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Peripheral Developer Participation in Open Source Projects: An Empirical Analysis

Published:13 January 2016Publication History
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Abstract

The success of the Open Source model of software development depends on the voluntary participation of external developers (the peripheral developers), a group that can have distinct motivations from that of project founders (the core developers). In this study, we examine peripheral developer participation by empirically examining approximately 2,600 open source projects. In particular, we hypothesize that peripheral developer participation is higher when the potential for building reputation by gaining recognition from project stakeholders is higher. We consider recognition by internal stakeholders (such as core developers) and external stakeholders (such as end-users and peers). We find a positive association between peripheral developer participation and the potential of stakeholder recognition after controlling for bug reports, feature requests, and other key factors. Our findings provide important insights for OSS founders and corporate managers for open sourcing or OSS adoption decisions.

References

  1. F. B. Abreu. 1995. The MOOD metrics set. In Proceedings of ECOOP'95. 267.Google ScholarGoogle Scholar
  2. P. Ågerfalk and B. Fitzgerald. 2008. Outsourcing to an unknown workforce: Exploring opensourcing as a global sourcing strategy. MIS Quarterly 32, 2, 385--409. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. R. D. Banker, G. B. Davis, and S. A. Slaughter. 1998. Software development practices, software complexity, and software maintenance performance: A field study. Management Science 44 433--450. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. M. E. Barth and S. Kallapur. 1996. The effects of cross sectional scale differences on regression results in empirical accounting research. Contemporary Accounting Research 13, 2, 527--567.Google ScholarGoogle ScholarCross RefCross Ref
  5. G. S. Becker. 1976. Altruism, egoism and genetic fitness: Economics and sociobiology. Journal of Economic Literature 14, 3, 817--826Google ScholarGoogle Scholar
  6. G. Burtch, A. Ghose, and S. Wattal. 2013. An empirical examination of the antecedents and consequences of contribution patterns in crowd-funded markets. Information Systems Research 24, 3, 499--519.Google ScholarGoogle ScholarCross RefCross Ref
  7. F. P. Brooks. 1975. The mythical man-month. In Proceedings of the International Conference on Reliable Software (Los Angeles, CA, April 21--23, 1975). ACM Press, New York, 193. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. A. C. Cameron and P. K. Trivedi. 1998. Regression Analysis of Count Data Book. 1st edition. Econometric Society Monograph No. 30. Cambridge University Press.Google ScholarGoogle Scholar
  9. S. Chengalur-Smith and A. Sidorova. 2003. Survival of open-source projects: A population ecology perspective. In Proceedings of the 24th International Conference on Information Systems, Association for Information Systems.Google ScholarGoogle Scholar
  10. S. R. Chidamber and C. F. Kemerer. 1994. A metrics suite for object oriented design. IEEE Transactions on Software Engineering 20, 6. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. K. Crowston, J. Howison, and H. Annabi. 2006. Information systems success in free and open source software development: Theory and measures. Software Process: Improvement and Practice (Special Issue on Free/Open Source Software Processes). Vol. 11, pp 123--148.Google ScholarGoogle ScholarCross RefCross Ref
  12. B. Curtis, S. B. Sheppard, P. Millman, M. A. Brost, and T. Love. 1979. Measuring the psychological complexity of software maintenance tasks with the Halstead and McCabe metrics. IEEE Transactions on Software Engineering SE-2, 2. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. L. Dahlander and M. Magnusson. 2008. How do firms make use of open source communities? Long Range Planning 41.Google ScholarGoogle Scholar
  14. Y. Fang and D. Neufeld. 2009. Understanding sustained participation in open source software projects. Journal of Management Information Systems 25, 4. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. C. Fershtman and N. Gandal. 2007. Open source software: Motivation and restrictive licensing. International Economics and Economic Policy 4, 2.Google ScholarGoogle ScholarCross RefCross Ref
  16. W. Green. 2007. Functional Form and Heterogeneity in Models for Count Data. Department of Economics, Stern School of Business, New York University, Working Paper 07--10, 2007.Google ScholarGoogle Scholar
  17. B. Golden. 2004. Succeeding with Open Source. Addison Wesley. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. M. Goeminne and T. Mens. 2011. Evidence for the pareto principle in open source activity. Joint Proceedings of the 1st Workshop on Model Driven Software Maintenance and 5th International Workshop on Software Quality and Maintainability. 74--82.Google ScholarGoogle Scholar
  19. R. A. Guth. 2006. Trolling the web for free labor, software upstarts are new force. Wall Street Journal, November 13, 2006. Last accessed May 4, 2007 at http://online.wsj.com/article/SB116338621999421269.html.Google ScholarGoogle Scholar
  20. M. H. Halstead. 1977. Elements of Software Science. Amsterdam: Elsevier North Holland. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. A. Hars and S. Ou. 2001, Working for free? Motivations of participating in open source projects. In Proceedings of the 34th Hawaii International Conference on System Sciences. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. J. S. Hammond, M. Gerush, and J. Silekis. 2009. Open source moves into the mainstream. Forrester Inc. Report. https://www.forrester.com/Open+Source+Software+Goes+Mainstream/fulltext/-/E-res54205. Last accessed: Dec 20 2015.Google ScholarGoogle Scholar
  23. J. Howison and K. Crowston. 2004. The perils and pitfalls of mining sourceforge. In Proceedings of the 26th International Conference on Software Engineering, International Workshop on Mining Software Repositories. 7--11.Google ScholarGoogle Scholar
  24. F. Hunt and P. Johnson. 2002. On the pareto distribution of sourceforge projects. In Proceedings of the F/OSS Software Development Workshop. 122--129.Google ScholarGoogle Scholar
  25. K. R. Jayanth. 2009. Essays on Software Development. Doctoral Dissertation. Graduate Program in Management Science. University of Texas at Dallas.Google ScholarGoogle Scholar
  26. A. Kaltenbrunner, V. Gomez, and V. Lopez. 2007. Description and prediction of Slashdot activity. In Proceedings of the 5th Latin American Web Congress (LA-WEB). Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. R. J. Kauffman, A. A. Techatassanasoontorn, and B. Wang. 2012. Event history, spatial analysis and count data methods for empirical research in information systems. Information Technology and Management 13, 3, 115--147. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. C. M. Kelty. 2001. Free software/free science. First Monday {S.l.}, Dec. 2001. ISSN 13960466. Last accessed February 17, 2014 at http://pear.accc.uic.edu/ojs/index.php/fm/article/view/902/811. doi:10.5210/fm.v6i12.902.Google ScholarGoogle Scholar
  29. S. C. Kolm and J. M. Ythier. 2006. Handbook of the economics of giving, altruism and reciprocity: Foundations. Amsterdam: North Holland, Elsevier.Google ScholarGoogle Scholar
  30. S. Krishnamurthy. 2002. Cave or community? An empirical examination of 100 mature open source projects. First Monday 7(4). http://www.firstmonday.dk/issues/issue7_6/Krishnamurthy/index.html.Google ScholarGoogle Scholar
  31. J. Kunegis, A. Lommatzsch, and C. Bauckhage. 2009. The Slashdot Zoo: Mining a social network with negative edges. In Proceedings of the 18th Conference on WWW. 741--750. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. K. Lakhani and E. von Hippel. 2003. How open source software works: “Free” user-to-user assistance. Research Policy 32, 923--943.Google ScholarGoogle ScholarCross RefCross Ref
  33. K. Lakhani and R. Wolf. 2005. Why hackers do what they do: Understanding motivation and effort in free/open source software projects. In Perspectives in Free and Open Source Software, Joe Feller, Brian Fitzgerald, Scott Hissam, and Karim R. Lakhani (Eds.). Cambridge, MA/London: MIT Press.Google ScholarGoogle Scholar
  34. C. Lampe, E. Johnston, and P. Resnick. 2007, Follow the reader: Filtering comments on Slashdot. In Proceedings of the 25th CHI. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. J. Lerner and J. Tirole. 2002. Some simple economics of open source. Journal of Industrial Economics 52, 197--234.Google ScholarGoogle ScholarCross RefCross Ref
  36. J. Lerner and J. Tirole. 2005. The scope of open source licensing. Journal of Law, Economics and Organization 21, 20--56.Google ScholarGoogle ScholarCross RefCross Ref
  37. B. Lev, C. Petrovits, and R. Radhakrishnan. 2010. Is doing good good for you? How corporate charitable contributions enhance revenue growth. Strategic Management Journal 31, 182--200.Google ScholarGoogle Scholar
  38. G. S. Maddala. 1983. Limited-Dependent and Qualitative Variables in Economics. New York: Cambridge University Press.Google ScholarGoogle Scholar
  39. G. S. Maddala. 1991. A perspective on the use of limited-dependent and qualitative variables models in accounting research. Accounting Review 66, 788--806.Google ScholarGoogle Scholar
  40. G. Madey, V. Freeh, and T Tynan. 2002. The open source software development phenomenon: An analysis based on social network theory. In Proceedings of the Americas Conference on Information Systems, Dallas, Texas, 1806--1813.Google ScholarGoogle Scholar
  41. K. S. Mathias, J. H. Cross, T. D. Hendrix, and L. A. Barowski. 1999. The role of software measures and metrics in studies of program comprehension. In Proceedings of the 37th Annual Southwest Regional Conference (ACM-SE 37). 13. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. T. J. McCabe. 1976. A complexity measure. IEEE Transactions on Software Engineering, 308--320. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. J. C. Meister. 2013. Make sure your dream company can find you. Harvard Business Review Blog. Last accessed January 12, 2013, from http://blogs.hbr.org/2013/12/make-sure-your-dream-company-can-find-you/.Google ScholarGoogle Scholar
  44. V. Midha. 2008. Does complexity matter? The impact of change in structural complexity on software maintenance and new developer's contributions in open source software. ICIS 2008 Proceedings. Paper 37.Google ScholarGoogle Scholar
  45. J. Marlow, L. Dabbish, and J. Herbsleb. 2013. Impression formation in online peer production: Activity traces and personal profiles in github. In Proceedings of the Conference on Computer Supported Cooperative Work. 117--128. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. W. Oh and S. Jeon. 2007. Membership herding and network stability in the open source community: The ising perspective. Management Science 53, 7, 1086--1101. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. E. Raymond. 1999. The Cathedral and the Bazaar. Sebastopol, CA: O'Reilly. Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. J. A. Roberts, Il-Horn Hann, and S. A. Slaughter. 2006. Understanding the motivations, participation, and performance of open source software developers: A longitudinal study of the Apache projects. Management Science 52, 7, 984--999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. C. M. Schweik and R. C. English. 2012. Internet Success: A Study of Open Source Software Commons. Cambridge, MA: MIT Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. H. Simon. 1993. Altruism and economics. American Economic Review 83, 2, 156--161.Google ScholarGoogle Scholar
  51. K. J. Stewart, A. P. Ammeter, and L. M Maruping. 2006. Impacts of license choice and organizational sponsorship on user interest and development activity in open source software projects. Information Systems Research 17, 2, 126. Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. I. Stamelos, L. Angelis, A. Oikonomou, and G. L. Bleris. 2002. Code quality analysis in open source software development. Information Systems Journal 12, 43--60.Google ScholarGoogle ScholarCross RefCross Ref
  53. M. Van Antwerp and G. Madey. 2008. Advances in the sourceforge research data archive (SRDA). In Proceedings of the 4th International Conference on Open Source Systems, IFIP 2.13 (WoPDaSD 2008), Milan, Italy, September 2008.Google ScholarGoogle Scholar
  54. G. Von Krogh, S. Spaeth, and K. R. Lakhani. 2003. Community, joining and specialization in open source software innovation: A case study. Research Policy 32 (2003) 1217--1241.Google ScholarGoogle ScholarCross RefCross Ref
  55. P. Wagstrom. 2009. Vertical Interaction in Open Software Engineering Communities. Doctoral Dissertation. Carnegie Institute of Technology and School of Computer Science, Carnegie Mellon University. Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. P. Wagstrom, A. Mockus, J. D. Herbsleb, and R. E. Kraut. 2010. The impact of commercial organizations on volunteer participation in online Montreal, Canada, August 2 community. In Proceedings of the Academy of Management Annual Meeting.Google ScholarGoogle Scholar
  57. A. Wiggins, J. Howison, and K. Crowston. 2009. Heartbeat: Measuring active user base and potential user interest in FLOSS projects. In Proceedings of 5th IFIP WG 2.13 International Conference on Open Source Systems (OSS 2009), C. Boldyreff, K. Crowston, B. Lundell, and A. I. Wasserman (Eds.), Skövde, Sweden, June 3, 94--104.Google ScholarGoogle Scholar
  58. J. M. Wooldridge. 2002. Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press, 2002.Google ScholarGoogle Scholar
  59. C. Wu, J. H. Gerlach, and C. E. Young. 2007. An empirical analysis of open source software developers' motivations and continuance intentions. Information & Management 44, 3, 253--262. Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. L. F. Wurster. 2008. User survey analysis: Open source software, worldwide. 2008. Gartner Report. Last accessed March 20, 2009, at http://www.gartner.com/it/page.jsp?id=801412.Google ScholarGoogle Scholar
  61. J. Xu, Y. Gao, S. Christley, and G. Madey. 2005. A topological analysis of the open source software development community. In Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05). Google ScholarGoogle ScholarDigital LibraryDigital Library
  62. Y. Ye and K. Kishida. 2003. Towards an understanding of the motivation of open source software developers. In Proceedings of the 25th International Conference on Software Engineering. Google ScholarGoogle ScholarDigital LibraryDigital Library
  63. Z. E. Zheng, P. Fader, and B. Padmanabhan. 2012. From business intelligence to competitive intelligence: Inferring competitive measures using augmented site-centric data. Information Systems Research 23, 3, 698--720.Google ScholarGoogle ScholarCross RefCross Ref

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    • Published in

      cover image ACM Transactions on Management Information Systems
      ACM Transactions on Management Information Systems  Volume 6, Issue 4
      January 2016
      73 pages
      ISSN:2158-656X
      EISSN:2158-6578
      DOI:10.1145/2869770
      Issue’s Table of Contents

      Copyright © 2016 ACM

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      Publication History

      • Published: 13 January 2016
      • Accepted: 1 September 2015
      • Revised: 1 June 2015
      • Received: 1 February 2014
      Published in tmis Volume 6, Issue 4

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