Paper Session 1.2: Emerging Trends in Systems Development
SIGMIS-CPR’18, June 18‒20, 2018, Buffalo-Niagara Falls, NY, USA
Determinants of Open Source Software Project Performance: A Stage-wise Analysis of GitHub Projects Senthilkumar Thangavelu
Amalendu Jyotishi
Amrita School of Business Amrita Vishwa Vidyapeetham Bangalore, India
[email protected]
Amrita School of Business Amrita Vishwa Vidyapeetham Bangalore, India
[email protected]
1. INTRODUCTION The phenomenon of open-source software (OSS) has gained importance among the information technology (IT) firms in the recent years due to its advantages over proprietary or closed source software (CSS). The advantages include low cost of development, availability of reusable architectural and functional components, free and unrestricted access to the source codes, and high level of innovation [2]. Firms have started recognizing the importance and value of OSS over CSS. Successful OSS projects such as Linux, Apache, Gnome, R, STATA, Perl, Python, and MySQL have created a significant impact [3] on the paradigm of software development. In recent times, firms and government institutions are giving much importance to OSS adoption [7] and it is an integral part of their strategy. The choice between growth and control plays a very important role in developing OSS adoption strategy. This choice can shift from one to another over the lifecycle of the business, [1] keeping the value it brings to the firm. Firms explore how to appropriate returns from innovations happening outside their boundaries [4] by getting involved in OSS development and balancing intellectual property rights (IPR). The innovation strategies of the firms are also changing from a closed structure within the firm to outside their boundaries [6]. The [10] R&D expenses and IPR impact the performance of IT firms. In CSS the level of advancement of that particular project is limited, but in OSS the projects are available to everyone and hosting services like GitHub, OpenSource, and SourceForge [8] enable them to modify the projects better. The delivery of the software services over the internet, the cloud computing, the reduced hardware cost, the
improved speed of the digital services, play major roles in making OSS a popular choice. They are able to bring a new outlook and innovation to the existing mechanism which seems to be superior to the CSS. GitHub is one of the most popular OSS hosting services firms that hosts and supports a large number of OSS projects. The contributors of OSS projects develop programs with a freedom to introduce new features and advancement in the functionalities and create a social identification and reputation. The key objective of this study is to address the research question: What are the characteristics of firm, team and project that influence the performance of an OSS project at various development stages?
2. THEORETICAL FOUNDATIONS The authors invoke the Self-Determination Theory (SDT) [9], the theory of collaboration through open superposition [5] and the Affective Events Theory (AET) [11] to understand the development of OSS project. The SDT explains the behavior of human beings, self-motivation, self-regulation, and well-being. When the three innate psychological needs of human beings namely competence, autonomy, and relatedness are satisfied, it enhances the self-motivation and well-being. This applies in the OSS project development phenomenon, where the contributors expect the autonomy in their actions, involved in activities related to their knowledge, and a competitive environment to develop their expertise. The complex functionalities of OSS projects are developed by dividing them into smaller units which are developed by individuals or teams. This theory helps to explain the OSS development by the communities. According to the AET, the emotions and moods of contributors are important aspects of work experience which influence the participation and performance in OSS projects [11].
ACM Reference format: Senthilkumar Thangavelu, and Amalendu Jyotishi. 2018. Determinants of Open Source Software Project Performance: A Stage-wise Analysis of GitHub Projects. In Proceedings of ACM SIGMIS-CPR, June 18–20, 2018, Buffalo-Niagara Falls, NY, USA, 4 pages. https://doi.org/10.1145/3209626.3209723
3. THE CONCEPTUAL MODEL
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author. SIGMIS-CPR '18, June 18–20, 2018, Buffalo-Niagara Falls, NY, USA © 2018 Copyright is held by the owner/author(s). ACM ISBN 978-1-4503-5768-5/18/06. https://doi.org/10.1145/3209626.3209723
Figure 3.1 provides the conceptual model of this research study showing different stages of performance indicators being influenced by not only a number of independent variables discussed above but also by the previous stage performance.
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Paper Session 1.2: Emerging Trends in Systems Development
SIGMIS-CPR’18, June 18‒20, 2018, Buffalo-Niagara Falls, NY, USA
Figure 3.1: The Conceptual Model Number of contributors
License type Number of open issues
Number of forks
Ownership
Number of releases
Number of closed issues
Number of commits
Stage1: Issues
Number of closed pull requests
Stage2: Forking
Stage3: Pull requests
Stage4: Releases
projects and contribute to the OSS communities. The study also helps to design suitable governance mechanisms in order to get the maximum benefits from the OSS projects and OSS communities.
4. RESULTS AND DISCUSSION This study uses the OLS regression for the estimation. In this study, we theorize and empirically examine the influence of various factors on the success of OSS project at different levels using staged approach. In Stage1, the regression coefficient of the number of contributors, the license type, and the ownership shows that they positively and significantly influence the number of open issues. Thus H1a, H1b, H1c are supported. In Stage2, the open issues count and the number of contributors positively and significantly influence the number of forks. The license type and the ownership do not show any significant influence and hence do not support H2c and H2d. This shows an interesting finding that license type and ownership show significant influence in Stage1 but not in Stage2. In Stage3, the square of open issues count and the number of commits show positive influence on the number of pull requests and support H3b and H3c. The square of the number of forks shows positive influence and hence supports H3a. The number of contributors are not showing any significant influence and hence not supporting H3d. In Stage4, the number of closed pull requests and the square of the number of closed issues shows positive and significant influence on the number of releases and support H4a, H4b. These results show that the output of one stage has a positive and significant influence as input to the next stage. We will present the full results and findings at the SIGMIS CPR 2018 conference.
REFERENCES [1] [2] [3] [4] [5]
[6]
[7]
[8]
5. CONTRIBUTIONS AND IMPLICATION This paper has presented a conceptual model of the factors of projects, users, contributors, and property rights that influence the OSS project performance. This study is unique in this perspective and contributes to the academic research by shedding light on the internal dynamics and development of OSS projects, hence structural aspects of OSS project performance. The findings of this study significantly contribute to the software development methodology and the study on internal dynamics of the development lifecycle. The findings also contribute to change in the way the IT firms develop OSS
[9]
[10]
[11]
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Appleyard, M.M. and Chesbrough, H.W. 2017. The Dynamics of Open Strategy: From Adoption to Reversion. Long Range Planning. 50, 3 (2017), 310–321. Bonaccorsi, A. and Rossi, C. 2003. Why open source software can succeed. Research Policy. 32, 7 (2003), 1243–1258. Crowston, K. et al. 2003. Defining Open Source Software project success. International Conference on Information Systems (ICIS) (2003). Dahlander, L. 2005. Appropriation and appropriability in open source software. International Journal of Innovation Management. 9, 3 (2005), 259–285. Howison, J. and Crowston, K. 2014. COLLABORATION THROUGH OPEN SUPERPOSITION: A THEORY OF THE OPEN SOURCE WAY. MIS Quarterly. 38, 1 (2014), 29–50. Kumar, K.G.S. and Jyotishi, A. 2014. Differences in approach to and output of innovation. Proceedings of the 52nd ACM conference on Computers and people research - SIGSIM-CPR ’14. (2014), 59–68. van Loon, A. and Toshkov, D. 2015. Adopting open source software in public administration: The importance of boundary spanners and political commitment. Government Information Quarterly. 32, 2 (2015), 207–215. Medappa, P.K. and Srivastava, S.C. 2017. License Choice and the Changing Structures of Work in Organization Owned Open Source Projects. ACM SIGMIS-CPR 2017 (2017), 118–123. Ryan, R.M. and Deci, E.L. 2000. Self-Determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-Being. American Psychologist. 55, 1 (2000), 68–78. Thangavelu, S. and Jyotishi, A. 2017. Influence of R & D and IPR Regulations on the Performance of IT Firms in India : An Empirical Analysis using Tobin ’ s Q Approach. ACM SIGMIS-CPR 2017 (2017), 161–168. Weiss, H.M. and Cropanzano, R. 1996. Affective Events Theory: A theoretical discussion of the structure, causes and consequences of affective experiences at work.
