Integrated Ad Delivery Planning for Targeted Display Advertising

Huaxiao Shen (), Yanzhi Li (), Youhua (Frank) Chen () and Kai Pan ()
Additional contact information
Huaxiao Shen: School of Business, Sun Yat-sen University, Guangzhou 510275, China
Yanzhi Li: College of Business, City University of Hong Kong, Hong Kong, China
Youhua (Frank) Chen: College of Business, City University of Hong Kong, Hong Kong, China
Kai Pan: Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hong Kong, China

Operations Research, 2021, vol. 69, issue 5, 1409-1429

Abstract: Consider a publisher of online display advertising that sells its ad resources in both an up-front market and a spot market. When planning its ad delivery, the publisher needs to make a trade-off between earning a greater short-term profit from the spot market and improving advertising effectiveness in the up-front market. To address this challenge, we propose an integrated planning model that is robust to the uncertainties associated with the supply of advertising resources. Specifically, we model the problem as a distributionally robust chance-constrained program. We first approximate the program by using a robust optimization model, which is then transformed into a linear program. We provide a theoretical bound on the performance loss due to this transformation. A clustering algorithm is proposed to solve large-scale cases in practice. We implement ad serving of our planning model on two real data sets, and we demonstrate how to incorporate realistic constraints such as exclusivity and frequency caps. Our numerical experiments demonstrate that our approach is very effective: it generates more revenue while fulfilling the guaranteed contracts and ensuring advertising effectiveness.

Keywords: marketing: advertising and media; production/scheduling: planning; Operations and Supply Chains; display advertising; ad delivery planning; distributionally robust chance-constrained optimization; targeted advertising (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/opre.2021.2136 (application/pdf)

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:inm:oropre:v:69:y:2021:i:5:p:1409-1429

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().