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Advertising and Quality-Dependent Word-of-Mouth in a Contagion Sales Model

Author

Listed:
  • Fouad El Ouardighi

    (ESSEC Business School)

  • Gustav Feichtinger

    (Vienna University of Technology)

  • Dieter Grass

    (Vienna University of Technology)

  • Richard F. Hartl

    (University of Vienna)

  • Peter M. Kort

    (Tilburg University
    University of Antwerp)

Abstract

In the literature on marketing models, the assumption of mixed word-of-mouth has been limited to the Bass diffusion model. Yet explicit leveraging of the originating factors of such assumption is lacking. Apart from that example, mixed word-of-mouth has been disregarded in contagion sales models. This paper bridges the gap by suggesting a sales model, where both positive and negative word-of-mouth affect the attraction rate of new customers, along with advertising. The difference between positive and negative word-of-mouth is based on the distinction between satisfied and dissatisfied current customers, which is supposed to depend on conformance quality. A primary issue in this paper is to determine how a firm should determine the optimal intertemporal trade-off between investing in advertising-dependent word-of-mouth and quality-dependent word-of-mouth. To address this issue, a contagion sales model is suggested where mixed autonomous word-of-mouth alone can lead to either commercial success or failure of a given brand.

Suggested Citation

  • Fouad El Ouardighi & Gustav Feichtinger & Dieter Grass & Richard F. Hartl & Peter M. Kort, 2016. "Advertising and Quality-Dependent Word-of-Mouth in a Contagion Sales Model," Journal of Optimization Theory and Applications, Springer, vol. 170(1), pages 323-342, July.
  • Handle: RePEc:spr:joptap:v:170:y:2016:i:1:d:10.1007_s10957-015-0855-0
    DOI: 10.1007/s10957-015-0855-0
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    References listed on IDEAS

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    1. Dieter Grass & Jonathan P. Caulkins & Gustav Feichtinger & Gernot Tragler & Doris A. Behrens, 2008. "Optimal Control of Nonlinear Processes," Springer Books, Springer, number 978-3-540-77647-5, June.
    2. El Ouardighi, Fouad & Pasin, Federico, 2006. "Quality improvement and goodwill accumulation in a dynamic duopoly," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1021-1032, December.
    3. Dina Mayzlin & Judith A. Chevalier, 2003. "The Effect of Word of Mouth on Sales: Online Book Reviews," Yale School of Management Working Papers ysm413, Yale School of Management.
    4. Ahluwalia, Rohini, 2002. "How Prevalent Is the Negativity Effect in Consumer Environments?," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 29(2), pages 270-279, September.
    5. Nelson, Phillip, 1970. "Information and Consumer Behavior," Journal of Political Economy, University of Chicago Press, vol. 78(2), pages 311-329, March-Apr.
    6. 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.
    7. Tang, Christopher S., 2010. "A review of marketing-operations interface models: From co-existence to coordination and collaboration," International Journal of Production Economics, Elsevier, vol. 125(1), pages 22-40, May.
    8. Nelson, Philip, 1974. "Advertising as Information," Journal of Political Economy, University of Chicago Press, vol. 82(4), pages 729-754, July/Aug..
    9. Sheth, Jagdish N. & Sisodia, Rajendra S., 2002. "Marketing productivity: issues and analysis," Journal of Business Research, Elsevier, vol. 55(5), pages 349-362, May.
    10. George Li & S. Rajagopalan, 1998. "Process Improvement, Quality, and Learning Effects," Management Science, INFORMS, vol. 44(11-Part-1), pages 1517-1532, November.
    11. Fred M. Feinberg, 2001. "On Continuous-Time Optimal Advertising Under S-Shaped Response," Management Science, INFORMS, vol. 47(11), pages 1476-1487, November.
    12. Vijay Mahajan & Eitan Muller, 1986. "Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 89-106.
    13. Vijay Mahajan & Eitan Muller, 1986. "Reply—Reflections on Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 110-111.
    14. Huang, Jian & Leng, Mingming & Liang, Liping, 2012. "Recent developments in dynamic advertising research," European Journal of Operational Research, Elsevier, vol. 220(3), pages 591-609.
    15. Fouad El Ouardighi & Konstantin Kogan, 2013. "Dynamic conformance and design quality in a supply chain: an assessment of contracts’ coordinating power," Annals of Operations Research, Springer, vol. 211(1), pages 137-166, December.
    16. Yehuda Kotowitz & Frank Mathewson, 1979. "Advertising, Consumer Information, and Product Quality," Bell Journal of Economics, The RAND Corporation, vol. 10(2), pages 566-588, Autumn.
    17. Grass, D., 2012. "Numerical computation of the optimal vector field: Exemplified by a fishery model," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1626-1658.
    18. G. E. Fruchter, 2009. "Signaling Quality: Dynamic Price-Advertising Model," Journal of Optimization Theory and Applications, Springer, vol. 143(3), pages 479-496, December.
    19. Suresh Chand & Herbert Moskowitz & Andreas Novak & Ishpal Rekhi & Gerhard Sorger, 1996. "Capacity Allocation for Dynamic Process Improvement with Quality and Demand Considerations," Operations Research, INFORMS, vol. 44(6), pages 964-975, December.
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    Cited by:

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    2. De Giovanni, Pietro & Zaccour, Georges, 2023. "A survey of dynamic models of product quality," European Journal of Operational Research, Elsevier, vol. 307(3), pages 991-1007.
    3. Chenavaz, Régis Y. & Feichtinger, Gustav & Hartl, Richard F. & Kort, Peter M., 2020. "Modeling the impact of product quality on dynamic pricing and advertising policies," European Journal of Operational Research, Elsevier, vol. 284(3), pages 990-1001.
    4. Chernonog, Tatyana, 2020. "Inventory and marketing policy in a supply chain of a perishable product," International Journal of Production Economics, Elsevier, vol. 219(C), pages 259-274.
    5. Luca Grosset & Bruno Viscolani, 2021. "A dynamic advertising model in a vaccination campaign," 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. 29(2), pages 737-751, June.
    6. Régis Chenavaz & Sajjad M. Jasimuddin, 2017. "An analytical model of the relationship between product quality and advertising," Post-Print hal-01685892, HAL.
    7. Régis Chenavaz & Octavio Escobar & Xavier Rousset, 2019. "An analytical framework for retailer price and advertising decisions for products with temperature-sensitive demand," Applied Economics, Taylor & Francis Journals, vol. 51(52), pages 5683-5693, November.

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