IDEAS home Printed from https://ideas.repec.org/p/arx/papers/0707.2341.html
   My bibliography  Save this paper

A Cultural Market Model

Author

Listed:
  • Amac Herdagdelen
  • Haluk Bingol

Abstract

Social interactions and personal tastes shape our consumption behavior of cultural products. In this study, we present a computational model of a cultural market and we aim to analyze the behavior of the consumer population as an emergent phenomena. Our results suggest that the final market shares of cultural products dramatically depend on consumer heterogeneity and social interaction pressure. Furthermore, the relation between the resulting market shares and social interaction is robust with respect to a wide range of variation in the parameter values and the type of topology.

Suggested Citation

  • Amac Herdagdelen & Haluk Bingol, 2007. "A Cultural Market Model," Papers 0707.2341, arXiv.org, revised Apr 2008.
    • Handle: RePEc:arx:papers:0707.2341
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/0707.2341
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sheri Markose, 2006. "Developments in experimental and agent-based computational economics (ACE): overview," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 1(2), pages 119-127, November.
    2. Galam, Serge, 1997. "Rational group decision making: A random field Ising model at T = 0," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 238(1), pages 66-80.
    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. LeBaron Blake & Winker Peter, 2008. "Introduction to the Special Issue on Agent-Based Models for Economic Policy Advice," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 141-148, April.
    2. Piotr Przybyła & Katarzyna Sznajd-Weron & Rafał Weron, 2014. "Diffusion Of Innovation Within An Agent-Based Model: Spinsons, Independence And Advertising," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-22.
    3. repec:hal:wpaper:hal-00623966 is not listed on IDEAS
    4. Tiwari, Mukesh & Yang, Xiguang & Sen, Surajit, 2021. "Modeling the nonlinear effects of opinion kinematics in elections: A simple Ising model with random field based study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    5. Katarzyna Ostasiewicz & Michal H. Tyc & Piotr Goliczewski & Piotr Magnuszewski & Andrzej Radosz & Jan Sendzimir, 2006. "Integrating economic and psychological insights in binary choice models with social interactions," Papers physics/0609170, arXiv.org.
    6. AskariSichani, Omid & Jalili, Mahdi, 2015. "Influence maximization of informed agents in social networks," Applied Mathematics and Computation, Elsevier, vol. 254(C), pages 229-239.
    7. Baldassarri, Simone & Gallo, Anna & Jacquier, Vanessa & Zocca, Alessandro, 2023. "Ising model on clustered networks: A model for opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    8. Lucila G Alvarez-Zuzek & Cristian E La Rocca & Federico Vazquez & Lidia A Braunstein, 2016. "Interacting Social Processes on Interconnected Networks," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-17, September.
    9. Galam, Serge, 2004. "Sociophysics: a personal testimony," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 49-55.
    10. Gary Mckeown & Noel Sheehy, 2006. "Mass Media and Polarisation Processes in the Bounded Confidence Model of Opinion Dynamics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-11.
    11. Boudin, Laurent & Mercier, Aurore & Salvarani, Francesco, 2012. "Conciliatory and contradictory dynamics in opinion formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5672-5684.
    12. Juliette Rouchier & Emily Tanimura, 2012. "When overconfident agents slow down collective learning," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00623966, HAL.
    13. Itzhak Benenson & Erez Hatna & Ehud Or, 2009. "From Schelling to Spatially Explicit Modeling of Urban Ethnic and Economic Residential Dynamics," Sociological Methods & Research, , vol. 37(4), pages 463-497, May.
    14. Galam, Serge & Zucker, Jean-Daniel, 2000. "From individual choice to group decision-making," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 644-659.
    15. Laciana, Carlos E. & Rovere, Santiago L., 2011. "Ising-like agent-based technology diffusion model: Adoption patterns vs. seeding strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1139-1149.
    16. Iori, Giulia, 2002. "A microsimulation of traders activity in the stock market: the role of heterogeneity, agents' interactions and trade frictions," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 269-285, October.
    17. Schweitzer, Frank & Zimmermann, Jörg & Mühlenbein, Heinz, 2002. "Coordination of decisions in a spatial agent model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 303(1), pages 189-216.
    18. Pareschi, Lorenzo & Vellucci, Pierluigi & Zanella, Mattia, 2017. "Kinetic models of collective decision-making in the presence of equality bias," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 201-217.
    19. Juliette Rouchier & Emily Tanimura, 2012. "When overconfident agents slow down collective learning," Post-Print hal-00623966, HAL.
    20. Elizabeth L. Ogburn & Ilya Shpitser & Youjin Lee, 2020. "Causal inference, social networks and chain graphs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1659-1676, October.
    21. Carlos E. Laciana & Santiago L. Rovere, 2010. "Ising-like agent-based technology diffusion model: adoption patterns vs. seeding strategies," Papers 1011.3834, arXiv.org, revised Jan 2013.

    More about this item

    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:arx:papers:0707.2341. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.