An Empirical Investigation of Dual Network Effects in Innovation Project Development

As innovation project developers advance their knowledge through more project experience, cross-project learning is likely to enhance project performance. Past research has demonstrated positive contributions of developer networking at the macro (project) level. However, the network effects at the micro (project property) level have not been studied as much. To address this gap, we apply a network model to examine which project properties (e.g., the project's operating system and topic) generate positive or negative network effects in addition to the macro network effect when developers engage in multiple projects. In this dual (developer and property) network model, we theorize that positive network effects take place because of cross-project learning and knowledge exchange, whereas negative network effects can also occur due to time constraints and cognitive overloading. In addition to such dual network effects, we also consider such project success predictors as spatial and temporal reach opportunities for project users (scope of translations and project age) and human resources availability (developer team size). Our empirical application using open source software (OSS) data demonstrates that the presented model can effectively integrate both the dual network effects and non-network variables as factors influencing the commercial success of OSS projects.