IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v323y2025i1p253-266.html
   My bibliography  Save this article

An adoption model of cryptocurrencies

Author

Listed:
  • Rzayev, Khaladdin
  • Sakkas, Athanasios
  • Urquhart, Andrew

Abstract

The network effect, measured by users’ adoption, is considered an important driver of cryptocurrency market dynamics. This study examines the role of adoption timing in cryptocurrency markets by decomposing total adoption into two components: innovators (early adopters) and imitators (late adopters). We find that the innovators’ component is the primary driver of the association between user adoption and cryptocurrency returns, both in-sample and out-of-sample. Next, we show that innovators’ adoption improves price efficiency, while imitators’ adoption contributes to noisier prices. Furthermore, we demonstrate that the adoption model captures significant cryptocurrency market phenomena, such as herding behaviour, more effectively, making it better suited for forecasting models in cryptocurrency pricing. These results suggest that our methodology for linking early and late adopters to market dynamics can be applied to various domains, offering a framework for future research at the intersection of operational research and financial markets.

Suggested Citation

  • Rzayev, Khaladdin & Sakkas, Athanasios & Urquhart, Andrew, 2025. "An adoption model of cryptocurrencies," European Journal of Operational Research, Elsevier, vol. 323(1), pages 253-266.
    • Handle: RePEc:eee:ejores:v:323:y:2025:i:1:p:253-266
    DOI: 10.1016/j.ejor.2024.11.024
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221724008932
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2024.11.024?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. W. Scott Frame & Lawrence J. White, 2004. "Empirical Studies of Financial Innovation: Lots of Talk, Little Action?," Journal of Economic Literature, American Economic Association, vol. 42(1), pages 116-144, March.
    2. Wurgler, Jeffrey, 2000. "Financial markets and the allocation of capital," Journal of Financial Economics, Elsevier, vol. 58(1-2), pages 187-214.
    3. Bruno Biais & Christophe Bisière & Matthieu Bouvard & Catherine Casamatta & Albert J. Menkveld, 2023. "Equilibrium Bitcoin Pricing," Journal of Finance, American Finance Association, vol. 78(2), pages 967-1014, April.
    4. Atsalakis, George S. & Atsalaki, Ioanna G. & Pasiouras, Fotios & Zopounidis, Constantin, 2019. "Bitcoin price forecasting with neuro-fuzzy techniques," European Journal of Operational Research, Elsevier, vol. 276(2), pages 770-780.
    5. Jalal Akhavein & W. Scott Frame & Lawrence J. White, 2005. "The Diffusion of Financial Innovations: An Examination of the Adoption of Small Business Credit Scoring by Large Banking Organizations," The Journal of Business, University of Chicago Press, vol. 78(2), pages 577-596, March.
    6. Nimalendran, Mahendrarajah & Rzayev, Khaladdin & Sagade, Satchit, 2024. "High-frequency trading in the stock market and the costs of options market making," LSE Research Online Documents on Economics 124228, London School of Economics and Political Science, LSE Library.
    7. Bianchi, Daniele & Babiak, Mykola & Dickerson, Alexander, 2022. "Trading volume and liquidity provision in cryptocurrency markets," Journal of Banking & Finance, Elsevier, vol. 142(C).
    8. Joseph Farrell & Garth Saloner, 1985. "Standardization, Compatibility, and Innovation," RAND Journal of Economics, The RAND Corporation, vol. 16(1), pages 70-83, Spring.
    9. Jiang, Shangrong & Li, Yuze & Wang, Shouyang & Zhao, Lin, 2022. "Blockchain competition: The tradeoff between platform stability and efficiency," European Journal of Operational Research, Elsevier, vol. 296(3), pages 1084-1097.
    10. Erdinc Akyildirim & Oguzhan Cepni & Shaen Corbet & Gazi Salah Uddin, 2023. "Forecasting mid-price movement of Bitcoin futures using machine learning," Annals of Operations Research, Springer, vol. 330(1), pages 553-584, November.
    11. Menkveld, Albert J. & Koopman, Siem Jan & Lucas, Andre, 2007. "Modeling Around-the-Clock Price Discovery for Cross-Listed Stocks Using State Space Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 213-225, April.
    12. Fazıl Paç, M. & Savin, Sergei & Velu, Chander, 2018. "When to adopt a service innovation: Nash equilibria in a competitive diffusion framework," European Journal of Operational Research, Elsevier, vol. 271(3), pages 968-984.
    13. Pierre Collin‐Dufresne & Vyacheslav Fos, 2016. "Insider Trading, Stochastic Liquidity, and Equilibrium Prices," Econometrica, Econometric Society, vol. 84(4), pages 1441-1475, July.
    14. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    15. Jiang Wang, 1993. "A Model of Intertemporal Asset Prices Under Asymmetric Information," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(2), pages 249-282.
    16. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    17. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    18. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2002. "Order imbalance, liquidity, and market returns," Journal of Financial Economics, Elsevier, vol. 65(1), pages 111-130, July.
    19. Stummer, Christian & Kiesling, Elmar & Günther, Markus & Vetschera, Rudolf, 2015. "Innovation diffusion of repeat purchase products in a competitive market: An agent-based simulation approach," European Journal of Operational Research, Elsevier, vol. 245(1), pages 157-167.
    20. Robert T. Daigler & Marilyn K. Wiley, 1999. "The Impact of Trader Type on the Futures Volatility‐Volume Relation," Journal of Finance, American Finance Association, vol. 54(6), pages 2297-2316, December.
    21. Ballis, Antonis & Drakos, Konstantinos, 2020. "Testing for herding in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 33(C).
    22. Tadesse, Solomon, 2004. "The Allocation and Monitoring Role of Capital Markets: Theory and International Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(4), pages 701-730, December.
    23. Jennifer F. Reinganum, 1981. "On the Diffusion of New Technology: A Game Theoretic Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 48(3), pages 395-405.
    24. Christopher J. Easingwood & Vijay Mahajan & Eitan Muller, 1983. "A Nonuniform Influence Innovation Diffusion Model of New Product Acceptance," Marketing Science, INFORMS, vol. 2(3), pages 273-295.
    25. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    26. Pierre Collin‐Dufresne & Vyacheslav Fos, 2016. "Insider Trading, Stochastic Liquidity, and Equilibrium Prices," Econometrica, Econometric Society, vol. 84, pages 1441-1475, July.
    27. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    28. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-440, June.
    29. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    30. Alexander, Carol & Heck, Daniel F., 2020. "Price discovery in Bitcoin: The impact of unregulated markets," Journal of Financial Stability, Elsevier, vol. 50(C).
    31. Emilio Barucci & Giancarlo Giuffra Moncayo & Daniele Marazzina, 2023. "Market impact and efficiency in cryptoassets markets," Digital Finance, Springer, vol. 5(3), pages 519-562, December.
    32. Jain, Dipak C & Rao, Ram C, 1990. "Effect of Price on the Demand for Durables: Modeling, Estimation, and Findings," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 163-170, April.
    33. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    34. Brandt, Michael W. & Kang, Qiang, 2004. "On the relationship between the conditional mean and volatility of stock returns: A latent VAR approach," Journal of Financial Economics, Elsevier, vol. 72(2), pages 217-257, May.
    35. Richins, Marsha L & Bloch, Peter H, 1986. "After the New Wears Off: The Temporal Context of Product Involvement," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(2), pages 280-285, September.
    36. Nimalendran, Mahendrarajah & Rzayev, Khaladdin & Sagade, Satchit, 2024. "High-frequency trading in the stock market and the costs of options market making," Journal of Financial Economics, Elsevier, vol. 159(C).
    37. Andreas Hackethal & Tobin Hanspal & Dominique M Lammer & Kevin Rink, 2022. "The Characteristics and Portfolio Behavior of Bitcoin Investors: Evidence from Indirect Cryptocurrency Investments [The investor in structured retail products: advice driven or gambling oriented]," Review of Finance, European Finance Association, vol. 26(4), pages 855-898.
    38. David C. Schmittlein & Vijay Mahajan, 1982. "Maximum Likelihood Estimation for an Innovation Diffusion Model of New Product Acceptance," Marketing Science, INFORMS, vol. 1(1), pages 57-78.
    39. Philip Molyneux & Nidal Shamroukh, 1996. "Diffusion of financial innovations: the case of junk bonds and note issuance facilities," Proceedings, Federal Reserve Bank of Cleveland, issue Aug, pages 502-526.
    40. Rzayev, Khaladdin & Ibikunle, Gbenga, 2019. "A state-space modeling of the information content of trading volume," Journal of Financial Markets, Elsevier, vol. 46(C).
    41. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    42. Hellwig, Martin F., 1980. "On the aggregation of information in competitive markets," Journal of Economic Theory, Elsevier, vol. 22(3), pages 477-498, June.
    43. Meade, Nigel & Islam, Towhidul, 1995. "Forecasting with growth curves: An empirical comparison," International Journal of Forecasting, Elsevier, vol. 11(2), pages 199-215, June.
    44. Yanhao (Max) Wei & Anthony Dukes, 2021. "Cryptocurrency Adoption with Speculative Price Bubbles," Marketing Science, INFORMS, vol. 40(2), pages 241-260, March.
    45. Lin William Cong & Ye Li & Neng Wang, 2021. "Tokenomics: Dynamic Adoption and Valuation [The demand of liquid assets with uncertain lumpy expenditures]," The Review of Financial Studies, Society for Financial Studies, vol. 34(3), pages 1105-1155.
    46. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," The Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    47. Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2021. "Trading activity and price discovery in Bitcoin futures markets," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 107-120.
    48. Bianchi, Daniele & Babiak, Mykola, 2022. "On the performance of cryptocurrency funds," Journal of Banking & Finance, Elsevier, vol. 138(C).
    49. Thomas Lindner & Jonas Puck & Alain Verbeke, 2020. "Misconceptions about multicollinearity in international business research: Identification, consequences, and remedies," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 51(3), pages 283-298, April.
    50. Schnaubelt, Matthias, 2022. "Deep reinforcement learning for the optimal placement of cryptocurrency limit orders," European Journal of Operational Research, Elsevier, vol. 296(3), pages 993-1006.
    51. Naoum-Sawaya, Joe & Elhedhli, Samir & De Carvalho, Paulo, 2023. "Strategic blockchain adoption to deter deceptive counterfeiters," European Journal of Operational Research, Elsevier, vol. 311(1), pages 373-386.
    52. Michael Sockin & Wei Xiong, 2023. "A Model of Cryptocurrencies," Management Science, INFORMS, vol. 69(11), pages 6684-6707, November.
    53. Timothy King & Dimitrios Koutmos, 2021. "Herding and feedback trading in cryptocurrency markets," Annals of Operations Research, Springer, vol. 300(1), pages 79-96, May.
    54. Oliver Entrop & Bart Frijns & Marco Seruset, 2020. "The determinants of price discovery on bitcoin markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(5), pages 816-837, May.
    55. Ibikunle, Gbenga, 2018. "Trading places: Price leadership and the competition for order flow," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 178-200.
    56. Jonathan Lewellen, 2002. "Momentum and Autocorrelation in Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 533-564, March.
    57. Yukun Liu & Aleh Tsyvinski & Xi Wu, 2022. "Common Risk Factors in Cryptocurrency," Journal of Finance, American Finance Association, vol. 77(2), pages 1133-1177, April.
    58. Zhang, Zhiming & Ren, Da & Lan, Yanfei & Yang, Shanxue, 2022. "Price competition and blockchain adoption in retailing markets," European Journal of Operational Research, Elsevier, vol. 300(2), pages 647-660.
    59. Yukun Liu & Aleh Tsyvinski, 2021. "Risks and Returns of Cryptocurrency," The Review of Financial Studies, Society for Financial Studies, vol. 34(6), pages 2689-2727.
    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. Rzayev, Khaladdin & Ibikunle, Gbenga, 2019. "A state-space modeling of the information content of trading volume," Journal of Financial Markets, Elsevier, vol. 46(C).
    2. Mona Mortazian, 2022. "Liquidity and Volatility of Stocks Moved from the Main Market to the Alternative Investment Market (AIM)," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(2), pages 195-220, June.
    3. Vayanos, Dimitri & Wang, Jiang, 2013. "Market Liquidity—Theory and Empirical Evidence ," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1289-1361, Elsevier.
    4. Shahzad, Hassan & Duong, Huu Nhan & Kalev, Petko S. & Singh, Harminder, 2014. "Trading volume, realized volatility and jumps in the Australian stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 414-430.
    5. Thanh Huong Nguyen, 2019. "Information and Noise in Stock Markets: Evidence on the Determinants and Effects Using New Empirical Measures," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 7-2019, January-A.
    6. Liu, Yakun & Chen, Yan, 2024. "Skewness risk and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    7. Ibikunle, Gbenga & McGroarty, Frank & Rzayev, Khaladdin, 2020. "More heat than light: Investor attention and bitcoin price discovery," International Review of Financial Analysis, Elsevier, vol. 69(C).
    8. Huang, Guan-Ying & Gau, Yin-Feng & Wu, Zhen-Xing, 2022. "Price discovery in fiat currency and cryptocurrency markets," Finance Research Letters, Elsevier, vol. 47(PA).
    9. Patrick J. Kelly, 2014. "Information Efficiency and Firm-Specific Return Variation," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 4(04), pages 1-44.
    10. Sun, Xiaotong & Stasinakis, Charalampos & Sermpinis, Georgios, 2024. "Decentralization illusion in Decentralized Finance: Evidence from tokenized voting in MakerDAO polls," Journal of Financial Stability, Elsevier, vol. 73(C).
    11. Peress, Joel & Schmidt, Daniel, 2021. "Noise traders incarnate: Describing a realistic noise trading process," Journal of Financial Markets, Elsevier, vol. 54(C).
    12. Bryan Kelly & Alexander Ljungqvist, 2012. "Testing Asymmetric-Information Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1366-1413.
    13. Jank, Stephan & Roling, Christoph & Smajlbegovic, Esad, 2021. "Flying under the radar: The effects of short-sale disclosure rules on investor behavior and stock prices," Journal of Financial Economics, Elsevier, vol. 139(1), pages 209-233.
    14. Arjoon, Vaalmikki & Bhatnagar, Chandra Shekhar & Ramlakhan, Prakash, 2020. "Herding in the Singapore stock Exchange," Journal of Economics and Business, Elsevier, vol. 109(C).
    15. Sun, Licheng & Najand, Mohammad & Shen, Jiancheng, 2016. "Stock return predictability and investor sentiment: A high-frequency perspective," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 147-164.
    16. Şoiman, Florentina & Dumas, Jean-Guillaume & Jimenez-Garces, Sonia, 2023. "What drives DeFi market returns?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    17. Blankespoor, Elizabeth & deHaan, Ed & Marinovic, Iván, 2020. "Disclosure processing costs, investors’ information choice, and equity market outcomes: A review," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    18. Banti, Chiara & Phylaktis, Kate & Sarno, Lucio, 2012. "Global liquidity risk in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 31(2), pages 267-291.
    19. Aysan, Ahmet Faruk & Caporin, Massimiliano & Cepni, Oguzhan, 2024. "Not all words are equal: Sentiment and jumps in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    20. Ibikunle, Gbenga & Aquilina, Matteo & Diaz-Rainey, Ivan & Sun, Yuxin, 2021. "City goes dark: Dark trading and adverse selection in aggregate markets," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 1-22.

    More about this item

    Keywords

    Cryptocurrency adoption; Innovators; Imitators; Network effects; Predictive modelling; Market quality;
    All these keywords.

    JEL classification:

    • F3 - International Economics - - International Finance
    • G3 - Financial Economics - - Corporate Finance and Governance

    Statistics

    Access and download statistics

    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:ejores:v:323:y:2025:i:1:p:253-266. 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/locate/eor .

    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.