IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1904.06722.html
   My bibliography  Save this paper

Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms

Author

Listed:
  • Snehalkumar

    (Neil)

  • S. Gaikwad
  • Durim Morina
  • Adam Ginzberg
  • Catherine Mullings
  • Shirish Goyal
  • Dilrukshi Gamage
  • Christopher Diemert
  • Mathias Burton
  • Sharon Zhou
  • Mark Whiting
  • Karolina Ziulkoski
  • Alipta Ballav
  • Aaron Gilbee
  • Senadhipathige S. Niranga
  • Vibhor Sehgal
  • Jasmine Lin
  • Leonardy Kristianto
  • Angela Richmond-Fuller
  • Jeff Regino
  • Nalin Chhibber
  • Dinesh Majeti
  • Sachin Sharma
  • Kamila Mananova
  • Dinesh Dhakal
  • William Dai
  • Victoria Purynova
  • Samarth Sandeep
  • Varshine Chandrakanthan
  • Tejas Sarma
  • Sekandar Matin
  • Ahmed Nasser
  • Rohit Nistala
  • Alexander Stolzoff
  • Kristy Milland
  • Vinayak Mathur
  • Rajan Vaish
  • Michael S. Bernstein

Abstract

Paid crowdsourcing platforms suffer from low-quality work and unfair rejections, but paradoxically, most workers and requesters have high reputation scores. These inflated scores, which make high-quality work and workers difficult to find, stem from social pressure to avoid giving negative feedback. We introduce Boomerang, a reputation system for crowdsourcing that elicits more accurate feedback by rebounding the consequences of feedback directly back onto the person who gave it. With Boomerang, requesters find that their highly-rated workers gain earliest access to their future tasks, and workers find tasks from their highly-rated requesters at the top of their task feed. Field experiments verify that Boomerang causes both workers and requesters to provide feedback that is more closely aligned with their private opinions. Inspired by a game-theoretic notion of incentive-compatibility, Boomerang opens opportunities for interaction design to incentivize honest reporting over strategic dishonesty.

Suggested Citation

  • Snehalkumar & S. Gaikwad & Durim Morina & Adam Ginzberg & Catherine Mullings & Shirish Goyal & Dilrukshi Gamage & Christopher Diemert & Mathias Burton & Sharon Zhou & Mark Whiting & Karolina Ziulkoski, 2019. "Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms," Papers 1904.06722, arXiv.org.
    • Handle: RePEc:arx:papers:1904.06722
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1904.06722
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nisan,Noam & Roughgarden,Tim & Tardos,Eva & Vazirani,Vijay V. (ed.), 2007. "Algorithmic Game Theory," Cambridge Books, Cambridge University Press, number 9780521872829.
    2. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    3. Benjamin Edelman & Michael Ostrovsky & Michael Schwarz, 2007. "Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords," American Economic Review, American Economic Association, vol. 97(1), pages 242-259, March.
    4. George A. Akerlof, 1970. "The Market for "Lemons": Quality Uncertainty and the Market Mechanism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 84(3), pages 488-500.
    5. Unknown, 2005. "Internet Advertising and the Generalized Second Price Auction: Selling Billions of Dollars Worth of Keywords," Department of Economics, Working Paper Series qt8w16v26k, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    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. Scott Duke Kominers & Alexander Teytelboym & Vincent P Crawford, 2017. "An invitation to market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 541-571.
    2. Tuo Gladys & Yi Feng & Wang Wenxin & Sarpong Solomon, 2020. "The Second Round Resource Acquisition of Entrepreneurial Crowdfunded Ventures: The Relevance of Campaign and Project Implementation Performance Outcomes," Entrepreneurship Research Journal, De Gruyter, vol. 10(3), pages 1-21, July.
    3. Stefan Bechtold & Catherine Tucker, 2014. "Trademarks, Triggers, and Online Search," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 11(4), pages 718-750, December.
    4. Cristiano Codagnone & Federico Biagi & Fabienne Abadie, 2016. "The Passions and the Interests: Unpacking the ‘Sharing Economy’," JRC Research Reports JRC101279, Joint Research Centre.
    5. Avi Goldfarb, 2014. "What is Different About Online Advertising?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 44(2), pages 115-129, March.
    6. Axel Ockenfels & David Reiley & Abdolkarim Sadrieh, 2006. "Online Auctions," NBER Working Papers 12785, National Bureau of Economic Research, Inc.
    7. Evgenia Christoforou & Antonio Fernández Anta & Agustín Santos, 2016. "A Mechanism for Fair Distribution of Resources without Payments," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-20, May.
    8. Ricardo Buettner, 2017. "Predicting user behavior in electronic markets based on personality-mining in large online social networks," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 247-265, August.
    9. Anton Miglo & Victor Miglo, 2019. "Market imperfections and crowdfunding," Small Business Economics, Springer, vol. 53(1), pages 51-79, June.
    10. Mueller-Frank, Manuel & M. Pai, Mallesh, 2015. "Do Online Social Networks Increase Welfare?," IESE Research Papers D/1118, IESE Business School.
    11. Chen, Yongmin, 2023. "Search and Competition Under Product Quality Uncertainty," MPRA Paper 116609, University Library of Munich, Germany.
    12. Feldman, Michal & Fu, Hu & Gravin, Nick & Lucier, Brendan, 2020. "Simultaneous auctions without complements are (almost) efficient," Games and Economic Behavior, Elsevier, vol. 123(C), pages 327-341.
    13. Yongmin Chen & Chuan He, 2011. "Paid Placement: Advertising and Search on the Internet," Economic Journal, Royal Economic Society, vol. 121(556), pages 309-328, November.
    14. Thomas A. Weber & Zhiqiang (Eric) Zheng, 2007. "A Model of Search Intermediaries and Paid Referrals," Information Systems Research, INFORMS, vol. 18(4), pages 414-436, December.
    15. Ning Chen & Xiaotie Deng & Paul W. Goldberg & Jinshan Zhang, 2016. "On revenue maximization with sharp multi-unit demands," Journal of Combinatorial Optimization, Springer, vol. 31(3), pages 1174-1205, April.
    16. D Laffey & C Hunka & J A Sharp & Z Zeng, 2009. "Estimating advertisers' values for paid search clickthroughs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(3), pages 411-418, March.
    17. Eric Bax, 2019. "Computing a Data Dividend," Papers 1905.01805, arXiv.org, revised Jun 2019.
    18. Arash Asadpour & MohammadHossein Bateni & Kshipra Bhawalkar & Vahab Mirrokni, 2019. "Concise Bid Optimization Strategies with Multiple Budget Constraints," Management Science, INFORMS, vol. 65(12), pages 5785-5812, December.
    19. Jermain C. Kaminski & Christian Hopp, 2020. "Predicting outcomes in crowdfunding campaigns with textual, visual, and linguistic signals," Small Business Economics, Springer, vol. 55(3), pages 627-649, October.
    20. Assaf Razin & Efraim Sadka & Chi-Wa Yuen, 1999. "An Information-Based Model of Foreign Direct Investment: The Gains from Trade Revisited," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 6(4), pages 579-596, November.

    More about this item

    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:arx:papers:1904.06722. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.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.