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Consumer Search Activities and the Value of Ad Positions in Sponsored Search Advertising

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  • Tat Y. Chan

    (Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130)

  • Young-Hoon Park

    (Samuel Curtis Johnson Graduate School of Management, Cornell University, Ithaca, New York 14853)

Abstract

Consumer search activities can be endogenously determined by the ad positions in sponsored search advertising. We model how advertisers compete for ad positions in sponsored listings and, conditional on the list of sponsored ads, how online consumers search for information and make purchase decisions. On the consumer side, assuming that users browse information from top to bottom and adopt a sequential search strategy, we develop a two-stage model of consumer search (whether to click and whether to stop the search) that extends the standard sequential search framework in economics literature. On the advertiser side, it is very difficult to fully specify the optimal strategies of advertisers because the equilibrium outcome depends on variables that researchers do not observe. As we have an incomplete model of advertiser competition, we propose using the necessary condition that, at equilibrium, no advertiser will find another available ad position more valuable than the one it has chosen. Using a data set obtained from a search engine, we find that consumers can be classified into two segments that exhibit distinct search behaviors. For advertisers, the value of search advertising comes primarily from terminal clicks, which represent the last link (including organic results) clicked by an online user. We also demonstrate that the value of ad positions depends not only on the identities and positions of the advertisers in sponsored listings but also the composition of online consumers who exhibit distinct search behaviors.

Suggested Citation

  • Tat Y. Chan & Young-Hoon Park, 2015. "Consumer Search Activities and the Value of Ad Positions in Sponsored Search Advertising," Marketing Science, INFORMS, vol. 34(4), pages 606-623, July.
  • Handle: RePEc:inm:ormksc:v:34:y:2015:i:4:p:606-623
    DOI: 10.1287/mksc.2015.0903
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    Citations

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    Cited by:

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    4. Park, Chang Hee & Agarwal, Manoj K., 2018. "The order effect of advertisers on consumer search behavior in sponsored search markets," Journal of Business Research, Elsevier, vol. 84(C), pages 24-33.
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    6. Leon Yang Chu & Hamid Nazerzadeh & Heng Zhang, 2020. "Position Ranking and Auctions for Online Marketplaces," Management Science, INFORMS, vol. 66(8), pages 3617-3634, August.
    7. Kim, Alex Jiyoung & Jang, Sungha & Shin, Hyun S., 2021. "How should retail advertisers manage multiple keywords in paid search advertising?," Journal of Business Research, Elsevier, vol. 130(C), pages 539-551.
    8. Alison Watts, 2021. "Fairness and Efficiency in Online Advertising Mechanisms," Games, MDPI, vol. 12(2), pages 1-11, April.
    9. Hung, Yu-Chen & Song, Liang & Chao, Chih-Wei (Fred) & Guan, Chong, 2017. "Love at first sight: The effect of presentation order on evaluation of experiential options in luxury tour packages," Journal of Business Research, Elsevier, vol. 81(C), pages 181-191.
    10. Chalil, Tengku Munawar & Dahana, Wirawan Dony & Baumann, Chris, 2020. "How do search ads induce and accelerate conversion? The moderating role of transaction experience and organizational type," Journal of Business Research, Elsevier, vol. 116(C), pages 324-336.
    11. Gibbard, Peter, 2023. "Search with two stages of information acquisition: A structural econometric model of online purchases," Information Economics and Policy, Elsevier, vol. 65(C).
    12. Rafael P. Greminger, 2022. "Heterogeneous Position Effects and the Power of Rankings," Papers 2210.16408, arXiv.org, revised Dec 2023.
    13. Peter Landry, 2021. "Keywords, limited consideration, and organic product listings," Quantitative Marketing and Economics (QME), Springer, vol. 19(3), pages 505-566, December.
    14. Xiangyu Gao & Stefanus Jasin & Sajjad Najafi & Huanan Zhang, 2022. "Joint Learning and Optimization for Multi-Product Pricing (and Ranking) Under a General Cascade Click Model," Management Science, INFORMS, vol. 68(10), pages 7362-7382, October.
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    16. Viswanathan, Madhu & Narasimhan, Om & John, George, 2020. "Economic impact of category captaincy: an examination of assortments and prices," LSE Research Online Documents on Economics 107034, London School of Economics and Political Science, LSE Library.
    17. Carsten D. Schultz, 2020. "The impact of ad positioning in search engine advertising: a multifaceted decision problem," Electronic Commerce Research, Springer, vol. 20(4), pages 945-968, December.
    18. Raluca M. Ursu, 2018. "The Power of Rankings: Quantifying the Effect of Rankings on Online Consumer Search and Purchase Decisions," Marketing Science, INFORMS, vol. 37(4), pages 530-552, August.
    19. Mengzhou Zhuang & Eric (Er) Fang & Jongkuk Lee & Xiaoling Li, 2021. "The Effects of Price Rank on Clicks and Conversions in Product List Advertising on Online Retail Platforms," Information Systems Research, INFORMS, vol. 32(4), pages 1412-1430, December.
    20. Jiang Shen & Bang An & Man Xu & Dan Gan & Ting Pan, 2022. "Internal or External Word-of-Mouth (WOM), Why Do Patients Choose Doctors on Online Medical Services (OMSs) Single Platform in China?," IJERPH, MDPI, vol. 19(20), pages 1-14, October.
    21. Zhenling Jiang & Tat Chan & Hai Che & Youwei Wang, 2021. "Consumer Search and Purchase: An Empirical Investigation of Retargeting Based on Consumer Online Behaviors," Marketing Science, INFORMS, vol. 40(2), pages 219-240, March.
    22. Chunhua Wu, 2015. "Matching Value and Market Design in Online Advertising Networks: An Empirical Analysis," Marketing Science, INFORMS, vol. 34(6), pages 906-921, November.
    23. Yuxin Chen & Song Yao, 2017. "Sequential Search with Refinement: Model and Application with Click-Stream Data," Management Science, INFORMS, vol. 63(12), pages 4345-4365, December.
    24. Peter Gibbard, 2022. "A Model of Search with Two Stages of Information Acquisition and Additive Learning," Management Science, INFORMS, vol. 68(2), pages 1212-1217, February.

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