IDEAS home Printed from https://ideas.repec.org/a/kap/expeco/v20y2017i3d10.1007_s10683-016-9501-4.html
   My bibliography  Save this article

Intolerable nuisances: some laboratory evidence on survivor curve shapes

Author

Listed:
  • Ciril Bosch-Rosa

    (Colegio Universitario de Estudios Financieros
    Technische Universität Berlin)

  • Christina Aperjis

    (Power Auctions)

  • Daniel Friedman

    (University of California Santa Cruz)

  • Bernardo A. Huberman

    (HP Labs)

Abstract

The fraction of a user population willing to tolerate nuisances of size x is summarized in the survivor curve S(x); its shape is crucial in economic decisions such as pricing and advertising. We report a laboratory experiment that, for the first time, estimates the shape of survivor curves in several different settings. Laboratory subjects engage in a series of six desirable activities, e.g., playing a video game, viewing a chosen video clip, or earning money by answering questions. For each activity and each subject we introduce a chosen level $$x \in [x_{\min }, x_{\max }]$$ x ∈ [ x min , x max ] of a particular nuisance, and the subject chooses whether to tolerate the nuisance or to switch to a bland activity for the remaining time. New non-parametric techniques provide bounds on the empirical survivor curves for each activity. Parametric fits of the classic Weibull distribution provide estimates of the survivor curves’ shapes. The fitted shape parameter depends on the activity and nuisance, but overall the estimated survivor curves tend to be log-convex. An implication, given the model of Aperjis and Huberman (SSRN, doi: 10.2139/ssrn.1672820 , 2011), is that introducing nuisances all at once will generally be more profitable than introducing them gradually.

Suggested Citation

  • Ciril Bosch-Rosa & Christina Aperjis & Daniel Friedman & Bernardo A. Huberman, 2017. "Intolerable nuisances: some laboratory evidence on survivor curve shapes," Experimental Economics, Springer;Economic Science Association, vol. 20(3), pages 601-621, September.
  • Handle: RePEc:kap:expeco:v:20:y:2017:i:3:d:10.1007_s10683-016-9501-4
    DOI: 10.1007/s10683-016-9501-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10683-016-9501-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10683-016-9501-4?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Mark Bagnoli & Ted Bergstrom, 2006. "Log-concave probability and its applications," Studies in Economic Theory, in: Charalambos D. Aliprantis & Rosa L. Matzkin & Daniel L. McFadden & James C. Moore & Nicholas C. Yann (ed.), Rationality and Equilibrium, pages 217-241, Springer.
    2. Johannes Abeler & Armin Falk & Lorenz Goette & David Huffman, 2011. "Reference Points and Effort Provision," American Economic Review, American Economic Association, vol. 101(2), pages 470-492, April.
    3. Chen, Haipeng (Allan) & Levy, Daniel & Ray, Sourav & Bergen, Mark, 2008. "Asymmetric Price Adjustment in the Small," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 55(4), pages 728-737.
    4. Uri Gneezy, 2005. "Deception: The Role of Consequences," American Economic Review, American Economic Association, vol. 95(1), pages 384-394, March.
    5. Botond Kőszegi & Matthew Rabin, 2006. "A Model of Reference-Dependent Preferences," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(4), pages 1133-1165.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Ori Heffetz & John A. List, 2011. "Is the Endowment Effect a Reference Effect?," NBER Working Papers 16715, National Bureau of Economic Research, Inc.
    8. Manel Baucells & Martin Weber & Frank Welfens, 2011. "Reference-Point Formation and Updating," Management Science, INFORMS, vol. 57(3), pages 506-519, March.
    9. Gurumurthy Kalyanaram & Russell S. Winer, 1995. "Empirical Generalizations from Reference Price Research," Marketing Science, INFORMS, vol. 14(3_supplem), pages 161-169.
    10. Gadi Fibich & Arieh Gavious & Oded Lowengart, 2003. "Explicit Solutions of Optimization Models and Differential Games with Nonsmooth (Asymmetric) Reference-Price Effects," Operations Research, INFORMS, vol. 51(5), pages 721-734, October.
    11. Ioana Popescu & Yaozhong Wu, 2007. "Dynamic Pricing Strategies with Reference Effects," Operations Research, INFORMS, vol. 55(3), pages 413-429, June.
    12. Praveen K. Kopalle & Ambar G. Rao & João L. Assunção, 1996. "Asymmetric Reference Price Effects and Dynamic Pricing Policies," Marketing Science, INFORMS, vol. 15(1), pages 60-85.
    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. Meissner, Thomas & Pfeiffer, Philipp, 2022. "Measuring preferences over the temporal resolution of consumption uncertainty," Journal of Economic Theory, Elsevier, vol. 200(C).

    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. Christina Aperjis & Ciril Bosch-Rosa & Daniel Friedman & Bernardo A. Huberman, 2014. "Boiling the frog optimally: nan experiment on survivor curve shapes and internet revenue," SFB 649 Discussion Papers SFB649DP2014-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Colombo, Luca & Labrecciosa, Paola, 2021. "Dynamic oligopoly pricing with reference-price effects," European Journal of Operational Research, Elsevier, vol. 288(3), pages 1006-1016.
    3. Zhenyu Hu & Javad Nasiry, 2018. "Are Markets with Loss-Averse Consumers More Sensitive to Losses?," Management Science, INFORMS, vol. 64(3), pages 1384-1395, March.
    4. Necati Tereyağoğlu & Peter S. Fader & Senthil Veeraraghavan, 2018. "Multiattribute Loss Aversion and Reference Dependence: Evidence from the Performing Arts Industry," Management Science, INFORMS, vol. 64(1), pages 421-436, January.
    5. Zhang, Juan & Gou, Qinglong & Liang, Liang & Huang, Zhimin, 2013. "Supply chain coordination through cooperative advertising with reference price effect," Omega, Elsevier, vol. 41(2), pages 345-353.
    6. Amit Mehra & Sajeesh Sajeesh & Sudhir Voleti, 2020. "Impact of Reference Prices on Product Positioning and Profits," Production and Operations Management, Production and Operations Management Society, vol. 29(4), pages 882-892, April.
    7. Martín-Herrán, Guiomar & Taboubi, Sihem, 2015. "Price coordination in distribution channels: A dynamic perspective," European Journal of Operational Research, Elsevier, vol. 240(2), pages 401-414.
    8. Vincenzina Caputo & Jayson L Lusk & Rodolfo M Nayga, 2020. "Am I Getting a Good Deal? Reference‐DependentDecision Making When the Reference Price Is Uncertain," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 132-153, January.
    9. M. Güler & Taner Bilgiç & Refik Güllü, 2015. "Joint pricing and inventory control for additive demand models with reference effects," Annals of Operations Research, Springer, vol. 226(1), pages 255-276, March.
    10. Xin Chen & Peng Hu & Stephen Shum & Yuhan Zhang, 2016. "Dynamic Stochastic Inventory Management with Reference Price Effects," Operations Research, INFORMS, vol. 64(6), pages 1529-1536, December.
    11. Arnoud V. den Boer & N. Bora Keskin, 2022. "Dynamic Pricing with Demand Learning and Reference Effects," Management Science, INFORMS, vol. 68(10), pages 7112-7130, October.
    12. Zhang, Jie & Chiang, Wei-yu Kevin, 2020. "Durable goods pricing with reference price effects," Omega, Elsevier, vol. 91(C).
    13. Zhang, nan & Qin, Botao, 2020. "Reference point adaptation and air quality – Experimental evidence with anti-PM 2.5 facemasks from China," MPRA Paper 102935, University Library of Munich, Germany.
    14. Javad Nasiry & Ioana Popescu, 2011. "Dynamic Pricing with Loss-Averse Consumers and Peak-End Anchoring," Operations Research, INFORMS, vol. 59(6), pages 1361-1368, December.
    15. Yan, Xiaoming & Zhao, Wenhan & Yu, Yugang, 2022. "Optimal product line design with reference price effects," European Journal of Operational Research, Elsevier, vol. 302(3), pages 1045-1062.
    16. Tarık Kara & Emin Karagözoğlu & Elif Özcan-Tok, 2021. "Bargaining, Reference Points, and Limited Influence," Dynamic Games and Applications, Springer, vol. 11(2), pages 326-362, June.
    17. Ioana Popescu & Yaozhong Wu, 2007. "Dynamic Pricing Strategies with Reference Effects," Operations Research, INFORMS, vol. 55(3), pages 413-429, June.
    18. Aurélien Baillon & Han Bleichrodt & Vitalie Spinu, 2020. "Searching for the Reference Point," Management Science, INFORMS, vol. 66(1), pages 93-112, January.
    19. Régis Chenavaz, 2017. "Dynamic quality policies with reference quality effects," Applied Economics, Taylor & Francis Journals, vol. 49(32), pages 3156-3162, July.
    20. El Ouardighi, Fouad & Feichtinger, Gustav & Grass, Dieter & Hartl, Richard & Kort, Peter M., 2016. "Autonomous and advertising-dependent ‘word of mouth’ under costly dynamic pricing," European Journal of Operational Research, Elsevier, vol. 251(3), pages 860-872.

    More about this item

    Keywords

    Internet monetization; Online advertising; Pricing; Reference points; Adaptation; Laboratory experiment;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms

    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:kap:expeco:v:20:y:2017:i:3:d:10.1007_s10683-016-9501-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.