Optimal budget allocation across search advertising markets

Yanwu Yang, Daniel Zeng, Yinghui Yang, Jie Zhang

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


One critical operational decision facing online advertisers when they engage in sponsored search advertising is concerned with the allocation of a limited advertising budget. In particular, dealing with multi-keyword search markets over multiple decision periods poses significant decision-making challenges. In this paper, we develop a novel budget allocation optimization model with multiple search advertising markets and a finite time horizon. One key element of our modeling work is developing a customized advertising response function when considering distinctive features of sponsored search, including the quality score and the dynamic advertising effort. We derive a feasible solution to our budget model and study its properties. Computational experiments are conducted on real-world data to evaluate our budget model and perform parameter sensitivity analysis. Experimental results indicate that our budget allocation strategy significantly outperforms several baseline strategies. In addition, the identified properties derived from the solution process illuminate critical managerial insights for advertisers in sponsored search.

Original languageEnglish (US)
Pages (from-to)285-300
Number of pages16
JournalINFORMS Journal on Computing
Issue number2
StatePublished - Mar 1 2015


  • Budget allocation
  • Budget strategy
  • Search markets
  • Sponsored search

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Computer Science Applications
  • Management Science and Operations Research


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