Scheduling Advertising on Cable Television

被引:0
|
作者
Souyris, Sebastian [1 ]
Seshadri, Sridhar [2 ]
Subramanian, Sriram [3 ]
机构
[1] Rensselaer Polytech Inst, Lally Sch Management, Troy, NY 12180 USA
[2] Univ Illinois, Gies Coll Business, Champaign, IL 61820 USA
[3] Pinterest, New York, NY 10018 USA
关键词
scheduling; revenue management; analytics; machine learning; advertising; television-business; OPTIMIZATION;
D O I
10.1287/opre.2022.2430
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Advertisement scheduling is a daily essential operational process in the television business. Efficient distribution of viewers among advertisers allows the television network to satisfy contracts and increase ad sale revenues. Ad scheduling is a challenging multiperiod, mixed-integer programming problem in which the network must create schedules to meet advertisers' campaign goals and maximize ad revenues. Each campaign must meet a specific target group of viewers and a unique set of constraints. Moreover, the number of viewers is uncertain. To solve this problem, we develop and implement a practical approach that combines mathematical programming and machine learning to create daily schedules. These schedules are of high quality according to standard business metrics and the small integer programming gap. Leading networks in the United States and India using our methods experience a 3%-5% revenue increase.
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页码:2217 / 2231
页数:16
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