Socialization in Open Source Software Projects: A Growth Mixture Modeling Approach

The success of open source software (OSS) projects depends heavily on the voluntary participation of a large number of developers. To remain sustainable, it is vital for an OSS project community to maintain a critical mass of core developers. Yet, only a small number of participants (identified here as ‘‘joiners’’) can successfully socialize themselves into the core developer group. Despite the importance of joiners’ socialization behavior, quantitative longitudinal research in this area is lacking. This exploratory study examines joiners’ temporal socialization trajectories and their impacts on joiners’ status progression. Guided by social resource theory and using the growth mixture modeling (GMM) approach to study 133 joiners in 40 OSS projects, the authors found that these joiners differed in both their initial levels and their growth trajectories of socialization and identified four distinct classes of joiner socialization behavior. They also found that these distinct latent classes of joiners varied in their status progression within their communities. The implications for research and practice are correspondingly discussed.

[1]  James N. Baron,et al.  Resources and Relationships: Social Networks and Mobility in the Workplace , 1997 .

[2]  D. Nagin,et al.  Developmental trajectories of conduct problems and hyperactivity from ages 2 to 10. , 2005, Journal of child psychology and psychiatry, and allied disciplines.

[3]  G. Celeux,et al.  An entropy criterion for assessing the number of clusters in a mixture model , 1996 .

[4]  Alexandre J. S. Morin,et al.  A Multifoci Person-Centered Perspective on Workplace Affective Commitment: A Latent Profile/Factor Mixture Analysis , 2011 .

[5]  Arnon E. Reichers,et al.  An Interactionist Perspective on Newcomer Socialization Rates , 1987 .

[6]  K. G. J8reskoC,et al.  Simultaneous Factor Analysis in Several Populations , 2007 .

[7]  Judith D. Singer,et al.  Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models , 1998 .

[8]  Kouichi Kishida,et al.  Toward an understanding of the motivation of open source software developers , 2003, 25th International Conference on Software Engineering, 2003. Proceedings..

[9]  Louis.  Acculturation in the workplace : Newcomers as lay ethnographers , 1990 .

[10]  J. Herbsleb,et al.  Two case studies of open source software development: Apache and Mozilla , 2002, TSEM.

[11]  E. Morrison,et al.  NEWCOMERS' RELATIONSHIPS: THE ROLE OF SOCIAL NETWORK TIES DURING SOCIALIZATION , 2002 .

[12]  Frauke Kreuter,et al.  Analyzing Criminal Trajectory Profiles: Bridging Multilevel and Group-based Approaches Using Growth Mixture Modeling , 2008 .

[13]  J. Hox,et al.  Sufficient Sample Sizes for Multilevel Modeling , 2005 .

[14]  J. V. Maanen,et al.  Toward a theory of organizational socialization , 1977 .

[15]  Peter V. Marsden,et al.  Social Resources and Mobility Outcomes: A Replication and Extension , 1988 .

[16]  R. MacCallum,et al.  Studying Multivariate Change Using Multilevel Models and Latent Curve Models. , 1997, Multivariate behavioral research.

[17]  Karim R. Lakhani,et al.  Community, Joining, and Specialization in Open Source Software Innovation: A Case Study , 2003 .

[18]  B. Muthén.  Latent variable modeling in heterogeneous populations , 1989 .

[19]  Maria L. Kraimer,et al.  A Social Capital Theory of Career Success , 2001 .

[20]  Jennifer C. Sexton,et al.  Modeling Levels and Time in Entrepreneurship Research , 2010 .

[21]  Sonali K. Shah.  Motivation, Governance, and the Viability of Hybrid Forms in Open Source Software Development , 2006, Manag. Sci..

[22]  N. Lin,et al.  Social Resources and Occupational Status Attainment , 1981 .

[23]  B. Muthén.  Latent VariabLe Hybrids Overview of Old and new Models , 2006 .

[24]  Bengt Muthén,et al.  Latent Variable Analysis: Growth Mixture Modeling and Related Techniques for Longitudinal Data , 2004 .

[25]  D. Sörbom.  A GENERAL METHOD FOR STUDYING DIFFERENCES IN FACTOR MEANS AND FACTOR STRUCTURE BETWEEN GROUPS , 1974 .

[26]  Mary K. Hoard,et al.  First-Grade Predictors of Mathematical Learning Disability: A Latent Class Trajectory Analysis. , 2009, Cognitive development.

[27]  Katherine E. Masyn,et al.  General Growth Mixture Analysis with Antecedents and Consequences of Change , 2010 .

[28]  Kathleen M. Carley,et al.  Impact of license choice on Open Source Software development activity , 2009 .

[29]  Stephanie T. Lanza,et al.  Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences , 2009 .

[30]  W. DeSarbo,et al.  Finite-Mixture Structural Equation Models for Response-Based Segmentation and Unobserved Heterogeneity , 1997 .

[31]  Ines Schindler,et al.  Changes of life satisfaction in the transition to retirement: a latent-class approach. , 2007, Psychology and aging.

[32]  M. Goldman,et al.  Variation in the drinking trajectories of freshmen college students. , 2005, Journal of consulting and clinical psychology.

[33]  Jost Reinecke,et al.  Longitudinal Analysis of Adolescents Deviant and Delinquent Behavior: Applications of Latent Class , 2006 .

[34]  Stefan Koch,et al.  Effort, co‐operation and co‐ordination in an open source software project: GNOME , 2002, Inf. Syst. J..

[35]  Michael W. Browne,et al.  Best methods for the analysis of change: Recent advances, unanswered questions, future directions. , 1991 .

[36]  Nava Pliskin,et al.  The knowledge contribution of engineers to software development: a case study , 1991 .

[37]  Mo Wang,et al.  Profiling Retirees in the Retirement Transition and Adjustment Process: Examining the Longitudinal Change Patterns of Retirees' Psychological Well-Being , 2007, The Journal of applied psychology.

[38]  W. Miller,et al.  Combined pharmacotherapies and behavioral interventions for alcohol dependence (The COMBINE Study): examination of posttreatment drinking outcomes. , 2008, Journal of studies on alcohol and drugs.

[39]  Katie Witkiewitz,et al.  Network support for drinking: an application of multiple groups growth mixture modeling to examine client-treatment matching. , 2008, Journal of studies on alcohol and drugs.

[40]  Todd E. Bodner,et al.  Growth Mixture Modeling , 2007 .

[41]  Daniel E. Vetter,et al.  Replication in strategic management: scientific testing for validity, generalizability, and usefulness , 1998 .

[42]  Richard M. Stallman,et al.  Free Software, Free Society: Selected Essays of Richard M. Stallman , 2009 .

[43]  Emilio J. Castilla.  Vaccines: Preventing Disease & Protecting Health Edited by Ciro A. de Quadros Annapolis Junction, MD: Pan American Health Organization (PAHO) Publications, 2004. 412 pp., illustrated. $62.00 (paper) , 2005 .

[44]  N. Lin,et al.  Social Resources and Strength of Ties: Structural Factors in Occupational Status Attainment , 1981, Social Capital, Social Support and Stratification.

[45]  Daniel J Bauer,et al.  Distributional assumptions of growth mixture models: implications for overextraction of latent trajectory classes. , 2003, Psychological methods.

[46]  B. Muthén.  Latent Variable Mixture Modeling , 2001 .

[47]  Kamel Jedidi,et al.  A maximum likelihood method for latent class regression involving a censored dependent variable , 1993 .

[48]  Robert E. Ployhart,et al.  Growth Modeling Using Random Coefficient Models: Model Building, Testing, and Illustrations , 2002 .

[49]  Siu L. Chow,et al.  Science, Ecological Validity and Experimentation , 1987 .

[50]  Karel Cool,et al.  Asset stock accumulation and sustainability of competitive advantage , 1989 .

[51]  V. Neuhaus,et al.  Latent Class Analysis , 2010 .

[52]  Chen Zhang,et al.  Emergence of New Project Teams from Open Source Software Developer Networks: Impact of Prior Collaboration Ties , 2008, Inf. Syst. Res..

[53]  Brian Fitzgerald,et al.  The Transformation of Open Source Software , 2006, MIS Q..

[54]  Jane Greenberg,et al.  Open Source Software Development and Lotka's Law: Bibliometric Patterns in Programming , 2003, J. Assoc. Inf. Sci. Technol..

[55]  David Chan,et al.  The Conceptualization and Analysis of Change Over Time: An Integrative Approach Incorporating Longitudinal Mean and Covariance Structures Analysis (LMACS) and Multiple Indicator Latent Growth Modeling (MLGM) , 1998 .

[56]  E. Morrison,et al.  Longitudinal study of the effects of information seeking on newcomer socialization , 1993 .

[57]  Etienne Wenger,et al.  Situated Learning: Legitimate Peripheral Participation , 1991 .

[58]  Nicolas Ducheneaut,et al.  Socialization in an Open Source Software Community: A Socio-Technical Analysis , 2005, Computer Supported Cooperative Work (CSCW).

[59]  Sandra Slaughter,et al.  Understanding the Motivations, Participation, and Performance of Open Source Software Developers: A Longitudinal Study of the Apache Projects , 2006, Manag. Sci..

[60]  A. McCutcheon,et al.  Latent Class Analysis , 2021, Encyclopedia of Autism Spectrum Disorders.

[61]  Stephanie T. Lanza,et al.  A mixture model of discontinuous development in heavy drinking from ages 18 to 30: the role of college enrollment. , 2006, Journal of studies on alcohol.

[62]  Georg von Krogh,et al.  Open Source Software and the "Private-Collective" Innovation Model: Issues for Organization Science , 2003, Organ. Sci..

[63]  A. Strauss,et al.  The discovery of grounded theory: strategies for qualitative research aldine de gruyter , 1968 .

[64]  Daniel S. Nagin,et al.  Analyzing developmental trajectories: A semiparametric, group-based approach , 1999 .

[65]  Geoffrey J. McLachlan,et al.  Finite Mixture Models , 2019, Annual Review of Statistics and Its Application.

[66]  R. W. Lucky,et al.  Free software [Reflections] , 1999 .

[67]  Yulin Fang,et al.  Understanding Sustained Participation in Open Source Software Projects , 2009, J. Manag. Inf. Syst..

[68]  B. Muthén,et al.  Integrating person-centered and variable-centered analyses: growth mixture modeling with latent trajectory classes. , 2000, Alcoholism, clinical and experimental research.

[69]  Likoebe M. Maruping,et al.  Impacts of License Choice and Organizational Sponsorship on User Interest and Development Activity in Open Source Software Projects , 2006, Inf. Syst. Res..

[70]  Tony Jung,et al.  An introduction to latent class growth analysis and growth mixture modeling. , 2008 .

[71]  William L. Moore,et al.  Levels of Aggregation in Conjoint Analysis: An Empirical Comparison , 1980 .

[72]  Robert E. Cole,et al.  From a Firm-Based to a Community-Based Model of Knowledge Creation: The Case of the Linux Kernel Development , 2003, Organ. Sci..

[73]  John R. Nesselroade,et al.  Interindividual differences in intraindividual change. , 1991 .

[74]  Eric von Hippel,et al.  Satisfying Heterogeneous User Needs Via Innovation Toolkits: The Case of Apache Security Software , 2002 .

[75]  Terry E. Duncan,et al.  A Multivariate Associative Finite Growth Mixture Modeling Approach Examining Adolescent Alcohol and Marijuana Use , 2004 .

[76]  Karen Bandeen-Roche,et al.  Residual Diagnostics for Growth Mixture Models , 2005 .

[77]  Scott Highhouse.  Designing Experiments That Generalize , 2009 .

[78]  Sandeep Krishnamurthy,et al.  Cave or Community? An Empirical Examination of 100 Mature Open Source Projects , 2002, First Monday.

[79]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

[80]  Kevin Crowston,et al.  Defining Open Source Software Project Success , 2003, ICIS.

[81]  Ravi Sen,et al.  A Strategic Analysis of Competition Between Open Source and Proprietary Software , 2007, J. Manag. Inf. Syst..

[82]  J. Hox,et al.  Sample sizes for multilevel modeling , 2002 .

[83]  E. Hippel.  Innovation by User Communities: Learning From Open-Source Software , 2001 .

[84]  B. Muthén,et al.  Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study , 2007 .

[85]  Kenneth A. Bollen,et al.  Latent curve models: A structural equation perspective , 2005 .

[86]  Chris F. Kemerer,et al.  The assimilation of software process innovations: an organizational learning perspective , 1997 .

[87]  L. Goossens,et al.  Developmental Typologies of Identity Formation and Adjustment in Female Emerging Adults: A Latent Class Growth Analysis Approach , 2008 .

[88]  Gary L. Lilien,et al.  Location, Location, Location: How Network Embeddedness Affects Project Success in Open Source Systems , 2006, Manag. Sci..

[89]  C. Anderson‐Cook,et al.  Group-Based Modeling of Development , 2006 .

[90]  Karim R. Lakhani,et al.  Community, Joining, and Specialization in Open Source Software Innovation: A Case Study , 2003 .

[91]  Michael A. Shapiro,et al.  Generalizability in Communication Research , 2002 .

[92]  N. Lin.  Buidling a Network Theory of Social Capital , 1999, Connections.

[93]  Katherine J. Stewart,et al.  The Impact of Ideology on Effectiveness in Open Source Software Development Teams , 2006, MIS Q..

[94]  Mo Wang,et al.  Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status Change , 2011 .

[95]  P. Deb.  Finite Mixture Models , 2008 .

[96]  Guido Hertel,et al.  Motivation of software developers in Open Source projects: an Internet-based survey of contributors to the Linux kernel , 2003 .

[97]  Deborah Compeau,et al.  Assessing Between-Group Differences in Information Systems Research: A Comparison of Covariance-and Component-Based SEM , 2009, MIS Q..