IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v178y2022ics0040162522001160.html
   My bibliography  Save this article

Taming energy and electronic waste generation in bitcoin mining: Insights from Facebook prophet and deep neural network

Author

Listed:
  • Jana, Rabin K.
  • Ghosh, Indranil
  • Wallin, Martin W.

Abstract

The Bitcoin mining hosted in the blockchain network consumes enormous amounts of energy and generates electronic waste at an alarming rate. The paper aims to model and predict the future values of these two hazardous variables linked to conventional Bitcoin mining. We develop two predictive models using Facebook's Prophet algorithm and deep neural networks to identify and explain energy consumption and electronic waste generation patterns. The models rely on several explanatory features linked to the blockchain microstructure and the Bitcoin marketplace. We assess the predictive performance of the two models based on daily data of energy consumption and electronic waste generation and eleven key input features. We use local interpretable model-agnostic explanation (LIME) and Shapley additive explanation (SHAP) for explaining how these inputs can predict and control energy consumption and electronic waste generation. The findings assist in accurately estimating the future figures of energy discharge and electronic waste accumulation in the present Bitcoin mining setup. The study also reveals the block size to be the major driver.

Suggested Citation

  • Jana, Rabin K. & Ghosh, Indranil & Wallin, Martin W., 2022. "Taming energy and electronic waste generation in bitcoin mining: Insights from Facebook prophet and deep neural network," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:tefoso:v:178:y:2022:i:c:s0040162522001160
    DOI: 10.1016/j.techfore.2022.121584
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162522001160
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2022.121584?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Balasubramanian, Sreejith & Shukla, Vinaya & Sethi, Jaspreet Singh & Islam, Nazrul & Saloum, Roy, 2021. "A readiness assessment framework for Blockchain adoption: A healthcare case study," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    2. Sachin Kamble & Angappa Gunasekaran & Vikas Kumar & Amine Belhadi & Cyril Foropon, 2021. "A machine learning based approach for predicting blockchain adoption in supply chain," Post-Print hal-03539287, HAL.
    3. Sean J. Taylor & Benjamin Letham, 2018. "Forecasting at Scale," The American Statistician, Taylor & Francis Journals, vol. 72(1), pages 37-45, January.
    4. de Villiers, Charl & Kuruppu, Sanjaya & Dissanayake, Dinithi, 2021. "A (new) role for business – Promoting the United Nations’ Sustainable Development Goals through the internet-of-things and blockchain technology," Journal of Business Research, Elsevier, vol. 131(C), pages 598-609.
    5. Scharnowski, Stefan, 2021. "Understanding Bitcoin liquidity," Finance Research Letters, Elsevier, vol. 38(C).
    6. Poonam Garg & Bhumika Gupta & Ajay Kumar Chauhan & Uthayasankar Sivarajah & Shivam Gupta & Sachin Modgil, 2021. "Measuring the perceived benefits of implementing blockchain technology in the banking sector," Post-Print hal-03145195, HAL.
    7. Garg, Poonam & Gupta, Bhumika & Chauhan, Ajay Kumar & Sivarajah, Uthayasankar & Gupta, Shivam & Modgil, Sachin, 2021. "Measuring the perceived benefits of implementing blockchain technology in the banking sector," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    8. Nazifi, Amin & Murdy, Samantha & Marder, Ben & Gäthke, Jana & Shabani, Bardia, 2021. "A Bit(coin) of happiness after a failure: An empirical examination of the effectiveness of cryptocurrencies as an innovative recovery tool," Journal of Business Research, Elsevier, vol. 124(C), pages 494-505.
    9. Schlecht, Laura & Schneider, Sabrina & Buchwald, Arne, 2021. "The prospective value creation potential of Blockchain in business models: A delphi study," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    10. Malfuzi, A. & Mehr, A.S. & Rosen, Marc A. & Alharthi, M. & Kurilova, A.A., 2020. "Economic viability of bitcoin mining using a renewable-based SOFC power system to supply the electrical power demand," Energy, Elsevier, vol. 203(C).
    11. Kamble, Sachin S. & Gunasekaran, Angappa & Kumar, Vikas & Belhadi, Amine & Foropon, Cyril, 2021. "A machine learning based approach for predicting blockchain adoption in supply Chain," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    12. Koutmos, Dimitrios, 2018. "Bitcoin returns and transaction activity," Economics Letters, Elsevier, vol. 167(C), pages 81-85.
    13. Tandon, Anushree & Kaur, Puneet & Mäntymäki, Matti & Dhir, Amandeep, 2021. "Blockchain applications in management: A bibliometric analysis and literature review," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    14. Jana, Rabin K. & Ghosh, Indranil & Das, Debojyoti & Dutta, Anupam, 2021. "Determinants of electronic waste generation in Bitcoin network: Evidence from the machine learning approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    15. Li, Jingming & Li, Nianping & Peng, Jinqing & Cui, Haijiao & Wu, Zhibin, 2019. "Energy consumption of cryptocurrency mining: A study of electricity consumption in mining cryptocurrencies," Energy, Elsevier, vol. 168(C), pages 160-168.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yazıcı, Ali Fırat & Olcay, Ali Bahadır & Arkalı Olcay, Gökçen, 2023. "A framework for maintaining sustainable energy use in Bitcoin mining through switching efficient mining hardware," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    2. Mingxiong Bi & Chencheng Wang & Dian Fu & Xun Tan & Shurong Yu & Junbai Pan & Kun Lv, 2022. "Chinese-Style Fiscal Decentralization, Ecological Attention of Government, and Regional Energy Intensity," Energies, MDPI, vol. 15(22), pages 1-28, November.
    3. Ghosh, Indranil & Jana, Rabin K., 2024. "Clean energy stock price forecasting and response to macroeconomic variables: A novel framework using Facebook's Prophet, NeuralProphet and explainable AI," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    4. Yerushalmi, Erez & Paladini, Stefania, 2023. "Blockchain in Financial Intermediation and Beyond: What are the Main Barriers for Widespread Adoption?," CAFE Working Papers 22, Centre for Accountancy, Finance and Economics (CAFE), Birmingham City Business School, Birmingham City University.
    5. Ren, Yi-Shuai & Ma, Chao-Qun & Kong, Xiao-Lin & Baltas, Konstantinos & Zureigat, Qasim, 2022. "Past, present, and future of the application of machine learning in cryptocurrency research," Research in International Business and Finance, Elsevier, vol. 63(C).
    6. Zhang, Dongna & Chen, Xihui Haviour & Lau, Chi Keung Marco & Xu, Bing, 2023. "Implications of cryptocurrency energy usage on climate change," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    7. Kais Tissaoui & Taha Zaghdoudi & Sahbi Boubaker & Besma Hkiri & Mariem Talbi, 2024. "Testing the Nonlinear Long- and Short-Run Distributional Asymmetries Effects of Bitcoin Prices on Bitcoin Energy Consumption: New Insights through the QNARDL Model and XGBoost Machine-Learning Tool," Energies, MDPI, vol. 17(12), pages 1-19, June.
    8. Armenia, Stefano & Franco, Eduardo & Iandolo, Francesca & Maielli, Giuliano & Vito, Pietro, 2024. "Zooming in and out the landscape: Artificial intelligence and system dynamics in business and management," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    9. Huang, Yu-ting & Bai, Yu-long & Yu, Qing-he & Ding, Lin & Ma, Yong-jie, 2022. "Application of a hybrid model based on the Prophet model, ICEEMDAN and multi-model optimization error correction in metal price prediction," Resources Policy, Elsevier, vol. 79(C).
    10. Chi-Wei Su & Yuru Song & Hsu-Ling Chang & Weike Zhang & Meng Qin, 2023. "Could Cryptocurrency Policy Uncertainty Facilitate U.S. Carbon Neutrality?," Sustainability, MDPI, vol. 15(9), pages 1-15, May.
    11. Wang, Ning & Guo, Ziyu & Shang, Dawei & Li, Keyuyang, 2024. "Carbon trading price forecasting in digitalization social change era using an explainable machine learning approach: The case of China as emerging country evidence," Technological Forecasting and Social Change, Elsevier, vol. 200(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hiran, Kamal Kant & Dadhich, Manish, 2024. "Predicting the core determinants of cloud-edge computing adoption (CECA) for sustainable development in the higher education institutions of Africa: A high order SEM-ANN analytical approach," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    2. Ali, Fahad & Khurram, Muhammad Usman & Sensoy, Ahmet & Vo, Xuan Vinh, 2024. "Green cryptocurrencies and portfolio diversification in the era of greener paths," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    3. Rakshit, Sandip & Islam, Nazrul & Mondal, Sandeep & Paul, Tripti, 2022. "Influence of blockchain technology in SME internationalization: Evidence from high-tech SMEs in India," Technovation, Elsevier, vol. 115(C).
    4. Kraus, Sascha & Kumar, Satish & Lim, Weng Marc & Kaur, Jaspreet & Sharma, Anuj & Schiavone, Francesco, 2023. "From moon landing to metaverse: Tracing the evolution of Technological Forecasting and Social Change," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    5. Anatolyy Dzyuba & Irina Solovyeva & Dmitry Konopelko, 2023. "Managing Electricity Costs in Industrial Mining and Cryptocurrency Data Centers," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 76-90, July.
    6. Umara Noreen & Attayah Shafique & Zaheer Ahmed & Muhammad Ashfaq, 2023. "Banking 4.0: Artificial Intelligence (AI) in Banking Industry & Consumer’s Perspective," Sustainability, MDPI, vol. 15(4), pages 1-16, February.
    7. Mahmoona Khalil & Kausar Fiaz Khawaja & Muddassar Sarfraz, 2022. "The adoption of blockchain technology in the financial sector during the era of fourth industrial revolution: a moderated mediated model," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2435-2452, August.
    8. Dehghani, Milad & William Kennedy, Ryan & Mashatan, Atefeh & Rese, Alexandra & Karavidas, Dionysios, 2022. "High interest, low adoption. A mixed-method investigation into the factors influencing organisational adoption of blockchain technology," Journal of Business Research, Elsevier, vol. 149(C), pages 393-411.
    9. Michael L. Polemis & Mike G. Tsionas, 2023. "The environmental consequences of blockchain technology: A Bayesian quantile cointegration analysis for Bitcoin," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1602-1621, April.
    10. Zhang, Xi & Cheng, Yihang & Chen, Aoshuang & Lytras, Miltiadis & de Pablos, Patricia Ordóñez & Zhang, Renyu, 2022. "How rumors diffuse in the infodemic: Evidence from the healthy online social change in China," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    11. Latan, Hengky & Lopes de Sousa Jabbour, Ana Beatriz & Sarkis, Joseph & Chiappetta Jabbour, Charbel Jose & Ali, Murad, 2024. "The nexus of supply chain performance and blockchain technology in the digitalization era: Insights from a fast-growing economy," Journal of Business Research, Elsevier, vol. 172(C).
    12. Chand Bhatt, Priyanka & Kumar, Vimal & Lu, Tzu-Chuen & Daim, Tugrul, 2021. "Technology convergence assessment: Case of blockchain within the IR 4.0 platform," Technology in Society, Elsevier, vol. 67(C).
    13. Pandey, Dharen Kumar & Hassan, M.Kabir & Kumari, Vineeta & Zaied, Younes Ben & Rai, Varun Kumar, 2024. "Mapping the landscape of FinTech in banking and finance: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 67(PA).
    14. Chiarello, Filippo & Fantoni, Gualtiero & Hogarth, Terence & Giordano, Vito & Baltina, Liga & Spada, Irene, 2021. "Towards ESCO 4.0 – Is the European classification of skills in line with Industry 4.0? A text mining approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    15. Helder Miguel Correia Virtuoso Sebastião & Paulo José Osório Rupino Da Cunha & Pedro Manuel Cortesão Godinho, 2021. "Cryptocurrencies and blockchain. Overview and future perspectives," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 305-342.
    16. Sahebi, Iman Ghasemian & Mosayebi, Alireza & Masoomi, Behzad & Marandi, Fatemeh, 2022. "Modeling the enablers for blockchain technology adoption in renewable energy supply chain," Technology in Society, Elsevier, vol. 68(C).
    17. Ieva Meidute-Kavaliauskiene & Amir Karbassi Yazdi & Amir Mehdiabadi, 2022. "Integration of Blockchain Technology and Prioritization of Deployment Barriers in the Blood Supply Chain," Logistics, MDPI, vol. 6(1), pages 1-16, March.
    18. Nguyen, Loan T.Q. & Hoang, Thinh G. & Do, Linh H. & Ngo, Xuan T. & Nguyen, Phuong H.T. & Nguyen, Giang D.L. & Nguyen, Giang N.T., 2021. "The role of blockchain technology-based social crowdfunding in advancing social value creation," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    19. Paul, Tripti & Mondal, Sandeep & Islam, Nazrul & Rakshit, Sandip, 2021. "The impact of blockchain technology on the tea supply chain and its sustainable performance," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    20. Fairouz Mustafa & Suman Lodh & Monomita Nandy & Vikas Kumar, 2022. "Coupling of cryptocurrency trading with the sustainable environmental goals: Is it on the cards?," Business Strategy and the Environment, Wiley Blackwell, vol. 31(3), pages 1152-1168, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:178:y:2022:i:c:s0040162522001160. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.