Counterfeit Fashion: a Comprehensive Study Determining the Influence Factors of Fashion Counterfeit Purchase Decisions

COUNTERFEIT FASHION: A COMPREHENSIVE STUDY DETERMINING THE INFLUENCE FACTORS OF FASHION COUNTERFEIT PURCHASE DECISIONS

Kelly Gamble

A Thesis Submitted to the University of North Carolina Wilmington in Partial Fulfillment of the Requirements for the Degree of Masters of Business Administration

Cameron School of Business

University of North Carolina Wilmington

2011

Approved by

Advisory Committee

Dr. Alexis Papathanassis Dr. Helga Meyer

L. Vince Howe Chair

Accepted by

Dean, Graduate School

TABLE OF CONTENTS

ABSTRACT ...... iv ACKNOWLEDGEMENTS ...... v LIST OF TABLES ...... vi LIST OF FIGURES ...... vii LIST OF ABBREVIATIONS ...... viii 1.0 INTRODUCTION ...... 1 2.0 BACKGROUND AND RATIONAL ...... 1 2.1 Definitions and Classifications ...... 2 2.2 Impacts of Counterfeiting ...... 4 2.3 Historical Brand Aspects ...... 6 2.4 Inadequacies of Anti-Counterfeit Legislation ...... 8 2.5 Structural Overview ...... 12 3.0 LITERATURE REVIEW ...... 13 3.1 Scope and Reduction of Information Biases ...... 13 3.2 Search Method ...... 14 3.3 Content Analysis ...... 16 3.3.1 Consumers are more willing to Purchaser Counterfeit Fashion Items ...... 16 3.3.2 Unique Characteristics of Counterfeit Fashion ...... 18 3.3.3 Variables that Influence Counterfeit Purchase Decisions ...... 19 3.3.3.1 Demographic Variables ...... 20 3.3.3.2 Values and Attitudes Variables ...... 22 3.3.3.3 Consumption Variables ...... 28 4.0 METHODOLOGY ...... 32 4.1 Quantitative Analysis ...... 33 4.2 Advantages and Disadvantages of Internet Survey Analysis ...... 34 4.3 Research Process ...... 36 5.0 FINDINGS AND DISCUSSION ...... 42 5.1 Representative Sampling ...... 43 5.2 Demographic Correlations ...... 46 5.2.1 Age ...... 47 5.2.2 Income ...... 48 5.2.3 Education ...... 50

5.2.4 Other Demographic Findings ...... 51 5.3 Attitudes and Values Correlations ...... 52 5.3.1 Materialism ...... 52 5.3.2 Personal Values ...... 55 5.3.23 Attitudes ...... 57 5.4 Consumption Correlations ...... 58 5.4.1 Product Knowledge ...... 60 5.4.2 Product Involvement ...... 62 5.4.3 Brand Personality ...... 63 5.4.4 Product Attributes ...... 64 5.4.5 Product Benefits ...... 65 5.4.6 Financial Risk ...... 66 5.4.7 Social Risk ...... 67 5.4.8 In-Style ...... 69 6.0 CONCLUSION ...... 70 6.1 Managerial Implications ...... 71 6.2 Limitations and Further Research ...... 72 7.0 APPENDICES ...... 76 8.0 REFERENCES ...... 94

iii

ABSTRACT

A thorough analysis of the existing literature established a relatively concrete examination of consumer counterfeit purchase decisions but severely lacked relevant research directed toward one of the most commonly victimized industries of counterfeiting: fashion merchandise. In order to fill this hole in existing literature, this study transferred the components of past research to the relatively unexplored world of fashion counterfeiting. In doing so, the objective was to determine what variables influence a consumer’s willingness to purchase non-deceptive counterfeit fashion items. This allowed for a comparative analysis about how the influence factors differ from those that influence consumers to purchase general counterfeit items. In order to test 30 variables that were hypothesized to influence consumer willingness to purchase counterfeit fashion items, an internet survey was published and submitted by 117 respondents.

Nineteen hypotheses were formed based on two components. The first is how the selected variables correlated in past studies with consumer willingness to purchase general counterfeit items. The

second component is how logic and existing literature suggests those relationships may differ with fashion counterfeit items due to the unique characteristics of the fashion industry. A quantitative analysis determined that twelve of the tested variables either correlated, or showed a relationship with, consumer

willingness to purchase counterfeit fashion items. Demographic variables age, income, and education

negatively correlated with the control questions suggesting that younger consumers with lower income

and less education are more likely to purchase counterfeit fashion items. Materialism, respect for

tradition, and a need for an exciting life all showed positive correlations with one or both of the control questions in the survey. Attitudes toward counterfeit law and order, value, and past experiences showed

the strongest connection with consumers’ willingness to purchase counterfeit fashion items and the

consumption variables social risk and product attributes showed the highest tendency to influence the

counterfeit fashion purchase decision. The results of this study have implications for fashion designers

and legitimate fashion companies that are losing business due to a growing counterfeiting industry.

ACKNOWLEDGMENTS

I would like to express my appreciation and gratitude to everyone that supported me in this project. It has been a long journey since I began the writing process and I am very proud of the work and commitment that I dedicated to this final step in completing my International Master of Business

Administration.

First I would like to thank my thesis advisor Professor Doctor Alexis Papathanasis. Without his undying enthusiasm and commitment to challenging my way of thinking this thesis would never have received the intellectual depth and consideration it deserved. I am especially grateful to him for taking the time to teach me the right way to approach research and for giving me so many tools, for not just my education and career, but for many other aspects of life as well.

I also would like to thank Professor Helga Meyer for dedicating her time and attention to being my second reader. She has been very flexible and readily available to support me with any questions or concerns I have had along the way.

Lastly, I would like to thank my friends and family for all of their support. A special thanks goes to my father who has been my financial, mental, and emotional support system throughout this program.

Without him none of this would have been possible and I am extremely grateful for his encouraging words and commitment to my education. I am also deeply indebted to my mother for putting a roof over my head while I complete this laborious process and for believing in my strengths and abilities. Last but not least, I would like to express my sincerest appreciation for my amazing friends all around the world whose patience and love have supported me each step of the way.

LIST OF TABLES

Table Page 1. Variables and corresponding survey questions ...... 36 2. Respondent profile……………………...... 43 3. Demographic variables with significant correlations ...... 46 4. Values and attitudes variables with significant correlations ...... 51 5. Consumption variables and survey questions ...... 58 6. Control question errors ……...... 72 7. Survey data: Demographic variables control questions (respondents 1-58) ...... 82 8. Survey data: Demographic variables control questions (respondents 58-117) ...... 83 9. Survey Data: Variables 6-19 (respondents 1-58) ...... 84 10. Survey Data: Variables 6-19 (respondents 58-117) ...... 85 11. Survey Data: Variables 20-30 (respondents 1-58) ...... 86 12. Survey Data: Variables 20-30 (respondents 58-117) ...... 87

LIST OF FIGURES

Figure Page 1. List of items on the willingness to buy counterfeit goods scale and their ratings ……………… 17 2. Willingness to buy different counterfeit products ………………………………………………..17 3. Factor derived model………………...... 41 4. Demographic histograms…………………………………………………………………………44 5. Product knowledge responses ...... 60 6. Product involvement responses ...... 61 7. Brand personality responses...... 62 8. Product attributes responses ……………………………………………………………………..63 9. Product benefits responses ...... 64 10. Financial risk responses ...... 65 11. Social risk A: Q35 responses ...... 66 12. Social risk B: Q36 responses ...... 66 13. In-style responses …………...... 68 14. Survey ……………………...... 75

vii

LIST OF ABBREVIATIONS

OECD Organization for Economic Cooperation and Development WTO World Trade Organization TRIPS Trade Related Aspects of Intellectual Property Rights ICE Immigration and Customs Enforcement IMPACT International Medical Products Anti-Counterfeiting Taskforce IBM International Business Machines Corporation SPSS Statistical Package for the Social Science NA Not Answered/Not Applicable

viii

1.0 INTRODUCTION

It can be assumed that nearly every consumer has come across counterfeited products in one way or another, even if they were not aware of it at the time. Tourist destinations, the internet, and even mainstream distribution channels all over the world have become prime markets for knock-off products and consumer demand continues to grow. Whether it is termed knock-off, replica, counterfeit, or even the most obvious of terms: fake; it is all referring to the same rising phenomenon of imitated products. The issue of counterfeiting has spread in recent years across many industries.

Sports equipment, computer software, car parts, and even prescription drugs are being imitated and sold at a fraction of the price of the originals. This is causing legitimate manufacturing companies and genuine brand marketers a great deal of frustration. In 2009, the United States government seized over $260 million in counterfeited products, a figure that has been on the rise for many years (Ellis,

2011). Among those most impacted by counterfeiting are companies in the fashion industry, particularly high end fashion brands such as Louis Vuitton, Gucci, and Prada (Mavlanova &

Benbunan-Fich, 2010). Due to the relative ease of manufacturing imitated clothing, bags, shoes, and accessories, combined with the prestige and exclusivity achieved through expensive brand marketing campaigns, the fashion industry has become a viable target for counterfeiters all over the world

(Mavlanova & Benbunan-Fich, 2010).

2.0 BACKGROUND AND RATIONAL

This study focuses on non-deceptive counterfeiting in the fashion industry. In 2010, fashion items including footwear, apparel, and accessories were all among the most commonly counterfeited merchandise seized in the US (Ellis, 2011). Because this industry has been victimized by counterfeiters for many years, a significant amount of research aims to statistically evaluate the monetary damage that has been caused to individual companies and to the industry as whole. Further research in the field analyzes the effect of anti-counterfeit legislation in various countries, pointing out that utilitarian designs, such as clothing, have been left largely unprotected by trademark and copyright laws in the United States (Tu, 2010). Now that counterfeiting has reached new heights in many industries, the focus of relevant literature has shifted to some degree toward understanding the

driving consumer behavior, aiming to tackle the root of the problem: consumer demand for counterfeit merchandise. Following such logic, this study aims to understand why consumers choose to buy fashion counterfeit goods in the fashion industry. This industry offers different insights into the problem of counterfeiting than other types of products because fashion items have a unique set of characteristics that make them particularly susceptible to counterfeiters. Fashion items are relatively easy to imitate at a low cost to the counterfeiter, they often have globally recognized name brands that appeal to many consumer segments, and there is a limited time period in which these items are considered fashionable. Because of the unique characteristics of fashion items this study is predicted to yield different results than previous studies that focus on other industries or counterfeit products in general.

Past research highlights price savings as a key determinant in the consumers counterfeit purchase decision (Bian & Moutinho, 2009), however there are many other variables that can influence that decisions and this study intends to find out what some of those variables are in terms of fashion items. Having an understanding of the variables that influence counterfeit purchase decisions is the first step toward addressing the issue from the demand side. Anti-counterfeit legislation attempts to control the supply of counterfeit goods, but unless the demand for imitated fashion items is better controlled, the issue of counterfeiting and the associated costs will continue to grow. Gaining an understanding of the variables that increase the likeliness of a counterfeit purchase decision is crucial information for marketers of authentic brands. The results of this study will aid companies in the fight against fashion counterfeiting by allowing them to set up more effective marketing strategies and most importantly to understand what market segments to focus and how to meet the needs of their consumers that are currently being met by counterfeit products.

2.1 Definitions and Classifications

The term counterfeits can be defined as “any unauthorized product that infringes upon intellectual property rights (brand names, patents, trademarks, or copyrights)” (Swami, Chamorro-

Premuzic, & Furnham, 2009, p. 820). However, there are different types of counterfeiting and several

2 terms that existing literature uses to refer to counterfeits. The two most general categories of counterfeiting can be differentiated by whether or not the consumer knows they are buying a counterfeit product or not. Non-deceptive counterfeits refer to products that are not intended to deceive the consumer into believing that they are purchasing an original product (Bian, & Moutinho,

2009, p. 369). The consumer is fully aware that the product they are purchasing is not manufactured by, marketed by, nor profiting the company that the product is imitating. Deceptive counterfeits, on the other hand, are intended to fool the consumer into believing that they are buying the genuine brand when they are buying a counterfeited product (Mavlanova & Benbunan-Fich, 2010, p. 80). The differentiating factor between the two types is the intention of the consumer to buy the real product or to buy the imitated one. This is an important point to grasp in this study about why consumers buy counterfeit products, because if they are not knowingly purchasing a counterfeit product, i.e. they are purchasing a deceptive counterfeit, and then the influence factors affecting their purchase decision are unrelated to this study.

Within the category of non-deceptive counterfeit products, there is a type of counterfeiting limited to the fashion and apparel industry which is referred to as “designer-inspired” (Tu, 2010, p.

420). This type of counterfeit profits off of the notion that the product consumers are purchasing is related to and/or similar to the original fashion design (Tu, 2010, p. 420). While the imitator is not trying to pass off the product as the original, and is therefore a non-deceptive counterfeiter, the product is nonetheless taken from another person’s design. Tu (2010, p. 420) refers to this in his research as “style piracy,” in which imitators seek to capitalize on the popularity or desirability of a designer’s original creative work. The study suggests that the growth of the fashion industry and the increasing public awareness of designer brands have led to an upsurge of this “style-piracy” category of counterfeiting (Tu, 2010).

Berry Berman (2008, p 191-192) classifies counterfeits into four different categories. He refers to the first type as a “knock-off,” “look alike,” or a “sound alike.” This first type of counterfeit is distinguished by the fact that consumers are aware they are buying a counterfeit good for one or

3 several of three reasons: (1) the price is significantly lower than that of an original, (2) the packaging does not compare to the packaging of the authentic good, and/or (3) the distribution channel is unusual. This type of counterfeiting is very typical with fashion, apparel, and accessory products and can often be bought in street vendors, online, or in many tourist shopping destinations. The second type of counterfeit category, according to Berman (2008, p. 191-192), is deceptive and is often referred to as “reverse engineering” or “tear down” counterfeiting. These products are produced either by a reverse analysis of the way the product was put together or through stolen blueprints or masters.

This type of counterfeiting is common with software, CDs, and DVDs. The third category occurs when outsourced suppliers continue to manufacture a product during a third shift that the outsourcing company is unaware of. Often referred to as “third shift” counterfeiting, this type is often very difficult to distinguish from the original as it was produced with the same machinery. The fourth and last category occurs when substandard products produced by outsourced manufactures are supposed to be disposed of or destroyed but instead are reclaimed and sold as legitimate “up to par” products

(Berman, 2008, p. 191-192).

2.2 Impacts of Counterfeiting

Regardless of how the counterfeit came into existence or whether or not the consumer is aware they are buying a counterfeit product, the societal impacts cannot be denied. In 2005, it was estimated by the Organization for Economic Cooperation and Development (OECD) that infringement of intellectual property rights worldwide caused a loss of $200 billion in jobs, taxes, and sales (Swami et al., 2009, p820). By 2006, the International Chamber of Commerce estimated that world-wide sales of counterfeited products could reach $650 billion per year (Berman, 2008, p. 192).

These figures alone are disturbing but it is difficult to attach realistic values to the underlying costs of counterfeiting because many of the costs cannot be quantitatively measured. While one can generally measure a company’s loss in sales or money spent on controlling counterfeiting activity, it is difficult to measure such things as the loss of brand distinctiveness. Counterfeiting has costs for consumers and legitimate manufacturers on many levels. For authentic producers, one of the main concerns about a growing counterfeit culture is that when consumers have bad experiences with knock-off products,

4 and they do not know their product is a fake, the value of the genuine brand declines in the eyes of consumers (Berman, 2008). Another main concern is that counterfeiters have an unfair advantage because they do not have any expenses related to: “promotion, trademark licensing, research and development, design and engineering costs, quality control, test marketing, customer support, warranty claims, or product recall expenses” (Berman, 2008, p. 192).

While many people may not care about the “petty cash” that multibillion dollar corporations are losing because of counterfeiters, there are many impacts that affect society as a whole. Losses of employment and government tax revenues as well as a significant amount of safety issues all come along with a growing counterfeit industry (Berman, 2008). As counterfeiting begins to spill over into pharmaceuticals and automotive parts, buying knock-off products can cost consumers their lives and is no longer just an issue of hurting companies’ sales targets. Counterfeit medicines seized at

European customs borders increased from 2005 to 2006 by nearly 400% (Cabezas, 2010, p. 180). The seizure of illegal counterfeit medicines became such a concern in the early 2000’s that in 2006 the

World Trade Organization (WTO) established the International Medical Products Anti-Counterfeiting

Taskforce (IMPACT) specifically to combat this growing health concern (Cabezas, 2010, p. 182). US government bodies are not taking the safety threat of counterfeits lightly.

Another issue, recently appearing more often in literature on counterfeiting, is where the money generated by counterfeited product sales is ending up. Research shows that terrorists and criminal organizations such as Al-Qaeda and the Mafia are being funded in part by sales of counterfeited merchandise (Furnham & Valgeirsson, 2007, p. 678). This is growing concern, especially because counterfeits are becoming more difficult to detect and because the internet is making it so much easier for counterfeit transactions to take place (Berman, 2008; Mavlonava &

Benbunan-Fich, 2010). As the industry matures and anti-counterfeit bodies increase legislation, counterfeiters are becoming cleverer and are finding new ways to avoid detection (Berman, 2008).

For example, cargo coming in from countries that are known to be red flags for counterfeiting, such as

China, is being shipped first to a third country that is less likely to do rigorous inspections, before they

5 enter the country in which they are intended to be sold. This reduces the chance of inspection and the cargo appears to be coming from a country not known for counterfeiting and is therefore deemed less suspicious upon arrival at its destination (Berman, 2008, p. 193).

The internet is a popular distribution channel for counterfeit merchandise because it allows sellers to be anonymous and because products can be easily disguised as authentic brands as the consumer cannot physically inspect the product before purchasing (Mavlanova & Benbunan-Fich,

2010). There are many deception schemes used by internet counterfeiters and common merchandise illegitimately sold in this way includes designer goods, electronics, and pharmaceutical products

(Mavlanova & Benbunan-Fich, 2010). Auction sites such as E-bay are fueling internet counterfeit sales (Berman, 2008, p.193). Although many such sites have policies against selling replicas it is extremely difficult to enforce and many sites rely solely on allowing buyers to post negative feedback on sellers’ profiles when such instances occur (Berman, 2008, p. 193). Unfortunately, this does not prevent counterfeit sellers from simply starting a new account under a different name and continuing to sell fake merchandise until they are reported again (Berman, 2008, p. 193). According to Berman

(2008, p. 193) a study conducted in 2006 showed that out of 300,000 Dior products and 150,000

Louis Vuitton products offered on E-bay within a six month period, ninety percent of them were counterfeits.

2.3 Historical Brand Aspects

According to Juggessur and Cohen (2009, p. 384), the idea of identifying with or distinguishing oneself through clothing brands dates back to the mid-nineteenth century when a couturier by the name of Worth designed garments in Paris for the Empress Eugine, the wife of

Napoleon III. At the time, designers would often copy gowns worn by royalty that they saw in paintings or sketches. In order to show that royal families were wearing authentic garments made by the prestigious designer, Worth began branding his designs. As the industrial revolution reached new heights and competition increased, designers realized the importance of protecting and differentiating their designs through branding (Juggessur & Cohen, 2009, 384-385). Today, brands continue to create

6 value which also encourages the demand for imitated brands or designs. Many studies fail to consider these underlying brand aspects that essentially create the platform for counterfeiting (Bian &

Moutinho, 2009) Therefore, it is important to understand why consumers value brand names the way that they do. Consumers buy into brands mostly because it is a way of defining their identity and expressing their desirability (Juggesur & Cohen, 2008). Because of the growing global recognition of fashion brands they hold social meaning and allow people to express certain characteristics through the material possessions they consume. High fashion brands for example, offer value through their image of being “at the forefront of design, quality, status, and fashion” (Juggesur, & Cohen, 2008, p.

383). Wearing particular brands can also be a way for people to identify with certain groups or to do exactly the opposite, by expressing one’s individuality (Juggesur & Cohen, 2008).

According to a study by Juggessur and Cohen (2008, p. 389), “it is only recently that dress has been treated as a language.” In a time before civilization people identified themselves and expressed their desirability in different ways. Take, for example, hunter-gatherer societies of the

Mesolithic period over ten thousand years ago. Social status and desirability were defined then by one’s ability to contribute resources to the community and provide for a family, which required strength, speed, or fertility (Hamilton, Milne, Walker, Burger & Brown, 2007). These physical characteristics in ancient societies defined one’s social status. Today, one’s ability to provide no longer depends on physical strength, but more so on mental capacity which cannot be physically expressed. So instead people show their ability to provide by what they consume. From a purely human nature point of view, buying expensive brands such as Rolex or Gucci is society’s way of expressing one’s ability to provide. From an evolutionary stand point, ability to provide translates into desirability. In other words, Juggessur and Cohen (2008, p.389) say in their article that “the display, purchase, use and consumption of goods acts as a social status cue for many individuals.”

Understanding the concept of brand consumption as a way to express one’s desirability sheds light on what may be driving consumers to purchase counterfeit goods, particularly fashion goods which are constantly acting as status cues. They allow consumers to identify themselves with groups they perceive to be elite, without the exclusivity created by the high prices and restricted distribution

7 channels offered by genuine brands. While many aspects of consumer purchasing behavior can be hypothesized to have certain theoretical evolutionary explanations, the conscious decision process by which consumers choose to buy counterfeit products requires further empirical research.

2.4 Inadequacies of Anti-Counterfeit Legislation

Anti-counterfeit legislation has slowly progressed over recent decades. Internationally there are still many flaws in anti-counterfeiting enforcement and past research has repeatedly suggested a need to address the inadequacies. The United States instituted the Tariff Act in 1930 to address concerns about trademark infringement by overseas manufacturers (Chaudhry & Walsh, 1996, p. 38).

It outlawed the importation of “identical or deceptively similar” (Chaudhry & Walsh, 1996, p.38) merchandise. Unfortunately, it only granted victims of trademark infringement the right to receive monetary damages, which were rarely awarded because of the prohibitive costs of pursuing international enforcement (Chaudhry & Walsh, 1996, p.38). In 1946, the Lahnam Act was passed giving courts the power to order violators to pay damages and destroy their merchandise (Chaudhry &

Walsh, 1996, p.38). It wasn’t until 1984, when the Trademark Counterfeiting Act was passed that criminal penalties were established for importers of illegal counterfeits (Chaudhry & Walsh, 1996, p.38). More specifically, violators could be fined up to $2 million and face up to 10 years in prison

(Chaudhry & Walsh, 1996, p. 38).

As United States legislation intensified, government bodies pressured the rest of the world to get on board to ensure competitive market forces. The WTO instituted the Trade Related Aspects of

Intellectual Property Rights (TRIPS) agreement obligating all WTO members to have domestic laws and enforcement mechanisms that comply with international intellectual property rights standards

(Sutherlin, 2009). Lea’s (2008) research claims that many global issues with intellectual property rights began with the establishment of the TRIPS agreement. The US claimed that the policies of the agreement were not being properly enforced in many developing nations and that the result was that their intellectual property was being “stolen, pirated, counterfeited, and infringed” (Lea, 2007, p.49).

India and China had long been regarded as “the worst intellectual property rights violators on the

8 planet” (Sutherlin, 2009, p. 404) according to an editorial in 1989 in the Christian Science Monitor.

The editorial estimated that piracy by these nations was costing the US more than $60 billion annually, a significant portion of which is due to fashion replicating. The US, Europe, and Japan have been the main advocates of intellectual property rights over the last two decades, particularly within the information technology, electronic, pharmaceutical, entertainment, medical, and bio-technology industries (Lea, 2007, p. 48). They continue to pressure the WTO for global enforcement and sanctions.

Part of the problem with stricter global enforcement of intellectual property rights and anti- counterfeit legislation is that huge emerging economies such as China and India are generating significant income through their counterfeiting industries. The concept of counterfeiting is deeply ingrained in Asian cultures as a completely acceptable form of business (Swift, 2003). A writer of a

US magazine was quoted in his article about counterfeit trade stating: “Counterfeiting is so ingrained in the Chinese business culture that the perpetrators seldom feel they're doing anything wrong. They make and sell products--CDs, clothing, toys, electronics, golf clubs--more cheaply than the brand- name guys, offering consumers a comparable product at a lower cost. What's wrong with that?”

(Swift, 2003, p.66).This is the attitude that many Asian counterfeit product business owners have and it is creating an uproar in Western societies who consider counterfeiting to be a very serious crime.

Awokuse and Yin published an article (2009) examining China’s intellectual property rights progression. According to the article, after establishing China’s first patent laws in 1985, trading nations labeled their efforts insufficient due to a lack of enforcement. China amended its patent system in 1992 and then again in 2000. These amendments were made in order to comply with the

TRIPS agreement so that China could become the newest member of the WTO in 2002 (Awokuse &

Yin, 2009). While China has been repeatedly accused of failing to enforce intellectual property rights standards, it is important to keep in mind the novelty of this concept in Chinese culture. Significant strides are being made by the Chinese government to improve intellectual property rights enforcement. The government has established the Compendium of China National Intellectual

Property specifically to develop a five year plan to “drastically raise the level of intellectual property,

9 make intellectual property rights utilization further effective, prominently improve intellectual property rights protection, and greatly enhance public awareness about intellectual property throughout society” (Awokuse & Yin, 2009, p.1095).

There is an ongoing debate in current literature regarding the future hopes for better enforcement of anti-counterfeit legislation not only in China, but around the world. Some would argue that recent changes in global policies are looking more promising while others maintain that legal protection against counterfeiting is far from acceptable. It is clear however, that counterfeiting continues to grow and that it is currently at an all-time high, particularly in the fashion industry. Tu’s research (2010) claims that part of the underlying cause for this is that fashion and apparel manufacturers in the US are strongly lacking adequate protection against counterfeiters. According to

Tu (2010), despite the progressive global anti-counterfeit legislation, the United States offers very limited protection under US copyright and trademark laws for utilitarian works. His article states that copyright laws are generally limited only to non-utilitarian designs (Tu, 2010, p. 423). This means that anyone who wants to protect a design that falls under the category of “utilitarian,” which includes such things as clothing, must seek protection through other means (Tu, 2010, p. 423). Many clothing designers have therefore turned to trademark laws which have also provided them limited protection

(Tu, 2010). Trademark laws, although they are extended to utilitarian designs, only offer protection for those designs that have reached a certain level of brand recognition (Tu, 2010, p. 423). Tu (2010) maintains that neither of these means of protection is sufficient and that there is a need for greater protection of utilitarian designs in order to provide adequate rights for fashion designers. The purpose of copyright protection is to “promote the progress of science and useful arts” (Tu, 2010, p. 423) while the purpose of trademark protection is to “protect against unfair competition” (Tu, 2010, p.

423). Tu (2010) argues that neither one of these goals is being sufficiently met by copyright nor trademark laws in the fashion and apparel industry and that a more comprehensive plan is needed. On the other hand, reports released by the U.S. Customs and Border Protection and U.S. Immigration and

Customs Enforcement (ICE) claim that, while in the past most apparel brand companies have been left to handle their own counterfeit measures by taking civil action in courts, the US government is

10 contributing new levels of commitment by increasing protection at US borders (Ellis, 2010). The article quotes ICE director, John T. Morton stating that “2010 was a very successful year. The protection of intellectual property is a top priority for Homeland Security Investigations, as counterfeit products represent a triple threat by delivering shoddy and sometimes dangerous goods into commerce, by funding organized criminal activities and by denying Americans good-paying jobs” (Ellis, 2010, p.6).

In summary, there are several main points that are necessary for a complete understanding of this research, who it impacts, and how the results of this study could potentially provide solutions.

Until recently there is a lack of research in this field that focuses on solutions to counterfeiting from the perspective of understanding what variables are driving the consumer demand for counterfeit products. The research that does exist in this area is not specific to the fashion industry which offers a unique set of characteristics and predictably has different purchase decision influence factors than other types of counterfeited products. Considering that fashion items are globally among the most counterfeited products, this study fills a hole in existing literature and the results of this study will provide practical implications for genuine fashion brand companies, manufacturers and marketers as well as original fashion designers all over the world. Furthermore, this research is important to society as a whole because of the negative impacts that counterfeiting has on the economy. Losses in employment and government tax revenues are a major concern, particularly in the United States, and fashion counterfeiting accounts for a significant portion of the problem. Government anti-counterfeit legislation, although it is reaching new heights, is not sufficiently solving the problem. Issues of global enforcement agencies and differences in cultural business norms around the world are standing in the way of any viable supply side solutions. Therefore, this study offers an alternative approach to stricter anti-counterfeit enforcement by offering insights about consumer demand for counterfeit products in an industry infamous for knockoffs: the fashion industry. By understanding and being able to manipulate the variables that influence consumers’ counterfeit fashion purchase decisions, legitimate fashion companies will be better equipped to tackle the issue by understanding their

11 consumers and setting up more effective marketing strategies that reduce consumer demand for replicated fashion items.

2.5 Structural Overview

This study is divided into five main sections. The Background and Rational, concludes with this structural overview, and is intended to summarize all relevant background information.

Additionally it explains the relevance of the research question primarily to legitimate fashion brand companies but also to consumers. This research is of significant importance for legitimate brand companies because it offers an explanation for the consumer behavior which results in a significant loss of their sales. It also offers marketers of legitimate brands information on which to build marketing techniques to address the issue of counterfeiting. For consumers, this research highlights the extent of the damages that counterfeit products cause the community, economy, and even personal safety. Section three is comprised of the Literature Review which summarizes what other research has concluded about the research topic. This helps establish the hypotheses for the results of this study.

Unlike the Background and Rational section which encompasses more general information about the topic of counterfeiting, branding and fashion, the Literature Review only discusses information found in existing literature that is directly relevant to the research question. It should be noted that a systematic approach to the Literature Review has been conducted, which identifies and lists all databases, key words, and methods that were chosen to be used to explore the existing literature.

Section four follows with a description of the Methodology. Due to the amount of relevant literature found during the Literature Review process this study is conducted from an explanatory approach in which the hypothesized variables are tested for a correlation with consumer willingness to purchase a counterfeit fashion good. These hypotheses are tested in the form of a survey from which the data is quantitatively analyzed. The Methodology section describes step by step exactly how the research aspect of this study is carried out. Section five, Findings and Discussion, gives an analysis of the results of this research. It refers back to the literature found on this topic and compares and contrasts the results with that of other studies. This is an important section because it explains and interprets the findings of the study. This study comes to a close with the Conclusion section in which the limitations

12 and any weaknesses of the study are discussed and suggests any further research that should be done in order to fill in the missing pieces of this area of research.

3.0 LITERATURE REVIEW

It is of significant importance to this research to systematically approach a review of the relevant literature in the field of counterfeited products in the fashion industry. Counterfeiting has been an ongoing issue for legitimate manufacturers since the 1970’s (Bian, & Moutinho, 2009, p.

368). Since then, many companies have invested millions of dollars into developing their brand image only to have their profits reduced by copycat designers and knockoff enthusiasts. This has encouraged scholars to research the underlying causes behind this growing phenomenon. A significant portion of the research in this field focuses on the economic burden of counterfeiting as well as global intellectual property rights policies and how they apply to various products and industries. More recently researchers have shifted some of their focus to gaining an understanding of consumer behavior that is driving the demand for counterfeited goods. No industry can exist without consumer demand. This applies to the counterfeited goods industry just as it does to any other. Consumers are willing and able to purchase counterfeit goods and the demand is being met by suppliers all over the world. While government policies and anti-counterfeit legislation are at on all time high to combat the revenue losses faced by legitimate companies, an alternative approach to this issue can only be achieved through an understanding of the influence factors of consumer counterfeit purchase decisions.

3.1 Scope and Reduction of Information Biases

Due to the fact that there is a considerable amount of research about counterfeiting, the systematic literature review has two main purposes for this study. First, it helps to define the scope of the readings. There are many disciplines that cover different aspects of this topic including issues of law, ethics, global enforcement institutions, and various other industries being damaged by counterfeited trade. While all aspects of counterfeiting are indirectly relevant to the research, a full

13 review of all surrounding literature is neither feasible nor necessary for a better understanding of why consumers choose to buy counterfeit fashion items. Therefore, for the purpose of this study, the only sources used are sources directly related to the topics included in my outline or used to find appropriate research methods. This allows for a more selective process of searching for relevant information. The second purpose of the systematic literature review is to help reduce biases in the research process by first establishing my research question and defining inclusion criteria based on the sub topics of the outline. Literature reviews lacking a systematic approach often result in irrelevant readings, biased choice of literature, and little source variety.

3.2 Search Method

Two online search databases were used to find relevant literature about counterfeiting in the fashion industry: Science Direct and EBSCO Host. EBSCO Host offers access to Academic Search

Premier, Business Source Premier and several other databases. These two online search programs enable access to multidisciplinary academic texts. Because of the broad scope and encompassing variety of literature available through these databases the search was limited to these two search engines. Following the topics and subtopics of the outline of this study the search was conducted by investigating the literature associated with the following key words:

 Counterfeit (and) culture  Brand (and) identity

 Counterfeit (and) fashion  Counterfeit products

 Counterfeit (and) internet  Knock-offs

 Counterfeit (and) China  Knock-offs (and) fashion

 Counterfeits  Copyright

 Counterfeiting  Trademark

 Brand value  Intellectual Property Rights

 Fashion (and) apparel  Counterfeit (and) Variables

 Counterfeit (and) Influence  Counterfeit purchase decisions

Once a full investigation of the literature associated with the key words mentioned above was complete, a careful consideration of each article’s relevance to the topic of this research was conducted and all relevant information was sorted into pages of notes organized by references.

Additionally, certain periodicals were used to research appropriate data collection methods for this type of study. All articles are drawn from the following journals, publications, and government web pages:

 World development  The Journal of Socio-

 Business Horizons Economics

 Journal of Business Research  Journal of Brand Management

 Pharmaceutical Policy and Law  International Journal of

 Ethical and Moral Practice Electronic Commerce

 Webster’s Online Dictionary  Global Development and

 The Free Dictionary by Farflex Technology

 Texas Intellectual Property Law  Perspectives on Global

Journal Development & Technology

 The Royal Society  Field Methods Periodical

 Psychological Inquiry  Cyber-psychology, Behavior,

 Ethical Theory and Moral and Social Networking

Practice  Journal of Social Issues

 Journal of Consumer Research  U.S. Census Bureau

 The Columbia Journal of World

Business

In addition to these academic texts, two magazine articles were accessed in order to use quotations that illustrate a point. Two of the sources above are online dictionaries from which certain

15 elements were drawn to define terms used in this study. Some articles were found by viewing the reference list of other relevant articles. It should also be noted that there are several articles that are cited in other relevant studies that may have provided additional information about this topic but could not be accessed.

3.3 Content Analysis

The primary purpose of this study is to determine what variables influence a consumer’s decision to purchase a non-deceptive fashion counterfeit good. In order to strategically test for the correct variables it is important first to define what is meant by a fashion counterfeit good. There are several definitions from which this study draws certain components. Webster’s Online Dictionary defines the fashion industry as “the makers and sellers of fashionable clothing” (“Fashion Industry,”

2006). However, it is important to note that clothing is not the only type of fashion item to be considered in this study. As defined in an online encyclopedia fashion “is any mode of dressing or adornment that is popular during a particular time or in a particular place” (“Fashion,” 2007).

Therefore, for the purpose of this study, a counterfeit fashion item is defined as any dress or adornment item that infringes upon intellectual property rights including but not limited to footwear, apparel, and accessories. Using this definition this study can test if certain variables influence a consumer’s choice to knowingly purchase such an item.

3.3.1 Consumers are more willing to purchase counterfeit fashion items

The amount of literature in this field that pertains specifically to the fashion industry is surprisingly low considering that studies show that consumers are more willing to purchase counterfeit fashion items than many other types of products. Shown below are the results of two surveys conducted in two different studies that show peoples willingness to buy different kinds of counterfeit goods. In both studies, clothes rank among the highest of counterfeit items consumers are willing to buy. Handbags, watches, and shoes all rank among the top items consumers are willing to purchase (Swami et al., 2009, p. 822; Furnham & Valgeirsson, 2007, p. 680).

Figure 1: List of items on the willingness to buy counterfeit goods scale and their ratings (Swami, et al, 2009, p. 822)

Figure 2: Willingness to buy different counterfeit products (Furnham, & Valgeirsson, 2007, p. 680)

Existing literature clearly shows that consumers are generally more willing to purchase counterfeit fashion items than other types of counterfeit items. This is a red flag for legitimate fashion companies. What this means, is that there is something unique about fashion items that influence consumers’ willingness to purchase counterfeits. What those variables are and how they differ from those that influence consumer’s decisions to purchase other types of counterfeit goods is of significant importance.

3.3.2 Unique characteristics of counterfeit fashion

The majority of relevant research in this field applies to general counterfeit products.

However, research by Juggessur and Cohen (2008) focuses specifically on counterfeiting in the high- end fashion industry. The article draws several conclusions that are relevant to this study. The authors explore non-deceptive counterfeiting of high-end fashion brands which they define as “brands that hold considerable intangible worth and have enduring positive brand images deemed as being at the forefront of design, quality, status and fashion” (Juggessur & Cohen, 2008, p. 384). While this study is not limited only to high-end fashion brands, some of the findings of Juggessur and Cohen are applicable to the entire fashion industry. For example, the authors point out that consumers are attracted to certain fashion brands because of what they refer to as “the theory of lifestyle branding.”

This theory suggests that brands are associated with images of certain lifestyles with which various consumer segments identify or aspire to identify (Juggessur & Cohen, 2008, p. 382). Because of this association, counterfeit fashion goods are able to offer the same value. Consumers can appear to have the lifestyles associated with certain brands by purchasing a counterfeit version. This points to the logical conclusion that consumers are more likely to purchase a counterfeit good if the brand it is imitating is one associated with the lifestyle the consumer lives or aspires to live (Juggesuer & Cohen,

2008).

This article also points out a very important aspect of the fashion industry that does not apply to other industries. They define fashion as “a result of ever-changing cultural shifts in preferences, tastes, and choices” (Juggesuer & Cohen, 2008, p. 384). Due to these rapidly changing shifts in what

18 is considered fashionable, items that are at one point sought after and highly valued have only a limited time before they are deemed out of style and lose value. Once a fashion is first introduced to a market the process of adoption begins. With high-end fashion this typically starts with upper class consumer segments and then “trickles down,” as people who want to appear to have the upper class lifestyle that the brand portrays begin to imitate (Juggessur & Cohen, 2008, p. 384). As more people begin to imitate, the more common and non-exclusive the fashion becomes which deteriorates its value (Juggessur & Cohen, 2008). This offers an interesting opportunity for fashion counterfeiters.

Consumers know that fashion goods will only be fashionable for a limited amount of time. For most people who cannot afford to buy legitimate brands every time the new “in-style product” changes, counterfeit prices allow them to appear to have the exclusively of expensive fashionable brands at all times which they can afford to never wear again once the style is no longer in fashion. This counterfeit imitation of new fashions occurs so quickly now that the entire process of mass adoption and value deterioration happens in constant waves keeping legitimate brand manufacturers on their toes and pressuring them to constantly create new innovative designs that have not yet been adopted by the general public and imitated by counterfeiters (Juggessur & Cohen, 2008). This aspect of fashion brands is the foundation for the first hypothesis of the study. It suggests that the amount of time that has expired since the fashion good was introduced to the market or whether or not the fashion is still considered to be “in style,” could impact a consumer’s willingness to purchase the counterfeit version of that item.

Hypothesis 1: Being “in style” has a positive influence on consumer willingness to purchase counterfeit fashion items.

3.3.3 Variables that Influence Counterfeit Purchase Decisions

There have been several studies that are not specific to the fashion industry that aim to determine what variables influence consumers to purchase general counterfeit items. Comparing the results of these studies to the variables that influence fashion counterfeit purchase decisions may add interesting insights. Several studies have focused on which demographic groups are most likely to

19 purchase counterfeit merchandise. Other studies have determined certain personality traits that determine the likeliness that a consumer would purchase a counterfeit good. Apart from demographics and personality traits several influence factors have been discovered in past research including personal values, attitudes toward counterfeiting and various consumption variables. It is also important to note that several scales have been created in past studies to measure such things as consumer attitudes toward counterfeits, consumer’s material values, and consumer’s personality characteristics. It is essential to understand the influence that each of these variables has had on consumers counterfeit purchase decisions in past studies, so that it can be applied and compared to items of the fashion industry. The scales that have been constructed in past research are useful tools on which to build the research methods of this study. Using these scales may prove helpful by drawing conclusions about the relationships between participants’ scores and their willingness to purchase counterfeit fashion goods.

3.3.3.1 Demographic Variables

As previously stated, demographic influences have been the primary focus of several studies.

While some research has determined that certain demographic groups are no more likely to purchase counterfeit goods than others, other studies reveal different results. Bian and Moutinho’s research

(2009) explores the effects of four demographic variables on the likeness to consider the purchase of a counterfeit branded product. Their study determined that neither age, sex, income, nor educational attainment influenced their subject’s willingness to purchase counterfeit goods (Bian and Moutinho,

2009, p. 375). The authors disclose that their findings directly contradict the findings of other studies which found that people of higher educational attainment are more likely to purchase counterfeit merchandise (Bian and Moutinho, 2009, p. 375). Their findings also contradict studies in the early

2000s that determined that men and women are more likely to buy certain types of counterfeited goods such as CD’s versus clothing (Swami et al., 2009, p. 820). It has also been reported in several studies that younger demographic groups are more likely to purchase counterfeit items (Swami et al.,

2009, p. 821). Bian and Moutinho’s findings are questionable considering that other studies found

20 correlations age, sex, income, and educational attainment and consumer likeliness to purchase counterfeit goods.

The question then is whether or not this applies to fashion counterfeit items as well. Younger demographic groups have already been shown to be more likely to purchase general counterfeit goods. Some reasons for this could be that younger demographics do not have the financial means to afford genuine brands and second or perhaps that younger age groups have less traditionalist values and do not see anything wrong with purchasing counterfeit goods. Both of these assumptions can be applied to fashion counterfeit items as well and if true, would suggest younger generations are more likely to purchase counterfeit fashion items as well. Furthermore, one might assume that younger generations are more likely to buy counterfeit fashion items because they are still trying out different identities which ties into the concept of lifestyle branding (Juggessur and Cohen, 2008). This idea deserves further exploration because it seems to go hand in hand with the fact that younger generations are more dynamic with their shifts in fashion styles. As they grow up and develop more of a concrete self-image their desire to try different fashions decreases which lowers their need for low cost, disposable fashion. For these reasons it can be hypothesized that younger demographic groups are more likely to purchase counterfeit fashion items.

Based on the amount of fashion advertising effort targeting females the fashion industry appeals more to women than to men. Bian and Moutinho (2009) found that women are more likely than men to purchase counterfeit fashion items when compared with other types of counterfeit items such as CDs and DVDs. Following such logic it is hypothesized that females are more likely to purchase counterfeit fashion items than men. Consumer income has obvious implications on one’s likeliness to purchase counterfeit fashion items. Authentic fashion brands can be very expensive, often prohibitively expensive for consumers with lower incomes. Therefore one can conclude that consumers with lower income are more likely to purchase counterfeit fashion items because they cannot afford to buy the authentic brands. Educational attainment has many latent variables to be considered such as what a person is educated in, if they are educated because they come from a

21 wealthy background, or if they are older because they have spent many years in school. Some or all of these latent variables could influence the counterfeit purchase decision. For this reason, making a hypothesis about whether or not education level and consumer likeliness to purchase counterfeit fashion items has a correlation is difficult. Higher levels of education are typically associated with higher income and therefore if people with more income are less likely to purchase counterfeit fashion then it can be hypothesized that people with higher education are also less likely to purchase counterfeit fashion items.

Hypothesis 2: There is a negative correlation between consumer age and consumer willingness to purchase counterfeit fashion items.

Hypothesis 3: Females are more willing to purchase counterfeit fashion items than men.

Hypothesis 4: There is a negative correlation between consumer income and consumer willingness to purchase counterfeit fashion items.

Hypothesis 5: There is a negative correlation between level of education and consumer willingness to purchase a counterfeit fashion items.

3.3.3.2 Values and Attitudes Variables

These variables can be grouped into three subcategories: materialistic values, other personal values, and attitudes and beliefs. Furnham and Valgeirsson (2007) studied how materialistic values and other personal values influence a person’s willingness to buy counterfeit products. In order to evaluate an individual’s materialistic values their study makes use of the Richins and Dawson

Materialism Scale created in 1992. It measures the value an individual places on materialism by inquiring about three dimensions of their personality: happiness, success, and centrality (Richins &

Dawson, 1992). Furnham and Valgeirsson (2007, p. 678) define materialism as “the preoccupation with the pursuit of material objects while neglecting mental and spiritual aspects of life.” In order to evaluate their subject’s other personal values they used the Schwarz Value Model created in 1994,

22 which ranks individuals on ten aspects of personal values: power, achievement, hedonism, stimulation, self-direction, universalism, benevolence, tradition, conformity, and security (Schwartz,

1994). The hypotheses of their study estimated that materialism and the conformity and universalism aspects of personal values, all have an influence on an individual’s willingness to purchase a counterfeit good. Universalism is defined as “understanding, appreciation, tolerance, and protection for the welfare of all people and for nature,” and conformity as “involves restraints of actions that violate social expectations or norms” (Furnham and Valgeirsson, 2007, p. 679). The results of the study half support and half contradict the hypotheses of the researchers. The centrality aspect of materialism proved to have a negative relationship with ones willingness to purchase a counterfeit good (Furnham and Valgeirsson, 2007, p. 682). In other words, those who score high on the centrality factor of materialism are generally less likely to purchase a counterfeit good. This confirmed the aspect of their hypothesis that materialism does influence willingness to buy counterfeits and the authors explained this relationship by assuming this could be related to the fact that people who are more materialistic may be more inclined to own an authentic brand than a fake one. Universalism and conformity aspects of personal values both proved to have no relationship with an individual’s willingness to purchase a counterfeit good which contradicts the hypothesis of their study (Furnham and Valgeirsson, 2007, p. 683). The tradition aspect of personal values however, defined as “respect, commitment, and acceptance of customs and ideas that traditional culture and religion provide,” has a negative correlation with willingness to buy counterfeit goods (Furnham and Valgeirsson, 2007, p.

683). In summary the results of their study show that materialistic and traditional values have an influence on an individual’s decision to purchase counterfeit goods.

Each of the three aspects of materialism (centrality, happiness, and success) taken from the

Richins and Dawson Scale (1992), has certain implications for this study and how it relates to fashion counterfeit items. The centrality aspect of materialism reflects the extent to which material things and possessions are placed in the center of one’s life (Furnham & Valgeirsson, 2007, p. 678). People whose values reflect high levels of centrality materialism have been shown in past studies to be less likely to purchase general counterfeit goods (Furnham & Valgeirsson, 2007, p. 678). Their lifestyle,

23 behavior, and goals are all driven by a desire to own material possessions (Richins & Dawson, 1992, p. 304). Such people are more susceptible to advertising and desire exclusivity and brand names

(Furnham & Valgeirsson, 2007, p. 682). According to Furnham and Valgeirsson (2007, p. 682) “it matters to them that they possess items that are authentic, desirable and exclusive.” The fashion industry is heavily advertised and brand names carry connotations of desirability and exclusivity.

Therefore it is hypothesized that centrality materialism has a negative correlation with a consumer’s willingness to purchase counterfeit fashion items, just as it does with general counterfeit items.

The happiness aspect of materialism reflects how much the material possessions that one consumes impact one’s personal satisfaction and wellbeing (Furnham & Valgeirsson, 2007, p. 678).

For such consumers, their material possessions are the greatest source of both satisfaction and dissatisfaction. They measure their personal happiness and social progress by what they own and rarely pursue happiness through other means (Richins & Dawson, 1992, p. 304). However, according to Furnham & Valgeirsson (2007, p. 682) their happiness in consuming is relatively unrelated to quality or brand names. “For some, buying counterfeit products makes them happy while for others buying authentic brands makes them happy” (Furham & Valgeirsson, 2007, p. 682). Furnham and

Valgeirsson’s (2007, p. 682) findings suggest that there is no relationship between the happiness aspect of materialism and a consumer’s likeliness to purchase counterfeit goods. If this aspect of materialism is independent of quality and name brands then this is predicted to be true for fashion items as well. Therefore this study hypothesizes that there is no correlation between happiness materialism and a consumer’s likeliness to purchase counterfeit fashion items.

People whose values reflect success materialism judge success by the quantity and quality of possessions that one owns (Furnham and Valgeirsson, 2007, p. 678). They feel that people are successful if the possessions that they own project a desirable self-image and they “value possessions for the money they cost rather than by the satisfactions they yield” (Richins & Dawson, 1992, p. 304).

For this reason Furnham and Valgiersson’s (2007) results are surprising. Their data revealed that such people are no more or less likely to purchase counterfeit items (Furnham and Valgeirsson, 2007,

24 p. 683). With fashion counterfeit goods however this study hypothesizes different results. People with high levels of success materialism are concerned with their self-image which they project by consuming expensive material possessions. Following such logic they would want to own expensive authentic fashion brands and would therefore is less willing to purchase counterfeit fashion items.

Therefore this study hypothesizes that success materialism is negatively correlated with consumer willingness to purchase counterfeit fashion items.

Hypothesis 6: Centrality materialism has a negative correlation with consumer willingness to purchase counterfeit fashion items.

Hypothesis 7: Happiness materialism has no correlation with consumer willingness to purchase counterfeit fashion items.

Hypothesis 8: Success materialism has a negative correlation with consumer willingness to purchase counterfeit fashion items.

In addition to materialistic values, Furnham and Valgeirsson (2007) explore how other personal values influence consumers’ counterfeit purchase decisions. They use the Schwarz Value

Scale to correlate consumer willingness to purchase counterfeit goods with an individual’s rank on ten different aspects of their personal values: power, achievement, hedonism, stimulation, self-direction, universalism, benevolence, tradition, conformity, and security (Schwartz, 1994). They found that tradition is the only one of the Schwartz Value Scale’s ten aspects of personal values that predicts consumer willingness to purchase counterfeit items (Furnham & Valgeirsson, 2007, p. 684). Those with little commitment to traditional customs and religious ideas are more inclined to purchase counterfeit merchandise (Furnham & Valgeirsson, 2007, p. 684). This study hypothesizes this applies to all counterfeit items including fashion. The following personal values, which act as indicators as to how high an individual scores on each of the ten categories of personal values in the Schwartz Value

Scale (Schwartz, 1994), are hypothesized to influence a consumers counterfeit fashion purchase

25 decision: need to belong, need for an exciting life, need for wealth, spirituality, respect for tradition, need for social recognition, honesty, desire to preserve public image, obedience, self-indulgence, and observing social norms. How these values were chosen is explained in further detail in the

Methodology section.

Hypothesis 9: Need to belong, need for an exciting life, need for wealth, spirituality, respect for tradition, need for social recognition, honesty, desire to preserve public image, obedience, self- indulgence, and observing social norms all influence consumer likeliness to purchase counterfeit fashion items.

Another study explores the relationship between personality traits and willingness to purchase counterfeit merchandise based on the Big Five framework: agreeableness, conscientiousness, emotional stability, openness, and extraversion (Swami et al., 2009). Participants of their study were given a score for each of their personality traits based on their answers to a survey. They were then given a second survey in which they rated their willingness to purchase various counterfeit goods. The findings indicate that regardless of personality type, individual’s scores very similarly on their willingness to purchase counterfeit goods, with the exception of a slightly higher score for individuals with high “openness” personalities (Swami et al., 2009). This points to the conclusion that Big Five personality traits have little influence over an individual’s decision to buy counterfeit goods.

This can likely be attributed to the fact that Big Five personality traits lack stability (John &

Naumann, 2010). To claim that someone has a certain personality and be able to test that against their likeliness to do anything is very subjective. One might show indications of being extraverted one environment and completely introverted in another. The criticisms associated with the Big Five personality tests have been documented for many years. Some argue that one’s personality is highly dynamic over a person’s life span and that there are much more than five aspects of one’s personality to consider (John & Naumann, 2010). For these reasons and because the results of Swami, Chamorro-

Premuzic and Furnham’s (2009) study indicate no relationship between the Big Five framework and a

26 consumer’s willingness to purchase counterfeit merchandise, this element will not be examined in this study.

Furnham and Valgeirsson (2007) explored consumers’ attitudes toward law and order, beliefs about the value of counterfeit goods, and attitudes toward their past experiences with counterfeit goods. As with the other variables they tested each of these for a correlation with consumer willingness to purchase counterfeit items. The results of the study show that the attitudes and beliefs variables do predict willingness to purchase counterfeit goods (Furnham and Valgeirsson, 2007, p.

684). Each variable revealed fairly predictable results. People who feel that counterfeit law and order is insufficient and that it is dangerous to society are typically not willing to purchase counterfeit items.

People who feel that counterfeit goods offer good value are usually willing to purchase counterfeit items and people who have had positive experiences with counterfeits in the past are also more likely to purchase counterfeit items. While these results seem fairly predictable they are important as they indicate that people who can be convinced that counterfeiting laws should be strengthened or that counterfeits typically offer lower quality will be less likely to consider purchasing a counterfeit good.

They also indicate that if a consumer has a bad experience with counterfeits they will be less likely to purchase one again. This has implications for genuine brand companies suggesting they focus some of their anti-counterfeit strategies on consumer awareness. Swami, Chamorro-Premuzic and Furnham

(2009) replicated this portion of Furnham and Valgiersson’s (2007) study which yielded similar results; attitudes toward law and order having the most impact. It is hypothesized that these variables will show the same relationship with consumer willingness to purchase counterfeit fashion items because if an individual feels strongly that counterfeits do not offer better value, or that anti- counterfeiting laws should be strengthened then they are unlikely to purchase any type of counterfeit merchandise including fashion items.

Hypothesis 10: Attitudes toward the inadequacies of counterfeit law and order has a negative relationship with willingness to purchase counterfeit fashion items.

Hypothesis 11: Attitudes toward the value of counterfeits has a positive correlation with willingness to purchase counterfeit fashion items.

Hypothesis 12: Attitudes toward experiences with counterfeits has a positive correlation with willingness to purchase counterfeit fashion items.

3.3.3.3 Consumption variables

In addition to demographic variables, Bian and Moutinho’s research (2009) explores several other influence factors including consumer perceived brand image, perceived risk, product knowledge, and product involvement. Their study focuses on characteristics of the purchasing process, the product itself and how those influence consumers’ counterfeit purchase decisions. There is high product knowledge when consumers have more information about the product itself and the alternative products available to them allowing them to easily compare and make well informed evaluations (Bian & Moutinho, 2009, p. 369). The authors hypothesized that a negative relationship between product knowledge and willingness to purchase the counterfeit item exists but their results fail to confirm the hypothesis (Bian & Moutinho, 2009). Their discussion suggests that it really depends on the type of counterfeit brand or product. In their study, for example, they test this relationship for both Rolex and Gucci watches. In the case of the Gucci watches, which are valued more for their fashion connotation than for top notch quality and features, consumers with greater product knowledge know that watch technology is far enough advanced that a counterfeit Gucci watch would offer just as accurate of time telling as any other watch, while still obtaining the value offered by the brand name. Therefore the consumer, in the case of the Gucci watches, is more likely to buy the counterfeit version when product knowledge is high (Bian & Moutinho, 2009, p. 373).

However, in the case of the Rolex watches, consumers with high product knowledge are aware of the top quality and high performance offered by Rolex watches, which is extremely difficult to imitate.

Therefore, in this case, the more product knowledge the consumer has, the less likely the consumer is to buy a counterfeit version (Bian & Moutinho, 2009, p. 373). Because this study is about fashion

28 items it can be linked to the findings in the Gucci watch case. Gucci watches are not valued for high performance and its image value can easily be imitated by counterfeiters. Therefore it is hypothesized, like in the case of the Gucci watches, that high product knowledge positively influences consumer likeliness to purchase counterfeit fashion goods.

Hypothesis 13: High product knowledge positively influences consumer likeliness to purchase counterfeit fashion items.

Product involvement is defined as the “depth, complexity and extensiveness of cognitive and behavioral processes during the consumer choice process” (Bian & Moutinho, 2009, p. 369). Products or brands have high product involvement when consumers carefully weigh their alternatives and examine their features (Bian & Moutinho, 2009, p. 369). Although the authors hypothesized that goods with higher product involvement would have a negative relationship with a consumer’s willingness to buy a counterfeit good their results showed that product involvement had very little influence (Bian & Moutinho, 2009, p. 373). These results were surprising and the researchers attribute them to limitations of the study suggesting that they should have controlled for different uses or purposes to get their expected results (Bian & Moutinho, 2009, p. 373). Logically speaking, if a consumer is going to invest time and energy into evaluating and analyzing the pros and cons of a product, they are likely to conclude that authentic brands, which offer higher quality, would be a better investment. This holds true for fashion items as well. If a consumer is highly involved in a purchasing decision then it is likely that they are not looking for a cheap low quality alternative. After careful analysis, authentic fashion brands clearly possess higher quality and better features and would therefore be chosen over the counterfeit version. Therefore, it is hypothesized that purchasing decisions which receive a high degree of product involvement are likely to result in purchasing authentic fashion brands over the knockoff and therefore high product involvement would have a negative influence on consumer likeliness to purchase counterfeit fashion items.

Hypothesis 14: High product Involvement negatively influences consumer likeliness to purchase counterfeit fashion items.

According to Bian and Moutinho (2009, p. 369-370) there are three different aspects of brand image: brand personality, perceived product attributes, and perceived benefits. The first aspect, brand personality, is about the consumers’ ability to identify with the brand either by differentiating oneself or by being part of, or aspiring to be a part of, a group of people associated with the brand (Bian &

Moutinho, 2009, p. 369). This is related to a concept discussed earlier about lifestyle branding, in which brands portray a certain lifestyle or typical user with which consumers chose to identify

(Juggessur & Cohen, 2008, p. 382). The authors correctly hypothesized that a positive brand personality increases a consumer’s likeliness to buy the counterfeit product and, in fact, this factor had one of the highest influences both for Gucci and Rolex watches in their study (Bian, & Moutinho,

2009, p. 374). The second aspect, perceived product attributes is rather self-explanatory. The more features a product is perceived to have, the higher its perceived product attributes (Bian & Moutinho,

2009, p. 370). The authors correctly hypothesized that there is a positive relationship between willingness to buy a counterfeit product and perceived product attributes (Bian & Moutinho, 2009). It should be noted, however, that this factor has less of an influence on the counterfeit purchase decision than brand personality and perceived benefit (Bian & Moutinho, 2009, p. 374). With counterfeit fashion items, if it fits comfortably or is versatile enough to wear in different environments then those attributes are likely to positively influence the consumer to purchase it. The third aspect, perceived benefit, involves the previous two aspects of brand image and can be summarized simply as the perception the consumer has on “what the product can do for them” (Bian, & Moutinho, 2009, p.

370). In the case of fashion items, consumers may seek certain benefits such as improved popularity, appearing to have money and style, fitting in with a certain crowd, looking attractive, etc. Bian and

Moutinho state (2009, p. 370) that consumers who buy counterfeits, believe that they are getting the same benefits for a fraction of the price. In the case of each aspect of brand image, it is hypothesized that the consumption variables will show the same relationship with consumer willingness to purchase counterfeit fashion items as they show with general counterfeit items.

Hypothesis 15: Positive brand personality positively influences consumer likeliness to purchase counterfeit fashion items.

Hypothesis 16: High perceived product attributes positively influences consumer likeliness to purchase counterfeit fashion items.

Hypothesis 17: High perceived benefit positively influences consumer likeliness to purchase counterfeit fashion items.

The last influence factor explored in Bian and Moutinho’s study (2009, p. 370) is perceived risk. Perceived risk is broken down into financial and social risk. Financial risk is when a consumer bears a financial burden if, for example, he or she cannot return the product or if there is uncertainty that the product will perform. The social risks involve the risk of damaging one’s image, for example if one’s peers might look down on them for purchasing a counterfeit good (Bian & Moutinho, 2009, p.

370). In the case of the Gucci watches, which are a fashion item and therefore assumed to be a better predictor of the counterfeit fashion results, both financial risk and social risk are negative predictors of the influence factors of a consumer’s willingness to purchase a counterfeit good (Bian & Moutinho,

2009, p. 375). This means that if there is high financial or social risk, consumers are less likely to purchase a counterfeit. For example, if consumers cannot check to see if a counterfeit product works before they purchase it, there is high financial risk and the consumer is less likely to buy it. In terms of social risk, if a counterfeit item poorly imitates the original brand, a consumer will be less likely to purchase it because it is more obvious to one’s peers that they have purchased a fake. In the case of fashion items it is hypothesized that financial risk will negatively influence consumer likeliness to purchase fashion counterfeit items because there is the risk that it may not fit or look how the consumer expects and if one is unable to return it, it is likely to influence to consumer not to purchase it. In most counterfeit purchasing channels returning the product is not an option and therefore financial risk is high which would reduce a consumer’s willingness to purchase a fashion counterfeit item. Social risk is hypothesized to have a significantly negative relationship with a consumer’s

31 likeliness to purchase a counterfeit fashion item because counterfeit fashion items lose value if other people can tell that it is a fake.

Hypothesis 18: High perceived financial risk negatively influences consumer likeliness to purchase counterfeit fashion items.

Hypothesis 19: High perceived social risk negatively influences consumer likeliness to purchase counterfeit fashion items.

A thorough analysis of the existing literature establishes a relatively concrete examination of consumer counterfeit purchase decisions but severely lacks relevant research directed toward one of the most commonly victimized industries of counterfeiting: fashion merchandise. In order to fill this hole in existing literature, this study transfers the components of past research to the relatively unexplored world of fashion counterfeiting. This allows for a comparative analysis with past studies and a thorough examination of the influence factors of fashion counterfeit purchase decisions. The nineteen hypotheses are formed based on two components. The first is how the selected variables correlate in past studies with consumer willingness to purchase general counterfeit items. The second component is how logic and existing literature suggests those relationships may differ with fashion counterfeit items due to the unique characteristics of fashion items.

4.0 METHODOLOGY

This research was conducted with a quantitative/exploratory method. Beginning with a specific topic and a research question, the study commenced with an exploration of the available literature in the field about counterfeit goods. Once it was established that there is an ample amount of research on the question of consumer willingness to purchase counterfeit products it could be concluded that the quantitative/exploratory approach was an appropriate method. Certain independent variables were extracted from past studies after a systematic review of the existing literature. These variables, which were tested in the past for a correlation with consumer willingness to purchase

32 general counterfeit goods, were tested in this study for a correlation with consumer likeliness to purchase counterfeit fashion goods. Because counterfeit fashion items possess certain unique characteristics, hypotheses were formed about whether or not the variables correlate with consumer willingness to purchase fashion counterfeit items the same way that they correlate with consumer likeliness to purchase general counterfeit items.

In order to conduct a quantitative analysis of how consumer willingness to purchase counterfeit fashion items correlates with the variables drawn from past studies, a fifty-one question

Likert Scale internet survey was designed and published for online submission. There were 117 subjects who participated in the survey and were able to access the link either by email, Facebook, or an internet search. The subjects were briefed on the intention of the research and given a definition and examples of counterfeit fashion items in order to clarify certain terms in the questionnaire. This was achieved through a short introduction paragraph at the beginning of the survey. The paragraph also ensured subjects that all information and data collected for the purpose of this research is completely confidential in order to guarantee truthful and accurate responses. Each statement could be answered on a scale of 1 to 5 ranging either from Strongly Disagree to Strongly Agree or Not

Important to Extremely Important. Not Applicable was a sixth option on certain questions where necessary. Four demographic questions were also included in the questionnaire for two purposes. The first is to establish that the subjects of the survey are representative of the population and the second is to establish a correlation between demographic variables and the control questions. Three control questions were included to establish the subject’s willingness to purchase fashion counterfeit items.

One of the three control questions was thrown out after careful consideration due to its lack of clarity.

4.1 Quantitative Analysis

This method of data collection is appropriate because this study tested the correlations between two variables. It allows one to compare the subject’s willingness to purchase counterfeit fashion items with each of the independent variables in order to establish if certain variables have a positive or negative relationship with the control questions. It also allows one to test that the subjects

33 of the survey appropriately represent the population by including demographic questions. By being able to test the correlations between the variables drawn from past studies and the control questions, one can see what variables are commonly present in consumers who are willing to purchase counterfeit fashion items. For example, Bian and Moutinho discovered (2009, p. 375) in their research that subjects with higher levels of education strongly correlate with subjects who are willing to purchase counterfeit goods. From this one can draw conclusions that consumers who buy counterfeit goods are often also highly educated. It is important to note however that these are correlations and not causal relationships. Referring back to the example above, such a correlation does not mean that people purchase counterfeit goods because they are highly educated. It merely suggests that where one variable is present, the other variable is often also present. From the correlations found between the variables tested in the survey one can draw conclusions about why certain variables are often associated with consumers who are willing to purchase counterfeit fashion items.

4.2 Advantages and Disadvantages of Internet Survey Analysis

As with any type of data collection, internet surveys have both advantages and disadvantages.

There are four key characteristics to consider when evaluating quantitative data collection methods: response rates, timeliness, quality, and cost (Fricker & Schonlau, 2002, p. 3). One disadvantage to using online surveys as a data collection method is that response rates are not particularly high

(Fricker & Schonlau, 2002, p. 3). In order to address this issue one can contact personal acquaintances and ask them to fill out the questionnaire and to forward the questionnaire to as many people as possible with a personal request to do the same. People are more likely to fill out a survey as a favor to a friend than to fill it out simply for the purpose of research. However, this increases the risk that the subjects that fill out the survey do not reflect a representative sample. Therefore it is important to be aware of the demographic variables of survey participants and to reach subjects that represent the population appropriately. In order to do so for this study, IBM’s Statistical Package for the Social

Sciences software (SPSS) was utilized to continuously monitor the representativeness of the sample and if certain demographic groups were lacking, specific effort was made to reach more subjects of that demographic group.

Internet surveys have the obvious advantage of timeliness (Fricker & Schonlau, 2002, p. 9).

Being able to instantaneously publish the survey for public access and receive responses the moment a subject clicks on the Submit button at the bottom of the page, allows for a speedy data collection process. Compared to postal surveys in which one must calculate several days for the time it takes to reach the subject and be returned, the internet is a much more advantageous survey portal (Fricker &

Schonlau, 2002, p. 9). It does not however, offer any advantage in terms of getting subjects to fill out the survey on the spot. Surveys conducted on site, for example at malls and public places, offer the advantage of requiring the subject to fill out and return the survey immediately (Fricker & Schonlau,

2002, p. 9). Subjects may feel less inclined to immediately fill out and submit online surveys because there is no one in front of them waiting for them to complete it. This could delay the timeliness of internet survey responses.

Quality is the most important aspect of data collection. Responses are useless unless they are accurate, truthful, and reflect a representative sample (Fricker & Schonlau, 2002, p. 10). In order to ensure that all subjects answer truthfully, a statement was included at the beginning of the survey explaining the purpose of the study, listing examples of counterfeit fashion items and defining the term counterfeit. There are also instructions throughout the questionnaire explaining how to go about responding to the statements correctly. It is common for surveys to contain errors or unclear questions that subjects may not know how to answer (Fricker & Schonlau, 2002, p. 11). In order to address this issue the survey was reviewed by two outside parties who knew nothing about the study. They were asked to carefully read through each question and to write down anything that needed clarifying or needed to be reworded. Changes were made to ensure complete comprehension. Quality of data is also at risk because of coverage errors (Fricker & Schonlau, 2002, p. 11). Not everyone has access to the internet and this may interfere with maintaining a representative sample. The survey may lack access to older age groups who may not be comfortable using the internet. In order to ensure the sample is representative of the population certain respondents were contacted directly by email with special instructions on how to fill out the survey online.

The last key characteristic to consider when evaluating data collection methods is cost. The low cost of internet surveys is another key advantage to this method (Fricker & Schonlau, 2002, p.

14). The only real cost involved in designing, publishing, and collecting internet survey responses is time. Financially, internet surveying is the optimal data collection method (Fricker & Schonlau, 2002, p. 14). Postal surveys require money for postage, paper, and ink while internet and on-site surveys have paper and ink costs as well as transportation costs to and from the survey site. Choosing an internet survey for the research methodology is not only appropriate for the quantitative analysis needed to answer the research question, but it also saves time and money while obtaining sufficient response rates and quality information.

4.3 Research Process

The process of designing, publishing, collecting responses, and analyzing data took approximately five weeks. The survey questions were designed based on the variables that were to be tested for a correlation to consumer willingness to purchase counterfeit fashion items. Below is a list of all variables organized into three categories: demographic variables, values and attitudes variables, and consumption variables. Each variable was drawn from one of several previously conducted studies that tested the relationships between these variables and consumer likeliness to purchase general (not fashion) counterfeit items. These variables were then translated into survey questions so that the variables could be quantitatively analyzed for their relationship with a consumer’s willingness to purchase counterfeit fashion items.

Table 1: Variables and corresponding survey questions (Source: Own elaboration) Correlation Variables Demographic Variables Variable # and Survey Question Age V1: Question 2 Gender V2: Question 3 Yearly Income V3: Question 4 Education Level V4: Question 5 Country V5: Automatically recorded by Surveygizmo.com Values and Attitudes Variables Materialism: Centrality V6: Questions 6-12 (Averaged) Materialism: Happiness V7: Questions 13-17 (Averaged) Materialism: Success V8: Questions 18-23 (Averaged) Spirituality V9: Question 41

Desire to Preserve Public Image V10: Question 48 Obedient V11:Question 49 Self-Indulgent V12: Question 50 Observes social norms V13: Question 51 Sense of Belonging V14: Question42 Need for an Exciting Life V15: Question 43 Need for Wealth V16: Question 44 Respect for Tradition V17: Question 45 Need for Social Recognition V18: Question 46 Honesty V19: Question 47 Attitudes: toward counterfeit law and V20: Questions 24- 26 (Averaged) order V 21: Questions 27-28 Attitudes: toward counterfeit values (Averaged) Attitudes: toward counterfeit V22: Question 29 experiences

Table 1 cont. Consumption Variables Product Knowledge V23: Question 30 Product Involvement V24: Question 31 Brand Personality V25: Question 32 Perceived Product Attributes V26: Question 33 Perceived Benefits V27: Question 34 Social Risk V28: Question 35 & 36 Financial Risk V29: Question 37 Fashionable/In-style V30: Question 38 Control Question 1 Question 1 Control Question 2 Question 40 Control Question 3 Eliminated

The variables used are appropriate for several reasons. Determining if certain demographic variables strongly correlate with a consumer’s willingness to purchase counterfeit fashion items has very useful implications for authentic fashion companies and designers. It allows them to have an idea of what demographic groups are driving the demand for counterfeit fashion and shape their marketing and anti-counterfeiting efforts accordingly. The attitudes and values variables have similar implications for marketing and anti-counterfeiting efforts. By knowing the attitudes and values that many consumers who are willing to purchase fashion counterfeit goods often have in common, it allows fashion companies to know how to reach these consumers and how to make them understand and care about the issue of fashion counterfeiting. The consumption variables tell more about the process and the value that counterfeit fashion offers consumers. If authentic fashion companies can somehow offer the same value with legitimate fashion brands then consumers would have no reason to purchase counterfeit versions. Therefore, knowing what consumption variables influence consumers to purchase counterfeit fashion is extremely useful information for such companies.

Once these test variables were established, the designing process of the survey questions could begin. The online software Surveygizmo.com allowed for simple step by step construction of the survey and once published provided a link which could be sent to potential respondents to fill out

38 the survey. In order to ensure that at least one control question was answered in every survey taken, the first control question was placed as the very first question of the survey. Because the survey is fifty-one questions long, placing both of the control questions at the end would have invalidated any survey that was not fully completed. The second and third control questions were placed in the middle of the survey and the third was later eliminated after careful consideration determined that the question was phrased in a contradictory manner by combining two statements in one. The demographic questions (variables 1-5) were designed to be very straight forward, asking respondents to pick one of five categories which applied to them. The country from which the respondent was taking the survey was automatically recorded by Surveygizmo.com and was therefore added to the demographic data collected from each respondent. Eighteen of the questions were designed to gauge the respondent’s level of three different aspects of materialism: centrality, success, and happiness

(variables 6-8). These eighteen questions were drawn directly from Richins and Dawson’s

Materialism Scale (Richins &Dawson, 1992). By taking an average of the respondents’ scores on questions for each category of materialism, one can determine a consumer’s level of centrality materialism, success materialism, and happiness materialism. A similar process went into the attitudes toward counterfeiting variables. Furnam and Valgiersson’s (2007) study created a set of survey questions to gauge consumer’s attitudes toward law and order, beliefs about the value of counterfeit goods, and attitudes toward their past experiences with counterfeit goods. The survey questions in this study were based on the questions created by Furnam and Valgierson (2007, p. 681) for their own study and again each respondent’s scores on the questions related to each of those three variables were averaged together to determine their attitudes toward counterfeit law and order, beliefs about the value of counterfeit goods, and attitudes toward their past experiences with counterfeit goods.

The personal values in the second category (variables 9-19) were extracted from the Schwartz

Value Scale. Rather than use the exact scale, as Furnham and Valgeirsson (2007) chose to do, this study draws on certain pieces of the value model by gauging how the following personal values act as a guiding principle in each participant’s life: need to belong, need for an exciting life, need for wealth, spirituality, respect for tradition, need for social recognition, honesty, desire to preserve public image,

39 obedience, self-indulgence, and observing social norms (Schwartz, 1994). This difference in approach was instituted for two reasons. First, the Schwarz Value Scale requires participants to answer a very lengthy questionnaire. The survey for this study is already fifty-one questions and research shows that the amount of completed survey responses declines as the amount of questions and time required increases (Hoerger, 2010). The other reason for only partially using the Schwarz Value Scale is that many of the personal values it addresses have very little to do a consumer’s willingness to purchase counterfeit items. Therefore it is more efficient to use only certain values which could have a connection to the research question and only those personal values are used in this study.

The remainder of the questions was based on the consumption variables (variables 20-30) and was not designed to be correlated with the control questions. Instead the questions were set up in a way that directly asks the respondent if they would be more likely to purchase a counterfeit fashion item if the consumption variable is present. For example if product knowledge is high when a consumer is considering buying a counterfeit fashion item then that means the consumer knows a lot about the product and the alternative products available to them. The corresponding survey question therefore asks if the respondent would be more likely to purchase a counterfeit fashion item if they know a lot about the product and the alternative products available to them. Each of the consumption variable questions was designed in this way.

After the first draft of the questions was created it was reviewed by two outside parties for any unclear wording, misunderstandings, or biased questions. Several small changes were made before the survey was published on the internet and made accessible to respondents. Collecting responses was made possible primarily through email and Facebook posts. The survey link provided through

Surveygizmo.com was emailed to both personal acquaintances and to all students on the graduate student list at UNC Wilmington. Each person who received this email was also asked to forward the survey link to as many people they know in order to exponentially reach a large audience. A similar process was integrated with Facebook software by posting the survey link and asking people to post the link on their own page requesting their own friends to fill out the survey. In this way not only were

40 personal acquaintances reached but also friends of friends. Within three weeks 117 people had responded to the survey and a relatively representative sample had been reached.

The data provided by the survey responses was entered into the SPSS software in order to determine which variables correlated with the two control usable questions. They were also tested for correlations with other categories of variables and within like categories in order to help clarify any underlying latent variables. The figure below shows each category of variables with the lines indicating that correlations were tested between the two categories.

Figure 3: Factor derived model (Source: Own elaboration)

After the survey data was entered into SPSS two of the software’s functions were utilized.

The first function used was the descriptive statistics analysis in which the frequencies of the respondents were plotted into histograms in order to analyze their bell curve shaped tendencies. This function allows one to determine how representative the demographic variables of the sample are.

The second function of SPSS used was the two tailed Pearson correlation function in which all significant correlations between variables were analyzed. Significant correlations were marked by

SPSS with either one or two stars. One star indicated the correlation is significant at the 0.05 level and two stars indicated even stronger correlation significance at the 0.01 level. Each correlation was also specified as either positive or negative indicating the relationship between the variables. The findings are discussed in the following section organized by category of variables.

5.0 33333FINDINGS AND DISCUSSION

The findings are discussed in the following section organized by category of variables. In order to understand the significance of these results it is important to first note the differences between control question one and control question two. In the survey control question one reads as follows: I would consider purchasing a counterfeit fashion item. Control question two states: I like to purchase counterfeit fashion items. The difference between these two statements is rather significant which was done purposefully in order to approach the question of whether or not the respondent is willing to purchase counterfeit fashion items from different directions. It is important also to note that control question one and control question two have a very strong positive correlation meaning that nearly every respondent who agreed with control question one also agreed with control question two, suggesting that these two control questions gauged the respondents’ willingness to purchase counterfeit fashion items rather well. The difference between the two control questions is that in the first case, the respondent is stating that they are willing to consider purchasing counterfeit fashion items. This means that they are not entirely against the concept of purchasing counterfeit fashion items whereas in the second control question the respondent is admitting to having purchased counterfeit fashion items in the past and furthermore suggests that they had a positive experience and are likely to do it again.

5.1 Representative Sampling

Table 2: Respondent profile (Source: Own elaboration)

Gender

Male 51.8%

Female 48.2%

Age

Under 18 0.9%

18-24 30.7%

25-34 40.4%

35-54 21.9%

55+ 6.1%

Income

Less than $25,000 34.8%

$25,000-$49,999 28.7%

$50,000-$99,999 25.2%

$100,000-$149,000 6.1%

$150,000 or more 5.2%

Education

12th grade or less 0.9%

Graduated High school or equivalent 5.3%

Associate Degree 5.3%

Bachelors Degree 43%

Postgraduate Degree 45.6%

Each demographic variable was plotted into a histogram. This allows one to visualize the data in a way that makes it easier to interpret. Normal curves are often used in statistical analyses because

43 the bell shaped curve is a common distribution shape naturally found in many populations

(“Histograms,” 2011). If the shape of the distribution is comparable with a normal bell curve one can conclude that the variable being analyzed is relatively representative of the population. It is important to have a representative sample when conducting studies if the results are to have any real life applications. This is the case because one can only make generalizations about a larger population if the sample correctly represents it. Unfortunately this can be extremely difficult to achieve, especially in survey studies where respondents are being reached based on personal acquaintances. The first demographic variable extracted from the data into a histogram was age. Following the normal distribution curve, this variable is pleasingly representative. The largest age group in the sample accounts 40.4 percent of the sample size and is comprised of the 25-35 year old age group. Gender, although it does not follow the bell curve, since there are only two options for this variable, is fairly evenly divided between male and female respondents. This is ideal for comparing male and female likeliness to purchase counterfeit fashion items.

Unfortunately the income histogram is positively skewed meaning that the majority of the respondents (thirty-five percent) fall in the lowest income bracket and each higher income bracket is represented less than the previous. Only 5.1 percent of the respondents claim to have more than

$150,000 in yearly income and nearly ninety percent of the sample makes less than $100,000 a year.

Although this does not follow a normal distribution curve, according to the US Census Bureau the average household income in 2010 was $49,445 (U.S. Census Bureau, 2011). This is consistent with the sample in this study in which the mean of respondents falls in the $25,000-$49,999 category. It should be noted however that this sample consists of respondents not only in the United States.

Although the country from which the respondent filled out the survey was not originally a demographic variable considered in this study, Surveygizmo.com automatically recorded that data.

This shows that there are respondents from the United States, Germany, Spain, and Russia. Having several countries represented in the sample suggests that the results of the data have global implications. The demographic data is represented below in the form of histograms.

Figure 4: Demographic histograms (Source: SPSS data)

The education histogram is negatively skewed and also does not follow the normal distribution curve. Most populations one might consider do not typically have more people with post graduate degrees than lower levels of education. This is slightly surprising considering that the age distribution so closely follows the normal bell curve. According the U.S. Census Bureau, only 10.4 percent of Americans over the age of twenty-five have graduate or professional degrees (U.S. Census

Bureau, 2011). In this sample, seventy-two percent of the respondents are over twenty-five years old and a surprisingly high 45.7 percent of the respondents have a post graduate degree. The reason for this is most likely due to the data collection process in which an entire list of UNC Wilmington

45 graduate students were contacted via email and asked to fill out the survey. Because the survey was published for responses near the end of the UNC Wilmington graduate semester, most of the graduate students contacted most likely already consider themselves to fall within the post graduate degree category.

Although not every demographic variable follows a normal distribution curve the respondents are never-the-less fairly representative of larger populations to which the results of this study have hopeful implications. The findings of this study are divided into three sections based on the type of variables that are being analyzed and discussed. Section 5.2 discusses how the demographic characteristics of the respondents correlate with their willingness to purchase counterfeit fashion items and what might be the reasoning behind such results. The second category of variables gauges the values and attitudes of the survey respondents and correlates those with their willingness to purchase counterfeit fashion items. These results are discussed and analyzed in section 5.3. The last part of the

Results and Discussion section discusses the third category of variables, consumption variables. These variables are not correlated with the control questions as the previous two variable categories are.

Instead these variables are discussed based solely on the responses of the subjects of the study and analyzed for patterns.

5.2 Demographic Correlations

Each demographic variable was entered into SPSS and tested for a correlation with control questions one and two separately. Out of the five demographic variables that were measured in the survey, three show a strong correlation significance of 0.05 with either control question one or control question two. Variable one (Age) shows a negative 0.05 level correlation significance with control question one but an insignificant correlation with control question two. Variable three (Income) also shows a negative 0.05 level correlation significance with control question one, but an insignificant correlation with control question two. Variable four (Education) however, shows a significant negative correlation only with control question two, and none with control question one. Variable two

(Gender) and variable five (Country) show no significant correlation with control question one or control question two.

Table 3: Demographic variables with significant correlations (Source: Own elaboration)

Control Question 1 Control Question 3

Variable 1: Age -.230* -.186

Variable 2: Income -.215* -.168

Variable 3: Education -.052 -.241*

* Correlation is significant at the 0.05 level

5.2.1 Age

The fact that age has a significant negative correlation with control question one, suggests that younger age groups are more likely to consider purchasing counterfeit fashion items. Age has a less significant correlation with control question two, which this suggests that although many younger respondents, would consider purchasing counterfeit fashion items, fewer of them have actually done so have done so with a positive experience and would do it again.

These results have interesting implications when compared to past studies that have been conducted on consumer purchasing decisions toward general counterfeit items. Swami, Chamorro-

Premuzic, and Furnham’s research (2009, p. 821) found several instances in past studies where age negatively correlated with consumers’ likeliness to purchase general counterfeit items. This study shows that consumer’s decision to purchase counterfeit fashion items and general counterfeit items correlate similarly with age suggesting that younger age groups are more likely to purchase all types of counterfeit items including fashion. These results confirm hypothesis two that there is a negative correlation between consumer age and consumer willingness to purchase counterfeit fashion items.

This hypothesis was formed under three assumptions. The first was that younger demographic groups may be more likely to purchase counterfeit items because they typically have less income. The

47 second assumption was that younger demographic groups may have less traditionalist values and the last assumption was that younger age groups may buy into the concept of lifestyle branding more than older age groups because they are still trying out different identities with which they chose to associate themselves. The first of these three assumptions is confirmed by a significantly positive correlation between age and income of 0.01. This suggests, as one would assume, that older age groups typically make more money. Therefore, the fact those younger age groups are shown to be more likely to purchase counterfeit fashion items could have something to do with the fact that they have lower income and cannot afford authentic brands. The second assumption in the hypothesis that younger age groups have less traditionalist values cannot be confirmed because there is no significant correlation between variable one (Age) and variable thirteen (Respect for Tradition). While traditionalist values may find counterfeiting unethical, it is not necessarily the case that younger age groups are less likely to have traditionalist values according to the responses to the survey. The last assumption of the first hypothesis, that younger age groups are more susceptible to lifestyle branding can also not be confirmed with the available data. Out of the three assumptions only one can be confirmed in this study which is that younger age groups typically have less income. Therefore the data suggests that younger people are more likely to purchase counterfeit fashion items and that a reason for this could be that younger age groups have lower income. For authentic fashion brand companies seeking to address the issue of counterfeiting, this tells them that their target offenders are younger age groups who also typically have lower income. This is important because it helps to narrow down the target market that anti-counterfeiting efforts should try to reach.

5.2.2 Income

As with variable one (Age), variable three (Income) shows a strong negative correlation with control question one and not with control question two, confirming hypothesis four that there is a negative correlation between income and consumer willingness to purchase counterfeit fashion items.

Because authentic fashion items can be prohibitively expensive this outcome was fully expected. The concept of lifestyle branding involves consumers who purchase fashion brands that portray a lifestyle that they either identify with or seek to identify with (Juggessur & Cohen, 2008). People with lower

48 income who seek to identify with certain lifestyles that are outside of their price range often turn to counterfeit fashion brands to achieve the image regardless (Juggessur & Cohen, 2008). This allows them to appear to belong to certain social classes or appear to have an elite lifestyle at affordable prices. This is the most obvious answer to why people buy counterfeit fashion items: it is more affordable and therefore is available to a much larger population. The problem is that although this is the most obvious answer it could also be the most difficult problem for authentic fashion brand companies to fix. By reducing the price of authentic brands, brands lose their exclusivity which is often why people buy them in the first place. High-end fashion brands such as Juicy Couture or Louis

Vuitton are set at prices that make them exclusively available to a small high-class high-income market segment. Unfortunately, this makes them prime targets for counterfeiters because people want exclusive, at non- exclusive prices.

Past research has confirmed that higher income levels negatively influence a consumer’s likeliness to purchase fashion items such as Gucci watches (Bian & Moutinho, 2009, p. 375). The data of this study confirms this claim with the significantly negative correlation between income and control question one. The concept value added could be an underlying cause of this relationship.

Authentic fashion items are often much more expensive than other types of goods that are frequently counterfeited, for example CDs or DVDs. A typical recently released CD might sell for around fifteen dollars and counterfeit versions of that same CD could sell for as low as one or two dollars. That is a savings of about fourteen dollars at most. Authentic fashion items often cost hundreds of dollars and the counterfeited versions can sell for as low as ten to twenty dollars. Therefore the value added by purchasing counterfeit versions of fashion items is much greater than the value added by purchasing other types of counterfeit items such as CDs and DVDs. If the value added by getting counterfeit CDs or DVDs is enough to make money conscious consumers buy them, then the value added by buying expensive fashion items must be more than enough. For consumers with lower income, such savings are significant and therefore these findings logically make sense.

5.2.3 Education

Variable four (Education) has a strong negative correlation with control question two but not with control question one. This could have several meanings. and reveals flaws with control question two because there is no way of determining what the respondent was implying. Again, control question two reads: I like to purchase counterfeit fashion items. Stating Strongly Disagree to this statement could mean that the respondent has never purchased counterfeit fashion items or it could mean that they did not like it when they did or it could mean that they do not generally like to purchase counterfeit fashion items, which does not mean that they would not do so under certain circumstances.

Therefore control question three, although it was thrown out because it combines two statements, may offer some insights into what the respondents were implying. According to the data, control question two and control question three have a very strong positive correlation. Control question three reads: I have purchased counterfeit fashion items in the past and I would do it again. Because control question two and three so strongly correlate it means that in most cases when respondents answered in favor of one, they also answered in favor of the other. This rules out the option that the respondents were implying that they had never purchased counterfeit fashion items. Therefore, the most conclusive statement that the data implies is that people with higher levels of education are less likely to enjoy purchasing counterfeit fashion items, which implies they are therefore less likely to do so, and vice versa: people with lower levels of education are more likely to enjoy purchasing counterfeit fashion items (and therefore more likely to do so).

Hypothesis five, that there is a negative correlation between level of education and consumer willingness to purchase counterfeit fashion items, is therefore confirmed. Bian and Moutinho’s (2009) research indicated that education has no effect on counterfeit purchase decisions but this is one area where fashion items reveal different results. There are countless latent variables that could be underlying the reasoning of such a statement. It could be the case that people with less education are also younger and that age (not education) is the real reason for this relationship. The data confirms this is a possibility because there is a significant positive relationship between age and education. It cannot be explained with the assumption that people with less education have lower income because

50 the data shows no relationship between education and income for this sample. One might even assume the possibility that less educated people are more likely to buy counterfeits because they are unaware of the negative impacts counterfeiting has on society. But the data shows that more educated respondents are no more or less likely to answer positively to the statement Counterfeiting has negative impacts on our society. Therefore there is either a direct connection between education level and willingness to purchase counterfeits, or the age variable is creating this relationship.

5.2.4 Other Demographic Findings

Out of 117 respondents, fifty-nine are male, fifty-five are female, and three did not indicate their sex. Of those fifty-nine males, 52.5 percent indicated either Agree or Strongly Agree to control question one stating they would consider purchasing counterfeit fashion items. Of the fifty-four females, 54.5 percent indicated they either Agree or Strongly Agree to the same control question.

These are fairly equal percentages suggesting that males and females are equally willing to consider purchasing counterfeit fashion items. Past studies have shown that men are more likely to buy counterfeit CDs and women are more likely to buy counterfeit clothing (Swami et al., 2009, p. 820).

Although the findings of this study suggest women are no more likely than men to buy counterfeit clothing disproving hypothesis five, it could be due to the limited sample size and the fact that no alternatives to fashion items were given in this survey.

Thus far, the demographic variables which correlate with consumer willingness to purchase counterfeit fashion items are low age, low income, and little education. Fashion marketers and authentic fashion brand companies can use this information to better target the types of consumers that are more likely to purchase counterfeit versions of their brands or alternatively to focus on the consumers who are more willing to buy the authentic fashion brands. Any anti-counterfeiting efforts should be targeting young, low income, uneducated consumers. Older, wealthier, and more educated consumers are those who are more likely to buy authentic brands and should therefore be the focus of marketing efforts.

5.3 Values and Attitudes Correlations

Of the seventeen variables in the Values and Attitudes category, seven show a strong correlation either with control question one, control question two, or both. Out of the materialism subcategory, happiness and success aspects of materialism significantly correlate with one or both of the control questions. The success aspect of materialism is the only variable (besides the attitudes variables) that shows a highly significant correlation with both control questions. In the second subcategory only two personal values variables show significant correlations with one or both of the control questions. In the third subcategory, all three attitudes variables show extremely significant correlations with both control question one and two. The table below shows the variables that correlate with the control questions.

Table 4: Values and attitudes variables with significant correlations (Source: Own elaboration)

Control Question 1 Control Question 2

Variable 7: Materialism Happiness .159 .219*

Variable 8: Materialism Success .279** .390**

Variable 11: Need for Exciting Life .195* .198*

Variable 13: Respect for Tradition -.206* -.054

Variable 20: C-Law and Order -.496** -.469**

Variable 21: C-Value .492** .484**

Variable 22: C-Experiences .584** .498**

* Correlation is significant at the 0.05 level

* * Correlation is significant at the 0.01 level

5.3.1 Materialism

The three aspects of materialism drawn from the Richins and Dawson Scale (1992) are happiness, success and centrality. Every respondent’s level of materialism was gauged from all three of these aspects by asking a series of questions drawn directly from the survey used in Furham and

Valgierson’s study (2007) which was also based on the Richins and Dawson Scale (1992). The only aspect of materialism that does not show any significant correlation with either of the control questions is centrality. Centrality materialism is the extent to which material possessions are placed at the center of one’s life (Furnham and Valgierson, 2007, p. 678). Past studies have shown that people with high levels of centrality materialism are less likely to purchase general counterfeit items; they are more inclined to own authentic brands (Furnham and Valgierson, 2007, p. 682). In the case of fashion counterfeits however, no such conclusions can be drawn. According to the data of this study, a person’s level of centrality materialism has no effect on their likeliness to purchase fashion counterfeit items. Hypothesis six, that there would be a negative correlation between centrality materialism and consumer willingness to purchase counterfeit fashion items, is therefore disproved.

This outcome is surprising when considering how this aspect of materialism is defined. Richins and Dawson (1992) and Furnham and Valgiersson (2007) clearly state that people with centrality materialism values are highly susceptible to advertising and desire brand name items. This could have been affected by the limited sample size or the lack of representativeness with certain demographic variables. On the other hand, these results could be attributed to the fact that this study centers on fashion counterfeit items and not general counterfeit items. Future studies should test this correlation again to confirm if there actually is a relationship between centrality materialism and consumer willingness to purchase counterfeit fashion items and explore the reasons behind this inconsistency.

Happiness and success aspects of materialism both show strong correlations with consumers’ willingness to purchase counterfeit fashion items, disproving hypothesis seven and eight. Hypothesis seven predicted that the happiness aspect of materialism would show no correlation with consumer willingness to purchase counterfeit fashion items because according to Furnham and Valgierson’s study (2007, p. 682), happiness in consuming is unrelated to authentic versus counterfeit. For this sample this is not true regarding fashion items. This variable’s significant correlation with control question two implies that the people with higher levels of happiness materialism enjoy purchasing counterfeit fashion items more than people with lower levels. Happiness materialism reflects how

53 much one’s material possessions impact their personal satisfaction and wellbeing (Furnham and

Valgierson, 2007, p. 678). Although Furnham and Valggierson (2007) argue that happiness materialism is independent of quality and brand names, this may not apply to counterfeit fashion items because they allow a consumer to feel better about themselves by portraying even if they cannot afford to do so legitimately. This could explain why counterfeit fashion items correlate differently than general counterfeit items in this case. In this sample, the majority of respondents who showed high levels of happiness materialism also reported having lower income which has already been established to reflect willingness to purchase counterfeit fashion items. This offers another explanation for why the data does not support hypothesis seven.

The results for the success aspect of materialism deserve a significant analysis due to the significant correlation it shows with both control questions. Richins and Dawson (1992, p. 304) plainly state that people whose values reflect success materialism value possessions based on what they cost rather than the satisfactory they receive from it. This clearly suggests that such people would be more inclined to purchase expensive authentic fashion items. But the results show the exact opposite. This variable is one of the strongest positive predictors of consumer willingness to purchase counterfeit fashion items. Past research has indicated no relationship between the two (Furnham &

Valgeirsson, 2007) which is less contradictory that the current results but still lacks logic.

One characteristic of success materialism that might offer some explanation is that people with high levels of success materialism judge success by the quantity and quality of the material possessions one owns. By this definition, quantity is the key word that might indicate why there is such a strong correlation. It appears that with fashion items, if one owns a large quantity, even if they are not authentic brands, then people with high levels of success materialism interpret this as success.

Furnham and Valgierson state that such people feel successful not only if they own legitimate quality objects, but also by “getting good value for money when buying a number of counterfeit products”

(Furnham and Valgierson, 2007, p. 683). According to this data quantity outweighs quality in terms of judging success by one’s fashion possessions. People with high success materialism values are more

54 willing to buy counterfeit fashion items either because they allow them to portray themselves as successful, or because they feel they are getting good value for their money by being able to afford higher quantities of fashion items at counterfeit prices.

The implication of the materialism variables is that it allows brand marketers to better understand what drives their consumers. It also allows them to better understand those consumers who would rather buy the fake version of their brand. By understanding what drives people to buy fashion, companies can not only better focus their marketing campaigns but can also seek to meet the needs of the consumers who might not normally buy the real product. For example, the results show that the same market segment that the demographic variables point out to be more likely to purchase fashion counterfeits (young, low income, uneducated) also scored fairly high on happiness materialism values.

Consequently, if this market segment seeks personal satisfaction through the fashion items they consume then marketing campaigns should send the message that people who buy this fashion brand have personal satisfaction and well-being. They could do so by associating the brand with images of people who live in expensive homes, drive nice cars, and appear to be part of an elite class of people who are well off and satisfied with their self-image. The results of the success materialism variable suggest that consumers who typically would buy counterfeit fashion brands value quantity and getting good value for their money is important and interpreted as success ones money are things they interpret as success. This advocates promotional offers such as “two for the price of one” that allow consumers to end their shopping experience with large quantities of fashion items.

5.3.2 Personal Values

Ten personal values were drawn from the Schwarz Value Scale (Schwartz, 1994) and correlated with both of the control questions. Of those personal values only two show a significant correlation. The first personal value gauges ones need for an exciting life (stimulating experiences). It shows an almost equally significant positive correlation with both control questions. In the survey, respondents were asked to rate the items on how important each value is for them as a guiding principle in their life. Of the 117 respondents sixty-three stated that an exciting life is either a Very

Important or an Extremely Important guiding principle in their life. The variable positively correlates with whether or not one would consider purchasing a counterfeit fashion item (CQ1) and with whether or not one enjoys purchasing counterfeit fashion items (CQ2). This means that people who strongly value having an exciting life typically are also willing to purchase counterfeit fashion items and would typically agree that they enjoy purchasing them. The connection between the variables could be several things. People might find purchasing counterfeit items to be exciting because they know it is illegal. Or they may just get a thrill out of owning fashionable brands, regardless of their authenticity.

The second variable that correlates with one of the control questions is respect for tradition. It has a negative correlation with control question one: I would consider purchasing a counterfeit fashion item. Past research shows that people with traditionalist values are less likely to purchase general counterfeit items. Traditionalism is defined as “respect, commitment, and acceptance of customs and ideas that traditional culture and religion provide” (Furnham and Valgierson, 2007, p.

683). Counterfeiting is illegal and has negative impacts on society. Therefore traditionalists are likely to find counterfeiting to be immoral. This correlation makes sense because if buying general counterfeit items is immoral for people with traditionalist values then there is no reason why buying counterfeit fashion items would be any less immoral. The fact that this variable did not have a significant negative correlation with the second control question can be attributed to the fact that in many of the cases where the respondent scaled high on traditional values they also answered Not

Applicable to control question two: I like to purchase counterfeit fashion items. This most likely means that the respondent had never purchased counterfeit fashion items in the past, and therefore, could not say whether or not they like doing so.

The correlations found in this category of variables have noted two personal values which have an impact on a consumers’ willingness to purchase counterfeit fashion items: need for an exciting life, and respect for tradition. Conversely the correlations of the data show that the remainder of the personal values have no impact one’s willingness to purchase counterfeit fashion items:

56 spirituality, need to belong, need for wealth, need for social recognition, honesty, desire to preserve public image, obedience, self-indulgence, and observant of social norms. While all of these personal values could logically have an influence on a consumers counterfeit fashion purchase decisions the data clearly shows that they do not in this given sample. But the two personal values which do impact this decision have implications for authentic fashion brand companies and marketers. Counterfeit fashion consumers correlate with consumers who have a need for excitement in their life. A wise strategy then would be for fashion brands to create marketing campaigns which associate their brand with an exciting lifestyle. Drawing on images of danger and adrenaline evoking activities could draw in such consumers. Lifestyle branding is a very powerful marketing tool as it creates associations in the consumers mind between the brand and the lifestyle the consumer desires (Juggesuer & Cohen,

2008, p. 384). The respect for tradition variable, which correlates significantly with consumers who are not willing to purchase counterfeit fashion items, advocates conservative brands and designs. The data implies that brands and designers who sell to more traditional and conservative consumers are at lower risk for losing consumers to counterfeit brands.

5.3.3 Attitudes

All three of the attitudes variables showed the most significant correlations both control questions. Variable twenty gauges the respondents’ attitudes toward law and order. People who score high on this variable believe that counterfeit laws should be strengthened and that it has negative impacts on society. The data shows a negative 0.01 level significant correlation between people’s attitudes toward law and order and consumer willingness to purchase counterfeit fashion items meaning that consumers who strongly believe in strengthening laws, increasing punishments, and believe in the negative impacts it has on our society are less likely to purchase counterfeit fashion items. Variable twenty-one gauges the respondents’ attitudes toward the value of counterfeit goods.

This variable also shows a 0.01 level significant correlation with consumer willingness to purchase counterfeit fashion. In this case, however, the correlation is positive meaning that consumers who have a positive attitude toward the value of counterfeits are more likely to purchase counterfeit fashion items. Variable twenty-two gauges the respondents’ attitudes toward their experiences with

57 counterfeits in the past. As with the other two attitudes variables, this one shows a 0.01 level significant correlation with consumer willingness to purchase counterfeit fashion items. Since it is a positive correlation this data can be interpreted to say that consumers who have had positive experiences with counterfeit goods in the past are more likely to purchase counterfeit fashion items.

Due to the extremely significant correlations that all three of these attitudes variables show with both control questions it can be concluded, as one might expect, that consumers attitudes toward counterfeiting are the best predictors of whether or not a consumer would purchase counterfeit fashion items.

These three variables have been studied in past studies with very similar results. Both

Furnham and Valgierson’s study (2007) and Swami, Chamorro-Premuzic and Furnham’s study (2009) concluded that these variables significantly predict willingness to purchase counterfeit goods. This study now establishes that the variables predict willingness to purchase counterfeit fashion goods just as well. Looking back at hypotheses ten through twelve, it was predicted that these variables would behave the same way with fashion counterfeit as they did with general counterfeit items because a consumers’ attitudes toward law and order, value, and experiences with counterfeits include but are not limited to, fashion counterfeit items. These results are important for all victims of counterfeiting because they indicate that people who can be convinced of the negative realities of counterfeiting will be less likely to purchase counterfeit goods. Such a statement encourages the thought that consumer awareness campaigns about the impacts that counterfeiting has on society and the economy would have positive results, molding consumers attitudes toward counterfeiting, and in doing so would reduce counterfeit purchases.

5.4 Consumption Correlations

The consumption variables were analyzed differently than the other two categories of variables because they were phrased in a way that asked the respondent directly if they would be more likely to purchase a counterfeit fashion item if the variable was present. For a better understanding of how these variables were tested in the survey, the questions are shown below with their corresponding variables and what percentage of respondents.

Table 5: Consumption variables and survey questions (Source: Own elaboration)

Survey Question Variable I am more likely to buy a counterfeit fashion item if I know a Variable 23-Product lot about the product and the alternatives available to me. Knowledge I am less likely to buy a counterfeit fashion item if it requires I Variable 24- Product spend time and effort weighing my alternatives and examining Involvement its features. I am more likely to buy counterfeit fashion brands that I Variable 25- Brand Personality associate with a lifestyle I have or aspire to have. I am more likely to buy counterfeit fashion items if they are Variable 26-Product Attributes practical or comfortable. I am more likely to buy a counterfeit fashion item it I believe it Variable 27- Product Benefits can “do a lot for me.” (Such as improve popularity, appear to have money and style, fit in with a certain crowd, look attractive, etc.)

I am more likely to buy a counterfeit fashion item if it appears Variable 28- Social RiskA to be authentic. I am more likely to buy a counterfeit fashion item if it looks Variable 28- Social RiskB authentic enough that my peers will not know it is fake. I am more likely to buy a counterfeit fashion item if I can Variable 29- Financial Risk return it for a full refund if I decide I do not want it for any reason. I will only purchase counterfeit fashion items that I know are Variable 30- “In style” currently “in-style.”

Product attributes and social riskA have the highest percent of respondents that replied either

Agree or Strongly Agree to the statement. In both cases 52.1 percent of 117 respondents answered positively. This means that out of the consumption variables product attributes and social risk are the two highest positive influences on a consumer’s willingness to purchase counterfeit fashion items.

Product benefits had the highest percentage of respondents that answered either Disagree or Strongly

Disagree, fifty-nine percent. This variable shows only 19.76 percent of respondents would be more likely to purchase counterfeit fashion items if the item can “do a lot for them” which is defined in the questionnaire with the examples: improve popularity, appear to have money and style, fit in with a

59 certain crowd, look attractive or other such benefits. In-style followed closely with 51.3 percent of respondents answering negatively to the statement, which again is a surprising result. Product involvement and brand personality have relatively high neutrality rates of more than twenty percent and their percentages of negative and positive responses are relatively even suggesting that these two variables have little impact on a consumer’s willingness to purchase counterfeit fashion items. The variables show an average NA (either did not answer or selected Not Applicable) rate of 12.7 percent.

Most of the questions that received an NA followed a series of unanswered questions suggesting that the respondent skipped several questions in a row or did not complete the survey. Product knowledge, product involvement, and in-style variables all show a slightly higher NA rate than average of about

14.5 percent. The results for each variable are discussed in further detail below.

5.4.1 Product Knowledge Figure 5: Product knowledge responses

Product Knowledge

Strongly Agree or Agree

14.4% Strongly Disagree or 36.8% Disagree 18.8% Neutral

30.0% No Answer

Product Knowledge yielded fairly neutral results. The percentage of positive and negative responses is within seven percentage points of one another which is relatively insignificant. The percentage of respondents who did not answer this question is slightly higher than average but not alarming enough to suggest the statement was particularly confusing or difficult to answer. The neutrality rate, while slightly higher than average, is not alarmingly high either. These results suggest

60 that product knowledge has little impact on a consumer’s willingness to purchase counterfeit fashion items disproving hypothesis thirteen that product knowledge would have a positive influence on consumer likeliness to purchase counterfeit fashion items. This hypothesis was made considering the fact that fashion items are valued more for their intangible image than their tangible functions and that the more knowledgeable one is about fashion items and the counterfeit alternatives, the more likely he or she would be to purchase the counterfeit because it can be so similar to the original and offer nearly the same value.

Bian and Moutino (2009, p. 373) hypothesized with similar reasoning in their study and their results revealed that product knowledge does positively influence consumers to buy fake Gucci watches. The image benefit of Gucci watches, as with other fashion items, can be easily imitated by counterfeits, therefore persuading consumers who are knowledgeable of this, that it would be a smart purchase (Bian and Moutino, 2009, p. 373). While the results of this study are fairly neutral, the positive responses do outnumber the negative responses to the corresponding survey question by about seven percent, suggesting that there may be some positive impact of product knowledge on consumer willingness to purchase fashion counterfeits, but very little. A larger sample size might have allowed for more definitive results.

5.4.2 Product Involvement Figure 6: Product involvement responses

Product Involvement

Strongly Agree or Agree

14.5% Strongly Disagree or 35.9% Disagree

Neutral 29.9%

19.7% No Answer

Product involvement has a high percentage of neutral respondents and it also has the highest percentage of respondents who did not answer this question. This could mean that the question was difficult to understand or that many people were not sure how to respond and therefore skipped the question or answered neutrally as they were not sure how they felt about the statement. The statement was phrased differently than the others in that it began with I am less likely to… rather than I am more likely to… as most of the others are phrased. This could have thrown off respondents who were impatient or in a hurry to finish. Despite the large percentage of NA and neutral responses there were

16.6 percent more positive answers than negative answers which means that more people agree that high product involvement purchase decisions do not result in counterfeit fashion purchases. This confirms hypothesis fourteen that product involvement has a negative relationship with consumer willingness to purchase counterfeit fashion items. This is due to the fact that purchase decisions that are significant enough to dedicate time and effort into evaluating pros and cons and analyzing alternatives, are likely to result in a larger investment to achieve higher quality (Bian and Moutinho,

2009, p. 369). While Bian and Moutinho’s (2009, p. 373) results revealed that product involvement is not an influence factor in the purchasing decision, they attribute this result to not being able to control usage situations.

5.4.3 Brand Personality Figure 7: Brand personality responses

Brand Personality

Strongly Agree or Agree

12.8% 26.5% Strongly Disagree or Disagree

23.9% Neutral

No Answer 36.8%

While the previous two variables had more positive responses than negative ones, brand personality has approximately ten percent more participants that answered Strongly Disagree or

Disagree than Strongly Agree or Agree. A ten percent difference is not all that significant when compared with the other variables and especially considering the high neutrality rate revealed of 23.9 percent. These respondents did not have a positive or negative response to this statement which is nearly as high as the positive responses. In summary, 73.5 percent of all respondents answered

Neutral, Disagree, or Strongly Disagree to the statement I am more likely to buy counterfeit fashion brands that I associate with a lifestyle I have or aspire to have. This suggests that brand personality does not influence consumers to purchase counterfeit fashion items.

These findings directly contradict hypothesis fifteen and the results of Bian and Moutinho’s study (2009). According to their study, a positive brand personality of a brand name product positively influences consumers’ likeliness to purchase a counterfeit version of the brand (2009, p.

374). When comparing research methods of how these two results were reached, Bian and Moutinho’s results appear to be more reliable for several reasons. Their resources allowed for a much more extensive research process which included focus groups to help devise the correct way to measure the

63 brand image concept (Bian & Moutinho, 2009, p. 374). In this survey respondents were directly asked if they believe a positive brand personality would influence them to buy a counterfeit version of the brand as opposed to the much more complex method used by Bian and Moutinho (2009).

Unfortunately the results of this study only conclude that consumers are not consciously and admittedly any more or less likely to purchase counterfeit fashion items because the imitated brand has a positive brand personality. More extensive research and survey question development is required to establish if they do so subconsciously.

5.4.4 Product Attributes

Figure 8: Product attributes responses

Product Attributes

Strongly Agree or Agree

12.8% Strongly Disagree or Disagree 15.4% 52.1% Neutral

19.7% No Answer

Product attributes scored the highest positive percentage in the consumption variables category of

52.1 percent. The neutrality rate and no answer rate is comparable and within the same range as the other variables. This suggests that consumers are more likely to purchase counterfeit fashion items if they have positive attributes such as practicality or comfort. This makes sense especially in the case of fashion items which have to be worn. Features such as comfort, practicality, or versatility have obvious advantages. For example, if a consumer must decide between an authentic fashion item and a knockoff, holding all other variables constant, if the counterfeit is more comfortable or is a certain color, those attributes would influence him or her to purchase the counterfeit version. Bian and

Moutinho (2009, p. 374) found the same results in their data on this variable for both Rolex and Gucci watches.

5.4.5 Product Benefits Figure 9: Product benefits responses

Product Benefits

Strongly Agree or Agree

10.3% 19.6% Strongly Disagree or 11.1% Disagree

Neutral

59.0% No Answer

The results of the product benefits variable are also inconsistent with hypothesis seventeen and again this can be attributed to the research method and the way that this variable is measured. As with the brand personality variable, the survey question directly asks the respondent if they believe a high degree of this variable would make them more likely to purchase a counterfeit fashion item, which in retrospect lacks validity. It does not make sense that sixty percent of the participants would not be more likely to buy a product if it offers certain benefits such as improved popularity, appearing to have money and style, fitting in with a certain crowd, or looking attractive. Bian and Moutinho (2009, p. 374) broke product benefits down into three categories: satisfactory benefit, image benefit, and functional benefit. Their study found that with Gucci watches, the image benefit factor has the most impact on consumers’ willingness to purchase a counterfeit (Bian & Moutinho, 2009, p. 374). The benefit of brand image can easily be transferred to counterfeits simply by imitating the brand name or logo and, holding other variables constant; at a lower price consumers would be more likely to purchase the counterfeit because the image benefit is still present. These are the types of benefits that consumers seek when they buy fashion items and therefore these results seem misleading. The issue

65 here could be that people do not want to admit that they buy fashion items for that reason or again that they do it subconsciously.

5.4.6 Financial Risk

Figure 10: Financial responses

Financial Risk

Strongly Agree or Agree 12.8% Strongly Disagree or Disagree 16.2% 41.9%

Neutral

29.1% No Answer

Financial risk was hypothesized to have a negative relationship with consumer willingness to purchase counterfeit fashion items and the data of the associated survey question confirms this hypothesis. The positive responses to the question are more than eleven percent higher than the negative responses. Bian and Moutinho’s (2009, p. 375) results showed that financial risk was an influential factor in their study as well. Financial risk was measured in this survey by asking if consumers would be more willing to buy counterfeit fashion items if they could return it for a full refund for any reason. This eliminates the financial risk and is therefore an appropriate way to gauge this variable. Although in many counterfeit distribution channels, being able to return the item is highly clothing items are easy to try on and the financial investment in counterfeit fashion is relatively low. Therefore financial risk is typically low in fashion counterfeit purchase decisions, which would influence consumers to purchase the item.

5.4.7 Social Risk Figure 10: Social riskA Q35 responses

Social Risk (Q 35)

Strongly Agree or Agree

10.3% Strongly Disagree or 12.0% Disagree

52.1% Neutral

25.6%

No Answer

Figure 11: Social riskB Q36 responses

Social Risk (Q 36)

Strongly Agree or Agree 12.0% Strongly Disagree or 9.4% 39.3% Disagree

Neutral

39.3% No Answer

Social risk with fashion items involves the risks associated with the social status one portrays through the fashion one wears. Fashion items give off social cues such as status, class, wealth, or lifestyle (Furnham & Valgeirsson, 2007). There is social risk involved if wearing a particular item could give off undesired social cues (Bian & Moutinho’s, 2009, p. 370). In the case of counterfeited fashion, social risk is higher if the counterfeit does not imitate the authentic brand well enough that people will believe it is authentic. Wearing an obviously fake fashion item sends a message that many people would find undesirable. Questions thirty-five and thirty-six of the survey both gauged the

Social Risk variable but were phrased in different ways. Question thirty-five states I am more likely to buy a counterfeit fashion item if it appears to be authentic. This question draws on the aspect of Social

Risk that people do not want others to know that they are wearing a fake fashion item. Question thirty-six draws on this aspect as well but it does so more directly. The statement reads I am more likely to buy a counterfeit fashion item if it looks authentic enough that my peers will not know that it is a fake.

What is most interesting about these two questions is the difference in the responses. Question thirty-five which did not mention the intent to deceive one’s peers received a significantly higher positive response rate than question thirty-six, which did. This indicates either that people want their counterfeit fashion brands to appear authentic for their own sake, or that people don’t like to admit that they want their fashion brands to appear to be authentic for the purpose of deceiving their peers about their social status. Bian and Moutinho (2009, p. 375) found that Social risk is an influential factor in the counterfeit purchase decision for Rolex and Gucci watches. Hypothesis nineteen was based on those findings and is confirmed by the amount of positive responses in question thirty-five, although question thirty-six reflected fairly neutral responses. Question thirty-five had the highest percent of Agree or Strongly Agree responses, tied with the product attributes variable, 51.2 percent indicating that lower social risk is one of the highest positive influence factors of consumer willingness to purchase counterfeit fashion items.

5.4.8 In-Style Figure 13: In-style responses

In-Style

Strongly Agree or Agree 14.5% 15.4% Strongly Disagree or Disagree 18.8% Neutral

No Answer 51.3%

The last consumption variable, In-Style, was not drawn from any past studies and was added to the study due to the unique characteristics of fashion items. According to Juggesur and Cohen’s research (2008) as fashion items enter the market there is a limited amount of time that they considered fashionable or “in-style”, after which time their value deteriorates. Therefore, a statement was added to the survey to gauge whether or not being in-style would make the consumer more likely to purchase counterfeit fashion items. Unfortunately, the question contains a survey error that may have skewed the results. While all other consumption variables asked whether or not the variable would make the consumer more or less likely to purchase the counterfeit fashion item, question thirty- eight stated I will only purchase counterfeit fashion items that I know are currently “in-style.” The statement should have been phrased as the other ones were stating I am more likely to purchase counterfeit fashion items that I know are currently “in-style.” Because of this survey error the positive responses are much lower than they likely otherwise would have been. Just because people will not only buy fashion items that are currently in-style do not mean that they would not be more likely to purchase the item if it is currently in-style. The results of this variable are therefore deemed invalid.

6.0 CONCLUSION

The results of this study offer some unique insights into the issue of counterfeiting in the fashion industry. Demographic variables age, income, and education negatively correlate with consumer willingness to purchase counterfeit fashion items suggesting that the main perpetrators belong to a relatively young marketing segment, typically with lower income levels and less education. The attitudes and values variables were broken down into three sub-categories: materialism values, personal values, and attitudes toward counterfeiting. Materialism values revealed very unexpected results disproving all three materialism hypotheses. Centrality materialism showed no relationship, happiness materialism showed a positive relationship, and success materialism showed a very high positive relationship with consumer willingness to purchase counterfeit fashion items. The only two personal values variables that showed any relationship with the control questions were the need for an exciting life (positive) and respect for tradition (negative). The remaining nine personal values showed no relationship with consumer willingness to purchase counterfeit fashion items and therefore do not influence the counterfeit purchase decision. All three attitudes toward counterfeiting variables showed significant correlations at the 0.01 level to both control questions. Attitudes toward the law and order of counterfeiting showed the only negative relationship out of the three. This indicates that people who believe the laws on counterfeiting are insufficient despite its negative impacts on society are highly unwilling to purchase counterfeit fashion items. Alternatively, people who believe that counterfeits offer good value and have had positive experiences with counterfeits in the past are highly willing to purchase such items. This section of the study showed results that are consistent with past research and with the associated hypotheses. The results of the last category, consumption variables, revealed product attributes and social risk as the two highest predictors of counterfeit fashion purchase decisions. Product knowledge, product involvement, and financial risk showed indications of having a slightly less significant influence on the purchasing decision as well.

6.1 Managerial Implications

Overall the findings of this study support and contradict findings in past research. However those findings cannot be directly compared because this is the first study in which each of these variables were tested for a correlation with fashion counterfeit purchase decisions. Because this is the first fashion industry specific study with this variety of variables, the results of this study have useful implications for authentic fashion brand companies. The demographic variables define a market segment that is being lost to counterfeit competitors. With the knowledge that the primary offender of counterfeit fashion purchases is a young consumer with lower income and less education, there are several approaches one might take to address the issue. One thing legitimate fashion companies could do is offer a less expensive spin off brand that people know is associated with the much more expensive and exclusive brand. This way they profit off of the expensive brand’s reputation and exclusivity by having a less expensive brand that people associate with it. It would be wise to offer this brand at locations where younger age groups with low to average income consumers do their shopping, such a malls or discount department stores. Another recommendation considering the income variable result would be to develop a marketing campaign targeting younger and lower/ middle class consumers that educates people about the societal consequences of counterfeiting. Issues such as unemployment and lost tax revenues due to counterfeiting are likely to be of real concern for this market segment. The results of the attitudes toward counterfeiting variables further suggest that convincing consumers of the inadequacies of law and order and the negative societal impacts would make consumers less willing to purchase counterfeits.

The attitudes and values variables show how to reach those who are purchasing counterfeits and with those who are not. The results of this study generalize the values and attitudes that are common among these two groups. This has extremely useful marketing implications for targeting both groups.

Consumers who would normally be inclined to purchase counterfeits are people with less traditional values, who seek excitement in their life, and do not grasp the impacts that counterfeiting has on society. They also believe that counterfeits offer relatively good value and have had good experiences purchasing counterfeits in the past. Knowing this information about a segment that a marketing campaign is trying to reach shows ways to connect with these consumers and draw on things that they

71 value in order to win their loyalty. Likewise, the group that is less likely to purchase counterfeit fashion is a legitimate fashion company’s primary target market and understanding their attitudes and values is just as valuable.

The results of the consumption variables show that product attributes and social risk are the two most substantial influences on a consumers fashion counterfeit purchase decision. This means that legitimate fashion companies should attempt to make their features and their logo as difficult to imitate as possible. If consumers value certain product attributes that a counterfeit cannot imitate they will be less likely to settle for the counterfeit version. Likewise, if a logo or brand name is difficult to imitate then counterfeiters will have a hard time making their product look authentic. If it doesn’t look authentic, the data shows that consumers are less likely to buy a counterfeit because of the increased social risk involved.

6.2 Limitations and further research

This is an important area of exploration and further research is necessary to correct some of the errors of this study and confirm some of its underlying assumptions. It is recommended that this study is replicated with more advanced statistical analyses and survey question formulation in order to address some of the limitations of this study. As with any study achieving a representative sample is important but can be rather difficult. The income and education distributions are fairly skewed in the sample and could have impacted the results and implications of the study. An imitation of this study with a new sample to see if the data shows similar results would help confirm the validity of the results.

The questionnaire contained several errors and made it difficult to correctly interpret the data.

Control question three was rendered useless after careful consideration determined that the question combined two statements to which the respondent might have answered differently. A high percentage of the respondents did not answer this question or selected Not Applicable which suggested there may have been some lack of clarity. Control question two could also have been worded more precisely because it incorporates the underlying assumption that the respondent has purchased counterfeit fashion items in the past. It might have been a better approach to ask if the

72 respondent has ever knowingly purchased counterfeit fashion items in the past and to then include control question two as a sub question if the answer was yes. In future research careful reconsideration should be given to the wording of the control questions.

Table 6: Control question errors (Source: Own elaboration)

Control Question 1 I would consider purchasing a counterfeit fashion item.

Control Question 2 I like to purchase counterfeit fashion items.

Control Question 3 I have purchased counterfeit fashion items in the past and I would

(eliminated) do it again.

Gauging respondent’s personal values could have been done more precisely by using the entire Schwartz Value Model questionnaire. However, this would have significantly added to the length of the survey. In the case of internet surveys it is important not to overextend the amount of time required to finish filling it out because this increases the risk of incomplete responses. Therefore, this study simplified the model measuring only how important certain values are as a guiding principal in the respondent’s life. For future research, using the entire Schwartz Value Model questionnaire is recommended if the data collection process allows for a more lengthy survey. This would allow for a more precise exploration of the respondent’s personal values and result in a score for each of the ten primary values of the model, which could then be tested for correlations with the control questions.

The consumption variables were difficult to measure correctly. Each statement of this category directly asked the respondent if they would be more likely to purchase a counterfeit fashion item if the variable was present. After analyzing the findings in this category it became clear that in some cases respondents either did not want to admit to some of their self-indulging consumer habits or that they do not consciously consider some of these variables in the purchase decision process. By making use of focus groups and having more time and resources, better survey questions could be

73 formulated that achieve more honest responses and that have a way of measuring influence factors that may not be consciously obvious to the consumer during the purchase decision.

After speaking with several respondents about their opinions regarding the survey, there were two additional things that could improve the quality of the data for future replications of this study.

The first would be to include in the introduction paragraph of the survey that this study is about non- deceptive counterfeiting. One respondent admitted to some confusion because he/she believes there have been times when he/she unknowingly purchased a counterfeit fashion item in which case that person could not say for example if they had a positive experience or not. It should have been clearly stated in the survey introduction that these questions are regarding non-deceptive counterfeit purchase decisions in which the consumer is fully aware they are buying an imitated product. Another respondent admitted to answering Neutral to several questions because he/she felt there were no options that best reflected his/her opinion. This is often the case in surveys and future researchers may address this issue by creating parallel questions that address both sides of opposing values such as spirituality and materialism or conservative and liberal. This way the respondent feels that the survey allows them to correctly reflect their opinions.

There are two areas which require additional research to fully understand and confirm the results of this study and its implications. The results of the materialism values not only disproved the corresponding hypotheses but also seem illogical based on the definitions of the three aspects of materialism offered by Furnham and Valgeirsson (2007) and Richins and Dawson (1992). These aspects of materialism have never been applied directly to fashion counterfeit purchase decisions and it would be wise to test this relationship again, with revised control questions, to confirm the correlations and explain the reasoning behind the inconsistencies between the results and the definitions. The other area of interest is the relationship between age and lifestyle branding. This study predicts that part of the reason for younger age groups being more willing to purchase counterfeit fashion items is that during one’s teenage and twenties years people tend to have more dynamic and rapidly changing taste in fashion because they are still trying out different identities. As

74 people get older and are more stable in their beliefs, values, and consequently their self-image, they tend to become more static in their taste in fashion. Therefore younger generations have a greater need for affordable and disposable fashion that still carry the identity with which they want to be associated, a need which is met by counterfeits. This is an interesting concept that would help explain the relationship between age and willingness to purchase counterfeit fashion items and should be further explored.

7.0 APPENDICES

Figure 14: Survey Counterfeit Fashion Purchase Decisionsounterfeit Fashion The purpose of this study is to gain a better understanding of what variables influence a consumer's decision to purchase counterfeit fashion goods (for example clothing, bags, shoes, watches, sunglasses, accessories, etc.) The term counterfeit refers to imitated brands or designs that infringe upon intellectual property rights and such items are often referred to as knockoffs, fakes, or replicas. Please rate the following statements honestly and to the best of your ability. All information provided is completely confidential.

1. I would consider purchasing a counterfeit fashion item. *This question is required Strongly Strongly Not disagree Disagree Neutral Agree agree Applicable

2. Age under 18 18-24 25-34 35-54 55+

3. Gender Male Female

4. Approximate yearly income (USD) Less than $25,000 to $50,000 to $100,000 to $150,000 or $25,000 $49,999 $99,999 $149,999 more

5. Education Level Graduated high school or Post-graduate 12th grade or less equivalent Associate degree Bachelor's degree degree

6. I usually buy only the things that I need. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

7. I try to keep my life simple, as far as possessions are concerned. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

8. The things I own aren`t all that important to me.

Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

9. I enjoy spending money on things that aren't practical. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

10. Buying things gives me a lot of pleasure. Strongly disagree Disagree Neutral Agree Strongly agree Not Applicable

11. I like a lot of luxury in my life. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

12. I put less emphasis on material things than most people I know. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

13. I have all the material things I really need to enjoy life. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

14. My life would be better if I owned certain things I don't have. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

15. I wouldn't be any happier if I owned nicer things. Strongly disagree Disagree Neutral Agree Strongly agree Not Applicable

16. I'd be happier if I could afford to buy more things. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

17. It sometimes bothers me quite a bit that I can't afford to buy all the things I'd like. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

18. I admire people who own expensive homes, cars, and clothes. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

19. Some of the most important achievements in life include acquiring material possessions. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

20. I don't place much emphasis on the amount of material objects people own as a sign of success. Strongly disagree Disagree Neutral Agree Strongly agree Not Applicable

21. The things I own say a lot about how well I am doing in life. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

22. I like to own things that impress people. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

23. I don't pay much attention to the material objects other people own. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

24. I would strengthen the law against counterfeit manufacturers. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

25. I would strengthen the law against counterfeit salespeople. Strongly disagree Disagree Neutral Agree Strongly agree Not Applicable

26. Counterfeiting has negative impacts on our society. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

27. Most counterfeit goods offer the same value as the originals. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

28. So many branded goods are rip offs; counterfeits are better value. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

29. I have had good experiences with counterfeit goods in the past. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

30. I am more likely to buy a counterfeit fashion item if I know a lot about the product and alternative products available to me. Strongly disagree Disagree Neutral Agree Strongly agree Not Applicable

31. I am less likely to buy a counterfeit fashion item if it requires I spend time and effort weighing my alternatives and examining its features. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

32. I am more likely to buy counterfeit fashion brands that I associate with a lifestyle I have or aspire to have. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

33. I am more likely to buy counterfeit fashion items if they are practical or comfortable. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

34. I am more likely to buy a counterfeit fashion item if I believe it can "do a lot for me." (such as improve popularity, appear to have money and style, fit in with a certain crowd, look attractive, etc.) Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

35. I am more likely to buy a counterfeit fashion item if it appears to be authentic. Strongly disagree Disagree Neutral Agree Strongly agree Not Applicable

36. I am more likely to buy a counterfeit fashion item if it looks authentic enough that my peers will not know that it is a fake. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

37. I am more likely to buy a counterfeit fashion item if I can return it for a full refund if I decide I do not want it for any reason. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

38. I will only purchase counterfeit fashion items that I know are currently "in style." Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

39. I have purchased counterfeit fashion items in the past and I would do it again. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

40. I like to purchase counterfeit fashion items. Strongly Not disagree Disagree Neutral Agree Strongly agree Applicable

Please rate numbers 41 through 51 on how important each value is for you as a guiding principle in YOUR life.

41. A spiritual life (emphasis on spiritual not material matters) Slightly Extremely Not Important Important Important Very Important Important

42. Sense of belonging (feeling that other people care about me) Slightly Extremely Not Important important Important Very Important Important

43. An exciting life (stimulating experiences) Slightly Extremely Not Important important Important Very Important Important

44. Wealth (material possessions, money) Slightly Extremely Not Important important Important Very Important Important

45. Respect for tradition (preservation of time-honored customs) Slightly Extremely Not Important important Important Very Important Important

46. Social recognition (respect, approval by others) Slightly Extremely Not Important important Important Very Important Important

47. Honest (genuine, sincere) Slightly Extremely Not Important important Important Very Important Important

48. Preserving public image (protecting "face") Slightly Extremely Not Important important Important Very Important Important

49. Obedient (dutiful, following the rules) Slightly Extremely Not Important important Important Very Important Important

50. Self-indulgent (doing pleasant things) Slightly Extremely Not Important important Important Very Important Important

51. Observing social norms (to maintain face) Slightly Extremely Not Important important Important Very Important Important

Table 7: Survey data: Demographic variables and control questions (respondents 1-58)

# Age Gender Income (USD) Education C1 C2 C3 1 35- 54 Male $50,000 to $99,999 Post-graduate degree 4.0 2.0 4.0 2 25-34 Male $25,000 to $49,999 Graduated high school or equivalent 3.0 NA NA 3 18-24 Male $25,000 to $49,999 Bachelor's degree 4.0 1.0 2.0 4 35-54 Female $25,000 to $49,999 Post-graduate degree 2.0 1.0 1.0 5 25-34 NA $50,000 to $99,999 Bachelor's degree 1.0 1.0 NA 6 25-34 Female Less than $25,000 Post-graduate degree 5.0 3.0 4.0 7 NA Female $25,000 to $49,999 Associate degree 2.0 2.0 4.0 8 35-54 Male $25,000 to $49,999 Post-graduate degree 1.0 1.0 1.0 9 35-54 Female $50,000 to $99,999 Post-graduate degree 1.0 1.0 1.0 10 35-54 Female $100,000 to $149,999 Post-graduate degree 3.0 3.0 1.0 11 18-24 Female $25,000 to $49,999 Bachelor's degree 5.0 4.0 4.0 12 18-24 Female Less than $25,000 Bachelor's degree 2.0 2.0 2.0 13 18-24 Male Less than $25,000 NA 4.0 2.0 4.0 14 55+ Female $50,000 to $99,999 Post-graduate degree 4.0 4.0 4.0 15 55+ Female $100,000 to $149,999 Bachelor's degree 2.0 1.0 1.0 16 25-34 Female $150,000 or more Post-graduate degree 1.0 1.0 1.0 17 25-34 Male Less than $25,000 Post-graduate degree 4.0 1.0 2.0 18 35-54 Female $150,000 or more Post-graduate degree 4.0 2.0 3.0 19 18-24 Male $25,000 to $49,999 Post-graduate degree 4.0 NA NA 20 18-24 Male $25,000 to $49,999 Bachelor's degree 5.0 3.0 5.0 21 18-24 Female $50,000 to $99,999 Bachelor's degree 4.0 4.0 4.0 22 18-24 Female $25,000 to $49,999 Bachelor's degree 5.0 4.0 4.0 23 18-24 Male Less than $25,000 Post-graduate degree 4.0 1.0 4.0 24 55+ Female $100,000 to $149,999 Post-graduate degree 3.0 3.0 3.0 25 35-54 Female $25,000 to $49,999 Associate degree 5.0 4.0 4.0 26 35-54 Female $50,000 to $99,999 Post-graduate degree 4.0 3.0 4.0 27 35-54 Female $50,000 to $99,999 Post-graduate degree 1.0 1.0 3.0 28 35-54 Female $50,000 to $99,999 Bachelor's degree 2.0 2.0 2.0 29 18-24 Male Less than $25,000 Post-graduate degree 4.0 2.0 3.0 30 25-34 Female Less than $25,000 Post-graduate degree 3.0 1.0 NA 31 18-24 Female $25,000 to $49,999 Bachelor's degree 4.0 3.0 3.0 32 25-34 Male Less than $25,000 Associate degree 4.0 3.0 4.0 33 18-24 Female Less than $25,000 Bachelor's degree 4.0 3.0 4.0 34 < 18 Female $50,000 to $99,999 12th grade or less 4.0 3.0 4.0 35 25-34 Male Less than $25,000 Associate degree 4.0 3.0 4.0 36 35-54 Male $25,000 to $49,999 Graduated high school or equivalent 2.0 2.0 2.0 37 55+ Male $100,000 to $149,999 Post-graduate degree 3.0 2.0 4.0 38 25-34 Male $100,000 to $149,999 Associate degree 2.0 2.0 2.0 39 55+ Male $150,000 or more Post-graduate degree 4.0 2.0 4.0 40 55+ Male $50,000 to $99,999 Associate degree 4.0 3.0 4.0 41 25-34 Male $25,000 to $49,999 Graduated high school or equivalent 5.0 4.0 4.0 42 25-34 Male $50,000 to $99,999 Graduated high school or equivalent 4.0 3.0 4.0 43 18-24 Male Less than $25,000 Post-graduate degree NA NA NA 44 25-34 Female $25,000 to $49,999 Bachelor's degree 2.0 NA 1.0 45 25-34 Male $25,000 to $49,999 Post-graduate degree 1.0 1.0 1.0 46 25-34 Male Less than $25,000 Post-graduate degree NA NA NA 47 25-34 Female $25,000 to $49,999 Post-graduate degree 1.0 1.0 2.0 48 18-24 Male Less than $25,000 Bachelor's degree 1.0 NA NA 49 25-34 NA $50,000 to $99,999 Post-graduate degree 3.0 3.0 3.0 50 35-54 Male $50,000 to $99,999 Post-graduate degree 2.0 1.0 1.0 51 18-24 Female Less than $25,000 Post-graduate degree 4.0 4.0 5.0 52 25-34 Female $25,000 to $49,999 Post-graduate degree 4.0 2.0 3.0 53 25-34 Female $25,000 to $49,999 Post-graduate degree 2.0 NA NA 54 18-24 Female Less than $25,000 Graduated high school or equivalent 1.0 2.0 NA 55 25-34 Male $50,000 to $99,999 Bachelor's degree 4.0 2.0 4.0 56 25-34 Female $25,000 to $49,999 Bachelor's degree 4.0 2.0 NA 57 25-34 Male $25,000 to $49,999 Bachelor's degree 4.0 2.0 2.0 58 18-24 Female Less than $25,000 Bachelor's degree 1.0 1.0 1.0

Table 8: Survey data: demographic variables and control questions (respondents 58-117)

# Age Gender Income (USD) Education C1 C2 C3 59 25 -34 Male $50,000 to $99,999 Bachelor's degree 5.0 3.0 3.0 60 35-54 Male $150,000 or more Post-graduate degree 3.0 2.0 2.0 61 25-34 Male $50,000 to $99,999 Bachelor's degree 2.0 1.0 1.0 62 18-24 Male Less than $25,000 Post-graduate degree 2.0 2.0 2.0 63 25-34 Male $25,000 to $49,999 Post-graduate degree 3.0 3.0 NA 64 25-34 Male $50,000 to $99,999 Post-graduate degree 4.0 2.0 3.0 65 25-34 Male Less than $25,000 Post-graduate degree 2.0 1.0 4.0 66 25-34 Female $25,000 to $49,999 Post-graduate degree 4.0 2.0 4.0 67 35-54 Male $50,000 to $99,999 Post-graduate degree 1.0 2.0 2.0 68 35-54 Male $50,000 to $99,999 Post-graduate degree 4.0 3.0 4.0 69 25-34 Female Less than $25,000 Bachelor's degree 4.0 NA NA 70 25-34 Male $25,000 to $49,999 Post-graduate degree 2.0 2.0 2.0 71 35-54 Male $50,000 to $99,999 Bachelor's degree 3.0 2.0 3.0 72 25-34 Male $25,000 to $49,999 Post-graduate degree 3.0 2.0 2.0 73 55+ Male $150,000 or more Bachelor's degree 2.0 2.0 3.0 74 18-24 Male Less than $25,000 Post-graduate degree 5.0 2.0 4.0 75 25-34 Female $25,000 to $49,999 Post-graduate degree 4.0 3.0 2.0 76 35-54 Male $100,000 to $149,999 Post-graduate degree 1.0 1.0 1.0 77 25-34 Male $25,000 to $49,999 Post-graduate degree 4.0 3.0 3.0 78 25-34 Male $50,000 to $99,999 Post-graduate degree 5.0 3.0 5.0 79 25-34 Female $50,000 to $99,999 Bachelor's degree 1.0 1.0 1.0 80 25-34 Male Less than $25,000 Bachelor's degree 4.0 4.0 4.0 81 25-34 Female $50,000 to $99,999 Bachelor's degree 3.0 2.0 2.0 82 25-34 Female Less than $25,000 Bachelor's degree 4.0 2.0 4.0 83 18-24 Female Less than $25,000 Bachelor's degree 3.0 2.0 3.0 84 18-24 Female Less than $25,000 Bachelor's degree 5.0 4.0 5.0 85 25-34 Male $50,000 to $99,999 Post-graduate degree 4.0 2.0 2.0 86 18-24 Male Less than $25,000 Bachelor's degree 4.0 3.0 4.0 87 35-54 Female $25,000 to $49,999 Bachelor's degree 3.0 3.0 3.0 88 18-24 Female Less than $25,000 Bachelor's degree 2.0 2.0 2.0 89 35-54 Female $50,000 to $99,999 Bachelor's degree 2.0 2.0 2.0 90 18-24 NA Less than $25,000 Bachelor's degree 4.0 3.0 4.0 91 25-34 Male $50,000 to $99,999 Bachelor's degree 4.0 3.0 3.0 92 25-34 Female Less than $25,000 Post-graduate degree 4.0 NA NA 93 18-24 Male Less than $25,000 Bachelor's degree 2.0 1.0 NA 94 25-34 Male Less than $25,000 Post-graduate degree 2.0 2.0 3.0 95 35-54 Female $25,000 to $49,999 Bachelor's degree 3.0 NA NA 96 18-24 Female Less than $25,000 Bachelor's degree 4.0 3.0 4.0 97 25-34 Female Less than $25,000 Bachelor's degree 5.0 3.0 4.0 98 35-54 Male $100,000 to $149,999 Bachelor's degree 2.0 2.0 2.0 99 18-24 Female Less than $25,000 Post-graduate degree 5.0 2.0 4.0 100 18-24 Female Less than $25,000 Bachelor's degree 5.0 4.0 4.0 101 18-24 Female $25,000 to $49,999 Bachelor's degree 5.0 4.0 4.0 102 18-24 Female Less than $25,000 Bachelor's degree 3.0 NA 1.0 103 18-24 Male Less than $25,000 Post-graduate degree 1.0 1.0 3.0 104 35-54 Male $50,000 to $99,999 Post-graduate degree 5.0 3.0 4.0 105 18-24 Female $25,000 to $49,999 Bachelor's degree 4.0 4.0 2.0 106 25-34 Female $25,000 to $49,999 Bachelor's degree 4.0 NA NA 107 35-54 Male $50,000 to $99,999 Post-graduate degree 1.0 1.0 1.0 108 25-34 Male Less than $25,000 Bachelor's degree 4.0 2.0 4.0 109 18-24 Female Less than $25,000 Graduated high school or 1.0 1.0 1.0 110 18-24 Female Less than $25,000 Bachelor's degree 4.0 3.0 4.0 111 18-24 Male Less than $25,000 Post-graduate degree 5.0 4.0 4.0 112 25-34 Female $25,000 to $49,999 Bachelor's degree 4.0 NA NA 113 35-54 Male $150,000 or more Post-graduate degree 2.0 1.0 1.0 114 25-34 Female $25,000 to $49,999 Bachelor's degree 4.0 NA NA 115 25-34 Male $50,000 to $99,999 Post-graduate degree 3.0 1.0 1.0 116 18-24 Male Less than $25,000 Bachelor's degree 5.0 3.0 5.0 117 35-54 Male $25,999 to $49,000 Bachelor’s degree 4.0 3.0 5.0

Table 9: Survey data: Variables 6-19 (respondents 1-58)

# V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19

1 3.4 2.8 2.4 4.0 3.0 1.0 4.0 3.0 3.0 5.0 3.0 2.0 4.0 2.0 2 3.0 2.8 2.8 4.0 3.0 4.0 3.0 2.0 3.0 2.0 2.0 4.0 2.0 4.0 3 2.4 3.0 2.6 5.0 1.0 3.0 2.0 1.0 4.0 4.0 1.0 1.0 3.0 5.0 4 2.3 2.8 2.0 1.0 2.0 3.0 2.0 2.0 3.0 2.0 2.0 2.0 3.0 4.0 5 3.3 2.8 2.0 2.0 1.0 NA 3.0 2.0 3.0 3.0 2.0 3.0 3.0 5.0 6 3.4 3.2 2.8 2.0 3.0 2.0 3.0 3.0 3.0 3.0 2.0 1.0 2.0 3.0 7 3.3 3.6 2.8 4.0 3.0 2.0 4.0 3.0 4.0 4.0 3.0 4.0 3.0 5.0 8 2.3 2.2 3.0 3.0 4.0 3.0 3.0 3.0 3.0 4.0 3.0 3.0 3.0 4.0 9 2.6 3.8 2.2 4.0 1.0 2.0 1.0 2.0 1.0 3.0 1.0 1.0 2.0 5.0 10 2.1 3.2 3.2 3.0 3.0 3.0 3.0 3.0 5.0 4.0 2.0 3.0 4.0 5.0 11 3.6 3.4 2.6 4.0 1.0 2.0 3.0 2.0 3.0 4.0 3.0 3.0 3.0 5.0 12 3.3 3.0 1.8 3.0 3.0 4.0 5.0 3.0 4.0 3.0 2.0 4.0 4.0 5.0 13 2.7 3.2 2.4 5.0 1.0 2.0 2.0 2.0 5.0 4.0 2.0 2.0 2.0 5.0 14 2.9 3.4 2.2 4.0 5.0 5.0 5.0 3.0 5.0 5.0 4.0 2.0 5.0 5.0 15 3.1 2.6 1.0 3.0 2.0 2.0 3.0 2.0 3.0 4.0 3.0 5.0 3.0 5.0 16 3.7 2.8 1.6 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 17 2.2 3.4 1.8 3.0 2.0 3.0 NA 2.0 4.0 5.0 3.0 3.0 3.0 5.0 18 2.8 2.0 2.0 5.0 2.0 3.0 2.0 3.0 4.0 4.0 2.0 2.0 3.0 5.0 19 3.3 3.2 2.8 NA NA NA NA NA NA NA NA NA NA NA 20 3.0 3.6 4.4 2.0 2.0 3.0 5.0 1.0 5.0 4.0 3.0 3.0 4.0 5.0 21 2.3 2.8 3.6 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 22 3.7 3.2 3.2 3.0 1.0 2.0 3.0 2.0 4.0 4.0 3.0 2.0 3.0 4.0 23 2.7 3.4 2.2 5.0 1.0 3.0 3.0 1.0 3.0 2.0 2.0 3.0 1.0 5.0 24 3.0 3.2 2.4 4.0 2.0 2.0 3.0 2.0 4.0 2.0 2.0 4.0 2.0 4.0 25 2.1 3.6 3.6 5.0 3.0 4.0 4.0 4.0 5.0 5.0 3.0 5.0 3.0 5.0 26 2.6 2.8 2.0 2.0 2.0 3.0 2.0 3.0 3.0 2.0 2.0 2.0 3.0 3.0 27 3.3 2.8 1.6 4.0 4.0 4.0 4.0 4.0 5.0 4.0 3.0 4.0 4.0 5.0 28 2.6 2.8 2.0 4.0 2.0 2.0 3.0 1.0 4.0 3.0 1.0 4.0 2.0 5.0 29 2.6 3.2 3.2 5.0 2.0 2.0 3.0 1.0 2.0 5.0 3.0 4.0 3.0 5.0 30 1.6 2.6 1.0 4.0 1.0 1.0 3.0 1.0 5.0 4.0 1.0 5.0 3.0 4.0 31 2.4 3.6 3.2 3.0 2.0 3.0 3.0 2.0 3.0 4.0 2.0 4.0 3.0 5.0 32 2.7 3.4 3.4 2.0 1.0 2.0 3.0 1.0 3.0 4.0 2.0 1.0 2.0 4.0 33 2.0 3.4 3.4 1.0 2.0 2.0 4.0 1.0 3.0 5.0 3.0 1.0 3.0 5.0 34 3.4 3.6 3.2 4.0 3.0 1.0 3.0 2.0 4.0 5.0 2.0 2.0 2.0 4.0 35 3.7 3.4 3.4 2.0 3.0 1.0 3.0 4.0 3.0 4.0 3.0 2.0 3.0 5.0 36 3.0 3.0 3.0 3.0 1.0 3.0 2.0 2.0 3.0 3.0 2.0 2.0 2.0 3.0 37 2.6 2.4 2.4 1.0 3.0 3.0 3.0 3.0 4.0 3.0 3.0 3.0 3.0 5.0 38 3.4 3.6 3.2 2.0 3.0 4.0 4.0 3.0 4.0 4.0 4.0 4.0 4.0 5.0 39 1.9 3.2 3.2 4.0 2.0 2.0 3.0 2.0 2.0 4.0 3.0 2.0 2.0 4.0 40 2.6 3.8 3.0 1.0 3.0 2.0 4.0 3.0 2.0 4.0 4.0 1.0 3.0 5.0 41 2.9 3.6 3.6 1.0 3.0 2.0 3.0 2.0 2.0 3.0 1.0 2.0 3.0 3.0 42 4.3 3.0 3.8 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 43 3.3 2.6 2.6 3.0 1.0 2.0 4.0 1.0 1.0 4.0 3.0 2.0 1.0 5.0 44 1.9 3.4 2.6 2.0 2.0 2.0 3.0 2.0 4.0 3.0 2.0 2.0 2.0 5.0 45 2.7 2.8 1.2 5.0 3.0 2.0 2.0 2.0 3.0 4.0 3.0 4.0 2.0 5.0 46 2.6 2.8 2.4 3.0 3.0 1.0 4.0 3.0 4.0 3.0 2.0 1.0 2.0 4.0 47 3.4 2.8 2.8 3.0 3.0 4.0 3.0 2.0 3.0 5.0 3.0 4.0 3.0 5.0 48 4.1 3.0 2.6 2.0 1.0 3.0 2.0 1.0 1.0 5.0 4.0 4.0 1.0 5.0 49 2.7 2.8 2.0 2.0 2.0 3.0 2.0 2.0 3.0 4.0 2.0 2.0 2.0 4.0 50 1.3 2.8 2.0 1.0 1.0 NA 3.0 2.0 3.0 2.0 2.0 2.0 4.0 4.0 51 3.0 3.2 2.8 3.0 3.0 2.0 3.0 3.0 4.0 4.0 2.0 3.0 3.0 4.0 52 1.4 3.6 2.8 5.0 3.0 2.0 4.0 3.0 5.0 4.0 2.0 2.0 3.0 4.0 53 3.1 2.2 3.0 3.0 4.0 3.0 3.0 3.0 4.0 3.0 3.0 4.0 3.0 4.0 54 2.3 3.8 2.2 2.0 1.0 2.0 1.0 2.0 2.0 3.0 2.0 4.0 2.0 3.0 55 2.6 3.2 3.2 1.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 1.0 2.0 3.0 56 1.9 3.4 2.6 4.0 1.0 2.0 3.0 2.0 4.0 4.0 2.0 5.0 2.0 5.0 57 3.7 3.0 1.8 4.0 3.0 4.0 5.0 3.0 3.0 3.0 2.0 2.0 2.0 5.0 58 2.7 3.2 2.4 5.0 1.0 2.0 2.0 2.0 4.0 4.0 3.0 4.0 2.0 5.0

Table 10: Survey data: Variables 6-19 (respondents 58-117)

# V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19

59 1.9 3.6 3.2 4.0 4.0 1.0 4.0 3.0 4.0 4.0 3.0 3.0 3.0 5.0 60 2.0 3.0 2.2 4.0 3.0 3.0 2.0 2.0 4.0 3.0 2.0 2.0 2.0 4.0 61 2.6 3.2 2.4 1.0 4.0 3.0 2.0 4.0 3.0 3.0 3.0 2.0 3.0 4.0 62 2.0 3.2 4.0 1.0 3.0 1.0 4.0 3.0 NA NA 2.0 3.0 4.0 4.0 63 1.9 3.4 3.8 4.0 2.0 2.0 3.0 2.0 4.0 4.0 4.0 2.0 4.0 4.0 64 2.6 3.2 2.4 4.0 3.0 4.0 2.0 3.0 3.0 3.0 2.0 3.0 3.0 4.0 65 2.6 3.6 4.0 1.0 2.0 3.0 3.0 3.0 3.0 3.0 4.0 3.0 4.0 4.0 66 3.3 4.2 3.4 3.0 2.0 2.0 3.0 2.0 4.0 4.0 2.0 3.0 4.0 4.0 67 2.6 2.6 2.6 3.0 1.0 2.0 3.0 2.0 4.0 3.0 1.0 3.0 2.0 4.0 68 2.3 2.8 2.0 1.0 3.0 1.0 2.0 2.0 NA 4.0 2.0 2.0 2.0 3.0 69 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 70 3.6 2.6 3.0 1.0 4.0 4.0 3.0 4.0 2.0 4.0 3.0 3.0 3.0 4.0 71 2.0 3.0 2.2 2.0 3.0 2.0 3.0 1.0 NA 2.0 3.0 2.0 NA 5.0 72 1.9 2.6 1.8 3.0 2.0 3.0 2.0 2.0 3.0 3.0 2.0 2.0 1.0 4.0 73 2.4 2.4 1.2 3.0 2.0 3.0 3.0 2.0 3.0 2.0 2.0 3.0 2.0 3.0 74 1.6 3.0 2.6 1.0 3.0 3.0 2.0 NA 3.0 4.0 2.0 3.0 3.0 5.0 75 1.7 3.8 3.0 4.0 1.0 2.0 1.0 1.0 5.0 3.0 2.0 2.0 2.0 5.0 76 2.1 2.6 1.8 1.0 2.0 2.0 2.0 1.0 3.0 2.0 2.0 2.0 2.0 4.0 77 1.4 4.2 2.6 5.0 3.0 4.0 3.0 2.0 4.0 4.0 2.0 5.0 3.0 5.0 78 3.9 3.6 3.6 5.0 3.0 3.0 3.0 2.0 3.0 4.0 3.0 5.0 3.0 5.0 79 3.0 3.6 2.8 2.0 2.0 2.0 3.0 2.0 3.0 3.0 3.0 3.0 3.0 5.0 80 2.0 3.8 3.0 4.0 4.0 3.0 3.0 4.0 5.0 5.0 3.0 3.0 4.0 5.0 81 2.6 2.4 2.4 1.0 2.0 2.0 1.0 1.0 3.0 2.0 2.0 3.0 3.0 3.0 82 3.1 2.8 4.0 4.0 3.0 2.0 4.0 2.0 4.0 2.0 3.0 2.0 4.0 4.0 83 3.0 3.2 3.2 3.0 3.0 3.0 2.0 3.0 3.0 2.0 3.0 3.0 3.0 3.0 84 2.1 2.8 2.8 4.0 3.0 3.0 4.0 2.0 2.0 4.0 3.0 2.0 3.0 4.0 85 2.6 2.8 2.8 5.0 2.0 3.0 2.0 2.0 3.0 2.0 3.0 3.0 3.0 4.0 86 3.4 3.8 4.6 3.0 4.0 3.0 3.0 2.0 3.0 3.0 4.0 3.0 4.0 4.0 87 3.1 3.4 3.8 3.0 2.0 3.0 2.0 2.0 5.0 3.0 2.0 3.0 2.0 5.0 88 2.4 2.8 2.0 3.0 2.0 3.0 2.0 2.0 3.0 2.0 2.0 3.0 2.0 3.0 89 3.9 2.4 2.4 5.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 90 2.3 3.4 3.0 3.0 2.0 3.0 2.0 2.0 2.0 4.0 2.0 2.0 2.0 4.0 91 2.4 2.8 2.4 1.0 2.0 2.0 2.0 2.0 1.0 3.0 3.0 2.0 2.0 2.0 92 3.6 3.2 2.0 3.0 3.0 3.0 5.0 4.0 4.0 4.0 4.0 3.0 4.0 5.0 93 4.3 3.0 2.6 1.0 2.0 2.0 3.0 1.0 3.0 4.0 2.0 1.0 3.0 5.0 94 2.7 3.8 3.0 4.0 3.0 4.0 2.0 4.0 3.0 3.0 3.0 5.0 5.0 5.0 95 2.9 2.6 1.0 1.0 1.0 1.0 1.0 3.0 2.0 1.0 2.0 4.0 2.0 3.0 96 2.4 2.8 2.0 4.0 3.0 4.0 4.0 3.0 4.0 3.0 2.0 3.0 3.0 4.0 97 2.6 3.2 2.8 3.0 2.0 3.0 2.0 2.0 3.0 3.0 3.0 3.0 2.0 4.0 98 2.4 3.2 3.6 2.0 2.0 4.0 4.0 2.0 3.0 3.0 3.0 3.0 2.0 5.0 99 2.6 3.4 2.6 5.0 3.0 2.0 3.0 2.0 4.0 4.0 2.0 2.0 4.0 5.0 100 2.9 3.8 2.6 4.0 3.0 3.0 2.0 2.0 4.0 4.0 3.0 NA 3.0 3.0 101 2.0 2.4 2.4 4.0 2.0 3.0 3.0 2.0 3.0 4.0 2.0 2.0 3.0 5.0 102 3.4 1.8 1.8 5.0 1.0 5.0 2.0 2.0 3.0 5.0 2.0 5.0 1.0 5.0 103 3.3 3.2 4.0 5.0 5.0 3.0 4.0 4.0 5.0 5.0 4.0 4.0 5.0 5.0 104 3.3 3.2 2.4 1.0 2.0 2.0 3.0 2.0 2.0 4.0 3.0 2.0 2.0 3.0 105 2.9 3.2 2.4 5.0 3.0 1.0 3.0 2.0 4.0 5.0 2.0 4.0 4.0 5.0 106 3.4 3.4 3.4 3.0 3.0 3.0 4.0 3.0 3.0 4.0 4.0 4.0 4.0 5.0 107 2.0 3.6 2.0 4.0 1.0 2.0 3.0 1.0 2.0 1.0 1.0 3.0 2.0 5.0 108 3.7 3.6 4.4 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 109 2.8 3.4 1.8 3.0 1.0 1.0 4.0 1.0 5.0 5.0 2.0 3.0 3.0 5.0 110 4.3 4.0 3.2 2.0 2.0 3.0 3.0 2.0 3.0 3.0 3.0 4.0 4.0 4.0 111 2.9 3.2 4.0 5.0 3.0 5.0 3.0 3.0 4.0 5.0 3.0 5.0 5.0 5.0 112 2.3 3.8 3.4 4.0 3.0 5.0 4.0 3.0 4.0 3.0 3.0 4.0 4.0 4.0 113 2.1 3.4 2.6 1.0 1.0 2.0 2.0 2.0 2.0 3.0 2.0 3.0 2.0 4.0 114 3.6 2.8 2.4 3.0 1.0 1.0 2.0 1.0 3.0 4.0 2.0 2.0 2.0 4.0 115 1.0 2.6 1.0 2.0 5.0 5.0 1.0 1.0 5.0 5.0 1.0 1.0 5.0 5.0 116 2.4 3.2 3.2 1.0 3.0 2.0 3.0 3.0 3.0 5.0 2.0 2.0 3.0 4.0 117 2.3 3.2 2.4 5.0 4.0 3.0 2.0 2.0 3.0 1.0 3.0 3.0 2.0 4.0

Table 11: Survey data: Variables 20-30 (respondents 1-58)

# V20 V21 V22 V23 V24 V25 V26 V27 V28A V28B V29 V30 1 2.0 4.0 4.0 NA 4.0 4.0 5.0 4.0 5.0 5.0 5.0 3.0 2 2.0 3.0 NA 3.0 4.0 3.0 4.0 4.0 4.0 2.0 4.0 2.0 3 4.0 2.5 2.0 4.0 4.0 2.0 4.0 1.0 3.0 3.0 4.0 1.0 4 3.0 1.5 NA NA NA NA NA NA NA NA NA NA 5 3.7 1.5 NA 1.0 NA NA NA 1.0 1.0 1.0 1.0 1.0 6 4.3 3.0 3.0 NA 3.0 2.0 3.0 2.0 4.0 4.0 1.0 4.0 7 5.0 2.0 2.0 2.0 4.0 2.0 4.0 2.0 2.0 2.0 3.0 2.0 8 3.7 1.5 2.0 NA NA 1.0 1.0 1.0 1.0 1.0 NA 1.0 9 5.0 1.5 NA 1.0 NA NA NA NA NA NA NA NA 10 3.0 3.5 3.0 3.0 3.0 3.0 3.0 1.0 2.0 2.0 3.0 1.0 11 3.3 4.0 4.0 4.0 3.0 4.0 4.0 2.0 5.0 4.0 4.0 2.0 12 4.0 1.0 1.0 1.0 3.0 2.0 4.0 2.0 4.0 4.0 2.0 2.0 13 2.0 2.5 2.0 2.0 2.0 3.0 3.0 2.0 2.0 2.0 3.0 2.0 14 5.0 5.0 4.0 3.0 5.0 3.0 4.0 2.0 5.0 5.0 5.0 2.0 15 3.7 3.5 4.0 2.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 16 5.0 1.0 3.0 1.0 NA 1.0 1.0 1.0 1.0 1.0 1.0 NA 17 4.5 2.5 2.0 4.0 4.0 2.0 5.0 1.0 2.0 NA 4.0 1.0 18 3.0 2.0 4.0 NA NA 4.0 4.0 4.0 4.0 4.0 4.0 2.0 19 NA NA NA NA NA NA NA NA NA NA NA NA 20 1.0 3.0 4.0 3.0 2.0 4.0 4.0 5.0 5.0 5.0 5.0 3.0 21 2.0 4.0 4.0 4.0 2.0 2.0 4.0 2.0 4.0 4.0 2.0 4.0 22 2.3 2.0 2.0 5.0 2.0 5.0 3.0 4.0 5.0 5.0 5.0 4.0 23 3.7 4.0 4.0 3.0 3.0 3.0 3.0 1.0 3.0 3.0 3.0 1.0 24 4.7 2.0 3.0 2.0 4.0 3.0 4.0 2.0 4.0 2.0 4.0 3.0 25 2.0 4.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 26 3.0 2.5 3.0 3.0 3.0 2.0 4.0 2.0 3.0 2.0 4.0 3.0 27 3.3 1.5 2.0 2.0 2.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 28 4.0 2.0 3.0 2.0 3.0 5.0 2.0 1.0 2.0 2.0 2.0 2.0 29 2.0 4.0 4.0 4.0 2.0 4.0 5.0 2.0 4.0 4.0 4.0 2.0 30 2.7 3.0 NA 3.0 3.0 1.0 3.0 1.0 3.0 1.0 3.0 3.0 31 2.7 4.0 NA 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 32 2.3 3.0 4.0 2.0 4.0 2.0 4.0 2.0 4.0 2.0 2.0 2.0 33 1.0 2.5 3.0 5.0 2.0 4.0 5.0 4.0 2.0 2.0 5.0 1.0 34 2.3 3.5 3.0 4.0 4.0 4.0 4.0 2.0 4.0 4.0 4.0 3.0 35 3.3 2.0 3.0 4.0 3.0 NA 4.0 5.0 5.0 4.0 1.0 4.0 36 3.7 2.0 3.0 3.0 3.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 37 4.0 2.0 4.0 4.0 4.0 2.0 4.0 2.0 4.0 2.0 4.0 4.0 38 3.3 3.5 2.0 2.0 4.0 3.0 2.0 2.0 2.0 2.0 2.0 2.0 39 4.7 1.5 3.0 4.0 4.0 3.0 3.0 3.0 5.0 3.0 4.0 3.0 40 2.7 4.0 4.0 4.0 4.0 4.0 4.0 2.0 4.0 4.0 4.0 2.0 41 3.3 1.5 3.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 3.0 3.0 42 2.0 3.5 3.0 NA 3.0 4.0 2.0 4.0 4.0 4.0 3.0 2.0 43 2.0 3.0 3.0 NA NA NA NA NA NA NA NA NA 44 3.3 3.0 NA NA NA NA NA NA NA NA NA NA 45 5.0 1.0 1.0 1.0 3.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 46 3.0 2.5 NA NA NA NA NA NA NA NA NA NA 47 4.3 1.0 2.0 1.0 4.0 1.0 1.0 1.0 2.0 2.0 1.0 1.0 48 4.7 3.0 NA NA NA 1.0 1.0 1.0 2.0 2.0 3.0 NA 49 3.3 2.5 2.0 4.0 4.0 3.0 4.0 2.0 4.0 3.0 4.0 2.0 50 2.0 3.0 NA NA NA NA NA NA NA NA NA NA 51 2.0 4.0 4.0 3.0 3.0 4.0 4.0 2.0 4.0 4.0 3.0 4.0 52 4.0 3.0 4.0 4.0 NA 4.0 4.0 4.0 4.0 NA NA 2.0 53 3.0 4.0 NA 4.0 3.0 NA NA NA NA NA NA NA 54 4.0 2.0 NA 2.0 4.0 2.0 3.0 2.0 2.0 2.0 2.0 2.0 55 2.0 2.5 3.0 4.0 4.0 4.0 4.0 2.0 2.0 2.0 2.0 2.0 56 4.0 3.0 3.0 4.0 2.0 4.0 4.0 2.0 4.0 5.0 4.0 4.0 57 4.3 1.5 3.0 2.0 4.0 3.0 4.0 2.0 4.0 4.0 5.0 4.0 58 3.3 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

Table 12: Survey data: Variables 20-30 (respondents 58-117)

# V20 V21 V22 V23 V24 V25 V26 V27 V28A V28B V29 V30 59 2.3 4.0 3.0 4.0 3.0 NA 4.0 3.0 4.0 4.0 4.0 4.0 60 5.0 1.5 3.0 2.0 4.0 1.0 2.0 1.0 3.0 2.0 2.0 2.0 61 3.7 2.0 2.0 2.0 3.0 2.0 2.0 2.0 3.0 2.0 2.0 2.0 62 4.3 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 63 3.0 3.5 NA 4.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 3.0 64 3.3 2.5 4.0 3.0 5.0 3.0 3.0 2.0 4.0 4.0 4.0 3.0 65 4.3 1.5 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 66 4.7 4.5 3.0 4.0 4.0 3.0 2.0 2.0 4.0 2.0 2.0 2.0 67 4.0 1.0 1.0 1.0 3.0 3.0 2.0 1.0 1.0 1.0 2.0 1.0 68 3.7 2.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 3.0 4.0 69 NA NA NA NA NA NA NA NA NA NA NA NA 70 4.0 1.5 2.0 2.0 2.0 2.0 NA 2.0 2.0 2.0 2.0 2.0 71 3.3 2.0 3.0 3.0 4.0 2.0 4.0 2.0 3.0 3.0 4.0 2.0 72 2.7 2.0 2.0 4.0 2.0 1.0 4.0 1.0 4.0 4.0 2.0 2.0 73 3.7 1.5 3.0 4.0 4.0 3.0 3.0 1.0 3.0 2.0 2.0 2.0 74 3.3 2.0 2.0 2.0 4.0 4.0 NA 4.0 4.0 4.0 4.0 4.0 75 2.7 2.5 NA 4.0 3.0 2.0 4.0 1.0 1.0 1.0 4.0 1.0 76 3.7 2.0 NA NA NA NA NA NA NA NA NA NA 77 3.0 5.0 5.0 4.0 2.0 3.0 5.0 1.0 5.0 4.0 1.0 2.0 78 1.7 1.0 3.0 4.0 4.0 4.0 4.0 3.0 5.0 5.0 5.0 5.0 79 4.7 1.5 2.0 NA NA NA NA NA NA NA NA NA 80 1.7 2.0 4.0 5.0 2.0 3.0 5.0 4.0 4.0 4.0 5.0 2.0 81 4.0 2.0 2.0 2.0 4.0 2.0 2.0 2.0 4.0 4.0 4.0 2.0 82 2.0 2.5 4.0 2.0 4.0 4.0 4.0 3.0 4.0 2.0 2.0 2.0 83 2.3 3.0 2.0 2.0 3.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 84 3.3 3.0 4.0 4.0 4.0 4.0 4.0 2.0 3.0 2.0 5.0 2.0 85 3.7 1.5 2.0 3.0 2.0 3.0 3.0 3.0 4.0 4.0 3.0 3.0 86 3.0 2.0 4.0 3.0 3.0 3.0 4.0 4.0 4.0 3.0 4.0 3.0 87 3.3 3.0 3.0 4.0 3.0 2.0 4.0 2.0 4.0 3.0 3.0 3.0 88 3.3 3.0 2.0 3.0 3.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 89 2.0 2.0 3.0 2.0 2.0 2.0 4.0 4.0 4.0 4.0 4.0 4.0 90 3.3 3.0 4.0 4.0 4.0 2.0 4.0 2.0 4.0 4.0 4.0 2.0 91 3.0 2.0 2.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 3.0 3.0 92 3.0 NA NA 3.0 4.0 4.0 4.0 3.0 5.0 4.0 5.0 3.0 93 4.7 2.0 NA 1.0 5.0 1.0 4.0 4.0 4.0 2.0 4.0 2.0 94 2.7 2.0 3.0 4.0 2.0 3.0 3.0 3.0 4.0 2.0 4.0 3.0 95 2.0 3.5 NA NA NA NA NA NA NA NA NA NA 96 3.3 2.0 4.0 2.0 3.0 2.0 3.0 2.0 4.0 3.0 3.0 2.0 97 2.7 3.5 3.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 98 5.0 2.0 2.0 2.0 NA 2.0 4.0 2.0 2.0 4.0 4.0 NA 99 2.0 2.0 3.0 4.0 4.0 4.0 4.0 2.0 5.0 2.0 3.0 1.0 100 2.3 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 101 2.0 4.0 4.0 4.0 2.0 2.0 4.0 2.0 4.0 4.0 4.0 2.0 102 2.7 2.5 NA NA 3.0 3.0 4.0 1.0 3.0 1.0 NA 103 3.3 2.5 2.0 3.0 3.0 2.0 4.0 2.0 3.0 2.0 4.0 3.0 104 2.3 4.0 4.0 3.0 3.0 3.0 4.0 3.0 4.0 3.0 4.0 3.0 105 3.0 4.0 4.0 3.0 3.0 3.0 4.0 2.0 4.0 4.0 4.0 2.0 106 4.3 2.5 NA 2.0 4.0 2.0 4.0 2.0 3.0 4.0 4.0 NA 107 5.0 2.0 NA 1.0 2.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 108 3.7 3.5 4.0 2.0 3.0 4.0 4.0 2.0 4.0 2.0 5.0 4.0 109 5.0 2.0 2.0 4.0 5.0 2.0 3.0 1.0 2.0 2.0 2.0 2.0 110 2.7 3.0 4.0 4.0 4.0 5.0 5.0 2.0 5.0 4.0 4.0 2.0 111 3.0 3.0 3.0 4.0 4.0 3.0 4.0 4.0 4.0 4.0 4.0 3.0 112 4.3 4.0 NA 3.0 5.0 4.0 4.0 4.0 5.0 4.0 2.0 4.0 113 4.3 1.5 2.0 1.0 1.0 1.0 2.0 1.0 1.0 1.0 1.0 1.0 114 3.0 2.5 NA 4.0 2.0 4.0 4.0 3.0 5.0 4.0 5.0 2.0 115 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 116 2.7 4.0 5.0 4.0 3.0 3.0 3.0 5.0 5.0 4.0 3.0 4.0 117 2.0 3.5 3.0 4.0 4.0 4.0 4.0 3.0 4.0 4.0 4.0 1.0

8.0 REFERENCES

Awokuse, T., Yin, H. (2010). Does stronger intellectual property rights protection induce more bilateral trade? Evidence from Chinas imports. World Development, 38 (8), 1094-1104. Retrieved from http://0-web.ebscohost.com.uncclc.coast.uncwil.edu

Berman, B. (2008). Strategies to detect and reduce counterfeiting activity. Business Horizons, 51, 191-199. Retrieved from http://www.sciencedirect.com/science

Bian, X., & Moutinho, L. (2009). An investigation of determinants of counterfeit purchase consideration. Journal of Business Research, 63(3), 368-378. Retrieved from http://www.sciencedirect.com/science

Cabezas, M. (2010). Counterfeit medicines as global treat. Pharmaceutical Policy and Law, 12, 179- 192. Retrieved from http://0-web.ebscohost.com.uncclc.coast. uncwil.edu

Chaudry, P., & Walsh, M. (1996). An assessment of the impact of counterfeiting in international markets: The piracy paradox persists. The Columbia Journal of World Business, 34-48. Retrieved from http://0-web.ebscohost.com.uncclc.coast.uncwil. edu

Ellis, K. (2011, March 17). Counterfeit seizures up but value down in '10.Women's Wear Daily, 201(55), 6-11. Retrieved from http://0-search.ebscohost.com.uncclc.coast. uncw

Fashion. (2007). In The Free Dictionary by Farflex. Retrieved August 21, 2011, from http://encyclopedia2.thefreedictionary.com/fashion+industry

Fashion Industry. (2006). In Webster's Online Dictionary. Retrieved August 14, 2011, from http://www.websters-online-dictionary.org/

Fricker, R., & Schonlau, M. (2002). Advantages and disadvantages of internet research surveys: Evidence from the literature. Field Methods, 14 (4) 347-367. Retrieved from http://0- web.ebscohost.com.uncclc.coast.uncwil.edu

Furnham, A, & Valgeirsson, Halldor. (2007). the effect of life values and materialism on buying counterfeit products. The Journal of Socio-Economics, 36(5), 677-685. Retrieved from http://www.sciencedirect.com/science

Hamilton, M., Milne, B., Walker, R., Burger, O., Brown, J. (2007) the complex structure of hunter- gatherer social networks. The Royal Society, 274, 2195-2202. Retrieved from http://www.unm.edu/~marcusj/Hamilton%20et%20al%202007b.pdf

Histograms. (2011). Retrieved from http://www.moresteam.com/toolbox/t417.cfm

Hoerger, M. (2010). Participant dropout as a function of survey length in internet-mediated university studies: Implications for study design and voluntary participation in psychological research. Cyberpsychology, Behavior, and Social Networking, 13 (6), 697-700. Retrieved from http://0- web.ebscohost.com. uncclc.coast.uncwil.edu

John, O., & Naumann, L. (2010) Surviving two Critiques by block? The resilient big five have emerged as the paradigm for personality trait psychology. Psychological Inquiry, 21, 44-49. Retrieved from http://0-web.ebscohost.com.uncclc.coast. uncwil.edu

Juggessur, J, & Cohen, G. (2008). Is fashion promoting counterfeit brands? Journal of Brand Management, 16, 383-394. Retrieved from http://0-web.ebscohost.com.uncclc.coast.uncwil.edu

Lea, D. (2008). The Expansion and Restructuring of Intellectual Property and Its Implications for the Developing World. Ethical Theory & Moral Practice, 11(1), 37-60. Retrieved from

Mavlanova, T., & Benbunan-Fich, R. (2010). Counterfeit products on the internet: The role of seller- level and product-level information. International Journal of Electronic Commerce, 15(2), 79- 104. Retrieved from http://www.sciencedirect.com/science

Richins, M., & Dawson, S. (1992). Materialism and its measurement: Scale development and validation. Journal of Consumer Research, 19, 303-316. Retrieved from http://0- web.ebscohost.com.uncclc.coast.uncwil.edu

Sutherlin, J. (2009). Intellectual Property Rights: The West, India and China. Perspectives on Global Development & Technology, 8 (2/3), 399-413. Retrieved from http://0- web.ebscohost.com.uncclc.coast.uncwil.edu

Swami, V., Chamorro-Premuzic, T., & Furnham, A. (2009). Faking it: Personality and individual difference predictors of willingness to buy counterfeit goods. The Journal of Socio-Economics, 38, 820-825. Retrieved from http://0-web.ebscohost.com. uncclc.coast.uncwil.edu

Swift, E. (2003, May 26). Pssst...wanna buy some clubs? Sports Illustrated, 98(21), 66. Retrieved from http://0-search.ebscohost.com.uncclc.coast.uncwil.edu

Schwartz, S. (1994). Are there universal aspects in the structure and contents of human values? Journal of Social Issues, 50 (4), 19-45. Retrieved from http://onlinelibrary.wiley.com/doi/10.1111/j.1540-4560.1994.tb01196.x/pdf

Tu, K. (2010). Counterfeit fashion: the interplay between copyright and trademark law in original fashion designs and designer knockoffs. Texas Intellectual Property Law Journal, 18(3), 419- 449. Retrieved from http://0-ehis.ebscohost.com.uncclc.coast. uncwil.edu

U. S. Census Bureau. (2011). School enrollment by age. Retrieved October 2, 2011, from http://www.census.gov/compendia/statab/2011/tables/12s0223.pdf

U. S. Census Bureau. (2011). Income, expenditures, poverty, & wealth: Household income. Retrieved October 2, 2011, from http://www.census.gov/compendia /statab/2010/tables/12s0693.pdf