IDEAS home Printed from https://ideas.repec.org/a/eee/matsoc/v128y2024icp41-51.html
   My bibliography  Save this article

Optimal influence under observational learning

Author

Listed:
  • Tsakas, Nikolas

Abstract

We study the optimal targeting problem of a firm that is seeking to maximize the diffusion of a product in a society where agents learn from their neighbors. The firm can seed the product to a subset of the population and our goal is to find which the optimal subset to target is. We provide a condition that characterizes the optimal targeting strategy for any network structure. The key parameter in this condition is the agents’ decay centrality, which takes into account how close an agent is to others, in a way that distant agents are weighted less than closer ones.

Suggested Citation

  • Tsakas, Nikolas, 2024. "Optimal influence under observational learning," Mathematical Social Sciences, Elsevier, vol. 128(C), pages 41-51.
    • Handle: RePEc:eee:matsoc:v:128:y:2024:i:c:p:41-51
    DOI: 10.1016/j.mathsocsci.2024.01.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165489624000209
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.mathsocsci.2024.01.011?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. Lola Esteban & José M. Hernández & José Luis Moraga‐González, 2006. "Customer Directed Advertising and Product Quality," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 15(4), pages 943-968, December.
    2. Tsakas, Nikolas, 2017. "Diffusion by imitation: The importance of targeting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 139(C), pages 118-151.
    3. Vega-Redondo,Fernando, 2007. "Complex Social Networks," Cambridge Books, Cambridge University Press, number 9780521857406.
    4. Andrea Galeotti & Sanjeev Goyal, 2009. "Influencing the influencers: a theory of strategic diffusion," RAND Journal of Economics, RAND Corporation, vol. 40(3), pages 509-532, September.
    5. Sanjeev Goyal, 2007. "Introduction to Connections: An Introduction to the Economics of Networks," Introductory Chapters, in: Connections: An Introduction to the Economics of Networks, Princeton University Press.
    6. Vega-Redondo,Fernando, 2007. "Complex Social Networks," Cambridge Books, Cambridge University Press, number 9780521674096.
    7. Tsakas Nikolas, 2019. "On Decay Centrality," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 19(1), pages 1-18, January.
    8. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    9. Kostas Bimpikis & Asuman Ozdaglar & Ercan Yildiz, 2016. "Competitive Targeted Advertising Over Networks," Operations Research, INFORMS, vol. 64(3), pages 705-720, June.
    10. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska & Emily Tanimura, 2015. "Strategic influence in social networks," Post-Print hal-01158168, HAL.
    11. Kalyan Chatterjee & Bhaskar Dutta, 2016. "Credibility And Strategic Learning In Networks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(3), pages 759-786, August.
    12. David Bell & Sangyoung Song, 2007. "Neighborhood effects and trial on the internet: Evidence from online grocery retailing," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 361-400, December.
    13. Arthur Campbell, 2013. "Word-of-Mouth Communication and Percolation in Social Networks," American Economic Review, American Economic Association, vol. 103(6), pages 2466-2498, October.
    14. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    15. Kalyan Chatterjee & Bhaskar Dutta, 2016. "Credibility And Strategic Learning In Networks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57, pages 759-786, August.
    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. Nikolas Tsakas, 2014. "Optimal influence under observational learning," Gecomplexity Discussion Paper Series 4, Action IS1104 "The EU in the new complex geography of economic systems: models, tools and policy evaluation", revised Nov 2014.
    2. Giovanni Pegoretti & Francesco Rentocchini & Giuseppe Vittucci Marzetti, 2012. "An agent-based model of innovation diffusion: network structure and coexistence under different information regimes," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 145-165, October.
    3. Foerster, Manuel & Hellmann, Tim & Vega-Redondo, Fernando, 2024. "Strategic use of social media influencer marketing," UC3M Working papers. Economics 43985, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Daniel C. Opolot & Théophile T. Azomahou, 2021. "Strategic diffusion in networks through contagion," Journal of Evolutionary Economics, Springer, vol. 31(3), pages 995-1027, July.
    5. Paolo Zeppini & Koen Frenken & Luis R. Izquierdo, 2013. "Innovation diffusion in networks: the microeconomics of percolation," Working Papers 13-02, Eindhoven Center for Innovation Studies, revised Feb 2013.
    6. Goyal, S., 2016. "Networks and Markets," Cambridge Working Papers in Economics 1652, Faculty of Economics, University of Cambridge.
    7. Rusinowska, Agnieszka & Taalaibekova, Akylai, 2019. "Opinion formation and targeting when persuaders have extreme and centrist opinions," Journal of Mathematical Economics, Elsevier, vol. 84(C), pages 9-27.
    8. Jackson, Matthew O. & Zenou, Yves, 2015. "Games on Networks," Handbook of Game Theory with Economic Applications,, Elsevier.
    9. Goyal, S., 2018. "Heterogeneity and Networks," Cambridge Working Papers in Economics 1812, Faculty of Economics, University of Cambridge.
    10. Yuichiro Kamada & Aniko Öry, 2020. "Contracting with Word-of-Mouth Management," Management Science, INFORMS, vol. 66(11), pages 5094-5107, November.
    11. 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.
    12. Marcel Fafchamps & Måns Söderbom & Monique van den Boogart, 2022. "Adoption with Social Learning and Network Externalities," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1259-1282, December.
    13. Matthew O. Jackson, 2014. "Networks in the Understanding of Economic Behaviors," Journal of Economic Perspectives, American Economic Association, vol. 28(4), pages 3-22, Fall.
    14. 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.
    15. Lelarge, Marc, 2012. "Diffusion and cascading behavior in random networks," Games and Economic Behavior, Elsevier, vol. 75(2), pages 752-775.
    16. María Paz Espinosa & Jaromír Kovárík & Sofía Ruíz-Palazuelos, 2021. "Are close-knit networks good for employment?," Working Papers 21.06, Universidad Pablo de Olavide, Department of Economics.
    17. Galeotti, Andrea & W. Rogers, Brian, 2012. "Strategic immunization and group structure," ISER Working Paper Series 2012-16, Institute for Social and Economic Research.
    18. Konno, Tomohiko, 2013. "An imperfect competition on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5453-5460.
    19. Arcaute, E. & Dyagilev, K. & Johari, R. & Mannor, S., 2013. "Dynamics in tree formation games," Games and Economic Behavior, Elsevier, vol. 79(C), pages 1-29.
    20. Cabrales, Antonio & Calvó-Armengol, Antoni & Zenou, Yves, 2011. "Social interactions and spillovers," Games and Economic Behavior, Elsevier, vol. 72(2), pages 339-360, 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:matsoc:v:128:y:2024:i:c:p:41-51. 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.elsevier.com/locate/inca/505565 .

    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.