Is BlockChain Mining Profitable in the Long Run?

Article


Islam, N., Marinakis, Y., Olson, S., White, R. and Walsh, S. 2023. Is BlockChain Mining Profitable in the Long Run? IEEE Transactions on Engineering Management. 70 (2), pp. 386-399. https://doi.org/10.1109/TEM.2020.3045774
AuthorsIslam, N., Marinakis, Y., Olson, S., White, R. and Walsh, S.
Abstract

Blockchain technologies are at the heart of digital innovation and are a harbinger of Industry 4.0. Consequently, popular press and academic researchers alike have focused on its importance. Yet blockchain technologies’ most promising efforts, cryptocurrency and smart contracts, are underpinned by blockchain mining. The blockchain mining service is undergoing change, cryptocurrencies like Ethereum and others are nearing the end of their minting. Smart contracts are in their infancy. The financial impetus for providing the mining service has changed. Here, we add to the literature through a deep financial analysis of blockchain mining regarding its long-term financial viability. Our methods include a financial cost analysis and an analysis of the financial viability of cryptocurrency through focus on Ethereum. It is found that blockchain miners, despite initial profitability, cannot maintain sustainable financial viability without substantial fees. This article is important to those academics who focus on understanding how service technologies and products underpin Industry 4.0. Finally, this article contributes to the practitioners’ decision-making process to embrace blockchain mining as a technological entrepreneur.

JournalIEEE Transactions on Engineering Management
Journal citation70 (2), pp. 386-399
ISSN0018-9391
Year2023
PublisherIEEE
Digital Object Identifier (DOI)https://doi.org/10.1109/TEM.2020.3045774
Publication dates
Online15 Jan 2021
PrintFeb 2023
Publication process dates
Deposited17 Nov 2023
Permalink -

https://repository.uel.ac.uk/item/8wy8w

  • 3
    total views
  • 0
    total downloads
  • 0
    views this month
  • 0
    downloads this month

Export as

Related outputs

What keeps me engaging? A study of consumers' continuous social media brand engagement practices
Osei-Frimpong, K., Otoo, B. A. A., McLean, G., Islam, N. and Soga, L. R. 2023. What keeps me engaging? A study of consumers' continuous social media brand engagement practices. Information Technology and People. 36 (6), pp. 2440-2468. https://doi.org/10.1108/ITP-11-2021-0850
Emotions and food waste behavior: Do habit and facilitating conditions matter?
Jabeen, F., Dhir, A., Islam, N., Talwar, S. and Papa, A. 2023. Emotions and food waste behavior: Do habit and facilitating conditions matter? Journal of Business Research. 155 (Art. 113356). https://doi.org/10.1016/j.jbusres.2022.113356
Mobile Health Interventions for Cancer Care and Support: The Next Level of Digitalization in Healthcare
Tandon, A., Dhir, A. and Islam, N. 2023. Mobile Health Interventions for Cancer Care and Support: The Next Level of Digitalization in Healthcare. IEEE Transactions on Engineering Management. In Press. https://doi.org/10.1109/TEM.2023.3243724
Different strokes for different folks: Comparative analysis of 3D printing in large, medium and small firms
Dhir, A., Talwar, S., Islam, N., Alghafes, R. and Badghish, S. 2023. Different strokes for different folks: Comparative analysis of 3D printing in large, medium and small firms. Technovation. 125 (Art. 102792). https://doi.org/10.1016/j.technovation.2023.102792
Demystifying the Impact of Service Recovery Strategies: Evidence From Healthcare and Telecom Sectors
Shankar, A., Talwar, S., Islam, N., Alshibani, S. M. and Sharm, P. 2023. Demystifying the Impact of Service Recovery Strategies: Evidence From Healthcare and Telecom Sectors. IEEE Transactions on Engineering Management. In Press.
Resistance of multiple stakeholders to e-health innovations: Integration of fundamental insights and guiding research paths
Talwar, S., Dhir, A., Islam, N., Kaur, P. and Almusharraf, A. 2023. Resistance of multiple stakeholders to e-health innovations: Integration of fundamental insights and guiding research paths. Journal of Business Research. 166 (Art. 114135). https://doi.org/10.1016/j.jbusres.2023.114135
Investigating visibility affordance, knowledge transfer and employee agility performance. A study of enterprise social media
Pitafi, A. H., Rasheed, M. I., Islam, N. and Dhir, A. 2023. Investigating visibility affordance, knowledge transfer and employee agility performance. A study of enterprise social media. Technovation. 128 (Art.), p. 102874. https://doi.org/10.1016/j.technovation.2023.102874
Does digital transformation matter for operational risk exposure?
Uddin, M. H., Mollah, S., Islam, N. and Ali, M. H. 2023. Does digital transformation matter for operational risk exposure? Technological Forecasting and Social Change. 197 (Art. 122919). https://doi.org/10.1016/j.techfore.2023.122919
Emergency medical supplies scheduling during public health emergencies: algorithm design based on AI techniques
Xia, H., Sun, Z., Wang, Y., Zhang, Z., Kamal, M. M., Jasimuddin, S. M. and Islam, N. 2023. Emergency medical supplies scheduling during public health emergencies: algorithm design based on AI techniques. International Journal of Production Research. In Press. https://doi.org/10.1080/00207543.2023.2267680
Applying artificial intelligence in healthcare: lessons from the COVID-19 pandemic
Balasubramanian, S., Shukla, V., Islam, N. and Duong, L. 2023. Applying artificial intelligence in healthcare: lessons from the COVID-19 pandemic. International Journal of Production Research. In Press. https://doi.org/10.1080/00207543.2023.2263102
Resistance of multiple stakeholders to e-health innovations: Integration of fundamental insights and guiding research paths
Talwar, S., Dhir, A., Islam, N., Kaur, P. and Almusharraf, A. 2023. Resistance of multiple stakeholders to e-health innovations: Integration of fundamental insights and guiding research paths. Journal of Business Research. 166 (Art. 114135). https://doi.org/doi.org/10.1016/j.jbusres.2023.114135
Data sharing for business model innovation in platform ecosystems: From private data to public good
Kazantsev, N., Islam, N., Zwiegelaar, J., Brown, A. and Maull, R. 2023. Data sharing for business model innovation in platform ecosystems: From private data to public good. Technological Forecasting and Social Change. 192 (Art. 122515). https://doi.org/10.1016/j.techfore.2023.122515
Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda
Zirar, A., Ali, S. I. and Islam, N. 2023. Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda. Technovation. 124 (Art. 102747). https://doi.org/10.1016/j.technovation.2023.102747
Drivers of Sustainable Business Model Innovations: An Upper Echelon Theory Perspective
Dhir, A., Khan, S. J., Islam, N., Ractham, P. and Meenakshi, N. 2023. Drivers of Sustainable Business Model Innovations: An Upper Echelon Theory Perspective. Technological Forecasting and Social Change. 191 (Art. 122409). https://doi.org/10.1016/j.techfore.2023.122409
Theorizing the relationship between the digital economy and firm productivity: The idiosyncrasies of firm-specific contexts
Sun, Z., Zhao, L., Kaur, P., Islam, N. and Dhir, A. 2023. Theorizing the relationship between the digital economy and firm productivity: The idiosyncrasies of firm-specific contexts. Technological Forecasting and Social Change. 189 (Art. 122329). https://doi.org/10.1016/j.techfore.2023.122329