IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v202y2024ics1364032124004076.html
   My bibliography  Save this article

Digital technologies for a net-zero energy future: A comprehensive review

Author

Listed:
  • Ferdaus, Md Meftahul
  • Dam, Tanmoy
  • Anavatti, Sreenatha
  • Das, Sarobi

Abstract

The energy sector plays a vital role in achieving a sustainable net-zero future, and the adoption of advanced technologies such as AI, blockchain, quantum computing, digital twin, cloud computing, big data, IoT, and robotics is crucial to this transition. This paper presents a comprehensive review of over 2,000 papers to investigate the potential of these technologies in transforming the energy landscape. The analysis reveals nine main themes that emphasize the importance of these technologies in improving energy management, integrating renewable sources, and facilitating the transition to net zero emissions. The study highlights the need for future research in areas such as enhancing blockchain platforms, improving integration with traditional power systems, and refining regulations and incentives to support the adoption of these technologies. Additionally, the paper addresses the challenges faced in implementing quantum computing and digital twin technology in the energy sector and proposes potential solutions. The findings emphasize the critical role of these technologies in driving the energy sector towards a sustainable net-zero future and the need for continued research and development to align with global sustainability goals. This review provides valuable insights for researchers, policymakers, and industry stakeholders, emphasizing the importance of collaborative efforts in utilizing the potential of these technologies to create a more sustainable and resilient energy system.

Suggested Citation

  • Ferdaus, Md Meftahul & Dam, Tanmoy & Anavatti, Sreenatha & Das, Sarobi, 2024. "Digital technologies for a net-zero energy future: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 202(C).
  • Handle: RePEc:eee:rensus:v:202:y:2024:i:c:s1364032124004076
    DOI: 10.1016/j.rser.2024.114681
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032124004076
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rser.2024.114681?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. Jennifer Cronin & Gabrial Anandarajah & Olivier Dessens, 2018. "Climate change impacts on the energy system: a review of trends and gaps," Climatic Change, Springer, vol. 151(2), pages 79-93, November.
    2. Yu, Wei & Patros, Panos & Young, Brent & Klinac, Elsa & Walmsley, Timothy Gordon, 2022. "Energy digital twin technology for industrial energy management: Classification, challenges and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    3. Sara Saberi & Mahtab Kouhizadeh & Joseph Sarkis & Lejia Shen, 2019. "Blockchain technology and its relationships to sustainable supply chain management," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 2117-2135, April.
    4. Di Giorgio, Alessandro & Liberati, Francesco, 2014. "Near real time load shifting control for residential electricity prosumers under designed and market indexed pricing models," Applied Energy, Elsevier, vol. 128(C), pages 119-132.
    5. Lacity, Mary & Willcocks, Leslie P. & Craig, Andrew, 2015. "Robotic process automation: mature capabilities in the energy sector," LSE Research Online Documents on Economics 64520, London School of Economics and Political Science, LSE Library.
    6. Li, Rui & Xu, Shoufu & Zhang, Yun, 2023. "Can digital transformation reduce within-firm pay inequality? Evidence from China," Economic Modelling, Elsevier, vol. 129(C).
    7. Santos, Maria João & Ferreira, Paula & Araújo, Madalena, 2016. "A methodology to incorporate risk and uncertainty in electricity power planning," Energy, Elsevier, vol. 115(P2), pages 1400-1411.
    8. Dwivedi, Yogesh K. & Hughes, Laurie & Ismagilova, Elvira & Aarts, Gert & Coombs, Crispin & Crick, Tom & Duan, Yanqing & Dwivedi, Rohita & Edwards, John & Eirug, Aled & Galanos, Vassilis & Ilavarasan, , 2021. "Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy," International Journal of Information Management, Elsevier, vol. 57(C).
    9. Ahmed M. Nassef & Abdul Ghani Olabi & Hegazy Rezk & Mohammad Ali Abdelkareem, 2023. "Application of Artificial Intelligence to Predict CO 2 Emissions: Critical Step towards Sustainable Environment," Sustainability, MDPI, vol. 15(9), pages 1-27, May.
    10. Georgios Falekas & Athanasios Karlis, 2021. "Digital Twin in Electrical Machine Control and Predictive Maintenance: State-of-the-Art and Future Prospects," Energies, MDPI, vol. 14(18), pages 1-26, September.
    11. Sareen, Siddharth & Haarstad, Håvard, 2018. "Bridging socio-technical and justice aspects of sustainable energy transitions," Applied Energy, Elsevier, vol. 228(C), pages 624-632.
    12. Zhao, Xueyuan & Gao, Weijun & Qian, Fanyue & Ge, Jian, 2021. "Electricity cost comparison of dynamic pricing model based on load forecasting in home energy management system," Energy, Elsevier, vol. 229(C).
    13. Izabela Rojek & Adam Mroziński & Piotr Kotlarz & Marek Macko & Dariusz Mikołajewski, 2023. "AI-Based Computational Model in Sustainable Transformation of Energy Markets," Energies, MDPI, vol. 16(24), pages 1-26, December.
    14. Wang, Yingli & Singgih, Meita & Wang, Jingyao & Rit, Mihaela, 2019. "Making sense of blockchain technology: How will it transform supply chains?," International Journal of Production Economics, Elsevier, vol. 211(C), pages 221-236.
    15. Marina Dorokhova & Jérémie Vianin & Jean-Marie Alder & Christophe Ballif & Nicolas Wyrsch & David Wannier, 2021. "A Blockchain-Supported Framework for Charging Management of Electric Vehicles," Energies, MDPI, vol. 14(21), pages 1-32, November.
    16. Di Silvestre, Maria Luisa & Favuzza, Salvatore & Riva Sanseverino, Eleonora & Zizzo, Gaetano, 2018. "How Decarbonization, Digitalization and Decentralization are changing key power infrastructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 483-498.
    17. Morales, J.M. & Mínguez, R. & Conejo, A.J., 2010. "A methodology to generate statistically dependent wind speed scenarios," Applied Energy, Elsevier, vol. 87(3), pages 843-855, March.
    18. Wang, Zhe & Hong, Tianzhen & Piette, Mary Ann, 2020. "Building thermal load prediction through shallow machine learning and deep learning," Applied Energy, Elsevier, vol. 263(C).
    19. Allen,Robert C., 2009. "The British Industrial Revolution in Global Perspective," Cambridge Books, Cambridge University Press, number 9780521868273, November.
    20. Gales, Ben & Kander, Astrid & Malanima, Paolo & Rubio, Mar, 2007. "North versus South: Energy transition and energy intensity in Europe over 200 years," European Review of Economic History, Cambridge University Press, vol. 11(2), pages 219-253, August.
    21. Naser Hossein Motlagh & Mahsa Mohammadrezaei & Julian Hunt & Behnam Zakeri, 2020. "Internet of Things (IoT) and the Energy Sector," Energies, MDPI, vol. 13(2), pages 1-27, January.
    22. Imbulana Arachchi, Janaki & Managi, Shunsuke, 2021. "Preferences for energy sustainability: Different effects of gender on knowledge and importance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    23. Ajagekar, Akshay & You, Fengqi, 2022. "Quantum computing and quantum artificial intelligence for renewable and sustainable energy: A emerging prospect towards climate neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    24. Khaqqi, Khamila Nurul & Sikorski, Janusz J. & Hadinoto, Kunn & Kraft, Markus, 2018. "Incorporating seller/buyer reputation-based system in blockchain-enabled emission trading application," Applied Energy, Elsevier, vol. 209(C), pages 8-19.
    25. Chatterjee, Joyjit & Dethlefs, Nina, 2021. "Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    26. Irfan Khan & Fujun Hou, 2021. "The Impact of Socio-economic and Environmental Sustainability on CO2 Emissions: A Novel Framework for Thirty IEA Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(3), pages 1045-1076, June.
    27. Giuseppe Desogus & Emanuela Quaquero & Giulia Rubiu & Gianluca Gatto & Cristian Perra, 2021. "BIM and IoT Sensors Integration: A Framework for Consumption and Indoor Conditions Data Monitoring of Existing Buildings," Sustainability, MDPI, vol. 13(8), pages 1-22, April.
    28. Mehdinejad, Mehdi & Shayanfar, Heidarali & Mohammadi-Ivatloo, Behnam, 2022. "Peer-to-peer decentralized energy trading framework for retailers and prosumers," Applied Energy, Elsevier, vol. 308(C).
    29. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    30. Li, Yinan & Yang, Wentao & He, Ping & Chen, Chang & Wang, Xiaonan, 2019. "Design and management of a distributed hybrid energy system through smart contract and blockchain," Applied Energy, Elsevier, vol. 248(C), pages 390-405.
    31. Juho Hamari & Mimmi Sjöklint & Antti Ukkonen, 2016. "The sharing economy: Why people participate in collaborative consumption," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(9), pages 2047-2059, September.
    32. Baloko Makala & Tonci Bakovic, 2020. "Artificial Intelligence in the Power Sector," World Bank Publications - Reports 34303, The World Bank Group.
    33. Zaman, Khalid & Moemen, Mitwali Abd-el., 2017. "Energy consumption, carbon dioxide emissions and economic development: Evaluating alternative and plausible environmental hypothesis for sustainable growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1119-1130.
    34. Hua, Weiqi & Jiang, Jing & Sun, Hongjian & Wu, Jianzhong, 2020. "A blockchain based peer-to-peer trading framework integrating energy and carbon markets," Applied Energy, Elsevier, vol. 279(C).
    35. Hao Xiao & Wei Pei & Zuomin Dong & Li Kong & Dan Wang, 2018. "Application and Comparison of Metaheuristic and New Metamodel Based Global Optimization Methods to the Optimal Operation of Active Distribution Networks," Energies, MDPI, vol. 11(1), pages 1-29, January.
    36. Wadim Strielkowski & Andrey Vlasov & Kirill Selivanov & Konstantin Muraviev & Vadim Shakhnov, 2023. "Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review," Energies, MDPI, vol. 16(10), pages 1-31, May.
    37. Mohammad Mostafa Namar & Omid Jahanian & Hasan Koten & Adriana Del Carmen Téllez-Anguiano, 2022. "The Start of Combustion Prediction for Methane-Fueled HCCI Engines: Traditional vs. Machine Learning Methods," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-11, May.
    38. Mir Sayed Shah Danish & Tomonobu Senjyu, 2023. "AI-Enabled Energy Policy for a Sustainable Future," Sustainability, MDPI, vol. 15(9), pages 1-16, May.
    39. Ahl, A. & Yarime, M. & Goto, M. & Chopra, Shauhrat S. & Kumar, Nallapaneni Manoj. & Tanaka, K. & Sagawa, D., 2020. "Exploring blockchain for the energy transition: Opportunities and challenges based on a case study in Japan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    40. Kempitiya, Thimal & Sierla, Seppo & De Silva, Daswin & Yli-Ojanperä, Matti & Alahakoon, Damminda & Vyatkin, Valeriy, 2020. "An Artificial Intelligence framework for bidding optimization with uncertainty in multiple frequency reserve markets," Applied Energy, Elsevier, vol. 280(C).
    41. Matt, C. & Hess, Thomas & Benlian, Alexander, 2015. "Digital Transformation Strategies," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 75002, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    42. Nicolosi, Marco, 2010. "Wind power integration and power system flexibility-An empirical analysis of extreme events in Germany under the new negative price regime," Energy Policy, Elsevier, vol. 38(11), pages 7257-7268, November.
    43. Yael Parag & Benjamin K. Sovacool, 2016. "Electricity market design for the prosumer era," Nature Energy, Nature, vol. 1(4), pages 1-6, April.
    44. Hua, Weiqi & Chen, Ying & Qadrdan, Meysam & Jiang, Jing & Sun, Hongjian & Wu, Jianzhong, 2022. "Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    45. Lee Thomas & Yue Zhou & Chao Long & Jianzhong Wu & Nick Jenkins, 2019. "A general form of smart contract for decentralized energy systems management," Nature Energy, Nature, vol. 4(2), pages 140-149, February.
    46. Daiva Stanelyte & Neringa Radziukyniene & Virginijus Radziukynas, 2022. "Overview of Demand-Response Services: A Review," Energies, MDPI, vol. 15(5), pages 1-31, February.
    47. Christian Matt & Thomas Hess & Alexander Benlian, 2015. "Digital Transformation Strategies," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 57(5), pages 339-343, October.
    48. Madhubala Ganesan & Ah-Lian Kor & Colin Pattinson & Eric Rondeau, 2020. "Green Cloud Software Engineering for Big Data Processing," Sustainability, MDPI, vol. 12(21), pages 1-24, November.
    49. Amin Shokri Gazafroudi & Javier Prieto & Juan Manuel Corchado, 2019. "Virtual Organization Structure for Agent-Based Local Electricity Trading," Energies, MDPI, vol. 12(8), pages 1-11, April.
    50. Subhranshu Sekhar Tripathy & Mamata Rath & Niva Tripathy & Diptendu Sinha Roy & John Sharmila Anand Francis & Sujit Bebortta, 2023. "An Intelligent Health Care System in Fog Platform with Optimized Performance," Sustainability, MDPI, vol. 15(3), pages 1-17, January.
    51. Ustun, Taha Selim & Ozansoy, Cagil & Zayegh, Aladin, 2011. "Recent developments in microgrids and example cases around the world—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 4030-4041.
    52. Ford, Rebecca & Hardy, Jeffrey, 2020. "Are we seeing clearly? The need for aligned vision and supporting strategies to deliver net-zero electricity systems," Energy Policy, Elsevier, vol. 147(C).
    53. Andreas Richardson & Jiahua Xu, 2020. "Carbon Trading with Blockchain," Springer Proceedings in Business and Economics, in: Panos Pardalos & Ilias Kotsireas & Yike Guo & William Knottenbelt (ed.), Mathematical Research for Blockchain Economy, pages 105-124, Springer.
    54. C. D. Wilen & S. Abdullah & N. A. Kurinsky & C. Stanford & L. Cardani & G. D’Imperio & C. Tomei & L. Faoro & L. B. Ioffe & C. H. Liu & A. Opremcak & B. G. Christensen & J. L. DuBois & R. McDermott, 2021. "Correlated charge noise and relaxation errors in superconducting qubits," Nature, Nature, vol. 594(7863), pages 369-373, June.
    55. Abdellah Chehri & Issouf Fofana & Xiaomin Yang, 2021. "Security Risk Modeling in Smart Grid Critical Infrastructures in the Era of Big Data and Artificial Intelligence," Sustainability, MDPI, vol. 13(6), pages 1-19, March.
    56. Aditya Vasan Srinivasan & Mona de Boer, 2020. "Improving trust in data and algorithms in the medium of AI," Maandblad Voor Accountancy en Bedrijfseconomie Articles, Maandblad Voor Accountancy en Bedrijfseconomie, vol. 94(3-4), pages 147-160, April.
    57. Ekata Kaushik & Vivek Prakash & Om Prakash Mahela & Baseem Khan & Almoataz Y. Abdelaziz & Junhee Hong & Zong Woo Geem, 2022. "Optimal Placement of Renewable Energy Generators Using Grid-Oriented Genetic Algorithm for Loss Reduction and Flexibility Improvement," Energies, MDPI, vol. 15(5), pages 1-20, March.
    58. Lyu, Wenjing & Liu, Jin, 2021. "Artificial Intelligence and emerging digital technologies in the energy sector," Applied Energy, Elsevier, vol. 303(C).
    59. Oskar Juszczyk & Khuram Shahzad, 2022. "Blockchain Technology for Renewable Energy: Principles, Applications and Prospects," Energies, MDPI, vol. 15(13), pages 1-24, June.
    60. Dimitrios Kontogiannis & Dimitrios Bargiotas & Aspassia Daskalopulu, 2020. "Minutely Active Power Forecasting Models Using Neural Networks," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    61. Andoni, Merlinda & Robu, Valentin & Flynn, David & Abram, Simone & Geach, Dale & Jenkins, David & McCallum, Peter & Peacock, Andrew, 2019. "Blockchain technology in the energy sector: A systematic review of challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 143-174.
    62. Matt, C. & Hess, Thomas & Benlian, Alexander, 2015. "Digital Transformation Strategies," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 75202, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    63. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Design of distributed energy systems under uncertainty: A two-stage stochastic programming approach," Applied Energy, Elsevier, vol. 222(C), pages 932-950.
    64. Behm, Christian & Nolting, Lars & Praktiknjo, Aaron, 2020. "How to model European electricity load profiles using artificial neural networks," Applied Energy, Elsevier, vol. 277(C).
    65. Kaundinya, Deepak Paramashivan & Balachandra, P. & Ravindranath, N.H., 2009. "Grid-connected versus stand-alone energy systems for decentralized power--A review of literature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 2041-2050, October.
    Full references (including those not matched with items on IDEAS)

    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. Hua, Weiqi & Chen, Ying & Qadrdan, Meysam & Jiang, Jing & Sun, Hongjian & Wu, Jianzhong, 2022. "Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    2. Yildizbasi, Abdullah, 2021. "Blockchain and renewable energy: Integration challenges in circular economy era," Renewable Energy, Elsevier, vol. 176(C), pages 183-197.
    3. Ahl, Amanda & Goto, Mika & Yarime, Masaru & Tanaka, Kenji & Sagawa, Daishi, 2022. "Challenges and opportunities of blockchain energy applications: Interrelatedness among technological, economic, social, environmental, and institutional dimensions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    4. Lyu, Wenjing & Liu, Jin, 2021. "Artificial Intelligence and emerging digital technologies in the energy sector," Applied Energy, Elsevier, vol. 303(C).
    5. Javier Parra-Domínguez & Esteban Sánchez & Ángel Ordóñez, 2023. "The Prosumer: A Systematic Review of the New Paradigm in Energy and Sustainable Development," Sustainability, MDPI, vol. 15(13), pages 1-44, July.
    6. Roth, Tamara & Utz, Manuel & Baumgarte, Felix & Rieger, Alexander & Sedlmeir, Johannes & Strüker, Jens, 2022. "Electricity powered by blockchain: A review with a European perspective," Applied Energy, Elsevier, vol. 325(C).
    7. Malewska, Kamila & Cyfert, Szymon & Chwiłkowska-Kubala, Anna & Mierzejewska, Katrzyna & Szumowski, Witold, 2024. "The missing link between digital transformation and business model innovation in energy SMEs: The role of digital organisational culture," Energy Policy, Elsevier, vol. 192(C).
    8. Gourisetti, Sri Nikhil Gupta & Sebastian-Cardenas, D. Jonathan & Bhattarai, Bishnu & Wang, Peng & Widergren, Steve & Borkum, Mark & Randall, Alysha, 2021. "Blockchain smart contract reference framework and program logic architecture for transactive energy systems," Applied Energy, Elsevier, vol. 304(C).
    9. Kouhizadeh, Mahtab & Saberi, Sara & Sarkis, Joseph, 2021. "Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers," International Journal of Production Economics, Elsevier, vol. 231(C).
    10. Ko, Guihan & Amankwah-Amoah, Joseph & Appiah, Gloria & Larimo, Jorma, 2022. "Non-market strategies and building digital trust in sharing economy platforms," Journal of International Management, Elsevier, vol. 28(1).
    11. Hua, Weiqi & Jiang, Jing & Sun, Hongjian & Wu, Jianzhong, 2020. "A blockchain based peer-to-peer trading framework integrating energy and carbon markets," Applied Energy, Elsevier, vol. 279(C).
    12. Fernando, Yudi & Rozuar, Nor Hazwani Mohd & Mergeresa, Fineke, 2021. "The blockchain-enabled technology and carbon performance: Insights from early adopters," Technology in Society, Elsevier, vol. 64(C).
    13. Li, Wentao & Li, Xue & Peng, Lanying & Ning, Chong, 2024. "Silent actions: Digital transformation in private enterprises with state equity participation," Finance Research Letters, Elsevier, vol. 65(C).
    14. Bennich, Amelie, 2024. "The digital imperative: Institutional pressures to digitalise," Technology in Society, Elsevier, vol. 76(C).
    15. JooSeok Oh & Timothy Paul Connerton & Hyun-Jung Kim, 2019. "The Rediscovery of Brand Experience Dimensions with Big Data Analysis: Building for a Sustainable Brand," Sustainability, MDPI, vol. 11(19), pages 1-21, September.
    16. Lyu, Wenjing & Liu, Jin, 2021. "Soft skills, hard skills: What matters most? Evidence from job postings," Applied Energy, Elsevier, vol. 300(C).
    17. Zhang, Weike & Zeng, Ming, 2024. "Is artificial intelligence a curse or a blessing for enterprise energy intensity? Evidence from China," Energy Economics, Elsevier, vol. 134(C).
    18. Victoria Galkovskaya & Mariia Volos, 2022. "Economic Efficiency of the Implementation of Digital Technologies in Energy Power," Sustainability, MDPI, vol. 14(22), pages 1-17, November.
    19. Justyna Światowiec-Szczepańska & Beata Stępień, 2022. "Drivers of Digitalization in the Energy Sector—The Managerial Perspective from the Catching Up Economy," Energies, MDPI, vol. 15(4), pages 1-25, February.
    20. Swen Nadkarni & Reinhard Prügl, 2021. "Digital transformation: a review, synthesis and opportunities for future research," Management Review Quarterly, Springer, vol. 71(2), pages 233-341, April.

    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:rensus:v:202:y:2024:i:c:s1364032124004076. 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.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.