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Advertising disclosures: Measuring labeling alternatives in internet search engines

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  • Edelman, Benjamin
  • Gilchrist, Duncan S.

Abstract

In an online experiment, we measure users’ interactions with search engines, both in standard configurations and in modified versions with clearer labels identifying search engine advertisements. In particular, for a random subset of users, we change “Sponsored links” or “Ads” labels to instead read “Paid Advertisements.” Relative to users receiving the “Sponsored link” or “Ad” labels, users receiving the “Paid Advertisement” label click 25% and 27% fewer advertisements, respectively. Users seeing “Paid Advertisement” labels also correctly report that they click fewer advertisements, controlling for the number of advertisements they actually click. Results are most pronounced for commercial searches, and for vulnerable users with low education and little online experience.

Suggested Citation

  • Edelman, Benjamin & Gilchrist, Duncan S., 2012. "Advertising disclosures: Measuring labeling alternatives in internet search engines," Information Economics and Policy, Elsevier, vol. 24(1), pages 75-89.
    • Handle: RePEc:eee:iepoli:v:24:y:2012:i:1:p:75-89
    DOI: 10.1016/j.infoecopol.2012.01.003
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    References listed on IDEAS

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    Cited by:

    1. Alexandre de Cornière & Greg Taylor, 2019. "A model of biased intermediation," RAND Journal of Economics, RAND Corporation, vol. 50(4), pages 854-882, December.
    2. Sebastian Schultheiß & Dirk Lewandowski, 2021. "How users' knowledge of advertisements influences their viewing and selection behavior in search engines," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(3), pages 285-301, March.
    3. Navdeep S. Sahni & Harikesh S. Nair, 2020. "Sponsorship Disclosure and Consumer Deception: Experimental Evidence from Native Advertising in Mobile Search," Marketing Science, INFORMS, vol. 39(1), pages 5-32, January.
    4. Weiquan Wang & Jingjun (David) Xu & May Wang, 2018. "Effects of Recommendation Neutrality and Sponsorship Disclosure on Trust vs. Distrust in Online Recommendation Agents: Moderating Role of Explanations for Organic Recommendations," Management Science, INFORMS, vol. 64(11), pages 5198-5219, November.
    5. Engelhardt Sebastian von & Freytag Andreas & Köllmann Volker, 2013. "Wettbewerbspolitischer Handlungsbedarf bei der Verknüpfung von zweiseitigen Märkten im Internet: Der Fall Google," Zeitschrift für Wirtschaftspolitik, De Gruyter, vol. 62(3), pages 311-332, December.

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    Keywords

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    JEL classification:

    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising
    • M38 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Government Policy and Regulation
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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