IDEAS home Printed from https://ideas.repec.org/a/pal/jmarka/v9y2021i3d10.1057_s41270-021-00112-z.html
   My bibliography  Save this article

Incorporating negative and positive word of mouth (WOM) in compartment-based epidemiology models in a not-for-profit marketing context

Author

Listed:
  • John Andy Wood

    (James Madison University)

Abstract

The simultaneous occurrence of negative and positive word of mouth is often likely in a marketing context. Measuring the influence of these conflicting social pressures is not straightforward in current diffusion models. Adaptations from compartment models of epidemiology can provide methods for estimating both positive and negative word of mouth. This study examines the impact of positive and negative word of mouth on donating behavior using data from over 89,000 households that made a gift to a non-profit. The 10-year longitudinal dataset creates the opportunity to calculate negative and positive word of mouth on donating behavior.

Suggested Citation

  • John Andy Wood, 2021. "Incorporating negative and positive word of mouth (WOM) in compartment-based epidemiology models in a not-for-profit marketing context," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(3), pages 199-209, September.
    • Handle: RePEc:pal:jmarka:v:9:y:2021:i:3:d:10.1057_s41270-021-00112-z
    DOI: 10.1057/s41270-021-00112-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41270-021-00112-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1057/s41270-021-00112-z?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. Tal Garber & Jacob Goldenberg & Barak Libai & Eitan Muller, 2004. "From Density to Destiny: Using Spatial Dimension of Sales Data for Early Prediction of New Product Success," Marketing Science, INFORMS, vol. 23(3), pages 419-428, August.
    2. Vijay Mahajan & Eitan Muller & Roger A. Kerin, 1984. "Introduction Strategy for New Products with Positive and Negative Word-of-Mouth," Management Science, INFORMS, vol. 30(12), pages 1389-1404, December.
    3. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    4. 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.
    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. Olivier Toubia & Jacob Goldenberg & Rosanna Garcia, 2014. "Improving Penetration Forecasts Using Social Interactions Data," Management Science, INFORMS, vol. 60(12), pages 3049-3066, December.
    2. 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.
    3. Kopalle, Praveen K. & Lehmann, Donald R., 2015. "The Truth Hurts: How Customers May Lose From Honest Advertising," International Journal of Research in Marketing, Elsevier, vol. 32(3), pages 251-262.
    4. Hailin Zhang & Xina Yuan & Tae Ho Song, 2020. "Examining the role of the marketing activity and eWOM in the movie diffusion: the decomposition perspective," Electronic Commerce Research, Springer, vol. 20(3), pages 589-608, September.
    5. Jacob Goldenberg & Oded Lowengart & Daniel Shapira, 2009. "Zooming In: Self-Emergence of Movements in New Product Growth," Marketing Science, INFORMS, vol. 28(2), pages 274-292, 03-04.
    6. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
    7. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    8. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    9. Rohit Aggarwal & Ram Gopal & Ramesh Sankaranarayanan, 2007. "Negative Blogs, Positive Outcomes: When should Firms Permit Employees to Blog Honestly?," Working Papers 07-32, NET Institute, revised Sep 2007.
    10. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    11. Delre, Sebastiano A. & Panico, Claudio & Wierenga, Berend, 2017. "Competitive strategies in the motion picture industry: An ABM to study investment decisions," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 69-99.
    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. Andrea Ellero & Annamaria Sorato & Giovanni Fasano, 2011. "A new model for estimating the probability of information spreading with opinion leaders," Working Papers 13, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
    14. Vardit Landsman & Moshe Givon, 2010. "The diffusion of a new service: Combining service consideration and brand choice," Quantitative Marketing and Economics (QME), Springer, vol. 8(1), pages 91-121, March.
    15. Abedi, Vahideh Sadat, 2019. "Compartmental diffusion modeling: Describing customer heterogeneity & communication network to support decisions for new product introductions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    16. 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.
    17. Chao, Chih-Wei & Reid, Mike & Mavondo, Felix T., 2012. "Consumer innovativeness influence on really new product adoption," Australasian marketing journal, Elsevier, vol. 20(3), pages 211-217.
    18. Li, Pengdeng & Yang, Xiaofan & Yang, Lu-Xing & Xiong, Qingyu & Wu, Yingbo & Tang, Yuan Yan, 2018. "The modeling and analysis of the word-of-mouth marketing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 1-16.
    19. Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.
    20. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, 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:pal:jmarka:v:9:y:2021:i:3:d:10.1057_s41270-021-00112-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    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.