Developer Heterogeneity and Formation of Communication Networks in Open Source Software Projects
Journal of Management Information Systems, Volume 27, Number 3, 2010
63 Pages Posted: 1 Oct 2008 Last revised: 7 Nov 2017
Date Written: September 30, 2008
Abstract
Over the last few years, open source software (OSS) development has gained a huge popularity and has attracted a large variety of developers under its fold. According to software engineering folklore, the architecture and the organization of software depend on the communication patterns of the contributors. Communication patterns among developers influence knowledge sharing among them. Unlike in a formal organization, the communication network structures in an OSS project evolve unrestricted and unplanned. We develop a non-cooperative game theoretic model to investigate the network formation in an OSS team and to characterize the stable and efficient structures. We incorporate developer heterogeneity in the network based on their informative value. We find that, for a given scenario, there may exist several stable structures which are inefficient. We also find that there may not always exist a stable structure that is efficient. This can be explained by the fact that the stability of the structure is dependent on the developer's maximization of self utility whereas the efficiency of the structure is dependent on the maximization of group utility. In general, a tension exists between the stability and efficiency of structures because developers act in their self interest rather than the group interest. We find, whenever there is such a tension, the stable structure is either under-connected across types or over-connected within type of developers from an efficiency perspective. Empirically, we use the latent class model and analyze two real-world OSS projects hosted at Sourceforge.net. For each project, different types of developers and a stable structure is identified, which fits well with the predictions of our model. We further discuss implications of our results and provide directions for future research.
Keywords: social networks, network formation, game theory, open source, software, knowledge worker, teams
JEL Classification: A19, C72, D00, D61
Suggested Citation: Suggested Citation
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