Drawing on structural and relational dimensions of social capital, this study examines the simultaneous effects of both the structure of a social network and peer-to-peer relations within such a network on user innovation behaviour in online community-based innovation contests (OCICs). Specifically, it explores the interplay between relational mechanisms that drive and explain peers' interactions (namely learning and trust) and how diverse network configurations affect this relationship. Previous research has studied how either network structure or peer-to-peer relationships within social networks affect innovation. However, scholars know little about the way network structure and relational mechanisms interact in influencing users' innovative behaviour. Furthermore, OCICs, as a context in which user innovation occurs, have received scant attention so far. To address its objectives, the research adopts a single-case approach. The selected case, MoFilm, is an online community for film makers who compete to produce short films for global brands. A three-phase mixed-methods data-collection approach is adopted, which involves two qualitative phases and social network analysis of user innovators within the community. The findings unravel critical relational mechanisms of competence-based and intention-based trust, affective learning and cognitive learning. They show how these mechanisms interplay to influence user innovation. Furthermore, the results unravel network configurations of core-periphery, triads and a sparse network of strong ties, which act as major structures underpinning users' innovative behaviour. Finally, this study demonstrates how each of these structural configurations interacts with the unravelled relationships between trust and learning to impact on user innovation behaviour.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:765456 |
| Date | January 2018 |
| Creators | Galehbakhtiari, Sara |
| Publisher | University of Nottingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.nottingham.ac.uk/53469/ |
Page generated in 0.0021 seconds