Token-Weighted Crowdsourcing

Gerry Tsoukalas () and Brett Hemenway Falk ()
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Gerry Tsoukalas: The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Brett Hemenway Falk: Department of Computer and Information Sciences, University of Pennsylvania, Philadelphia, Pennsylvania 19104

Management Science, 2020, vol. 66, issue 9, 3843-3859

Abstract: Blockchain-based platforms often rely on token-weighted voting (“ τ -weighting”) to efficiently crowdsource information from their users for a wide range of applications, including content curation and on-chain governance. We examine the effectiveness of such decentralized platforms for harnessing the wisdom and effort of the crowd. We find that τ -weighting generally discourages truthful voting and erodes the platform’s predictive power unless users are “strategic enough” to unravel the underlying aggregation mechanism. Platform accuracy decreases with the number of truthful users and the dispersion in their token holdings, and in many cases, platforms would be better off with a “flat” 1/ n mechanism. When, prior to voting, strategic users can exert effort to endogenously improve their signals, users with more tokens generally exert more effort—a feature often touted in marketing materials as a core advantage of τ -weighting—however, this feature is not attributable to the mechanism itself, and more importantly, the ensuing equilibrium fails to achieve the first-best accuracy of a centralized platform. The optimality gap decreases as the distribution of tokens across users approaches a theoretical optimum, which we derive, but tends to increase with the dispersion in users’ token holdings.

Keywords: blockchain; crowdsourcing; cryptocurrency; information aggregation; on-chain governance; strategic voting; tokenomics; token-curated registries (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (12)

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