Current analysis of cryptocurrency mining industry
Vol 8, Issue 7, 2024
VIEWS - 479 (Abstract) 202 (PDF)
Abstract
In this regard the key factor determining the success of the mining industry is the cost of electricity. By understanding the risks associated with crypto mining industry. The method is based on systemic literature review and bibliometric analysis exploring keyword “bitcoin mining”. This review paper studies 50 papers for the period of 2019–2023. The results propose recommendations for crypto miners. Currently, the results confirm that bitcoin mainly depends on the consumption of inexpensive electricity. Consequently, the bitcoin network predominantly uses energy in regions where it is abundant and cannot be stored or exported. Most miners rely on electricity generated from hydroelectric power plants, geysers and geothermal sources, which are not easy to transport or store. Bitcoin will continue to look for such cost-effective and underutilized energy sources, as mining in urban areas or industrial centers will remain financially unviable. If the price of bitcoin stabilizes and a sufficient number of miners enter the market, it is quite possible that in the near future we may witness a fivefold increase in their energy consumption.
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An, J., Mikhaylov, A., Chang, T. (2024). Relationship between the popularity of a platform and the price of NFT assets. Finance Research Letters, 61, 3, 105057. https://doi.org/10.1016/j.frl.2024.105057
An, J., Mikhaylov, A., Jung, S. U. (2020). The Strategy of South Korea in the Global Oil Market. Energies, 13(10), 2491. https://doi.org/10.3390/en13102491
An, J., Mikhaylov, A. (2020). Russian energy projects in South Africa. Journal of Energy in Southern Africa, 31(3), 58–64, http://dx.doi.org/10.17159/2413-3051/2020/v31i3a7809
An, J., Mikhaylov, A. (2024). Technology-Based Forecasting Approach for recognizing trade-off between time-to-market reduction and devising a scheduling process in open innovation management. Journal of Open Innovation: Technology, Market, and Complexity, 10, 1, 100207, https://doi.org/10.1016/j.joitmc.2024.100207
Benhamed, A., Messai, A. S., & El Montasser, G. (2023). On the Determinants of Bitcoin Returns and Volatility: What We Get from Gets? Sustainability, 15(3), 1761. https://doi.org/10.3390/su15031761
Bouri, E., Cepni, O., Gabauer, D., et al. (2021). Return connectedness across asset classes around the COVID-19 outbreak. International Review of Financial Analysis, 73, 101646. https://doi.org/10.1016/j.irfa.2020.101646
Bouri, E., Saeed, T., Vo, X. V., et al. (2021). Quantile connectedness in the cryptocurrency market. Journal of International Financial Markets, Institutions and Money, 71, 101302. https://doi.org/10.1016/j.intfin.2021.101302
Candila, V., Maximov, D., Mikhaylov, A., et al. (2021). On the Relationship between Oil and Exchange Rates of Oil-Exporting and Oil-Importing Countries: From the Great Recession Period to the COVID-19 Era. Energies, 14(23), 8046. https://doi.org/10.3390/en14238046
Chen, J., Tang, G., Yao, J., et al. (2021). Investor Attention and Stock Returns. Journal of Financial and Quantitative Analysis, 57(2), 455–484. https://doi.org/10.1017/s0022109021000090
Chicarino, V., Albuquerque, C., Jesus, E., et al. (2020). On the detection of selfish mining and stalker attacks in blockchain networks. Annals of Telecommunications, 75(3–4), 143–152. https://doi.org/10.1007/s12243-019-00746-2
Chirtoaca, D., Ellul, J., & Azzopardi, G. (2020). A Framework for Creating Deployable Smart Contracts for Non-fungible Tokens on the Ethereum Blockchain. 2020 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS). https://doi.org/10.1109/dapps49028.2020.00012
CoinMarketCap (2024). Available: https://coinmarketcap.com/en/
Corbet, S., Larkin, C., & Lucey, B. (2020). The contagion effects of the COVID-19 pandemic: Evidence from gold and cryptocurrencies. Finance Research Letters, 35, 101554. https://doi.org/10.1016/j.frl.2020.101554
Dowling, M. (2021a). Fertile LAND: Pricing non-fungible tokens. Finance Research Letters, 44, 102096. https://doi.org/10.1016/j.frl.2021.102096
Dowling, M. (2021b). Is non-fungible token pricing driven by cryptocurrencies? Finance Research Letters, 44, 102097. https://doi.org/10.1016/j.frl.2021.102097
Fadeyi, O., Krejcar, O., Maresova, P., et al. (2019). Opinions on Sustainability of Smart Cities in the Context of Energy Challenges Posed by Cryptocurrency Mining. Sustainability, 12(1), 169. https://doi.org/10.3390/su12010169
Gao, X., Li, D., & Huang, W. (2023). Intergenerational education mobility: A machine learning perspective. World Journal of Vocational Education and Training, 5(1), 1–10. https://doi.org/10.18488/119.v5i1.3268
Gao, X., Gu, Z., Niu, S., & Ryu, S. (2022). Effects of International Tourist Flow on Startup Financing: Investment Scope and Market Potential Perspectives. SAGE Open, 12(4). https://doi.org/10.1177/21582440221126455
Goodell, J. W., & Goutte, S. (2021). Diversifying equity with cryptocurrencies during COVID-19. International Review of Financial Analysis, 76, 101781. https://doi.org/10.1016/j.irfa.2021.101781
Grobys, K., & Huynh, T. L. D. (2021). When Tether says “JUMP!” Bitcoin asks “How low?” Finance Research Letters, 47, 102644. https://doi.org/10.1016/j.frl.2021.102644
Guidi, B., Michienzi, A., & Ricci, L. (2020). Steem Blockchain: Mining the Inner Structure of the Graph. IEEE Access, 8, 210251–210266. https://doi.org/10.1109/access.2020.3038550
Hamill, P. A., Li, Y., Pantelous, A. A., et al. (2021). Was a deterioration in ‘connectedness’ a leading indicator of the European sovereign debt crisis? Journal of International Financial Markets, Institutions and Money, 74, 101300. https://doi.org/10.1016/j.intfin.2021.101300
Han, R., Foutris, N., & Kotselidis, C. (2019). Demystifying Crypto-Mining: Analysis and Optimizations of Memory-Hard PoW Algorithms. 2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS). https://doi.org/10.1109/ispass.2019.00011
Hasan, M., Naeem, M. A., Arif, M., et al. (2021). Higher moment connectedness in cryptocurrency market. Journal of Behavioral and Experimental Finance, 32, 100562. https://doi.org/10.1016/j.jbef.2021.100562
Häusler, K., & Xia, H. (2021). Indices on Cryptocurrencies: An Evaluation. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3895083
Hoang, L. T., & Baur, D. G. (2021). How Stable Are Stablecoins? SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3519225
Horky, F., Rachel, C., & Fidrmuc, J. (2022). Price determinants of non-fungible tokens in the digital art market. Finance Research Letters, 48, 103007. https://doi.org/10.1016/j.frl.2022.103007
Hossain, M. S. (2021). What do we know about cryptocurrency? Past, present, future. China Finance Review International, 11(4), 552–572. https://doi.org/10.1108/cfri-03-2020-0026
Huang, W., & Gao, X. (2023). Forecasting Bitcoin Futures: A Lasso-BMA Two-Step Predictor Selection for Investment and Hedging Strategies. SAGE Open, 13(1), 215824402311516. https://doi.org/10.1177/21582440231151652
Huang, Y., & Luk, P. (2020). Measuring economic policy uncertainty in China. China Economic Review, 59, 101367. https://doi.org/10.1016/j.chieco.2019.101367
Jabłczyńska, M., Kosc, K., Ryś, P., et al. (2023). Energy and cost efficiency of Bitcoin mining endeavor. PLOS ONE, 18(3), e0283687. https://doi.org/10.1371/journal.pone.0283687
Jia, D., & Li, Y. (2023). Bounded pool mining and the bounded Bitcoin price. Finance Research Letters, 52, 103529. https://doi.org/10.1016/j.frl.2022.103529
Jung, E., Le Tilly, M., Gehani, A., et al. (2019). Data Mining-Based Ethereum Fraud Detection. 2019 IEEE International Conference on Blockchain (Blockchain). https://doi.org/10.1109/blockchain.2019.00042
Li, J., Li, N., Peng, J., et al. (2019). Energy consumption of cryptocurrency mining: A study of electricity consumption in mining cryptocurrencies. Energy, 168, 160–168. https://doi.org/10.1016/j.energy.2018.11.046
Mathivanan, P., & Balaji Ganesh, A. (2023). ECG steganography using Base64 encoding and pixel swapping technique. Multimedia Tools and Applications, 82(10), 14945–14962. https://doi.org/10.1007/s11042-022-14072-8
Mathivanan, P., & Maran, P. (2023). A color image encryption scheme using customized map. The Imaging Science Journal, 71(4), 343–361. https://doi.org/10.1080/13682199.2023.2182547
Metaxas, T., Gallego, J. S., & Juarez, L. (2023). Sustainable urban development and the role of mega-projects: Experts’ view about Madrid Nuevo Norte Project. Journal of Infrastructure, Policy and Development, 7(2), 2161. https://doi.org/10.24294/jipd.v7i2.2161
Mikhaylov, A. (2021). Development of Friedrich von Hayekʼs theory of private money and economic implications for digital currencies. Terra Economicus, 19(1), 53–62. https://doi.org/10.18522/2073-6606-2021-19-1-53-62
Mikhaylov, A. (2022). Efficiency of renewable energy plants in Russia. Anais Da Academia Brasileira de Ciências, 94(4). https://doi.org/10.1590/0001-3765202220191226
Mikhaylov, A. (2023). Understanding the risks associated with wallets, depository services, trading, lending, and borrowing in the crypto space. Journal of Infrastructure, Policy and Development, 7(2), 2223. https://doi.org/10.24294/jipd.v7i2.2223
Mikhaylov, A., Dinçer, H., & Yüksel, S. (2023). Analysis of financial development and open innovation oriented fintech potential for emerging economies using an integrated decision-making approach of MF-X-DMA and golden cut bipolar q-ROFSs. Financial Innovation, 9(1). https://doi.org/10.1186/s40854-022-00399-6
Mikhaylov, A., Dinçer, H., Yüksel, S., et al. (2023). Bitcoin mempool growth and trading volumes: Integrated approach based on QROF Multi-SWARA and aggregation operators. Journal of Innovation & Knowledge, 8(3), 100378. https://doi.org/10.1016/j.jik.2023.100378
Mikhaylov, A., Bhatti, I.M., Dinçer, H., Yüksel, S. (2024). Integrated decision recommendation system using iteration-enhanced collaborative filtering, golden cut bipolar for analyzing the risk-based oil market spillovers. Computational Economics, 63, 305-338, https://doi.org/10.1007/s10614-022-10341-8
Moiseev, N., Mikhaylov, A., Dinçer, H., et al. (2023). Market capitalization shock effects on open innovation models in e-commerce: golden cut q-rung orthopair fuzzy multicriteria decision-making analysis. Financial Innovation, 9(1). https://doi.org/10.1186/s40854-023-00461-x
Mutalimov, V., Kovaleva, I., Mikhaylov, A., & Stepanova, D. (2021). Assessing regional growth of small business in Russia. Entrepreneurial Business and Economics Review, 9(3), 119-133, https://doi.org/10.15678/EBER.2021.090308
Náñez Alonso, S. L., Jorge-Vázquez, J., Echarte Fernández, M. Á., et al. (2021). Cryptocurrency Mining from an Economic and Environmental Perspective. Analysis of the Most and Least Sustainable Countries. Energies, 14(14), 4254. https://doi.org/10.3390/en14144254
Nerem, R. R., & Gaur, D. R. (2023). Conditions for advantageous quantum Bitcoin mining. Blockchain: Research and Applications, 4(3), 100141. https://doi.org/10.1016/j.bcra.2023.100141
Podhorsky, A. (2023). Taxing bitcoin: Incentivizing the difficulty adjustment mechanism to reduce electricity usage. International Review of Financial Analysis, 86, 102493. https://doi.org/10.1016/j.irfa.2023.102493
Rahman, M.M., Mikhaylov, A., Bhatti, I. (2024). The impact of investment in human capital on investment efficiency: a PLS-SEM approach in the context of Bangladesh. Quality and Quantity, https://doi.org/10.1007/s11135-024-01889-8
Qin, R., Yuan, Y., & Wang, F. Y. (2020). Optimal Block Withholding Strategies for Blockchain Mining Pools. IEEE Transactions on Computational Social Systems, 7(3), 709–717. https://doi.org/10.1109/tcss.2020.2991097
Saqib, A., Chan, T. H., Mikhaylov, A., et al. (2021). Are the Responses of Sectoral Energy Imports Asymmetric to Exchange Rate Volatilities in Pakistan? Evidence From Recent Foreign Exchange Regime. Frontiers in Energy Research, 9. https://doi.org/10.3389/fenrg.2021.614463
Sarkodie, S. A., Amani, M. A., Ahmed, M. Y., et al. (2023). Assessment of Bitcoin carbon footprint. Sustainable Horizons, 7, 100060. https://doi.org/10.1016/j.horiz.2023.100060
Siddique, I. M., Siddique, A. A., Smith, E. D., et al. (2023). Assessing the Sustainability of Bitcoin Mining: Comparative Review of Renewable Energy Sources. Journal of Alternative and Renewable Energy Sources, 10(1), 1–12. https://doi.org/10.46610/joares.2024.v10i01.001
Srbová, P., Režňáková, M., & Tomášková, A. (2023). Socially responsible activities and the economic performance of family businesses. Journal of Infrastructure, Policy and Development, 7(1), 1958. https://doi.org/10.24294/jipd.v7i1.1958
Tang, C., Li, C., Yu, X., et al. (2019). Cooperative Mining in Blockchain Networks with Zero-Determinant Strategies. IEEE Transactions on Cybernetics, 50(10), 4544–4549. https://doi.org/10.1109/tcyb.2019.2915253
Thuy, N. T. T., & Khai, L. D. (2020). A fast approach for bitcoin blockchain cryptocurrency mining system. Integration, 74, 107-114.
Wang, T., Liew, S. C., & Zhang, S. (2021). When blockchain meets AI: Optimal mining strategy achieved by machine learning. International Journal of Intelligent Systems, 36(5), 2183–2207. Portico. https://doi.org/10.1002/int.22375
Yang, R., Chang, X., Mišić, J., et al. (2020). Assessing blockchain selfish mining in an imperfect network: Honest and selfish miner views. Computers & Security, 97, 101956. https://doi.org/10.1016/j.cose.2020.101956
Yumashev, A., & Mikhaylov, A. (2020). Development of polymer film coatings with high adhesion to steel alloys and high wear resistance. Polymer Composites, 41(7), 2875–2880. Portico. https://doi.org/10.1002/pc.25583
Zhang, J. (2020). Interaction design research based on large data rule mining and blockchain communication technology. Soft Computing, 24(21), 16593–16604. https://doi.org/10.1007/s00500-020-04962-0
DOI: https://doi.org/10.24294/jipd.v8i7.4803
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