Competition and Collaboration in Crowdsourcing Communities: What happens when peers evaluate each other?

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Riedl, Christoph, Grad, Tom, Lettl, Christopher
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866917646971174912
author Riedl, Christoph
Grad, Tom
Lettl, Christopher
author_facet Riedl, Christoph
Grad, Tom
Lettl, Christopher
contents Crowdsourcing has evolved as an organizational approach to distributed problem solving and innovation. As contests are embedded in online communities and evaluation rights are assigned to the crowd, community members face a tension: they find themselves exposed to both competitive motives to win the contest prize and collaborative participation motives in the community. The competitive motive suggests they may evaluate rivals strategically according to their self-interest, the collaborative motive suggests they may evaluate their peers truthfully according to mutual interest. Using field data from Threadless on 38 million peer evaluations of more than 150,000 submissions across 75,000 individuals over 10 years and two natural experiments to rule out alternative explanations, we answer the question of how community members resolve this tension. We show that as their skill level increases, they become increasingly competitive and shift from using self-promotion to sabotaging their closest competitors. However, we also find signs of collaborative behavior when high-skilled members show leniency toward those community members who do not directly threaten their chance of winning. We explain how the individual-level use of strategic evaluations translates into important organizational-level outcomes by affecting the community structure through individuals' long-term participation. While low-skill targets of sabotage are less likely to participate in future contests, high-skill targets are more likely. This suggests a feedback loop between competitive evaluation behavior and future participation. These findings have important implications for the literature on crowdsourcing design, and the evolution and sustainability of crowdsourcing communities.
format Preprint
id arxiv_https___arxiv_org_abs_2404_14141
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Competition and Collaboration in Crowdsourcing Communities: What happens when peers evaluate each other?
Riedl, Christoph
Grad, Tom
Lettl, Christopher
General Economics
Economics
Computer Science and Game Theory
Human-Computer Interaction
Applications
Crowdsourcing has evolved as an organizational approach to distributed problem solving and innovation. As contests are embedded in online communities and evaluation rights are assigned to the crowd, community members face a tension: they find themselves exposed to both competitive motives to win the contest prize and collaborative participation motives in the community. The competitive motive suggests they may evaluate rivals strategically according to their self-interest, the collaborative motive suggests they may evaluate their peers truthfully according to mutual interest. Using field data from Threadless on 38 million peer evaluations of more than 150,000 submissions across 75,000 individuals over 10 years and two natural experiments to rule out alternative explanations, we answer the question of how community members resolve this tension. We show that as their skill level increases, they become increasingly competitive and shift from using self-promotion to sabotaging their closest competitors. However, we also find signs of collaborative behavior when high-skilled members show leniency toward those community members who do not directly threaten their chance of winning. We explain how the individual-level use of strategic evaluations translates into important organizational-level outcomes by affecting the community structure through individuals' long-term participation. While low-skill targets of sabotage are less likely to participate in future contests, high-skill targets are more likely. This suggests a feedback loop between competitive evaluation behavior and future participation. These findings have important implications for the literature on crowdsourcing design, and the evolution and sustainability of crowdsourcing communities.
title Competition and Collaboration in Crowdsourcing Communities: What happens when peers evaluate each other?
topic General Economics
Economics
Computer Science and Game Theory
Human-Computer Interaction
Applications
url https://arxiv.org/abs/2404.14141