SavedAdd your journal

Journals / An International Journal of Optimization and Control: Theories & Applications (IJOCTA) / 2013 / Cilt: 3 - Sayı: 1

Application of a mathematical model to an advertisement reservation problem

Ozlem COSGUN
Ilkay GULTAS
Mehmet N SERARSLAN
Pages
23–33
Publication Date
2022-10-11
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This approach has been implemented to a case taken from one of the biggest TV networks of Turkey.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Television networks provide TV programs free of charge to the public.
📊
Key Findings & Data:However, they acquire their revenue by telecasting advertisements in the midst of continuing programs or shows.
💡
Conclusion & Impact:This approach has been implemented to a case taken from one of the biggest TV networks of Turkey.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Television networks provide TV programs free of charge to the public. However, they acquire their revenue by telecasting advertisements in the midst of continuing programs or shows. A key problem faced by the TV networks in Turkey is how to accept and televise the advertisements reserved by a client on a specified advertisement break which we called "Advertisement Reservation Problem" (ARP). The problem is complicated by limited time inventory, by different rating points for different target groups, competition avoidance and the relationship between TV networks and clients. In this study we have developed a mathematical model for advertisement reservation problem and extended this model for some cases encountered in real business life. We have also discussed how these cases affect the decisions of a TV network. Mixed integer linear programming approach is proposed to solve these problems. This approach has been implemented to a case taken from one of the biggest TV networks of Turkey.

🔖

Cite This Article

COSGUN, O., GULTAS, I., SERARSLAN, M. N. (2022). Application of a mathematical model to an advertisement reservation problem. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), Cilt: 3 - Sayı: 1, 23–33. https://ajindex.com/articles/440738

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (18)

  1. Zhang, X., Mathematical Models for the Television Advertising Allocation Problem. IJOR, 1(3), 302-322 (2006)
  2. Alvarado, C., Revenue Management for the Inventory Optimization of Television Azteca. Television Azteca external communication document (2007
  3. Bollapragada, S., Mallik, H. M., Managing On-air Ad Inventory in Broadcast TV. IIE Transactions, 40 (12), 1107-1123 (2008)
  4. Bollapragada, S., Cheng, H., Phillips, M., Garbiras, M., NBC's optimization systems increase revenues and productivity. Interfaces, 32 (1), 47-60 (2002)
  5. Bollapragada, S., Garbiras, M., Scheduling commercials on broadcast television. Operations Research, 53 (3), 337-345 (2004)
  6. Kimms, A., Muller-Bungart, M., Revenue management for broadcasting commercials: the channel's problem of selecting and scheduling the advertisements to be aired. Int. J. of Revenue Management, 1(1), 28 - 44 (2007)
  7. Metheringham, R.A., Measuring the Net Cumulative Coverage of a Print Campaign. J. of Advertising Research, 4, 23-28 (1964)
  8. Kanetkar, V., Weinberg, C.B., Price Sensitivity and Television Advertising Exposures: Some Empirical Findings. Marketing Science, 11(4), 359-371 (1992)
  9. Lodish, L.M., Abraham, M., Kalmenson, S., Livelsberger, J., Lubetkin, B., Richardson, B., Stevens, M.E., How TV Advertising Works: A Meta-Analysis of 389 Real World Cable TV Advertising Experiments. J. of Marketing Research, 32, 125-139 (1995)
  10. Hairong, L., Advertising media, http://www.admedia.org (2005). Accessed November (2011
  11. Riorden, J., An Introduction to Combinatorial Analysis, John Wiley, New York (1958)
  12. Lee, A.M., Burkart, A.J., Some optimization problems in advertising media planning. Operational Research Quarterly, 11, 113- 122 (1960)
  13. Day, R.L., Linear programming in media selection. J. of Advertising Research, 2, 40- 44 (1962)
  14. Engel, J.F., Warshaw, M.R., Allocating advertising dollars by linear programming. J. of Advertising Research, 4, 42-48 (1964)
  15. Stasch, S.F., Linear programming and space-time considerations in media selection. J. of Advertising Research, 5, 40- 46 (1965)
  16. Brown, D.B., Warshaw, M., Media selection by linear programming. J. of Marketing Research, 2, 83-88 (1965)
  17. Little, J.D.C., Lodish, L.M., A media selection model and its optimization by dynamic programming. Industrial Management Review, 8, 15-23 (1966)
  18. Maffei, R.B., Planning advertising expenditures by dynamic programming methods. Management Technology, 1, 94-