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Article
Optimal Prizes for All-Pay Contests in Heterogeneous Crowdsourcing
Proceedings of the IEEE 11th International Conference on Mobile Ad Hoc and Sensor Systems (2014, Philadelphia, PA)
  • Tony Tie Luo, Missouri University of Science and Technology
  • Salil S. Kanhere
  • Sajal K. Das, Missouri University of Science and Technology
  • Hwee-Pink Tan
Abstract

Incentive is key to the success of crowdsourcing which heavily depends on the level of user participation. This paper designs an incentive mechanism to motivate a heterogeneous crowd of users to actively participate in crowdsourcing campaigns. We cast the problem in a new, asymmetric all-pay contest model with incomplete information, where an arbitrary n of users exert irrevocable effort to compete for a prize tuple. The prize tuple is an array of prize functions as opposed to a single constant prize typically used by conventional contests. We design an optimal contest that (a) induces the maximum profit - total user effort minus the prize payout - for the crowdsourcer, and (b) ensures users to strictly have incentive to participate. In stark contrast to intuition and prior related work, our mechanism induces an equilibrium in which heterogeneous users behave independently of one another as if they were in a homogeneous setting. This newly discovered property, which we coin as strategy autonomy(SA), is of practical significance: it (a) reduces computational and storage complexity by n-fold for each user, (b) increases the crowdsourcer's revenue by counteracting an effort reservation effect existing in asymmetric contests, and (c) neutralizes the (almost universal) law of diminishing marginal returns (DMR). Through an extensive numerical case study, we demonstrate and scrutinize the superior profitability of our mechanism, as well as draw insights into the SA property.

Meeting Name
IEEE 11th International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2014 (2014: Oct. 28-30, Philadelphia, PA)
Department(s)
Computer Science
Keywords and Phrases
  • Complex networks,
  • Profitability,
  • All-pay auction,
  • Asymmetric contest,
  • Incentive mechanism,
  • Network economics,
  • Participatory Sensing,
  • Strategy autonomy,
  • Economics
International Standard Book Number (ISBN)
978-1-4799-6036-1
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2014 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
10-1-2014
Disciplines
Citation Information
Tony Tie Luo, Salil S. Kanhere, Sajal K. Das and Hwee-Pink Tan. "Optimal Prizes for All-Pay Contests in Heterogeneous Crowdsourcing" Proceedings of the IEEE 11th International Conference on Mobile Ad Hoc and Sensor Systems (2014, Philadelphia, PA) (2014) p. 136 - 144
Available at: http://works.bepress.com/sajal-das/95/