IDEAS home Printed from https://ideas.repec.org/p/keo/dpaper/2020-020.html
   My bibliography  Save this paper

Efficiency and resistance to extinction of lottery-based incentives in human: Survey response behavior in 12-week real-world field experiment

Author

Listed:
  • Satoshi Nakano

    (R&D Division, INTAGE Inc.)

  • Ryo Kato

    (Research Institute for Economics and Business Administration, Kobe University)

  • Makito Takeuchi

    (Faculty of Business Administration, Tohoku Gakuin University)

  • Takahiro Hoshino

    (Department of Economics, Keio University)

Abstract

This study aims to improve survey response behavior by including schedules of reinforcement with financial incentives in a 12-week real-world field experiment. We found that lottery based-incentives produce more resistance to extinction and are also more cost-efficient than fixed honorariums, despite having the same expectations. We also found that immediate reinforcement and the high chance, low prize incentives reduce underreporting bias. In addition, we confirmed the resistance to extinction when switching incentives and sustained responses due to lottery-based incentives. Moreover, we evaluated the past reward winning experience and the habit of past responses, and found that experience influenced subsequent survey responses. Thus, participants' responses are dependent on incentive programs.

Suggested Citation

  • Satoshi Nakano & Ryo Kato & Makito Takeuchi & Takahiro Hoshino, 2020. "Efficiency and resistance to extinction of lottery-based incentives in human: Survey response behavior in 12-week real-world field experiment," Keio-IES Discussion Paper Series 2020-020, Institute for Economics Studies, Keio University.
    • Handle: RePEc:keo:dpaper:2020-020
    as

    Download full text from publisher

    File URL: http://ies.keio.ac.jp/upload/pdf/en/DP2020-020.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Resistance to extinction; Financial incentive; Underreporting bias; Schedule of reinforcement; Survey response;
    All these keywords.

    JEL classification:

    • D10 - Microeconomics - - Household Behavior - - - General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    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:keo:dpaper:2020-020. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Institute for Economics Studies, Keio University (email available below). General contact details of provider: https://edirc.repec.org/data/iekeijp.html .

    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.