Investigating Innovation in Free/Libre Open Source Software Development Teams


We propose a social science study in the context of software development to advance our understanding of fundamental processes of learning, process change and product innovation in distributed teams. Our study addresses the general research question: How do members of distributed technology-supported teams of Free/Libre Open Source Software (FLOSS) developers learn to improve their performance by forming shared mental models, individual roles, informal norms and formal rules and how do these structures guide effective behaviours leading to innovations? This question is important because organizational work is increasingly performed by distributed teams of interdependent knowledge workers. These teams have many benefits, but the distance (geographic, organizational and social) between members challenges team members to create the shared understandings and social structures necessary to be effective. But as yet, research and practitioner communities know little about the dynamics of learning and innovation in distributed teams.
To answer our research question, we will conduct a longitudinal in-depth study identifying and comparing the formation, learning and innovation processes of distributed teams of FLOSS developers. The proposed research will be guided by an advisory board of FLOSS developers to ensure relevance and to help promote diffusion of our findings into practice. We will study how these distributed groups develop shared mental models to guide members’ behavior, roles to mediate access to resources, and norms and rules to shape action, as well as the processes by which independent, geographically-dispersed individuals are socialized into teams. As a basis for this study, we develop a conceptual framework that uses a structurational perspective to integrate research on team behaviour, organizational learning, communities of practice and shared mental models. We will utilize qualitative data analysis of team interactions, observation and interview data to investigate these processes. We will also use social network analysis to study the socialization process of members and change in roles over time.

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