Abstract

This study contributes to the understanding of collaborative innovation in online user communities. Aside from providing evidence for the existence of these communities, prior research focused on users’ motivations, backgrounds, and roles at the micro level but largely neglected to examine the effects of individual user activities on joint activities at the community level. By applying a netnographic research design, which is followed by a content analysis step and logistic regression analysis, we explore to what degree different user activities trigger collaborative innovation inside a community. We find two factors inherent to the initial post of a thread, problem complexity and collaboration intention, which explain the probability of collaborative innovation. The likelihood of joint activities is raised significantly if the contribution of a user ranks high on both dimensions. By quantifying collaborative user innovation, we hope to encourage the inclusion of user activities in future policy considerations. Moreover, understanding the effects of individual user activities at the community level may help companies to understand users of technologies better and to identify opportunities for collaboration.

Highlights

  • Users rarely innovate in isolation [1,2]

  • As we aimed to determine which types of individual user activities increase the probability of collaborative innovation, we inductively derived all different types of triggers [62]

  • Of all the 1887 threads in our dataset, about 28% resulted in collaborative innovation activities

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Summary

Introduction

Users rarely innovate in isolation [1,2]. A plethora of online-based user innovation communities has emerged recently [3]. The dissemination of internet-based settings has massively facilitated this development by increasing connectivity among users worldwide while reducing transaction costs at the same time. New types of digital infrastructures, for example, digital makerspaces, online communities, and work execution forums, provide users with fertile soil to conduct their innovation activities [4,5,6,7]. Prior user innovation research extensively discussed the motives of users to join and actively contribute to communities [8], characterized the members’. Characteristics and motivation [9,10], and examined the structure and composition of online communities [11,12]. We have learned that users are willing to share their ideas and knowledge to assist each other and work on an output collectively [13,14]

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