A sharp rise in the rate of cryptocurrencies led to natural consequences – the rush demand for graphic processing units (GPUs) that can be used for mining resulted in their shortage. Moreover, high-performance GPUs have completely disappeared from the open market, severely damaging different industries such as gaming and designing industries. The GPU market uses a simple supply-demand principle. After an increase in demand, while the supply level falls or remains the same, the cost of the cards will rise respectively. It is essential to understand that the crypto market has already become a valuable part of the global economy. Mueller (2020) supports the claim: “Since the introduction of Bitcoin, the cryptocurrency market has grown substantially, reaching a combined market capitalization of over 390 billion USD for all cryptocurrencies” (p. 1). This also affects the already unsteady balance of the market – the mining process becomes increasingly complicated because of the involvement of the big companies who strive to make it impossible for regular users to mine at home. The topic of the market’s perspective remains open. However, there are some ways to alleviate the future of the GPU crisis.
One of the biggest contributors to the current situation with GPUs is scalpers. They create an artificial deficit of the items by buying out the entire stock to resell them at a higher price. The restriction of one order for one person does not apply to them, as they use bots to bypass this limitation, simultaneously ordering multiple copies through different proxies and using different customer data. This makes the scalpers untraceable. In this case, even the classical market regulation, when the price determines the value of the goods for different kinds of buyers, does not work properly.
Moreover, when a company begins to correct their pricing and distributing course, it may create a negative bias from regular customers, which can snowball and lead to a downtrend for the brand. Although the companies try to use different security methods to prevent the bots from overriding their sales, the technology is not fully developed. One of the ways to resolve the bot problem would be integrative research of the existing digital security systems. The accumulated studies of protective algorithms and bot behavior patterns would contribute to developing a new, more effective approach to digital security.
A good example of such an approach is the cryptocurrency transactions ledger known as a blockchain. Huang et al. (2014) state, that “While individual transactions can be validated simply by reading the chain, preventing double-spending and other misbehavior requires ensuring that there is only one append-only ledger, and the integrity of the blockchain is ensured through the mining process” (p. 2). All cryptocurrency transactions are recorded on the blockchain; however, blockchains do not contain real user identities. Although the amount of thefts, hacks, and fraud in the cryptocurrency market is still high, the implementation of sophisticated blockchain analysis solutions is paying off by providing transaction monitoring, risk assessment, and investigations. The main idea is to link addresses on the blockchain with real individuals or organizations – this allows the analyzing tools to detect and report bots or suspicious activity. “Through blockchain-based networks, individuals and organizations can source ideas, information, capital, and labor, and enforce contracts for digital assets with substantially reduced frictions,” claim Catalini and Gans (2020, p. 22). The blockchain analysis solutions can be implemented into the regular market security system to help identify scalpers and prevent stock buying-out.
Catalini, C., & Gans, J. S. (2020). Some simple economics of the blockchain. Communications of the ACM, 63(7), 80–90. Web.
Huang, D. Y., McCoy, D., Dharmdasani, H., Meiklejohn, S., Dave, V., Grier, C., … Levchenko, K. (2014). Botcoin: Monetizing stolen cycles. Proceedings 2014 Network and Distributed System Security Symposium. Web.
Mueller, P. (2020). Cryptocurrency mining: Asymmetric response to price movement. SSRN Electronic Journal. Web.