DocumentCode
2466413
Title
An iterative auction model for digital signage network scheduling
Author
Salimi, Payman ; Wang, Chun
Author_Institution
Concordia Inst. for Inf. Syst. Eng., Concordia Univ., Montreal, QC, Canada
fYear
2012
fDate
14-17 Oct. 2012
Firstpage
826
Lastpage
831
Abstract
Digital signage network (DSN) is capable of delivering customized content to designated screens in a real-time or near real-time manner, which provides tremendous potential for building dynamic demand stimulation tools. However current DSN media buying process is mainly carried out through manually conducted negotiation between the DSN operator and the advertisers. This practice does not capitalize the unique technology advantage offered by the newly emerged advertising medium. In this paper, we propose automated DSN media buying models which allow advertisers to customize their promotion schedules in a highly responsive manner. Specifically, we design an iterative bidding model for DSN promotion scheduling. We develop a lower bound that guarantees the solution quality given a small price increment at each round of bidding. Through computational studies, we also evaluate the impact of scheduling customization levels on the overall solution value and the revenue performance of the proposed model.
Keywords
advertising; electronic commerce; pricing; scheduling; tendering; DSN promotion scheduling; automated DSN media buying models; customized content delivery; digital signage network scheduling; iterative auction model; iterative bidding model; revenue performance; solution value; Advertising; Aggregates; Computational modeling; Media; Processor scheduling; Schedules; Scheduling; auction-based scheduling; customization; digital signage network; promotion management;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location
Seoul
Print_ISBN
978-1-4673-1713-9
Electronic_ISBN
978-1-4673-1712-2
Type
conf
DOI
10.1109/ICSMC.2012.6377830
Filename
6377830
Link To Document