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Models used to characterise blockchain features. A systematic literature review and bibliometric analysis

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  • Rico-Peña, Juan Jesús
  • Arguedas-Sanz, Raquel
  • López-Martin, Carmen

Abstract

Blockchain has emerged as an innovative technology with potential to transform business management, through operational efficiency improvements. Nevertheless, several performance and vulnerability issues have been identified for the different typologies supporting the wide range of blockchain-based applications currently implemented in different domains.

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  • Rico-Peña, Juan Jesús & Arguedas-Sanz, Raquel & López-Martin, Carmen, 2023. "Models used to characterise blockchain features. A systematic literature review and bibliometric analysis," Technovation, Elsevier, vol. 123(C).
  • Handle: RePEc:eee:techno:v:123:y:2023:i:c:s0166497223000226
    DOI: 10.1016/j.technovation.2023.102711
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    as
    1. Luisanna Cocco & Michele Marchesi, 2016. "Modeling and Simulation of the Economics of Mining in the Bitcoin Market," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-31, October.
    2. Nazmiye Ceren Abay & Cuneyt Gurcan Akcora & Yulia R. Gel & Umar D. Islambekov & Murat Kantarcioglu & Yahui Tian & Bhavani Thuraisingham, 2019. "ChainNet: Learning on Blockchain Graphs with Topological Features," Papers 1908.06971, arXiv.org.
    3. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    4. Luisanna Cocco & Giulio Concas & Michele Marchesi, 2017. "Using an artificial financial market for studying a cryptocurrency market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 345-365, July.
    5. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    6. 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.
    7. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2018. "Bitcoin technical trading with artificial neural network," CARF F-Series CARF-F-441, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    8. Zhong, Huiling & Zhang, Fa & Gu, Yimiao, 2021. "A Stackelberg game based two-stage framework to make decisions of freight rate for container shipping lines in the emerging blockchain-based market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    9. Ziaul Haque Munim & Mohammad Hassan Shakil & Ilan Alon, 2019. "Next-Day Bitcoin Price Forecast," JRFM, MDPI, vol. 12(2), pages 1-15, June.
    10. Ewerhart, Christian, 2020. "Finite blockchain games," Economics Letters, Elsevier, vol. 197(C).
    11. Giudici, Paolo & Abu-Hashish, Iman, 2019. "What determines bitcoin exchange prices? A network VAR approach," Finance Research Letters, Elsevier, vol. 28(C), pages 309-318.
    12. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2018. "Bitcoin technical trading with artificial neural network," CIRJE F-Series CIRJE-F-1078, CIRJE, Faculty of Economics, University of Tokyo.
    13. Jiri Chod & Nikolaos Trichakis & Gerry Tsoukalas & Henry Aspegren & Mark Weber, 2020. "On the Financing Benefits of Supply Chain Transparency and Blockchain Adoption," Management Science, INFORMS, vol. 66(10), pages 4378-4396, October.
    14. Akcora, Cuneyt Gurcan & Dixon, Matthew F. & Gel, Yulia R. & Kantarcioglu, Murat, 2018. "Bitcoin risk modeling with blockchain graphs," Economics Letters, Elsevier, vol. 173(C), pages 138-142.
    15. Wenjuan Lian & Qi Fan & Bin Jia & Yongquan Liang, 2020. "A Blockchain Prediction Model on Time, Value, and Purchase Based on Markov Chain and Queuing Theory in Stock Trade," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-13, November.
    16. Brian Fralix, 2020. "On classes of Bitcoin-inspired infinite-server queueing systems," Queueing Systems: Theory and Applications, Springer, vol. 95(1), pages 29-52, June.
    17. Cross, Jamie L. & Hou, Chenghan & Trinh, Kelly, 2021. "Returns, volatility and the cryptocurrency bubble of 2017–18," Economic Modelling, Elsevier, vol. 104(C).
    18. Jong-Min Kim & Chulhee Jun & Junyoup Lee, 2021. "Forecasting the Volatility of the Cryptocurrency Market by GARCH and Stochastic Volatility," Mathematics, MDPI, vol. 9(14), pages 1-16, July.
    19. Jana Schmitz & Giulia Leoni, 2019. "Accounting and Auditing at the Time of Blockchain Technology: A Research Agenda," Australian Accounting Review, CPA Australia, vol. 29(2), pages 331-342, June.
    20. Adam Turner & Angela Samantha Maitland Irwin, 2018. "Bitcoin transactions: a digital discovery of illicit activity on the blockchain," Journal of Financial Crime, Emerald Group Publishing Limited, vol. 25(1), pages 109-130, January.
    21. Ye Guo & Chen Liang, 2016. "Blockchain application and outlook in the banking industry," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 2(1), pages 1-12, December.
    22. Micha Ober & Stefan Katzenbeisser & Kay Hamacher, 2013. "Structure and Anonymity of the Bitcoin Transaction Graph," Future Internet, MDPI, vol. 5(2), pages 1-14, May.
    23. Bruno Biais & Christophe Bisière & Matthieu Bouvard & Catherine Casamatta, 2019. "The Blockchain Folk Theorem," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1662-1715.
    24. Bumho Son & Jaewook Lee & Huisu Jang, 2020. "A Scalable IoT Protocol via an Efficient DAG-Based Distributed Ledger Consensus," Sustainability, MDPI, vol. 12(4), pages 1-11, February.
    25. Yufang Wang & Haiyan Wang, 2020. "Using Networks and Partial Differential Equations to Predict Bitcoin Price," Papers 2001.03099, arXiv.org.
    26. Yuzhi Cai & Thanaset Chevapatrakul & Danilo V. Mascia, 2021. "How is price explosivity triggered in the cryptocurrency markets?," Annals of Operations Research, Springer, vol. 307(1), pages 37-51, December.
    27. Kamwoo Lee & Sinan Ulkuatam & Peter Beling & William Scherer, 2018. "Generating Synthetic Bitcoin Transactions and Predicting Market Price Movement Via Inverse Reinforcement Learning and Agent-Based Modeling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(3), pages 1-5.
    28. Wu, Chuanzhen, 2021. "Window effect with Markov-switching GARCH model in cryptocurrency market," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    29. Mehrdokht Pournader & Yangyan Shi & Stefan Seuring & S.C. Lenny Koh, 2020. "Blockchain applications in supply chains, transport and logistics: a systematic review of the literature," International Journal of Production Research, Taylor & Francis Journals, vol. 58(7), pages 2063-2081, April.
    30. Aniruddha Dutta & Saket Kumar & Meheli Basu, 2020. "A Gated Recurrent Unit Approach to Bitcoin Price Prediction," JRFM, MDPI, vol. 13(2), pages 1-16, February.
    31. De Giovanni, Pietro, 2020. "Blockchain and smart contracts in supply chain management: A game theoretic model," International Journal of Production Economics, Elsevier, vol. 228(C).
    32. Lahmiri, Salim & Bekiros, Stelios, 2020. "Intelligent forecasting with machine learning trading systems in chaotic intraday Bitcoin market," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    33. Chen, Ting & Wang, Derong, 2020. "Combined application of blockchain technology in fractional calculus model of supply chain financial system," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    34. Huberman, Gur & Leshno, Jacob & Moallemi, Ciamac C., 2017. "Monopoly Without a Monopolist: An Economic Analysis of the Bitcoin Payment System," CEPR Discussion Papers 12322, C.E.P.R. Discussion Papers.
    35. Cuneyt Akcora & Matthew Dixon & Yulia Gel & Murat Kantarcioglu, 2018. "Bitcoin Risk Modeling with Blockchain Graphs," Papers 1805.04698, arXiv.org.
    36. Meryam Essaid & Sejin Park & Hong‐Taek Ju, 2020. "Bitcoin's dynamic peer‐to‐peer topology," International Journal of Network Management, John Wiley & Sons, vol. 30(5), September.
    37. Hughes, Laurie & Dwivedi, Yogesh K. & Misra, Santosh K. & Rana, Nripendra P. & Raghavan, Vishnupriya & Akella, Viswanadh, 2019. "Blockchain research, practice and policy: Applications, benefits, limitations, emerging research themes and research agenda," International Journal of Information Management, Elsevier, vol. 49(C), pages 114-129.
    38. Yuri Bespalov & Alberto Garoffolo & Lyudmila Kovalchuk & Hanna Nelasa & Roman Oliynykov, 2021. "Probability Models of Distributed Proof Generation for zk-SNARK-Based Blockchains," Mathematics, MDPI, vol. 9(23), pages 1-31, November.
    39. Syed Jawad Hussain Shahzad & Elie Bouri & Sang Hoon Kang & Tareq Saeed, 2021. "Regime specific spillover across cryptocurrencies and the role of COVID-19," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
    40. Aggarwal, Divya, 2019. "Do bitcoins follow a random walk model?," Research in Economics, Elsevier, vol. 73(1), pages 15-22.
    41. Figà-Talamanca, Gianna & Focardi, Sergio & Patacca, Marco, 2021. "Regime switches and commonalities of the cryptocurrencies asset class," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    42. Noura Metawa & Mohamemd I. Alghamdi & Ibrahim M. El-Hasnony & Mohamed Elhoseny, 2021. "Return Rate Prediction in Blockchain Financial Products Using Deep Learning," Sustainability, MDPI, vol. 13(21), pages 1-16, October.
    43. Huberman, Gur & Leshno, Jacob D. & Moallemi, Ciamac, 2017. "Monopoly without a monopolist: An economic analysis of the bitcoin payment system," Bank of Finland Research Discussion Papers 27/2017, Bank of Finland.
    44. Mizerka, Jacek & Stróżyńska-Szajek, Agnieszka & Mizerka, Piotr, 2020. "The role of Bitcoin on developed and emerging markets – on the basis of a Bitcoin users graph analysis," Finance Research Letters, Elsevier, vol. 35(C).
    45. William J. Luther, 2016. "Cryptocurrencies, Network Effects, And Switching Costs," Contemporary Economic Policy, Western Economic Association International, vol. 34(3), pages 553-571, July.
    46. Suhwan Ji & Jongmin Kim & Hyeonseung Im, 2019. "A Comparative Study of Bitcoin Price Prediction Using Deep Learning," Mathematics, MDPI, vol. 7(10), pages 1-20, September.
    47. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2018. "Bitcoin technical trading with artificial neural network," CARF F-Series CARF-F-430, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    48. Chin, Tachia & Shi, Yi & Singh, Sanjay Kumar & Agbanyo, George Kwame & Ferraris, Alberto, 2022. "Leveraging blockchain technology for green innovation in ecosystem-based business models: A dynamic capability of values appropriation," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    49. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    50. Lahmiri, Salim & Bekiros, Stelios, 2019. "Cryptocurrency forecasting with deep learning chaotic neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 118(C), pages 35-40.
    51. Song-Kyoo (Amang) Kim, 2021. "Enhanced IoV Security Network by Using Blockchain Governance Game," Mathematics, MDPI, vol. 9(2), pages 1-13, January.
    52. Angelis, Jannis & Ribeiro da Silva, Elias, 2019. "Blockchain adoption: A value driver perspective," Business Horizons, Elsevier, vol. 62(3), pages 307-314.
    53. 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).
    54. Lian, Yu-Min & Chen, Jun-Home, 2021. "Pricing virtual currency-linked derivatives with time-inhomogeneity," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 424-439.
    55. Nicola Uras & Lodovica Marchesi & Michele Marchesi & Roberto Tonelli, 2020. "Forecasting Bitcoin closing price series using linear regression and neural networks models," Papers 2001.01127, arXiv.org.
    56. Laura Alessandretti & Abeer ElBahrawy & Luca Maria Aiello & Andrea Baronchelli, 2018. "Anticipating cryptocurrency prices using machine learning," Papers 1805.08550, arXiv.org, revised Nov 2018.
    57. Sascha Kraus & Matthias Breier & Sonia Dasí-Rodríguez, 2020. "The art of crafting a systematic literature review in entrepreneurship research," International Entrepreneurship and Management Journal, Springer, vol. 16(3), pages 1023-1042, September.
    58. Chowdhury, Reaz & Rahman, M. Arifur & Rahman, M. Sohel & Mahdy, M.R.C., 2020. "An approach to predict and forecast the price of constituents and index of cryptocurrency using machine learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    59. Luisanna Cocco & Roberto Tonelli & Michele Marchesi, 2019. "An Agent Based Model to Analyze the Bitcoin Mining Activity and a Comparison with the Gold Mining Industry," Future Internet, MDPI, vol. 11(1), pages 1-12, January.
    60. Kurbucz, Marcell Tamás, 2019. "Predicting the price of Bitcoin by the most frequent edges of its transaction network," Economics Letters, Elsevier, vol. 184(C).
    61. Tak Kuen Siu & Robert J. Elliott, 2021. "Bitcoin option pricing with a SETAR-GARCH model," The European Journal of Finance, Taylor & Francis Journals, vol. 27(6), pages 564-595, April.
    62. Christofi, Michael & Vrontis, Demetris & Cadogan, John W., 2021. "Micro-foundational ambidexterity and multinational enterprises: A systematic review and a conceptual framework," International Business Review, Elsevier, vol. 30(1).
    63. repec:zbw:bofrdp:2017_027 is not listed on IDEAS
    64. Gidea, Marian & Goldsmith, Daniel & Katz, Yuri & Roldan, Pablo & Shmalo, Yonah, 2020. "Topological recognition of critical transitions in time series of cryptocurrencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    65. Tan, Chia-Yen & Koh, You-Beng & Ng, Kok-Haur & Ng, Kooi-Huat, 2021. "Dynamic volatility modelling of Bitcoin using time-varying transition probability Markov-switching GARCH model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    66. Riad Shams, S.M. & Vrontis, Demetris & Chaudhuri, Ranjan & Chavan, Gitesh & Czinkota, Michael R., 2020. "Stakeholder engagement for innovation management and entrepreneurial development: A meta-analysis," Journal of Business Research, Elsevier, vol. 119(C), pages 67-86.
    67. Altan, Aytaç & Karasu, Seçkin & Bekiros, Stelios, 2019. "Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 325-336.
    68. Ahluwalia, Saurabh & Mahto, Raj V. & Guerrero, Maribel, 2020. "Blockchain technology and startup financing: A transaction cost economics perspective," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    69. Kowalski, Michał & Lee, Zach W.Y. & Chan, Tommy K.H., 2021. "Blockchain technology and trust relationships in trade finance," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    70. Nakano, Masafumi & Takahashi, Akihiko & Takahashi, Soichiro, 2018. "Bitcoin technical trading with artificial neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 587-609.
    71. Meegan, Andrew & Corbet, Shaen & Larkin, Charles & Lucey, Brian, 2021. "Does cryptocurrency pricing response to regulatory intervention depend on underlying blockchain architecture?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 70(C).
    72. Easley, David & O'Hara, Maureen & Basu, Soumya, 2019. "From mining to markets: The evolution of bitcoin transaction fees," Journal of Financial Economics, Elsevier, vol. 134(1), pages 91-109.
    73. Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
    74. Vrontis, Demetris & Christofi, Michael, 2021. "R&D internationalization and innovation: A systematic review, integrative framework and future research directions," Journal of Business Research, Elsevier, vol. 128(C), pages 812-823.
    75. Fahad Mostafa & Pritam Saha & Mohammad Rafiqul Islam & Nguyet Nguyen, 2021. "GJR-GARCH Volatility Modeling under NIG and ANN for Predicting Top Cryptocurrencies," JRFM, MDPI, vol. 14(9), pages 1-22, September.
    76. Dimitrios Koutmos & James E. Payne, 2021. "Intertemporal asset pricing with bitcoin," Review of Quantitative Finance and Accounting, Springer, vol. 56(2), pages 619-645, February.
    77. Samet Gunay & Kerem Kaskaloglu & Shahnawaz Muhammed, 2021. "Bitcoin and Fiat Currency Interactions: Surprising Results from Asian Giants," Mathematics, MDPI, vol. 9(12), pages 1-18, June.
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