IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v598y2022ics0378437122001996.html
   My bibliography  Save this article

Agent-based modelling of the global phonographic market

Author

Listed:
  • Buda, Andrzej
  • Kwapień, Jarosław

Abstract

Based on empirical properties of the global phonographic market, we propose a simple epidemiological model of innovation spread on a network whose structure reflects the structure of the real-world market. The global phonographic market consists of the national markets of various size and mutual interconnections. In the model, we assume that the national markets are the subnetworks that have a scale-free structure achieved by the preferential attachment construction with a node hierarchy and binary edges, while the global market is a complete, directed, weighted network of these subnetworks treated as nodes with the edges representing the cultural and geographical proximity of the national markets. “Viruses” with a defined strength or aggressiveness occur independently at one of the nodes of a selected subnetwork and correspond to a piece of music that has been released by an artist somewhere in the world. We study the virus dynamics set by varying parameter values and observe a variety of phenomena including local and global pandemics and the existence of an epidemic threshold in the subnetworks. Apart from studying the model, we also present some results on empirical data from the European and the U.K. phonographic markets, which are then utilized in the model construction.

Suggested Citation

  • Buda, Andrzej & Kwapień, Jarosław, 2022. "Agent-based modelling of the global phonographic market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    • Handle: RePEc:eee:phsmap:v:598:y:2022:i:c:s0378437122001996
    DOI: 10.1016/j.physa.2022.127209
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437122001996
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2022.127209?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. Ilkka Hanski, 1998. "Metapopulation dynamics," Nature, Nature, vol. 396(6706), pages 41-49, November.
    2. Lambiotte, R. & Ausloos, M., 2006. "Endo- vs. exogenous shocks and relaxation rates in book and music “sales”," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 485-494.
    3. Marco Alberto Javarone, 2014. "Competitive dynamics of lexical innovations in multi-layer networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 25(10), pages 1-33.
    4. A. Chakraborti & I. Muni-Toke & M. Patriarca & F. Abergel, 2011. "Econophysics Review : II. Agent-based models," Post-Print hal-03332946, HAL.
    5. Buda, Andrzej, 2012. "Does pop music exist? Hierarchical structure in phonographic markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(21), pages 5153-5159.
    6. David García & Dorian Tanase, 2013. "Measuring Cultural Dynamics Through The Eurovision Song Contest," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 16(08), pages 1-33.
    7. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frédéric Abergel, 2011. "Econophysics review: II. Agent-based models," Post-Print hal-00621059, HAL.
    8. Dominic Power & Daniel Hallencreutz, 2007. "Competitiveness, Local Production Systems and Global Commodity Chains in the Music Industry: Entering the US Market," Regional Studies, Taylor & Francis Journals, vol. 41(3), pages 377-389.
    9. Siudem, Grzegorz & Hołyst, Janusz A., 2019. "Diffusion on hierarchical systems of weakly-coupled networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 675-686.
    10. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    11. B. Dybiec, 2009. "SIR model of epidemic spread with accumulated exposure," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 377-383, February.
    12. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: II. Agent-based models," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1013-1041.
    13. Sadedin, Suzanne & Dybiec, Bartłomiej & Briscoe, Gerard, 2003. "A toy model of faith-based systems evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 715-725.
    14. Peter Tschmuck, 2012. "Creativity and Innovation in the Music Industry," Springer Books, Springer, edition 2, number 978-3-642-28430-4, December.
    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. Pietro DeLellis & Anna DiMeglio & Franco Garofalo & Francesco Lo Iudice, 2017. "The evolving cobweb of relations among partially rational investors," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-21, February.
    2. Inoua, Sabiou M. & Smith, Vernon L., 2023. "A classical model of speculative asset price dynamics," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    3. Robin Nicole & Peter Sollich, 2017. "Dynamical selection of Nash equilibria using Experience Weighted Attraction Learning: emergence of heterogeneous mixed equilibria," Papers 1706.09763, arXiv.org.
    4. Christoph J. Borner & Ingo Hoffmann & John H. Stiebel, 2024. "A closer look at the chemical potential of an ideal agent system," Papers 2401.09233, arXiv.org.
    5. Kiran Sharma & Subhradeep Das & Anirban Chakraborti, 2017. "Global Income Inequality and Savings: A Data Science Perspective," Papers 1801.00253, arXiv.org, revised Aug 2018.
    6. Ban Zheng & François Roueff & Frédéric Abergel, 2014. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Post-Print hal-00777941, HAL.
    7. A. O. Glekin & A. Lykov & K. L. Vaninsky, 2014. "On Simulation of Various Effects in Consolidated Order Book," Papers 1402.4150, arXiv.org.
    8. Hong Guo & Jianwu Lin & Fanlin Huang, 2023. "Market Making with Deep Reinforcement Learning from Limit Order Books," Papers 2305.15821, arXiv.org.
    9. Fei Cao & Sebastien Motsch, 2021. "Derivation of wealth distributions from biased exchange of money," Papers 2105.07341, arXiv.org.
    10. Pierre Gosselin & Aïleen Lotz & Marc Wambst, 2020. "A path integral approach to business cycle models with large number of agents," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(4), pages 899-942, October.
    11. Dias, Thiago & Gonçalves, Sebastián, 2024. "Effectiveness of wealth-based vs exchange-based tax systems in reducing inequality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
    12. Pierre Gosselin & Aïleen Lotz & Marc Wambst, 2019. "A Statistical Field Approach to Capital Accumulation," Working Papers hal-02280634, HAL.
    13. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
    14. Zhang, Jiu & Jin, Li-Fu & Zheng, Bo & Li, Yan & Jiang, Xiong-Fei, 2022. "Simplified calculations of time correlation functions in non-stationary complex financial systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    15. repec:hal:wpaper:hal-00777941 is not listed on IDEAS
    16. T. T. Chen & B. Zheng & Y. Li & X. F. Jiang, 2017. "New approaches in agent-based modeling of complex financial systems," Papers 1703.06840, arXiv.org.
    17. Fernandes, Leonardo H.S. & Silva, José W.L. & de Araujo, Fernando H.A., 2022. "Multifractal risk measures by Macroeconophysics perspective: The case of Brazilian inflation dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    18. Di Xiao & Jun Wang & Hongli Niu, 2016. "Volatility Analysis of Financial Agent-Based Market Dynamics from Stochastic Contact System," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 607-625, December.
    19. Pierre Gosselin & Aïleen Lotz & Marc Wambst, 2017. "A Path Integral Approach to Interacting Economic Systems with Multiple Heterogeneous Agents," Working Papers hal-01549586, HAL.
    20. Ivan Jericevich & Patrick Chang & Tim Gebbie, 2021. "Simulation and estimation of an agent-based market-model with a matching engine," Papers 2108.07806, arXiv.org, revised Aug 2021.
    21. Alexander Lykov & Stepan Muzychka & Kirill Vaninsky, 2016. "Investor'S Sentiment In Multi-Agent Model Of The Continuous Double Auction," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(06), pages 1-29, September.

    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:phsmap:v:598:y:2022:i:c:s0378437122001996. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.