1. Factors that contribute to open source software project success Rizwan Ur Rehman Telecommunications Technology Management Program February 13, 2006

3. Relevance Company managers and entrepreneurs who wish to set up OSS projects To reduce the cost of having to change an OSS component due to the failure of OSS project Project managers who wish to incorporate OSS into their development projects To avoid costly mistakes and reduce the risk of failure Why? Who is interested?

4. Literature review Number and experience of software developers, targeted users of OSS, software type, license type, OSS project success Development team, target market, product type, product success Factors Bates et al. (2002); Bonaccorsi & Rossi (2003); Comino et al. (2005); Crowston et al. (2003, 2004); Crowston & Scozzi (2002); Duijnhouwer & Widdows (2003); Evers (2000); Freshtman & Gandal (2004); Healy & Schussman (2003); Hertel et al. (2003); Koch (2004); Lakhani et al. (2002); Lerner & Tirole (2002, 2005); Nissila (2004); O’Mahony (2003); Paulson et al. (2004); Peng (2004); Raymond (1999);Rossi & Bonaccorsi (2005); Stewart et al. (2005); West & O’Mahony (2005); Zhao (2003) Open source software development Brown & Eisenhardt (1995); Caramel & Sawyer (1998); Cooper & Kleinschmidt (1987); Curtis (1981); Curtis et al. (1988); Griffin & Page (1993,1996); Johne & Snelson (1988); Krishnan (1998); Page (1993); Storey & Easingwood (1996); Story et al. (2001); Thomke & von Hippel (2002); Maidique & Zirger (1985); Zirger & Maidique (1990) Product development References Literature

9. Variable measurement Total years of experience of developers taking part in the development of OSS project Experience of developers Categorical variable measured on nominal scale with values: 1 = developers, 2 = system administrators, 3 = end-users Target users type Categorical variable measured on nominal scale with values: 1 = commonly used programming languages (C, C++, Java, PHP), 2 = others (other than C, C++, Java, PHP) Number of developers taking part in the development of OSS project Measurement Variable Programming language type Number of developers

10. Variable measurement (cont’d) Categorical variable measured on nominal scale with values: 1 = application software, 2 = application development and deployment tools, 3 = system infrastructure software Type of software Total number of releases from the start of the OSS project to the date of data collection Number of releases Total number of downloads from the start of the OSS project to the date of data collection Number of downloads Categorical variable measured on nominal scale with values: 1 = very restrictive licenses, 2 = moderately restrictive licenses, 3 = non-restrictive licenses Measurement Variable Type of license

11. Data analysis Multivariate General Linear Model Test for Hypotheses 1 to 6 One-Way ANOVA and Bonferroni Test for Hypotheses 4a, 4b, 6a, 6b Welch and Brown-Forsythe robust F and Tamhane T2 Tests for Hypotheses 3a, 3b, 5a, 5b Levene test of equality of variance Test for Hypotheses 3a, 3b, 4a, 4b, 5a, 5b, 6a, 6b Pearson correlation Test for Hypotheses 1a, 1b, 2a, 2b Histograms with normality curve, descriptive statistics and natural log transformations Descriptive

22. Multivariate general linear model .983 8.44(***) .000 .052 Hotelling’s trace .983 8.44(***) .000 .950 Wilk’s lambda .983 8.44(***) .000 .052 Roy’s largest root .983 8.44(***) .000 .050 Pillai’s trace Number of developers (LN) Observed power F Value Effect

23. Multivariate general linear model (cont’d) .906 5.38(***) .005 .033 Hotelling’s trace .906 5.38(***) .005 .968 Wilk’s lambda .906 5.38(***) .005 .033 Roy’s largest root .906 5.38(***) .005 .032 Pillai’s trace Experience of developers (LN) Observed power F Value Effect

24. Multivariate general linear model (cont’d) .879 3.02(**) .017 .038 Hotelling’s trace .878 3.02(**) .018 .964 Wilk’s lambda .903 5.32(***) .005 .033 Roy’s largest root .877 3.01(**) .018 .037 Pillai’s trace Target users type Observed power F Value Effect

25. Multivariate general linear model (cont’d) .169 .299 (.742) .002 Hotelling’s trace .169 .299 (.742) .998 Wilk’s lambda .169 .299 (.742) .002 Roy’s largest root .169 .299 (.742) .002 Pillai’s trace Programming language type Observed power F Value Effect

26. Multivariate general linear model (cont’d) .929 3.62(***) .006 .045 Hotelling’s trace .930 3.63(***) .006 .956 Wilk’s lambda .825 4.15(**) .017 .026 Roy’s largest root .931 3.64(***) .006 .044 Pillai’s trace Software type Observed power F Value Effect

27. Multivariate general linear model (cont’d) .299 .586 (.673) .007 Hotelling’s trace .300 .587 (.672) .993 Wilk’s lambda .363 1.134 (.323) .007 Roy’s largest root .300 .588 (.671) .007 Pillai’s trace Type of license Observed power F Value Effect

28. Test results supported Targeting developers as users is positively associated with the number of releases of OSS projects Hypothesis 3b Not supported Using a commonly used programming language is positively associated with the number of downloads of OSS projects Hypothesis 4a Outcome Hypothesis supported Targeting developers as users is positively associated with the number of downloads of OSS projects Hypothesis 3a supported Experience of developers is positively associated with the number of releases of OSS projects Hypothesis 2b supported Experience of developers is positively associated with the number of downloads of OSS projects Hypothesis 2a supported Number of developers is positively associated with the number of releases of OSS projects Hypothesis 1b supported Number of developers is positively associated with the number of downloads of OSS projects Hypothesis 1a

29. Test results Outcome Hypothesis Not supported Use of non-restrictive OSS license is positively associated with the number of releases of OSS projects Hypothesis 6b Not supported Use of non-restrictive OSS license is positively associated with the number of downloads of OSS projects Hypothesis 6a supported Development of application development and deployment tools is positively associated with the number of releases of OSS projects Hypothesis 5b supported Development of application development and deployment tools is positively associated with the number of downloads of OSS projects Hypothesis 5a Not supported Using a commonly used programming language is positively associated with the number of releases of OSS projects Hypothesis 4b