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Modeling Advertisers' Willingness to Pay in TV Commercial Slot Auctions

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  • Shi, Yang
  • Zhao, Ying

Abstract

Auctions are receiving increasing attention from both practitioners and researchers in the TV advertising market. This paper studies advertisers' willingness to pay (WTP) in Hong Kong television commercial slot auctions, defined as overlapped, multiple-winner auctions with discrete, ascending, semi-sealed bids. We specify advertisers' WTP as a parametric function of their valuations of slot-specific attributes and the valuations that depend on the context of the focal auction and on the competition from other auctions of similar commercial slots. We extend the two “no-regret” bidding principles (first proposed by Haile and Tamer 2003) to obtain informative boundary conditions for asymptotical identification. The estimation results suggest that advertisers' WTP increases with the TV rating of the program in which the advertisement is embedded and decreases with the bidder's bidding experience and the number of similar slot options available. The WTP also depends on the number of bidders classified into the same product category, as two directly competing advertisers are not allowed to advertise in the same commercial break. In the current practice, advertisers submit discrete bids using price levels set by the TV station. Based on the recovered bidder's WTP, we investigate how the TV station can set adjacent price levels and examine the resulting revenue implications.

Suggested Citation

  • Shi, Yang & Zhao, Ying, 2019. "Modeling Advertisers' Willingness to Pay in TV Commercial Slot Auctions," Journal of Interactive Marketing, Elsevier, vol. 48(C), pages 120-133.
    • Handle: RePEc:eee:joinma:v:48:y:2019:i:c:p:120-133
    DOI: 10.1016/j.intmar.2019.05.005
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    References listed on IDEAS

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    1. Edward Clarke, 1971. "Multipart pricing of public goods," Public Choice, Springer, vol. 11(1), pages 17-33, September.
    2. Kenneth C. Wilbur & Linli Xu & David Kempe, 2013. "Correcting Audience Externalities in Television Advertising," Marketing Science, INFORMS, vol. 32(6), pages 892-912, November.
    3. Kannan Srinivasan & Xin Wang, 2010. "Commentary--Bidders' Experience and Learning in Online Auctions: Issues and Implications," Marketing Science, INFORMS, vol. 29(6), pages 988-993, 11-12.
    4. Tanjim Hossain, 2008. "Learning by bidding," RAND Journal of Economics, RAND Corporation, vol. 39(2), pages 509-529, June.
    5. Srinivas Bollapragada & Michael R. Bussieck & Suman Mallik, 2004. "Scheduling Commercial Videotapes in Broadcast Television," Operations Research, INFORMS, vol. 52(5), pages 679-689, October.
    6. Philip A. Haile & Elie Tamer, 2003. "Inference with an Incomplete Model of English Auctions," Journal of Political Economy, University of Chicago Press, vol. 111(1), pages 1-51, February.
    7. J. Scott Long & Jeremy Freese, 2006. "Regression Models for Categorical Dependent Variables using Stata, 2nd Edition," Stata Press books, StataCorp LLC, edition 2, number long2, March.
    8. Bajari, Patrick & Hortacsu, Ali, 2003. "The Winner's Curse, Reserve Prices, and Endogenous Entry: Empirical Insights from eBay Auctions," RAND Journal of Economics, The RAND Corporation, vol. 34(2), pages 329-355, Summer.
    9. Paulo B. Goes & Gilbert G. Karuga & Arvind K. Tripathi, 2010. "Understanding Willingness-to-Pay Formation of Repeat Bidders in Sequential Online Auctions," Information Systems Research, INFORMS, vol. 21(4), pages 907-924, December.
    10. Bharat N. Anand & Ron Shachar, 2011. "Advertising, the matchmaker," RAND Journal of Economics, RAND Corporation, vol. 42(2), pages 205-245, June.
    11. Srinivas Bollapragada & Hong Cheng & Mary Phillips & Marc Garbiras & Michael Scholes & Tim Gibbs & Mark Humphreville, 2002. "NBC's Optimization Systems Increase Revenues and Productivity," Interfaces, INFORMS, vol. 32(1), pages 47-60, February.
    12. Milgrom, Paul R & Weber, Robert J, 1982. "A Theory of Auctions and Competitive Bidding," Econometrica, Econometric Society, vol. 50(5), pages 1089-1122, September.
    13. Srinivas Bollapragada & Marc Garbiras, 2004. "Scheduling Commercials on Broadcast Television," Operations Research, INFORMS, vol. 52(3), pages 337-345, June.
    14. Ali Hortaçsu & David McAdams, 2018. "Empirical Work on Auctions of Multiple Objects," Journal of Economic Literature, American Economic Association, vol. 56(1), pages 157-184, March.
    15. Song Yao & Carl F. Mela, 2008. "Online Auction Demand," Marketing Science, INFORMS, vol. 27(5), pages 861-885, 09-10.
    16. Joni L. Jones & Gary J. Koehler, 2005. "A Heuristic for Winner Determination in Rule-Based Combinatorial Auctions," INFORMS Journal on Computing, INFORMS, vol. 17(4), pages 475-489, November.
    17. Groves, Theodore, 1973. "Incentives in Teams," Econometrica, Econometric Society, vol. 41(4), pages 617-631, July.
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