IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v62y2016i4p1145-1164.html
   My bibliography  Save this article

Ad Revenue Optimization in Live Broadcasting

Author

Listed:
  • Dana G. Popescu

    (Department of Technology and Operations Management, INSEAD, Singapore 138676)

  • Pascale Crama

    (Department of Operations Management, Lee Kong Chian School of Business, Singapore Management University, Singapore 178899)

Abstract

In live broadcasting, the break lengths available for commercials are not always fixed and known in advance (e.g., strategic and injury time-outs are of variable duration in live sports transmissions). Broadcasters actively manage their advertising revenue by jointly optimizing sales and scheduling policies. We characterize the optimal dynamic schedule in a simplified setting that incorporates stochastic break durations and advertisement lengths of 15 and 30 seconds. The optimal policy is a “greedy” look-ahead rule that accounts for the remaining number of breaks; in this setting, there is no value to perfect information at the scheduling stage, and hence knowing the duration of all breaks would not change the schedule. We present heuristics to help solve scheduling problems of even greater complexity. The performance of these heuristics under various scenarios is tested by running simulations calibrated using industry data. The simple greedy heuristic is shown to perform well except when revenues are concave in ad length, in which case the look-ahead aspect of the optimal schedule becomes more important. Finally, we recommend ways for broadcasters to balance their portfolio of booked ads by determining the optimal overbooking level and mix of ads as a function of their associated revenues generated and penalties incurred. This paper was accepted by Yossi Aviv, operations management .

Suggested Citation

  • Dana G. Popescu & Pascale Crama, 2016. "Ad Revenue Optimization in Live Broadcasting," Management Science, INFORMS, vol. 62(4), pages 1145-1164, April.
  • Handle: RePEc:inm:ormnsc:v:62:y:2016:i:4:p:1145-1164
    DOI: 10.1287/mnsc.2015.2185
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2015.2185
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.2015.2185?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Juhwen Hwang & Medini R. Singh, 1998. "Optimal Production Policies for Multi-Stage Systems with Setup Costs and Uncertain Capacities," Management Science, INFORMS, vol. 44(9), pages 1279-1294, September.
    2. Wascher, Gerhard & Hau[ss]ner, Heike & Schumann, Holger, 2007. "An improved typology of cutting and packing problems," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1109-1130, December.
    3. Alf Kimms & Michael Muller-Bungart, 2007. "Revenue management for broadcasting commercials: the channel's problem of selecting and scheduling the advertisements to be aired," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 1(1), pages 28-44.
    4. P. C. Gilmore & R. E. Gomory, 1961. "A Linear Programming Approach to the Cutting-Stock Problem," Operations Research, INFORMS, vol. 9(6), pages 849-859, December.
    5. Kannapha Amaruchkul & William L. Cooper & Diwakar Gupta, 2007. "Single-Leg Air-Cargo Revenue Management," Transportation Science, INFORMS, vol. 41(4), pages 457-469, November.
    6. Srinivas Bollapragada & Michael R. Bussieck & Suman Mallik, 2004. "Scheduling Commercial Videotapes in Broadcast Television," Operations Research, INFORMS, vol. 52(5), pages 679-689, October.
    7. Dan Zhang & William L. Cooper, 2005. "Revenue Management for Parallel Flights with Customer-Choice Behavior," Operations Research, INFORMS, vol. 53(3), pages 415-431, June.
    8. Yunzeng Wang & Yigal Gerchak, 1996. "Periodic Review Production Models with Variable Capacity, Random Yield, and Uncertain Demand," Management Science, INFORMS, vol. 42(1), pages 130-137, January.
    9. Abraham Grosfeld-Nir & Yigal Gerchak, 2004. "Multiple Lotsizing in Production to Order with Random Yields: Review of Recent Advances," Annals of Operations Research, Springer, vol. 126(1), pages 43-69, February.
    10. Do Ba Khang & Okitsugu Fujiwara, 2000. "Optimality of Myopic Ordering Policies for Inventory Model with Stochastic Supply," Operations Research, INFORMS, vol. 48(1), pages 181-184, February.
    11. Xiaoqiang Cai & Xianyi Wu & Xian Zhou, 2009. "Stochastic Scheduling Subject to Preemptive-Repeat Breakdowns with Incomplete Information," Operations Research, INFORMS, vol. 57(5), pages 1236-1249, October.
    12. Brian Tomlin, 2009. "Impact of Supply Learning When Suppliers Are Unreliable," Manufacturing & Service Operations Management, INFORMS, vol. 11(2), pages 192-209, August.
    13. Srinivas Bollapragada & Marc Garbiras, 2004. "Scheduling Commercials on Broadcast Television," Operations Research, INFORMS, vol. 52(3), pages 337-345, June.
    14. Candace Arai Yano & Hau L. Lee, 1995. "Lot Sizing with Random Yields: A Review," Operations Research, INFORMS, vol. 43(2), pages 311-334, April.
    15. Frank W. Ciarallo & Ramakrishna Akella & Thomas E. Morton, 1994. "A Periodic Review, Production Planning Model with Uncertain Capacity and Uncertain Demand---Optimality of Extended Myopic Policies," Management Science, INFORMS, vol. 40(3), pages 320-332, March.
    16. P. C. Gilmore & R. E. Gomory, 1965. "Multistage Cutting Stock Problems of Two and More Dimensions," Operations Research, INFORMS, vol. 13(1), pages 94-120, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sermpinis, Georgios & Stasinakis, Charalampos & Hassanniakalager, Arman, 2017. "Reverse adaptive krill herd locally weighted support vector regression for forecasting and trading exchange traded funds," European Journal of Operational Research, Elsevier, vol. 263(2), pages 540-558.
    2. Bert De Reyck & Ioannis Fragkos & Yael Grushka-Cockayne & Casey Lichtendahl & Hammond Guerin & Andrew Kritzer, 2017. "Vungle Inc. Improves Monetization Using Big Data Analytics," Interfaces, INFORMS, vol. 47(5), pages 454-466, October.
    3. Shinjini Pandey & Goutam Dutta & Harit Joshi, 2017. "Survey on Revenue Management in Media and Broadcasting," Interfaces, INFORMS, vol. 47(3), pages 195-213, June.
    4. José Antonio Carbajal & Wes Chaar, 2017. "Turner Optimizes the Allocation of Audience Deficiency Units," Interfaces, INFORMS, vol. 47(6), pages 518-536, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gel, Esma S. & Salman, F. Sibel, 2022. "Dynamic ordering decisions with approximate learning of supply yield uncertainty," International Journal of Production Economics, Elsevier, vol. 243(C).
    2. Qi Feng & J. George Shanthikumar, 2018. "Supply and Demand Functions in Inventory Models," Operations Research, INFORMS, vol. 66(1), pages 77-91, 1-2.
    3. Yi Yang & Youhua (Frank) Chen & Yun Zhou, 2014. "Coordinating Inventory Control and Pricing Strategies Under Batch Ordering," Operations Research, INFORMS, vol. 62(1), pages 25-37, February.
    4. Seung Hwan Jung, 2020. "Offshore versus Onshore Sourcing: Quick Response, Random Yield, and Competition," Production and Operations Management, Production and Operations Management Society, vol. 29(3), pages 750-766, March.
    5. Arifoglu, Kenan & Özekici, Süleyman, 2011. "Inventory management with random supply and imperfect information: A hidden Markov model," International Journal of Production Economics, Elsevier, vol. 134(1), pages 123-137, November.
    6. Iida, Tetsuo, 2002. "A non-stationary periodic review production-inventory model with uncertain production capacity and uncertain demand," European Journal of Operational Research, Elsevier, vol. 140(3), pages 670-683, August.
    7. Wu, Meng & Zhu, Stuart X. & Teunter, Ruud H., 2013. "The risk-averse newsvendor problem with random capacity," European Journal of Operational Research, Elsevier, vol. 231(2), pages 328-336.
    8. Wen Chen & Burcu Tan, 2022. "Dynamic procurement from multiple suppliers with random capacities," Annals of Operations Research, Springer, vol. 317(2), pages 509-536, October.
    9. Matthew J. Sobel & Volodymyr Babich, 2012. "Optimality of Myopic Policies for Dynamic Lot-Sizing Problems in Serial Production Lines with Random Yields and Autoregressive Demand," Operations Research, INFORMS, vol. 60(6), pages 1520-1536, December.
    10. Melega, Gislaine Mara & de Araujo, Silvio Alexandre & Jans, Raf, 2018. "Classification and literature review of integrated lot-sizing and cutting stock problems," European Journal of Operational Research, Elsevier, vol. 271(1), pages 1-19.
    11. Y. Boulaksil & J. C. Fransoo & T. Tan, 2017. "Capacity reservation and utilization for a manufacturer with uncertain capacity and demand," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 689-709, July.
    12. Cheong, Taesu & Song, Sang Hwa, 2013. "The value of information on supply risk under random yields," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 60(C), pages 27-38.
    13. Wen-Ya Wang & Diwakar Gupta, 2014. "Nurse Absenteeism and Staffing Strategies for Hospital Inpatient Units," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 439-454, July.
    14. Sierra-Paradinas, María & Soto-Sánchez, Óscar & Alonso-Ayuso, Antonio & Martín-Campo, F. Javier & Gallego, Micael, 2021. "An exact model for a slitting problem in the steel industry," European Journal of Operational Research, Elsevier, vol. 295(1), pages 336-347.
    15. Xu, He & Zuo, Xiaolu & Liu, Zhixue, 2015. "Configuration of flexibility strategies under supply uncertainty," Omega, Elsevier, vol. 51(C), pages 71-82.
    16. Wuttke, David A. & Heese, H. Sebastian, 2018. "Two-dimensional cutting stock problem with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 265(1), pages 303-315.
    17. Furini, Fabio & Malaguti, Enrico & Medina Durán, Rosa & Persiani, Alfredo & Toth, Paolo, 2012. "A column generation heuristic for the two-dimensional two-staged guillotine cutting stock problem with multiple stock size," European Journal of Operational Research, Elsevier, vol. 218(1), pages 251-260.
    18. Delorme, Maxence & Iori, Manuel & Martello, Silvano, 2016. "Bin packing and cutting stock problems: Mathematical models and exact algorithms," European Journal of Operational Research, Elsevier, vol. 255(1), pages 1-20.
    19. José Antonio Carbajal & Wes Chaar, 2017. "Turner Optimizes the Allocation of Audience Deficiency Units," Interfaces, INFORMS, vol. 47(6), pages 518-536, December.
    20. Asli Sencer Erdem & Mehmet Murat Fadilog̃lu & Süleyman Özekici, 2006. "An EOQ model with multiple suppliers and random capacity," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(1), pages 101-114, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:62:y:2016:i:4:p:1145-1164. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.