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Being in the Right Place: A Natural Field Experiment on the Causes of Position Effects in Individual Choice

Author

Listed:
  • Harris, Mark
  • Novarese, Marco
  • Wilson, Chris

Abstract

This paper uses a natural field experiment to better understand why individuals tend to select items at the top of lists. After randomizing the order in which new economics research papers are presented in email alerts and measuring the subsequent downloads, we provide robust evidence of position effects. Moreover, our novel user-level data offers two key findings: i) most users exhibit both top and bottom position effects, and ii) distinct groups of users consider the listed items in different orders. These results allow us to conclude that the causes of top position effects are complex and heterogeneous across individuals, but are most consistent with a version of choice fatigue where users consider the listed items in a non-monotonic order.

Suggested Citation

  • Harris, Mark & Novarese, Marco & Wilson, Chris, 2019. "Being in the Right Place: A Natural Field Experiment on the Causes of Position Effects in Individual Choice," MPRA Paper 94072, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:94072
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    References listed on IDEAS

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    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. Mark Armstrong, 2017. "Ordered Consumer Search," Journal of the European Economic Association, European Economic Association, vol. 15(5), pages 989-1024.
    3. 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.
    4. 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.
    5. Heiko Jacobs & Alexander Hillert, 2016. "Alphabetic Bias, Investor Recognition, and Trading Behavior," Review of Finance, European Finance Association, vol. 20(2), pages 693-723.
    6. 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.
    7. Alexandre Cornière & Greg Taylor, 2014. "Integration and search engine bias," RAND Journal of Economics, RAND Corporation, vol. 45(3), pages 576-597, September.
    8. 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.
    9. Andrew Caplin & Mark Dean & Daniel Martin, 2011. "Search and Satisficing," American Economic Review, American Economic Association, vol. 101(7), pages 2899-2922, December.
    10. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Greene, William, 2010. "Testing hypotheses about interaction terms in nonlinear models," Economics Letters, Elsevier, vol. 107(2), pages 291-296, May.
    16. repec:cup:judgdm:v:6:y:2011:i:4:p:333-342 is not listed on IDEAS
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Glenn Ellison & Alexander Wolitzky, 2012. "A search cost model of obfuscation," RAND Journal of Economics, RAND Corporation, vol. 43(3), pages 417-441, September.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. Sergei Koulayev, 2014. "Search for differentiated products: identification and estimation," RAND Journal of Economics, RAND Corporation, vol. 45(3), pages 553-575, September.
    29. 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.
    30. Fishman, Arthur & Lubensky, Dmitry, 2018. "Search prominence and return costs," International Journal of Industrial Organization, Elsevier, vol. 58(C), pages 136-161.
    31. 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.
    32. 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.
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    More about this item

    Keywords

    Position Effects; Order Effects; 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

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