201
Views
2
CrossRef citations to date
0
Altmetric
Original Articles

Sustained Participation in Open Source Software Project Communities

ORCID Icon & ORCID Icon

References

  • Carillo K, Huff S, Chawner B. What makes a good contributor? Understanding contributor behavior within large Free/Open Source Software projects–A socialization perspective. The Journal of Strategic Information Systems. 2017. doi:10.1016/j.jsis.2017.03.001.
  • Carillo K, Okoli C. The open source movement: a revolution in software development. J Comput Inf Syst. 2008;49:1–9.
  • Fang Y, Neufeld D. Understanding sustained participation in open source software projects. Journal of Management Information Systems. 2009;25(4):9–50. doi:10.2753/MIS0742-1222250401.
  • Raja U, Tretter MJ. Defining and evaluating a measure of open source project survivability. IEEE Trans Softw Eng. 2012;38(1):163–74. doi:10.1109/TSE.2011.39.
  • Shaikh M, Levina N. Selecting an open innovation community as an alliance partner: looking for healthy communities and ecosystems. Res Policy. 2019;48(8):103766. doi:10.1016/j.respol.2019.03.011.
  • Zhang C, Hahn J, De P. Research note—Continued participation in online innovation communities: does community response matter equally for everyone? Information Systems Research. 2013;24(4):1112–30. doi:10.1287/isre.2013.0485.
  • Stewart KJ, Gosain S. The impact of ideology on effectiveness in open source software development teams. In: MIS quarterly. MIS Research Center, Carlson School of Management, University of Minnesota; 2006. p. 291–314.
  • Sinha VS, Mani S, Sinha S. Entering the circle of trust: developer initiation as committers in open-source projects. In: Proceedings of the 8th working conference on mining software repositories; May. Waikiki, Honolulu (HI); 2011. p. 133–42.
  • Mayer RC, Davis JH, Schoorman FD. An integrative model of organizational trust. Academy of Management Review. 1995;20(3):709–34. doi:10.5465/amr.1995.9508080335.
  • Rogers EM. Diffusion of innovations. New York (NY): Simon and Schuster; 2010.
  • Wenger E. Communities of practice and social learning systems: the career of a concept. In: Blackmore C, editor. Social learning systems and communities of practice. London (UK): Springer; 2010. p. 179–98.
  • Nahapiet J, Ghoshal S. Social capital, intellectual capital, and the organizational advantage. Academy of Management Review. 1998;23(2):242–66. doi:10.5465/amr.1998.533225.
  • Blau PM. Exchange and power in social life. New York (NY): Wiley; 1964.
  • Lakhani KR, Von Hippel E. How open source software works: “free” user-to-user assistance. Res Policy. 2003;32(6):923–43. doi:10.1016/S0048-7333(02)00095-1.
  • Lindberg A, Berente N, Gaskin J, Lyytinen K. Coordinating interdependencies in online communities: a study of an open source software project. Information Systems Research. 2016;27(4):751–72. doi:10.1287/isre.2016.0673.
  • O’mahony S, Ferraro F. The emergence of governance in an open source community. Academy of Management Journal. 2007;50(5):1079–106. doi:10.5465/amj.2007.27169153.
  • Butler JKJ. Toward understanding and measuring conditions of trust: evolution of a conditions of trust inventory. J Manage. 1991;17(3):643–63. doi:10.1177/014920639101700307.
  • Mishra AK. Organizational responses to crisis. In: Kramer R, Tyler T, editors. Trust in organizations: frontiers of theory and research. Thousand Oaks: SAGE Publications, Inc. p. 261–87. https://www.doi.org/10.4135/9781452243610.n13
  • Bolino MC, Turnley WH, Bloodgood JM. Citizenship behavior and the creation of social capital in organizations. Academy of Management Review. 2002;27(4):505–22. doi:10.5465/amr.2002.7566023.
  • Colquitt JA, Scott BA, LePine JA. Trust, trustworthiness, and trust propensity: a meta-analytic test of their unique relationships with risk taking and job performance. The American Psychological Association; 2007.
  • McAllister DJ. Affect-and cognition-based trust as foundations for interpersonal cooperation in organizations. Academy of Management Journal. 1995;38:24–59.
  • Cheng X, Gu Y, Shen J. An integrated view of particularized trust in social commerce: an empirical investigation. Int J Inf Manage. 2019;45:1–12. doi:10.1016/j.ijinfomgt.2018.10.014.
  • Porter CE, Donthu N. Cultivating trust and harvesting value in virtual communities. Manage Sci. 2008;54(1):113–28. doi:10.1287/mnsc.1070.0765.
  • Jarvenpaa SL, Knoll K, Leidner DE. Is anybody out there? Antecedents of trust in global virtual teams. Journal of Management Information Systems. 1998;14(4):29–64. doi:10.1080/07421222.1998.11518185.
  • Serva MA, Fuller MA, Mayer RC. The reciprocal nature of trust: a longitudinal study of interacting teams. J Organ Behav. 2005;26(6):625–48. doi:10.1002/job.331.
  • Landis JR, Koch GG. The measurement of observer agreement for categorical data. In: Biometrics. International Biometric Society; 1977. p. 159–74.
  • Rousseau DM, Sitkin SB, Burt RS, Camerer C. Not so different after all: a cross-discipline view of trust. Academy of Management Review. 1998;23(3):393–404. doi:10.5465/amr.1998.926617.
  • Ridings CM, Gefen D, Arinze B. Some antecedents and effects of trust in virtual communities. The Journal of Strategic Information Systems. 2002;11(3–4):271–95. doi:10.1016/S0963-8687(02)00021-5.
  • Xiong L, Liu L. Peertrust: supporting reputation-based trust for peer-to-peer electronic communities. IEEE Trans Knowl Data Eng. 2004;16(7):843–57. doi:10.1109/TKDE.2004.1318566.
  • Zhang X, Cui L, Wang Y. Commtrust: computing multi-dimensional trust by mining e-commerce feedback comments. IEEE Trans Knowl Data Eng. 2013;26(7):1631–43. doi:10.1109/TKDE.2013.177.
  • Nitti M, Girau R, Floris A, Atzori L, 2014, May. On adding the social dimension to the internet of vehicles: friendship and middleware. In 2014 IEEE international black sea conference on communications and networking (BlackSeaCom). Chisinau (Moldova): IEEE. p. 134–38.
  • Arya A, Hine M, Khataei A, 2018. User trust graph: a model to measure trustworthiness. Presented at the 3rd International Workshop on Personalization in Persuasive Technology, PPT 2018 (April 2018), Waterloo.
  • Dale R. Text analytics APIs, Part 1: the bigger players. Natural Language Engineering. 2018;24(2):317–24. doi:10.1017/S1351324918000013.
  • Pinto HL, Rocio V, 2019, September. Combining sentiment analysis scores to improve accuracy of polarity classification in MOOC Posts. In EPIA Conference on Artificial Intelligence (pp. 35–46). Springer, Cham.
  • Satyanarayana G, Bhuvana J, Balamurugan M, 2020, January. Sentimental Analysis on voice using AWS Comprehend. In: 2020 International conference on computer communication and informatics (ICCCI). Coimbatore (India): IEEE. p. 1–4.
  • Carvalho A, Harris L. Off-the-shelf technologies for sentiment analysis of social media data: two empirical studies. AMCIS 2020 Proceedings. 2020;6. https://aisel.aisnet.org/amcis2020/social_computing/social_computing/6.
  • Anand S, Vidyarthi P, Rolnicki S. Leader-member exchange and organizational citizenship behaviors: contextual effects of leader power distance and group task interdependence. Leadersh Q. 2018;29(4):489–500. doi:10.1016/j.leaqua.2017.11.002.
  • Bowler WM, Brass DJ. Relational correlates of interpersonal citizenship behavior: a social network perspective. Journal of Applied Psychology. 2006;91(1):70. doi:10.1037/0021-9010.91.1.70.
  • Lin CP, Hung WT, Chiu CK. Being good citizens: understanding a mediating mechanism of organizational commitment and social network ties in OCBs. Journal of Business Ethics. 2008;81(3):561–78. doi:10.1007/s10551-007-9528-8.
  • Temizkan O, Kumar RL. Exploitation and exploration networks in open source software development: an artifact-level analysis. Journal of Management Information Systems. 2015;32(1):116–50. doi:10.1080/07421222.2015.1029382.
  • Brooks C. Introductory econometrics for finance. 2nd ed. UK: Cambridge University Press; 2008.
  • Bernanke BS, Boivin J, Eliasz P. Measuring the effects of monetary policy: a factor-augmented vector autoregressive (FAVAR) approach. Q J Econ. 2005;120:387–422.
  • Cuaresma JC, Feldkircher M, Huber F. Forecasting with global vector autoregressive models: a Bayesian approach. Journal of Applied Econometrics. 2016;31(7):1371–91. doi:10.1002/jae.2504.
  • Weitzel JR, Kerschberg L. Developing knowledge-based systems: reorganizing the system development life cycle. Commun ACM. 1989;32(4):482–88. doi:10.1145/63334.63340.
  • Cohen S, Dori D, de Haan U. A software system development life cycle model for improved stakeholders’ communication and collaboration. International Journal of Computers Communications & Control. 2010;5(1):20–41. doi:10.15837/ijccc.2010.1.2462.
  • Tsay RS. Multivariate time series analysis: with R and financial applications. Hoboken (NJ): John Wiley & Sons; 2014.
  • Craik FI. Memory changes in normal aging. Curr Dir Psychol Sci. 1994;3(5):155–58. doi:10.1111/1467-8721.ep10770653.
  • Parkin AJ. Chapter Eight normal age-related memory loss and its relation to frontal lobe dysfunction. Methodology of frontal and executive function. Routledge; 1997. p. 171.
  • Sara SJ. Retrieval and reconsolidation: toward a neurobiology of remembering. Learning & Memory. 2000;7(2):73–84. doi:10.1101/lm.7.2.73.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.