Understanding the Emergence and Recombination of Distant Knowledge on Crowdsourcing Platforms
Journal
International Conference on Information Systems (ICIS)
Type
conference paper
Date Issued
2017-12-10
Author(s)
Abstract (De)
Crowdsourcing represents a powerful approach for organizations to engage in distant search and mobilize knowledge distributed amongst a diverse network of people. While organizations generally succeed in generating large amounts of knowledge, they frequently fail to identify useful ideas that have the potential to solve problems or serve as innovation. We combine text mining and network analysis to examine how such contributions emerge on crowdsourcing platforms and how organizations may identify them. We find that useful ideas typically originate from members in a crowd with only few network ties and that these contributions become especially useful when they are enriched with local knowledge provided by experienced members on the platform. We extend existing research by examining the effects of network relationships and knowledge (re)combination in crowdsourcing. We also discuss the potential of network analysis and text mining to support organizations in tracking the origin of contributions and analyzing their content.
Funding(s)
Language
English
HSG Classification
contribution to scientific community
HSG Profile Area
SoM - Business Innovation
Publisher place
Seoul, South Korea
Event Title
International Conference on Information Systems (ICIS)
Event Location
Seoul, South Korea
Event Date
13-15 Dec 2017
Subject(s)
Division(s)
Eprints ID
252462
File(s)![Thumbnail Image]()
Name
RhynEtAl_ICIS_2017.pdf
Size
472.86 KB
Format
Adobe PDF
Checksum (MD5)
0136e8bf10a79d841b9e212cc1518983