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Learning and Open Source Software License Choice
Author(s) -
Peng Gang,
Mu Jifeng,
Di Benedetto C. Anthony
Publication year - 2013
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/deci.12036
Subject(s) - license , experiential learning , knowledge management , open source software , computer science , exploit , software , business , psychology , mathematics education , computer security , programming language , operating system
ABSTRACT Licensing is the defining characteristic of open source software (OSS) and often has tremendous impact on the success of OSS projects. However, OSS licenses are very different from those for proprietary software, and our understanding of the choice of OSS licenses is very limited. In this study, we explore this important decision from a learning perspective. We build collaboration networks and trace paths through which potential learning and knowledge flow across projects using a dataset derived from SourceForge. We identify that both experiential learning and vicarious learning have significant influence on OSS license choice. We provide reasons why experiential learning and vicarious learning affect decision‐making regarding OSS license choice, and explore important contingencies under which the two modes of learning are more effective. We find that leadership roles on prior projects and similarities between projects significantly moderate these two modes of learning, respectively. More importantly, we argue and empirically illustrate that experiential learning is more effective than vicarious learning in influencing OSS license choice. Our research sheds new light on our understanding of license choice for OSS projects and provides practical guidelines for future OSS development.