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Offensive versus defensive marketing: What is the optimal spending allocation?

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  • Martín-Herrán, Guiomar
  • McQuitty, Shaun
  • Sigué, Simon Pierre

Abstract

This article investigates the optimal spending allocation between offensive and defensive marketing in a dynamic, mature market when two firms are competing for market share. A modified Lanchester model is used to determine Nash stationary feedback strategies that allow the competitors to adjust their marketing expenditures as their market shares evolve over time. The interaction between offensive and defensive marketing activities is an important component of the model. Previous studies have not considered this variable. Our findings suggest that a cost differential between offensive and defensive marketing cannot fully explain resource allocation in a competitive market. Instead, optimal allocation largely depends on the firms' relative positions in the market, their competitive advantages in offensive and defensive marketing, and the costs and effectiveness of these two classes of marketing activities. This article discusses the theoretical and managerial implications.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ijrema:v:29:y:2012:i:2:p:210-219
    DOI: 10.1016/j.ijresmar.2011.10.003
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    References listed on IDEAS

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    2. 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.
    3. Mariusz Górajski & Dominika Machowska, 2017. "Optimal double control problem for a PDE model of goodwill dynamics," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 85(3), pages 425-452, June.
    4. Mian, G. Mujtaba & Sharma, Piyush & Gul, Ferdinand A., 2018. "Investor sentiment and advertising expenditure," International Journal of Research in Marketing, Elsevier, vol. 35(4), pages 611-627.
    5. Wang, Xinyu & Zhang, Yuxing & Zhang, Shuhua, 2024. "Dynamic order allocation in a duopoly hybrid workforce of competition: A machine learning approach," European Journal of Operational Research, Elsevier, vol. 315(2), pages 668-690.
    6. Hanssens, Dominique M. & Wang, Fang & Zhang, Xiao-Ping, 2016. "Performance growth and opportunistic marketing spending," International Journal of Research in Marketing, Elsevier, vol. 33(4), pages 711-724.
    7. Shu He & Huaxia Rui & Andrew B. Whinston, 2018. "Social Media Strategies in Product-Harm Crises," Information Systems Research, INFORMS, vol. 29(2), pages 362-380, June.
    8. Steffen Jørgensen & Simon-Pierre Sigué, 2015. "Defensive, Offensive, and Generic Advertising in a Lanchester Model with Market Growth," Dynamic Games and Applications, Springer, vol. 5(4), pages 523-539, December.
    9. Pietro De Giovanni, 2016. "Coordination in a distribution channel with decisions on the nature of incentives and share-dependency on pricing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(8), pages 1034-1049, August.
    10. Mariusz Górajski & Dominika Machowska, 2019. "How do loyalty programs affect goodwill? An optimal control approach," 4OR, Springer, vol. 17(3), pages 297-316, September.
    11. 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.

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