Combining guaranteed and spot markets in display advertising: Selling guaranteed page views with stochastic demand |
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| Institution: | 1. Adam Smith Business School, University of Glasgow, UK;2. School of Computing Science, University of Glasgow, UK;3. Trinity Business School, Trinity College Dublin, Ireland;4. School of Management, Northwestern Polytechnical University, China;5. School of Computer Science, University of Lincoln, UK;1. Department of Economics and Business, University of Catania, Corso Italia, 55, 95129, Catania, Italy;2. Portsmouth Business School, Centre for Operational Research and Logistics (CORL), University of Portsmouth, Portsmouth, United Kingdom;1. Department of Industrial and Systems Engineering, University of Florida, 303 Weil Hall, Gainesville, FL 32611, USA;2. Department of Industrial Engineering and Management Systems, University of Central Florida, 12800 Pegasus Dr., Orlando, FL 32816, USA;3. Department of Industrial Engineering, University of Pittsburgh, 1048 Benedum Hall, Pittsburgh, PA 15261, USA;1. HEC Liège, Management School of the University of Liège, Liège, Belgium;2. School of Business and Economics, Maastricht University, Maastricht, the Netherlands;1. Isenberg School of Management, University of Massachusetts-Amherst, 90 Campus Center Way, 209A Flint Lab, Amherst, MA 01003, USA;2. Management School, University of Liverpool, L69 7ZH, UK;3. Lancaster University Management School, LA1 4YX, UK |
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| Abstract: | While page views are often sold instantly through real-time auctions when users visit websites, they can also be sold in advance via guaranteed contracts. In this paper, we present a dynamic programming model to study how an online publisher should optimally allocate and price page views between guaranteed and spot markets. The problem is challenging because the allocation and pricing of guaranteed contracts affect how advertisers split their purchases between the two markets, and the terminal value of the model is endogenously determined by the updated dual force of supply and demand in auctions. We take the advertisers’ purchasing behaviour into consideration, i.e., risk aversion and stochastic demand arrivals, and present a scalable and efficient algorithm for the optimal solution. The model is also empirically validated with a commercial dataset. The experimental results show that selling page views via both channels can increase the publisher’s expected total revenue, and the optimal pricing and allocation strategies are robust to different market and advertiser types. |
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