IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0166323.html
   My bibliography  Save this article

The Hunt Opinion Model—An Agent Based Approach to Recurring Fashion Cycles

Author

Listed:
  • Rafał Apriasz
  • Tyll Krueger
  • Grzegorz Marcjasz
  • Katarzyna Sznajd-Weron

Abstract

We study a simple agent-based model of the recurring fashion cycles in the society that consists of two interacting communities: “snobs” and “followers” (or “opinion hunters”, hence the name of the model). Followers conform to all other individuals, whereas snobs conform only to their own group and anticonform to the other. The model allows to examine the role of the social structure, i.e. the influence of the number of inter-links between the two communities, as well as the role of the stability of links. The latter is accomplished by considering two versions of the same model—quenched (parameterized by fraction L of fixed inter-links) and annealed (parameterized by probability p that a given inter-link exists). Using Monte Carlo simulations and analytical treatment (the latter only for the annealed model), we show that there is a critical fraction of inter-links, above which recurring cycles occur. For p ≤ 0.5 we derive a relation between parameters L and p that allows to compare both models and show that the critical value of inter-connections, p*, is the same for both versions of the model (annealed and quenched) but the period of a fashion cycle is shorter for the quenched model. Near the critical point, the cycles are irregular and a change of fashion is difficult to predict. For the annealed model we also provide a deeper theoretical analysis. We conjecture on topological grounds that the so-called saddle node heteroclinic bifurcation appears at p*. For p ≥ 0.5 we show analytically the existence of the second critical value of p, for which the system undergoes Hopf’s bifurcation.

Suggested Citation

  • Rafał Apriasz & Tyll Krueger & Grzegorz Marcjasz & Katarzyna Sznajd-Weron, 2016. "The Hunt Opinion Model—An Agent Based Approach to Recurring Fashion Cycles," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-19, November.
  • Handle: RePEc:plo:pone00:0166323
    DOI: 10.1371/journal.pone.0166323
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0166323
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0166323&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0166323?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
    ---><---

    References listed on IDEAS

    as
    1. Rand, William & Rust, Roland T., 2011. "Agent-based modeling in marketing: Guidelines for rigor," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 181-193.
    2. Patryk Siedlecki & Janusz Szwabiński & Tomasz Weron, 2016. "The Interplay Between Conformity and Anticonformity and its Polarizing Effect on Society," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(4), pages 1-9.
    3. Byrka, Katarzyna & Jȩdrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna & Weron, Rafał, 2016. "Difficulty is critical: The importance of social factors in modeling diffusion of green products and practices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 723-735.
    4. Jerker Denrell & Balázs Kovács, 2015. "The Effect of Selection Bias in Studies of Fads and Fashions," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-19, April.
    5. Zhigang Cao & Haoyu Gao & Xinglong Qu & Mingmin Yang & Xiaoguang Yang, 2013. "Fashion, Cooperation, and Social Interactions," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-14, January.
    6. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    7. Tatiana Bouzdine-Chameeva & Serge Galam, 2011. "Word-Of-Mouth Versus Experts And Reputation In The Individual Dynamics Of Wine Purchasing," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 14(06), pages 871-885.
    8. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    9. Krawczyk, M.J. & Dydejczyk, A. & Kułakowski, K., 2014. "The Simmel effect and babies’ names," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 384-391.
    10. Gene Callahan & Andreas Hoffmann, 2017. "Two-Population Social Cycle Theories," Research in the History of Economic Thought and Methodology, in: Including a Symposium on New Directions in Sraffa Scholarship, volume 35, pages 303-321, Emerald Group Publishing Limited.
    11. Paul R. Nail & Katarzyna Sznajd-Weron, 2016. "The diamond model of social response within an agent-based approach," HSC Research Reports HSC/16/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shang, Lihui & Zhao, Mingming & Ai, Jun & Su, Zhan, 2021. "Opinion evolution in the Sznajd model on interdependent chains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    2. Chaitanya S. Gokhale & Joseph Bulbulia & Marcus Frean, 2022. "Collective narratives catalyse cooperation," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.

    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. Jędrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna, 2018. "Impact of memory on opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 306-315.
    2. Weron, Tomasz & Kowalska-Pyzalska, Anna & Weron, Rafał, 2018. "The role of educational trainings in the diffusion of smart metering platforms: An agent-based modeling approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 591-600.
    3. Agnieszka Kowalska-Styczeń & Krzysztof Malarz, 2020. "Noise induced unanimity and disorder in opinion formation," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-22, July.
    4. 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.
    5. Hesselink, Laurens X.W. & Chappin, Emile J.L., 2019. "Adoption of energy efficient technologies by households – Barriers, policies and agent-based modelling studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 29-41.
    6. Scheller, Fabian & Johanning, Simon & Bruckner, Thomas, 2019. "A review of designing empirically grounded agent-based models of innovation diffusion: Development process, conceptual foundation and research agenda," Contributions of the Institute for Infrastructure and Resources Management 01/2019, University of Leipzig, Institute for Infrastructure and Resources Management.
    7. Giannoccaro, Ilaria & Carbone, Giuseppe, 2017. "An Ising-based dynamic model to study the effect of social interactions on firm absorptive capacity," International Journal of Production Economics, Elsevier, vol. 194(C), pages 214-227.
    8. Anna Kowalska-Pyzalska, 2016. "What makes consumers adopt to innovative energy services in the energy market?," HSC Research Reports HSC/16/09, Hugo Steinhaus Center, Wroclaw University of Technology.
    9. Shi, Yingying & Zeng, Yongchao & Engo, Jean & Han, Botang & Li, Yang & Muehleisen, Ralph T., 2020. "Leveraging inter-firm influence in the diffusion of energy efficiency technologies: An agent-based model," Applied Energy, Elsevier, vol. 263(C).
    10. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    11. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2014. "Diffusion and adoption of dynamic electricity tariffs: An agent-based modeling approach," HSC Research Reports HSC/14/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    12. Jeffery S. McMullen & Dimo Dimov, 2013. "Time and the Entrepreneurial Journey: The Problems and Promise of Studying Entrepreneurship as a Process," Journal of Management Studies, Wiley Blackwell, vol. 50(8), pages 1481-1512, December.
    13. Yue Chen & Xiaojian Niu & Yan Zhang, 2019. "Exploring Contrarian Degree in the Trading Behavior of China's Stock Market," Complexity, Hindawi, vol. 2019, pages 1-12, April.
    14. Jovanovic, Franck & Schinckus, Christophe, 2016. "Breaking down the barriers between econophysics and financial economics," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 256-266.
    15. Xin, C. & Yang, G. & Huang, J.P., 2017. "Ising game: Nonequilibrium steady states of resource-allocation systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 666-673.
    16. Alexandre Lucas & Konstantinos Pegios & Evangelos Kotsakis & Dan Clarke, 2020. "Price Forecasting for the Balancing Energy Market Using Machine-Learning Regression," Energies, MDPI, vol. 13(20), pages 1-16, October.
    17. John Rutledge, 2015. "Economics as energy framework: Complexity, turbulence, financial crises, and protectionism," Review of Financial Economics, John Wiley & Sons, vol. 25(1), pages 10-18, April.
    18. Yuichi Ikeda, 2020. "An Interacting Agent Model of Economic Crisis," Papers 2001.11843, arXiv.org.
    19. Roman Šperka & Michal Halaška, 2017. "MAREA Trading Simulations Experiments with the Focus on Marketing Campaign," Working Papers 0036, Silesian University, School of Business Administration.
    20. Arthur Matsuo Yamashita Rios de Sousa & Hideki Takayasu & Misako Takayasu, 2017. "Detection of statistical asymmetries in non-stationary sign time series: Analysis of foreign exchange data," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-18, May.

    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:plo:pone00:0166323. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.