Networks, Social Influence, and the Choice Among Competing Innovations: Insights from Open Source Software Licenses

Networks, Social Influence, and the Choice Among Competing Innovations: Insights from Open Source Software Licenses

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Article ID: iaor20135193
Volume: 24
Issue: 3
Start Page Number: 539
End Page Number: 560
Publication Date: Sep 2013
Journal: Information Systems Research
Authors: ,
Keywords: networks, social, behaviour, economics, statistics: inference
Abstract:

Existing research provides little insight into how social influence affects the adoption and diffusion of competing innovative artifacts and how the experiences of organizational members who have worked with particular innovations in their previous employers affect their current organizations' adoption decision. We adapt and extend the heterogeneous diffusion model from sociology and examine the conditions under which prior adopters of competing open source software (OSS) licenses socially influence how a new OSS project chooses among such licenses and how the experiences of the project manager of a new OSS project with particular licenses affects its susceptibility to this social influence. We test our predictions using a sample of 5,307 open source projects hosted at SourceForge. Our results suggest the most important factor determining a new project's license choice is the type of license chosen by existing projects that are socially closer to it in its inter‐project social network. Moreover, we find that prior adopters of a particular license are more infectious in their influence on the license choice of a new project as their size and performance rankings increase. We also find that managers of new projects who have been members of more successful prior OSS projects and who have greater depth and diversity of experience in the OSS community are less susceptible to social influence. Finally, we find a project manager is more likely to adopt a particular license type when his or her project occupies a similar social role as other projects that have adopted the same license. These results have implications for research on innovation adoption and diffusion, open source software licensing, and the governance of economic exchange.

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