IDEAS home Printed from https://ideas.repec.org/p/net/wpaper/0923.html
   My bibliography  Save this paper

Testing Models of Consumer Search Using Data on Web Browsing Behavior

Author

Abstract

Using a large data set on consumers' web browsing and purchasing behavior we contrast various classical search models. We find that the benchmark model of sequential search with a known distributions of prices can be rejected based on the recall patterns we observe in the data. Moreover, we show that even if consumers are initially unaware of the price distribution and have to learn the price distribution, observed search behavior for given consumers over time is more consistent with non-sequential search than sequential search with learning. Our findings suggest non-sequential search provides a more accurate description of observed consumer search behavior. We then utilize the non-sequential search model to estimate the price elasticities and markups of online book retailers.

Suggested Citation

  • Babur De los Santos & Ali Hortacsu & Matthijs R. Wildenbeest, 2009. "Testing Models of Consumer Search Using Data on Web Browsing Behavior," Working Papers 09-23, NET Institute, revised Aug 2009.
  • Handle: RePEc:net:wpaper:0923
    as

    Download full text from publisher

    File URL: http://www.netinst.org/DelosSantos_Hortacsu_Wildenbeest_09-23.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rothschild, Michael, 1974. "Searching for the Lowest Price When the Distribution of Prices Is Unknown," Journal of Political Economy, University of Chicago Press, vol. 82(4), pages 689-711, July/Aug..
    2. Chen, Xiaohong & Hong, Han & Shum, Matthew, 2007. "Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models," Journal of Econometrics, Elsevier, vol. 141(1), pages 109-140, November.
    3. Sonnemans, Joep, 1998. "Strategies of search," Journal of Economic Behavior & Organization, Elsevier, vol. 35(3), pages 309-332, April.
    4. J. J. McCall, 1970. "Economics of Information and Job Search," The Quarterly Journal of Economics, Oxford University Press, vol. 84(1), pages 113-126.
    5. Kogut, Carl A., 1990. "Consumer search behavior and sunk costs," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 381-392, December.
    6. Rami Zwick & Amnon Rapoport & Alison King Chung Lo & A. V. Muthukrishnan, 2003. "Consumer Sequential Search: Not Enough or Too Much?," Marketing Science, INFORMS, vol. 22(4), pages 503-519, October.
    7. Reinganum, Jennifer F, 1979. "A Simple Model of Equilibrium Price Dispersion," Journal of Political Economy, University of Chicago Press, vol. 87(4), pages 851-858, August.
    8. Moraga-González, José Luis & Wildenbeest, Matthijs R., 2008. "Maximum likelihood estimation of search costs," European Economic Review, Elsevier, vol. 52(5), pages 820-848, July.
    9. Weitzman, Martin L, 1979. "Optimal Search for the Best Alternative," Econometrica, Econometric Society, vol. 47(3), pages 641-654, May.
    10. R. Manning & P. B. Morgan, 1982. "Search and Consumer Theory," Review of Economic Studies, Oxford University Press, vol. 49(2), pages 203-216.
    11. Chou, Chien-fu & Talmain, Gabriel, 1993. "Nonparametric search," Journal of Economic Dynamics and Control, Elsevier, vol. 17(5-6), pages 771-784.
    12. Harrison, Glenn W & Morgan, Peter, 1990. "Search Intensity in Experiments," Economic Journal, Royal Economic Society, vol. 100(401), pages 478-486, June.
    13. Han Hong & Matthew Shum, 2006. "Using Price Distributions to Estimate Search Costs," RAND Journal of Economics, The RAND Corporation, vol. 37(2), pages 257-275, Summer.
    14. Rosenfield, Donald B. & Shapiro, Roy D., 1981. "Optimal adaptive price search," Journal of Economic Theory, Elsevier, vol. 25(1), pages 1-20, August.
    15. Michael Rothschild, 1974. "Searching for the Lowest Price When the Distribution of Prices Is Unknown: A Summary," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 1, pages 293-294, National Bureau of Economic Research, Inc.
    16. Han Hong & Matthew Shum, 2006. "Using price distributions to estimate search costs," RAND Journal of Economics, RAND Corporation, vol. 37(2), pages 257-275, June.
    17. De los Santos, Babur, 2018. "Consumer search on the Internet," International Journal of Industrial Organization, Elsevier, vol. 58(C), pages 66-105.
    18. Schotter, Andrew & Braunstein, Yale M, 1981. "Economic Search: An Experimental Study," Economic Inquiry, Western Economic Association International, vol. 19(1), pages 1-25, January.
    19. Mortensen, Dale T, 1970. "Job Search, the Duration of Unemployment, and the Phillips Curve," American Economic Review, American Economic Association, vol. 60(5), pages 847-862, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Syngjoo Choi & Lars Nesheim & Imran Rasul, 2010. "Reserve price effects in auctions: estimates from multiple RD designs," CeMMAP working papers CWP30/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Sergei Koulayev, 2009. "Estimating demand in search markets: the case of online hotel bookings," Working Papers 09-16, Federal Reserve Bank of Boston.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Babur De Los Santos & Ali Hortacsu & Matthijs R. Wildenbeest, 2012. "Testing Models of Consumer Search Using Data on Web Browsing and Purchasing Behavior," American Economic Review, American Economic Association, vol. 102(6), pages 2955-2980, October.
    2. repec:smu:ecowpa:1301 is not listed on IDEAS
    3. Babur De los Santos & Ali Hortacsu & Matthijs R. Wildenbeest, 2012. "Search with Learning," Working Papers 2012-03, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    4. Marcu, Emanuel & Noussair, Charles, 2018. "Sequential Search with a Price Freeze Option - Theory and Experimental Evidence," Other publications TiSEM dacf4815-c001-44c3-bda3-f, Tilburg University, School of Economics and Management.
    5. Xing Zhang & Tat Y. Chan & Ying Xie, 2018. "Price Search and Periodic Price Discounts," Management Science, INFORMS, vol. 64(2), pages 495-510, February.
    6. Elisabeth Honka & Pradeep Chintagunta, 2017. "Simultaneous or Sequential? Search Strategies in the U.S. Auto Insurance Industry," Marketing Science, INFORMS, vol. 36(1), pages 21-42, January.
    7. Gerald Häubl & Benedict G. C. Dellaert & Bas Donkers, 2010. "Tunnel Vision: Local Behavioral Influences on Consumer Decisions in Product Search," Marketing Science, INFORMS, vol. 29(3), pages 438-455, 05-06.
    8. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2019. "Modeling Consumer Footprints on Search Engines: An Interplay with Social Media," Management Science, INFORMS, vol. 65(3), pages 1363-1385, March.
    9. Rauh, Michael T., 2009. "Strategic complementarities and search market equilibrium," Games and Economic Behavior, Elsevier, vol. 66(2), pages 959-978, July.
    10. Rafael P. Greminger, 2022. "Optimal Search and Discovery," Management Science, INFORMS, vol. 68(5), pages 3904-3924, May.
    11. DeSarbo, Wayne S. & Choi, Jungwhan, 1998. "A latent structure double hurdle regression model for exploring heterogeneity in consumer search patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 423-455, November.
    12. Dmitry Ryvkin & Danila Serra, 2019. "Is More Competition Always Better? An Experimental Study Of Extortionary Corruption," Economic Inquiry, Western Economic Association International, vol. 57(1), pages 50-72, January.
    13. Xinyu Cao & Yuting Zhu, 2024. "The Power of Commitment in Group Search," Marketing Science, INFORMS, vol. 43(1), pages 213-228, January.
    14. De los Santos, Babur, 2018. "Consumer search on the Internet," International Journal of Industrial Organization, Elsevier, vol. 58(C), pages 66-105.
    15. Jhunjhunwala, Tanushree, 2021. "Searching to avoid regret: An experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 298-319.
    16. Raluca M. Ursu & Qingliang Wang & Pradeep K. Chintagunta, 2020. "Search Duration," Marketing Science, INFORMS, vol. 39(5), pages 849-871, September.
    17. Rauh, Michael T., 1997. "A Model of Temporary Search Market Equilibrium," Journal of Economic Theory, Elsevier, vol. 77(1), pages 128-153, November.
    18. Pantelis P. Analytis & Amit Kothiyal & Konstantinos Katsikopoulos, 2014. "Multi-attribute utility models as cognitive search engines," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(5), pages 403-419, September.
    19. Schunk, Daniel & Winter, Joachim, 2009. "The relationship between risk attitudes and heuristics in search tasks: A laboratory experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 347-360, August.
    20. Matthijs R. Wildenbeest, 2011. "An empirical model of search with vertically differentiated products," RAND Journal of Economics, RAND Corporation, vol. 42(4), pages 729-757, December.
    21. repec:cup:judgdm:v:9:y:2014:i:5:p:403-419 is not listed on IDEAS
    22. Bart J. Bronnenberg & Jun B. Kim & Carl F. Mela, 2016. "Zooming In on Choice: How Do Consumers Search for Cameras Online?," Marketing Science, INFORMS, vol. 35(5), pages 693-712, September.

    More about this item

    Keywords

    search costs; sequential search; fixed-sample search; non-sequential search; online browsing; online book industry; consumer search;
    All these keywords.

    JEL classification:

    • L80 - Industrial Organization - - Industry Studies: Services - - - General
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:net:wpaper:0923. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nicholas Economides (email available below). General contact details of provider: http://www.NETinst.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.