Unravelling the effects of knowledge-sharing dynamics on crowdsourcing contest participation

Hanieh Javadi Khasraghi, Xuan Wang, Yaojie Li and Xi Mao

Behaviour and Information Technology, 2025, vol. 44, issue 15, 3669-3683

Abstract: Crowdsourcing contests have emerged as a popular approach for organisations to leverage collective intelligence and tap into the expertise of a diverse crowd. Knowledge sharing in such contests is paramount in promoting individual or team participation. This study employs negative binomial regression analysis to explore the impact of dynamic knowledge-sharing features – knowledge volume, knowledge expansion, knowledge innovation, and knowledge popularity – on team participation, using data from 211 crowdsourcing contests hosted on Kaggle. The findings offer significant implications for researchers and practitioners regarding effective knowledge management within crowdsourcing platforms. Encouraging knowledge sharing and collaboration and promoting innovative practices can significantly boost the attraction of more participating teams while amplifying the volume of submissions. Additionally, this study underscores the importance of implementing mechanisms to mitigate knowledge overload and ensure diversity of ideas, thereby sustaining engagement and promoting more unique submissions.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2024.2446400 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tbitxx:v:44:y:2025:i:15:p:3669-3683

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20

DOI: 10.1080/0144929X.2024.2446400

Access Statistics for this article

Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos

More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().