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How effective is advertising in duopoly markets?

Author

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  • K. Sznajd-Weron
  • R. Weron

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.

Suggested Citation

  • K. Sznajd-Weron & R. Weron, 2002. "How effective is advertising in duopoly markets?," Papers cond-mat/0211058, arXiv.org, revised Dec 2002.
    • Handle: RePEc:arx:papers:cond-mat/0211058
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    Cited by:

    1. 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).
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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 Science and Technology.
    9. Shin, J.K., 2010. "Tipping news in information accumulation system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2118-2126.
    10. Situngkir, Hokky, 2006. "Advertising in Duopoly Market," MPRA Paper 885, University Library of Munich, Germany.
    11. 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.
    12. 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 Science and Technology.
    13. 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).
    14. 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.
    15. 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 Science and Technology.
    16. 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.
    17. 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.
    18. 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.

    More about this item

    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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