Interplay of network structure and neighbour performance in user innovation

Kunhao Yang (), Itsuki Fujisaki and Kazuhiro Ueda ()
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Kunhao Yang: The University of Tokyo
Itsuki Fujisaki: The University of Tokyo
Kazuhiro Ueda: The University of Tokyo

Palgrave Communications, 2020, vol. 6, issue 1, 1-8

Abstract: Abstract Previous studies showed that regular users have become an important source of innovation (called user innovation). Previous studies also suggested that two factors have significant impacts on user innovation: the social network structure of the users and neighbours’ innovation performance (neighbours mean users having interactions with the focal user). However, in these studies, the influence of the two factors were only discussed separately, and it remained unclear whether these two factors interdependently affected a focal user’s innovation. To examine the interplay between the network structure and the neighbours’ innovation performance, we harnessed data sets from “Idea Storm”, which collects data on user network and idea submission. Through panel regression analyses, we found that—within an open-network structure—the higher innovation performance of neighbours has a larger positive impact on the focal user’s innovation ability. Conversely, in an enclosed network structure, neighbours’ higher performance has a larger negative impact on the focal user’s innovation ability. Our findings filled an important gap in understanding the interplay between the network structure and the neighbours’ performance in user innovation. More broadly, these results suggested that the interplay between the neighbours and the network structures merits attention that even goes beyond user innovation.

Date: 2020
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DOI: 10.1057/s41599-019-0383-x

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