IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v344y2025i2d10.1007_s10479-023-05578-x.html
   My bibliography  Save this article

Dynamic investment in online advertising of multi-oligopoly competitive enterprises with spillover effect

Author

Listed:
  • Huini Zhou

    (Beijing Institute of Technology
    Yangzhou University)

  • Guo Li

    (Beijing Institute of Technology)

  • Yong Tan

    (Wuhan Polytechnic University)

  • Xu Guan

    (Huazhong University of Science and Technology)

Abstract

This paper aims to provide solutions to the dynamic investment strategies of online advertising for multi-oligopoly enterprises. Specifically, by considering the spillover effect of online advertising, the investment cost function incorporating the characteristics of online advertising is constructed and then combined with external interference factors, and the dynamic investment decision-making model of online advertising of three oligarchic competitive enterprises is constructed. Subsequently, using the Hamilton–Jacobi–Bellman function, the Nash equilibrium solutions of the online advertising amount and profits are attained in symmetrical, semisymmetric, and asymmetric cases. We then calculated and empirically analysed the share of the market. Finally, the model is extended to n-dimensional space. Our study suggests that (1) investment in fixed-location online advertising is inversely proportional to the spillover effect, while the amount of pay-per-click online advertising investment is directly proportional to the spillover effect. (2) In the semisymmetric case, enterprises with a low initial share are easily affected by the spillover effect, while in the semisymmetric and asymmetric cases, dominant enterprises are more easily affected by the spillover effect. (3) The amount of investment in online advertising is inversely proportional to external interference factors. (4) When there are more than three enterprises in the market, the profit is negative, indicating that new enterprise should be cautious about entering the industry.

Suggested Citation

  • Huini Zhou & Guo Li & Yong Tan & Xu Guan, 2025. "Dynamic investment in online advertising of multi-oligopoly competitive enterprises with spillover effect," Annals of Operations Research, Springer, vol. 344(2), pages 1057-1099, January.
  • Handle: RePEc:spr:annopr:v:344:y:2025:i:2:d:10.1007_s10479-023-05578-x
    DOI: 10.1007/s10479-023-05578-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-023-05578-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-023-05578-x?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. N. Amrouche & G. Martín-Herrán & G. Zaccour, 2008. "Pricing and Advertising of Private and National Brands in a Dynamic Marketing Channel," Journal of Optimization Theory and Applications, Springer, vol. 137(3), pages 465-483, June.
    2. A. Prasad & S. P. Sethi, 2004. "Competitive Advertising Under Uncertainty: A Stochastic Differential Game Approach," Journal of Optimization Theory and Applications, Springer, vol. 123(1), pages 163-185, October.
    3. S. A. Ozga, 1960. "Imperfect Markets Through Lack of Knowledge," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 74(1), pages 29-52.
    4. Fei Gao & Gilvan C. Souza, 2022. "Carbon Offsetting with Eco-Conscious Consumers," Management Science, INFORMS, vol. 68(11), pages 7879-7897, November.
    5. Ivanov, Dmitry & Dolgui, Alexandre, 2021. "OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications," International Journal of Production Economics, Elsevier, vol. 232(C).
    6. Mishra, Sita & Malhotra, Gunjan, 2021. "The gamification of in-game advertising: Examining the role of psychological ownership and advertisement intrusiveness," International Journal of Information Management, Elsevier, vol. 61(C).
    7. 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.
    8. Martín-Herrán, Guiomar & McQuitty, Shaun & Sigué, Simon Pierre, 2012. "Offensive versus defensive marketing: What is the optimal spending allocation?," International Journal of Research in Marketing, Elsevier, vol. 29(2), pages 210-219.
    9. David A. Soberman, 2004. "Research Note: Additional Learning and Implications on the Role of Informative Advertising," Management Science, INFORMS, vol. 50(12), pages 1744-1750, December.
    10. Viscolani, Bruno, 2012. "Pure-strategy Nash equilibria in an advertising game with interference," European Journal of Operational Research, Elsevier, vol. 216(3), pages 605-612.
    11. Pradeep K. Chintagunta, 1993. "Investigating the Sensitivity of Equilibrium Profits to Advertising Dynamics and Competitive Effects," Management Science, INFORMS, vol. 39(9), pages 1146-1162, September.
    12. Charles S. Tapiero, 1979. "A Generalization of the Nerlove-Arrow Model to Multi-Firms Advertising under Uncertainty," Management Science, INFORMS, vol. 25(9), pages 907-915, September.
    13. S. P. Sethi & A. Prasad & X. He, 2008. "Optimal Advertising and Pricing in a New-Product Adoption Model," Journal of Optimization Theory and Applications, Springer, vol. 139(2), pages 351-360, November.
    14. Sridhar Moorthy & Shervin Shahrokhi Tehrani, 2023. "Targeting Advertising Spending and Price on the Hotelling Line," Marketing Science, INFORMS, vol. 42(6), pages 1057-1079, November.
    15. Dirk Bergemann & Alessandro Bonatti, 2011. "Targeting in advertising markets: implications for offline versus online media," RAND Journal of Economics, RAND Corporation, vol. 42(3), pages 417-443, September.
    16. Frank M. Bass & Norris Bruce & Sumit Majumdar & B. P. S. Murthi, 2007. "Wearout Effects of Different Advertising Themes: A Dynamic Bayesian Model of the Advertising-Sales Relationship," Marketing Science, INFORMS, vol. 26(2), pages 179-195, 03-04.
    17. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2018. "Ripple effect in the supply chain: an analysis and recent literature," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 414-430, January.
    18. F. Gozzi & C. Marinelli & S. Savin, 2009. "On Controlled Linear Diffusions with Delay in a Model of Optimal Advertising under Uncertainty with Memory Effects," Journal of Optimization Theory and Applications, Springer, vol. 142(2), pages 291-321, August.
    19. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    20. Bernd Skiera & Nadia Abou Nabout, 2013. "Practice Prize Paper ---PROSAD: A Bidding Decision Support System for Profit Optimizing Search Engine Advertising," Marketing Science, INFORMS, vol. 32(2), pages 213-220, March.
    21. M. L. Vidale & H. B. Wolfe, 1957. "An Operations-Research Study of Sales Response to Advertising," Operations Research, INFORMS, vol. 5(3), pages 370-381, June.
    22. Erickson, Gary M., 2009. "An oligopoly model of dynamic advertising competition," European Journal of Operational Research, Elsevier, vol. 197(1), pages 374-388, August.
    23. Dan Horsky & Leonard S. Simon, 1983. "Advertising and the Diffusion of New Products," Marketing Science, INFORMS, vol. 2(1), pages 1-17.
    24. Kang, Yuxiao & Mao, Shuhua & Zhang, Yonghong, 2022. "Fractional time-varying grey traffic flow model based on viscoelastic fluid and its application," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 149-174.
    25. Shaofu Du & Jiaang Zhu & Huifang Jiao & Wuyi Ye, 2015. "Game-theoretical analysis for supply chain with consumer preference to low carbon," International Journal of Production Research, Taylor & Francis Journals, vol. 53(12), pages 3753-3768, June.
    26. Jalil Heidary Dahooie & Mehrdad Estiri & Mahshid Janmohammadi & Edmundas Kazimieras Zavadskas & Zenonas Turskis, 2022. "A novel advertising media selection framework for online games in an intuitionistic fuzzy environment," Oeconomia Copernicana, Institute of Economic Research, vol. 13(1), pages 109-150, March.
    27. 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.
    28. Raghav Singal & Omar Besbes & Antoine Desir & Vineet Goyal & Garud Iyengar, 2022. "Shapley Meets Uniform: An Axiomatic Framework for Attribution in Online Advertising," Management Science, INFORMS, vol. 68(10), pages 7457-7479, October.
    29. Dmitry Ivanov & Alexandre Dolgui, 2020. "Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak," International Journal of Production Research, Taylor & Francis Journals, vol. 58(10), pages 2904-2915, May.
    30. Sorger, Gerhard, 1989. "Competitive dynamic advertising : A modification of the Case game," Journal of Economic Dynamics and Control, Elsevier, vol. 13(1), pages 55-80, January.
    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. 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.
    2. Yanwu Yang & Baozhu Feng & Joni Salminen & Bernard J. Jansen, 2022. "Optimal advertising for a generalized Vidale–Wolfe response model," Electronic Commerce Research, Springer, vol. 22(4), pages 1275-1305, December.
    3. 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.
    4. S. P. Sethi & A. Prasad & X. He, 2008. "Optimal Advertising and Pricing in a New-Product Adoption Model," Journal of Optimization Theory and Applications, Springer, vol. 139(2), pages 351-360, November.
    5. Dengpan Liu & Subodha Kumar & Vijay S. Mookerjee, 2012. "Advertising Strategies in Electronic Retailing: A Differential Games Approach," Information Systems Research, INFORMS, vol. 23(3-part-2), pages 903-917, September.
    6. Anshuman Chutani & Suresh Sethi, 2012. "Cooperative Advertising in a Dynamic Retail Market Oligopoly," Dynamic Games and Applications, Springer, vol. 2(4), pages 347-375, December.
    7. Mohammad Kazem Sayadi & Ahmad Makui, 2014. "Feedback Nash Equilibrium for Dynamic Brand and Channel Advertising in Dual Channel Supply Chain," Journal of Optimization Theory and Applications, Springer, vol. 161(3), pages 1012-1021, June.
    8. Dengpan Liu & Subodha Kumar & Vijay S. Mookerjee, 2020. "Flexible and Committed Advertising Contracts in Electronic Retailing," Information Systems Research, INFORMS, vol. 31(2), pages 323-339, June.
    9. Gary M. Erickson, 2009. "Advertising Competition in a Dynamic Oligopoly with Multiple Brands," Operations Research, INFORMS, vol. 57(5), pages 1106-1113, October.
    10. Guidolin, Mariangela & Guseo, Renato, 2015. "Technological change in the U.S. music industry: Within-product, cross-product and churn effects between competing blockbusters," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 35-46.
    11. Machowska Dominika, 2018. "Investigating the role of customer churn in the optimal allocation of offensive and defensive advertising: the case of the competitive growing market," Economics and Business Review, Sciendo, vol. 4(2), pages 3-23, June.
    12. Aust, Gerhard & Buscher, Udo, 2014. "Cooperative advertising models in supply chain management: A review," European Journal of Operational Research, Elsevier, vol. 234(1), pages 1-14.
    13. Peng, Yifeng & Tao, Xiangyang & Hong, Jingke & Sun, Lulu & Yuan, Xin, 2024. "Understanding the optimal strategy of carbon labelled product advertising delivery: A dynamic differential equation analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    14. Frank M. Bass & Anand Krishnamoorthy & Ashutosh Prasad & Suresh P. Sethi, 2005. "Generic and Brand Advertising Strategies in a Dynamic Duopoly," Marketing Science, INFORMS, vol. 24(4), pages 556-568, February.
    15. Burgos, Diana & Ivanov, Dmitry, 2021. "Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    16. Chang, Shuhua & Zhang, Zhaowei & Wang, Xinyu & Dong, Yan, 2020. "Optimal acquisition and retention strategies in a duopoly model of competition," European Journal of Operational Research, Elsevier, vol. 282(2), pages 677-695.
    17. Erickson, Gary M., 1995. "Differential game models of advertising competition," European Journal of Operational Research, Elsevier, vol. 83(3), pages 431-438, June.
    18. Tarek Ben Rhouma & Georges Zaccour, 2018. "Optimal Marketing Strategies for the Acquisition and Retention of Service Subscriber," Management Science, INFORMS, vol. 64(6), pages 2609-2627, June.
    19. Jørgensen, Steffen & Zaccour, Georges, 2014. "A survey of game-theoretic models of cooperative advertising," European Journal of Operational Research, Elsevier, vol. 237(1), pages 1-14.
    20. Brusset, Xavier & Ivanov, Dmitry & Jebali, Aida & La Torre, Davide & Repetto, Marco, 2023. "A dynamic approach to supply chain reconfiguration and ripple effect analysis in an epidemic," International Journal of Production Economics, Elsevier, vol. 263(C).

    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:spr:annopr:v:344:y:2025:i:2:d:10.1007_s10479-023-05578-x. 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.springer.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.