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How effective is advertising in duopoly markets?

Author

Listed:
  • Katarzyna Sznajd-Weron

    (University of Wroclaw)

  • Rafal Weron

    (Hugo Steinhaus Center, Wroclaw University of Technology)

Abstract

A simple Ising spin model which can describe the mechanism of advertising in a duopoly market is proposed. In contrast to other agent- based models, the influence does not flow inward from the surrounding neighbors to the center site, but spreads outward from the center to the neighbors. The model thus describes the spread of opinions among customers. It is shown via standard Monte Carlo simulations that very simple rules and inclusion of an external field - an advertising campaign - lead to phase transitions, ie. extreme and fast changes in market share.

Suggested Citation

  • Katarzyna Sznajd-Weron & Rafal Weron, 2003. "How effective is advertising in duopoly markets?," Public Economics 0306005, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwppe:0306005
    Note: Type of Document - PDF; prepared on PC-TEX; pages: 7; figures: 6 included. Appeared in: Physica A 324 (2003) 437-444.
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    References listed on IDEAS

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    1. Jean Tirole, 1988. "The Theory of Industrial Organization," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262200716, April.
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    Cited by:

    1. Luo, Gui-Xun & Liu, Yun & Zeng, Qing-An & Diao, Su-Meng & Xiong, Fei, 2014. "A dynamic evolution model of human opinion as affected by advertising," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 254-262.
    2. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    3. 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.
    4. 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.
    5. Sznajd-Weron, Katarzyna & Sznajd, Józef & Weron, Tomasz, 2021. "A review on the Sznajd model — 20 years after," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    6. Shin, J.K., 2009. "Information accumulation system by inheritance and diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3593-3599.
    7. Shin, J.K., 2010. "Tipping news in information accumulation system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2118-2126.
    8. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2013. "Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs," HSC Research Reports HSC/13/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    9. Zhu, Hou & Hu, Bin, 2018. "Impact of information on public opinion reversal—An agent based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 578-587.
    10. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2014. "Modeling consumer opinions towards dynamic pricing: An agent-based approach," HSC Research Reports HSC/14/06, Hugo Steinhaus Center, Wroclaw University of Technology.
    11. Situngkir, Hokky, 2006. "Advertising in Duopoly Market," MPRA Paper 885, University Library of Munich, Germany.
    12. 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.
    13. Agnieszka Kowalska-Styczen, 2009. "Simulation model ofconsumer decision making," Operations Research and Decisions, Wroclaw University of Technology, Institute of Organization and Management, vol. 4, pages 47-60.
    14. Gündüç, Semra & Eryiğit, Recep, 2015. "The role of persuasion power on the consensus formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 426(C), pages 16-24.
    15. Oliveira, Igor V.G. & Wang, Chao & Dong, Gaogao & Du, Ruijin & Fiore, Carlos E. & Vilela, André L.M. & Stanley, H. Eugene, 2024. "Entropy production on cooperative opinion dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    16. Catherine A. Glass & David H. Glass, 2021. "Social Influence of Competing Groups and Leaders in Opinion Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 799-823, October.
    17. 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.
    18. Agnieszka Kowalska-Styczeń, 2009. "Simulation model of consumer decision making," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 19(4), pages 47-60.

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    More about this item

    Keywords

    advertising; oligopoly; duopoly; Ising model; agent-based model;
    All these keywords.

    JEL classification:

    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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