Building Brand Awareness in Dynamic Oligopoly Markets

Published Online:https://doi.org/10.1287/mnsc.1070.0755

References

  • Akasie J. F. Ford's Model E. Forbes (2000) July 17):30–34Google Scholar
  • Bass F. M., Bruce N., Majumdar S., Murthi B. P. S. Wearout effects of different advertising themes: A dynamic Bayesian model of the advertising-sales relationship. Marketing Sci. (2007) 26(2):179–195LinkGoogle Scholar
  • Batra R., Lehmann D., Burke J., Pae J. When does advertising have an impact? A study of tracking data. J. Advertising Res. (1995) 35(5):19–32Google Scholar
  • Blattberg R., Golanty J. TRACKER: An early test market forecasting and diagnostic model for new product planning. J. Marketing Res. (1978) 15(2):192–202CrossrefGoogle Scholar
  • Chintagunta P. K., Jain D. C. Empirical analysis of a dynamic duopoly model of competition. J. Econom. Management Strategy (1995) 4:109–131CrossrefGoogle Scholar
  • Chintagunta P. K., Vilcassim N. An empirical investigation of advertising strategies in a dynamic duopoly. Management Sci. (1992) 38(9):1230–1244LinkGoogle Scholar
  • Dekimpe M., Franses P. H., Hanssens M., Naik P., Wierenga B. Time series models in marketing. Handbook of Marketing Decision Models (2007) . ForthcomingGoogle Scholar
  • Dockner E. J., Jorgensen S. New product advertising in dynamic oligopolies. Zeitschrift fur Oper. Res. (1992) 36:459–473Google Scholar
  • Dockner E. J., Jorgensen S., Van Long N., Sorger G.Differential Games in Economics and Management Science (2000) (Cambridge University Press, Cambridge, UK) CrossrefGoogle Scholar
  • Dodson J. A., Muller E. Models of new product diffusion through advertising and word of mouth. Management Sci. (1978) 24(11):1568–1578LinkGoogle Scholar
  • Erickson G. M. Empirical analysis of closed-loop duopoly advertising strategies. Management Sci. (1992) 38(5):1732–1749LinkGoogle Scholar
  • Erickson G. M. Advertising strategies in a dynamic oligopoly. J. Marketing Res. (1995) 32(2):233–237CrossrefGoogle Scholar
  • Erickson G. M.Dynamic Models of Advertising Competition (2003) 2nd ed.(Kluwer, Norwell, MA) CrossrefGoogle Scholar
  • Feichtinger G., Hartl R. F., Sethi S. P. Dynamic optimal control models in advertising: Recent developments. Management Sci. (1994) 40(2):195–226LinkGoogle Scholar
  • Fershtman C. Goodwill and market shares in oligopoly. Economica (1984) 51(23):271–281CrossrefGoogle Scholar
  • Fruchter G. The many-player advertising game. Management Sci. (1999) 45(11):1609–1611LinkGoogle Scholar
  • Fruchter G., Kalish S. Closed-loop advertising strategies in a duopoly. Management Sci. (1997) 43(1):54–63LinkGoogle Scholar
  • Harvey A. C.Forecasting, Structural Time Series Models and the Kalman Filter (1994) (Cambridge University Press, New York) Google Scholar
  • Jones J. P.What's in a Name: Advertising and the Concept of Brands (1986) (D. C. Heath and Company, Lexington, MA) Google Scholar
  • Jones J. P. Ad spending: Maintaining market share. Harvard Bus. Rev. (1990) 68(1):38–42Google Scholar
  • Jorgensen S., Zaccour G.Differential Games in Marketing (2004) (Kluwer, Norwell, MA) CrossrefGoogle Scholar
  • Keller K.Strategic Brand Management (2002) 2nd ed.(Prentice Hall, Upper Saddle River, NJ) Google Scholar
  • Lilien G., Kotler P., Moorthy K. S.Marketing Models (1992) (Prentice-Hall, Englewood Cliffs, NJ) Google Scholar
  • Luati A., Tassinari G. Intervention analysis to identify significant exposures in pulsing advertising campaigns: An operative procedure. Computational Management Sci. (2005) 2(4):295–308CrossrefGoogle Scholar
  • Mahajan V., Muller E., Sharma S. An empirical comparison of awareness forecasting models of new product introduction. Marketing Sci. (1984) 3(3):179–197LinkGoogle Scholar
  • McQuarie A., Tsai C.-L.Regression and Time Series Model Selection (1998) (World Scientific, Singapore) CrossrefGoogle Scholar
  • Naik P., Raman K. Understanding the impact of synergy in multimedia communications. J. Marketing Res. (2003) 40(4):375–388CrossrefGoogle Scholar
  • Naik P., Mantrala M. K., Sawyer A. Planning media schedules in the presence of dynamic advertising quality. Marketing Sci. (1998) 17(3):214–235LinkGoogle Scholar
  • Naik P., Raman K., Winer R. Planning marketing-mix strategies in the presence of interactions. Marketing Sci. (2005) 24(1):25–34LinkGoogle Scholar
  • Naik P., Shi P., Tsai C.-L. Extending the akaike information criterion to mixture regression models. J. Amer. Statist. Assoc. (2007) 102:244–254CrossrefGoogle Scholar
  • Pauwels K. How dynamic consumer response, competitor response, company support, and company inertia shape long-term marketing effectiveness. Marketing Sci. (2004) 23(4):596–610LinkGoogle Scholar
  • Prasad A., Sethi S. P. Advertising under uncertainty: A stochastic differential game approach. J. Optim. Theory Appl. (2004) 123(1):163–185CrossrefGoogle Scholar
  • Rossiter J., Percy L.Advertising Communications and Promotions Management (1997) 2nd ed.(McGraw Hill, New York) Google Scholar
  • Sethi S. P. Deterministic and stochastic optimization of a dynamic advertising model. Optimal Control Appl. Methods (1983) 4:179–184CrossrefGoogle Scholar
  • Sethi S. P., Thompson G. L.Optimal Control Theory: Applications to Management Science and Economics (2000) (Kluwer, Norwell, MA) Google Scholar
  • Sheth J., Sisodia R.The Rule of Three: Surviving and Thriving in Competitive Markets (2002) (Free Press, New York) Google Scholar
  • Sorger G. Competitive dynamic advertising: A modification of the case game. J. Econom. Dynam. Control (1989) 13:55–80CrossrefGoogle Scholar
  • Sutherland M.Advertising and the Mind of the Consumer (1993) (Allen and Unwin Pty. Ltd., Sydney, Australia) Google Scholar
  • Tellis G.Effective Advertising (2004) (Sage Publications, Thousand Oaks, CA) Google Scholar
  • Teng J.-T., Thompson G. L. Oligopoly models for optimal advertising when production costs obey a learning curve. Management Sci. (1983) 29(9):1087–1101LinkGoogle Scholar
  • Vakratsas D., Feinberg F. M., Bass F., Kalyanaram G. The shape of advertising response functions revisited: A model of dynamic probabilistic thresholds. Marketing Sci. (2004) 23(1):109–119LinkGoogle Scholar
  • White H. Maximum likelihood estimation of misspecified models. Econometrica (1982) 50(1):1–25CrossrefGoogle Scholar
  • Xie J., Song M., Sirbu M., Wang Q. Kalman filter estimation of new product diffusion models. J. Marketing Res. (1997) 34(3):378–393CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.