An incentive mechanism for crowdsourcing systems with network effects

Yanjiao Chen*, Xu Wang, Baochun Li, Qian Zhang

*Corresponding author for this work

Research output: Contribution to journalJournal Articlepeer-review

13 Citations (Scopus)

Abstract

In a crowdsourcing system, it is important for the crowdsourcer to engineer extrinsic rewards to incentivize the participants. With mobile social networking, a user enjoys an intrinsic benefit when she aligns her behavior with the behavior of others. Referred to as network effects, such an intrinsic benefit becomes more significant as more users join and contribute to the crowdsourcing system. But should a crowdsourcer design her extrinsic rewards differently when such network effects are taken into consideration? In this article, we incorporate network effects as a contributing factor to intrinsic rewards, and study its influence on the design of extrinsic rewards. We show that the number of participating users and their contributions to the crowdsourcing system evolve to a steady equilibrium, thanks to subtle interactions between intrinsic rewards due to network effects and extrinsic rewards offered by the crowdsourcer. Taken network effects into consideration, we design progressively more sophisticated extrinsic reward mechanisms, and propose new and optimal strategies for a crowdsourcer to obtain a higher utility. Through simulations and examples, we demonstrate that with our new strategies, a crowdsourcer is able to attract more participants with higher contributed efforts; and the participants gain higher utilities from both intrinsic and extrinsic rewards.

Original languageEnglish
Article number49
JournalACM Transactions on Internet Technology
Volume19
Issue number4
DOIs
Publication statusPublished - Nov 2019

Bibliographical note

Publisher Copyright:
© 2019 Association for Computing Machinery.

Keywords

  • Crowdsourcing
  • Incentive mechanism
  • Intrinsic rewards
  • Network effects

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