Optimal keyword bidding in search-based advertising with budget constraint and stochastic ad position
Hande Küçükaydin,
Barış Selçuk and
Özgür Özlük
Journal of the Operational Research Society, 2020, vol. 71, issue 4, 566-578
Abstract:
This paper analyses the search-based advertising problem from an advertiser’s view point, and proposes optimal bid prices for a set of keywords targeted for the advertising campaign. The advertiser aims to maximise its expected potential revenue given a total budget constraint from a search-based advertising campaign. Optimal bid prices are formulated by considering various characteristics of the keywords such that the expected revenue from a keyword is a function of the ad’s position on the search page, and the ad position is a stochastic function of both the bid price and the competitive landscape for that keyword. We explore this problem analytically and numerically in an effort to generate important managerial insights for campaign setters.
Date: 2020
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/01605682.2019.1567650 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tjorxx:v:71:y:2020:i:4:p:566-578
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjor20
DOI: 10.1080/01605682.2019.1567650
Access Statistics for this article
Journal of the Operational Research Society is currently edited by Tom Archibald
More articles in Journal of the Operational Research Society from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().