Featuring research by UNC Kenan-Flagler Business School Professor of Operations and Kenan Institute Senior Faculty Fellow Jay Swaminathan, Ivey Business School Associate Professor of Management Science and Hubert Pun and Tianjin University College of Management and Economics Professor Pengwen Hou
Counterfeiting is a severe problem with significant economic impact. In the clothing, cosmetics, handbags and watches industry, counterfeiting is estimated to cost US$98 billion annually. The economic impact of counterfeit electronic parts is estimated to be $169 billion. From the perspective of customers, there are two types of counterfeit products: deceptive and non-deceptive counterfeits. In the case of non-deceptive counterfeits, a customer can distinguish between a genuine article and a counterfeit version; she may still buy the counterfeit item because she cannot afford the genuine product. In contrast, the customer cannot differentiate a deceptive counterfeit item from the genuine product before buying it. Both types of counterfeits negatively affect a manufacturer’s profit and brand. In this research project, the authors focus on deceptive counterfeits, as blockchain-based solutions can help the customer make informed decisions by helping them identify deceptive counterfeits. The research cited in this report comes from the research paper, “Blockchain Adoption for Combating Deceptive Counterfeits,” authored by Hubert Pun, Ivey Business School; Jayashankar M. Swaminathian, University of North Carolina at Chapel Hill; and Pengwen Hou, Tianjin University College of Management and Economics.
Blockchain technology is a promising solution for establishing the genuineness of a product and identifying deceptive counterfeits. In a blockchain, each party in the supply chain is given a public key (their address on the blockchain) and a private key (i.e., a password). Products are tagged with the user’s identifier as it moves along the supply chain. Blockchain uses distributed ledgers that store all transactions across a shared database. By scanning the QR code with a smartphone, customers can check the entire history of the product. Firms such as Walmart, IBM, and Alibaba are initiating blockchain-based efforts to fight counterfeiting in a wide variety of products from food to pharmaceuticals.
Despite the capability of blockchain to identify counterfeited goods, there are at least two major roadblocks in its implementation. First is customers’ potential privacy concerns. While using blockchain, a customer is expected to leave her digital footprint (i.e., timestamp and digital signature) when the ownership of the product is transferred from the retailer to her. Furthermore, blockchain solutions, such as BlockVerify, Everledger, and Provenance, often require customers to register their digital identity. There is increased consumer concern about how firms will use this type of data and how well they will protect it from hackers. Second, implementation of a blockchain solution can be costly. The manufacturer incurs a cost for switching from the de facto standard of barcode to tags capable of storing much bigger identifiers; they also incur a cost for generating/processing an identifier for every unique item.
A country could suffer from a bad brand perception if counterfeiting or copying is rampant. In such situations, the government has a strong incentive to combat counterfeiting by encouraging blockchain adoption. The government could subsidize the blockchain implementation to nudge the manufacturer toward adoption. However, a manufacturer’s decision on whether to implement blockchain may not always align with the government’s interest.
In this research project, the authors examine how blockchain technology can be used by firms and government to combat counterfeiting. They consider a setting where a manufacturer sells products to customers in the presence of a counterfeiter. The counterfeit product looks identical to the manufacturer’s product, so customers cannot differentiate before purchasing (deceptive counterfeit). The manufacturer can use blockchain technology to prove the genuineness of its product, but the implementation is costly, and customers have privacy concerns around blockchain usage. Instead of adopting blockchain, the manufacturer could use a pricing strategy to signal product authenticity. They can also choose to adopt neither of these anti-counterfeiting strategies. The government has the option of providing a subsidy to the manufacturer to incentivize the implementation of the blockchain. Within this context, the authors explore the following research questions, using stylized mathematical modeling and game theory:
Which market conditions encourage a manufacturer to adopt blockchain technology to combat counterfeiting?
How do customers’ post-purchase regret about buying counterfeit products and concern about leaving a digital footprint affect blockchain implementation?
How does government subsidy motivate the manufacturer to adopt blockchain? What are the implications for social welfare?
The manufacturer has three options: to adopt blockchain to signal the genuineness of the product, use pricing to signal genuineness, or not adopt any anti-counterfeiting strategy. One of the critical factors that influence the manufacturer’s anti-counterfeiting strategy is the confidence customers have about the genuineness of the product in the market. In regions where legislation against counterfeiting is very strict, customers’ confidence would be high; in markets with more relaxed regulations, customers may have serious distrust about products sold in the market. Another critical factor influencing blockchain adoption is the quality level of the counterfeit product itself. Through rigorous analysis of the underlying setting, the authors characterize the optimal anti-counterfeiting strategy for the manufacturer.
Results (Figure 1) show that blockchain adoption may not be beneficial to the manufacturer in many settings. Only in markets where customers have an intermediate level of distrust about the products in the market such that uncertainty about authenticity is the highest should the manufacturer implement blockchain. In markets where there is a greater proportion of counterfeit products (e.g., in developing countries), customers may have serious distrust of the product. In this case, price-based signaling may be more effective than blockchain in indicating product authenticity. On the other hand, in markets where counterfeiters’ product quality is high, the manufacturer is better off not adopting any anti-counterfeiting strategy. Instead, they can take advantage of customers’ lack of knowledge on product type and instead price identically to the counterfeiter to avoid engaging in price competition. With other market conditions staying the same, blockchain is less likely to be adopted when the blockchain implementation is more expensive, or when customers are more concerned about privacy.
Social welfare in this context is defined as the sum of the manufacturer’s profit and the consumer surplus – specifically excluding the counterfeiter’s profit. To quantify the damage when customers purchase counterfeit products unknowingly, the authors define the notion of post-purchase regret: the difference in utility between what the customer expects before purchase and what he receives after purchase. Blockchain can be more effective than price-based signaling in eliminating customers’ post-purchase regret. This result highlights how customers may prefer a blockchain implementation, but the manufacturer may choose not to adopt.
When blockchain implementation is more expensive or when customers are more concerned about leaving their digital footprint, manufacturer profit, consumer surplus and social welfare decrease. The negative link between blockchain implementation cost and social welfare highlights why governments may consider subsidizing blockchain implementation.
When a government decides to offer a subsidy for blockchain implementation, it decides the optimal subsidy to maximize social welfare. When government subsidy is an option, blockchain implementation becomes more likely. The manufacturer will either adopt blockchain or not adopt any anti-counterfeiting strategy; it will never use price-based signaling strategy. For example, in Figure 1, the price-based signaling region will be added to the blockchain region. Even with government subsidy, if the counterfeiting firm provides a high enough quality product, and customers have high confidence in the market, the manufacturer will not implement blockchain.
Interestingly, the authors also find that governments will provide a smaller subsidy when blockchain implementation cost is higher, or if the customers’ privacy concern is higher. They also find that the subsidy decreases when the counterfeit product’s quality is higher.
This research paper is the first to study how governments and manufacturers should implement blockchain based on manufacturer profit and social welfare. The authors find that blockchain should be used when customers have intermediate distrust about products in the market. While blockchain is effective in eliminating consumer post-purchase regret, the manufacturer should not implement blockchain when the counterfeiter produces a product of comparable quality, even in the presence of government subsidy or costless implementation.
 Business and Finance Market Research Reports. 2018. Global Brand Counterfeiting Report.
 Havoscope Global Black Market Information. 2016.
Read the full research paper, here.