IDEAS home Printed from
   My bibliography  Save this article

Oligopoly Models for Optimal Advertising When Production Costs Obey a Learning Curve


  • Jinn-Tsair Teng

    (University of Bridgeport)

  • Gerald L. Thompson

    (Carnegie-Mellon University)


Business policy questions frequently involve competitive encounters among several different firms. Oligopoly theory in economics was devised to answer similar questions, but its results so far are largely confined to cases of monopoly (one firm), duopoly (two firms), and many firms (wheat farmers). The cases with n firms, where 3 \le n \le 10, are of great interest to business policy, but are rarely treated in the economics literature because of their extreme difficulty. The natural mathematical model for studying such questions is the theory of differential games, originally devised by R. Isaacs (Isaacs, R. 1975. Differential Games. Robert E. Krieger Publishing Co., Huntington, New York. Originally published by John Wiley & Sons, New York, 1965.) for pursuer-evader games; later it was extended by J. Case (Case, J. H. 1979. Economics and the Competitive Process. New York University Press, New York.) to nonzero-sum differential games for application to questions of economic competition. The problem of characterizing an optimal advertising policy over time is an important question in the field of marketing. It is especially important during the period of the introduction of a new product; and it is also during this time that the production learning curve phenomenon is most pronounced. In this paper we study oligopoly models which combine elements of Bass's demand growth model (Bass, F. M. 1969. A new product growth model for consumer durables. Management Sci. 15 (January) 215--227.), the Vidale-Wolfe (Vidale, M. L., H. B. Wolfe. 1957. An operations research study of sales response to advertising. Oper. Res. 5 370--381.) and Ozga (Ozga, S. 1960. Imperfect markets through lack of knowledge. Quart. J. Econom. 74 29--52.) advertising models with linear or quadratic costs, and the production learning curve (Hirschmann, W. P. 1964. Profit from the learning curve. Harvard Bus. Rev. 42 (January--February) 125--139; The Boston Consulting Group. 1972. Perspectives on Experience. The Boston Consulting Group, Boston.). In the monopoly case (n = 1), the optimal advertising function is derived by applying Green's theorem. In the duopoly (n = 2) and triopoly (n = 3) cases we use discrete differential game models, and find Nash equilibrium solutions. In each of these models the form of the optimal policy is easy to find, but because of the complicated nature of the resulting differential equations, closed form solutions for the optimal state and control trajectories are impossible to find. Hence we use a computer to compute these optimal trajectories and plot them for various parameter settings. Because 13n parameters must be chosen to define a model with n players, a complete search of the parameter space is clearly impossible. We content ourselves in this paper with presenting computer plots of four different interesting encounters of the triopoly model. Our methods can be extended to work just as well for competitive encounters among n players, where 1 \le n \le 10. We believe that in this paper we have opened up the way to studying oligopoly theory with a small number of participants and under widely varying conditions. Although the lack of closed form solutions may disappoint some readers, we feel that the easy availability of graphical solutions is a more than adequate substitute.

Suggested Citation

  • Jinn-Tsair Teng & Gerald L. Thompson, 1983. "Oligopoly Models for Optimal Advertising When Production Costs Obey a Learning Curve," Management Science, INFORMS, vol. 29(9), pages 1087-1101, September.
  • Handle: RePEc:inm:ormnsc:v:29:y:1983:i:9:p:1087-1101

    Download full text from publisher

    File URL:
    Download Restriction: no


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Kouvelis, Panagiotis & Mukhopadhyay, Samar K., 1995. "The effects of learning on the firm's optimal design quality path," European Journal of Operational Research, Elsevier, vol. 84(2), pages 235-249, July.
    2. Dung Nguyen & Lei Shi, 2006. "Competitive Advertising Strategies and Market-Size Dynamics: A Research Note on Theory and Evidence," Management Science, INFORMS, vol. 52(6), pages 965-973, June.
    3. Erickson, Gary M., 1995. "Differential game models of advertising competition," European Journal of Operational Research, Elsevier, vol. 83(3), pages 431-438, June.
    4. Fred M. Feinberg, 2001. "On Continuous-Time Optimal Advertising Under S-Shaped Response," Management Science, INFORMS, vol. 47(11), pages 1476-1487, November.
    5. Trichy V. Krishnan & Dipak C. Jain, 2006. "Optimal Dynamic Advertising Policy for New Products," Management Science, INFORMS, vol. 52(12), pages 1957-1969, December.
    6. Mesak, Hani I. & Bari, Abdullahel & Babin, Barry J. & Birou, Laura M. & Jurkus, Anthony, 2011. "Optimum advertising policy over time for subscriber service innovations in the presence of service cost learning and customers' disadoption," European Journal of Operational Research, Elsevier, vol. 211(3), pages 642-649, June.
    7. Teng, Jinn-Tsair & Thompson, Gerald L., 1996. "Optimal strategies for general price-quality decision models of new products with learning production costs," European Journal of Operational Research, Elsevier, vol. 93(3), pages 476-489, September.
    8. Swami, Sanjeev & Dutta, Arindam, 2010. "Advertising strategies for new product diffusion in emerging markets: Propositions and analysis," European Journal of Operational Research, Elsevier, vol. 204(3), pages 648-661, August.
    9. repec:spr:annopr:v:261:y:2018:i:1:d:10.1007_s10479-017-2610-4 is not listed on IDEAS
    10. Erickson, Gary M., 2009. "An oligopoly model of dynamic advertising competition," European Journal of Operational Research, Elsevier, vol. 197(1), pages 374-388, August.
    11. Nair, Anand & Narasimhan, Ram, 2006. "Dynamics of competing with quality- and advertising-based goodwill," European Journal of Operational Research, Elsevier, vol. 175(1), pages 462-474, November.
    12. Prasad A. Naik & Ashutosh Prasad & Suresh P. Sethi, 2008. "Building Brand Awareness in Dynamic Oligopoly Markets," Management Science, INFORMS, vol. 54(1), pages 129-138, January.
    13. Jun, Duk B. & Kim, Seon K. & Park, Yoon S. & Park, Myoung H. & Wilson, Amy R., 2002. "Forecasting telecommunication service subscribers in substitutive and competitive environments," International Journal of Forecasting, Elsevier, vol. 18(4), pages 561-581.
    14. Teng, Jinn-Tsair & Chern, Maw-Sheng & Kim, Ki-Hee, 2001. "Entry strategies for multinational enterprises and host countries," European Journal of Operational Research, Elsevier, vol. 133(1), pages 62-68, August.
    15. Teng, Jinn-Tsair & Lou, Kuo-Ren & Wang, Lu, 2014. "Optimal trade credit and lot size policies in economic production quantity models with learning curve production costs," International Journal of Production Economics, Elsevier, vol. 155(C), pages 318-323.


    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:inm:ormnsc:v:29:y:1983:i:9:p:1087-1101. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.