IDEAS home Printed from https://ideas.repec.org/a/eee/jeborg/v194y2022icp24-40.html
   My bibliography  Save this article

Being in the right place: A natural field experiment on the causes of position effects in individual choice

Author

Listed:
  • Harris, Mark N.
  • Novarese, Marco
  • Wilson, Chris M.

Abstract

This paper aims to better understand why individuals tend to select items at the top of lists. Within a natural field experiment, we randomize the order in which new economics research papers are presented in email alerts and measure the subsequent download activity. Our novel disaggregate data allows us to evidence i) how position effects vary across users, ii) the order in which users select their items, and iii) how position effects are related to users’ selection orders. Overall, the findings are most consistent with an explanation of choice fatigue where users consider the listed items in a downwards-then-upwards order.

Suggested Citation

  • Harris, Mark N. & Novarese, Marco & Wilson, Chris M., 2022. "Being in the right place: A natural field experiment on the causes of position effects in individual choice," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 24-40.
    • Handle: RePEc:eee:jeborg:v:194:y:2022:i:c:p:24-40
    DOI: 10.1016/j.jebo.2021.12.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S016726812100514X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jebo.2021.12.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Susan Athey & Glenn Ellison, 2011. "Position Auctions with Consumer Search," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(3), pages 1213-1270.
    2. 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.
    3. Alexandre Cornière & Greg Taylor, 2014. "Integration and search engine bias," RAND Journal of Economics, RAND Corporation, vol. 45(3), pages 576-597, September.
    4. Mark Armstrong, 2017. "Ordered Consumer Search," Journal of the European Economic Association, European Economic Association, vol. 15(5), pages 989-1024.
    5. Raluca M. Ursu & Daria Dzyabura, 2020. "Retailers’ product location problem with consumer search," Quantitative Marketing and Economics (QME), Springer, vol. 18(2), pages 125-154, June.
    6. Babur De los Santos & Sergei Koulayev, 2017. "Optimizing Click-Through in Online Rankings with Endogenous Search Refinement," Marketing Science, INFORMS, vol. 36(4), pages 542-564, July.
    7. Marco Haan & S. Dijkstra & Peter Dijkstra, 2005. "Expert Judgment Versus Public Opinion – Evidence from the Eurovision Song Contest," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 29(1), pages 59-78, February.
    8. Heiko Jacobs & Alexander Hillert, 2016. "Alphabetic Bias, Investor Recognition, and Trading Behavior," Review of Finance, European Finance Association, vol. 20(2), pages 693-723.
    9. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    10. Ned Augenblick & Scott Nicholson, 2016. "Ballot Position, Choice Fatigue, and Voter Behaviour," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(2), pages 460-480.
    11. Andrew Caplin & Mark Dean & Daniel Martin, 2011. "Search and Satisficing," American Economic Review, American Economic Association, vol. 101(7), pages 2899-2922, December.
    12. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    13. Michael R. Baye & Babur De los Santos & Matthijs R. Wildenbeest, 2016. "Search Engine Optimization: What Drives Organic Traffic to Retail Sites?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 25(1), pages 6-31, March.
    14. Lee Pinkowitz, 2002. "Research Dissemination and Impact: Evidence from Web Site Downloads," Journal of Finance, American Finance Association, vol. 57(1), pages 485-499, February.
    15. Eran Dayan & Maya Bar-Hillel, 2011. "Nudge to nobesity II: Menu positions influence food orders," Discussion Paper Series dp581, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    16. 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.
    17. Michael Dinerstein & Liran Einav & Jonathan Levin & Neel Sundaresan, 2018. "Consumer Price Search and Platform Design in Internet Commerce," American Economic Review, American Economic Association, vol. 108(7), pages 1820-1859, July.
    18. Glenn Ellison & Alexander Wolitzky, 2012. "A search cost model of obfuscation," RAND Journal of Economics, RAND Corporation, vol. 43(3), pages 417-441, September.
    19. Tom Coupé & Victor Ginsburgh & Abdul Noury, 2010. "Are leading papers of better quality? Evidence from a natural experiment," Oxford Economic Papers, Oxford University Press, vol. 62(1), pages 1-11, January.
    20. Sergei Koulayev, 2014. "Search for differentiated products: identification and estimation," RAND Journal of Economics, RAND Corporation, vol. 45(3), pages 553-575, September.
    21. Sridhar Narayanan & Kirthi Kalyanam, 2015. "Position Effects in Search Advertising and their Moderators: A Regression Discontinuity Approach," Marketing Science, INFORMS, vol. 34(3), pages 388-407, May.
    22. Fishman, Arthur & Lubensky, Dmitry, 2018. "Search prominence and return costs," International Journal of Industrial Organization, Elsevier, vol. 58(C), pages 136-161.
    23. Jennifer Itzkowitz & Jesse Itzkowitz & Scott Rothbort, 2016. "ABCs of Trading: Behavioral Biases affect Stock Turnover and Value," Review of Finance, European Finance Association, vol. 20(2), pages 663-692.
    24. Jonathan Levav & Mark Heitmann & Andreas Herrmann & Sheena S. Iyengar, 2010. "Order in Product Customization Decisions: Evidence from Field Experiments," Journal of Political Economy, University of Chicago Press, vol. 118(2), pages 274-299, April.
    25. Baye, Michael R. & De los Santos, Babur & Wildenbeest, Matthijs R., 2016. "What’s in a name? Measuring prominence and its impact on organic traffic from search engines," Information Economics and Policy, Elsevier, vol. 34(C), pages 44-57.
    26. Greene, William, 2010. "Testing hypotheses about interaction terms in nonlinear models," Economics Letters, Elsevier, vol. 107(2), pages 291-296, May.
    27. repec:cup:judgdm:v:6:y:2011:i:4:p:333-342 is not listed on IDEAS
    28. Maarten Janssen & Alexei Parakhonyak, 2014. "Consumer search markets with costly revisits," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 55(2), pages 481-514, February.
    29. Yuval Salant, 2011. "Procedural Analysis of Choice Rules with Applications to Bounded Rationality," American Economic Review, American Economic Association, vol. 101(2), pages 724-748, April.
    30. Ryan C. McDevitt, 2014. ""A" Business by Any Other Name: Firm Name Choice as a Signal of Firm Quality," Journal of Political Economy, University of Chicago Press, vol. 122(4), pages 909-944.
    31. Daniel Feenberg & Ina Ganguli & Patrick Gaulé & Jonathan Gruber, 2017. "It’s Good to Be First: Order Bias in Reading and Citing NBER Working Papers," The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 32-39, March.
    32. Przemyslaw Jeziorski & Ilya Segal, 2015. "What Makes Them Click: Empirical Analysis of Consumer Demand for Search Advertising," American Economic Journal: Microeconomics, American Economic Association, vol. 7(3), pages 24-53, August.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Novarese, Marco & Wilson, Chris M., 2013. "Being in the Right Place: A Natural Field Experiment on List Position and Consumer Choice," MPRA Paper 48074, University Library of Munich, Germany.
    3. Raluca M. Ursu & Qianyun Zhang & Elisabeth Honka, 2023. "Search Gaps and Consumer Fatigue," Marketing Science, INFORMS, vol. 42(1), pages 110-136, January.
    4. Huang, Yangguang & Xie, Yu, 2023. "Search algorithm, repetitive information, and sales on online platforms," International Journal of Industrial Organization, Elsevier, vol. 88(C).
    5. Mark Armstrong, 2017. "Ordered Consumer Search," Journal of the European Economic Association, European Economic Association, vol. 15(5), pages 989-1024.
    6. Hana Choi & Carl F. Mela, 2019. "Monetizing Online Marketplaces," Marketing Science, INFORMS, vol. 38(6), pages 948-972, November.
    7. Rafael P. Greminger, 2022. "Optimal Search and Discovery," Management Science, INFORMS, vol. 68(5), pages 3904-3924, May.
    8. Helmers, Christian & Krishnan, Pramila & Patnam, Manasa, 2019. "Attention and saliency on the internet: Evidence from an online recommendation system," Journal of Economic Behavior & Organization, Elsevier, vol. 161(C), pages 216-242.
    9. Raluca M. Ursu & Daria Dzyabura, 2020. "Retailers’ product location problem with consumer search," Quantitative Marketing and Economics (QME), Springer, vol. 18(2), pages 125-154, June.
    10. Rafael P. Greminger, 2022. "Heterogeneous Position Effects and the Power of Rankings," Papers 2210.16408, arXiv.org, revised Dec 2023.
    11. Jiarui Liu, 2021. "Sequential Search Models: A Pairwise Maximum Rank Approach," Papers 2104.13865, arXiv.org, revised Nov 2021.
    12. Yangguang Huang, 2021. "Search Algorithm and Sales on Online Platforms: Evidence from Food Delivery Platforms," HKUST CEP Working Papers Series 202101, HKUST Center for Economic Policy.
    13. Chen Jin & Luyi Yang & Kartik Hosanagar, 2023. "To Brush or Not to Brush: Product Rankings, Consumer Search, and Fake Orders," Information Systems Research, INFORMS, vol. 34(2), pages 532-552, June.
    14. Kris J. Ferreira & Sunanda Parthasarathy & Shreyas Sekar, 2022. "Learning to Rank an Assortment of Products," Management Science, INFORMS, vol. 68(3), pages 1828-1848, March.
    15. Ajzenman, Nicolás & Elacqua, Gregory & Marotta, Luana & Westh Olsen, Anne Sofie, 2021. "Order Effects and Employment Decisions: Experimental Evidence from a Nationwide Program," IDB Publications (Working Papers) 11541, Inter-American Development Bank.
    16. Wei Zhou & Zidong Wang, 2020. "Competing for Search Traffic in Query Markets: Entry Strategy, Platform Design, and Entrepreneurship," Working Papers 20-12, NET Institute.
    17. Giovanni Compiani & Gregory Lewis & Sida Peng & Peichun Wang, 2024. "Online Search and Optimal Product Rankings: An Empirical Framework," Marketing Science, INFORMS, vol. 43(3), pages 615-636, May.
    18. Hunold, Matthias & Kesler, Reinhold & Laitenberger, Ulrich, 2018. "Hotel rankings of online travel agents, channel pricing, and consumer protection," ZEW Discussion Papers 18-059, ZEW - Leibniz Centre for European Economic Research.
    19. Aishwarya Deep Shukla & Guodong (Gordon) Gao & Ritu Agarwal, 2021. "How Digital Word-of-Mouth Affects Consumer Decision Making: Evidence from Doctor Appointment Booking," Management Science, INFORMS, vol. 67(3), pages 1546-1568, March.
    20. Andrey Simonov & Shawndra Hill, 2021. "Competitive Advertising on Brand Search: Traffic Stealing and Click Quality," Marketing Science, INFORMS, vol. 40(5), pages 923-945, September.

    More about this item

    Keywords

    Position effect; Order effect; Choice fatigue; Prominence; Lists;
    All these keywords.

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L00 - Industrial Organization - - General - - - General

    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:eee:jeborg:v:194:y:2022:i:c:p:24-40. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jebo .

    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.