as customers might have concerns regarding potential loss of control over their own individual information when they perform online purchasing (Garbarino and Stra- hilevitz 2004). With the feeling of having less control over their personal private information in the online setting, customers may hesitate to provide their personal information required for the online transactions. In traditional shopping, Roselius (1971) suggests that time risk covers the concerns regarding the amount of time required to make a purchase or wait for the product to be delivered. It also relates to the time wasted as a result of having to return or replace purchased products. The same time loss concept can be applied to online shopping contexts where customers who are not familiar with online shopping might need to spend more time in browsing and navigating through a website (Forsythe and Shi 2003; Forsythe et al. 2006). The downloading time especially for high-pixel images and the time spent while waiting for the transaction to complete can also cause perceived time risk (Forsythe et al. 2006). In previous research with catalog or mail-order shopping, source risk refers to the concern and discomfort customers experience because they are unsure whether they should trust the catalog or mail-order retailer (McCorkle 1990). The same concern exists in the online shopping context. In the era where so many websites launch and close every day, customers have reasons to worry whether the online retailer and the group buying company from which they want to purchase a product is trustworthy and legally operated (Torkzadeh and Dillion 2002). They may also be concerned about the legitimacy of the goods. Jacoby and Kaplan (1972) define psychological risk as dissatisfaction or mental stress caused by the purchase of the product. It covers the concern that use or possession of the product will not match the personality or style of the consumers and how they perceive themselves. The same concept is applicable to the online context in which such frustration can cause mental stress for individual customers. Given the similar nature between psychological risk and social risk, which concerns the customers’ worry about how others perceive the apparel bought with the customers’ style (Simpson and Lakner 1993), we group social risk and psychological risk together for the sake of simplicity.

2.3 Factors Influencing Customers’ Perceived Risk

In the literature, Dowling (1986) and Liebermann and Stashevsky (2002) suggest that experience will be one of the most important factors in affecting the level of perceived risk. As implied by their study, consumers’ previous purchasing experience via a certain shopping channel is negatively correlated to the perceived risks associated with the future purchase in that channel. In other words, when a consumer gets more experience with shopping on the Internet, he/she will see shopping online as a less risky action in all terms and is more likely to continue to shop 9 Consumer Perceived Risks Towards Online Group Buying Service … 137 online. For example, even if customers are not able to touch the fabric or try on a denim jacket to test its fitness in the online setting, those who have purchased similar products online may not have as many concerns as those who have never purchased online. As a result, it is believed that experience will play an important role in determining the level of perceived risk. Prior research suggests that possessing product knowledge could reduce the product perceived risk (Wendler 1983; Jacoby and Kaplan 1972). The reported finding in the literature indicates that the greater the perceived risk in the prepurchase stage, the more information customers would search for. Thus, the more information customers possess, the higher their confidence in their abilities to make reasonable decisions and the smaller the perceived risk. Putting this concept into our current study, it means the more the customers know about the apparel products, the smaller the perceived risks become. This implies that product knowledge should be an influential factor to a certain extent. Richardson and Dick (1994) find that brand name is one of the most important extrinsic cues affecting the level of perceived risk. They also demonstrate that brand names are the most important signal across cultures to evaluate purchasing risk when customers face uncertainty about products, especially for the customers who have relatively little product knowledge and previous experience. The underlying reason is that over time brand name products develop a certain reputation or image that conveys information useful to customers in their prepurchased decision- making process (Ernest et al. 2003). The information is used by customers as a cue to assess quality. Hence, putting this argument into this study, customers’ familiarity of brand names of group buying websites, the apparel retailers, and above all, the apparel itself should influence the perceived risk in online purchasing processes to some extent. Laroche et al. (2000) state that customers will experience a higher level of perceived risks when the products are bought for others than for themselves, since they will spend more time on searching suitable products and information. Comparing with purchasing products for themselves, customers will find a higher level of uncertainty and a more severe consequence if they purchase for others. Apparel products belong to the “high involving products” category in which customers have to make sure the size, color, style, and other attributes of the apparel products should be suitable (for the receivers). More considerations before purchase are hence needed, leading to a higher perceived risk. Comments of others and word-of-mouth have long been a determining factor of customers’ perceived risks (e.g. Wangenheim 2004). Along with the advancement of technology, word-of-mouth is spread through the Internet through social networks, chat rooms, and forums. If customers who want to purchase apparel through online group buying websites have worries, they may talk to friends via the social networks or search online. As a result, the comments of others on group buying companies will be a crucial factor in determining perceived risks. Price and quality have different effects on perceived value for money, which may in turn affect the level of perceived financial risk (Bhatnangar et al. 2000). It is well argued that functional risk (on product performance) is to a certain extent 138 Y.-H. Chui et al. associated with the price of products. As for the product quality, Starr (1972) states that customers incorporate an adjustment for value and cost with respect to their own projected “end use” for the product when assessing quality. The concepts of perceived quality and consumer satisfaction are hence inherently interrelated. Both concepts encompass the comparative process of evaluation of products against expectations (Fiore and Damhorst 1992), which may thus affect their perceived risk. Akaah and Korgaonkar (1988) find out that there are different types of strategies adopted by customers to reduce the perceived risks and the most useful one is money-back guarantee, followed by brand name of retailers and maker, cost of product, free sample, quality of warranty, and past experience. Tan (1999) discovers that customers prefer quality of warranty where there is an endorsement of expert or celebrity most, followed by brand name and guarantee. Derbaix (1983) states that brand loyalty, money-back guarantee, image of shop, and shopping around are more useful in reducing financial risks while shopping around is also useful in reducing psychological risk. To conclude, customers with different perceived risks will adopt different strategies. With reference to the above literature, this chapter aims at exploring the following: (1) Do customers face the six types of perceived risks (namely: performance risk, financial risk, privacy risk, time risk, source risk, and psychological risk) when purchasing apparel through online group buying websites? Which types of the perceived risks are most concerned by customers? (2) What factors have influence on the degree of the above perceived risks? and (3) What kinds of risk-reducing strategies can help with individual influential factors?

3 Methodology

An online questionnaire survey is conducted for the data-collection purpose. The set of structured questionnaires consists of different sections to measure: (1) respondents’ online buying habit, (2) respondents’ level of different types of perceived risks towards online apparel group buying, (3) degree of the influence of various factors on respondents’ perceived risks, (4) degree of the usefulness of various risk- reducing strategies, and (5) respondents’ demographic profile. In particular, the level of perceived risks, impact of influential factors, and the degree of usefulness of risk-reducing strategies are measured by 5-point Likert scale with reference to previous literature (see Table 9.1). The set of questionnaires is distributed via social websites such as Facebook, MSN. Nonrandom snowball sampling is used under which respondents help identify others they know who are qualified for the research (Berg 1988). The method relies on finding initial respondents who fit the profile for the study, contacting them, asking them to participate in the study, and asking them to refer other qualified potential respondents. The initial group of respondents of the snowball is a nonrandom “quota” sample, selected to represent the population. Snowball sampling allows the study to reach potential qualified respondents through interpersonal relationships. 9 Consumer Perceived Risks Towards Online Group Buying Service … 139

Table 9.1 Main contents of the questionnaire set Constructs Questionnaire content Related literature Perceived (Q1–5) Performance risk Forsythe et al. (2006); Torkza- risks deh and Dillion (2002); Bhatnagar et al. (2000); Fram and Grady (1997) (Q6–10) Financial risk Fram and Grady (1997); Bhatnagar et al. (2000); Forsythe et al. (2006) (Q11–14) Privacy risk Miyazaki et al. (2001); Garba- rino and Strahilevitz (2004) (Q15–18) Time risk Roselius (1971); Forsythe and Shi (2003); Forsythe et al. (2006) (Q19–21) Source risk McCorkle (1990); Torkzadeh and Dillion (2002) (22–24) Psychological risk Jacoby and Kaplan (1972); Simpson and Lakner (1993) Factors (Q25) Previous experience of purchase through Dowling (1986); Liebermann affecting group buying websites and Stashevsky (2002) perceived (Q26) Degree of product knowledge Wendler (1983); Jacoby and Risks Kaplan (1972) (Q27) Brand name of the online group buying Richardson and Dick (1994); website Ernest et al (2003) (Q28) Brand name of the apparel retailer (Q29) Brand name of the apparel (Q30) Selling price of the apparel Bhatnangar et al. (2000) (Q31) Purpose of purchase (self- use) (Q32) Purpose of purchase (as gift) (Q33) Comments on Group buying by Others Starr (1972), Fiore and Dam- (Q34) Quality of the apparel horst (1992) (Q35) Style of the apparel Risk (Q36) Purchase a brand that one has purchased Doolin et al (2005); Akaah reducing before and Korgaonka (1988); Tan strategies (Q37) Purchase a well-known brand (1999); Derbaix (1983) (Q38) Purchase through those online group buying companies that have money-back guarantee policy (Q39) Seek others’ comments before purchasing (Q41) Purchase based on one’s previous experience (Q42) Purchase apparel brands with endorsement of expert or celebrity (Q43) Visit different online group buying websites to make comparison before purchase (Q44) Purchase based on suggestions of consumer reports

By initially starting with a quota sample, which represents various subpopulations in the target population, it may be possible that the final data-producing sample closely represents the target population, thereby helps strengthen the external validity of study findings. 140 Y.-H. Chui et al.

Table 9.2 Respondents’ Profile Frequency Mix (%) Gender Male 73 36.1 Female 129 63.9 Age 18 or below 3 1.5 19–25 128 63.4 26–35 64 31.7 36–45 5 2.5 46 or above 2 1.0 Education Secondary 18 8.9 College 35 17.3 University 149 73.8 Occupation Student 103 51.0 Professional 29 14.4 Managerial 11 5.4 Retail & Services 22 10.9 Clerical 32 15.8 Self-employed 2 1.0 Unemployed 3 1.5 Income Under 2,500 57 28.2 2,501–5,000 38 18.8 5,001–10,000 27 13.4 10,001–20,000 52 25.7 20,001 or above 28 13.9

4 Data Analysis

4.1 Respondents’ Profile

A total of 226 sets of questionnaires were received, among which 202 respondents have heard of group buying, and are thus valid for further data analysis. Over 60 % of the qualified respondents are female, 95 % are aged between 19 and 35. Nearly third-quarter of them have received or are taking university education. Half of the respondents are students and less than 40 % of them have monthly income greater than HK$ 10,000 (see Table 9.2). Regarding their online purchase experience, around 70 % of the respondents have bought apparel online before. Forty-six percent of them spent HK$ 100– 1,000 on online apparel purchase over the past 12 months while slightly less than 18 % of them spent over HK$ 1,000 (Table 9.3). A similar proportion of respondents (67 %) have experience to purchase through online group buying websites but only less than 30 % of them have bought apparel through online group buying (Table 9.4). 9 Consumer Perceived Risks Towards Online Group Buying Service … 141

Table 9.3 Online Apparel Purchase Experience Frequency Mix (%) No. of times respondents have Never 61 30.2 experience purchasing apparel 1–3 times 63 31.2 online 4–6 times 41 20.3 7–9 times 8 4.0 10 times or above 29 14.4 Amount (in HKD) respondents spent Never purchased online 61 30.2 on online apparel purchase over Below $ 100 12 5.9 the past 12 months $ 101–500 51 25.2 $ 501–1,000 42 20.8 $ 1,001–2,000 19 9.5 $ 2,0001 or above 17 8.4

Table 9.4 Online Group Buying Experience Frequency Mix (%) No. of times respondents have Never 66 32.7 purchased through online 1–3 times 78 38.6 group buying 4–6 times 40 19.8 7–9 times 8 4.0 10 times or above 10 5.0 No. of times respondents have Never 145 71.8 purchased apparel through online 1–3 times 46 22.8 group buying 4–6 times 7 3.5 7–9 times 2 1.0 10 times or above 2 1.0

Table 9.5 Statistical Test Results—Perceived Risks Perceived risk Cronbach’s Alpha Mean S.D t-Statistics (Test Value= 3) Performance risk 0.851 3.7188 0.67724 15.085** Financial risk 0.733 3.0980 0.67691 2.058* Privacy risk 0.850 3.5767 0.78603 10.428** Time risk 0.767 3.4109 0.76057 7.678** Source risk 0.855 2.7921 0.82906 −3.564** Psychological risk 0.716 2.8053 0.75788 −3.652** * p-value <0.05; ** p-value <0.01.

4.2 Level of Perceived Risks

As depicted in Table 9.5, Cronbach’s alphas of items measuring the six perceived risks are well above the generally accepted threshold of 0.6. Thus, the internal consistency of our measurement is ensured for valid analysis. Next, we proceed to check whether respondents have a significant level of perceived risk towards online apparel group buying. The results of t-tests show that among the six types of perceived risks, four of them are significantly greater than the mean value of 3. 142 Y.-H. Chui et al.

Table 9.6 Comparison of Perceived Risks between respondents with and without online apparel purchase experience Perceived risk Mean S.D t-statistics No online With online No online With online apparel apparel apparel apparel purchase purchase purchase purchase experience experience experience experience Performance 3.9246 3.6298 0.55277 0.70789 3.186** Financial 3.1934 3.0567 0.66530 0.68005 1.320 Privacy 3.6066 3.5638 0.65584 0.83794 0.390 Time 3.5287 3.3599 0.72183 0.77366 1.452 Source 2.9891 2.7069 0.85628 0.80522 2.243* Psychological 2.9126 2.7589 0.69363 0.78184 1.326 * p-value <0.05; **p-value <0.01.

Table 9.7 Comparison of Perceived Risks between respondents with and without apparel online group buying experience Perceived risk Mean S.D t-statistics No online With online No online With online apparel apparel apparel apparel group group group group buying buying buying buying experience experience experience experience Performance 3.7917 3.5333 0.63678 0.74482 2.471** Financial 3.1421 2.9860 0.67820 0.66640 1.479 Privacy 3.6276 3.4474 0.75984 0.84216 1.471 Time 3.4224 3.3816 0.73805 0.82118 0.343 Source 2.8299 2.6959 0.83437 0.81475 1.034 Psychological 2.8598 2.6667 0.70016 0.87966 1.637 * p-value <0.05; **p-value <0.01.

In particular, performance risk has the highest mean value (3.719), followed by privacy risk (3.577), time risk (3.411), and financial risk (3.098). This reflects that respondents are most concerned about product quality and the danger of disclos- ing privacy through online apparel group purchase. On the contrary, respondents seem to be less concerned about the source and psychological risks related as their respective mean scores on the two aspects are significantly less than the average score of 3. Noticing that not all respondents have experience of online apparel purchase or online apparel group buying before, we compare the level of perceived risks between respondents with previous online (group) purchase experience and those without. The results of t-tests indicate that having previous online (group) purchase does have an effect on respondents’ certain types of perceived risks. In particular, respondents without previous online apparel purchase would have a higher degree of performance and source risks (Table 9.6) whereas respondents without previous online apparel group purchase would also have a higher degree of performance risk (Table 9.7). 9 Consumer Perceived Risks Towards Online Group Buying Service … 143

Table 9.8 Results of Reliability Test—Influential Factors for Perceived Risks Construct Cronbach’s Item Alpha Influential Reputation 0.837 Brand name of online grouping company factors Brand name of apparel retailer Brand name of apparel Product attributes 0.797 Quality of apparel Style of apparel Risk reducing Past performance 0.777 Purchase a brand that one has purchased before strategy tracking Purchase a well-known brand Purchase through those online group buying companies that have money-back guarantee policy Words-of-month Purchase based on one’s previous experience Information 0.591 Purchase apparel brands with endorsement of collection expert or celebrity Visit different online group buying websites to make comparison before purchase Purchase based on suggestions of consumer reports

4.3 Relationship Among Perceived Risks, Influential factors and Risk-Reducing Strategies

In this study, we consider different factors that affect the level of perceived risks, as well as various risk-reducing strategies based on a variety of existing literature. After conducting exploratory factor analysis and checking for internal consistency, the various influential factors can be reduced to two main components. Based on the nature of the individual items in the components, we name one component as “reputation” as it appears to be related to the reputation of the online group buying websites, apparel retailers, and the apparel brand, while the other is named “product attributes” as it is associated with the quality and the style of the apparel. Similarly, the list of risk-reducing strategies can also be consolidated into two main components and they are named “past performance tracking” and “information collection” according to the apparent natures of the items involved (Table 9.8). We employ correlation analysis to explore the relationship among the different types of perceived risks, influential factors, and risk-reducing strategies. The statistical results show that reputation (of the online group buying website, apparel retailer, and apparel brands) is significantly correlated to performance, privacy, time, and source risks (Table 9.9). On the other hand, the risk-reducing strategies that focused on tracking product/service providers’ past performance is significantly correlated to both types of influential factors (Table 9.10). 144 Y.-H. Chui et al.

Table 9.9 Correlation coefficients between various types of Perceived Risks and influential factors Influential factor Perceived risk Performance Financial Privacy Time Source Psychological Reputation 0.194** 0.088 0.147* 0.169* 0.154* 0.031 Product attributes 0.107 0.103 0.119 0.110 0.009 0.123 * p-value <0.05; ** p-value <0.01.

Table 9.10 Correlation coefficients between various Influential Factors and Risk-reducing Strategies Risk-reducing Influential factor Strategy Reputation Product attributes Past performance tracking 0.305** 0.197** Information collection 0.035 0.119 ** p-value <0.01.

5 Insights and Conclusions

5.1 Insights: Consumer Welfare and Managerial Implications

According to the statistically significant results presented in the previous section, consumers have a high level of perceived risks towards online apparel group buying in terms of product performance, privacy, and time. These are in fact the concerns generally shared by online customers of all kinds and affect the consumer welfare substantially (because the perceived risk reduce their happiness of online purchasing and hence satisfaction). The high level of perceived risk is particularly prevalent for online apparel customers since satisfaction of apparel purchase largely relies on how fit and good-looking the customers feel wearing the apparel, but the outcome is unknown until the apparel is delivered. This leads to doubts and uncertainty which directly implies a rise of risk and hence damages to consumer satisfaction and welfare. Our study reflects that reputation (of the online group buying website, the apparel retailer, and the apparel brand name) plays an important role to the customers’ perception to the above risks. We also reveal that for customers considering reputation and product attributes influential to their perceived risks towards online apparel group buying, they also find tracking past performance of the online group buying websites and apparel retailers as useful risk-reducing strategy. Whereas there is no doubt that both the online group buying companies and the apparel retailers should exert huge efforts to improve/maintain the quality of their apparels and services, we strongly suggest that they should also boost their reputation by emphasizing their product/service quality through different promotional or advertising channels. Our study also shows that respondents without online apparel purchase experience have a higher level of perceived performance risk and source risk. In this aspect, we suggest that online group buying websites and apparel retailers partici- pating in online group purchase should launch special promotions to attract the group of inexperience customers to try online group buying. Having experienced 9 Consumer Perceived Risks Towards Online Group Buying Service … 145 the process, these customers would have more confidence towards the approach of online apparel group buying.

5.2 Limitations and Future Direction

Certain limitations of the current study are identified. Firstly, owing to the adoption of snowball sampling as the sampling method and the current sample size, the respondents may not be representative enough to reflect the perception of the actual population of potential online apparel group buying customers. Besides the list of influential factors and risk-reducing strategies under consideration are also not exhaustive. Since online group buying is a relatively new business model while development in information technology is advancing tremendously fast, more factors and strategies will emerge for consideration. On the other hand, the risk aspect this study concerns is related to the entry barrier that hinders customers from online apparel group buying. As customers get more accustomed to this business model, the corresponding risk should be alleviated. A future direction may focus on retaining customers in the presence of keen competition among online group buying providers.

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A Birtwistle, G., 8 Aagerup, U., 36 Brand association, 118 Aaker, J. L., 30–32, 36–38 Brand awareness, 5, 8, 15, 113–119, 121–130 Advertisement, 20, 29, 32, 34–36, 38–42 literature on, 114 as a communication tool, 31 Brand awareness–price relationship, 118 schemes, 12 Brand equity, 5, 14, 15, 41, 63, 102, 113, 114, Advertising, 117 116, 117, 119, 120, 122, 123, 126, 128, Alford, B. L., 35, 36 129 All commodity volume (ACV), 121 Brand extension, 63 Allen, C. T., 32 strategies of, 9, 64 Al-Mutawa, F.S., 12 Brand extensions, 63, 71 Amaldoss, W., 20 category extension, 63 Amatulli, C., 11 line extension, 63 Analytical model, 3, 20, 51 Branding, 103 Ang, S. H., 29, 30, 34–36 strategies of, 3 ANOVA, 63, 86–88 Brand ladder, 9 Apparel Brand meaning, 4, 31–35, 37, 39, 40–42, 119 as a status symbol, 80 Brand owners, 102 Apparel purchase, 78, 84, 140, 142, 144 Brand personality, 3, 11, 29–32, 34–42 Apparel Stores Company Index, 64 dimensions of, 30 Armstrong, K. L., 35, 39 Brands, 103 Arrigo, E., 12 Brand selection, 109 Artificial neural network (ANN), 4, 64–66, British luxury fashion brand, 8 69–71 Brownian motion, 52 analysis of, 4 Bruce, M., 63 Australia, 77, 81, 84, 86, 87, 89, 95, 96 Brun, A., 9 Australian apparel industry, 95 Business challenges, 133 Australian fashion industry, 5 Business development, 109 Australian luxury brand apparel, 78, 84, Business growth 86–91, 94 strategies for, 63 Australian luxury brands, 96 Business model, 145 Azcarraga, A. P., 64 C B Caballero, R., 50 Baldursson, F., 50 Cachon, G. P., 49 Belk, R. W., 30 Capella, L. M., 35, 36 Bentolila, S., 50 Caro, F., 49 Bertola, G., 50 Carrigan, M., 12, 24 Biel, A. L., 31, 41 T.-M. Choi (ed.), Fashion Branding and Consumer Behaviors, 147 International Series on Consumer Science, DOI 10.1007/978-1-4939-0277-4, © Springer Science+Business Media New York 2014 148 Index

Chen, C.-M., 63 Emond, P. L., 7 Cheng, T. C. E., 50 Empirical Chen, J., 16 analysis of, 3, 8, 22, 64 China, 5, 15, 16, 78, 82, 84, 87, 94–96 hypothesis on, 70 Chiu, C. H., 64 models of, 3 Choi, T. M., 15, 50, 63–65, 70, 71 research literature on, 8 Christopher, M., 51, 63 research methodology on, 106 Chu, S. C., 15 studies on, 15, 42 Clothing selection, 104 Environment, 4, 29, 31, 33, 37, 39, 40–42, 80, Co-brand, 5, 9, 103, 109 116, 118, 127 Co-branding, 5, 35, 102, 103 Environmental conditions, 127 Co-branding alliance, 109 Environmental sustainability, 3, 24 Collaboration, 101, 102 Ethnocentrism, 82, 96 Collaborative brands, 103, 109 Conspicuous, 81 F Conspicuous consumption, 11, 12, 20, 79, 104 Fan, F., 63 Conspicuous fashion, 20 Farzin, Y. H., 50 Consumer behavior, 6, 11, 12, 24, 25, 37, 40, Fashion advertisement, 36 102, 106 Fashion and apparel industry, 4 Consumer perceived risk, 6 Fashion brand extensions, 63 Consumer science, 25 Fashion branding, 3, 6, 9, 11, 12, 14, 15, Consumer survey, 12, 14, 16, 17 20–22, 24, 25 Consumer welfare, 3, 4–6, 25, 37, 42, 57, 71, Fashion brand personality, 4, 11, 32, 34, 37 108, 129, 134, 144 Fashion brands, 29 issues of, 4 Fashion-conscious consumers, 77 Coordination, 110 Fashion industry, 63, 101 Correlation analysis, 143 Fashion products, 38 Cotte, J., 31–33, 37, 39, 42 Fast fashion, 101 Counterfeiting, 24 Fast fashion brand, 5, 101, 102, 104, 105 Country of origin, 81 Fast fashion co-branding, 5, 101, 102, Crane, D., 11 104–106, 109, 110 Cross Cluster Cross Region Analysis, 63 Fast fashion co-brands, 5, 102–104, 107–109 Customer equity, 14, 15, 17 Fast fashion consumption, 104 Customer lifetime value, 17 Ferdows, K., 49 Customer mindset, 114, 116, 117, 119, 122, Financial risks, 135 125, 129 Fines, C. H., 50 Customer mindset brand equity, 119, 122 Fionda, A. M., 9, 25 Customer relationships, 14 Fishbein’s model, 78 Customer-salesperson relationship, 16 Fleming, P. J., 64 Customers’ perceived risk, 136, 137, 144 Flexibility, 50 Forecast, 15, 50, 51, 123, 125 D Foreign brand apparel Daly, L., 63 study of, 78 Demand fluctuation, 4, 49 Foreign luxury apparel, 82 Demand predictability, 63 Fournier, S., 31, 32 Distribution, 117, 118 Fujita, Y., 50, 52 Dixit, A. K., 50, 52, 53 Functional risk, 135, 137 Future research, 3, 6, 11, 22, 25, 42, 110, 114, E 129, 130 Effective communication, 41 Ehrenberg, A., 30 G Eicher, J. B., 33 Gallien, J., 49 Eisenhardt, K. M., 50 Gao, L., 15 Index 149

Grathwohl, H. L., 37 Kim, J. H., 16 Group buying, 6, 133–138, 140–145 Kim, K. H., 7, 17 risks of, 6 Kim, M., 16 Grubb, E. L., 37 Kim, S., 16 Guido, G., 11 Kleine, R. E, 30, 32, 37 Kleine, R. E, III, 32 H Kleine, S. S., 30, 32, 37 Hayes, J. B., 34, 35, 36 Ko, E., 7, 14 Haytko, D. L., 32, 37 Kort, P. M., 50 Hecht-Nielsen, R., 66 Kressman, F., 36 Heine, K., 11 Hergeth, H., 63 L H&M, 5, 49, 101, 102, 104, 109 Large, J., 11 Hoffmann, J., 9 Lead time, 49 Holt, D. B., 32, 37 Leahy, J. V., 50 Hong, J. W., 37 Lee, S. H., 14 Hong Kong, 5, 106, 110, 133 Levy, S. J., 31 Hsieh, M.-H., 64 Lewis, M. A., 49 Hui, C. L., 63, 64 Liao, S.-H., 63, 64 Huisman, K. J. M., 50 Li, D., 64 Human personality, 3 Li, G., 15 Hyllegard, K., 40 Ligas, M., 31–33, 37, 39, 42 Hypothesis, 69, 70, 82, 86–88, 91, 92, 103, Lim, E. A. I., 29, 30, 34–36 107, 108, 116–118 Literature review, 3, 7, 21, 25, 78, 134 Liu, S.C., 15, 63–65, 70, 71 I Lowson, R., 51 Influential factors, 6, 134, 138, 143, 145 Luxury brand apparel, 78 Internet, 6, 80, 133, 134 Luxury fashion brand, 3, 5, 7–9, 11, 12, Italian luxury fashion industry, 9 14–17, 20, 24, 25 Italy, 5, 11, 12, 78, 82, 84, 87, 93, 94, 96 models of, 8 Luxury fashion branding, 7, 8 J Luxury fashion industry, 7 Jain, S., 20 Japan, 5, 78, 82, 84, 87, 94, 96 M Jin, B., 64 Machuca, J. A. D., 49 Johar, G. V., 34 Mail-order shopping, 136 Johar, J. S., 38 Malär, L., 38, 40, 42 Johnson, K., 49 Malhotra, N. K., 30 Jung, J., 15 Managerial insights, 103 Marconi, J., 31 K Marketing mix, 117 Kahle, L. R., 33 Marketing mix elements, 5, 114, 117, 119, Kaiser, S. B., 33, 38, 39 121, 125, 129 Kamal, S., 15 Marketing science, 20 Karatzas, I., 50 Market outcome, 5, 113, 114, 116, 117, Keel, A., 36 122–124, 126, 128, 129 Keller, K. L., 30, 35, 36, 38, 40 Mathematical model, 64 Kernan, J. B., 30, 32, 37 Matthiesen, I. M., 17 Khan, B. M., 31, 38 McCracken, G., 31, 35 Kim, A. J., 14 McDonald, R., 50 Kim, H.–S., 30 Mean absolute percent error (MAPE), 124, Kim, H. Y., 17 125 Kim, J., 16 Megehee, C. M., 7 Miller, K. W., 17 150 Index

Mills, M. K., 17 Psychological risks, 136 Moore, C. M., 8, 9, 25 Public data, 8, 71 Morace, F., 11 Public interest, 11 Multi-attribute attitude model, 5, 83, 84 Public relations, 34, 127 Purchase, 5, 11, 14, 20, 40, 41, 51, 63, 77, 82, N 84, 102, 104, 105, 116, 126, 127–129, Ng, S. F. F., 64 134, 136, 137 Ni, Y., 63 Purchase intention, 14–16 Nobbs, K., 9 Purchase perception, 5, 102, 103, 105–109 Non-status seeking consumers, 78, 79, 86, 96 Puzakova, M., 36

O Q Objective function, 53 Quantitative decisions, 50 Obsolesce proofness, 50, 51 Quantitative empirical based studies, 3, 8, 12, Ogle, J., 40 16, 22 Onkvisit, S., 37 Quantitative research, 21 Online group buying, 133 Questionnaires, 138 Online shopping, 134, 135 Questionnaire survey, 5, 106, 138 models of, 133 Quick Response (QR), 50 risks of, 135 On-line shopping platform, 136 R Optimal stochastic product switching Reliability test, 107 strategy, 56 Research agenda, 7, 25 Optimal stopping theory, 4, 50, 59 Research trend, 3, 7, 8, 21, 22 Optimization, 20 Respondents, 14, 94, 106, 107, 114, 119, 138, Orth, U. R., 33 140–142, 145 Return, 136 P Risk, 6 Pan, S. L., 64 Roach-Higgins, M. E., 33 Pashkevich, M. A., 64 Rohwedder, C., 49 Passariello, C., 49 Romaniuk, J., 30 Paul, O., 40 Rook, D. W., 30, 36 Peck, H., 51, 63 Rosenberg, M., 37 Perceived risk, 6, 134–138, 141–144 Rossiter, J. R., 38 concept of, 135 Perception, 11, 17, 30, 31, 35, 36, 40, 42, 64, S 80, 81, 94, 95, 102, 109 Savelli, E., 8 Percy, L., 38 Scott, L. M., 32, 34, 37 Performance risk, 6, 135, 138, 142, 144 Self-concept domain, 37 Phau, I., 17 Service, 6, 105, 113, 116, 128, 129, 135, 144 Pindyck, R. S., 50, 52, 53 Setiono, R., 64 Plummer, J. T., 30 Seven-point scale, 84 Poisson process, 52 Shaw, J., 37 Poisson regression, 65 Shen, D., 15 Price, 5, 6, 82, 87, 89–95, 102, 105, 114, Shepard, B., 34 117–121, 123, 125, 133–135, 137 Siegel, D., 50 Price promotion, 113, 114, 117–119, 121, 125, Sigmoid function, 67 127–129 Sirgy, J., 30, 37, 38 Privacy, 136 Sirgy, M. J., 38 Product-related attributes, 30 Snowball sampling, 138 Product uniqueness, 5 Social function, 105 Promotions, 39 Social interaction, 33 Provocative fashion advertising, 40 Social media advertising, 15 Index 151

Social media marketing, 14 V Social relationship, 16 Veeraraghavan, S., 20 Souiden, N., 11 Venkatesh, A., 11 Stankeviciute, R., 9 Veryzer, R. W., 29 Status consumption, 79, 84 Vézina, R., 40 Status Consumption Scale (SCS), 84, 85 Visual bricolage, 39 Status-oriented consumers, 79 Status seeking consumers, 77, 78, 80, 86, W 94–96 Wall, R. S., 11 Stochastic, 50, 51, 53 Walters, H., 37 Stochastic dynamic model, 50, 59 Wen, C.-H., 64 Stochastic process, 4, 50, 52 Wiener process, 52 Sullivan, M. W., 63 Williams, J. R., 50 Supply chain management, 3, 25 Woodside, A. G., 12 Survey, 84, 85, 106, 114, 116, 117, 119 Wu, C.-H., 63 Swinney, R., 49 Symbolic interaction, 4, 31–33, 42 Y Yan, R.-N., 40 T Yoo, B., 14 Teenage market, 80 Yu, Y., 63, 64 Tereyagoglu, N., 20 Thompson, C. J., 32, 37 Z To, K. M. C., 64 Zhang, B., 16 Traditional shopping, 136 Zheng, J., 20 Zinkhan, G. M., 37 U Zmuda, N., 37 Uncertainty, 135, 137, 144 Uniqueness, 104, 109 Utility, 5, 105, 108