From oligarchy to decentralization: Network structures and collaboration on digital platforms

Chao Liu

Technological Forecasting and Social Change, 2025, vol. 219, issue C

Abstract: The potential of peer production on digital platforms—leveraging collective intelligence and decentralized collaboration—has gained increasing attention from organizations. However, peer production is not purely non-hierarchical, and its models and effectiveness vary significantly. While some platforms successfully engage participants and harness collective intelligence, others struggle with involvement and evolve into oligarchical structures. Existing research has largely overlooked the variety of peer production models and the influence of network embeddedness on these variations. This study addresses this gap by examining peer production projects on GitHub and analyzing how network structures affect decentralized collaboration. This is particularly important because participant anonymity on digital platforms obscures social cues that typically signal trust and reputation. The findings reveal that social networks play a vital role in signaling status and reputation. Specifically, network brokerage—manifested through structural holes—positively impacts decentralized collaboration, while higher network cohesion and centrality are linked to reduced collaboration. This research advances theoretical understanding by uncovering the diversity of peer production models and highlighting the critical role of network structures in shaping decentralized collaboration on digital platforms. It also offers practical insights for organizations aiming to enhance collaborative environments and suggests promising directions for future research in this area.

Keywords: Digital platforms; Collective intelligence; Oligarchy; Decentralized collaboration; Network embeddedness; Structural hole (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:219:y:2025:i:c:s0040162525003178

DOI: 10.1016/j.techfore.2025.124286

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