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A day without a search engine: an experimental study of online and offline searches

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  • Yan Chen
  • Grace Jeon
  • Yong-Mi Kim

Abstract

With the evolution of the Web and development of web-based search engines, online searching has become a common method for obtaining information. Given this popularity, the question arises as to how much time people save by using search engines for their information needs compared to offline sources, as well as how online searching affects both search experiences and search outcomes. Using a random sample of queries from a major search engine and a sample of reference questions from the Internet Public Library (IPL), we conduct a real-effort experiment to compare online and offline search experiences and outcomes. We find that participants are significantly more likely to find an answer on the Web (100 %), compared to offline searching (between 87 % and 90 %). Restricting our analysis to the set of questions in which participants find answers in both treatments, a Web search takes on average 7 (9) minutes, whereas the corresponding offline search takes 22 (19) minutes for a search-engine (IPL) question. Furthermore, while raters judge library sources to be significantly more trustworthy and authoritative than the corresponding Web sources, they judge Web sources as significantly more relevant. Balancing all factors, we find that the overall source quality is not significantly different between the two treatments for the set of search-engine questions. However, for IPL questions, we find that non-Web sources are judged to have significantly higher overall quality than the corresponding Web sources. In comparison, for factual questions, Web search results are significantly more likely to be correct (66 % vs. 43 %). Lastly, post-search questionnaires reveal that participants find online searching more enjoyable than offline searching. Copyright Economic Science Association 2014

Suggested Citation

  • Yan Chen & Grace Jeon & Yong-Mi Kim, 2014. "A day without a search engine: an experimental study of online and offline searches," Experimental Economics, Springer;Economic Science Association, vol. 17(4), pages 512-536, December.
    • Handle: RePEc:kap:expeco:v:17:y:2014:i:4:p:512-536
    DOI: 10.1007/s10683-013-9381-9
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    2. Charles Hulten & Leonard I. Nakamura, 2020. "Expanded GDP for Welfare Measurement in the 21st Century," NBER Chapters, in: Measuring and Accounting for Innovation in the Twenty-First Century, pages 19-59, National Bureau of Economic Research, Inc.
    3. Leonard Nakamura & Jon Samuels & Rachel Soloveichik, 2017. "Measuring the “Free” Digital Economy within the GDP and Productivity Accounts," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2017-03, Economic Statistics Centre of Excellence (ESCoE).
    4. Constantin Mang, 2016. "Market Consequences of ICT Innovations," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 70.
    5. Díaz, Asunción & Gómez, Mar & Molina, Arturo, 2017. "A comparison of online and offline consumer behaviour: An empirical study on a cinema shopping context," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 44-50.
    6. Charles Hulten & Leonard Nakamura, 2017. "Accounting for Growth in the Age of the Internet: The Importance of Output-Saving Technical Change," NBER Working Papers 23315, National Bureau of Economic Research, Inc.
    7. Ariel Goldszmidt & John A. List & Robert D. Metcalfe & Ian Muir & V. Kerry Smith & Jenny Wang, 2020. "The Value of Time in the United States: Estimates from Nationwide Natural Field Experiments," NBER Working Papers 28208, National Bureau of Economic Research, Inc.
    8. Leonard Nakamura & Jon Samuels & Rachel Soloveichik, 2016. "Valuing Free Media in GDP: An Experimental Approach," BEA Working Papers 0133, Bureau of Economic Analysis.
    9. Zhenjie Wang & Chunling Zhu & Shanwu Tian & Ping Li, 2019. "Differentiation and pricing power of online retailers," Frontiers of Business Research in China, Springer, vol. 13(1), pages 1-20, December.
    10. Sang Kim Tran, 2017. "GOOGLE: a reflection of culture, leader, and management," International Journal of Corporate Social Responsibility, Springer, vol. 2(1), pages 1-14, December.
    11. Konrad Grabiszewski & Alex Horenstein, 2022. "Profiling dynamic decision-makers," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-22, April.
    12. Tebbe, Eva & Wegener, Benjamin, 2022. "Is natural language processing the cheap charlie of analyzing cheap talk? A horse race between classifiers on experimental communication data," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 96(C).
    13. Arnold, René & Taş, Serpil, 2019. "The value of rich interaction applications for Vietnam: Final report," Study Series, WIK Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH, number 251547.
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    More about this item

    Keywords

    Search; Productivity; Experiment; C93; H41;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods

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