IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v52y2006i12p1957-1969.html
   My bibliography  Save this article

Optimal Dynamic Advertising Policy for New Products

Author

Listed:
  • Trichy V. Krishnan

    (Department of Marketing, NUS Business School, National University of Singapore, Singapore 117592)

  • Dipak C. Jain

    (Kellogg School of Management, Northwestern University, Evanston, Illinois 60208)

Abstract

Advertising is one of the key marketing tools managers have at their disposal to influence their customers into purchasing a new product. The overall objective of new product advertising is to inform and persuade customers. Drawing up an advertising plan for a new product that is under the influence of diffusion phenomenon is not an easy task. Hence, research in this area is very limited. In our research, we use an empirically proven diffusion demand function that explicitly incorporates the advertising component. Our results suggest that optimal advertising is determined by the advertising effectiveness, discount rate, and the ratio of advertisement to profits. Depending upon the interplay among these factors, the optimal advertising takes decrease-increase, increase-decrease, monotonically increasing or monotonically decreasing shape.

Suggested Citation

  • Trichy V. Krishnan & Dipak C. Jain, 2006. "Optimal Dynamic Advertising Policy for New Products," Management Science, INFORMS, vol. 52(12), pages 1957-1969, December.
    • Handle: RePEc:inm:ormnsc:v:52:y:2006:i:12:p:1957-1969
    DOI: 10.1287/mnsc.1060.0585
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.1060.0585
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.1060.0585?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
    ---><---

    References listed on IDEAS

    as
    1. Engelbert Dockner & Steffen Jørgensen, 1988. "Optimal Advertising Policies for Diffusion Models of New Product Innovation in Monopolistic Situations," Management Science, INFORMS, vol. 34(1), pages 119-130, January.
    2. Dan Horsky & Leonard S. Simon, 1983. "Advertising and the Diffusion of New Products," Marketing Science, INFORMS, vol. 2(1), pages 1-17.
    3. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    4. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    5. Dan Horsky, 1990. "A Diffusion Model Incorporating Product Benefits, Price, Income and Information," Marketing Science, INFORMS, vol. 9(4), pages 342-365.
    6. Demetrios Vakratsas & Fred M. Feinberg & Frank M. Bass & Gurumurthy Kalyanaram, 2004. "The Shape of Advertising Response Functions Revisited: A Model of Dynamic Probabilistic Thresholds," Marketing Science, INFORMS, vol. 23(1), pages 109-119, April.
    7. Trichy V. Krishnan & Frank M. Bass & Dipak C. Jain, 1999. "Optimal Pricing Strategy for New Products," Management Science, INFORMS, vol. 45(12), pages 1650-1663, December.
    8. Gerald L. Thompson & Jinn-Tsair Teng, 1984. "Optimal Pricing and Advertising Policies for New Product Oligopoly Models," Marketing Science, INFORMS, vol. 3(2), pages 148-168.
    9. Hartl, Richard F., 1987. "A simple proof of the monotonicity of the state trajectories in autonomous control problems," Journal of Economic Theory, Elsevier, vol. 41(1), pages 211-215, February.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Hongmin Li & Woonghee Tim Huh, 2012. "Optimal pricing for a short life‐cycle product when customer price‐sensitivity varies over time," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(7), pages 552-576, October.
    2. Ghobadi, Somayeh Najafi- & Bagherinejad, Jafar & Taleizadeh, Ata Allah, 2021. "A two-generation new product model by considering forward-looking customers: Dynamic pricing and advertising optimization," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    3. Yan, Xiaoming & Liu, Ke, 2009. "Optimal control problems for a new product with word-of-mouth," International Journal of Production Economics, Elsevier, vol. 119(2), pages 402-414, June.
    4. Daekook Kang, 2021. "Box-office forecasting in Korea using search trend data: a modified generalized Bass diffusion model," Electronic Commerce Research, Springer, vol. 21(1), pages 41-72, March.
    5. Giovanni Modanese, 2023. "The Network Bass Model with Behavioral Compartments," Stats, MDPI, vol. 6(2), pages 1-13, March.
    6. Zhengrui Jiang & Dipak C. Jain, 2012. "A Generalized Norton-Bass Model for Multigeneration Diffusion," Management Science, INFORMS, vol. 58(10), pages 1887-1897, October.
    7. Vahideh Sadat Abedi & Oded Berman & Dmitry Krass, 2014. "Supporting New Product or Service Introductions: Location, Marketing, and Word of Mouth," Operations Research, INFORMS, vol. 62(5), pages 994-1013, October.
    8. Zhen, Xueping & (George) Cai, Gangshu & Song, Reo & Jang, Sungha, 2019. "The effects of herding and word of mouth in a two-period advertising signaling model," European Journal of Operational Research, Elsevier, vol. 275(1), pages 361-373.
    9. Ramírez-Hassan, Andrés & Montoya-Blandón, Santiago, 2020. "Forecasting from others’ experience: Bayesian estimation of the generalized Bass model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 442-465.
    10. Kato, Ryo & Hoshino, Takahiro, 2021. "Unplanned purchase of new products," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    11. Alicia Barroso & Gerard Llobet, 2011. "Advertising and Consumer Awareness of New, Differentiated Products," Working Papers wp2011_1104, CEMFI.
    12. Helmes, Kurt & Schlosser, Rainer & Weber, Martin, 2013. "Optimal advertising and pricing in a class of general new-product adoption models," European Journal of Operational Research, Elsevier, vol. 229(2), pages 433-443.
    13. Hariharan, Vijay Ganesh & Talukdar, Debabrata & Kwon, Changhyun, 2015. "Optimal targeting of advertisement for new products with multiple consumer segments," International Journal of Research in Marketing, Elsevier, vol. 32(3), pages 263-271.
    14. Lei Zhou & Yue Qi & Xinshang You, 2023. "Research on Time to Market and Pricing of Platform Products in a Competitive Environment," Sustainability, MDPI, vol. 15(7), pages 1-19, March.
    15. Régis Chenavaz & Sajjad M. Jasimuddin, 2017. "An analytical model of the relationship between product quality and advertising," Post-Print hal-01685892, HAL.
    16. Koray Cosguner & P. B. (Seethu) Seetharaman, 2022. "Dynamic Pricing for New Products Using a Utility-Based Generalization of the Bass Diffusion Model," Management Science, INFORMS, vol. 68(3), pages 1904-1922, March.
    17. 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.
    18. Gila E. Fruchter & Ashutosh Prasad & Christophe Van den Bulte, 2022. "Too Popular, Too Fast: Optimal Advertising and Entry Timing in Markets with Peer Influence," Management Science, INFORMS, vol. 68(6), pages 4725-4741, June.
    19. Fruchter, Gila E. & Van den Bulte, Christophe, 2011. "Why the Generalized Bass Model leads to odd optimal advertising policies," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 218-230.
    20. 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).
    21. Lim, Hyungsoo & Jun, Duk Bin & Hamoudia, Mohsen, 2019. "A choice-based diffusion model for multi-generation and multi-country data," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 163-173.
    22. Vahideh Sadat Abedi & Oded Berman & Fred M. Feinberg & Dmitry Krass, 2022. "Strategic new product media planning under emergent channel substitution and synergy," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2143-2166, May.
    23. Arda Yenipazarli, 2015. "A road map to new product success: warranty, advertisement and price," Annals of Operations Research, Springer, vol. 226(1), pages 669-694, March.

    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. Hariharan, Vijay Ganesh & Talukdar, Debabrata & Kwon, Changhyun, 2015. "Optimal targeting of advertisement for new products with multiple consumer segments," International Journal of Research in Marketing, Elsevier, vol. 32(3), pages 263-271.
    2. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    3. Fruchter, Gila E. & Van den Bulte, Christophe, 2011. "Why the Generalized Bass Model leads to odd optimal advertising policies," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 218-230.
    4. 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.
    5. Barnes, Belinda & Southwell, Darren & Bruce, Sarah & Woodhams, Felicity, 2014. "Additionality, common practice and incentive schemes for the uptake of innovations," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 43-61.
    6. Marius F. Niculescu & Seungjin Whang, 2012. "Research Note ---Codiffusion of Wireless Voice and Data Services: An Empirical Analysis of the Japanese Mobile Telecommunications Market," Information Systems Research, INFORMS, vol. 23(1), pages 260-279, March.
    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. Krishnamoorthy, Anand & Prasad, Ashutosh & Sethi, Suresh P., 2010. "Optimal pricing and advertising in a durable-good duopoly," European Journal of Operational Research, Elsevier, vol. 200(2), pages 486-497, January.
    9. Hongmin Li, 2020. "Optimal Pricing Under Diffusion-Choice Models," Operations Research, INFORMS, vol. 68(1), pages 115-133, January.
    10. Wei-yu Kevin Chiang, 2012. "Supply Chain Dynamics and Channel Efficiency in Durable Product Pricing and Distribution," Manufacturing & Service Operations Management, INFORMS, vol. 14(2), pages 327-343, April.
    11. M. Breton & F. Chauny & G. Zaccour, 1997. "Leader–Follower Dynamic Game of New Product Diffusion," Journal of Optimization Theory and Applications, Springer, vol. 92(1), pages 77-98, January.
    12. M. Berk Ataman & Carl F. Mela & Harald J. van Heerde, 2008. "Building Brands," Marketing Science, INFORMS, vol. 27(6), pages 1036-1054, 11-12.
    13. Liu, John, 2000. "On the dynamics of stochastic diffusion of manufacturing technology," European Journal of Operational Research, Elsevier, vol. 124(3), pages 601-614, August.
    14. Ghobadi, Somayeh Najafi- & Bagherinejad, Jafar & Taleizadeh, Ata Allah, 2021. "A two-generation new product model by considering forward-looking customers: Dynamic pricing and advertising optimization," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    15. Avagyan, Vardan & Esteban-Bravo, Mercedes & Vidal-Sanz, Jose M., 2014. "Licensing radical product innovations to speed up the diffusion," European Journal of Operational Research, Elsevier, vol. 239(2), pages 542-555.
    16. Ferreira, Kevin D. & Lee, Chi-Guhn, 2014. "An integrated two-stage diffusion of innovation model with market segmented learning," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 189-201.
    17. Peter N. Golder & Gerard J. Tellis, 2004. "Growing, Growing, Gone: Cascades, Diffusion, and Turning Points in the Product Life Cycle," Marketing Science, INFORMS, vol. 23(2), pages 207-218, December.
    18. Shun-Chen Niu, 2006. "A Piecewise-Diffusion Model of New-Product Demands," Operations Research, INFORMS, vol. 54(4), pages 678-695, August.
    19. 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.
    20. Arda Yenipazarli, 2015. "A road map to new product success: warranty, advertisement and price," Annals of Operations Research, Springer, vol. 226(1), pages 669-694, March.

    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:inm:ormnsc:v:52:y:2006:i:12:p:1957-1969. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.