IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v518y2019icp50-70.html
   My bibliography  Save this article

Modeling Competitive Marketing Strategies in Social Networks

Author

Listed:
  • Goel, Rahul
  • Singh, Anurag
  • Ghanbarnejad, Fakhteh

Abstract

A model is developed in which two players compete to spread information in the large network. Players choose their initial seed nodes simultaneously and the information is diffused according to Independent Cascade model (ICM). The main aim of the player is to choose the seed nodes such that they will spread its information to as many nodes as possible in a social network. Here we show and discuss how the rate of spreading of information as well as seed choosing depending on topological features play roles in information diffusion process. Any node in a social network will get influenced by none or one or more than one information. We also analyzed how much fraction of nodes in different compartment changes by changing the rate of spreading of information. Finally, a game theory model is developed to obtain the Nash equilibrium based on best response function of the players. This model is based on Hotelling’s model of electoral competition.

Suggested Citation

  • Goel, Rahul & Singh, Anurag & Ghanbarnejad, Fakhteh, 2019. "Modeling Competitive Marketing Strategies in Social Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 50-70.
    • Handle: RePEc:eee:phsmap:v:518:y:2019:i:c:p:50-70
    DOI: 10.1016/j.physa.2018.11.035
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118314523
    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.2018.11.035?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. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. Karimi, Fariba & Holme, Petter, 2013. "Threshold model of cascades in empirical temporal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3476-3483.
    3. Blume Lawrence E., 1993. "The Statistical Mechanics of Strategic Interaction," Games and Economic Behavior, Elsevier, vol. 5(3), pages 387-424, July.
    4. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    5. Martin J. Osborne & Ariel Rubinstein, 1994. "A Course in Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262650401, April.
    6. Centola, Damon & Eguíluz, Víctor M. & Macy, Michael W., 2007. "Cascade dynamics of complex propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 449-456.
    7. Brown, Jacqueline Johnson & Reingen, Peter H, 1987. "Social Ties and Word-of-Mouth Referral Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(3), pages 350-362, December.
    8. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331, October.
    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. Singh, Anurag & Arquam, Md, 2022. "Epidemiological modeling for COVID-19 spread in India with the effect of testing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    2. Ahmad, Amreen & Ahmad, Tanvir & Bhatt, Abhishek, 2020. "HWSMCB: A community-based hybrid approach for identifying influential nodes in the social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    3. Geng, Yang & Zhang, Yulin, 2020. "Platform launch in two-sided markets and users’ expectations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).

    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. Claus, Bart & Geyskens, Kelly & Millet, Kobe & Dewitte, Siegfried, 2012. "The referral backfire effect: The identity-threatening nature of referral failure," International Journal of Research in Marketing, Elsevier, vol. 29(4), pages 370-379.
    2. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    3. Bary Pradelski, 2019. "Control by social influence: durables vs. non-durables," Post-Print hal-03100218, HAL.
    4. Tolotti, Marco & Yepez, Jorge, 2020. "Hotelling-Bertrand duopoly competition under firm-specific network effects," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 105-128.
    5. M Günther & C Stummer & L M Wakolbinger & M Wildpaner, 2011. "An agent-based simulation approach for the new product diffusion of a novel biomass fuel," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 12-20, January.
    6. Oyama, Daisuke & Takahashi, Satoru, 2015. "Contagion and uninvadability in local interaction games: The bilingual game and general supermodular games," Journal of Economic Theory, Elsevier, vol. 157(C), pages 100-127.
    7. Flachsbarth, Insa & Grassnick, Nina & Masood, Amjad & Bruemmer, Bernhard, 2018. "The Uneven Spread of Private Food Quality Standards over Time and Space," 2018 Annual Meeting, August 5-7, Washington, D.C. 274197, Agricultural and Applied Economics Association.
    8. Hellmann, Tim & Staudigl, Mathias, 2014. "Evolution of social networks," European Journal of Operational Research, Elsevier, vol. 234(3), pages 583-596.
    9. Ishii, Akira & Sakaidani, Shota & Iwanaga, Saori, 2016. "Possilibity of estimating payoff matrix from model for hit phenomena," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 72-80.
    10. Mohsen Mosleh & Peter Ludlow & Babak Heydari, 2016. "Distributed Resource Management in Systems of Systems: An Architecture Perspective," Systems Engineering, John Wiley & Sons, vol. 19(4), pages 362-374, July.
    11. Côme Billard, 2020. "Technology Contagion in Networks," Working Papers 2020.01, FAERE - French Association of Environmental and Resource Economists.
    12. H Peyton Young & Lucas Merrill Brown, 2016. "The Diffusion of a Social Innovation: Executive Stock Options from 1936," Economics Series Working Papers 777, University of Oxford, Department of Economics.
    13. Pan, Yue & Zhang, Jason Q., 2011. "Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews," Journal of Retailing, Elsevier, vol. 87(4), pages 598-612.
    14. Nejad, Mohammad G. & Amini, Mehdi & Babakus, Emin, 2015. "Success Factors in Product Seeding: The Role of Homophily," Journal of Retailing, Elsevier, vol. 91(1), pages 68-88.
    15. Mitja Steinbacher & Matthias Raddant & Fariba Karimi & Eva Camacho Cuena & Simone Alfarano & Giulia Iori & Thomas Lux, 2021. "Advances in the agent-based modeling of economic and social behavior," SN Business & Economics, Springer, vol. 1(7), pages 1-24, July.
    16. Michael Braun & André Bonfrer, 2011. "Scalable Inference of Customer Similarities from Interactions Data Using Dirichlet Processes," Marketing Science, INFORMS, vol. 30(3), pages 513-531, 05-06.
    17. Hu, Nan & Liu, Ling & Tripathy, Arindam & Yao, Lee J., 2011. "Value relevance of blog visibility," Journal of Business Research, Elsevier, vol. 64(12), pages 1361-1368.
    18. Tingting Song & Qian Tang & Jinghua Huang, 2019. "Triadic Closure, Homophily, and Reciprocation: An Empirical Investigation of Social Ties Between Content Providers," Information Systems Research, INFORMS, vol. 30(3), pages 912-926, September.
    19. Jia-Ping Huang & Yang Zhang & Juanxi Wang, 2023. "Dynamic effects of social influence on asset prices," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 671-699, July.
    20. Ye Hu & Kitty Wang & Ming Chen & Sam Hui, 2021. "Herding Among Retail Shoppers: the Case of Television Shopping Network," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 8(1), pages 27-40, June.

    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:518:y:2019:i:c:p:50-70. 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.