Intellectual property policy and attractiveness: a longitudinal study of free and open source software projects

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Citation: Carlos Denner Santos, Marcos Bonci Cavalca, Fabio Kon, Julio Singer, Victor Ritter, Damaris Regina, Tamy Tsujimoto (2011) Intellectual property policy and attractiveness: a longitudinal study of free and open source software projects. Proceedings of the ACM 2011 conference on Computer supported cooperative work (RSS)
DOI (original publisher): 10.1145/1958824.1958950
Semantic Scholar (metadata): 10.1145/1958824.1958950
Sci-Hub (fulltext): 10.1145/1958824.1958950
Internet Archive Scholar (search for fulltext): Intellectual property policy and attractiveness: a longitudinal study of free and open source software projects
Download: http://www.ime.usp.br/~kon/papers/p705-santos.pdf
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Summary

Propose theoretic model in which a project's license influences the project's attractiveness, which influences activeness and efficiency ("production dynamics"), which influence "software quality (success)".

Using flossmole.org database, authors selected 756 projects with license changes and no category changes (to avoid potential confounding variable) between October 2005 and June 2009 and collected attractiveness indicators (web hits, downloads, members) for the projects over that time period.

Project licenses were placed in 7 categories:

A None (e.g., “other” or “adaptive”).
B Non-Restrictive and Relicensable (e.g., Public Domain or MIT).
C Academic Free License-AFL (Non-Restrictive and Relicensable).
D Restrictive and Non-Relicensable (e.g., GNU Lesser General Public License-LGPL).
E Restrictive and Relicensable (e.g., Mozilla Public License-MPL).
F Restrictive, Highly Restrictive and Non- Relicensable (e.g., GNU General Public License-GPL).
G Restrictive, Highly Restrictive and Relicensable (e.g., dual licensed: GPL and Apache).

Most common license category changed from is F (417 changes), producing a 16% increase in attractiveness. F was also the most common license category changed to (298 changes), producing a 1% decrease in attractiveness.

Authors consider AFL under-studied and find with a small number of changes (12) it produced 100% increase in attractiveness.

Unfortunately a complete data table is not provided. Unclear how (mutually exclusive, per summary table) changes to and from F add up to larger number than total projects in dataset.


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