Search the archive.

This study shows that counterfeit and pirated products are being produced and consumed in virtually all economies, with Asia emerging as the single largest-producing region. In recent years, there has been an alarming expansion of the types of products being infringed, from luxury items (such as deluxe watches and designer clothing), to items that have an impact on personal health and safety (such as pharmaceutical products, food and drink, medical equipment, personal care items, toys, tobacco and automotive parts).

With respect to magnitude, the study notes that promising work has been done in a number of sectors to measure the extent of counterfeiting and piracy, but that much more can and should be done. The situation of each industry is unique, therefore techniques for carrying out such analysis need to be tailored to the sectors concerned.

The U.S. Patent and Trademark Office (USPTO) leads the federal government’s efforts to develop and strengthen domestic intellectual property policies, protections, and enforcement measures. It promotes the use of stronger and more effective intellectual property initiatives internationally as well. Among these projects, which include granting U.S. patents and registering U.S. trademarks, is a focus on understanding the scope of illicit trades of counterfeit goods, along with tracking the movements and impacts of such products.

As of 2018, counterfeiting is the largest criminal enterprise in the world, with domestic and international sales of counterfeit and pirated goods totaling between an estimated $1.7 trillion and $4.5 trillion a year—a higher amount than either drugs or human trafficking.2 Around 80 percent of these goods are produced in China, and 60 percent to 80 percent of those products are purchased by Americans.3 Both statistics provide a general sense of the significant impacts such illicit trade has on the U.S. economy, U.S. business interests, and U.S. innovations.

Last month U.S. Homeland Security Investigations and the NYPD announced the seizure of more than $1 billion worth of counterfeit luxury goods here. It was the largest bust of its kind in U.S. history.

Sands used to spend much of her time working with major fashion retailers cracking down on counterfeits sold on the streets and in back alleys. But she says her work has shifted to an explosion of counterfeits being sold direct-to-consumers online and through e-commerce platforms.

Ashly Sands, an intellectual property attorney and head of litigation and anti-counterfeiting at the law firm Epstein Drangel LLP, emphasized the severity of the issue during a recent visit to Canal Street in Manhattan, known for its bootleg market. "When I started, I guess about 12 years ago, we did this all the time. We would do monthly raids with our clients," she said. Last month U.S. Homeland Security Investigations and the NYPD announced the seizure of more than $1 billion worth of counterfeit luxury goods here. It was the largest bust of its kind in U.S. history. Sands used to spend much of her time working with major fashion retailers cracking down on counterfeits sold on the streets and in back alleys. But she says her work has shifted to an explosion of counterfeits being sold direct-to-consumers online and through e-commerce platforms. "It's massive. If you can get a real version of something, an authentic version of something, there is a 99% chance that you can get a counterfeit," said Sands. It's a booming industry, considered the largest illicit trade in the world, with $2 trillion worth of counterfeit products sold to consumers annually, according to the National Crime Prevention Council. U.S. Customs and Border Protection warns that online shopping has transformed the counterfeit trade into a breeding ground for criminals pushing potentially dangerous fakes. Counterfeit electronics, for instance, contribute to over 70 deaths and 350,000 serious injuries in the United States annually, the National Crime Prevention Council reports, shedding light on the grim consequences of purchasing fraudulent goods.

Although bad-to-worst case scenarios remain underexplored in the scientific literature, statements labeling climate change as catastrophic are not uncommon. UN Secretary-General António Guterres called climate change an “existential threat.” Academic studies have warned that warming above 5 °C is likely to be “beyond catastrophic” (50), and above 6 °C constitutes “an indisputable global catastrophe” (9).

Current discussions over climate catastrophe are undermined by unclear terminology. The term “catastrophic climate change” has not been conclusively defined. An existential risk is usually defined as a risk that cause an enduring and significant loss of long-term human potential (51, 52). This existing definition is deeply ambiguous and requires societal discussion and specification of long-term human values (52). While a democratic exploration of values is welcome, it is not required to understand pathways to human catastrophe or extinction (52). For now, the existing definition is not a solid foundation for a scientific inquiry.

Developing countries will be the most severely affected by accelerating climate change and, even excluding China from the calculation, are likely to emit more than half the annual global total of greenhouse gas (GHG) emissions as early as 2030. But the international community has not focused sufficiently on the range of development, adaptation, and resilience priorities and constraints these countries face in tackling the world’s interwoven emissions mitigation imperative. In an effort to help shift the global policy frame toward the crucial perspectives of developing countries themselves, we recently published an edited volume, Keys to climate action: How developing countries could drive global success and local prosperity. Within the volume, a wide range of distinguished contributors present both country case studies (on Bangladesh, Egypt, India, Indonesia, Nigeria, and South Africa) and wider geography-focused assessments (on East Africa, Africa as a whole, Latin America and the Caribbean, and the V20 group of vulnerable countries), in addition to an assessment of the overarching financing challenges. As a collection, these studies describe how climate change is hindering local development efforts while also providing new opportunities. They draw attention to the vital importance of elevating developing country perspectives in driving global climate action. They also offer central insights on the diverse and evolving issues that need to be front-of-mind when considering the relevant challenges.

Shoes, clothing, handbags, electronics: While trading items infringing on international intellectual property laws is illegal, the corresponding market has been bustling over the last couple of years. According to data from the report by the OECD and EUIPO, trading with counterfeit goods amounted to roughly $449 billion in 2019. As our chart comparing this amount to 2019 GDP figures of selected OECD countries and regions shows, selling fake sneakers, watches and clothes is about as lucrative as running a mid-sized European country.

For example, Ireland's economy generated approximately $431 billion according to OECD data, while Portugal claimed seventh place among the organization's member states with $372 billion. Interestingly, the market size of the trade with fake goods is also in roughly the same ballpark as Hong Kong's GDP of $466 billion, which is itself responsible for around 20 percent of the value of seized items between 2017 and 2019.

Open-source software quietly affects nearly every issue in AI policy, but it is largely absent from discussions around AI policy—policymakers need to more actively consider OSS’s role in AI.

Open-source software (OSS), software that is free to access, use, and change without restrictions, plays a central role in the development and use of artificial intelligence (AI). Across open-source programming languages such as Python, R, C++, Java, Scala, Javascript, Julia, and others, there are thousands of implementations of machine learning algorithms. OSS frameworks for machine learning, including tidymodels in R and Scikit-learn in Python, have helped consolidate many diverse algorithms into a consistent machine learning process and enabled far easier use for the everyday data scientist. There are also OSS tools specific to the especially important subfield of deep learning, which is dominated by Google’s Tensorflow and Facebook’s PyTorch. Manipulation and analysis of big data (data sets too large for a single computer) were also revolutionized by OSS, first by the Hadoop ecosystem and later by projects like Spark. These are not simply some of the AI tools—they are the best AI tools. While proprietary data analysis software may sometimes enable machine learning without the need to write code, it does not enable analytics that are as well developed as those in modern OSS.

Latin America, however, still has a lot of room to grow: ECLAC data indicate that the combined investment of all countries in the region in AI last year did not exceed 1.7% of U.S. investment or 5% of China. The difference is mainly explained by a still-developing digital infrastructure, which hinders the implementation of technology, and the gap in technical and data skills.

To overcome these challenges and accelerate the implementation of artificial intelligence, many organizations are betting on open source. With solutions offering everything from resilient and secure infrastructure to platforms for process automation, these technologies enable large-scale development, testing and execution of language models (LLMs) for business applications.

For several decades, open source has been a quiet revolution that has been democratizing people's ability to innovate and improve their communities. What began as a counter-cultural movement by AI researchers few decades ago has evolved today into a powerful global phenomenon. The concept of software freedom allowed programmers to do better work faster by explicitly permitting others to use, study, modify, and share their work. But as the discussions in New York reminded us all, open source is more than software development. It is about promoting transparency, collaboration, and innovation. By adopting open-source solutions, governments and organizations can create more efficient, cost-effective, and sustainable digital services. UNDP and ITU are excited to be engaging with the open-source community as we move the OSEE initiative forward.

The OSEE framework is intended as a practical guide for the adoption of open-source solutions as choices to countries to ensure that solutions are scalable, sustainable, and impactful. The framework is informed by insights gathered from open-source experts in different parts of the world and adopts lessons and best practices from the analysis of several successful open-source initiatives. It is envisioned that the framework will serve as a responsive ecosystem offer to the increasing demand from countries for building national-level support for open-source technology that can improve a range of services. This includes enhancing the capacity of local and regional public and private actors to adopt open-source solutions. Multi-purpose by design, the framework is designed to: Promote inclusive digital public infrastructure (DPI): Accelerating digital growth and transformative solutions, including digital public goods (DPGs); Build a comprehensive knowledge base: Maintaining a repository with videos, interviews, presentations, and hands-on training to support the adoption of open-source technologies; Facilitate community engagement: Building robust, lasting relationships with open-source communities nationally and globally to foster collaboration and innovation; Enhance training and education: Offering comprehensive and customized training to educate public sector employees on open-source best practices and tools; Improve knowledge and coordination: Strengthening local public and private sectors' capacities to support the creation, adoption, and sustainable maintenance of open-source solutions; and Accelerate digital transformation: Enabling rapid, reliable development of innovative public services that can adapt to the fast-paced digital landscape.

Consumers and businesses alike are concerned about artificial intelligence (AI). The more they question it, however, the more obvious the solution becomes: The antidote to public distrust of AI is transparency — and no one does transparency better than developers of open source software. “Transparency is essential for building trust in AI systems,” Nikhil Vadgama, co-founder of the DLT Science Foundation, a London-based nonprofit dedicated to advancing blockchain technology, wrote in a 2024 op-ed. “Users can scrutinize the underlying mechanisms, which helps mitigate the risk of unintended consequences and promotes responsible AI development.” For exactly that reason, open source software is already popular amongst a large contingent of business, government, and academic users, a growing number of whom have adopted it over the past 40 years. Its fans cite its low cost, increased flexibility, and highly collaborative nature as its biggest benefits, all of which encourage innovation. “History has proven that openness fosters innovation rather than hinders it,” Vadgama continued. “If AI projects are open-source, a global community of developers, researchers and enthusiasts can contribute their expertise, ideas and improvements. By making AI tools freely available, developers and organizations with limited resources can leverage state-of-the-art algorithms without the need for substantial financial investments. This inclusivity facilitates the widespread adoption of AI, benefiting a broader range of industries and applications.” Artificial intelligence figures, especially generative AI (GenAI), continue to grow. A study by Stanford University showed that investments in this technology reached US$25 billion last year, almost nine times more than in 2022. What makes the fruit of open source software possible is the open source community. Because it’s built on trust, it’s perfectly positioned to shepherd the development of AI. By applying the open source principles of the past to the technology of the future, it can help create the guardrails that are necessary to make AI safe, secure and successful. Open Source Software Benefits According to OpenLogic’s “2024 State of Open Source Report,” which tracks open source software usage and market trends, 95% of those who work with open source software say their organization has either increased or maintained its use of open source software in the past year. One-third say their organization has increased its use “significantly.” According to OpenLogic, what makes open source software most appealing to enterprises is its affordability. 36.64% of open source users cite the lack of a licensing fee and overall cost reduction as their greatest benefits. Also valuable is its ability to improve development velocity, cited by 30.71% of open source software users. Rounding out the top five reasons why organizations use open source software: its stability and available support (27.64%), the access it affords to innovations and new technologies (26.86%), and its ability to reduce vendor lock-in (21.29%). The last decade of open source software has been “incredibly transformative,” Richard Harmon, vice president and global head of financial services at Red Hat, told The Forecast. He said there are now more than a million open source projects worldwide, spanning government organizations, businesses, and academic institutions. “It’s a global community,” said Harmon. Democratizing AI Open source in AI development is helping to democratize AI by making it more accessible, according to Harmon. “Many of the most advanced algorithms are in the open source space,” he said, adding that there are free libraries and tools that can help people code more efficiently — including generative AI tools that can make code writing easier. Bev Gunn, global FSI ecosystem manager at Red Hat, added that open source software allows developers from different organizations and communities to contribute to emerging AI technologies, develop new talent, and improve productivity. “The extensive open source ecosystem provides exposure to niche areas while at the same time breaking down silos across industries,” she noted. She explained that the ecosystem collates many contributions around open source and AI development, making them work in a more structured, programmatic way. Yet open source isn’t just about accessibility. Equally important is governance, according to Harmon, who said regulated industries, in particular, must be able to audit their next-generation AI capabilities. Consider the banking sector, for example. Harmon said banks are combining open source software with AI to automate processes in ways that make them more efficient, effective, secure and resilient. Layered on top of this intelligent automation is the ability to monitor systems, identify problems and correct errors. SWIFT, a global payments system jointly owned by 11,000 banks, describes it as leveraging open source in AI development to build “financial transaction intelligence at scale.” Although it’s a compelling vision, realizing it will require the financial services industry to overcome key hurdles in AI development, such as licensing and data usage. Creating Impact with Innovation Alan Clark, a spokesperson for the Open Enterprise Linux Association (OpenELA), said the biggest reason companies are using open source software is that it has become the breeding ground for innovation. “People are throwing things out there and seeing if they stick,” said Clark, who leads the Industry Standards and New Initiatives Program at open source software company SUSE. The global collaboration that’s inherent in the open source software movement draws together people with different backgrounds and experiences to drive innovation. Gunn said this spirit of community and collaboration is exemplified by Red Hat OpenShift’s family of containerization software. In the last five years, major cloud providers like Microsoft and Amazon Web Services have embraced Red Hat OpenShift. “Building out managed service offerings within their own organizations with our technologies is kudos to the value that they see” in open source, Gunn said. But innovation isn’t just about generating revenue. Often, it’s also about generating impact, according to Harmon, who noted that Red Hat — the largest open source company in the world — employs many passionate engineers who are focused on solving challenges in various industries. “It’s not just about building a piece of software,” he said. “It’s about trying to make something better.” To get a sense for the positive impact open source can have when it’s coupled with AI, consider its influence on global issues like climate change, suggested Harmon, who cited as an example OS-Climate (OS-C), an open source collaboration community whose members — including Red Hat — are rallying together to build a data and software platform that will boost the flow of global capital into climate change mitigation and resilience. “Our goal is to build analytical tools and a data commons platform that enables the access, generation and structuring of relevant, global datasets. The platform, data and tools work in combination to generate vital information that can inform climate-related decision making,” OS-C explains on its website. “All of our infrastructure and tools are produced at a pre-competitive layer with open source end-to-end models.” ‘Trust and Meritocracy’ At its core, what makes open source work is its “survival of the fittest” mentality. “Open source projects are built on trust and meritocracy,” Clark said. “I can bring ideas, and people will evaluate those ideas. As the trust builds, they give me more rights and access to do more things.” In the early days of open source software, people were unsure about the code being generated and who had the rights to it. If that sounds familiar, it’s because AI is currently facing those very same challenges. According to Clark, it can overcome them by relying on the same meritocracy that ultimately endeared people to open source. “The way AI is going to fit in is using the same open source model that we have today,” he continued, noting that current large language models (LLMs) are not as deterministic as some enterprises need them to be — especially in regulated industries like finance and healthcare. “There’s a lot of model refinement that needs to happen.” Although AI seems to be everywhere, its adoption is still in its infancy. By applying to AI the same models and processes that helped open source build trust over decades, the open source community can establish itself as a leader in responsible AI. Therein lies the future of open source software. “Open source is not just an innovator," Clark concluded. “It’s also going to help … enterprises build … trust to consume AI in the future.”

Last month, when addressing the counterfeiting problem in China, Alibaba founder Jack Ma said, “The problem is that the fake products today, they make better quality, better prices than the real products, the real names.” This comment outraged international brands and brought the problem of Chinese shanzhai culture back into the spotlight. Translated literally, the phrase shanzhai mean “mountain village,” but in recent decades, the phrase was given a life of its own. Today, it means an imitation of trademarked brands, including (but not limited to) international fashion labels and electronic products. For a long time, this norm in China’s manufacturing sector has invited bitter denunciations. International companies have been infuriated by Chinese manufacturers’ infringements on their intellectual properties, while Chinese authorities and scholars have been perturbed about how the shanzhai phenomenon could jeopardize the country’s international standing and hamper the sprouting of creativity. Meanwhile, the “brighter sides” of shanzhai have often been muted. Recently, WIRED broadcast a four-part documentary on the development of shanzhai culture in the electronic manufacturing industry in Shenzhen, a major city in Guangdong Province, which is also the heartland of Chinese shanzhai products. A number of intriguing arguments appear in the documentary, though they do not necessarily reflect the stance of the tech magazine. Jack Ma’s viewpoint that shanzhai products could indeed be of better quality and of better prices is brought into the discussion; this contention is not only supported by local shanzhai producers, but also echoed by foreign investors. The documentary also explores the perspective that the affordability of shanzhai products has allowed a wider public to gain access to modern technology and, in this sense, a shanzhai manufacturer could be considered a modern Chinese “Robin Hood.” Without any doubt, the above allegations and shanzhai culture itself give life to inexhaustible debates, especially in regards to the moral grounds of the concept. Yet the most thought-provoking aspect of shanzhai culture concerns how it has shaped a unique ecosystem in the Chinese tech industry. In the West, the tech industry is rather monopolistic while manufacturers and designers usually take on quite different and well-defined roles. But in China, where shanzhai culture prevails, the market operates under a more competitive structure and the boundary between the two sides is nebulous. Often producers functions out of small workshops and simultaneously take on “design” duties. In this market structure, shanzhai producers are subject to fewer bureaucratic constraints in developing their new products. Equally important is their guerrilla-like modus operandi; it allows skills and market information to flow more quickly, and enhances their responsiveness to market demands. Originally, shanzhai producers made a living by making knock-offs with constituents from the same or similar manufacturers as those used by the real brands. But due to increasing market demand, today they also manufacture hybrid gadgets with self-developed components accompanied by parts from different names. In terms of technical procedures such as re-configuration, enhancing functions, and refining designs, as the WIRED documentary reveals, the shanzhai producers already enjoy a high level of skill that critics of shanzhai culture often underestimate. The most unique part of the ecosystem indeed lies in how the industry players view the sharing of techniques and skills. In the West, tech industry players hold patents in high regard, since patents are considered as the ultimate tool to protect intellectual property. But in China, shanzhai culture has forced industrial players to accept that preventing others from copying is impossible. Thus, they allow skills and techniques to be shared in an open-source environment, and waste no time and effort in playing the protracted games of patent lawsuits. Most importantly, as brands recognize that they could easily be replaced by their competitors, they strive to leap forward before others copy their techniques. Survival is always the most powerful source of motivation; the cruelty of the shanzhai ecosystem has made the Chinese market a perfect breeding ground (also battleground) where industrial players are motivated to achieve faster delivery, higher affordability, and higher quality. Intellectual property rights should be definitely respected and this article is not trying to justify shanzhai culture — which is often deemed as theft in Western culture — on moral grounds. But the security granted by patents could also be a hindrance barring innovators from leaping forward. In societies where innovators are too comfortable with patent systems, it will be difficult for them to accept a competitive, open-source ecosystem — not to mention the harrowing survival-oriented market structure. Now that shanzhai culture has prepared Chinese industrial players (and not only those in tech industry) to sustain themselves and even thrive in tough but effective environments, the country could indeed seize this advantage when coping with the “new normal” of slow growth. In 2015, Chinese government-backed venture funds raised an historic 1.5 trillion yuan ($224 billion) fund to support high-tech start-up companies. Known as the government guidance fund, the money has granted the government the power of purse over the future development of the Chinese tech industry. Certainly, the industry needs better-defined laws and patent systems to protect intellectual property. But it is also a golden opportunity for the government to strengthen the open source culture. Should it be able to preserve this unique advantage across various industries through well-designed sharing systems, the transition of the Chinese economy into a knowledge economy will surely be smoother than many observers expect.

Although bad-to-worst case scenarios remain underexplored in the scientific literature, statements labeling climate change as catastrophic are not uncommon. UN Secretary-General António Guterres called climate change an “existential threat.” Academic studies have warned that warming above 5 °C is likely to be “beyond catastrophic” (50), and above 6 °C constitutes “an indisputable global catastrophe” (9).

Current discussions over climate catastrophe are undermined by unclear terminology. The term “catastrophic climate change” has not been conclusively defined. An existential risk is usually defined as a risk that cause an enduring and significant loss of long-term human potential (51, 52). This existing definition is deeply ambiguous and requires societal discussion and specification of long-term human values (52). While a democratic exploration of values is welcome, it is not required to understand pathways to human catastrophe or extinction (52). For now, the existing definition is not a solid foundation for a scientific inquiry.

Brazil is in a strong position to give its people a better life while also successfully confronting the threat of climate change, a new World Bank Group report released today said. According to the Country Climate and Development Report for Brazil, the country can become a global clean energy power and save the Amazon with a development plan that grows more food on less land and better protects the forests. Brazil can grow its economy and fight climate change with relatively modest investments in agriculture and deforestation, the energy sector, and cities and transport systems. “Climate shocks could push between 800,000 and 3,000,000 Brazilians into extreme poverty as soon as 2030. It is crucial that Brazil accelerate investments towards a resilient and low carbon growth pathway,” said Johannes Zutt, World Bank Country Director for Brazil. “To take full advantage of its potential, Brazil would need net investments of 0.8 percent of its annual GDP each year between now and 2030. The World Bank is committed to work together with the Government of Brazil to achieve its development goals while delivering on climate action.” The report highlights that Brazil is already in a strong position to source more renewable energy. Almost half of Brazil’s energy supply, including over 80 percent of its electricity, already comes from renewables, compared with world averages of between 15 and 27 percent. Adding more clean energy would not be more expensive for Brazil than current plans to expand fossil fuel generation. An increase in investment for renewables would have higher upfront costs for power generation, transmission and storage. But the report says these would be fully recouped by savings in fuel and operations costs. Likewise, a move in transport and industry to more electrification and green hydrogen, produced with wind and solar instead of gas, would not increase costs for the economy.

In a special two-part edition of our series on physical marketplaces around the world that reportedly engage in the trade of counterfeit goods, we head to Brazil. Spanning the 14 states of the largest country in Latin America, brand protection experts reveal markets that brand owners should have on their enforcement radars.

The issue of counterfeit goods has been an increasing problem in Brazil for a number of years. According to a recent WTR magazine article, “thousands of factories in Brazil have dedicated themselves to producing counterfeits” in the past decade. The reasons for this include an ongoing economic crisis and political developments that disrupted the country’s international business chain. For that reason, domestically made fakes are available across the country.

For Brazil, real GDP was flat in the second half of 2023, registering a rounded 0.0% growth in both quarters. Real GDP in the fourth quarter was still up 2.2% from a year earlier. Strong agricultural output at the beginning of the year allowed for an export surge, which supported economic output for the full year. By the end of the year, however, that support faded. Private consumer spending fell slightly in the fourth quarter, while exports grew by just 0.2%. Government spending grew by 0.9% in that quarter, and gross fixed capital formation—a measure of investment—grew for the first time since the third quarter of 2022. Looking ahead though, Brazil’s economy will likely grow. Banco Central do Brasil (BCB), the country’s central bank, has been reducing interest rates, which should support the recovery ahead. At the same time, the labor market remains tight, which has allowed for relatively strong wage growth that is expected to usher in higher consumer spending. However, exports likely weighed on growth for the first quarter of this year, and a relatively tepid global economy may prevent exports from adding much to growth soon. Fortunately, the drag from the agricultural sector is expected to diminish this year, which would put a floor under export levels. In addition, should the federal government miss its fiscal targets, higher taxes or lower federal spending may need to be implemented

ABSTRACT As counterfeiting activity continues to thrive around the world, firms manufacturing genuine items work hard to discourage counterfeiting and protect their revenues. But the authors suggested the possibility that firms might benefit from counterfeits. The purpose of this research was to investigate the extent to which counterfeit items function as a promotion to increase sales of genuine items. Based on survey data from five luxury fashion product categories, Study 1 strongly confirmed that both consumers of counterfeit and genuine items generally prefer genuine items to counterfeits, that consumers of genuine items do not have a stronger intention to buy counterfeits than nonconsumers of genuine items, and that consumers of counterfeits also have a stronger purchase intention for the genuine items than nonconsumers of counterfeits. But the purchase intent difference between genuine and counterfeit items was smaller for consumers of counterfeits than for consumers of genuine items. Based on experimental data from two luxury handbag brands, Study 2 generally repeated the results of Study 1, but showed that when price information is provided the preference of genuine items diminishes, resulting in no significant difference from the preference of counterfeits. In addition, the hypothesis that consumers of counterfeits will show stronger intention to buy genuine items than will nonconsumers of counterfeits was not supported with price information given. Key words: Counterfeits, counterfeiting, genuine items, fashion, luxury Do Counterfeits Promote Genuine Products? Counterfeiting activity is a worldwide phenomenon rapidly increasing in every country, developing or developed. Counterfeits are now estimated to account for 5% to 7% of world trade (Business News 2005a). Counterfeiting is defined as “the act of producing or selling a product containing an intentional and calculated reproduction of a genuine trademark. A ‘counterfeit mark’ is identical to or substantially indistinguishable from a genuine mark” (McCarthy 2004). A counterfeit is called by many different names such as knock-off, imitation, fake, bogus, copy, copycat, and overrun, which are a little bit different in exact meaning but not different in creating similar problems to businesses (Wilke and Zaichkowsky 1999). Product categories being counterfeited include designer apparels, accessories, pharmaceuticals, computer memory chips, automobile parts, motorcycles, cell phones, cigarettes, liquor, tea, golf clubs, video game controllers, music, movies, and computer software, to name a few. Counterfeits of some product categories threaten consumer safety, often resulting in fatalities. For example, counterfeit airplane parts, recycled from downed airplanes, become a major source of plane crashes (Maloo and Darrow 2001). Counterfeit drugs account for five percent of all medicines, seriously damaging human lives and public health (Wechsler 2002). According to the U.S. Bureau of Customs and Border Protection, it is estimated that counterfeiting costs the United States $200 billion annually (The U.S. House of Representatives 2005). And Chinese counterfeits alone cost the U.S., Europe, and Japan more than $60 billion in retail sales (Time 2005). In summary, counterfeiting activity has been understood to be negative as damaging brand reputations, revenues, and profits; undermining research and development and marketing costs; threatening human lives; increasing legal fees to prosecute counterfeiters; and raising product prices (see Wee, Tan, and Cheok 1995). Accordingly, practitioners, researchers, and policy makers have paid a great amount of attention to developing strategies to discourage counterfeiting and protect the victims of counterfeiting. Various anti-counterfeiting measures have been proposed and implemented, including international treaties and enforcement of intellectual property rights to prosecute counterfeiters, use of multiple labeling and packaging techniques to make counterfeiting difficult, consumer education via a warning through an advertising campaign, tight control of retail stores, and consultations with both government agencies and other industry manufacturers (Chaudhury and Walsh 1996; Collins-Dodd and Zaichkowsky 1999). The documentary episode of a CEO’s anticounterfeiting operations in Thailand provides a clear illustration on the difficulty, complexity, and danger of fighting counterfeiters (Green and Smith 2002). Despite such efforts, counterfeiting continues to thrive around the world because of worldwide growing demand for well-known brands, lack of consumer and counterfeiter morality, technological advances enabling counterfeiting, production and distribution capabilities in less developed countries, and inadequate penalties for counterfeiters (Business Week 2005a; Wee et al. 1995). While firms are often unsuccessfully struggling with counterfeiting, however, some researchers have examined with cautions the possibility that firms might benefit from counterfeits because consumers of counterfeits might become buyers of genuine items. Such a possibility was examined, in particular, in computer software piracy. For example, Conner and Rumelt (1991) argued that piracy increases the number of program users, and the existence of pirated software stimulates an interest in legal copies. In conclusion, they objected to software protection because it decreases the number of users. Givon, Mahajan, and Muller (1995) found that the sales of genuine word processors and spreadsheets in the United Kingdom significantly increased because of active word-of-mouth resulting from pirates. Furthermore, Maltz and Chiappetta (2002) object to eliminating software pirates because they can help firms identify useful technologies. Two questions arise from the studies of software piracy. First, can the same findings be found in other product categories, especially luxury fashion product categories, which are the biggest counterfeit item categories? For example, in the UK, more than 64 per cent of the UK Customs seizure cases were fashion products, and of these cases, 17.5 per cent were fake Louis Vuitton goods (The Financial Times 2005). Likewise, the U.S. Customs and Border Protection reports fashion products as a major product type of counterfeiting. Second, pirated software functions in exactly the same way as the genuine item, but counterfeited fashion products do not. They are more often disposable, fall apart, and are inferior in all aspects except for brand name, although the quality of some counterfeits can be occasionally as high as that of the genuine items (Gentry et al. 2001). Therefore, it will be important to investigate whether or not counterfeiting of fashion products helps the sales of genuine items, as observed in the case of software piracy

While firms are often unsuccessfully struggling with counterfeiting, however, some researchers have examined with cautions the possibility that firms might benefit from counterfeits because consumers of counterfeits might become buyers of genuine items. Such a possibility was examined, in particular, in computer software piracy. For example, Conner and Rumelt (1991) argued that piracy increases the number of program users, and the existence of pirated software stimulates an interest in legal copies. In conclusion, they objected to software protection because it decreases the number of users. Givon, Mahajan, and Muller (1995) found that the sales of genuine word processors and spreadsheets in the United Kingdom significantly increased because of active word-of-mouth resulting from pirates. Furthermore, Maltz and Chiappetta (2002) object to eliminating software pirates because they can help firms identify useful technologies.

Two questions arise from the studies of software piracy. First, can the same findings be found in other product categories, especially luxury fashion product categories, which are the 3 biggest counterfeit item categories? For example, in the UK, more than 64 per cent of the UK Customs seizure cases were fashion products, and of these cases, 17.5 per cent were fake Louis Vuitton goods (The Financial Times 2005). Likewise, the U.S. Customs and Border Protection reports fashion products as a major product type of counterfeiting. Second, pirated software functions in exactly the same way as the genuine item, but counterfeited fashion products do not. They are more often disposable, fall apart, and are inferior in all aspects except for brand name, although the quality of some counterfeits can be occasionally as high as that of the genuine items (Gentry et al. 2001). Therefore, it will be important to investigate whether or not counterfeiting of fashion products helps the sales of genuine items, as observed in the case of software piracy.

It’s true that millions of fake luxury handbags are sold each year. But very few of them, if any, cannibalize the sales of the real thing. Davenport Lyons reports that in 2006 only 20% of purchasers of fake brands would have bought the genuine article. I suspect even this figure is an exaggeration.

The second flawed argument against fakes is that they harm the brand equity of the luxury brand. Perhaps, but I would argue that for every negative incident in which a fake damages a brand’s reputation, there is an equal number of occasions on which it helps protect the genuine brand.